Stream data analysis of body sensors for sleep posture monitoring: An automatic labelling approach

Poyuan Jeng, Li-Chun Wang

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

3 Scopus citations

Abstract

Sleeping is one of the most important activities in our daily lives. However, very few people really understand their sleeping habits, which affect sleep-related diseases such as sleep apnea, back problems or even snoring. Most current techniques that monitor, predict and quantify sleep postures are limited to use in hospitals and/or need the intervention of caregivers. In this paper, we describe a system to automatically monitor, predict and quantify sleep postures that may be self-applied by the general public even in a non-hospital environment such as at a persons home. A Random Forest approach is adopted during training to predict and quantify sleep postures. After going through training procedures, a person needs only one sensor placed on the wrist to recognize the persons sleep postures. Our preliminary experiments using a set of testing data show about 90 percent accuracy, indicating that this design has a promising future to accurately analyze, predict and quantify human sleep postures.

Original languageEnglish
Title of host publication2017 26th Wireless and Optical Communication Conference, WOCC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509049097
DOIs
StatePublished - 15 May 2017
Event26th Wireless and Optical Communication Conference, WOCC 2017 - Newark, United States
Duration: 7 Apr 20178 Apr 2017

Publication series

Name2017 26th Wireless and Optical Communication Conference, WOCC 2017

Conference

Conference26th Wireless and Optical Communication Conference, WOCC 2017
CountryUnited States
CityNewark
Period7/04/178/04/17

Keywords

  • accelerometer
  • body sensor network
  • sleep posture
  • stream data

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  • Cite this

    Jeng, P., & Wang, L-C. (2017). Stream data analysis of body sensors for sleep posture monitoring: An automatic labelling approach. In 2017 26th Wireless and Optical Communication Conference, WOCC 2017 [7928969] (2017 26th Wireless and Optical Communication Conference, WOCC 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WOCC.2017.7928969