Feasibility of Exploiting Physiological and Motion Features for Camera-based Sleep Staging: A Clinical Study

Qiongyan Wang1; Hanrong Cheng2; Wenjin Wang1

10.1109/EMBC40787.2023.10340835

2023

45th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

2375-7477

1558-4615

979-8-3503-2448-8

2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

1-5

24-27 July 2023

Sydney, Australia

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Camera-based sleep monitoring is an emergent research topic in sleep medicine. The feasibility of using both the physiological features and motion features measured by a video camera for sleep staging was not thoroughly investigated. In this paper, we built a camera-based non-contact sleep monitoring setup in the Institute of Respiratory Diseases, Shenzhen People's Hospital, and created a clinical sleep dataset (nocturnal video data of 11 adults) including the expert-corrected PSG references synchronized with the video. The camera-based measurements have shown high correlations with the PSG. It obtains an overall Mean Absolute Error (MAE) of 1.5 bpm for heart-rate (HR), 0.7 bpm for breathing-rate (BR), 13.9 ms for heart-rate variability (HRV), and an accuracy of 93.5% for leg motion detection. The statistical analysis indicates that the averaged HR and variations of BR are distinct features for annotating four sleep stages (awake, REM, light sleep, and deep sleep). HRV parameter (SDNN) can clearly differentiate rapid-eye-movement (REM) and non-REM, while the leg movement is a distinctive feature for separating awake and sleep. The clinical trial demonstrated the feasibility of using physiological and motion features measured by a camera for joint sleep staging, and provides insights for sleep-related feature selection.

camera sleep staging physiological measurement motions

第一

英语

EI ; CPCI-S

National Key R&D Program of China[2022YFC2407800]

Computer Science ; Engineering

Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical

WOS:001133788303182

20240215362281

Eye movements ; Heart ; Sleep research

Biological Materials and Tissue Engineering:461.2 ; Ergonomics and Human Factors Engineering:461.4 ; Television Systems and Equipment:716.4 ; Photographic Equipment:742.2

IEEE

1.Department of Biomedical Engineering, Southern University of Science and Technology, China
2.Institute of Respiratory Diseases, Shenzhen People’s Hospital, Shenzhen, China

Qiongyan Wang,Hanrong Cheng,Wenjin Wang. Feasibility of Exploiting Physiological and Motion Features for Camera-based Sleep Staging: A Clinical Study[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:1-5.