使用肌電訊號預測腿部角度之初步研究

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姓名

黃和鈞(Ho-Chun Huang) 查詢紙本館藏

畢業系所

機械工程學系

論文名稱

使用肌電訊號預測腿部角度之初步研究

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至系統瀏覽論文 (2025-7-1以後開放)

摘要(中)

肌電訊號(electromyography)是人體的肌肉在收縮過程中所產生的生理訊號，此訊號會依人的動作不同而有不同的輸出電壓，因此可以藉由此訊號控制機械外骨骼或是估測人的意圖。
本研究透過兩通道的表面貼面電極，搭配自製的肌電訊號截取電路，量測大腿的股直肌與股外側肌兩塊肌肉的肌電訊號，再搭配均方根、平均絕對值及波形長度，對每塊肌肉萃取出三項特徵，再通過極限梯度提升法(eXtreme Gradient Boosting, XGBoost)建立與角度之間的模型

摘要(英)

Electromyography is a physiological signal generated by the muscles of the human body during the contraction process. This signal will have different output voltages depending on the person′s actions.Therefore, the signal can be used to control the mechanical exoskeleton or estimate the person′s intention. In this study , the rectus femoris and lateral femoris muscles electromyographic signal were be measured by two-channel surfacemounted electrodes with a self-made ectromyographic signal interception circuit and extracted the feature signals with the root mean square, mean absolute value and waveform length . Then use these feature signals to establish a model with eXtreme Gradient Boosting in order to predict angle.

關鍵字(中)

★ 肌電訊號
★ 機器學習
★ 下肢

關鍵字(英)

★ Electromyography
★ machine learning
★ Lower limbs

論文目次

中文摘要 ii
ABSTRACT iii
誌謝 iv
目錄 v
圖目錄 vii
表目錄 ix
一、緒論 1
1-1 研究背景 1
1-2 研究目的 1
1-3 文獻回顧 2
1-4 論文架構 3
二、背景與原理 4
2-1 肌電訊號之背景 4
2-2 肌電訊號產生與量測 4
2-3 肌電訊號特性 10
2-4 肌電訊號雜訊 11
三、研究方法 12
3-1 硬體設備與電路架構 12
3-1-1 角度感測器 12
3-1-2 電路架構 13
3-2 移動平均法 17
3-3 CART 原理說明 17
3-3-1 CART 生成方式 17
3-3-2 CART 剪枝 18
3-4 XGBoost 20
3-4-1 原理說明 20
3-4-2 參數說明 23
3-5 參數搜索 24
3-5-1 Grid Search 網格搜索演算法 25
3-5-2 RandomizedSearch 隨機搜索演算法 26
3-6 特徵值說明 26
四、實驗結果 28
4-1 前言 28
4-2 肌電訊號數值處理 28
4-3 特徵值與角度計算 32
4-4 使用之模型參數與模型預測結果 40
五、結論與未來展望 42
參考文獻 44

參考文獻

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指導教授

董必正

審核日期

2020-8-24

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