睡眠呼吸中止雖然是在睡眠期間才會發生，但也會連帶影響白天的生理狀態，由於患有呼吸中止症的患者容易引起各種心血管疾病，所以睡眠呼吸障礙越來越被受到重視，但因為量測過程繁雜且診斷耗時，所以有許多研究嘗試著在不同的生理訊號頻道找尋具有鑑別度的特徵變數以簡化診斷的流程。而本文透過心電圖訊號觀察有無呼吸中止症患者之間具有何種差異，並加入了傳統心率變異分析沒有考慮到的心電圖波形內容，進而衍生的頻譜集中度演算法。
結果也發現，患有呼吸中止症患者的頻譜集中度低於一般人，其中患有中樞型呼吸中止症的患者與一般人的心電圖訊號具有最明顯的差異，本文也使用Multiscale Entropy檢驗心跳的複雜度，也觀察到呼吸中止症患者心跳波形及心跳變化都比一般人複雜，且年紀較大的族群的變化會低於年紀輕的族群。

Even though the sleep apnea breathing occurs during the sleep,but it also affects the daytime's physiological status.Since sleep apnea breathing increases the risk of getting cardiovascular diseases,sleep disordered breathing has attracted significant amount attention.Conventional diagnosis processes for sleep disorder breathing is complex and time-consuming,therefore many efforts have been made in developing simplified physiological signal feature to detect sleep disorder breathing.To simplify the process of diagnosis,this study uses the ECG signals to differentiate patients and healthy subjects.In addition to traditional HRV features,this study also test a newly proposed ECG feature called degree of spectrum concentration which characterizes the degree of periodicity of the ECG waveform.
Our experimental results show that sleep apnea patients have higher degree of spectrum concentration than healthy subjects.This work also tests the mutliscale entropy of this degree of spectrum concentration signal.The results demonstrate that complexity of the degree of spectrum concentration signal of the patients is higher than that of the healthy subjects.Finally,our results also detect differences between different age groups.

論文審定書 i
誌謝 ii
圖目錄 vi
表目錄 vii
摘要 viii
Abstract ix
第一章 緒論 1
1.1 前言 1
1.2 研究動機與目的 2
1.3文獻回顧 4
1.4論文架構 6
第二章 呼吸中止症與心電圖訊號 7
2.1 呼吸中止症 7
2.2 睡眠呼吸中止症診斷方式 11
2.3 心電圖訊號的產生 12
2.4 心電圖波型特徵 14
第三章 心電圖訊號衍生之特徵變數 17
3.1心率變異(Heart Rate Variability, HRV) 17
3.2譜集中度指標 19
3.3 Multiscale Entropy 21
3.4 假設檢定 23
3.4.1 兩母體平均數差異的假設檢定-獨立樣本且母體變異數未知 25
第四章 實驗結果與討論 26
4.1頻譜集中度應用於呼吸中止症的比較 26
4.1.1 頻譜集中度整合指標 27
4.1.2 合併頻譜集中度整合指標與HRV指標 29
4.2頻譜集中度應用於性別比較 30
4.2.1頻譜集中度整合指標 31
4.2.2合併頻譜集中度整合指標與HRV指標 31
4.3頻譜集中度應用於同性別且不同年齡的比較 32
4.3.1頻譜集中度整合指標 32
4.3.2合併頻譜集中度整合指標與HRV指標 33
4.4 頻譜集中度未整合與整合指標、合併HRV頻域指標鑑別度的比較 34
4.5頻譜集中度 - Mode峰值指標應用於睡眠結構的比較 37
4.5.1 集中度應用於睡眠結構比較 38
4.6 Multiscale Entropy應用於Mode峰值及RRI 39
4.6.1 呼吸中止症的比較 40
4.6.2性別的比較 42
4.6.3同性別但不同年齡比較的資料庫 43
第五章 結論 45
參考文獻 47
附錄I OSA VS Healthy各Mode與HRV指標的t* 49
附錄II CSA VS Healthy各Mode與HRV指標的t* 51
附錄III CSA VS OSA各Mode與HRV指標的t* 53
附錄IV 性別比較各Mode與HRV指標的t* 55
附錄V 女生年紀比較各Mode與HRV指標的t* 57
附錄VI 男生年紀比較各Mode與HRV指標的t* 59

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