Automated detection of arousal event with fuzzy entropy using physiological signals

Wenhai Tang; Zongqing Lu; Qingmin Liao

doi:10.1117/12.2539930

14 August 2019 Automated detection of arousal event with fuzzy entropy using physiological signals

Wenhai Tang, Zongqing Lu, Qingmin Liao

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 1117925 (2019) https://doi.org/10.1117/12.2539930
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

Abstract

Analyzing physiological signals during sleep can assist experts in diagnosing sleep arousal. To overcome this timeconsuming manual work for medical technologists, in this work a multi task algorithm for automatic identifying sleep arousal events proposed. The algorithm contains two parts: feature extractions and classification. The feature extractions are made of two regular features of arousal and one proposed feature (fuzzy entropy). Fuzzy entropy highlights the possibilities of events. With this contribution and the rest, our result reaches a sensitivity of 0.903 and a specificity of 0.834.

Citation Download Citation

Wenhai Tang, Zongqing Lu, and Qingmin Liao "Automated detection of arousal event with fuzzy entropy using physiological signals", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 1117925 (14 August 2019); https://doi.org/10.1117/12.2539930

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