Classification of breathing events using load cells under the bed

Annu Int Conf IEEE Eng Med Biol Soc. 2009:2009:3921-4. doi: 10.1109/IEMBS.2009.5333548.

Abstract

Sleep disturbances are prevalent, financially taxing, and have a negative effect on health and quality of life. One of the most common sleep disturbances is obstructive sleep apnea-hypopnea syndrome (OSAHS) which frequently goes undiagnosed. The gold standard for diagnosing OSAHS is polysomnography (PSG)-a procedure that is inconvenient, time-consuming, and interferes with normal sleep patterns. We are investigating an alternative to PSG in which unobtrusive load cells fitted under the bed are used to monitor movement, heart rate, and respiration. In this paper we describe how load cell data can be used to distinguish between clinically relevant disordered breathing (apneas and hypopneas) and normal respiration. The method correctly classified disordered breathing segments with a sensitivity of 0.77 and a specificity of 0.91.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Bayes Theorem
  • Entropy
  • Equipment Design
  • Heart Rate
  • Humans
  • Monitoring, Ambulatory / methods
  • Movement
  • Pattern Recognition, Automated / methods
  • Polysomnography / instrumentation*
  • Polysomnography / methods*
  • Quality of Life
  • Respiration*
  • Sensitivity and Specificity
  • Sleep Apnea, Obstructive / diagnosis*
  • Sleep Apnea, Obstructive / pathology
  • Sleep Wake Disorders / diagnosis
  • Sleep Wake Disorders / pathology