Classification of breathing events using load cells under the bed

• Published in: 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2009; pp. 3921 - 3924
• Main Authors: Beattie, Z.T., Hagen, C.C., Pavel, M., Hayes, T.L.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2009
• Subjects: Accidents; Algorithms; Bayes Theorem; Biomedical engineering; Bonding; Clinical diagnosis; Costs; Entropy; Equipment Design; Gold; Heart Rate; Humans; Life estimation; Monitoring, Ambulatory - methods; Movement; Pattern Recognition, Automated - methods; Polysomnography - instrumentation; Polysomnography - methods; Quality of Life; Respiration; Sensitivity and Specificity; Sleep; Sleep Apnea, Obstructive - diagnosis; Sleep Apnea, Obstructive - pathology; Sleep Wake Disorders - diagnosis; Sleep Wake Disorders - pathology; Testing
• ISSN: 1094-687X; 2375-7477; 1557-170X; 1558-4615; 1557-170X
• DOI: 10.1109/IEMBS.2009.5333548

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.