A Gaussian model for movement detection during sleep.

Adriana M. Adami, André G. Adami, Tamara L. Hayes, Misha Pavel, Zachary T. Beattie

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Quality of sleep is an important attribute of an individual's health state and its assessment is therefore a useful diagnostic feature. Changes in the patterns of mobility in bed during sleep can be a disease marker or can reflect various abnormal physiological and neurological conditions. This paper describes a method for detection of movement in bed that is evaluated on data collected from patients admitted for regular polysomnography. The system is based on load cells installed at the supports of a bed. Since the load cell signal varies the most during movement, the approach uses a weighted combination of the short-term mean-square differences of each load cell signal to capture the variations in the signal caused by movement. We use a single univariate Gaussian model to represent each class: movement versus non-movement. We assess the performance of the method against manual annotation performed by a sleep clinic technician from seventeen patients. The proposed detection method achieved an overall sensitivity of 97.9% and specificity of 98.7%.

Original languageEnglish (US)
Pages (from-to)2263-2266
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
Volume2012
StatePublished - 2012
Externally publishedYes

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Sleep
Hospital beds
Polysomnography
Health
Sensitivity and Specificity

ASJC Scopus subject areas

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

Cite this

A Gaussian model for movement detection during sleep. / Adami, Adriana M.; Adami, André G.; Hayes, Tamara L.; Pavel, Misha; Beattie, Zachary T.

In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, Vol. 2012, 2012, p. 2263-2266.

Research output: Contribution to journalArticle

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