人一天需睡眠約7~8小時，換句話說，睡眠在人們一天的時間中約占了1/3。在這麼長時間的過程中，大腦活動並不是完全靜止不動的，相反地，大腦會進行一連串不同階段的活動，且在不同的階段會產生一些不同型態的訊號；據此，人們將睡眠分為兩大類-非快速眼動期(NREM)ˋ快速眼動期(REM)，而非快速眼動期中由淺至深可再分為淺睡期1(s1)ˋ淺睡期2(s2)ˋ熟睡期(SWS)。另一方面，大腦在不同階段所進行的一些活動經研究發現和學習或是疾病有關，像是s2和記憶學習有顯著的相關性;這些研究說明了判斷睡眠週期的重要性，但是，若是由人工判斷的話，會很耗時ˋ耗力，所以，本篇論文的目標就是提出一個準確率高且值得信賴的自動睡眠週期判讀的方法。
在這篇論文中，從兩台儀器中各收集了10筆共20筆的正常人的記錄，且經由對訊號和頻譜的分析，提出了一個高準確率(88.7% , 87.9%)且可靠的自動睡眠週期判讀方法。為了降低個體差異對自動睡眠週期判斷的影響，在分類之前，會先將運算好的特徵值(feature)作正規劃的動作，之後，再根據階層式的決策樹作判斷。決策樹最後判斷出來的結果總共分成14類，其中，清醒期佔1類，s1佔6類，s2佔4類，SWS佔1類，REM佔2類。週期的判斷是由結果所屬的週期來決定，ex.判斷出來的結果屬於s2的其中一類，則將目前週期判為s2。最後，根據睡眠週期的連續性和一些其他特性，考慮前後週期，將目前判斷的睡眠週期結果做調整，則得到最後判讀的睡眠週期結果。

People need to sleep about 7~8 hours each day. In other words, sleep takes about the 1/3 of the time one day. In such long time, the activation of the brain doesn’t stop. Contrarily, the brain carries through a series of multi-stepped and progressive activities, and produces some different types of signal in different step. Based on this, people divide the sleep into two clusters : non-rapid-eye-movement sleep (NREM), rapid-eye-movement sleep (REM), and NREM from light to deep is divided as s1, s2, SWS. On the other hand, it is found from the research that activities in different step have relation to the learning or diseases, like s2 have strong relation to memory learning. These researches prove the importance of separating sleep stages. But if doing by human beings, it consumes time and energy. Therefore, the aim of the paper is to propose a high accuracy and reliable automatic sleep staging method.
In this paper, we collect 10 records of normal subjects from each device of two, totally 20 records. Based on the analysis of the signal and the spectrum, we propose a high accuracy (88.8 % , 87.9%) and reliable automatic sleep staging method. For decreasing the effect of the individual difference on staging, we do normalization on features before the classification, and then make a decision by the hierarchical decision tree. The final result of the decision tree consists of 14 rules. Among 14 rules, wake holds 1, s1 holds 6, s2 holds 4, SWS holds 1, and REM holds 2. The staging is decided by the stage that the type of the result belongs to. For example, if the staging result is one of the types that belong to s2, the present epoch is staged as s2. Finally, according to the continuity and some other restrictions of the sleep stage, we consider the temporal contextual information and make some modifications on the proceeding results of sleep staging, getting the final answer of the automatic sleep staging.

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