Sleep apnea is a sleep disorder distinguished by repetitive absence of breathing. Compared with the traditional expensive and cumbersome methods, sleep apnea diagnosis or screening with physiological information that can be easily acquired is needed. This paper describes algorithms using heart rate variability (HRV) to automatically detect sleep apneas as long as it can be easily acquired with unobtrusive sensors. Because the changes in cardiac activity are usually hysteretic than the presence of apneas with a few minutes, we propose to use the delayed HRV features to identify the episodes with sleep apneic events. This is expected to help improve the apnea detection performance. Experiments were conducted with a data set of 23 sleep apnea patients using support vector machine (SVM) classifiers and cross validations. Results show that using eleven HRV features with a time delay of 1.5 minutes rather than the features without time delay for SA detection, the overall accuracy increased from 74.9% to 76.2% and the Cohen's Kappa coefficient increased from 0.49 to 0.52. Further, an accuracy of 94.5% and a Kappa of 0.89 were achieved when applying subject-specific classifiers.
|Title of host publication||Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'15), 25-29 August 2015, Milan, Italy|
|Place of Publication||Piscataway|
|Publisher||Institute of Electrical and Electronics Engineers|
|Number of pages||4|
|Publication status||Published - 2015|
|Event||37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - "MiCo" , Milan, Italy|
Duration: 25 Aug 2015 → 29 Aug 2015
Conference number: 37
|Conference||37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015|
|Abbreviated title||EMBC 2015|
|Period||25/08/15 → 29/08/15|
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Merel M. van Gilst (Content manager) & M.B. (Beatrijs) van der Hout-van der Jagt (Content manager)
Impact: Research Topic/Theme (at group level)