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Detection of Arousal in Patients with Respiratory Sleep Disorder Using Single Channel EEG  

Cho, Sung-Pil (연세대학교 의료공학협동과정)
Choi, Ho-Seon (대원과학대 의료정보시스템과)
Lee, Kyoung-Joung (연세대학교 의공학과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.55, no.5, 2006 , pp. 240-247 More about this Journal
Abstract
Frequent arousals during sleep degrade the quality of sleep and result in sleep fragmentation. Visual inspection of physiological signals to detect the arousal events is cumbersome and time-consuming work. The purpose of this study is to develop an automatic algorithm to detect the arousal events. The proposed method is based on time-frequency analysis and the support vector machine classifier using single channel electroencephalogram (EEG). To extract features, first we computed 6 indices to find out the informations of a subject's sleep states. Next powers of each of 4 frequency bands were computed using spectrogram of arousal region. And finally we computed variations of power of EEG frequency to detect arousals. The performance has been assessed using polysomnographic (PSG) recordings of twenty patients with sleep apnea, snoring and excessive daytime sleepiness (EDS). We could obtain sensitivity of 79.65%, specificity of 89.52% for the data sets. We have shown that proposed method was effective for detecting the arousal events.
Keywords
Arousal; Sleep Fragment; Time-Frequency Analysis; Electroencephalogram; Support Vector Machine;
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