A dense pressure sensitive bedsheet design for unobtrusive sleep posture monitoring

Jason J. Liu, Wenyao Xu, Ming Chun Huang, Nabil Alshurafa, Majid Sarrafzadeh, Nitin Raut, Behrooz Yadegar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

71 Scopus citations

Abstract

Sleep plays a pivotal role in the quality of life, and sleep posture is related to many medical conditions such as sleep apnea. In this paper, we design a dense pressure-sensitive bedsheet for sleep posture monitoring. In contrast to existing techniques, our bedsheet system offers a completely unobtrusive method using comfortable textile sensors. Based on high-resolution pressure distributions from the bedsheet, we develop a novel framework for pressure image analysis to monitor sleep postures, including a set of geometrical features for sleep posture characterization and three sparse classifiers for posture recognition. We run a pilot study and evaluate the performance of our methods with 14 subjects to analyze 6 common postures. The experimental results show that our proposed method enables reliable sleep posture recognition and offers better overall performance than state-of-the-art methods, achieving up to 83.0% precision and 83.2% recall on average.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Pervasive Computing and Communications, PerCom 2013
Pages207-215
Number of pages9
DOIs
StatePublished - Jul 18 2013
Event11th IEEE International Conference on Pervasive Computing and Communications, PerCom 2013 - San Diego, CA, United States
Duration: Mar 18 2013Mar 22 2013

Publication series

Name2013 IEEE International Conference on Pervasive Computing and Communications, PerCom 2013

Other

Other11th IEEE International Conference on Pervasive Computing and Communications, PerCom 2013
Country/TerritoryUnited States
CitySan Diego, CA
Period3/18/133/22/13

Keywords

  • Bedsheet
  • Pressure Image Analysis
  • Sleep Posture
  • Sparse Classifier

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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