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研究生： 黃健峻
Huang, Chien-Chun
論文名稱： 應用S轉換於去除生物訊號電源雜訊與震顫訊號量測分析之研究
Application of S-transform in Removing Powerline Interference from Biosignals and Design of a Tremor Measurement and Analysis System
指導教授： 楊明興
Young, Ming-Shing
學位類別： 博士
Doctor
系所名稱： 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年： 2009
畢業學年度： 97
語文別： 英文
論文頁數： 75
中文關鍵詞： 電源雜訊 、S轉換 、去雜訊 、肌肉疲勞 、加速度計 、震顫
外文關鍵詞： S-transform, powerline interference, denoising, tremor, muscle fatigue, accelerometer
相關次數： 點閱：99  下載：7 
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    • 微弱的生物電訊號非常容易受到交流電源雜訊的干擾，特別是缺乏良好接地或屏蔽設施的場合。雖然許多去除電源雜訊的方法已經被開發出來，但是這些技術往往在去除電源雜訊干擾的同時，也衰減原本生物電訊號在60 Hz頻帶(電源雜訊)附近的能量。我們採用了S轉換，藉由它可在特定頻率成份解析出絕對相位的特性，以及多重時頻解析度的優點，來進行去除60 Hz電源雜訊干擾的計算。我們以心電圖(ECG)加上模擬60 Hz干擾的訊號測試結果，證實利用S轉換離線式去除雜訊的方法不但可以保留原始心電圖訊號的功率頻譜，更可以顯著降低60 Hz干擾的能量強度。此外，以S轉換去除60 Hz電源雜訊的能力，並不因為雜訊成份的強度大小有所改變。我們也從MIT心電圖資料庫中取出標準心電訊號、以生理訊號放大器(Model P511, Grass)記錄的肌電圖(EMG)與自發性癲癇大鼠受電源雜訊污染的腦波(EEG)測試，分別與陷波濾波器在去除60 Hz雜訊與保留原訊號能力的結果比較，證實了以S轉換去除電源雜訊此方法的卓越之處。參照以上的測試結果，我們成功建立了這個以S轉換去除電源雜訊干擾的新穎方法。
    本研究另外建立一套多肢段生理性震顫量測與分析系統，並且於人體實驗中驗證系統的可用性，除了應用S轉換去除量測訊號中的電源雜訊，也以S轉換的時頻分析功能來探討震顫訊號的時頻能量分佈。本系統主要以黏貼於人體的微機械電容式加速度計，來量測肢體震顫(Tremor)。實驗包含有: (1)研究年齡效應在疲勞引發的肢體施力性震顫(Force Tremor)造成的影響，結果顯示:相較於肌電圖(Electromyography)、力量波動(Force Fluctuation)，震顫訊號最適合用來描述不同年齡族群肌肉疲勞的特徵變化。(2)探討射擊選手瞄射過程中多肢段姿勢性震顫的特徵，證實較佳震顫控制是決定選手成績表現的因素之一。

    Powerline interference always disturbs recordings of biomedical signals, especially when good grounding or shielding facilities are absence. Numerous methods have been developed to reduce powerline interference. However, most of these techniques not only reduce the interference but also attenuate the 60-Hz power of the biomedical signals themselves. We applied the S-transform, which provides an absolute phase of each frequency in a multi-resolution time-frequency analysis, to reduce 60-Hz interference offline. According to results from an electrocardiogram (ECG) to which a simulated 60-Hz noise was added, the S-transform de-noising process restored an identical power spectrum to that of the original ECG coincident with a significant reduction in the 60-Hz interference. Moreover, the S-transform de-noised the signal in an intensity-independent manner when reducing the 60-Hz interference. In the real ECG signal derived from the MIT database, electromyography (EMG) recorded by commercial biosignal amplifier (Model P511, Grass) and natural brain activity contaminated with 60-Hz interference, the S-transform also displayed superior merit to a notch filter in terms of noise removal and signal preservation. Based on these data, a novel application of the S-transform for removing powerline interference is established.
    In this study, a multi-segment physiological tremor measurement and analysis system was built and its usability was verified in human experiments. MEMs type capacitive accelerometers were attached on human body for sensing tremor. The S-transform denoising method was applied to eliminate powerline interference from physiological signals. Besides, time-frequency presentation of tremor signal was performed based on S-transform. Conducted experiments included: (1) Investigation of age effect on fatigue-induced force tremor. Compared with EMG and force fluctuation (FF), muscle fatigue was most characterized with tremor in different age population. (2) Examining the organization of postural tremor of pistol shooters while they were aiming. The results implied that optimizing control in tremor leads to successful shooting.

    摘要 I ABSTRACT III 誌謝 V CONTENTS VII LIST OF TABLES X LIST OF FIGURES XI CHAPTER 1 INTRODUCTION 1 1.1 Powerline Interference 1 1.1.1 Influence of Powerline Interference on Biosignals 1 1.1.2 Conventional Removing Techniques 2 1.2 Tremor Measurement System 4 1.2.1 Introduction of Tremor 4 1.2.2 Methods for Studying Tremor 5 1.2.2.1 Accelerometry 5 1.2.2.2 Electromyography 5 1.2.3 Quantification of Tremor 5 1.2.4 Physiological Tremor 7 1.2.4.1 Physiological Tremor as an Indicator for Muscle Fatigue 8 1.2.4.2 Physiological Tremor during Pistol Shooting 9 CHARPTER 2 METHODS 11 2.1 Algorithm for Removing Powerline Interference 11 2.1.1 S-transform 11 2.1.2 Implementation of the Discrete S-transform 14 2.2 Tremor Measurement System 16 2.2.1 Accelerometer 16 2.2.2 Signal Conditioning System 18 2.2.2.1 Power Supply 18 2.2.2.2 High Pass Filter 18 2.2.2.3 Selectable Gain Amplifier 19 2.2.2.4 Low Pass Filter 19 2.2.2.5 Verification of the Signal Conditioning System 19 2.2.3 Data Acquisition System 19 2.3 Software Design 20 2.4 System Calibration 20 2.4.1 Static Calibration 20 2.4.2 Dynamic Calibration 21 CHARPTER 3 Removing Powerline Interference from Biomedical Signals 22 3.1 Subjects and Data Acquisition 22 3.1.1 Human ECG recording 22 3.1.2 Human EMG recording 23 3.1.3 Rat EEG recording 23 3.2 Implementation of Algorithm and De-noising Process 24 3.2.1 Notch filter 24 3.2.2 S-transform 25 3.2.2.1 Choosing Optimal Parameters of S-transform 26 3.2.2.2 Four Derivations for Estimating the Amplitude and Phase of the Powerline Interference 27 3.2.2.3 Effect of the Time-frequency Window Parameter b in the De-noising Process 29 3.3 Comparisons of De-noising Performance 31 3.4 Discussion 41 CHARPTER 4 System Implementation I – Measurement of Physiological Tremor 45 4.1 Force Tremor as an Indicator for Muscle Fatigue 45 4.2 System Setup and Experimental Procedures 45 4.2.1 Subjects 45 4.2.2 EMG Recording 45 4.2.3 Force Recording 46 4.2.4 Tremor Recording 46 4.2.5 Experiment Procedures 47 4.3 Data Analysis 48 4.3.1 Correlation Coefficients 48 4.3.2 Partial Correlation 49 4.3.3 Frequency Domain 50 4.4 Results & Discussion 51 CHARPTER 5 System Implementation II – Application in Sports Science 55 5.1 Postural Tremor in Air Pistol Shooting 55 5.2 System Setup and Experimental Procedures 55 5.2.1 Participants 55 5.2.2 Instrumentation 55 5.2.3 Experimental Paradigm 56 5.3 Data Analysis 57 5.4 Time-Frequency Representation of Tremor Signal 57 5.5 Discussion 62 CHAPTER 6 Conclusions and Future Development 63 REFERENCES 66 APPENDIX A Schematics of Tremor Signal Conditioning Circuits 72 APPENDIX B Power Quality Report in Decades- Frequency Variation 73 簡 歷 74 PUBLICATION LIST 75

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