DocumentCode
737811
Title
BreathSens: A Continuous On-Bed Respiratory Monitoring System With Torso Localization Using an Unobtrusive Pressure Sensing Array
Author
Liu, Jason J. ; Ming-Chun Huang ; Wenyao Xu ; Xiaoyi Zhang ; Stevens, Luke ; Alshurafa, Nabil ; Sarrafzadeh, Majid
Author_Institution
Dept. of Comput. Sci., Univ. of California, Los Angeles, Los Angeles, CA, USA
Volume
19
Issue
5
fYear
2015
Firstpage
1682
Lastpage
1688
Abstract
The ability to continuously monitor respiration rates of patients in homecare or in clinics is an important goal. Past research showed that monitoring patient breathing can lower the associated mortality rates for long-term bedridden patients. Nowadays, in-bed sensors consisting of pressure sensitive arrays are unobtrusive and are suitable for deployment in a wide range of settings. Such systems aim to extract respiratory signals from time-series pressure sequences. However, variance of movements, such as unpredictable extremities activities, affect the quality of the extracted respiratory signals. BreathSens, a high-density pressure sensing system made of e-Textile, profiles the underbody pressure distribution and localizes torso area based on the high-resolution pressure images. With a robust bodyparts localization algorithm, respiratory signals extracted from the localized torso area are insensitive to arbitrary extremities movements. In a study of 12 subjects, BreathSens demonstrated its respiratory monitoring capability with variations of sleep postures, locations, and commonly tilted clinical bed conditions.
Keywords
biomedical telemetry; body sensor networks; feature extraction; medical signal processing; patient monitoring; pneumodynamics; pressure sensors; time series; BreathSens; arbitrary extremities movements; bodypart localization algorithm; clinics; continuous on-bed respiratory monitoring system; e-Textile; high-density pressure sensing system; high-resolution pressure images; homecare; in-bed sensors; localized torso area; long-term bedridden patients; patient breathing monitoring; respiration rates; respiratory monitoring capability; respiratory signal extraction; sleep postures; tilted clinical bed conditions; time-series pressure sequences; torso localization; underbody pressure distribution; unobtrusive pressure sensing array; unpredictable extremities activities; variance of movements; Arrays; Biomedical measurement; Hip; Hospitals; Monitoring; Sensors; Torso; Pictorial structure; pressure sensor; respiration monitoring; signal extraction;
fLanguage
English
Journal_Title
Biomedical and Health Informatics, IEEE Journal of
Publisher
ieee
ISSN
2168-2194
Type
jour
DOI
10.1109/JBHI.2014.2344679
Filename
6869013
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