A method for classification of movements in bed

Adriana M. Adami, Misha Pavel, Tamara L. Hayes, André G. Adami, Clifford Singer

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

11 Scopus citations

Abstract

Sleep is characterized by episodes of immobility interrupted by periods of voluntary and involuntary movement. Increased mobility in bed can be a sign of disrupted sleep that may reduce sleep quality. This paper describes a method for classification of the type of movement in bed using load cells installed at the corners of a bed. The approach is based on Gaussian Mixture Models using a time-domain feature representation. The movement classification system is evaluated on data collected in the laboratory, and it classified correctly 84.6% of movements. The unobtrusive aspect of this approach is particularly valuable for longer-term home monitoring against a standard clinical setting.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages7881-7884
Number of pages4
DOIs
StatePublished - Dec 26 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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