Occlusion-robust Sleep Posture Detection using Body Rolling Motion in a Video

Yingen Zhu1; Yongshen Zeng1; Dongmin Huang1; Jia Huang2; Hongzhou Lu2; Wenjin Wang1

10.1109/EMBC40787.2023.10340050

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

It has been reported that the monitoring of sleep postures is useful for the treatment and prevention of sleep diseases such as obstructive sleep apnea and heart failure. Camera-based sleep posture detection is attractive for the nature of comfort and convenience of use. However, the main challenge is to detect postures from images of the body that are occluded by bed sheets or covers. To address this issue, we propose a novel occlusion-robust sleep posture detection method exploiting the body rolling motion in a video. It uses the head orientation to indicate the posture direction (supine, left or right lateral), triggered by the full-body rolling motion (as a sign of posture change). The experimental results show that our proposed method, as compared with the state-of-theart approaches such as skeleton-based (MediaPipe) and fullimage ResNet based methods, obtained clear improvements on sleep posture detection with heavy body occlusions, with an averaged precision, recall and F1-score of 0.974, 0.993 and 0.983, respectively. The next step is to integrate the sleep posture detection algorithm into a camera-based sleep monitoring system for clinical validations.

Head Estimation Sleep apnea Biology Cardiovascular diseases Detection algorithms Monitoring

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:001133788300107

20240215361547

Cameras ; Sleep research

Ergonomics and Human Factors Engineering:461.4 ; Photographic Equipment:742.2

IEEE

1.Department of Biomedical Engineering, Southern University of Science and Technology, China
2.Intensive Care Unit, The Third People’s Hospital of Shenzhen, China

Yingen Zhu,Yongshen Zeng,Dongmin Huang,et al. Occlusion-robust Sleep Posture Detection using Body Rolling Motion in a Video[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:1-5.