https://scholars.lib.ntu.edu.tw/handle/123456789/632256
標題: | A Vision-Based System for In-Sleep Upper-Body and Head Pose Classification | 作者: | Li Y.-Y Wang S.-J YI-PING HUNG |
關鍵字: | Deep multi-task learning; Head and upper-body detection; Head and upper-body pose classification; Sleep monitoring; Sleep posture | 公開日期: | 2022 | 卷: | 22 | 期: | 5 | 來源出版物: | Sensors | 摘要: | Sleep quality is known to have a considerable impact on human health. Recent research shows that head and body pose play a vital role in affecting sleep quality. This paper presents a deep multi-task learning network to perform head and upper-body detection and pose classification during sleep. The proposed system has two major advantages: first, it detects and predicts upper-body pose and head pose simultaneously during sleep, and second, it is a contact-free home security camera-based monitoring system that can work on remote subjects, as it uses images captured by a home security camera. In addition, a synopsis of sleep postures is provided for analysis and diagnosis of sleep patterns. Experimental results show that our multi-task model achieves an average of 92.5% accuracy on challenging datasets, yields the best performance compared to the other methods, and obtains 91.7% accuracy on the real-life overnight sleep data. The proposed system can be applied reliably to extensive public sleep data with various covering conditions and is robust to real-life overnight sleep data. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126070704&doi=10.3390%2fs22052014&partnerID=40&md5=9bb1ff8592cadcdafa718fce7701e6d6 https://scholars.lib.ntu.edu.tw/handle/123456789/632256 |
ISSN: | 14248220 | DOI: | 10.3390/s22052014 | SDG/關鍵字: | Cameras; Deep learning; Image recognition; Patient monitoring; Body pose; Deep multi-task learning; Head and upper-body detection; Head and upper-body pose classification; Head pose; Pose classifications; Sleep monitoring; Sleep posture; Upper bodies; Sleep research; body position; human; sleep; Humans; Posture; Sleep |
顯示於: | 電機工程學系 |
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