SleepCon: Sleeping Posture Recognition Model using Convolutional Neural Network
نویسندگان
چکیده
Recognition of sleep patterns and posture has sparked interest in various clinical applications. Sleep postures can be monitored autonomously constantly to provide useful information for decreasing health risks. Existing systems mostly use images train the model learn based on many sensors. For example, a camera, pressure sensor, electrocardiogram. In this study, (named as SleepCon) was designed using deep learning, which will have capability with any threshold image obtained from sensor. This paper presented system where data camera installed top mattress. The located movement body mattress while subject lying down doing so, CNN other pre-processed steps took place collect then analyze recognize different postures. stored real-time three major postures, i.e., left, right, supine. A application is also developed operates SleepCon through an accompanying desktop detecting live. accuracy classification greater than 90%, actual 100% after carrying out experiment model. Doi: 10.28991/ESJ-2023-07-01-04 Full Text: PDF
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ژورنال
عنوان ژورنال: Emerging science journal
سال: 2022
ISSN: ['2610-9182']
DOI: https://doi.org/10.28991/esj-2023-07-01-04