CNN-Based Smart Sleep Posture Recognition System
نویسندگان
چکیده
Sleep pattern and posture recognition have become of great interest for a diverse range clinical applications. Autonomous constant monitoring sleep postures provides useful information reducing the health risk. Prevailing systems are designed based on electrocardiograms, cameras, pressure sensors, which not only expensive but also intrusive in nature, uncomfortable to use. We propose an unobtrusive affordable smart system electronic mat called Mat-e activity individuals living residential care facilities. The uses sensing constructed using piezo-resistive material be placed mattress. sensors detect distribution body during we use convolution neural network (CNN) analyze collected data recognize different sleeping postures. is capable recognizing four major postures—face-up, face-down, right lateral, left lateral. A real-time feedback mechanism provided through accompanying smartphone application keeping diary send alert user case there danger falling from bed. It produces synopses activities over given duration time. Finally, conducted experiments evaluate accuracy prototype, proposed achieved classification around 90%.
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ژورنال
عنوان ژورنال: Iot
سال: 2021
ISSN: ['2624-831X']
DOI: https://doi.org/10.3390/iot2010007