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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.
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.
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.
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