跳到主要內容

臺灣博碩士論文加值系統

(34.204.180.223) 您好!臺灣時間:2021/08/01 16:57
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:陳俊佑
研究生(外文):Chun-YuChen
論文名稱:基於心率變異度之自動睡眠判讀方法
論文名稱(外文):A heart-rate-variability based automatic sleep scoring method
指導教授:梁勝富梁勝富引用關係
指導教授(外文):Sheng-Fu Liang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:醫學資訊研究所
學門:醫藥衛生學門
學類:醫學技術及檢驗學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:58
中文關鍵詞:自動睡眠判讀方法心電圖心跳速率心率變異度睡眠週期受測者間獨立
外文關鍵詞:automatic sleep scoring methodElectrocardiographyECGheart rateheart-rate-variabilityHRVsleep cyclesubject-dependent
相關次數:
  • 被引用被引用:0
  • 點閱點閱:445
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
睡眠,是十分重要的。然而,並不是每個人都可以擁有良好的睡眠品質。在臨床上常以多重睡眠生理記錄儀 (PSG) 來收錄病患整晚的睡眠生理訊號,並藉此訊號來觀察病患的睡眠品質。由於人工睡眠判讀十分費時且時常包含專家自身的主觀想法,因此自動睡眠判讀方法的開發便成為一件十分重要的課題。傳統的腦電圖、眼電圖、肌電圖之生理訊號組合對使用者的睡眠品質干擾較大,使得判讀結果有時無法準確反映出該使用者真正的睡眠狀況。因此在本研究中我們採用對使用者睡眠品質干擾較低的心率訊號來開發自動睡眠判讀演算法。雖然目前使用心率相關訊號來做睡眠判讀的方法還不算成熟,但它低干擾、方便收錄且又可以觀察完整睡眠週期的特性,使得它未來的發展不可限量。
由於每個人的心率特徵不盡相同,現有方法卻大多採用將受測者分群,交叉驗證的方式進行睡眠判讀,導致普遍準確度都不高。故使用心電圖作為分類特徵時,無法如腦電圖、眼電圖、肌電圖等生理訊號,訓練一個通用模組套用在每位受測者身上。故在本研究中,我們改採每位受測者間獨立訓練自己參數的模式,搭配三個特徵值來建構演算法:此三項特徵分別是平均心率、心率變異數及心率變異度中的低頻功率。本演算法在測試過15位受測者之後,得到整體判讀準確度為69.48%、清醒準確度為63.48%、淺度睡眠準確度為71.30%、深度睡眠準確度為68.06%、快速眼動期準確度為68.78%。本研究未來預期可與現有的心率量測系統如心電圖、指夾式血氧計等結合,實際應用於臨床監測與居家照護等相關領域。
Sleep is important to everyone. However, not everyone can acquire good sleep quality. For the diagnosis, all night polysomnographic (PSG) recordings are usually taken from the patients. The doctor needs to realize the sleep quality and quantity of them. Nevertheless, visual sleep scoring is a time consuming and subjective process. Therefore, developing an automatic sleep scoring method is a very important issue. Due to the disturbance from typical biomedical signals: EEG, EOG, and EMG recording are too huge, the sleep quality scored from those signals is not accurate enough. So our objective of this study is developing an automatic sleep scoring method which only uses the heart rate as the input signal. Although the method using HRV as the input signal is not good enough, the benefits like less disturbance, easy to use and capability of detecting sleep cycle, make it has unlimited potential.
Everyone has different heart rate features. However, most of recent studies used cross-subject concept to develop their automatic sleep scoring method, cause they have lower accuracy. According to this, we can’t use cross-subject way to treat the signal like EEG, EOG and EMG dataset. In the study, we use the concept of subject-dependent to construct our method. Using this concept and 3 features: average heart rate, variance of heart rate and HRV LF power, we have 69.48% total accuracy, 63.48% accuracy for wake, 71.30% accuracy for light sleep, 68.06% accuracy for deep sleep, and 68.78% accuracy for REM sleep. We expect this study can integrate with various heart rate signal recorder such as ECG and pulse oximeter for sleep monitoring in clinical or homecare application.
摘要 I
ABSTRACT II
誌謝 III
目錄 V
表目錄 VII
圖目錄 VIII
第1章 緒論 1
1.1 前言 1
1.2 研究動機 2
1.3 相關研究 4
1.4 論文架構 5
第2章 研究背景與原理 6
2.1 人類睡眠狀態的定義 6
2.2 心臟收縮機制 9
2.3 心電圖簡介 12
2.4 心率變異度分析 16
2.5 Pan-Tompkins 演算法 20
第3章 研究方法 24
3.1 實驗環境 24
3.2 實驗收錄 25
3.3 使用特徵 26
3.3.1 平均心跳速率與心率變異數 31
3.3.2 HRV頻域分析指標LF 32
3.4 自動睡眠判讀演算法 35
第4章 研究結果 42
4.1 PSG收錄資料分析 42
4.2 自動睡眠判讀效能分析 42
第5章 討論 48
第6章 結論與未來展望 53
參考文獻 55
黃蓮奇(譯)(1996)。心臟和循環系統。台北市:光復書局。
楊杞柳(譯)(1911)。心電圖判讀之快速學習法。台北縣:財團法人徐氏基金會。
Adnane, M., & Jiang, Z. (2009). Automatic sleep-wake stages classifier based on ECG.
Agnew Jr, H., Webb, W. B., & Williams, R. L. (1966). THE FIRST NIGHT EFFECT: AN EEG STUDYOF SLEEP. Psychophysiology, 2(3), 263-266.
Chang, D. W., Liang, S. F., Young, C. P., Shaw, F. Z., Su, A. W. Y., Liu, Y. D., . . . Chen, C. Y. A Versatile Wireless Portable Monitoring System for Brain–Behavior Approaches. Emerging and Selected Topics in Circuits and Systems, IEEE Journal on(99), 1-1.
Chang, D. W., Liu, Y. D., Young, C. P., Chen, J. J., Chen, Y. H., Chen, C. Y., . . . Liang, S. F. Design and Implementation of a Modularized Polysomnography System. Instrumentation and Measurement, IEEE Transactions on(99), 1-12.
Compumedics Limited, “Siesta. Available:
http://www.compumedics.com/product_detail.asp?id=13&item=product ,2012.
Danker-Hopfe, H., Anderer, P., Zeitlhofer, J., Boeck, M., Dorn, H., Gruber, G., . . . Parapatics, S. (2009). Interrater reliability for sleep scoring according to the Rechtschaffen & Kales and the new AASM standard. Journal of sleep research, 18(1), 74.
Danker-Hopfe, H., Kunz, D., Gruber, G., Klösch, G., Lorenzo, J., Himanen, S., . . . Dorn, H. (2004). Interrater reliability between scorers from eight European sleep laboratories in subjects with different sleep disorders. Journal of sleep research, 13(1), 63.
Diekelmann, S., & Born, J. (2010). The memory function of sleep. Nature Reviews Neuroscience, 11(2), 114-126.
Edinger, J. D., Fins, A. I., Sullivan Jr, R. J., Marsh, G. R., Dailey, D. S., Hope, T. V., . . . Vasilas, D. (1997). Sleep in the laboratory and sleep at home: Comparisons of older insomniacs and normal sleepers. Sleep: Journal of Sleep Research & Sleep Medicine; Sleep: Journal of Sleep Research & Sleep Medicine.
Fischer, Y., Junge‐hülsing, B., Rettinger, G., & Panis, A. (2004). The use of an ambulatory, automatic sleep recording device (QUISI™ Version 1.0) in the evaluation of primary snoring and obstructive sleep apnoea. Clinical Otolaryngology & Allied Sciences, 29(1), 18-23.
Grass Technologies, Astro-Med, Inc. Subsidiary., “AURA® PSG Ambulatory Systems. Available: http://www.grasstechnologies.com/products/clinsystems/aurapsg1.html, 2012.
Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. (1996). Eur Heart J, 17(3), 354-381.
Jansen, B., & Dawant, B. (1989). Knowledge-based approach to sleep EEG analysis-a feasibility study. Biomedical Engineering, IEEE Transactions on, 36(5), 510-518.
Kawada, T., Xin, P., Kuroiwa, M., Sasazawa, Y., Suzuki, S., & Tamura, Y. (2001). Habituation of Sleep to Road Traffic Noise as determined by Polysomnography and an Accelerometer. Journal of sound and vibration, 242(1), 169-178.
Kawase, M., Komatsu, T., Nishiwaki, K., Kimura, T., Fujiwara, Y., Takahashi, T., & Shimada, Y. (2000). Heart rate variability during massive hemorrhage and progressive hemorrhagic shock in dogs. Canadian Journal of Anesthesia/Journal canadien d'anesthésie, 47(8), 807-814.
Kesper, K., Canisius, S., Penzel, T., Ploch, T., & Cassel, W. (2012). ECG signal analysis for the assessment of sleep-disordered breathing and sleep pattern. Medical and Biological Engineering and Computing, 1-10.
Liang, S. F., Kuo, C. E., Hu, Y. H., & Cheng, Y. S. (2012). A rule-based automatic sleep staging method. Journal of Neuroscience Methods, 205(1), 169-176.
Liang, S. F., Kuo, C. E., Hu, Y. H., Pan, Y. H., & Wang, Y. H. (2012). Automatic Stage Scoring of Single-Channel Sleep EEG by Using Multiscale Entropy and Autoregressive Models. Instrumentation and Measurement, IEEE Transactions on(99), 1-9.
Liang, S. F., Young, C. P., Chang, D. W., Shaw, F. Z., Liu, Y. D., Liu, Y. C., & Chen, J. J. (2011). Development of an actigraph system for sleep-wake identification.
Macor, F., Fagard, R., & Amery, A. (1996). Power spectral analysis of RR interval and blood pressure short-term variability at rest and during dynamic exercise: comparison between cyclists and controls. International journal of sports medicine, 17(3), 175-181.
Mahowald, M. W., & Schenck, C. H. (2005). Insights from studying human sleep disorders. Nature, 437(7063), 1279-1285.
Norman, R. G., Pal, I., Stewart, C., Walsleben, J. A., & Rapoport, D. M. (2000). Interobserver agreement among sleep scorers from different centers in a large dataset. Sleep, 23(7), 901.
Ohayon, M. M. (2002). Epidemiology of insomnia: what we know and what we still need to learn. Sleep medicine reviews, 6(2), 97-111.
Palatini, P., & Julius, S. (2009). The role of cardiac autonomic function in hypertension and cardiovascular disease. Current hypertension reports, 11(3), 199-205.
Pan, J., & Tompkins, W. J. (1985). A real-time QRS detection algorithm. Biomedical Engineering, IEEE Transactions on(3), 230-236.
Park, H., Park, K. S., & Jeong, D. U. (2000). Hybrid neural-network and rule-based expert system for automatic sleep stage scoring.
Pittman, S., MacDonald, M., Fogel, R., Malhotra, A., Todros, K., Levy, B., . . . White, D. (2004). Assessment of automated scoring of polysomnographic recordings in a population with suspected sleep-disordered breathing. Sleep, 27(7), 1394.
Politano, L., Palladino, A., Nigro, G., Scutifero, M., & Cozza, V. (2008). Usefulness of heart rate variability as a predictor of sudden cardiac death in muscular dystrophies. Acta Myol, 27, 114-122.
Rechtschaffen, A., & Kales, A. (1968). A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects, no. 204. National Institutes of Health Publications, U.S. Government Printing Office.
Rosen, M. R. (1988). The links between basic and clinical cardiac electrophysiology. Circulation, 77(2), 251-263.
Sadeh, A., & Acebo, C. (2002). The role of actigraphy in sleep medicine. Sleep medicine reviews, 6(2), 113-124.
Sazonov, E., Sazonova, N., Schuckers, S., & Neuman, M. (2004). Activity-based sleep–wake identification in infants. Physiological measurement, 25, 1291.
Scanlon, V. C., Sanders, T., Ref, S., & Systems, T. D. (1991). Essentials of anatomy and physiology: FA Davis.
Schaltenbrand, N., Lengelle, R., Toussaint, M., Luthringer, R., Carelli, G., Jacqmin, A., . . . Macher, J. (1996). Sleep stage scoring using the neural network model: comparison between visual and automatic analysis in normal subjects and patients. Sleep, 19(1), 26.
Shin, K., MINAMITANI, H., ONISHI, S., YAMAZAKI, H., & LEE, M. (1997). Autonomic differences between athletes and nonathletes: spectral analysis approach. Medicine & Science in Sports & Exercise, 29(11), 1482.
Shinar, Z., Baharav, A., Dagan, Y., & Akselrod, S. (2001). Automatic detection of slow-wave-sleep using heart rate variability.
Smith, J. R., Negin, M., & Nevis, A. H. (1969). Automatic analysis of sleep electroencephalograms by hybrid computation. Systems Science and Cybernetics, IEEE Transactions on, 5(4), 278-284.
Steriade, M. (2000). Corticothalamic resonance, states of vigilance and mentation. Neuroscience, 101(2), 243-276.
Steriade, M., McCormick, D. A., & Sejnowski, T. J. (1993). Thalamocortical oscillations in the sleeping and aroused brain. Science, 262(5134), 679-685.
Whitney, C. W., Gottlieb, D. J., Redline, S., Norman, R. G., Dodge, R. R., Shahar, E., . . . Nieto, F. J. (1998). Reliability of scoring respiratory disturbance indices and sleep staging. Sleep, 21(7), 749.
連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊