臺灣博碩士論文加值系統

背景：入睡困難是現今社會常見之睡眠疾患，睡眠檢測已逐漸受到重視。多頻道睡眠生理記錄儀是目前評估睡眠品質之標準工具，然其成本高且操作不易，難以推廣為居家使用。過往研究發現活動計可用於睡醒判讀，其成本低、便利性高且可長時間記錄睡眠情況及白天活動，皆優於傳統方式。目前關於研究及臨床上的活動計 (Actiwatch, Actigraph, wActiSleep-BT Monitor, Pensacola) 於睡醒判讀及部份活動力偵測之準確性上仍待提升。目的：為了提高活動計辨別睡醒特徵的準確度以及遠距離照護的應用品質，本研究利用實驗室過去已開發之活動計 (KY9, K&;Y lab, Taiwan, size: 3.5 x 3.5 x 0.6 cm3, weight: 16 g) 及睡醒判讀演算法，透過多頻道睡眠生理記錄儀測量及人工睡眠判讀來確認及比較新建立的自動判讀分析系統與市面上的各式活動計辨別睡醒功能。材料與方法：受試者同時配戴實驗室開發之活動計及市售具睡醒判別功能之活動計，配合微型多頻道睡眠生理記錄儀 (TD1, Taiwan Telemedicine Device Company, Taiwan) 進行二十四小時測量及人工睡眠判讀來確認及比較新建立的睡醒判讀分析與市面上活動計，辨別睡醒功能。結果：兩種活動計之演算法在判讀總睡眠時間(total sleep time, TST)上與微型多頻道睡眠生理記錄儀的相關性都極高 (p <0.001)；但實驗室開發的活動計穩定性較高 (p = 0.02)。此外，計算各個睡眠參數，如睡眠效率(sleep efficiency, SE)與入睡後醒來的時間(wake after sleep onset, WASO)的準確度都有提升 (p <0.01)。結論：實驗室開發的活動計及睡醒判讀分析方法準確度都比市面上的活動計高，尤其在計算總睡眠時間。除了更方便、更穩定量化睡眠品質，甚至能雲端化來提升遠距照護與大眾生活的品質。

Background: Sleep disorders have become a common disease in recent years and we pay more attention on sleep detecting gradually. Polysomnography (PSG) is the gold standard for assessing sleep quality, but it needs high cost and long set-up time which is not suitable for public. Actigraphy, is low cost, small size, set up fast, and long-term recording, can be used to distinguish sleep and detect activities. As we known, detecting sleep/wake pattern by using actigraphy is more convenient and less-cost than traditional sleep detecting tool, also can long-term recording. However, because of low accuracy, using actigraphy on sleep scoring and physical activity detecting is still not well-estimated. Aim: To raise the accuracy of actigraphy in distinguishing sleep/wake patterns and application for long-distance health care, we develop sleep/wake discrimination algorithm by laboratory actigraphy, and the comparison with polysomnography (PSG) by using sleep scoring and commercial actiwatch to confirm sleep/wake analysis function. Methods: Each participant carried a laboratory actigraphy with the function of sleep/wake pattern analysis (KY9, K&;Y lab, Taiwan, size: 3.5 x 3.5 x 0.6 cm3, weight: 16 g), a commercial actigraphy (Actiwatch, Actigraph, wActiSleep-BT Monitor, Pensacola) as well as a miniature PSG (TD1, Taiwan Telemedicine Device Company, Taiwan) for 24 hours recording. We compared the results which from the laboratory sleep/wake patterns analysis, standard sleep/wake scoring system and commercial actiwatch. Results: The correlation between TD1 and KY9 by the Pearson linear regression was higher than the correlation between TD1 and commercial actiwatch in total sleep time (r = 0.98, p < 0.001). The Bland-Altman plot used to calculate the variation of KY9 and Actiwatch between TD1 showed that KY9 was better than commercial actiwatch in stability (p = 0.02). Moreover, the similarity between KY9 and TD1 of the sleep parameters, including sleep efficiency (SE) and wakening time after sleep onset (WASO) was higher than commercial actiwatch (p < 0.01). Conclusion: The laboratory-made actigraphy with our developed sleep/wake discrimination analysis have higher accuracy for sleep/wake scoring than the commercial actiwatch, especially in total sleep time. This can provide low power and more convenient sleep monitoring technique with great stability and consistency; even combine cloud computing technique to raise the life quality for general population.

中文摘要 i
英文摘要 ii
目錄 iv
第一節、前言 1
第二節、研究假設 1
第三節、研究動機與目的 2
第二章 相關文獻探討 3
第一節、睡眠品質檢測工具 3
多頻道睡眠生理記錄儀 3
活動計 3
第二節、活動計於睡眠研究上的應用 4
第三節、活動計之睡醒判讀方法 4
第三章 實驗設計與方法 7
第一節、研究對象 7
第二節、研究工具 7
一、攜帶式微型多頻道生理紀錄儀 7
二、Actiwatch 8
三、KY9 8
四、睡眠判讀分析 10
五、活動計睡醒判讀分析 10
第三節、實驗架構與流程 11
第四節、統計方式 12
第四章 實驗結果 14
比較KY9-新的睡醒演算法與Actiwatch-其睡醒演算法與TD1-人工判讀睡眠參數之相關 14
比較KY9-新的睡醒演算法與Actiwatch-其睡醒演算法與TD1-人工判讀睡眠參數之一致性 14
比較KY9-新的睡醒演算法與Actiwatch-其睡醒演算法與TD1-人工判讀之睡眠參數比較 16
第五章 討論 18
本研究最重要之發現 18
市售活動計之睡醒判讀功能與黃金標準之比較 18
實驗室自製活動計之睡醒判讀功能與黃金標準之比較 19
實驗室自製活動計與睡醒判讀方法與黃金標準之比較 19
研究限制 20
結論 20
參考文獻 21
附表 24
表一、 健康受試者基本資料。 25
表二、 成年自覺具睡眠困擾受試者基本資料。 26
表三、KY9活動計硬體規格 27
表四、各種主流無線傳輸規格比較 28
表五、比較各個活動計與傳統儀器運用在健康受試者之準確度 30
表六、比較各個活動計與傳統儀器運用在自覺具睡眠困擾受試者之準確度 31
附圖 32
圖一、實驗流程圖 33
圖二、攜帶式微型多功能生理記錄儀 (TD1) 與市售活動計 34
圖三、雲端活動計與系統模型 35
圖四、雲端活動計之雲端傳輸系統示意圖 36
圖五、KY9活動計原始資料之分析處理流程圖 37
圖六、四種演算法計算TST與黃金標準TD1比較之健康受試者之相關圖 38
圖七、四種演算法計算TST與黃金標準TD1比較之健康受試者之相關圖 39
圖八、四種演算法計算WASO與黃金標準TD1比較之自覺具睡眠困擾受試者之相關圖 40
圖九、四種演算法計算WASO與黃金標準TD1比較之自覺具睡眠困擾受試者之相關圖 41
圖十、以Bland-altman plot 分析法進行人工判讀與不同活動計演算法之健康受試者之總睡眠時間之一致性比較 42
圖十一、以Bland-altman plot 分析法進行人工判讀與不同活動計演算法之健康受試者之入睡後清醒時間結果之一致性比較 43
圖十二、 以Bland-Altman plot 分析法進行人工判讀與不同活動計演算法之健康受試者之睡眠效度結果一致性比較 44
圖十三、以Bland-altman plot 分析法進行人工判讀與不同活動計演算法之自覺具睡眠困擾受試者之總睡眠時間之一致性比較 45
圖十四、以Bland-altman plot 分析法進行人工判讀與不同活動計演算法之自覺具睡眠困擾受試者之入睡後清醒時間結果之一致性比較 46
圖十五、 以Bland-Altman plot 分析法進行人工判讀與不同活動計演算法之自覺具睡眠困擾受試者之睡眠效度結果一致性比較 47
圖十六、比較TD1與活動計演算法所分析之睡眠參數差異值 48
圖十七、比較TD1與活動計演算法所分析之睡眠參數差異值 49
圖十八、比較活動計演算法所分析之睡眠效度曲線下面積 50
附件 51
附件一、人體研究倫理委員會同益人體研究證明書 52
附件二、匹茲堡睡眠品質評量表 53
附件三、貝氏焦慮量表 54
附件四、貝氏憂鬱量表 55
附件五、嗜睡程度評量表 56
附件六、2014台灣睡眠醫學學會第十二屆學術研討會 57

[1] A. Sadeh, "The role and validity of actigraphy in sleep medicine: An update," Sleep Med Rev., vol. 15, pp. 259–267, 2011.
[2] K. D. Cole RJ, Gruen W, Mullaney DJ, Gillin JC, "Automatic sleep/wake identification from wrist activity," Sleep Med Rev., vol. 15, 1992.
[3] W. Tryon, "Issues of validity in actigraphic sleep assessment," Sleep, vol. 27, pp. 158-165, 2004.
[4] B.-S. A. de Souza L, Pires ML, Poyares D, Tufik S, Calil HM, "Further validation of actigraphy for sleep studies," Sleep, vol. 5, 2003.
[5] W. J. Hauri PJ, "Wrist actigraphy in insomnia," Sleep, vol. 15, pp. 293-301, 1992.
[6] L. Y. Marino M, Rueschman MN, Winkelman JW, Ellenbogen JM, Solet JM, Dulin H, Berkman LF, Buxton OM., "Measuring Sleep: Accuracy, Sensitivity, and Specificity of Wrist Actigraphy Compared to Polysomnography," Sleep, vol. 36, pp. 1747-1755, 2013.
[7] v. G. H. Jean-Louis G, Zizi F et al, "Determination of sleep and wakefulness with the actigraph data analysis software (ADAS)," Sleep vol. 19, pp. 739-743, 1996.
[8] S. R. Blood ML, Percy DC, Pen JC, " A comparison of sleep detection by wrist actigraphy, behavioral response, and polysomnography," Sleep, vol. 20, pp. 388-395, 1997.
[9] M. Chambers, "Actigraphy and insomnia: A closer look Part I," Sleep vol. 17, pp. 405-408, 1994.
[10] G. C. Gertner S, Sadeh A, Dolfin Z, Sirota L, Ben-Nun Y, "Sleep-wake patterns in preterm infants and 6 month’s home environment: implications for early cognitive development
" Early Hum Dev, vol. 68, pp. 93-102, 2002.
[11] B. A. Lemke MR, Zeitelberger M, Hartmann W, "Motor activity and daily variation of symptom intensity in depressed patients," Neuropsychobiology, vol. 36, pp. 57-61, 1997.
[12] T. M. Glod CA, Polcari A, McGreenery CE, Ito Y, "Circadian rest-activity disturbances in children with seasonal affective disorder," J Am Acad Child Adoles Psychiatry, vol. 36, pp. 195-199, 1997.
[13] S. D. Lockley SW, Arendt J, "Comparison between subjective and actigraphic measurement of sleep and sleep rhythms," J Sleep Res, vol. 8, pp. 175-184, 1999.
[14] A. H. U. Lindemann, M. Stuber,W. Keck, and C. Becker., "Evaluation of a fall detector based on accelerometers: A pilot study," Medical and Biological Engineering and Computing, vol. 43, 2005.
[15] K. D. Webster JB, Messin S, Mullaney DJ, Wyborney G, "An activity-based sleep monitor system for ambulatory use," Sleep, vol. 5, pp. 389-399, 1982.
[16] S. K. Sadeh A, Carskadon MA., "Activity-based sleep-wake identification: An empirical test of methodological issues.," Sleep, vol. 17, pp. 201-207, 1994.
[17] K. J. Jutta Backhaus, Andreas Broocks, Dieter Riemann, Fritz Hohagen, "Test–retest reliability and validity of the Pittsburgh Sleep Quality Index in primary insomnia," Journal of Psychosomatic Research, vol. 53, pp. 737-740, 2002.
[18] C. C. H. Y. Terry B.J. Kuo, "Frequency domain analysis of electrooculogram and its correlation with cardiac sympathetic function," Experimental Neurology, vol. 217, pp. 38-45, 2009.
[19] A. P. Moser D, Gruber G, Parapatics S, Loretz E, Boeck M, Kloesch G, Heller E, Schmidt A, Danker-Hopfe H, Saletu B, Zeitlhofer J, Dorffner G., "Sleep classification according to AASM and Rechtschaffen &; Kales: effects on sleep scoring parameters," Sleep, vol. 32, pp. 139-149, 2009.
[20] A. D. Bland MJ, "Statistical methods for assessing agreement between two methods of clinical measurement," Lancet, vol. 327, pp. 307-310, 1986.
[21] T. B. Leon Straker, Jennifer Walsh, Stuart King, Peter Eastwod "Assessing Sleep with Wrist and Hip Actigraphy in young adults-Comparison to Simultaneous Laboratory Polysomnography," 2013.