TY - JOUR
T1 - SleepSense
T2 - A Noncontact and Cost-Effective Sleep Monitoring System
AU - Lin, Feng
AU - Zhuang, Yan
AU - Song, Chen
AU - Wang, Aosen
AU - Li, Yiran
AU - Gu, Changzhan
AU - Li, Changzhi
AU - Xu, Wenyao
N1 - Publisher Copyright:
© 2007-2012 IEEE.
PY - 2017/2
Y1 - 2017/2
N2 - Quality of sleep is an important indicator of health and well being. Recent developments in the field of in-home sleep monitoring have the potential to enhance a person's sleeping experience and contribute to an overall sense of well being. Existing in-home sleep monitoring devices either fail to provide adequate sleep information or are obtrusive to use. To overcome these obstacles, a noncontact and cost-effective sleep monitoring system, named SleepSense, is proposed for continuous recognition of the sleep status, including on-bed movement, bed exit, and breathing section. SleepSense consists of three parts: a Doppler radar-based sensor, a robust automated radar demodulation module, and a sleep status recognition framework. Herein, several time-domain and frequency-domain features are extracted for the sleep recognition framework. A prototype of SleepSense is presented and evaluated using two sets of experiments. In the short-term controlled experiment, the SleepSense achieves an overall 95.1% accuracy rate in identifying various sleep status. In the 75-minute sleep study, SleepSense demonstrates wide usability in real life. The error rate for breathing rate extraction in this study is only 6.65%. These experimental results indicate that SleepSense is an effective and promising solution for in-home sleep monitoring.
AB - Quality of sleep is an important indicator of health and well being. Recent developments in the field of in-home sleep monitoring have the potential to enhance a person's sleeping experience and contribute to an overall sense of well being. Existing in-home sleep monitoring devices either fail to provide adequate sleep information or are obtrusive to use. To overcome these obstacles, a noncontact and cost-effective sleep monitoring system, named SleepSense, is proposed for continuous recognition of the sleep status, including on-bed movement, bed exit, and breathing section. SleepSense consists of three parts: a Doppler radar-based sensor, a robust automated radar demodulation module, and a sleep status recognition framework. Herein, several time-domain and frequency-domain features are extracted for the sleep recognition framework. A prototype of SleepSense is presented and evaluated using two sets of experiments. In the short-term controlled experiment, the SleepSense achieves an overall 95.1% accuracy rate in identifying various sleep status. In the 75-minute sleep study, SleepSense demonstrates wide usability in real life. The error rate for breathing rate extraction in this study is only 6.65%. These experimental results indicate that SleepSense is an effective and promising solution for in-home sleep monitoring.
KW - Evaluation
KW - non-contact sensing
KW - sleep monitoring
UR - http://www.scopus.com/inward/record.url?scp=84979938916&partnerID=8YFLogxK
U2 - 10.1109/TBCAS.2016.2541680
DO - 10.1109/TBCAS.2016.2541680
M3 - Article
AN - SCOPUS:84979938916
SN - 1932-4545
VL - 11
SP - 189
EP - 202
JO - IEEE Transactions on Biomedical Circuits and Systems
JF - IEEE Transactions on Biomedical Circuits and Systems
IS - 1
M1 - 7524724
ER -