Classification of breathing events using load cells under the bed

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.

[1]  Trevor Hastie,et al.  Feature Extraction for Nonparametric Discriminant Analysis , 2003 .

[2]  B. Efron.  The jackknife, the bootstrap, and other resampling plans , 1987 .

[3]  Byoung Hoon Choi,et al.  Noninvasive Heart Rate Variability Analysis Using Loadcell-Installed Bed During Sleep , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  Daniel J Buysse,et al.  Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. The Report of an American Academy of Sleep Medicine Task Force. , 1999, Sleep.

[5]  Misha Pavel,et al.  Detection of Movement in Bed Using Unobtrusive Load Cell Sensors , 2010, IEEE Transactions on Information Technology in Biomedicine.

[6]  Xavier L. Aubert,et al.  Estimation of vital signs in bed from a single unobtrusive mechanical sensor: Algorithms and real-life evaluation , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  David Gozal,et al.  The scoring of respiratory events in sleep: reliability and validity. , 2007, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.

[8]  T. Young,et al.  The occurrence of sleep-disordered breathing among middle-aged adults. , 1993, The New England journal of medicine.

[9]  M. Pavel,et al.  Unobtrusive monitoring of sleep patterns , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[10]  M. Brink,et al.  Contact-free measurement of heart rate, respiration rate, and body movements during sleep , 2006, Behavior research methods.

[11]  Susan Redline,et al.  Underdiagnosis of Sleep Apnea Syndrome in U.S. Communities , 2002, Sleep and Breathing.

[12]  A.M. Adami,et al.  Detection and Classification of Movements in Bed using Load Cells , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[13]  K. Harding,et al.  Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem , 2008 .

[14]  H. Colten,et al.  Sleep Disorders and Sleep Deprivation , 2006 .

[15]  Daniel J Buysse,et al.  Sleep–Related Breathing Disorders in Adults: Recommendations for Syndrome Definition and Measurement Techniques in Clinical Research , 2000 .

[16]  W. B. Webb,et al.  The first night effect: an EEG study of sleep. , 1966, Psychophysiology.

[17]  E. Gaensler,et al.  The mechanics of breathing. , 1959, Progress in cardiovascular diseases.

[18]  Silverthorn Dee Unglaub.  Human Physiology: An Integrated Approach , 1998 .