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"IEEE Sensors Alert" is a pilot project of the IEEE Sensors Council. Started as one of its new initiatives, this weekly digest publishes teasers and condensed versions of our journal papers in layperson's language.
Articles Posted in the Month (March 2026)
Tattoo-Like Flexible Ethylene Sensor for Plant Stress Monitoring in Real-Time
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Shawana Tabassum (Author)
Imagine a "tattoo" for plants that helps them "talk" with agriculturist and researchers about their physiological processes. This paper presents a paper-thin, flexible sensor that sticks to a leaf like a temporary tattoo for real-time, continuous monitoring of ethylene, a key plant stress hormone. This breakthrough tattoo sensor will enable smarter crop management and early stress detection in plants before any visible damage occurs.
Silver Microneedle Array Printed via Aerosol Jet Enhance the Electrochemical Detection of Carboxylated Carbon Nanotubes for Chloramphenicol
Author: Cao Lei, Xiong Shixian, Fan Lanlan, Gu Feng, Liu Feng, Liu Shiji, Liu Yin, Liu Zhecheng, Zhu Qian
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Cao Lei (Author)
Excessive use of Chloramphenicol (CAP), a widely used broad-spectrum antibiotic in livestock, is harming the environment and health. This paper introduces a carboxylated multiwalled carbon nanotube (MWCNTs-COOH)-decorated 3-D silver microneedle array, fabricated using aerosol jet printing (AJP) technology on a screen-printed carbon working electrode (SPCE). This approach enabled compact, minimally invasive, and sensitive detection of CAP, facilitating quicker, more accurate environmental monitoring, enhancing food safety, and supporting public health protection.
A Stretchable Tactile Sensor Array Based on Hydrogel Ionic Diodes
Author: Liu Xinyu, Wu Xia, Zhang Zefang
Published in: IEEE Sensors Journal (Volume: 25, Issue: 16, August 2025)
Summary Contributed by: Xinyu Liu (Author)
Human skin transmits the sensation of touch through precisely regulated ionic signals. Researchers developed a soft-gel tactile sensor array that integrates ionic diodes, applying this principle to robotic skin. These diodes control the movement of ions similar to biological synapses, converting gentle pressure into ionic responses. The innovation brings artificial skin closer to mimicking the functions of real skin, showing potential for advanced iontronic applications in robotics and prosthetics.
The fragility of smart wearables has driven demand for flexible, stretchable sensors. This study presents a self-healing, recyclable strain sensor made from a Diels–Alder polymer and liquid metal, which can fully restore its functionality even when cut in half. This durable, repairable, and eco-friendly stretchable device, with excellent sensing performance, is well-suited for smart wearables and paves the way for sustainable soft electronics in health monitoring and robotics.
Evaluating Event-Based Vision Sensing in Rain and Fog
Author: Delaney Ethan, Brophy Tim, Collins Fiachra, Deegan Brian, Glavin Martin, Jones Edward, Ward Enda
Published in: IEEE Sensors Journal (Volume: 25, Issue: 16, August 2025)
Summary Contributed by: Ethan Delaney (Author)
Event-based sensors are being considered for use in automotive perception systems, due to their high temporal resolution, high dynamic range, and low latency. However, their performance in adverse weather conditions must be validated before large-scale rollout. This study characterizes the impact of rain and fog on event camera performance in controlled conditions. It introduces methods to mitigate these effects, offering fresh insights for autonomous vehicles, outdoor monitoring, and robotics.
Phytic Acid/MXene@Polyurethane Sponge-Based Flexible Pressure Sensor With Assistance of MC-GRU Model for Motion Posture Recognition
Author: Zhang Dongzhi, Guo Yihong, Wang Weiwei, Xia Hui, Yang Chunqing, Zhang Hao, Zhou Lina
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Payal Savani
Pressure sensors, essential for flexible electronics, face limitations in detection range and structural instability. This study presents a flexible pressure sensor fabricated using phytic acid-modified MXene nanosheets coated on a polyurethane sponge. The device demonstrates high sensitivity (16.71 kPa⁻¹), a broad detection range (0–175 kPa), and excellent flame retardancy. When integrated with a multilayer convolutional gated recurrent unit (MC-GRU) model, the system achieved high-fidelity human-motion recognition, enabling next-generation smart wearables and human–machine interfaces.
HBV-Testing: HKUST-1-Modified Electrochemical Immunosensor for Point-of-Care Testing of Hepatitis B
Author: Yuliarto Brian, Dewi Kariana Kusuma, Raihan Muhammad Fadlan, Septiani Ni Luh Wulan, Wustoni Shofarul
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Brian Yuliarto (Author)
Early detection of Hepatitis B is crucial to prevent severe liver conditions. The hepatitis B surface antigen (HBsAg) appears early in infection, making it a key biomarker. This study introduces the HBV-Test, a portable electrochemical immunosensor designed for rapid, affordable HBsAg detection at the point-of-care. Using a copper-based nanomaterial (HKUST-1), it almost accurately identifies viral antigens in 5 minutes. Its robust clinical performance supports its use directly in healthcare systems.
High-Sensitivity CQDs-Modified ZnO Nanowire Gas Sensor Fabricated on 3-D Substrate for Acetone Detection
Author: Ma Liuhong, Chen Pandi, Duan Zhiyong, Fu Yingchun, He Fan, Li Mengke, Li Puguang, Si Chaowei, Zhang Xin
Published in: IEEE Sensors Journal (Volume: 25, Issue: 12, June 2025)
Summary Contributed by: Saurabh Dubey
A Carbon quantum dot (CQD)-modified zinc oxide (ZnO) nanowire gas sensor designed on a 3-D micropillar substrate enables high-sensitivity, low-temperature acetone detection. The 3-D structure increases surface area, while CQD form p–n heterojunctions that enhance adsorption and selectivity. This sensor shows scalable, energy-efficient, and reliable performance, achieving higher sensitivity and lower operating temperature than unmodified ZnO, making it ideal for industrial, environmental, and commercial applications in acetone monitoring.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Frank J. Wouda (Author)
With increasing life expectancy, gait disorders that worsen with age have become a global concern. Presently, body-worn devices with multiple on-body sensors are required for accurate gait monitoring. This study proposes a novel portable gait analysis setup that combines an ultra-wideband (UWB) sensor and an inertial measurement unit (IMU) on each foot to track accurately their positions (within 2.5cm) and orientation (within 4 degrees) in real time without drift.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Payal Savani
In diabetes management, noninvasive and painless glucose monitoring is challenging. This work presents a flexible, side-gated field-effect transistor (FET) test strip that uses graphene oxide (GO)-catalyzed CuO-ZnO hollow spheres for saliva-based glucose sensing. Demonstrating excellent reproducibility and repeatability, this portable platform achieved an ultra-low limit of detection (0.001 μM) and high sensitivity (1600 μA·mM⁻¹) across a wide range of saliva concentrations, offering a point-of-care solution for glucose monitoring.
Electrochemical Study of a WO₃ NPs/MoO₃ Heterojunction-Based Dual-Enzyme Amperometric Acetylcholine Sensor
Author: Chou Jung-chuan
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Jung-Chuan Chou (Author)
Acetylcholine (ACh) is a crucial neurotransmitter, and fluctuations in its concentration are associated with neurodegenerative diseases. This study presents an amperometric dual-enzyme acetylcholine sensor integrating tungsten oxide (WO₃) nanoparticles with a molybdenum oxide (MoO₃) thin film to form a heterojunction structure. Dual-enzyme immobilization enables a wide linear range, ultra-low detection limit, high selectivity, and stable operation. The sensor shows potential for mass-producible, low-cost platforms for real-time neurochemical monitoring and portable biomedical applications.
Web Dynamic Stress Identification and Damping Analysis of High-Speed Spiral Bevel Gear
Author: Zhu Rupeng, Chen Weifang, Wang Shuai, Yan Weiping, Yu Hu
Published in: IEEE Sensors Journal (Volume: 25, Issue: 12, June 2025)
Summary Contributed by: Saurabh Dubey
Thin-webbed spiral bevel gears are susceptible to dangerous nodal diameter (ND) vibrations in high-speed transmissions, increasing web dynamic stress (WDS). The Single-Mode Forced Response (SMFR) method introduced in this work integrates prestressed modal analysis with traveling-wave resonance prediction to identify critical resonances and influence passive ring-damper design. These dampers reduce resonance by 65% and WDS from 123.5 MPa to 43 MPa, offering a reliable and cost-effective framework for improving aerospace gear performance.
An Intestine-Based Biocompatible Humidity Sensor for Environmental and Medical Measurements
Author: Yavsan Emrehan, Erismis Mehmet Akif, KARA MUHAMMET ROJHAT
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Emrehan Yavsan (Author)
The rise in electronic waste has driven demand for sustainable, biodegradable alternatives. This study presents a sustainable and biocompatible humidity sensor derived from processed cattle intestine for environmental and medical measurements. The inherent durability of intestinal tissue ensures exceptional longevity, with the sensor remaining functional for more than a year under any conditions. Its capability to detect respiratory cycles demonstrates strong potential for integration into non-invasive medical and environmental sensing platforms.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Kamalesh Tripathy
Flood prediction is crucial for disaster management. This paper introduces a novel smart framework designed with digital twin modelling, Internet of Thing (IoT) sensing, neuro-fuzzy learning, and blockchain security to forecast flood risks with exceptional accuracy. By combining real-time environmental data with modelling complex hydrological interactions, this approach delivers a highly reliable Flood Index Value with testing accuracy above 95%, making it an efficient tool for disaster preparedness and planning.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 13, July 2025)
Summary Contributed by: Subham Das (Author)
Replicating the complexity of human touch is challenging. This research introduces a novel tactile sensing skin designed to detect and interpret surface textures accurately. Combining a flexible tactile sensor and a thermal sensor creates a system capable of distinguishing surface features with precision. By integrating machine learning, the system can identify terrain with high accuracy, bringing machines closer to mimicking human touch and advancing the field of intelligent robotics and prosthetics.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 16, August 2025)
Summary Contributed by: Kamonrat Phopin (Author)
Hazardous pesticides have posed life-threatening effects to human livelihood and wellness for a decade. This paper presents an aptamer-based impedimetric sensor for glyphosate (GLY) detection in environmental and food commodities. The proposed aptasensor offers a simple, cost-effective, and fast alternative to conventional methods. It also demonstrates effective real-world performance, including a wide dynamic range and satisfactory cross-reactivity against common interferences, making it promising for real-life applications.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 2, January 2025)
Summary Contributed by: Elzenheimer Eric (Author)
Benchmarking highly sensitive magnetometers is essential across diverse application fields. This study introduces, for the first time, a dedicated test bench and a set of key parameters that enable cross-technology comparison between non-cryogenic magnetometers and Superconducting Quantum Interference Devices (SQUIDs). It exemplifies and standardizes definitions of core metrics such as sensitivity, linear range, stability, directivity, frequency response, time delay, and noise spectral density within a controlled evaluation framework.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 15, August 2025)
Summary Contributed by: Saurabh Dubey
A laser-reduced graphene oxide (LrGO) sensor offers a low-cost, scalable, and additive-free solution for real-time detection of ammonia and ethanol gases. Fabricated directly on PET films via laser reduction, the sensor achieves sensitivities of 0.0402 %/ppm for ammonia and 0.0140 %/ppm for ethanol at room temperature. With simple fabrication, stable performance, and strong linear response, LrGO enables sustainable, eco-friendly gas sensing for environmental and workplace safety monitoring.
Mercury (Hg²⁺) contamination poses severe health risks, yet current detection is slow and costly. This study introduces a breakthrough MoS2-functionalized MgZnO/CdZnO high-electron-mobility transistor (HEMT) sensor for ultrasensitive detection of Hg²⁺ ions. Using chemical vapor–deposited grown MoS2, the device could detect mercury ions at an ultralow concentration (as low as 6.5 ppt) within 4 seconds. This highly selective, portable solution provides reliable, real-time monitoring for water quality and environmental surveillance.
Two-Electrode Screen-Printed pH Sensors for Monitoring Soil and Other Growing Media
Author: Whiting Gregory, Arias Ana, Atreya Madhur, Barba Juan Pablo Cisneros, Baumbauer Carol L., Bihar Eloise, Bruno Nicholas, Crichton Catherine A., Goodrich Payton J., Lahann Lucas, Pister Kris, Silver Whendee L., Strand Elliot J., Yuan Titan
Published in: IEEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Gregory L. Whiting (Author)
Monitoring the pH of growing media is essential for optimizing agricultural practices and maintaining both crop and environmental health. This study introduces a screen-printed pH sensor featuring a simplified two-electrode design consisting of an Alizarin working electrode and stabilizing Nafion/salt membranes. The design demonstrated stable, real-time pH measurements. It integrates affordable readout electronics, making it a reliable approach for high-density pH monitoring in environmental and agricultural applications.
Photo-Assisted Selective and Reversible Acetone Sensors Based on 2-D MoSe₂ Nanoflakes
Author: Ray S. K., Das Saranya, Das Shreyasi
Published in: EEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Saranya Das (Author)
Driven by industrial growth and urbanization, research in volatile organic compounds (VOC) sensing has gained importance for environmental and medical applications. This study introduces a two-dimensional molybdenum diselenide (MoSe2)-based chemiresistor for acetone detection at room temperature, featuring high selectivity, low detection limit, and UV-light-enhanced recovery. Its simple design and low-cost fabrication make it promising for real-time VOC sensing applications.
Thermal Fault Detection of High-Speed Direct-Driven Blower Components Using Thermal-Visible Image Fusion and Semantic Segmentation
Author: Chu Ning, Ali Mohammad-Djafari, Cai Caifang, Li Li, Sun Zekun, Zhang Shanqing
Published in: IEEE Sensors Journal (Volume: 25, Issue: 12, June 2025)
Summary Contributed by: Payal Savani
Thermal fault detection is crucial for maintaining industrial blowers, as high-speed rotation can lead to overheating and performance loss. The proposed system combines thermal infrared and visible images using an Improved Diffusion-Based Fusion (IDF) model. A lightweight Convolutional Cross-Attention Encoder Network (CCAE-Net) analyzes these images, segmenting components and identifying abnormal temperature zones. This method enables accurate, real-time monitoring, enhancing the reliability, efficiency, and safety of high-speed direct-driven blowers.
Published in: EEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Ritu Poonia (Author)
Mercury exposure poses a threat to both human health and the environment, necessitating its strict monitoring. This work introduces a dual-metal-gate AlGaN/GaN high-electron-mobility transistor (HEMT) sensor for mercury ion detection. The device features an extended electrode functionalized with thioglycolic acid for mercury detection and a quasi-reference electrode enabling gate biasing. The design improves sensitivity, selectivity, and stability while validating trace-level mercury detection through quantification analysis, offering a compact solution for environmental monitoring.
Ultralow-Cost and Selective Water-Based Colorimetric Ink for Indoor CO₂ Monitoring
Author: Maria González-Gómez, Ismael Benito-Altamirano, Joan Daniel Prades, Olga Casals, Cristian Fàbrega
Published in: IEEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Maria González-Gómez (Author)
Indoor air quality (IAQ) control is increasingly recognized as crucial for human health. Carbon dioxide (CO₂) levels reflect co-exhaled pathogens and serve as an indicator of air quality. This work presents low-cost, printable CO₂ sensors using a novel water colorimetric ink. Operating within the relevant 150-1500 ppm range, they remain stable and selective even under 10-70% humidity. Their excellent specificity, repeatability, and affordability make them suitable for real-world applications.
Ethylenediamine-Coupled Lysine-Modified Pencil Graphite Electrode for the Quantification of Indigo Carmine
Author: R Rejithamol, Sadanandan Sandhya, C Devu, P J Sreelekshmi, V Devika
Published in: IEEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: R. Rejithamol (Author)
The widespread use of synthetic food colors has raised concerns about public health safety and the need for effective detection methods. In this study, a novel compound, ethylenediamine-coupled lysine (EDAK), was used to modify a pencil graphite electrode (PGE) through electropolymerisation for the detection of indigo carmine. The developed sensor exhibited high sensitivity, excellent selectivity, and a low detection limit, offering a cost-effective and reliable option for food safety monitoring.
A Novel Anti-Relaxation Material Applied in Miniaturized Atomic Spin Gyroscope
Author: Li Shun, Bi Zhangzhe, Lin Longbin, Wu Yunong, Xu Fangqi, Zhang Haifeng
Published in: EEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Saurabh Dubey
A novel perfluorododecyltrichlorosilane (PDTS) anti-relaxation coating enhances miniaturized atomic spin gyroscopes (NMRGs) by reducing spin relaxation in tiny vapor cells. Offering excellent thermal stability, strong adhesion, and ultralow surface energy, PDTS extends transverse relaxation time to 28.8 s, surpassing traditional methods. Validated via spectroscopy and atomic force microscopy, it improves spin coherence, sensitivity and reliability. Ideal for UAV navigation and GPS-denied environments, it enables next-generation compact gyroscopes with superior performance.
Radio Frequency Characterization of Gold Nanoparticles With 3-D Printed U-Cavity Sensor
Author: Kattel Bibek, Hutchcraft Winn Elliott, Syed Azeemuddin, Tanner Eden E. L., Vashisth Priyavrat
Published in: IEEE Sensors Journal (Volume: 25, Issue: 12, June 2025)
Summary Contributed by: Bibek Kattel (Author)
Gold nanoparticles (AuNPs) have diverse applications in medicine, electronics, optical devices, sensors, and sensing technologies. Hence, the development of advanced characterization technology to determine its potential toxicity is essential. This paper introduces a novel 3D-printed U-cavity sensor for radio frequency (RF) characterization of gold nanoparticles based on three different geometric shapes. Each nanoparticle's shape exhibited a unique RF spectral signature, enabling the accurate characterization of the gold nanoparticles.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 12, June 2025)
Summary Contributed by: Kamalesh Tripathy
Cinnamic acid (CA) has multiple benefits, including its antioxidant, anti-inflammatory, antibacterial, and anticancer properties. However, its unregulated usage has harmful effects. This paper introduces a novel molecularly imprinted polymer-based graphite electrode developed for the detection and quantification of CA in black tea and cinnamon powder. Using differential pulse voltammetry, it shows a wide linear range (1–1000 µM) and a low detection limit (8.2 nM), exhibiting excellent repeatability and stability.
Author: Yang Xh, Gao Shuai, Ge Zhongxuan., Jones Adam, Li Kang, Liu Zhihai, Ma Minghua., Sivanathan Sivagunalan, Teng Pingping, Tian Fengjun, Wang Shengjia, Wen Xingyue., Zhang Bo, Zhang Yang, Zhang Yu, Zhu Zheng
Published in: IEEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Diabetes management usually involves frequent checks of blood glucose levels. This study proposes an early prototype of a skin-friendly photoelectrochemical (PEC) sensing patch for noninvasive glucose monitoring. The patch uses a tiny optical fiber coated with specialized materials and an enzyme that reacts only with glucose. It delivers fast and accurate readings, even at very low glucose levels, making it a promising tool for painless, real-time health monitoring.
Design and Implementation of a System to Control Bioreceptor Layer Formation on Au Electrodes
Author: Przadka Marcin Paweł, Pala Katarzyna, Wojcieszak Damian
Published in: IEEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Payal Savani
In electrochemical biosensors, electrodes convert biochemical reactions into accurate electrical signals. Their surface quality and preparation directly influence the sensor's accuracy. This study introduces an in-situ quality control system to monitor bioreceptor layer formation on gold electrodes in aquaculture biosensors. By integrating real-time measurements of the wetting angle and electrochemical impedance, the system detects defects early, ensures consistent electrode performance, improves reproducibility, and enables efficient, automated production of biosensors.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Alessandra Fusco (Author)
Monitoring and tracking the breathing rate (BR) accurately is vital for healthcare applications. However, current contactless methods are often restrictive and face challenges in real-life scenarios. This study presents a deep learning approach that uses frequency-modulated continuous wave (FMCW) radar to estimate breathing rates across multiple ranges. The method achieves high accuracy with minimal memory requirements, making it suitable for reliable, accurate, and cost-effective monitoring in everyday environments.
Braille Recognition Based on a Dual-Mode Tactile Sensor With Piezoresistive and Piezoelectric Properties by the CNN-ResNet-BiLSTM Fusion Model
Author: Wang Feilu, Hu Anyang, Liu Mengru, Song Yang, Zhu Jinggen
Published in: IEEE Sensors Journal (Volume: 25, Issue: 9, May 2025)
Summary Contributed by: Saurabh Dubey
Braille is a tactile writing system to assist visually impaired individuals in reading and writing. This research presents a micropyramid-structured dual-mode tactile sensor that combines piezoresistive and piezoelectric properties to capture static and dynamic pressures for Braille Recognition. A CNN-ResNet-BiLSTM fusion model analyzes the sensor data and extracts spatiotemporal features to identify Braille characters accurately and improve tactile information processing. This compact, robust system enables reliable and real-time Braille recognition.
Highly Sensitive Enzyme-Modified Field Effect Transistor Based Biosensor for Sarcosine Detection
Author: Saikia Onishaa, Dutta Jiten Ch
Published in: IEEE Sensors Journal (Volume: 25, Issue: 12, June 2025)
Summary Contributed by: Onishaa Saikia (Author)
Precise measurement of very low concentrations of Sarcosine present in the human body is challenging. This study introduces an enzyme-modified field effect transistor based biosensor that integrates a nano-composite based enzyme supporting layer with a high-k dielectric CNT-ISFET. This biosensor achieves high sensitivity, a very low limit of detection, acceptable stability, along with good repeatability and reproducibility, making it ideal for detecting Sarcosine, a crucial biomarker for Prostate Cancer.
A Novel All-Solid-State Levocetirizine-Selective Potentiometric Microsensor
Author: Dere Nursen
Published in: EE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Payal Savani
Antihistamines like Levocetirizine (LEV) are globally used to treat allergies. Accurate pharmaceutical formulations and quality control are essential to ensure the effectiveness of drugs. This study presents a novel all-solid-state potentiometric microsensor that selectively detects Levocetirizine utilizing Levocetirizine-tetraphenylborate (LEV-TPB). This compact, low-cost microsensor shows low detection limits, a wide operating range, short response times, high accuracy, sensitivity, and selectivity, making it a reliable solution for the effective monitoring of Levocetirizine.
Bismuth Functionalized Inkjet-Printed Electrochemical Sensor for Aqueous Lead (II) Detection
Author: Arif Annatoma, Acevedo-Gonzalez Alexis J., Cabrera Carlos R., Roberts Robert Christopher
Published in: IEEE Sensors Journal (Volume: 25, Issue: 11, June 2025)
Summary Contributed by: Arif Annatoma (Author)
Routine monitoring of water quality includes testing it for lead contamination. The paper presents an innovative 3D bismuth-functionalized, inkjet-printed electrochemical sensor offering reliable and rapid detection of lead(II) in water. This affordable, reusable, flexible, and scalable sensor provides a portable solution with high sensitivity and selectivity, enabling communities and industries to protect public health, meet environmental compliance standards, and integrate advanced sensing technologies, thereby ensuring water safety in real-world applications.
The Dynamics of Flexural Ultrasonic Transducers With Nitinol Plates
Author: Hamilton Alexander, Adams Sam, Chambers John, Feeney Andrew, Hafezi Mahshid, Liu Yuchen
Published in: EEE Sensors Journal (Volume: 25, Issue: 12, June 2025)
Summary Contributed by: Alex Hamilton (Author)
The dynamics of commercial aluminium flexural ultrasonic transducers, such as proximity sensors for car parking, are sensitive to fabrication inconsistencies and temperature, which limit their applications. This paper introduces Nitinol for better control of sensor dynamics. Through stress and temperature dependent moduli, Nitinol sensors exhibit a stable resonance frequency up to 80°C. This stability is due to the complex interplay between the dynamic nonlinearity of the piezoceramic and Nitinol moduli.
Unobtrusive Multimodal Monitoring of Physiological Signals for Driver State Analysis
Author: Amidei Andrea, Pavan Paolo, Rabbeni Roberto, Tagliavini Giuseppe
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Andrea Amidei (Author)
Driver distractions, stress, and fatigue are leading causes of accidents. This study introduces ANGELS v2, an enhanced smart steering wheel system that processes electrodermal activity (EDA) and photoplethysmography (PPG) signals by capturing signals such as heart rate, respiration, and skin response to assess the driver's physiological states in real time. Integrated into the vehicle's steering wheel for unobtrusive multimodal sensing, ANGELS v2 showed near-clinical accuracy in a high-fidelity simulator study.
Investigation on Substrate Material for a Sensitive Flexible Piezoresistive Pressure Sensor
Author: Gupta Navneet, Neeraj Neeraj
Published in: IEEE Sensors Journal (Volume: 25, Issue: 7, April 2025)
Summary Contributed by: Saurabh Dubey
Flexible piezoresistive pressure sensors (FPPS) are revolutionizing wearable electronics, soft robotics, and healthcare monitoring. This study identifies polyethylene naphthalate (PEN) as the optimal substrate, offering superior thermal stability, flexibility, and chemical resistance. Validated through simulations, PEN-based FPPS achieved high sensitivity, superior charge transport, and improved mechanical stability than traditional alternatives. By combining multi-criteria material ranking with simulation, this research leads to the development of the next-generation wearable sensors and energy-harvesting devices.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 7, April 2025)
Summary Contributed by: Roger Hasler (Author)
Understanding biomolecular interactions at the solid-liquid interface is key to biotechnology innovations. This study describes the development of a multimodal sensor that integrates optical and electronic readout principles on a single chip, enabling simultaneous monitoring of surface mass and charge density variations associated with (bio)interactions. Combining grating-coupled surface plasmon resonance (SPR) with coplanar-gated field-effect transistors (FET), this scalable, portable platform offers high-precision, dual-mode analysis of complex bio-interfaces for next-generation diagnostics.
Low Latency Visual Inertial Odometry With On-Sensor Accelerated Optical Flow for Resource-Constrained UAVs
Author: Kuhne Jonas, Benini Luca, Magno Michele
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Jonas Kühne (Author)
Visual-inertial odometry (VIO) is increasingly used for autonomous navigation in unmanned aerial vehicles (UAVs). This study introduces a low-latency VIO system that integrates an on-camera optical flow accelerator with an existing state-of-the-art VIO pipeline. Offloading motion tracking to the sensor itself significantly reduces computational load (53.7%), energy consumption (14.24%), and latency (49.4%). This approach maintains, and in some cases even improves, tracking accuracy, making it ideal for resource-constrained UAVs.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 6, March 2025)
Summary Contributed by: Payal Savani
Sensors are the silent sentinels of technology, translating invisible changes into meaningful data. Among them, pH sensors are vital for monitoring hydrogen ion concentration in biomedical and environmental fields. The study explores a high-performance Extended-Gate Field-Effect Transistor (EGFET) based pH sensor, developed by modifying zinc oxide with phosphorene. It has boosted sensitivity from 51.0 to 62.5 mV/pH and lowered the drift rate from 1.428 to 0.714 mV/h.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Gianluca Barile (Author)
The ease of fabrication and versatile use make capacitive sensors a popular choice. This work introduces a fully differential analogue read-out circuit for differential capacitive sensors, featuring an auto-balancing bridge with voltage-controlled capacitors (VCCs) and integral negative feedback. The interface achieved 102 mV/pF sensitivity, and a linearity error of 0.47%, with 8–11 ms dynamic response times. The design enhances sensitivity and linearity, reduces parasitic effects, and demonstrates strong potential for precision sensing.
The Implementation of Single VCII-Based RC Sinusoidal Oscillators: 28 Novel Configurations
Author: Barile Gianluca, Scarsella Massimo
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Gianluca Barile (Author)
The design of sinusoidal oscillators is a challenging research area. This work presents 28 novel, energy-efficient RC (Resistor-Capacitor) sinusoidal oscillators based on a single second-generation voltage conveyor (VCII). These designs significantly reduce component count compared to traditional operational amplifier circuits and operate in current-mode, enabling low power consumption without requiring an additional voltage output buffer. Experimental validation confirmed 16 configurations operating as expected, highlighting their potential for advanced sensor interfacing applications.
Design and Optimization of a Highly Sensitive Surface Plasmon Resonance Biosensor for Accurate Detection of Mycobacterium tuberculosis
Author: Mahmud Russel Reza, Barua Bobby, Islam M. Shariful, Mondal Tanu Prava, Rafi Shah Ali
Published in: IEEE Sensors Journal (Volume: 25, Issue: 6, March 2025)
Summary Contributed by: Russel Reza Mahmud (Author)
Surface Plasmon Resonance (SPR) has transformed medical diagnostics. This paper presents a highly sensitive SPR biosensor developed for the accurate detection of tuberculosis (TB) causing bacteria, Mycobacterium tuberculosis. By leveraging a novel hybrid structure incorporating black phosphorus and optimized material layers, the sensor achieved remarkable angular sensitivity, enabling rapid, label-free diagnosis with high precision. It can detect even trace amounts of bacteria, providing a powerful tool for faster and accurate TB screening.
Enhancement of Target Localization Based on Angle-of-Arrival Measurement via Quantum Sensor Networks
Author: Chai Hongzhou, Hui Jun
Published in: IEEE Sensors Journal (Volume: 25, Issue: 6, March 2025)
Summary Contributed by: Hongzhou Chai (Author)
With the advancement of quantum information technology, integrating quantum resources, such as entangled photons into traditional measurement fields can improve parameter estimation accuracy. This study introduces a novel quantum-enhanced angle-of-arrival (AoA) estimation method for evaluating the performance of a quantum sensing localization system. The work contributes to realizing quantum navigation and localization with drastically improved integrated accuracy, thereby refining its applications in radar, navigation, wireless communication, and target localization.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Simone Benatti (Author)
Accurate hand motion modeling is important for intuitive human–machine interaction (HMI). This paper introduces an event-based high-density surface electromyography encoding method for multifinger force estimation, optimized for real-time, low-power microcontroller applications. Evaluated on the High-densitY Surface Electromyogram Recording (HYSER) dataset in realistic multiday settings, it showed competitive accuracy. With energy consumption under 6.5 μJ per sample and latency below 280 μs, it enables efficient, real-time regression for future wearable HMI applications.
Volatile Organic Compounds (VOCs) pose significant health risks, making the effective monitoring of these compounds essential. This article presents a novel, cost-effective chemoresistive sensor that uses citrate-functionalized gold nanoparticles (AuNPs) deposited on cotton fabric for precise acetone (CH3COCH3) detection. Its impedance-based mechanism demonstrates high selectivity and strong reusability. This AuNP-Textile sensor offers a promising solution for portable, real-time VOC exposure assessment in applications ranging from health monitoring to environmental pollution.
A Multimatrix E-Nose With Optimal Multiranged AFE Circuit for Human Volatilome Fingerprinting
Author: Radogna Antonio Vincenzo, Capone Simonetta, D'Amico Stefano, Forleo Angiola, Grassi Giuseppe, Siciliano Pietro Aleardo
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Radogna Antonio Vincenzo (Author)
The human volatilome, a combination of volatile organic compounds (VOCs) present in breath and bodily fluids, reflects overall health and can signal the early onset of disease. This study presents SPYROX, an electronic nose that converts VOC signatures into digital fingerprints. It features a multirange analog front-end (AFE) circuit with a multimatrix learning algorithm for adaptive sensitivity across diverse samples. SPYROX offers an accurate, non-invasive, portable solution for routine health screenings and diagnostics.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Saurabh Dubey
Niobium-doped BZT-BCT thin films are emerging as a sustainable, high-performance alternative to the toxic lead zirconate titanate (PZT) for piezoelectric devices. Fabricated via a sol-gel process and optimized poling, these lead-free films exhibit enhanced dielectric, ferroelectric, and piezoelectric properties. With stable switching, improved resonance, and strong mechanical integrity, they demonstrate promise for MEMS devices, biomedical implants, and energy-harvesting applications, thus paving the way for eco-friendly piezoelectric technologies.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Hussain Irfan (Author)
Supernumerary robotic arms (SRAs) can assist post-stroke patients with daily activities. However, its conventional designs are bulky and power-hungry. This paper introduces a novel SRA featuring twisted, string-driven flexure joints that eliminate large actuators, resulting in a compact, lightweight, and energy-efficient wearable device. This advance in assistive robotics empowers stroke survivors to regain independence in bimanual activities and paves the way for the next generation of affordable, human-assistive technologies.
Smart, Wearable and Power-Controlled Mixed-Signal Platform for Screening and Follow-Up of Cystic Fibrosis Based on Real-Time Chloride Concentration Evaluation in Sweat
Author: De Venuto Daniela, Bollella Paolo, De Venuto Domenica, Mascellaro Grazia, Spadavecchia Giuseppe, Torsi Luisa
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Payal Savani
Wearable sensors have garnered significant attention in recent years, particularly in the realm of personalized diagnostics and continuous health monitoring. This paper discusses the development of a wearable sweat-based sensor system for monitoring cystic fibrosis (CF) in patients. It offers a resolution of ±2 mV and sensitivity of 56.9 mV/dec, with an average power consumption of 350 micro watts. The sensor is a compact, energy-efficient, and developed for home use.
A Wearable Multisensor Fusion System for Neuroprosthetic Hand
Author: Liu Honghai, Meng Jianjun, Ding Han, Guo Weichao, Shi Shang, Yang Xingchen, Yin Zongtian
Published in: IEEE Sensors Journal (Volume: 25, Issue: 8, April 2025)
Summary Contributed by: Liu Honghai (Author)
Getting a near-natural control from neuroprosthetic hands is challenging. This study introduces a compact, wearable multisensor system that integrates ultrasound, surface electromyography (sEMG), and Inertial Measurement Unit (IMU) sensors to improve prosthetic hand control. Ultrasound and EMG model gestures, sEMG detects resting states, and the IMU filters unintended movements like shaking. The system's small size allows seamless integration into prosthetic sockets, and control strategies enhance stability, offering an improved experience for amputees.
An Open-Path Optical Sensor for Hydrogen Sulfide and Methane Detection by QCL
Author: Li Jun, Fan Binbin, Hao Le, Jaworski Piotr, Luan Guohua, Ma Tian, Wang Zhen, Zeng Qingjie, Zhai Xiaowei, Zhang Jiarui
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Saurabh Dubey
A Quantum Cascade Laser–based open-path optical sensor enables real-time, precise, and high-sensitivity detection of harmful hydrogen sulfide (H₂S) and methane (CH₄) gases up to 50 m and a response time of 3.4 s. Resistant to water vapor interference, it delivers a strong signal-to-noise ratio, surpassing traditional sensors. Ideal for remote oilfields, refineries, and hazardous sites, it ensures reliable long-range monitoring with future IoT integration and multi-gas detection for enhanced industrial safety.
Nonlinear Behavioral Model of Capacitive MEMS Microphone for Predicting Ultrasound Intermodulation Distortion
Author: Rahaman Ashiqur, Albahri Shehab, Boor Steven, Bradt Christopher, Lee Sung B.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 1, January 2025)
Summary Contributed by: Ashiqur Rahaman (Author)
Ultrasound intermodulation distortion (IMD) in microphones, particularly in hearing aids, can lead to audible distortions around ultrasonic devices. The primary source of this nonlinearity is the micro-electromechanical systems (MEMS) transducer. This paper explores how specific design features of capacitive MEMS microphones affect IMD using a nonlinear behavioral model to reduce distortion while maintaining acoustic performance. The optimized design shows 15 dB IMD reduction at 20 kHz, providing excellent electro-acoustic characteristics.
Design and Simulation Analysis of Electrolyte-Gated Aluminum Oxide Organic Thin-Film Transistor Biosensor for High Sensitivity
Author: Wadhwa Girish, Proto Antonino, Taibi Angelo, Thakur Anchal
Published in: IEEE Sensors Journal (Volume: 25, Issue: 6, March 2025)
Summary Contributed by: Payal Savani
The pH sensor has various applications in environmental, industrial, and healthcare monitoring. This paper introduces an electrolyte-gated aluminum oxide organic thin-film transistor (EG-Al₂O₃ OTFT) biosensor with a pentacene structure designed for highly sensitive detection. Using aluminum oxide improved stability, sensitivity, and low-voltage operation. The biosensor detects biomolecules by converting biochemical interactions into electrical signals. This low-cost, flexible, efficient device can prove to be a reliable biosensing for medical diagnostics and environmental monitoring.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 4, February 2025)
Summary Contributed by: Gutierrez-rojas Daniel (Author)
As industrial systems grow more complex powered by wireless sensor networks (WSNs), effective anomaly detection becomes essential. This paper introduces a smart, explainable framework to detect and classify anomalies in WSN-enabled Cyber-Physical Systems. Enhanced by novel explainable AI (XAI) techniques, the model incorporates data acquisition, fusion, and analytics. The results show high accuracy and reliability with reduced risks, faster fault correction, enhanced efficiency, system security, and resilience against cyber threats.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 5, March 2025)
Summary Contributed by: Kamalesh Tripathy
Transimpedance amplifiers (TIAs) are essential for sensing applications that require accurate current-to-voltage conversion, such as biosensing, materials analysis, and device testing. Conventional TIA designs face trade-offs between gain, bandwidth, noise, and chip area. This paper introduces a programmable TIA fabricated in 65-nm Si-CMOS for high-capacitance inputs, using active feedback to achieve high effective resistance. The result is a compact, efficient, and flexible solution ideal for modern high-capacitance sensor interfaces.
Substrate Effects on the Transient Chemiresistive Gas Sensing Performance of Monolayer Graphene
Author: Fahrenthold Eric, Doshi Manasi, Zhang Jie
Published in: IEEE Sensors Journal (Volume: 25, Issue: 3, February 2025)
Summary Contributed by: Eric P. Fahrenthold (Author)
The substrate supporting monolayer graphene profoundly impacts its electronic properties and electrochemical response. Using a novel, non-contact eddy current method, the researchers show that different substrates dope the graphene in different ways, altering its conductivity, and can reverse how it reacts to gas exposure. This approach offers a fast, non-destructive method for qualitative assessment of low-dimensional materials and provides practical insights for sensor design.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 3, February 2025)
Summary Contributed by: Saurabh Dubey
Health monitoring systems integrated into vehicles improve road safety. This paper presents a novel reflective photoplethysmogram (PPG) sensor designed for in-vehicle heart rate monitoring. Embedded in the backrest of the vehicle's seat, the device provides non-intrusive, regular, and accurate heart rate monitoring with minimal motion or clothing interference. It is ideal for in-vehicle health monitoring applications that monitor heart rate, stress, and fatigue, thus enhancing driver comfort and safety.
Temperature-sensing methods with high sensitivity and quick response times are crucial for applications that require real-time temperature monitoring in challenging conditions. This paper introduces a novel optical fiber temperature sensor with a silicon Fabry-Pérot cavity attached to a single-mode fiber tip that achieves high sensitivity (84.6 pm/°C), exceptional resolution (0.0006°C), and a fast response time of 0.51 ms. The innovative design and performance metrics make it ideal for dynamic environments.
Tradeoff Between the Number of Transmitted Molecules and the BER Performance in Molecular Communication Between Bionanosensors
Author: Eckford Andrew, Jing Dongliang, Li Linjuan, Lin Lin
Published in: IEEE Sensors Journal (Volume: 25, Issue: 1, January 2025)
Summary Contributed by: Anupama
Molecular communication (MC) uses bionanosensors to transmit data using molecules. Due to limited transmitter resources, optimizing communication efficiency is critical. This study analyzes the relationship between the number of transmitted molecules and the bit error rate (BER). It introduces a balance function and uses a Gradient Descent Algorithm to find an optimal tradeoff. Results highlight a tunable framework for balancing communication reliability and molecular resource usage, benefiting applications in defense, healthcare, entertainment, and biosensing.
Monitoring the concentration of proteins in interstitial fluid is vital for assessing various diseases, including albuminuria and edema. This paper proposed an electrical spectroscopy-based system enhanced with admittance relaxation time distribution (aRTD) for protein concentration quantification. Results indicate that aRTD shows a positive correlation with total protein concentration at high relaxation times and can distinguish between albumin and γ-globulin concentration fluctuation at lower relaxation times.
Real-Time Vehicle Classification and License Plate Recognition via Deformable Convolution-Based Yolo v8 Network
Author: R Srinivasan, A Arivarasi, D Rajeswari, Govindasamy Alagiri
Published in: IEEE Sensors Journal (Volume: 24, Issue: 23, December 2024)
Summary Contributed by: Saurabh Dubey
An exponential increase in vehicles has made traffic management challenging. The proposed novel DEN-YOLO uses a YOLOv8 model with a deformable convolution network for better adaptation to varying object shapes. It uses low-light enhancement, defogging, and super-resolution to improve image clarity even in challenging conditions. It provides fast and reliable vehicle and license plate detection for traffic management, toll collection, and surveillance, making it ideal for real-world applications.
Design and Fabrication of Highly Performance EGFET and Application in Thrombin Detection
Author: Wang Yiqing, Ding Song, Jiang Jidong, Liu Tao, Wang Ting, Zhang Minghui, Zhang Wei, Zhu Xinglong
Published in: IEEE Sensors Journal (Volume: 25, Issue: 3, February 2025)
Summary Contributed by: Yiqing Wang (Author)
Extended-gate field-effect transistors (EGFETs) are highly effective in ion detection, particularly pH sensing. Their unique design simplifies fabrication and maintenance. This study introduces a 3D simulation-optimized EGFET designed for pH sensing and detecting highly sensitive thrombin, a crucial biomarker in blood coagulation. The device demonstrated exceptional pH sensitivity, long-term stability, and quick and specific thrombin recognition. The results highlight the potential applications in biomedical diagnostics, environmental monitoring and point-of-care testing.
Flexible Conductive Polymer Reinforced Polyurethane Foam for Real-Time Human Body Electrical Signal Sensing and ECG Peaks
Author: Subramanian Jeyanthi, M Suchetha, Rajeev Krishna, Vijayan Akash
Published in: IEEE Sensors Journal (Volume: 25, Issue: 3, February 2025)
Summary Contributed by: Saurabh Dubey
Polymer composites made from conductive and flexible material are transforming wearable health devices. This study introduces a soft, flexible foam made from polyurethane and reinforced with conductive polymers, designed to detect the human body’s electrical signals like electrocardiogram (ECG). This sensor captures real-time data without requiring the traditional gel electrodes. The eco-friendly device provides stable monitoring and enhances accuracy and comfort, making it ideal for wearable medical technologies and biosensing applications.
Monitoring the properties of aqueous solutions is essential across various industries like agriculture and oceanics. This paper introduces a novel, low-cost, interdigitated electrode (IDE) sensor based on electrochemical impedance spectroscopy to assess the properties of aqueous solutions. This sensor effectively detects subtle differences in concentration and provides reliable pH measurements with high sensitivity, showing its potential for applications in different areas, like the food industry and environmental and biological studies.
Author: Joseph Jose, A. V. Akshaya, ANANTHASURESH G. K., Bosco Michael John, Nair Nikila
Published in: IEEE Sensors Journal (Volume: 25, Issue: 1, January 2025)
Summary Contributed by: Anupama
Traditional glass pH sensors often degrade in harsh environments and become ineffective under extreme pH conditions. This study introduces an innovative all-solid-electrode pH sensor featuring an antimony sensing electrode and an Ag/AgCl solid reference electrode. The sensor demonstrated stability, repeatability and linear performance in controlled and real-world applications. It offers a robust, durable, low-maintenance solution for continuous inline pH monitoring in various fields, including food processing, water treatment, agriculture, and pharmaceuticals.
Flexible Electrospun Nanofibers for Tactile Sensing and Integrated System Research
Author: Chen Rongsheng, Ma Zhiling, Huang Wei, Yang Mei
Published in: IEEE Sensors Journal (Volume: 25, Issue: 1, January 2025)
Summary Contributed by: Rongsheng Chen (Author)
The demand for flexible sensors has grown with the advancement in wearable technology and smart systems. This paper discusses the development of a flexible piezoelectric sensor using electrospun nanofibers with a controlled structure and alignment, which improves the sensor's performance. It highlights the advantages and exceptional piezoelectric properties, flexibility, and sensitivity of materials like polyvinylidene fluoride (PVDF) and its copolymers. Its applications include wearable electronics, human-computer interaction, electronic skins, and soft robotics.
Highly Sensitive Flexible Sensor Over a Wide Linear-Range Based on Carbon Nanotube Toward Physiological Monitoring
Author: Pan Gebo, Gao Xin, Lv Peiyu, Qin Xu, Xu Wenqing, Yang Limei
Published in: IEEE Sensors Journal (Volume: 25, Issue: 3, February 2025)
Summary Contributed by: Saurabh Dubey
Capacitive pressure sensing is crucial in real-time physiological monitoring and human-robot interaction. This study presents a novel sensor developed using a composite dielectric layer of polyvinylidene fluoride, thermoplastic polyurethane, and multi-walled carbon nanotubes (MWCNTs). Its exceptional sensitivity and wide range effectively detect substantial and subtle human motion, including swallowing and muscle and joint movement. Flexibility, mechanical stability, and responsiveness make it suitable for next-generation wearable health monitoring and healthcare applications.
Microwave Glucose Sensing Using Double Circular Split Ring Resonators for Improved Sensitivity: The Role of Artificial Blood Plasma and Deionized Water
Author: Borges Ben-hur, Alarcon Julio Cesar, Pepino Vinicius Marrara, Santos Natalia M., Souza Mateus Isaac de Oliveira, Varanda Laudemir C.
Published in: IEEE Sensors Journal (Volume: 25, Issue: 3, February 2025)
Summary Contributed by: Borges Ben-hur (Author)
Accurate and affordable glucose monitoring is vital for managing diabetes, affecting millions worldwide. This research presents a compact, passive 2.48 GHz microwave sensor for enhanced glucose monitoring. The sensor's accuracy is significantly boosted by replacing deionized water with artificial blood plasma, achieving a 0-400 mg/dL range with 25 mg/dL resolution. Low cost and license-free operation make this novel sensor promising for comfortable, accurate, and accessible next-generation wearable health devices.
Research on Intelligent Diagnosis Method of Swallowing Signal Based on Complex Electrical Impedance Myography
Author: Yu Shaoshuai, Chu Xu, Fu Letian, Fu Zhang, Liu Qi, Yang Yuxiang
Published in: IEEE Sensors Journal (Volume: 25, Issue: 4, February 2025)
Summary Contributed by: Payal Savani
Dysphagia or swallowing disorders occur when the muscles or nerves involved in swallowing malfunction. Early and accurate detection will reduce risks to health and life. This study presents an innovative diagnostic framework that integrates Complex Electrical Impedance Myography (C-EIM) with advanced machine learning algorithms that analyze both amplitude and phase data. The smart system achieves an accuracy of 95.2%, demonstrating strong potential in early diagnosis and clinical decision-making for managing dysphagia.
Microneedle Uric Acid Biosensor With Graphite Ink and Electrodeposited MWCNT
Author: Kameoka Jun, Kawahira Hiroshi, Nohgi Toru, Tu Yifan
Published in: IEEE Sensors Journal (Volume: 25, Issue: 3, February 2025)
Summary Contributed by: Jun Kameoka (Author)
Uric acid is a well-established biomarker for gout. Recent studies have suggested its prospective as an indicator of visceral fat accumulation, particularly in monitoring metabolic syndrome. This paper introduces a microneedle-based uric acid biosensor using graphite ink and electrodeposited multi-walled carbon nanotubes (MWCNTs). The device supports non-invasive, real-time monitoring of uric acid concentrations in interstitial skin fluid (ISF). It has excellent potential for point-of-care applications and integration into wearable health technologies.
Parallel Detection of Mixed Pesticides Based on Dual Quantum Dot/Porous Silicon Optical Biosensors
Author: Jia Zhenhong, Cao Jianghong, Huang Xiaohui, Lv Xiaoyi, Wang Jiajia, Yang Jie, Yue Haitao
Published in: IEEE Sensors Journal (Volume: 24, Issue: 23, December 2024)
Summary Contributed by: Saurabh Dubey
Pesticide detection is vital for protecting human health and the environment. The proposed optical biosensor uses dual quantum dots and porous silicon technology to provide a cost-effective and real-time solution for detecting mixed pesticides. With high sensitivity, stability, and low cross-reactivity, this biosensor can efficiently monitor pesticides, thus improving food and environmental safety. Its application in resource-limited areas helps reduce costs and facilitates automated pesticide monitoring and detection.
Liquid Crystal Microlens Arrays Based on Aluminum-Doped Zinc Oxide Oriented Microstructure Facilitate Light Field Image Resolution Enhancement
Author: Li Hui, Li Zikang, Qiao Chuan, Wu Yuntao
Published in: IEEE Sensors Journal (Volume: 25, Issue: 4, February 2025)
Summary Contributed by: Hui Li (Author)
Light-field cameras are excellent at capturing comprehensive scene information; however, they often face issues due to unstable liquid crystal (LC) alignment in their liquid crystal microlens arrays (LC-MLAs). This study introduces an LC-MLA imaging system based on an aluminum-doped zinc oxide (AZO) alignment layer, achieving ordered LC alignment. The system enhances image resolution by integrating full variational denoising and convex optimization, contributing significantly to the advancements in light-field imaging technology.
Design and Test of a High-Sensitivity MEMS Capacitive Resonator for Photoacoustic Gas Detection
Author: Shi Junhui, Gao Da, Ren Danyang, Wang Yuqi, Yin Yonggang
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Anupama
Photoacoustic spectroscopy (PAS) enables precise trace gas detection by converting absorbed laser energy into acoustic signals. This study introduces a high-sensitivity micro-electromechanical system (MEMS) capacitive resonator for photoacoustic gas detection designed by altering the overlapping areas to minimize gas damping. Experimental results demonstrate increased sensitivity and stability of the resonator and improved trace gas detection methods. The advancement paves the way for more sensitive and accurate environmental monitoring and other applications.
HOT Watch: IoT-Based Wearable Health Monitoring System
Author: Jhansi Bharathi Madavarapu, S. Nachiyappan, S. Rajarajeswari, N. Anusha, Nirmala Venkatachalam, Rahul Charan Bose Madavarapu, A. Ahilan
Published in: IEEE Sensors Journal (Volume: 24, Issue: 15, October 2024)
Summary Contributed by: Saurabh Dubey
Heart rate oxygen rate temperature watch (HOT Watch) transforms IoT-based health monitoring by providing real-time tracking of vital signs with an accuracy exceeding 99.4%. It outperforms other leading devices available. Powered by IoT and the Pan-Tompkins algorithm(PTA), it efficiently processes health data and transmits it via Bluetooth for instant notification. GPS tracking and real-time alerts facilitate prompt medical responses, making it a dependable solution for personal and remote healthcare.
Discriminating Between Indoor and Outdoor Environments During Daily Living Activities Using Local Magnetic Field Characteristics and Machine Learning Techniques
Author: Vincenzo Marcianò, Andrea Cereatti, Stefano Bertuletti, Tecla Bonci, Lisa Alcock, Eran Gazit, Neil Ireson, Antonio Bevilacqua, Claudia Mazzà, Fabio Ciravegna, Silvia Del Din, Jeffrey M. Hausdorff, Georgiana Ifrim, Brian Caulfield, Marco Caruso
Published in: IEEE Sensors Journal (Volume: 25, Issue: 1, January 2025)
Summary Contributed by: Marco Caruso (Author)
Wearable sensors are essential for context-aware applications. But can they distinguish between indoor and outdoor environments? This study presents a novel method for distinguishing indoor and outdoor environments by analyzing magnetometer data and deep learning models to improve traditional inertial-based methods. It offers more reliable and high classification accuracy. The approach opens new possibilities for enhanced navigation and supports environmental detection in wearable and mobile health monitoring systems.
A Microwave Sensor Based on Grounded Coplanar Waveguide for Solid Material Measurement
Author: Liu Guohua, Gong YuXiang, Jiang Shuren, Zhang Jiaqi, Zhang Rui
Published in: IEEE Sensors Journal (Volume: 25, Issue: 3, February 2025)
Summary Contributed by: Liu Guohua (Author)
Accurate measurement of permittivity is crucial for characterizing the electromagnetic properties of materials. This study presents a compact, high-sensitivity microwave sensor utilizing a grounded coplanar waveguide (GCPW) integrated with a parallel interdigital capacitor (P-IDC) and split-ring resonator (SRR). This design enhances electric field concentration and signal isolation, enabling precise permittivity detection. The optimized GCPW and interdigital capacitor (IDC) parameters show significant potential in advanced communication and electronic applications.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Saurabh Dubey
Urinary tract infections (UTIs) are among the most common infections worldwide. This paper introduces an innovative gas-phase detection technology for UTI diagnostics that uses metal-oxide sensors and change-point detection (CPD) to efficiently identify bacterial growth through volatile organic compounds (VOCs) emissions. The approach showed promising results for rapid, non-invasive UTI detection, enabling real-time monitoring, reducing diagnostic delays, minimizing unnecessary antibiotic intake, and providing cost-effective point-of-care diagnostics with minimal equipment.
Nanoelectromechanical resonators are some of the most sensitive devices to external perturbations that can be built. However, reading nanoscale vibrational motion with the help of electrical signals in the background of noise from a profusion of sources can be very challenging. The method in this paper utilizes the materials’ intrinsic piezoresistivity to transduce the mechanical vibrations to electrical signals, effectively leveraging a simple circuit configuration compared to existing methods.
High-Throughput Separation of Alexandrium Cells Based on Deterministic Lateral Displacement Arrays With Different Post Shapes
Author: Wang Junsheng, Ding Gege, Liu Jiayue, Wang Yanjuan, Wen Jie, Yan Yuxian, Zhao Jun
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Kamalesh Tripathy
Separating and purifying algae cells is crucial for studying algae and monitoring algal blooms in water bodies. This paper explores a novel algae separation technique, mainly for Alexandrium algae, a leading cause of red tide that affects the marine environment. It utilizes a deterministic lateral displacement (DLD)-based microfluidic chip with two different micropillar designs to separate microalgae cells, facilitating fast, high-throughput, and large-scale separation of Alexandrium cells vital for protecting marine ecosystems.
A 30-nΩ Accuracy Low Power Two-Step Ratiometric Shunt Resistance Measurement System Using a Switching Regulator- Based Current Generator for Shunt- Based Current Sensors
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Shogo Kawahara (Author)
Shunt-based current sensors have low offset and low gain error, and they are used for accurate estimation of the state-of-charge of the batteries in automotive applications. However, the gain error changes by ~1% due to the long-term drift of the shunt resistance (RS). This paper proposes a two-step ratiometric resistance measurement system that can measure a 25 µΩ RS with an accuracy of ≤ 30 nΩ (0.12%) to calibrate the drift.
Split Gate Bulk-Planar Junctionless FET-Based Biosensor for Label-Free Detection of Biomolecules
Author: Deepika Singh, Ganesh C. Patil, Bikash Dev Choudhury
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Saurabh Dubey
The split-gate Bulk-planar junctionless field-effect transistors (SG-BPJLFET) biosensor offers cost-effective, high sensitivity, and precise detection of biomolecules through drain current changes. Its innovative design enhances selectivity and sensitivity by leveraging a split-gate structure and junctionless architecture, ensuring effective biomolecule interaction and charge modulation. The device exhibits fast response and high performance due to the reduced leakage current and scalable fabrication. It holds the potential for medical diagnostics and advanced biosensing.
Double-Beam Cantilever Probe for Crack Probability Analysis of Multilayer Substrates During Wafer Probing
Author: Tremmel Florian, Holmer Rainer, Kutter Christoph, Nagler Oliver
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Tremmel Florian (Author)
Semiconductor devices undergo mechanical stress during functionality checks in the wafer prober, which may cause hidden cracks. This paper introduces an innovative double-beam cantilever probe to evaluate these cracks in multilayer substrate during wafer probing. This sensor solution regulates the load limits of the chips and detects crack sounds faster in real-time, ensures safer and more reliable chip testing, and offers a promising solution for wafer probing processes in semiconductor manufacturing.
Subblescope: Novel Thin-Film Haptic Sensing Using a Single-Bubble Approach
Author: Debadutta Subudhi, Prasanna K. Routray, Manivannan Muniyandi
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Anupama
The Subblescope is a novel vision-based haptic sensor that uses a single air bubble embedded in a flexible elastomer to detect and measure forces. By capturing and analyzing the deformation of the bubble, the sensor can perform precise measurements of force and torque, enabling accurate tactile sensing. This simple yet effective design has potential applications in robotics, virtual reality, and human-computer interaction.
Acoustofluidic Particle Trapping in a Structured Microchannel Using Lateral Transducer Modes
Author: Fuchsluger Andreas, Andrianov Nikolai, Cselyuszka Norbert, De Pastina Annalisa, Ecker Rafael, Jakoby Bernhard, Mitteramskogler Tina, Voglhuber-Brunnmaier Thomas
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Fuchsluger Andreas (Author)
Acoustofluidics uses sound waves for contactless manipulation of particles and fluids within microfluidic systems, which is relevant for various medical applications. This study presents a novel lateral-mode acoustofluidic trapping device using a disc-shaped resonator to create a two-dimensional standing wave for efficient particle trapping. The device operates at lower frequencies and efficiently traps large sizes and volumes of particles, demonstrating high predictability, reproducibility, and stability, making it suitable for advanced particle manipulation.
Ultrahigh Sensitivity Surface Plasmon Resonance Magnetic Field Sensor Based on D-Shape Four-Hole Fiber
Author: Chen Zhenshi, Chen Cheng, Chu Paul K., Fu Haihao
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Payal Savani
Magnetic field sensors are essential in modern technology, with applications ranging from smart gadgets, biomedicine, industrial automation, and environmental monitoring to aerospace technology. This paper presents a highly sensitive sensor using surface plasmon resonance (SPR) and a D-shaped four-hole fiber designed for accurate magnetic field detection. Integrating SPR with fiber optics enhances the devices' sensitivity and performance, advancing its potential applications in areas where detecting weak magnetic signals is crucial.
Antibody-Free SERS Detection of Severe Fever With Thrombocytopenia Syndrome Virus Using Micron Bowl Array PDMS Substrates
Author: Hsu Wei-li, Wang Gou-jen, Lin Ying-Ting, Lin Ze-Cheng, Tseng Ching-Yu
Published in: IEEE Sensors Journal (Volume: 25, Issue: 4, February 2025)
Summary Contributed by: Hsu Wei-li (Author)
Severe fever with thrombocytopenia syndrome (SFTS) is a newly identified zoonotic infectious disease discovered in several East Asian countries. It is caused by the SFTS virus (SFTSV), also known as Dabie bandavirus or Huaiyangshan virus. The paper presents a novel surface-enhanced Raman scattering (SERS) chip with silver nanoparticles (AgNPs) uniformly deposited on a micron bowl array polydimethylsiloxane (PDMS) substrate to detect the virus responsible for SFTS effectively.
Scorpion-Inspired, Hydrophobic, Highly Sensitive, and Paper-Based Magnetoelastic Biosensor for C-Reactive Protein Detection
Author: Sang Shengbo, Ge Yang, Guo Xing, Yuan Zhongyun, Zhao Dong, Luo Man
Published in: IEEE Sensors Journal (Volume: 24, Issue: 8, April 2024)
Summary Contributed by: Saurabh Dubey
C-reactive protein (CRP) in human blood is a vital biomarker for detecting inflammation or acute infection. This study presents a hydrophobic, paper-based magnetoelastic biosensor inspired by scorpion anatomy and made using eco-friendly materials and V-shaped grooves to enhance sensitivity for detecting CRP. The sensor overcomes the limitations of traditional detection methods and offers rapid, cost-effective, and highly sensitive diagnostics for acute inflammation and tissue damage.
Improving the Spatial Resolution of Small Satellites by Implementing a Super-Resolution Algorithm Based on the Optical Imaging Sensor’s Rotation Approach
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Iman Kazemi (Author)
Image processing can improve the image quality of data transmitted by small satellites. This paper presents a novel method of enhancing small satellite image resolution using a super-resolution algorithm combined with a rotating sensor. The algorithm reconstructs a high-resolution image by boosting spatial resolution. This method increases image clarity by gathering more data in flight and vertical directions and efficiently processing images in approximately 0.713 seconds, making it suitable for microsatellite applications.
Rule the Joule: An Energy Management Design Guide for Self-Powered Sensors
Author: Monagle Daniel, Ponce Eric Andrew, Leeb Steven
Published in: IEEE Sensors Journal (Volume: 24, Issue: 01, January 2024)
Summary Contributed by: Saurabh Dubey
Rule the Joule Energy Management System for self-powered sensors features dynamic control, cold-start capability, and robust maximum power point tracking (MPPT) to optimize energy harvesting and storage. Its real-time energy flow regulation reduces reliance on predictive models, enhancing efficiency in noisy environments. Experimental validation confirms its reliability for powering wireless sensor nodes, providing overvoltage protection and improved component longevity, paving the way for advancement in IoT, smart technologies, and wireless sensor networks.
Microfluidic Electrochemical Sensor for Online Detection of Chemical Oxygen Demand Based on AuNPs/Au Electrodes
Author: Yang Xiaozhan, Wu Haotian, Xie Song
Published in: IEEE Sensors Journal (Volume: 24, Issue: 23, December 2024)
Summary Contributed by: Xiaozhan Yang (Author)
Chemical oxygen demand (COD) is a key parameter for water quality assessment. The paper presents a compact, microfluidic electrochemical sensor for real-time monitoring of COD in water. The sensor uses gold nanoparticles (AuNPs) on modified gold electrodes to enhance sensitivity and accuracy. It does real-time COD monitoring with high efficiency and quick response, i.e., 3 minutes. Successful tests on water samples highlight its potential for water quality monitoring and environmental management.
Triaxial 3-D-Channeled Soft Optical Sensor for Tactile Robots
Author: Matteo Lo Preti, Federico Bernabei, Anderson B. Nardin, Lucia Beccai
Published in: IEEE Sensors Journal (Volume: 24, Issue: 17, September 2024)
Summary Contributed by: Payal Savani
Robotic systems integrated with sensors show enhanced performance in challenging environments and tasks. The proposed novel triaxial 3D-channeled soft fingertip-shaped optical sensor designed for tactile robots uses transparent channels to detect forces in three dimensions. The compact and flexible sensors made from soft materials with optical waveguides enhance the robot's sensitivity to touch. It offers flexibility and accuracy for real-time tactile feedback, showing potential for real-time force detection in robotic hands.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Toshihiko Noda (Author)
Accurate plant monitoring is vital for smart agriculture. Traditional pH sensors struggle with light interference and require dark conditions for accurate pH measurement. This study introduces a novel pH image sensor mitigating light interference. Employing dual-pixel technology, it distinguishes between pH and light signals, enabling precise measurements under illumination. Results show errors within 10%, a significant improvement over existing methods. This advancement facilitates real-time multi-ion sensing for optimized crop management.
Noninvasive Blood Glucose Measurement Using RF Spectroscopy and a LightGBM AI Model
Author: Dominic Klyve, Steve Lowe, Kaptain Currie, James H. Anderson, Carl Ward, Barry Shelton
Published in: IEEE Sensors Journal (Volume: 24, Issue: 17, September 2024)
Summary Contributed by: Saurabh Dubey
Blood glucose monitoring is crucial in diabetes patients. This paper combines radiofrequency (RF) spectroscopy with a LightGBM AI model to explore a non-invasive method for measuring blood glucose levels. RF signals detect the change in blood glucose concentration in the skin, which is processed through the AI model to estimate blood glucose levels accurately. The approach aims to provide a non-invasive, safe, and convenient way for regular glucose monitoring in diabetic care.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 23, December 2024)
Summary Contributed by: Brent Leier (Author)
The limitations of conventional temperature sensors in extremely cold environments pose significant challenges across various industries. This paper introduces a microwave sensor utilizing a stripline transmission for low-temperature sensing. The sensor exploits the temperature-sensitive properties of dielectric materials, enabling precise detection of frequency shifts correlated with temperature variations. The innovatively designed sensor is feasible for low and sub-zero temperature measurement owing to its linear sensitivity and stable, repeatable measurements.
Author: N. Bhavana, Mallikarjun M. Kodabagi, B. Muthu Kumar, P. Ajay; N. Muthukumaran, A. Ahilan
Published in: IEEE Sensors Journal (Volume: 24, Issue: 15, August 2024)
Summary Contributed by: Anupama
Road potholes pose significant risks to road safety and infrastructure. POT-YOLO is a novel real-time detection system combining edge segmentation with the You Look Only Once (YOLOv8) architecture. This innovative approach improves pothole localization by accurately identifying their contours. POT-YOLO demonstrates exceptional performance, ensuring accurate and efficient detection even in challenging conditions. Its real-time capabilities allow for deployment on edge devices, facilitating proactive maintenance and improving road safety.
Analysis and Design of Biplanar Coils Within Magnetic Shielding Room Considering Actual Ferromagnetic Boundaries
Author: Xu Xueping, Liu Yi, Sun Xin, Zhou Weiyong
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Xu Xueping (Author)
Studying the coupling relationship between the magnetic shield and coil is crucial for designing a magnetic field coil with high uniformity. This paper presents a novel method for designing high-uniformity biplanar coils inside a closed magnetic shielding room with ferromagnetic boundaries. The approach accounts for the permeability and thickness of the magnetic shielding materials to effectively improve the uniformity of the coil, which is important for achieving a near-zero magnetic field environment.
High-Sensitivity of Self-Powered Gas Sensors Based on Piezoelectric Nanogenerators With Y-Doped 1-D ZnO Nanostructures
Author: Ji Liang-wen, Chu Tung-Te, Chu Yen-Lin, Xie Jun-Hong
Published in: IEEE Sensors Journal (Volume: 24, Issue: 12, June 2024)
Summary Contributed by: Saurabh Dubey
Self-powering sensors will make the sensing devices portable. This study explores a self-powered gas sensor using Yttrium-doped zinc oxide (Y-doped ZnO) nanorod arrays and piezoelectric nanogenerators (PENGs). The sensor demonstrated self-powering capability, offering portability and energy efficiency. It exhibits superior sensitivity to carbon monoxide (CO) compared to conventional sensors. The advantages include portability, improved gas adsorption and functionality, facilitating integration into the IoT systems, and wearable sensors for real-time environmental monitoring.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Tobias Gnos (Author)
Vertical Hall Devices (VHD) offer a way for accurate low-cost angular position sensing. In-plane stresses on the silicon die caused by packaging or external forces challenge the increasing accuracy requirements in the automotive and automation industry over a wide temperature range. The study presents a novel active stress compensation method to increase the accuracy of angle measurements in CMOS-integrated VHD’s. The approach is particularly beneficial for applications requiring high-accuracy magnetic field sensing.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Saurabh Dubey
Contact scanning probes may have issues of reduced accuracy due to high speed and high frequency. This paper presents the innovative contact scanning probe, utilizing dual-parameter feedback to optimize pole configuration. It enhances accuracy by correcting high-speed and high-frequency errors with real-time accuracy and dynamic compensation. The approach aims to improve measurement accuracy and stability in high-speed scanning systems. It has promising potential in precision manufacturing, nanotechnology, and medical fields.
From Simulation to Surgery: Comprehensive Validation of an Optical Sensor for Monitoring Focal Laser Ablation of Solid Organ Tumors
Author: Geoghegan Rory, Hughes Griffith, Marks Leonard, Natarajan Shyam, Priester Alan, Sisk Anthony, Sun Songping, Tirado Richard
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Rory Geoghegan (Author)
Focal laser ablation (FLA) is a minimally invasive procedure using thermal coagulation to treat tumors with fewer side effects than surgery. However, it lacks an accurate and affordable monitoring method. This paper presents an optical sensor for real-time monitoring of the ablation process. The sensor has been validated through simulations, ex vivo, and clinical studies and can detect the coagulation boundary precisely without tissue-specific calibration.
Exploring and Identifying Bias-Instability Noise Sources in Mode-Split MEMS Gyroscopes Based on Electrostatic Frequency Tuning
Author: Jie Lin, Yang Zhao, Guoming Xia, Qin Shi, Anping Qiu
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Kamalesh Tripathy
MEMS gyroscope has advanced with the advancements in processing and manufacturing technology. However, their structure and system-based noise level continue to pose challenges in proper implementation and restrict their performance with high accuracy and precision. This paper proposes a system-level noise model that analyzes the relationship between frequency split and noise performance. It identifies noise sources and contributes to bias instability, establishing a frequency-tuning criterion for different noise requirements.
Conventional electronic substrates offer stability and reliability. However, they significantly contribute to electronic waste (e-waste). This study explores stone-based substrates, ranging from natural raw stone to stone paper, as sustainable alternatives for high-performance thin-film temperature sensors. Integrating biodegradable zinc (Zn)-based resistance temperature detectors (RTDs) and amorphous InGaZnO (IGZO)-based thermistors pave the way for dissolvable sensors and reusable substrates, thus leading to less harmful e-waste and advancing eco-friendly electronics.
EV-Fusion: A Novel Infrared and Low-Light Color Visible Image Fusion Network Integrating Unsupervised Visible Image Enhancement
Author: Wang Xia, Sun Qiyang, Yan Changda, Zhang Xin
Published in: IEEE Sensors Journal (Volume: 24, Issue: 4, February 2024)
Summary Contributed by: Saurabh Dubey
EV-Fusion is an innovative technology for low-light visibility applications. It enhances infrared and color images, surpassing nine leading methods in visual fidelity, brightness, and spatial frequency. Its real-time, high-contrast fusion capabilities show promise for military surveillance and traffic security, ensuring visibility of critical details in low-light conditions. Built on a Swin Local-Global Block framework, it utilizes color visible image enhancement and intensity image fusion modules to enhance texture and overall image quality.
Classification Strategies for Radar-Based Continuous Human Activity Recognition With Multiple Inputs and Multilabel Output
Author: Ingrid Ullmann, Ronny G. Guendel, Nicolas Christian Kruse, Francesco Fioranelli, Alexander Yarovoy
Published in: IEEE Sensors Journal (Volume: 24, Issue: 24, December 2024)
Summary Contributed by: Ullmann Ingrid (Author)
Fall detection systems can support independent living for people prone to falls. This paper introduces a novel approach using a radar-based continuous human activity recognition(HAR) system to study different activities by processing radar data in segments and using multilabel classification to recognize activities. The study explores deep learning methods, sensor networks, radar data types, and classification settings to enhance the effectiveness of accurate real-time activity recognition and detecting falls.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Saurabh Dubey
A breakthrough in PbSe thin-film transverse thermoelectric (TTE) photodetectors enhances sensitivity by adding 15-µm graphite coatings with light-trapping structures. This innovation improves photothermal conversion and sensitive light absorption, achieving a detection sensitivity of 415 µV cm/W, five times higher than traditional uncoated films. The increased efficiency positions this sensor as an advanced self-powered, ultrabroadband photodetector with future thermal sensor applications across various fields, ranging from ultraviolet to far-infrared wavelengths.
A Novel Plasmonic Nanoantenna-Based Sensor for Illicit Materials and Drugs Detection
Author: Marco Scalici, Patrizia Livreri
Published in: IEEE Sensors Journal (Volume: 24, Issue: 17, September 2024)
Summary Contributed by: Patrizia Livreri (Author)
The advancements in terahertz(THz) radiation have opened avenues for potential applications in the security and defense sectors. This paper introduces novel plasmonic nanoantennas-based sensors for detecting illicit materials and drugs through terahertz (THz) spectroscopy. Two innovative designs, the butterfly and shamrock nanoantennas, offer high sensitivity across specific THz frequencies. Their combined performance enables accurate, non-destructive molecular identification, providing an advanced tool for security, biomedical, and environmental applications.
Displacement Sensitivity and Range Enhancement Through Buckled Beam-Assisted OE-HCCR
Author: Qi Zhang, Yizheng Chen, Zhuo Li, Yan Tang, Yun Liang, Yi Huang, Xiaobei Zhang
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Kamalesh Tripathy
Displacement measurement sensitivity has broad industrial, scientific and construction applications. The paper proposes an ultrasensitive and wide-range displacement sensor using an open-ended hollow coaxial cable resonator (OE-HCCR) assisted by a buckled beam. The integration of buckled beams enhances sensitivity and extends the measurement range. The sensor demonstrates significant improvements in signal-to-noise ratio and accuracy. The developed system will contribute to advancing micro-scale and nano-scale displacement technology.
Monitoring of Lactococcus Lactis Growth Based on Reduced-Graphene Oxide TFT for Dairy Industry Applications
Author: L. Franchin, S. Casalini, A. Cester; A. Paccagnella, S. Bonaldo
Published in: IEEE Sensors Journal (Volume: 24, Issue: 17, September 2024)
Summary Contributed by: Franchin Lara (Author)
The biological activity of Lactococcus lactis (L. lactis) affects milk fermentation. This paper explores reduced-graphene oxide thin-film (rGO-TFT) to develop an effective biosensor, based on the field-effect transistor, for monitoring bacteria proliferation in dairy plants. This biosensor offers a real-time, highly sensitive, reliable, and non-invasive method to assess fermentation processes by detecting changes in electrical properties as bacterial populations grow, thus enabling precise bacterial growth monitoring in the dairy industry.
Deep Neural Network-Assisted Terahertz Metasurface Sensors for the Detection of Lung Cancer Biomarkers
Author: Hu Fangrong, Su An, Yang Mo, Chen Jie, Lin Shangjun, Ma Xiaoya
Published in: IEEE Sensors Journal (Volume: 24, Issue: 10, May 2024)
Summary Contributed by: Saurabh Dubey
Terahertz (THz) metasurface sensing technology, combined with deep neural networks (DNNs), offers an innovative method for detecting lung cancer biomarkers, including miRNA-21, miRNA-92a, and miRNA-339-3p. This integrated system achieved a classification accuracy of 97.22% for miRNA-21, showcasing its effectiveness as a low-energy, label-free solution for early cancer detection. It demonstrates significant advantages over traditional methods for real-time clinical applications, facilitating rapid diagnosis and monitoring of lung cancer.
Self-Powered and Cost-Effective Wireless Sensor Node for Air Quality Monitoring With an Optically Transparent Smart Antenna System
Author: Maria Bermudez Arboleda, Atif Shamim
Published in: IEEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Maria Bermudez Arboleda (Author)
Air quality monitoring is crucial for the environment and public health. However, traditional air quality monitoring systems are bulky, costly, and challenging to install. To overcome these shortcomings, this study introduces a compact, self-powered sensor node with optically transparent, reconfigurable antennas and modular solar panels. Its innovative design enables 80% size reduction. Equipped with comprehensive pollutant detectors, easy deployment of these cost-effective sensors enables high-resolution monitoring, previously unattainable with traditional systems.
Design and Output Voltage Model of Folding Magnetized Electronic Skin for Intelligent Manipulator
Author: Guoheng Lin, Ling Weng; Hui Zhang, Yang Liu, Yuxin Chen, Zhuolin Li
Published in: EEE Sensors Journal (Volume: 24, Issue: 18, September 2024)
Summary Contributed by: Payal Savani
Flexible electronic skin (e-skin) broadens the application of tactile sensing and flexible sensor technology. The paper presents the design and modeling of a folding magnetized electronic skin with advanced multilayer designs and mathematical modeling for intelligent manipulators. It also combines flexible electronics and magnetic sensing for enhanced flexibility and precision. This e-skin boosts robotics performance in complex tasks requiring precise object handling and interaction by providing tactile and spatial awareness.
A Self-Calibration Method for Engineering Using 3-D Laser Scanning System Based on Cube Vertices
Author: Hongqiang Chen, Ruiheng Xia, Yi Zhang, Hua Deng, Kejun Li
Published in: IEEE Sensors Journal (Volume: 24, Issue: 3, February 2024)
Summary Contributed by: Yi Zhang (Author)
To meet the rapid calibration needs of engineering sites, a novel self-calibration technique is proposed for 3D scanners using 2D light detection and ranging (LiDAR) and a rotating platform. The calibration process uses a cube of known size as the calibration object, ensuring a straightforward process with no additional equipment. This approach addresses the limitations of shape-based calibration, enabling efficient on-site calibration and accurate measurements for most engineering applications.
A Multi-Sensor Tactile System Based on Fiber Bragg Grating Sensors for Soft Tissue Palpation
Author: M. Pulcinelli, L. Zoboli, F. De Tommasi, C. Massaroni, V. Altomare, A. Grasso, A. Gizzi, E. Schena, D. Lo Presti
Published in: IEEE Sensors Journal (Volume: 24, Issue: 16, August 2024)
Summary Contributed by: Saurabh Dubey
Diagnostic tissue palpitation is a common clinical practice to detect soft tissue tumors. This paper presents an innovative multi-sensor tactile system based on Fiber Bragg Grating sensors for non-invasive soft tissue palpation. It improves diagnostic accuracy with enhanced spatial resolution, reduced probe size, and minimized crosstalk errors. The simple and non-invasive tool is effective for soft tissue cancer and tumor detection, with the future potential for automated detection.
Two-port MEMS (Micro-Electro-Mechanical Systems) microphones offer better directional sensitivity than one-port designs but may be more affected by vibrations. The paper presents a simple universal expression for the vibration sensitivity of two-port MEMS microphones. It analytically and experimentally demonstrates that the vibration sensitivity of two-port MEMS mics is independent of their natural frequency (i.e., their stiffness) and is inversely proportional to frequency. Experimental results confirm these findings across various microphone designs.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 13, July 2024)
Summary Contributed by: Anupama
An integrated sensing and communication (ISAC) system combines communication and radar sensing functions to optimize resource utilization. This paper has developed a hybrid analog-digital beamforming method for multi-user, multi-beam ISAC scenarios. The approach prioritizes communication performance through iterative optimization of digital and analog precoders while ensuring effective radar sensing. The proposed algorithm enhances cost, power and spectrum efficiency, and performance, making it ideal for next-generation communication systems.
The increasing threat of harmful algal blooms necessitates affordable and accessible water quality monitoring. This research presents a low-cost, portable, Internet of Thing (IoT)-enabled fluorometer-nephelometer for measuring key water quality parameters. This open-source, customizable system can be adapted to various applications, from single-point measurements to distributed networks. By adjusting sensitivity and adding components, it can monitor diverse aquatic environments, aiding in the research and management of marine ecosystems.
YOLOX-SAR: High-Precision Object Detection System Based on Visible and Infrared Sensors for SAR Remote Sensing
Author: Qiang Guo, Jianing Liu, Mykola Kaliuzhnyi
Published in: IEEE Sensors Journal (Volume: 22, Issue: 17, September 2022)
Summary Contributed by: Saurabh Dubey
Object detection using Synthetic Aperture Radar (SAR) sensors is significant in artificial intelligence, signal processing, radar imaging, and image processing. However, complex electromagnetic scattering backgrounds create challenges in accurate detection. The paper proposes the state-of-the-art YOLOX-SAR system, built upon the YOLOX architecture with advanced features and techniques for precise SAR image object detection. Incorporating technological advancements such as Meta-ACON and CBAM promises improved accuracy and robustness of SAR image object detection.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 17, September 2024)
Summary Contributed by: Weileun Fang (Author)
The pandemic created the demand for a suitable alternative to lab tests to quickly detect antibodies with high precision. This paper presents a fast, sensitive, and accurate new system to detect COVID-19 neutralizing antibodies using optical spectroscopy and hybrid machine learning. The method evaluates immunity by detecting antibodies that block virus-receptor interactions, thus effectively monitoring vaccine efficacy and immune responses. Its high accuracy and scalability make it suitable for diagnostic and research applications.
Machine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things
Author: Maede Zolanvari, Marcio A. Teixeira, Lav Gupta, Khaled M. Khan, Raj Jain
Published in: IEEE Internet of Things Journal (Volume: 6, Issue: 4, August 2019)
Summary Contributed by: Anupama
A cyberattack on the Industrial Internet of Things (IIoT) could have devastating consequences. The researchers have conducted a detailed assessment of existing IIoT protocols for cyber vulnerability. The case study demonstrates the effectiveness of the proposed machine learning (ML)-based intrusion detection system (IDS) against cyberattacks. An in-house developed testbed simulated real-world IIoT scenarios and potential cyberattacks to evaluate the performance of the proposed ML-based system.
Single-Channel DoA Estimation Based on Nonuniform Time-Modulated Array With Asynchronous Sampling
Author: Li Long, Han Jiaqi, Liu Gong-Xu, Mu Yajie, Shi Yan, Wang Xin, Xia Dexiao
Published in: IEEE Sensors Journal (Volume: 24, Issue: 14, July 2024)
Summary Contributed by: Long Li (Author)
Direction-of-arrival (DoA) is essential for accurate target positioning and is important in wireless communication, radar detection, satellite navigation, etc. This paper introduces a single-channel direction-of-arrival (DoA) estimation method using a nonuniform time-modulated array (NTMA) with asynchronous sampling. The technique reduces hardware complexity and improves estimation accuracy using a single-channel receiver and an optimized modulation scheme. The results demonstrate the system's effectiveness, especially in applications with limited resources and where synchronous sampling is challenging.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 14, July 2022)
Summary Contributed by: Payal Savani
Rice, a Global staple, is often plagued by various diseases that impact crop production. The challenge of identifying these diseases exacerbates the issue. While deep learning is a powerful tool in image processing and computer vision, its application in plant disease recognition has been restricted. This paper introduces MobInc-Net, a lightweight Inception network that recognizes and detects rice plant diseases. It offers a practical solution that achieves high accuracy even in challenging conditions.
Self-Driven Photodetectors Based on Flexible Silicon Nanowires Array Surface-Passivated With Tin-Based Perovskites
Author: Yang Shengyi, Ge Zhenhua, Jiang Yurong, Wang Ying, Xin Haiyuan, Zhang Zhenheng, Zou Bingsuo
Published in: IEEE Sensors Journal (Volume: 24, Issue: 14, July 2024)
Summary Contributed by: Shengyi Yang (Author)
Silicon nanowire (Si-NW) photodetectors show great potential as efficient, self-driven, and compact devices in optoelectronic applications. However, their intrinsic surface defects reduce their responsivity and specific detectivity, limiting their performance. This paper introduces a novel self-driven photodetector based on flexible silicon nanowires array surface passivated with tin-based perovskites (FASnBr₃). The innovative design significantly enhances device performance and flexibility, making it a promising candidate for next-generation photodetectors.
Published in: IEEE Sensors Journal (Volume: 23, Issue: 3, February 2023)
Summary Contributed by: Saurabh Dubey
Anomalies between trains and platform doors threaten intercity railway safety. The paper proposes a method for anomaly detection using train predeparture key frame extraction and an Image-inpainting Anomaly Detection Network (IADN) based on image-inpainting autoencoder (AE) and local abnormal information enhancement and global-attentive reconstruction error (GARE). The tested results show effective and accurate anomaly detection, even outperforming state-of-the-art methods, ensuring safety with potential applications in security and locomotive industries.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 15, August 2024)
Summary Contributed by: Nhien-An Le-Khac (Author)
Human activity recognition (HAR) using multiple sensors offers higher accuracy but raises privacy and convenience issues, while single sensors often lack detail and accuracy. The paper proposes Virtual Fusion with Contrastive Learning (VFCL), a novel framework for single-sensor-based activity recognition. Virtual fusion uses data from multiple sensors across different modalities for training but requires only one for predictions, while contrastive learning improves the accuracy and performance of each sensor independently.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 13, July 2022)
Summary Contributed by: Saurabh Dubey
Early detection of breast cancer saves lives. The research presents a novel and adaptable breast cancer detection system integrating dual-polarized Ultra-Wideband (UWB) antennas on flexible Kapton polyimide, ensuring high precision. Eight UWB units surround the breast phantom and reconstruct 3D images using a delay-and-sum (DAS) algorithm to locate tumors with minimal clutter. Wearable and versatile, it can detect tumors with a 15 mm edge-to-edge distance, offering convenient health monitoring and self-diagnosis.
Design, Fabrication, and Validation of a Flexible Tactile Sensor for a Hand Prosthesis
Author: Kuo Chung-hsien, Nguyen Dai-Dong, Su Shun-Feng, Xie Wu-Qi
Published in: IEEE Sensors Journal (Volume: 24, Issue: 16, March 2024)
Summary Contributed by: Chung-Hsien Kuo (Author)
The design of a flexible tactile sensor using liquid metal (LM) and elastic fibers provides sensing capability and enhances the performance of a hand prosthesis. This study details the measurement principles of the LM-based force sensor, the design and fabrication process, and the sensor signal processing circuit. The proposed flexible tactile sensor offers reliable performance with high sensitivity in three axes, low error, and improved functionality in hand prostheses.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 17, September 2022)
Summary Contributed by: Payal Savani
In our technology-driven world, devices require quick and efficient data processing. Edge computing enables rapid local decision-making, preserving bandwidth and privacy. Understanding platform intricacies is crucial for informed decision-making while navigating through vast data. The paper explores innovative approaches and experimental findings, providing insights into Deep Neural Networks (DNNs) architecture performance across diverse edge technologies. This aids in selecting optimal architectures based on performance metrics for specific applications.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 13, July 2024)
Summary Contributed by: Arantxa Uranga (Author)
Hydrophones are devices that convert underwater acoustic pressure into electrical signals. The paper proposes a hydrophone designed using Aluminum Scandium Nitride (AlScN) piezoelectric micromachined ultrasonic transducers (PMUTs) integrated monolithically on CMOS (Complementary Metal-Oxide-Semiconductor). This single-chip AIScN PMUTs with COMS (PMUTs-on-CMOS) hydrophone offers compactness, high sensitivity, and energy efficiency for underwater acoustic sensing. It supports high-performance underwater detection and has promising applications in underwater communications, sonar, and environmental monitoring systems.
A Retail Object Classification Method Using Multiple Cameras for Vision-Based Unmanned Kiosks
Author: Ji-Ye Jeon, Shin-Woo Kang, Hyuk-Jae Lee, Jin-Sung Kim
Published in: IEEE Sensors Journal (Volume: 22, Issue: 22, November 2022)
Summary Contributed by: Saurabh Dubey
Sensor technology, wireless communications, and Internet of Things (IoT) use in unmanned self-checkout systems has elevated the retail experience. This paper presents a vision-based RGB kiosk using a sophisticated combination of multiple cameras and a cutting-edge Convolutional Neural Network (CNN) framework, yielding a 33.67% improvement over conventional methods. It solves inter-classification challenges and intra-class variations in products with 142k+ real-world dataset points, with promising applications in retail and lifestyle sectors.
TSSTDet: Transformation-Based 3-D Object Detection via a Spatial Shape Transformer
Author: Yoo Myungsik, Bui Cuong Duy, Hoang Hiep Anh
Published in: IEEE Sensors Journal (Volume: 24, Issue: 5, March 2024)
Summary Contributed by: Myungsik Yoo (Author)
Accurate 3D object detection is essential for the safe navigation of autonomous vehicles. The novel transformation-based 3-D object detection via a spatial shape transformer (TSSTDet) overcomes the challenges of incomplete and varying orientations of the obstructions. Its key features include a rotational transformation convolutional backbone (RTConv) for orientation-invariant detection and a voxel-point shape transformer for reconstructing missing parts, thus improving obstacle detection and avoidance and enhancing safe navigation in autonomous driving.
Camera-Augmented Non-Contact Vital Sign Monitoring in Real Time
Author: Arash Shokouhmand, Samuel Eckstrom, Behnood Gholami, Negar Tavassolian
Published in: EEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Payal Savani
Vital signs, such as heart rate (HR) and respiratory rates (RR), are crucial for patients' health assessment. Technological advancements have led to non-contact monitoring using cameras and radars. This paper introduces a camera-guided frequency-modulated continuous-wave (FMCW) radar system for real-time non-contact vital sign monitoring. The novel singular value-based point detection (SVPD) method is designed to optimize respiratory and heart rate monitoring. Experiments show high accuracy and effective vital signs monitoring.
Environment mapping is a key component in assisted and autonomous driving. This paper introduces a method to generate 2D occupancy maps using light detection and ranging (LiDAR) and radar data, leveraging their clustered, sparse nature. It presents a linear sensor measurement model and pattern-coupled sparse Bayesian learning approach for occupancy map estimation. Tested with real-world data highlighting the methods, it shows superior performance in detecting obstacles.
A Fully Flexible Hydrogel Electrode for Daily EEG Monitoring
Author: Gencai Shen, Kunpeng Gao, Nan Zhao, Zhuangzhuang Wang, Chunpeng Jiang, Jingquan Liu
Published in: IEEE Sensors Journal (Volume: 22, Issue: 13, July 2022)
Summary Contributed by: Saurabh Dubey
The study explores fully flexible hydrogel electrodes for daily monitoring of electroencephalogram (EEG) Signals. Synthesized through a NAGA (n-acryloyl glycinamide) hydrogel enriched with glycerol, these electrodes exhibit enhanced skin conductivity compared to dry and semi-dry electrodes. With stable signal monitoring, 70% deformation tolerance, and 90-day durability, these electrodes prove ideal for daily EEG monitoring, aiding brain activity monitoring applications in Brain Computer Interface studies based on data analysis algorithms.
Glyphosate Detection Through Piezoelectric and Fiber Optic Sensors Based on Molecular Imprinted Polymers
Author: Sequeira Filipa, Bilro Lucia, Gomes Maria Teresa S. R., Oliveira Ricardo, Reis Silvia, Rudnitskaya Alisa, Verissimo Marta
Published in: IEEE Sensors Journal (Volume: 24, Issue: 13, July 2024)
Summary Contributed by: Sequeira Filipa (Author)
Glyphosate is a harmful herbicide often detected in soil and groundwater. The study demonstrates the proof of concept of a portable “sensing pen” for glyphosate detection using sensors with molecularly imprinted polymers (MIPs). MIPs are engineered to bind glyphosate to enhance detection accuracy. The sensors combine piezoelectric and fiber optic technologies to achieve high sensitivity and specificity. These sensors can rapidly detect glyphosate, offering a cost-effective and reliable solution for environmental monitoring.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 24, December 2022)
Summary Contributed by: Payal Savani
Ammonia (NH3), a vital environmental gas, is hazardous to health. Traditional methods to detect ammonia are slow and expensive. The study investigates the sensitivity, selectivity, and optimal operating conditions of Tungsten disulfide (WS2)-based gas sensors. Using materials like WS2 offers fast and effective detection methods, highlighting their strong response to ammonia, selectivity against other gasses, and improved efficiency under light illumination, offering valuable insights for developing more efficient gas detection technologies.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 4, February 2024)
Summary Contributed by: Zhang Kehua (Author)
Simultaneous Localization and Mapping (SLAM) is essential for robots navigating new environments. DN-SLAM is a novel SLAM system designed to navigate dynamic environments. It integrates ORB (Oriented FAST and Rotated BRIEF) features for robust extraction and neural radiance fields (NeRF) for high-quality 3D representation to accurately estimate trajectory in dynamic environments. Its enhanced real-time tracking and dense mapping in dynamic scenes make it a promising solution for various robotics applications.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 11, June 2022)
Summary Contributed by: Saurabh Dubey
The Interdigital Capacitive sensor integrated with CPW (Coplanar Waveguide) feeding is economical and effective for measuring soil moisture, air humidity, and liquid levels. Coated with a Polyvinyl Alcohol layer, it maintains linearity for soil moisture and is reliable for liquid-level detection. Tested at 915 MHz, it exhibits high sensitivity. With low power consumption and reliability, it finds application across diverse fields like agriculture, oil, and medical equipment.
Low Cost, Flexible, Room Temperature Gas Sensor: Polypyrrole-Modified Laser-Induced Graphene for Ammonia Detection
Author: Salehnia Foad, Vilanova X., Llobet Eduard, Romero Nevado Alfonso Jose, Santos Ceballos Jose Carlos
Published in: IEEE Sensors Journal (Volume: 24, Issue: 7, April 2024)
Summary Contributed by: Salehnia Foad (Author)
The hazardous nature of ammonia (NH3) makes its monitoring crucial. The paper presents a novel, low-cost, and flexible ammonia gas sensor using polypyrrole-modified laser-induced graphene (PPy@LIG) developed for real-time monitoring and detection of ammonia in atmosphere. It demonstrates enhanced sensitivity, excellent repeatability, and a low detection limit of 1 ppm at room temperature. This breakthrough opens opportunities for advanced air quality monitoring systems and potential applications in agriculture and industrial settings.
Fabrication and Characterization of P3HT/MoS₂ Thin-Film Based Ammonia Sensor Operated at Room Temperature
Author: Ankit Verma, Praveen Kumar Sahu, Vivek Chaudhary, Arun Kumar Singh, V. N. Mishra, Rajiv Prakash
Published in: IEEE Sensors Journal (Volume: 22, Issue: 11, June 2022)
Summary Contributed by: Anupama
The study presents a high-performance ammonia gas sensor using poly(3-hexylthiophene)/molybdenum disulfide (P3HT/MoS2) nanocomposite in a top-contact organic field-effect transistor (OFET) assembly. The P3HT/MoS2 surface, with superior crystallinity and extended nanofiber morphology, improves charge interaction and transport with ammonia, yielding a gas sensor response of 63.45% at 100 ppm ammonia concentration. The fabricated OFET showcases high efficiency, sensitivity, and non-invasiveness, demonstrating significant potential for environmental protection as an ammonia gas sensor.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 7, April 2024)
Summary Contributed by: Kaziz Sameh (Author)
Advanced computational models like artificial neural networks (ANN) and particle swarm optimization with artificial neural networks (PSO-ANN) are revolutionizing the prediction of microfluidic biosensor performance. They predict detection times based on critical input variables and identify optimal conditions for enhanced biosensor performance by systematically varying key parameters. Machine learning (ML) algorithms analyze the data to predict outcomes and improve detection accuracy. The findings promise advancements in biosensor technology across diverse applications.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 20, October 2022)
Summary Contributed by: Saurabh Dubey
The advancements in human-computer interaction (HCI) have proved effective in training machines and fostered research in automatic emotion recognition. Convolutional neural networks (CNNs) have shown promising results in electroencephalogram (EEG)-based emotion recognition. The study investigates electroencephalogram (EEG) based signals for precise emotional recognition trained over novel and effective Convolutional Neural Networks (CNN) and Contrastive Learning methods. This technology holds promise for future applications in emotional understanding and mental health monitoring.
Development of Flexible Electronic Biosensors for Healthcare Engineering
Author: Yan Jian, Yan Jiasheng, Cheng Jie, Fu Yusheng, Guo Jinhong, Zhao Ying, Zhou Jun
Published in: IEEE Sensors Journal (Volume: 24, Issue: 8, April 2024)
Summary Contributed by: Jian Yan (Author)
With the potential for real-time health monitoring and personalized diagnosis, wearable biosensors are the future of the healthcare system. The portability and stretchability of flexible electronics allow them to substitute bulky diagnostic devices with wearable devices, thus creating possibilities for non-invasive continuous health monitoring. These biosensors convert physiological data into interpretable information by integrating innovative sensing mechanisms and designs, enabling healthcare professionals to detect warning signs, diagnose diseases, and assess health accurately.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 17, September 2022)
Summary Contributed by: Anupama
The paper explores the impact of Earth rotation compensation on the microelectromechanical systems-based inertial measurement units (MEMS-IMU) preintegration in navigation system accuracy. Experimental evaluations reveal substantial accuracy degradation without Earth rotation compensation and highlight the transformative potential of refined IMU preintegration in achieving high accuracy. The proposed advanced navigation system integrates global navigation satellite system positioning (GNSS) with IMU preintegration through Factor Graph Optimization, offering a promising avenue for enhanced accuracy and robustness in navigation systems.
Published in: IEEE Sensors Journal (Volume: 24, Issue: 9, May 2024)
Summary Contributed by: Palma Lorenzo (Author)
Accidental falls across age groups and occupations could affect the quality of life. This work presents an innovative deep-learning approach specifically designed for edge devices for fall detection. The wearable sensor combines a three-axis accelerometer, gyroscope, and pressure sensor. It operates in real-time, recognizing the actions performed and categorizing them as everyday activities or falls. The power-efficient, low-cost, simple model with 99.38% accuracy and 25ms inference time is practical for real-world applications.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Saurabh Dubey
Indoor localization based on WiFi Fingerprint techniques, augmented with the proposed FASR (Fingerprint Augment Based on Super-Resolution) framework, demonstrates increased localization accuracy and cost-effectiveness. The study explores the processing of the FASR framework and its super-resolution attributes in multiple modules. Assisted by deep neural network learning models, the framework shows consistent performance across various spatial samples with high position accuracy and promising application in the field of image processing.
Published in: IEEE Sensors Journal (Volume: 23, Issue: 4, February 2023)
Summary Contributed by: Kamalesh Tripathy
Maintaining indoor air quality (IAQ) is crucial for health and wellness. Accurate data analysis and contextual anomaly detection are essential for IAQ monitoring. The paper introduces a hybrid deep-learning model, combining long short-term memory (LSTM) with autoencoder (AE). LSTM learns typical carbon dioxide (CO2) time sequence patterns, while AE computes optimal reconstruction errors and detects anomalies. Achieving 99.50% accuracy in real-world testing, the model shows promise for enhancing IAQ monitoring.
3-D-Printing and Reliability Evaluation of an Easy-to-Fabricate Position Sensing System for Printed Functional Wearable Assistive Devices
Author: Michalec Paweł, Faller Lisa-Marie
Published in: IEEE Sensors Journal (Volume: 24, Issue: 4, February 2024)
Summary Contributed by: Michalec Paweł (Author)
The demand for advanced medical devices has created challenges in integrating sensors into cost-effective wearable medical assistive devices. The paper presents a novel, fully 3D-printed linear encoder developed using commercially available electrically conductive and nonconductive materials. This easy-to-fabricate technology was tested in a sensorized hand orthosis (sHO). It aims to enhance the functionality of wearable assistive devices by accurately detecting and monitoring movements, thus offering promising solutions for rehabilitation devices.
CAMs-SLAM: Cloud-Based Multisubmap VSLAM for Multisource Asynchronous Sensing of Biped Climbing Robots
Author: Zhang Hong, Chen Weinan, Gu Shichao, Zhu Lei
Published in: IEEE Sensors Journal (Volume: 24, Issue: 14, July 2024)
Summary Contributed by: Hong Zhang (Author)
Understanding and navigating the surroundings is a key feature of biomimetic Biped climbing robots (BiCRs). This is achieved through visual simultaneous localization and mapping (VSLAM). The paper presents a cloud-based asynchronous multisubmap VSLAM (CAMs-SLAM) system, which assists these robots with necessary computing, mapping, environment perception, and autonomous navigation. Even with weak internet connections and low data, this system demonstrates its feasibility and superiority in autonomous climbing applications, offering practical benefits for real-world use.
TSF: Two-Stage Sequential Fusion for 3D Object Detection
Author: Heng Qi, Peicheng Shi, Zhiqiang Liu, Aixi Yang
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Anupama
This paper introduces a two-stage sequential fusion (TSF) method for 3D object detection in autonomous driving. TSF fuses the raw LiDAR point cloud with corresponding image data to produce an improved point cloud. The study also analyzes the impact of the fusion module on detection capabilities and explores the balance between accuracy and speed. The results show that TSF substantially boosts LiDAR detection accuracy, especially in small-object detection.
GPS-based navigation, widely used worldwide, is cost-effective for providing position, velocity, and time data. However, it is susceptible to spoofing, especially in UAVs (unmanned aerial vehicles). The paper proposes a GPS spoofing detection and mitigation method using distributed radar tracking and data fusion techniques. The approach combines primary and secondary data through extended Kalman filters and track-to-track association. It ensures accuracy even during spoofing attacks, making it ideal for drone swarms.
Published in: IEEE Sensors Journal ( Volume: 22, Issue: 10, May 2022)
Summary Contributed by: Kamalesh Tripathy
Micro-Electro-Mechanical-Systems (MEMS) based piezoresistive pressure sensors are widely used across various industries. However, these sensors are prone to failure due to junction leakage at high-temperature applications. The paper presents three piezoresistive pressure sensors designed using different technologies: standard diffused piezoresistors, oxide-isolated polysilicon, and single crystal silicon piezoresistors. Tested up to 200°C and 140 bar, all sensors showed reduced sensitivity with temperature, with oxide-isolated polysilicon sensors exhibiting the best performance.
Fetal Movement Detection by Wearable Accelerometer Duo Based on Machine Learning
Author: Jingyi Xu, Chao Zhao, Bo Ding, Xiaoxia Gu, Wenru Zeng, Liang Qiu, Hong Yu, Yang Shen, Hong Liu
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Chao Zhao (Author)
Fetal movement monitoring is vital for fetal health. The accuracy of the maternal perception in monitoring fetal movement varies. In this work, a wearable device with two accelerometers and machine learning algorithms was developed for accurate and continuous fetal movement monitoring. It aims for accuracy comparable to ultrasound. The device showed promising results in fetal movement monitoring, potentially providing valuable insights into the fetal biological profile during the perinatal period.
Single Aerosol Particle Detection by Acoustic Impaction
Author: Nadine Karlen, Tobias Rüggeberg, Bradley Visser, Jana Hoffmann, Daniel A. Weiss, Ernest Weingartner
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Saurabh Dubey
Accurate detection of aerosol particles is vital for health and addressing climate risks. The paper discusses DustEar, a state-of-the-art measurement method, which employs an acoustic Piezo transducer to accelerate particles in a nozzle, enabling precise detection of individual aerosol particles up to 15 μm. The design reduces airflow interference and noise levels, ensuring accurate single-particle measurement. It has diverse applications in drug quality control, pollution source analysis, and environmental management.
Estimating Relative Angles Using Two Inertial Measurement Units Without Magnetometers
Author: Seung Yun Song, Yinan Pei, Elizabeth T. Hsiao-Wecksler
Published in: IEEE Sensors Journal (Volume: 22, Issue: 20, October 2022)
Summary Contributed by: Seung Yun Song (Author)
Wearable technology heavily relies on miniature sensors called inertial measurement units (IMU). IMUs are vital for computing body segment angular kinematics in biomechanics and clinical settings. This study presents a low-cost two 6-axis IMU system without magnetometers to estimate relative angles. It validates existing algorithms for 3D orientation computation. The system's user-friendly design and accurate orientation calculation hold promise for advancements in virtual reality, health monitoring, and wearable technologies.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 14, July 2022)
Summary Contributed by: Anupama
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires rapid and accurate detection to control its spread. When COVID-19, a disease caused by the SARS-CoV-2 virus, became a Global pandemic, a novel method for fast identification of the new coronavirus was developed using Surface Plasmon Resonance (SPR) techniques. This paper reviews the potential of SPR-based biosensing chips and sensors for portable devices to rapidly and accurately detect the SARS-CoV-2 virus.
Balanced Adaptation Regularization Based Transfer Learning for Unsupervised Cross-Domain Fault Diagnosis
Author: Qin Hu, Xiaosheng Si, Aisong Qin, Yunrong Lv, Mei Liu
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Qin Hu (Author)
Fault diagnosis technology for rolling bearings is crucial for preventing mechanical accidents. In the field of fault diagnosis, inconsistent data distribution due to variable working conditions hampers diagnostic accuracy. This study proposes a novel method, Balanced Adaptation Regularization-based Transfer Learning (BARTL), leveraging enhanced multi-scale sample entropies. BARTL improves feature discriminability and similarity across conditions, achieving accurate diagnosis and surpassing existing transfer learning methods, as validated by two public datasets.
Deep Transfer Learning With Self-Attention for Industry Sensor Fusion Tasks
Author: Ze Zhang, Michael Farnsworth, Boyang Song, Divya Tiwari, Ashutosh Tiwari
Published in: IEEE Sensors Journal (Volume: 22, Issue: 15, August 2022)
Summary Contributed by: Anupama
The paper introduces a promising approach using deep transfer learning techniques to address the challenges in processing multisource, heterogeneous data in Industry 4.0. By repurposing a Transformer model pre-trained from data-rich natural language domain, the proposed method allows industrial applications to leverage deep learning capabilities with minimal training data requirements. It represents a significant step toward making Industry 4.0 more efficient, faster, and cost effective.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 11, June 2022)
Summary Contributed by: Weiguan Zhang (Author)
In smart control of robots, proximity and pressure information complement each other in detecting objects from approach to contact. Using a simple and cost-effective fabrication method, the researchers developed a textile-based sensor combining magneto-straining (proximity) and piezoresistive modes (pressure). This sensor exhibits high sensitivity for proximity and pressure perception. The unique design offers a seamless transition between modes, making it suitable for applications in human-machine interaction and intelligent prosthetics.
Usage of IR Sensors in the HVAC Systems, Vehicle and Manufacturing Industries: A Review
Author: Muhammad Adeel Altaf, Jongsik Ahn, Danish Khan, Min Young Kim
Published in: IEEE Sensors Journal (Volume: 22, Issue: 10, May 2022)
Summary Contributed by: Kamalesh Tripathy
Thermal sensors are used in various industries to measure temperature and convert it into a readable output. Its selection depends on cost, resolution, and accuracy, which are crucial factors to consider when designing the sensor system. This paper explores the significance of infrared sensors as thermal sensors in detecting temperature, movement, and occupancy. It reviews the use of thermal sensors in HVAC (Heating, ventilation, and air conditioning) systems, vehicles, and manufacturing industries.
Self-Supervised Monocular Depth Estimation Using Hybrid Transformer Encoder
Author: Seung-Jun Hwang, Sung-Jun Park, Joong-Hwan Baek, Byungkyu Kim
Published in: IEEE Sensors Journal (Volume: 22, Issue: 19, October 2022)
Summary Contributed by: Seung-Jun Hwang (Author)
Depth estimation using camera sensors is vital in autonomous driving, robotics, 3D scene reconstruction, and augmented reality. This paper presents a novel method for monocular-camera depth estimation using a hybrid transformer encoder-decoder. The self-supervised view synthesis method used eliminates the need for depth supervision. It uses a cost-volume structure, combining neural network and transformer architectures for accurate depth prediction. The system enhances global feature representation with an attention decoder, improving depth estimation accuracy.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 20, October 2022)
Summary Contributed by: Saurabh Dubey
The CMOS Algae Growth Period Monitor, consisting of an algae sensor and a CMOS converter, is a cutting-edge solution for monitoring algae growth in algaculture applications. It utilizes a proton exchange membrane to translate algae growth data into a duty cycle, facilitating rapid assessment. With increased sensitivity, it functions in suboptimal conditions and has a maximum linear error of only 0.49%. Integration with IoT technology holds potential applications in the advanced monitoring of aquatic life.
Joint Hybrid 3D Beamforming Relying on Sensor-Based Training for Reconfigurable Intelligent Surface Aided TeraHertz-Based Multiuser Massive MIMO Systems
Author: Xufang Wang, Zihuai Lin, Feng Lin, Lajos Hanzo
Published in: IEEE Sensors Journal (Volume: 22, Issue: 14, July 2022)
Summary Contributed by: Zihuai Lin (Author)
The Terahertz (THz) era promises lightning-fast internet but faces challenges like signal degradation over distances. The paper introduces a joint 3D-beamformer for THz Multi-user Massive multiple-input multiple-output (MIMO) systems, leveraging Reconfigurable Intelligent Surfaces to improve signal strength and coverage. The system uses smart sensing to beam signals directly to devices, promising unparalleled speeds and connection stability, even in crowded spaces. Scalable and adaptable, the proposed architecture is the future of connectivity.
OFET and OECT, Two Types of Organic Thin-Film Transistor Used in Glucose and DNA Biosensors: A Review
Author: Xin Ma, Hongquan Chen, Peiwen Zhang, Martin C. Hartel, Xiaona Cao, Sibel Emir Diltemiz, Qinglei Zhang, Javed Iqbal, Natan Roberto de Barros, Liyan Liu, Hao Liu
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Anupama
Diabetes leads to serious health challenges and is a leading cause of numerous chronic diseases. This study explores electronics-based biosensors, particularly Organic Field Effect Transistors (OFET) and Organic Electrochemical Transistors (OECT), as adept glucose and DNA biosensors in diabetes management. The biosensors, fabricated from biodegradable natural materials, offer a flexible, cost-effective, and easily accessible solution, showcasing exceptional sensitivity and selectivity in their performance.
Concentrated Coverage Path Planning Algorithm of UAV Formation for Aerial Photography
Author: Yi Cao, Xianghong Cheng, Jinzhen Mu
Published in: IEEE Sensors Journal (Volume: 22, Issue: 11, June 2022)
Summary Contributed by: Yi Cao (Author)
Ensuring successful aerial photography requires effective coverage path planning for UAVs. However, complexities in outdoor spaces pose challenges, necessitating innovative solutions. This paper introduces a novel concentrated coverage path planning algorithm, revolutionizing traditional probabilistic roadmap methods. Integrating round-trip mode and path constraints optimizes coverage while minimizing computational complexity and repetitions. The approach enhances efficiency and feasibility in real-world environments, promising to redefine aerial photography landscapes.
Real-Time Deep Anomaly Detection Framework for Multivariate Time-Series Data in Industrial IoT
Author: Hussain Nizam, Samra Zafar, Zefeng Lv, Fan Wang, Xiaopeng Hu
Published in: IEEE Sensors Journal (Volume: 22, Issue: 23, December 2022)
Summary Contributed by: Payal Savani
In the realm of smart machines and interconnected devices, the Industrial Internet of Things (IIoT) is ushering in a revolution across industries. Due to a constant stream of diverse and time-stamped data, real-time anomaly detection becomes paramount for industrial process improvement. The article explores a hybrid deep anomaly detection (DAD) model that could accurately identify real-time anomalies. Experimental results showcase its superior performance in terms of accuracy and precision over existing methods.
Deep Learning Approach for Detecting Work-Related Stress Using Multimodal Signals
Author: Wonju Seo, Namho Kim, Cheolsoo Park, Sung-Min Park
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Cheolsoo Park (Author)
Work-related stress should be detected and managed to avoid adverse impacts on individuals and society. This study proposes a deep learning approach to detect work-related stress automatically by analyzing multimodal signals. Deep neural networks, facial expressions, and physiological signals were fused at different levels to achieve promising accuracy. The novel approach of studying the level of work-related stress with just a 10-second-long electrocardiogram, respiration, and facial images shows potential for effective stress detection.
Research on Self-Powered Coded Angle Sensor for Rock Climbing Training
Author: Jun Zhang, Chuan Wu
Published in: IEEE Sensors Journal (Volume: 22, Issue: 18, September 2022)
Summary Contributed by: Payal Savani
Rock climbing is an adventure or competitive sport in which monitoring speed is vital. It is measured using an angle sensor entangled with climbers, causing safety concerns. The self-powered angle sensor offers a practical alternative to conventional rock-climbing sensors. The proposed self-powered coded angle sensors based on a single-electrode triboelectric nanogenerator can accurately measure the rotation angle, direction, and speed in indoor and outdoor climbing, even without a power supply.
Hallway Gait Monitoring Using Novel Radar Signal Processing and Unsupervised Learning
Author: Hajar Abedi, Jennifer Boger, Plinio P. Morita, Alexander Wong, George Shaker
Published in: IEEE Sensors Journal (Volume: 22, Issue: 15, August 2022)
Summary Contributed by: Hajar Abedi (Author)
The novel hallway gait monitoring system developed leveraging radar signal processing and unsupervised machine learning introduces the future of personalized gait monitoring of individuals without wearable devices. It aims to create a system capable of monitoring human gait indoors and in natural settings using radar technology. This breakthrough architecture offers non-invasive and precise monitoring, paving the way for enhanced patient care and personal health insights.
Value of Information in Wireless Sensor Network Applications and the IoT: A Review
Author: Faiga Alawad, Frank Alexander Kraemer
Published in: IEEE Sensors Journal (Volume: 22, Issue: 10, May 2022)
Summary Contributed by: Anupama
The Value of Information (VoI) is crucial in handling large data volumes in the Industrial Internet of Things (IIoT), filtering redundant information, and optimizing data processes. It is a key metric influencing path-planning algorithms, source switching, and trajectory optimization in mobile sensors. The paper systematically reviews VoI definitions, categorizing valuation methods and performance across applications, and provides guidelines for parameterized and adaptable VoI techniques to optimize diverse systems.
Hand gesture recognition has become an integral part of Human-Computer Interactions. The paper introduces a methodology using a video-based dataset and convolutional neural network (CNN) model. It utilizes an RGB-Depth camera to create a dataset of six distinct hand gestures. A lightweight CNN model is then developed to detect and classify hand movements. The experimental results highlight its accuracy and efficiency, facilitating its practical use in scenarios demanding precise gesture recognition.
Non-Enzymatic Glucose Detection Based on GO/Ag Nanocomposite in SiO2 Trench Embedded Field Effect Transistor
Author: Monica Naorem, Roy P. Paily
Published in: IEEE Sensors Journal (Volume: 22, Issue: 16, August 2022)
Summary Contributed by: Saurabh Dubey
SiO2 trench-embedded Field Effect Transistors (FET) with a graphene oxide-silver ( GO/Ag) nanocomposite for non-enzymatic glucose detection are crucial for effective diabetes management by accurately monitoring glucose concentration range of 1 μM to 10 mM. Validated through structural analysis, the fabricated device structure exhibits excellent glucose storage and sensing abilities, ensuring stability, reproducibility, and selectivity. Compact and easy to produce, it has promising applications in portable glucose sensors for point-of-care diagnostics and healthcare.
An EEG Data Processing Approach for Emotion Recognition
Author: Guofa Li, Delin Ouyang, Yufei Yuan, Wenbo Li, Zizheng Guo, Xingda Qu, Paul Green
Published in: IEEE Sensors Journal (Volume: 22, Issue: 11, June 2022)
Summary Contributed by: Yufei Yuan (Author)
Emotion recognition has garnered interest from researchers because of its importance in affective computing. Facial expressions can mask human emotions. However, studies show that electroencephalogram (EEG) signals can recognize and identify human emotions. Hence, EEG has emerged as an alternate method for emotion recognition. The paper proposes a novel approach through a reduced number of EEG electrode channels and a normalization method, demonstrating its promising applications in real-time emotion recognition.
Technologies Driving the Shift to Smart Farming: A Review
Author: Nabila ElBeheiry, Robert S. Balog
Published in: IEEE Sensors Journal (Volume: 23, Issue: 3, February 2023)
Summary Contributed by: Vinay S Palaparthy
Agriculture requires sustainable solutions, especially when facing challenges like climate change, unqualified farmers, and urbanization. Smart farming (SF) helps enhance crop quality and quantity with minimal labor, ensuring sustainable agriculture and consistent food supply to meet the global food demand. This survey includes various themes like sensors, communication, big data, actuators, and data analysis. The article emphasizes integrating multiple technologies, highlighting popular SF systems: remote monitoring, autonomous, and intelligent decision-making.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 15, August 2022)
Summary Contributed by: Satoshi Ikezawa (Author)
Material selection is crucial when designing and fabricating metasurfaces. The metasurface optical element produces a tightly focused beam from a visible laser, thus maximizing light utilization and minimizing energy loss. This study focuses on enhancing metasurface microfabrication precision and achieving remarkable light transmittance through traditionally impermeable silicon, providing opportunities for developing miniature wearable technology, cameras, and augmented reality (AR) devices and has significant implications for micro-scanning within confined spatial domains.
E-Nose System Based on Fourier Series for Gases Identification and Concentration Estimation From Food Spoilage
Author: Jie Luo, Zehao Zhu, Wen Lv, Jian Wu, Jianhua Yang, Min Zeng, Nantao Hu, Yanjie Su, Ruili Liu, Zhi Yang
Published in: IEEE Sensors Journal (Volume: 23, Issue: 4, February 2023)
Summary Contributed by: Leena Jha
Improper and prolonged storage of perishable food items like meat and fruits may lead to microbial contamination and spoilage. The paper presents an electronic nose (EN) system, a portable electronic gas-sensing device comprising a sensor array-based gas identification, concentration estimation system, and data acquisition circuit boards. A machine learning algorithm assists it. It accurately detects gases like ammonia (NH3), hydrogen sulphide (H2S), and ethanol (C2H5OH) emitted by spoiled food.
Monolithic Sensor Integration in CMOS Technologies
Author: Daniel Fernández, Piotr Michalik, Juan Valle, Saoni Banerji, Josep Maria Sánchez-Chiva, Jordi Madrenas
Published in: IEEE Sensors Journal (Volume: 23, Issue: 2, January 2023)
Summary Contributed by: Daniel Fernández (Author)
In the wearable market, where the area is a limiting factor, monolithic sensor integration with mainstream gadget electronics can provide an efficient means to archive a small device footprint while maintaining good performance. For a minimum cost, CMOS-MEMS devices built using backend-of-line (BEOL) interconnections as structural material offer an interesting, cost-effective approach with the potential to become a market game-changer.
An Improved YOLOv5 Crack Detection Method Combined With Transformer
Author: Xuezhi Xiang, Zhiyuan Wang, Yulong Qiao
Published in: IEEE Sensors Journal (Volume: 22, Issue: 14, July 2022)
Summary Contributed by: Kamalesh Tripathy
A robust pavement crack detection network is imperative to mitigate traffic accidents and minimize maintenance costs. The paper proposed an efficient hybrid model by merging YOLOv5 and Transformer, utilizing one-stage architecture and long-range dependency capture for reliable crack detection. The network's performance is further improved using test time augmentation (TTA) for crack detection. An efficient solution for urban pavement damage detection, it paves the way for expanding datasets to tackle diverse pavement issues.
Angle-Insensitive Human Motion and Posture Recognition Based on 4D Imaging Radar and Deep Learning Classifiers
Author: Yubin Zhao, Alexander Yarovoy, Francesco Fioranelli
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Francesco Fioranelli (Author)
Human Activity Recognition (HAR) is crucial to support the needs of an aging population. The paper proposes a new method for HAR using 4D imaging radars. The technique combines point cloud and spectrogram data to capture the spatial and temporal features of the activities. The method is tested on an experimental dataset and performs better than existing alternatives.
Gait-Based Person Identification and Intruder Detection Using mm-Wave Sensing in Multi-Person Scenario
Author: Zhongfei Ni, Binke Huang
Published in: IEEE Sensors Journal (Volume: 22, Issue: 10, May 2022)
Summary Contributed by: Saurabh Dubey
MGait is a multi-person identification and intruder detection system that utilizes mm-wave sensing to identify users based on gait micro-Doppler (m-D) signatures. Individuals are continuously tracked in indoor scenarios using low-cost mm-wave radars in range-Doppler (R-D) space frame by frame to extract their distinct gait signatures. Trained in a deep learning-based Gaussian mixture loss model, MGait is a promising solution for biometrics and has wide applications in health and security.
Design Methodology for Industrial Internet-of-Things Wireless Systems
Author: Carlos Mendes da Costa, Peter Baltus
Published in: IEEE Sensors Journal (Volume: 21, Issue: 4, February 2021)
Summary Contributed by: Payal Savani
The rise in Internet of Things (IoT) usage in industrial applications requires robust wireless systems. The researchers proposed an innovative approach for designing low-latency, power-efficient, and reliable wireless systems. This paper comprehensively studies system requirements, hardware, and architecture for optimal design choices. The prototype design was validated through practical experiments. It demonstrates superior performance compared to existing wireless standards.
Online Learning for Active Odor Sensing Based on a QCM Gas Sensor Array and an Odor Blender
Author: Manuel Aleixandre, Takamichi Nakamoto
Published in: IEEE Sensors Journal (Volume: 22, Issue: 23, December 2022)
Summary Contributed by: Manuel Aleixandre (Author)
This work presents an active odor sensing system that blends odorous ingredients, iteratively adjusting their mix ratios to match the sensor response of a target scent. Online learning adapts the sensor model parameters in real-time, optimizing the control loop to compensate for drift and humidity variations. It improves the accuracy and robustness despite the inherent limitations of gas sensors.
Research of Low-Power MEMS-Based Micro Hotplates Gas Sensor: A Review
Author: Zhenyu Yuan, Fan Yang, Fanli Meng, Kaiyuan Zuo, Jin Li
Published in: IEEE Sensors Journal (Volume: 21, Issue: 17, September 2021)
Summary Contributed by: Anupama
The MEMS-based micro hotplate gas sensors are small and mass-producible with excellent performance compared to traditional ceramic tube sensors. Energy efficiency is a crucial parameter of portable, reliable sensors. Heat loss significantly increases the power consumption of hotplates. To optimize energy consumption and efficiency, an analytical study of heat loss in different parts of sensor parts and their remedies through fabrication methods is presented.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 15, August 2022)
Summary Contributed by: Saurabh Dubey
Scientific and technological advancement has increased the risk of environmental pollutants like chemicals, heavy metals, and toxic gases, thus affecting human health. The need is to detect the contaminants at the source for corrective measures. This paper discusses the sensitivity, selectivity, response time, recovery time, and repeatability of nanocomposite thin-film-based optical fiber sensors coated with metal oxide semiconductors, polymers, metals, carbon nanotubes, graphene, etc., in relation to monitoring environmental health.
Wireless Communication and Power Harvesting in Wearable Contact Lens Sensors
Author: Mengyao Yuan, Rupam Das, Eve McGlynn, Rami Ghannam, Qammer H. Abbasi, Hadi Heidari
Published in: IEEE Sensors Journal (Volume: 21, Issue: 11, June 2021)
Summary Contributed by: Anupama
Our corneal surface and tears make an excellent alternative to blood as a source of biomarkers. Incorporating sensors into contact lenses could provide a convenient, non-invasive platform for continuously detecting and monitoring diseases like glaucoma, diabetes, and heart disease. Researchers explored current technologies for sensing materials, energy, and data transmission techniques in electronic contact lens sensors. The study systematically explores the challenges and future trends.
Technology to detect signs of life under rubble could save lives. The study proposes a novel radar system with a two-step computation model for detecting live victim's vital signs behind or under obstructions. The first step is to establish a region of interest and identify obstacles. The second step detects respiratory vital signs patterns through time-varying phase data. Experimental demonstration of the proposed system shows significant accuracy in detecting live victims.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 9, May 2021)
Summary Contributed by: Payal Savani
Sensors have been pivotal in making human life comfortable. Sensor technology offers many research opportunities for innovations, contributing to smart living. Here the authors have streamlined the latest literature in the field, providing an overview of sensors and their role in our lives. The article summarizes research into four main sensor-based applications: fitness tracking, emotions analysis, sleep tracking, and food intake monitoring.
MS-YOLO: Object Detection Based on YOLOv5 Optimized Fusion Millimeter-Wave Radar and Machine Vision
Author: Yunyun Song, Zhengyu Xie, Xinwei Wang, Yingquan Zou
Published in: IEEE Sensors Journal (Volume: 22, Issue: 15, August 2022)
Summary Contributed by: Yingquan Zou (Author)
Multi-sensor fusion is becoming an increasingly crucial part of the environmental perception system in autonomous driving. Experience the cutting-edge fusion of millimeter-wave radar and machine vision in the proposed MS-YOLO, powered by You Only Look Once (YOLOv5) algorithm. The proposed fusion model offers exceptional accuracy in detecting objects and provides immediate real-time insights regardless of light and weather conditions.
BabyPose: Real-Time Decoding of Baby’s Non-Verbal Communication Using 2D Video-Based Pose Estimation
Author: M. Mücahit Enes Yurtsever, Süleyman Eken
Published in: IEEE Sensors Journal (Volume: 22, Issue: 14, July 2022)
Summary Contributed by: Saurabh Dubey
Decoding or understanding non-verbal communication forms in babies is paramount to parents. These forms are expressed in various poses and body-language signals, which can be interpreted using a Human Pose Estimation method. Babies are tracked in real-time using 2D videos. Pose estimators that model these poses into keypoints are then employed to recognize and monitor these activities. This study delves into these estimation models that interpret baby poses with 99% accuracy.
Published in: IEEE Sensors Journal (Volume: 22, Issue: 22, November 2022)
Summary Contributed by: Shixin Zhang (Author)
Vision-based tactile sensors (VBTS) are attracting attention for their application in robotics. As an innovative optical sensor, VBTS leverages tactile sensing to enhance the interpretation and utilization tactile information. The paper presents an overview of the hardware aspects of VBTS, including their technology, capabilities, challenges, and potential solutions. It provides insightful guidelines for optimizing the design and fabrication processes of VBTS to improve their performance.
Smart Healthcare: RL-Based Task Offloading Scheme for Edge-Enable Sensor Networks
Author: Rahul Yadav, Weizhe Zhang, Ibrahim A. Elgendy, Guozhong Dong, Muhammad Shafiq, Asif Ali Laghari, Shiv Prakash
Published in: IEEE Sensors Journal (Volume: 21, Issue: 22, November 2021)
Summary Contributed by: Anupama
Smart healthcare systems produce massive data, which is challenging to manage. The Internet of Medical Things (IoMT) and Artificial intelligence (AI) based smart healthcare systems and applications have shown potential in intelligent and accurate data management and support healthcare. While the edge-enabled network provides necessary computational resources to deal with enormous data, the proposed Computation Offloading using Reinforcement Learning (CORL) algorithm minimizes total latency and energy consumption.
A Radar-Based Human Activity Recognition Using a Novel 3-D Point Cloud Classifier
Author: Zheqi Yu, Ahmad Taha, William Taylor, Adnan Zahid, Khalid Rajab, Hadi Heidari, Muhammad Ali Imran, Qammer H. Abbasi
Published in: IEEE Sensors Journal (Volume: 22, Issue: 19, October 2022)
Summary Contributed by: William Taylor (Author)
Wearable sensors for human activity recognition (HAR) have many uses, especially in health, surveillances and man-machine conversation. Technological advancements have enabled non-invasive, contactless sensing methods to detect human activities. However, insufficient training data severely affects the performance of HAR applications. The paper discusses the dataset collection using 3-D cloud point technology and deep learning algorithms to classify the dataset, which will enable a transition from wearable to contactless sensing.
Published in: IEEE Sensors Journal (Volume: 21, Issue: 8, April 2021)
Summary Contributed by: Laxmeesha Somappa
Origami is the art of paper folding to create a two-dimensional and three-dimensional sculpture. Inspired by this art, the researchers developed a flexible pressure sensor, which finds various applications in wearable devices and healthcare products. The origami structure inherently offers higher sensitivity and measurement range. These pressure sensors can easily be fabricated with 3-D printing technology, making them low-cost and enabling mass production.
Data Fusion Based on Temperature Monitoring of Aquaculture Ponds With Wireless Sensor Networks
Author: Haohui Chen, Xinyuan Nan, Sibo Xia
Published in: IEEE Sensors Journal (Volume: 23, Issue: 1, January 2023)
Summary Contributed by: Haohui Chen (author)
Aquaculture is the farming of aquatic animals and plants in a controlled environment. The water temperature is a vital environmental factor that affects the water quality and life of the aquatic species. The paper proposes an effective real-time aquaculture temperature monitoring method through a layered and clustered wireless sensor networks (WSNs) framework. It is more effective in temperature monitoring with improved accuracy in comparison to the traditional monitoring methods.
Image-Based Force Estimation in Medical Applications: A Review
Author: Ali A. Nazari, Farrokh Janabi-Sharifi, Kourosh Zareinia
Published in: IEEE Sensors Journal (Volume: 21, Issue: 7, April 2021)
Summary Contributed by: Anupama
Precise, real-time force estimation is still an ongoing challenge in minimally invasive robotic surgical (MIRS) interventions. The applied force depends on the size and deformity of the tissue. Advanced imaging techniques and deep-learning algorithms provide efficient object recognition and force estimation in MIRS. The researchers present a comprehensive review of image-based force estimation techniques for MIRS haptic force feedback.
Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns With SDR Sensing and Deep Multilayer Perceptron
Author: Umer Saeed, Syed Yaseen Shah, Adnan Zahid, Jawad Ahmad, Muhammad Ali Imran, Qammer H. Abbasi, Syed Aziz Shah
Published in: IEEE Sensors Journal (Volume: 21, Issue: 18, September 2021)
Summary Contributed by: Kamalesh Tripathy
The COVID-19 pandemic highlighted the need for contactless respiration monitoring systems. A software-defined radio frequency sensing technique integrated with a deep learning algorithm was proposed for the non-invasive monitoring of various breathing patterns. The system used variations in channel state information produced by human motions to identify six distinct respiratory patterns. The prototype could classify these respiratory patterns with up to 99% accuracy.
On the Detection of Unauthorized Drones—Techniques and Future Perspectives: A Review
Author: Muhammad Asif Khan, Hamid Menouar, Aisha Eldeeb, Adnan Abu-Dayya, Flora D. Salim
Published in: IEEE Sensors Journal (Volume: 22, Issue: 12, June 2022)
Summary Contributed by: Muhammad Asif Khan (Author)
The increasing number of commercial drones poses severe threats to the security of critical infrastructure and people’s privacy. A drone detection system thus becomes inevitable to detect unauthorized drones in the low altitude airspace. This paper delves into the various aspects of an efficient, reliable, robust, and scalable drone detection system by investigating the four fundamental technologies and the associated challenges and limitations.
Inkjet-Printed, Nanofiber-Based Soft Capacitive Pressure Sensors for Tactile Sensing
Author: Riikka Mikkonen, Anastasia Koivikko, Tiina Vuorinen, Veikko Sariola, Matti Mäntysalo
Published in: IEEE Sensors Journal (Volume: 21, Issue: 23, December 2021)
Summary Contributed by: Anupama
Soft electronics enable lighter and more flexible human-machine interfaces. Learn about an inexpensive, additive approach to fabricating flexible, soft electronics using inkjet printing. Inkjet-printed micro-structured dielectric layers were sandwiched between conductive mesh electrodes to form the capacitive tactile pressure sensors. The sensor exhibits high sensitivity, long-term repeatability, and low hysteresis. The proposed approach can fabricate inexpensive, customizable soft electronics human-machine interfaces.
Precise Detection and Quantitative Prediction of Blood Glucose Level With an Electronic Nose System
Author: Zhenyi Ye, Jie Wang, Hao Hua, Xiangdong Zhou, Qiliang Li
Published in: IEEE Sensors Journal (Volume: 22, Issue: 13, July 2022)
Summary Contributed by: Zhenyi Ye (Author)
Monitoring blood glucose levels after exercise, diet, and medication is vital, especially in people with diabetes. A low-cost, no-pain glucose measurement method outside clinical settings for diabetes patients is essential. The work presents a non-invasive glucose measurement method using a novel electronic nose (E-Nose) device enabled by the machine learning algorithm. The proposed method is capable of precise qualitative glucose identification and quantitative analysis.
The recent COVID outbreaks highlighted the need for breathing rate monitoring and increased the demand for hospitalized patients. Monitoring breathing rate is vital for diagnosing diseases and observing patients with pulmonary conditions. The pros and cons of different techniques are studied and categorized under contact and remote modes of respiratory monitoring systems. Various Radar-based methods found to be more suitable for respiration monitoring are discussed.
Radar detection of smaller targets requires lowering the radar cross-section and velocity thresholds. With it, an abundance of target signatures gets generated, making it necessary to classify only relevant targets. Micro-motions of targets are significant characteristics. Micro-Doppler signatures have emerged as an effective method of classifying such targets. The study presents a systematic review of various micro-Doppler-based radar target signature analysis and classification techniques.
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