Authors:
Meng-Chieh Yu
;
Huan Wu
;
Jia-Ling Liou
;
Ming-Sui Lee
and
Yi-Ping Hung
Affiliation:
National Taiwan University, Taiwan
Keyword(s):
Non-contact breath measurement, Sleep monitoring, Sleep position, Sleep cycle, Depth camera.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Decision Support Systems
;
Development of Assistive Technology
;
Electronic Health Records and Standards
;
Health Information Systems
;
Healthcare Management Systems
;
Pattern Recognition and Machine Learning
;
Pervasive Health Systems and Services
Abstract:
Sleep monitoring is increasingly seen as a common and important issue. In this paper, a depth analysis technique was developed to monitor user’s sleep conditions without any physical contact. In this research, a cross-section method was proposed to detect user’s head and torso from the depth images. Then, the system can monitor user’s breathing rate, sleep position, and sleep cycle. In order to evaluate the measurement accuracy of this system, two experiments were conducted. In the first experiment, eight participants with various body shapes were asked to join the experiment. They were asked to change the sleep positions (supine and side-lying) every fifteen breathing cycles in two circumstances (sleep with and without a thin quilt) on the bed. The experimental results showed that the system is promising to detect the head and torso with various sleeping postures. In the second experiment, a realistic over-night sleep monitoring experiment was conducted. The experimental results dem
onstrated that this system is promising to monitor the sleep conditions in realistic sleep conditions. To conclude, this study is important for providing a non-contact technology to detect multiple sleep conditions and assist users in better understanding of their sleep quality.
(More)