A method for classification of movements in bed.

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

Research output: Contribution to journalArticle

9 Citations (Scopus)

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)
Pages (from-to)7881-7884
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Volume2011
StatePublished - 2011
Externally publishedYes

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Sleep
Dyskinesias
Monitoring

ASJC Scopus subject areas

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

Cite this

A method for classification of movements in bed. / Adami, Adriana M.; Pavel, Misha; Hayes, Tamara L.; Adami, André G.; Singer, Clifford.

In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, Vol. 2011, 2011, p. 7881-7884.

Research output: Contribution to journalArticle

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