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"IEEE Sensors Alert" is a new service 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 (April 2025)
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.
Knee injuries and other minor or chronic knee conditions are prevalent. Monitoring rehabilitation or medication progress in knee treatment is time-consuming, expensive, and requires regular imaging, follow-ups, and several tests. However, knee health can be monitored and “joint health score” calculated remotely with wearable sensors that pick up sound, swelling, temperature and motion. Packaging these sensors into a wearable brace is vital for monitoring the knee.
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.
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