睡眠在人類生活中佔據了三分之一以上，擁有良好的睡眠對於生活品質有著明顯 的幫助。但並不是所有人都擁有良好的睡眠品質，許多人受到睡眠相關疾病所困擾， 因此在臨床上會使用多通道睡眠生理紀錄儀 (Polysomnography, PSG) 進行檢查，由 專家對於收錄的生理訊號進行人工判讀並由專家或醫生進行診斷。由於人工判讀是 一件十分主觀且耗時的工作，故有許多睡眠自動判讀演算法被提出。雖然這些演算 法在準確率上有不錯的表現，但都只提供了一個最終的判讀結果。由於專家無法得 知自動判讀方法的判讀依據，故若專家無法完全相信自動判讀的結果就得重新進行 人工判讀，如此一來自動判讀演算法就不能達到其設計的目的，減少判讀時間。因 此本研究提出一套基於睡眠生理訊號的特徵分析，進而提供信賴度當參考的人機合 作睡眠輔助判讀系統本系統的優點是把判讀結果分為高信賴度與低信賴度兩部份， 使得人工判讀時可以略過高信賴度的判讀結果，來達到減少判讀時間，也讓專家可 以相信整體的判讀結果。本系統經過兩名判讀者測試，全人工判讀與透過輔助判讀 系統之平均整體一致性可達到 88.47%，kappa 僻數為 0.82，平均可以減少 56.2% 的 判讀時間。未來我們系望藉由這套人機合作的睡眠輔助判讀系統在臨床上可以有實 際的應用，除了提供更可靠之判讀結果外，同時真正的減少睡眠判讀所需之時間。

Sleep occupy more than one-third of human life, have a good sleep for the quality of life has a significant help. But not everyone has a good quality of sleep, many people have been plagued by sleep-related disorders. Therefore, the clinical use Polysomnog- raphy (PSG) to recording sleep physiological signals. The collection of physiological signals will be manual scoring by expert for diagnosis. Since manual scoring is a very subjective and time-consuming work, so there are many sleep automatic scoring methods have been proposed. Although the agreement of these methods on a good performance, but only provides a final interpretation of the results. Experts can not know the basis of automatic scoring methods, so experts need to re-scoring when the scoring result not to be believed, in this way automatic scoring method can not achieve its designed purpose, to reduce interpretation time. Therefore, this study proposes a human-computer cooperation scoring system which based on sleep physiological signals, to providing reliability as reference. Advantages of this system is the scoring results is divided into two parts, high reliability and low reliability. Scorer can skip the high reliability epochs to reduce scoring time, and let experts believe the overall scoring re- sults. The system has been testing by two scorer, the average agreement of full manual scoring and work with cooperation systems can reach 88.47%, kappa coefficient was 0.82, and can reduce 56.2% scoring time. We hope this human-computer cooperation scoring system can practical on clinical applications, providing a more reliable scoring results, in addition to reduce scoring time.

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