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Feature extraction of light sleep state in polysomnogram by use of conditional probability
Hiroaki Yoshiyama,Takenao Sugi,Bei Wang,Shuichiro Shirakawa,Masatoshi Nakamura 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
Human sleep stages during whole right are usually classified into six stages based on polysommnographic (PSG) record. Sleep state of human light sleep changes gradually and continously. In this study, automatic judgrenet of light sleep state in PSG record was developed. Parameters for characterizing the PSG were calculated from the periodogram and the discriminant funtion was constructed by using conditional probability. Estimated value of wake full level was grdually decreased according to the stage charged from W to S1. In conuast, changing the sleep state from S1 to S2 increased estimated value of sleep level accordingly.