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研究生:高文偉
研究生(外文):Man-Wai Kou
論文名稱:隨機共振電刺激對動作學習及大腦活性之影響
論文名稱(外文):Effects of Stochastic Resonance Electrical Stimulation on Motor Learning and Brain Activity
指導教授:周立偉周立偉引用關係
指導教授(外文):Li-Wei Chou
學位類別:碩士
校院名稱:國立陽明大學
系所名稱:物理治療暨輔助科技學系
學門:醫藥衛生學門
學類:復健醫學學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:66
中文關鍵詞:動作學習隨機共振電刺激腦電波肌電圖共調性
外文關鍵詞:motor learningstochastic resonance electrical stimulationEEGEMGcoherence
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研究背景
  動作學習指經由練習或經驗而產生運動表現相對永久性改變之過程。在一系列的學習過程中,可透過表現回饋功能來修正錯誤的動作行為及增進動作能力,且造成持久性的改變,從而適應各種複雜的動作任務。此外,臨床上改善中樞神經系統損傷患者動作再學習能力及運動表現可顯著提升患者的生活品質,因此如何有效提升動作學習成為了一個被廣泛研究的議題。體感覺輸入在動作學習上扮演著很重要的角色,許多研究證實,週邊電刺激藉由產生大量感覺訊號的回傳可誘發大腦運動皮質區的活性,進而提升運動表現。
  近年來,已有文獻指出隨機共振刺激可以影響視覺、聽覺或觸覺等感覺系統的功能,且應用在健康成年人及中樞神經系統損傷患者上發現平衡等動作能力表現的提升;也有學者發現隨機共振電刺激於週邊肌肉可同時增加運動表現、大腦運動皮質區腦波頻譜密度、以及皮質肌肉共調性。
  儘管有大量的研究在探討電刺激對於運動皮質興奮性及運動表現的效果,但尚未有研究探討隨機共振電刺激對於動作學習之影響,以及是否在動作學習期間同時提供隨機共振電刺激將有更好之動作學習成效。
研究目的
  本研究主要目的為探討隨機共振電刺激對動作學習之成效及學習過程中大腦皮質活性之效應,並以握力的動作任務表現及腦波-肌電圖共調性作為測試方法。
研究方法
  本研究共招募16位健康成年人為受試者,接受有無隨機共振電刺激對動作學習效應的實驗。實驗分兩天進行,受試者隨機參與兩種不同實驗狀態之動作學習測試,包含隨機共振電刺激及偽電刺激。實驗開始前先找出受試者之最佳電刺激強度,在隨機共振電刺激狀態會提供最佳強度之隨機共振電刺激,而偽電刺激狀態則沒有電流輸出。測試時,受試者產生握力以吻合螢幕出現振幅為10, 20及30%最大自主握力,週期為0.5Hz之連續正弦波的目標力量,出現之順序為20, 30及10%,每個力量重覆2次。每次測試一回合25秒,重覆4回合,共測試兩次,第一次測試為動作學習當下,第二次測試為動作學習後。以受試者實際產生的握力與目標力量間之誤差計算來代表力量表現,學會握力動作任務所需之時間快慢來代表學習效率,力量表現越好且學習效率越快表示有更好之動作學習成效。受試者進行動作學習測試同時記錄腦波電訊號及表面肌電訊號,並以腦波能量頻譜密度及皮質肌肉共調性之方式呈現。
統計分析
  本研究以二因子重複變異數分析來比較兩個實驗狀態間動作學習當下以及動作學習後力量表現之差異及大腦活性的變化。統計顯著水準設定在α = 0.05。
結果
  隨機共振電刺激顯著提升動作學習當下以及動作學習後之力量表現(p=0.001, p=0.002),並顯著提升動作學習效率(p=0.038)。大腦活性方面,在偽電刺激的狀態下,動作學習後γ頻帶峰值與β頻帶面積值皆顯著下降(p=0.020, p=0.001)。而在動作學習當下提供隨機共振電刺激,γ頻帶峰值與β頻帶面積值皆顯著下降(p=0.047, p=0.019)。
討論與結論
  本研究證實了提供隨機共振電刺激確實能有更好之動作學習成效。我們認為隨機共振電刺激提升了大腦皮質興奮性,以致在動作學習當下力量表現之進步且有更好的學習效率。而在動作學習後,感覺運動整合能力已處於活化狀態或感覺運動整合能力較佳,以致大腦活性沒有明顯的變化。
Background
  Motor learning refers to the process of generating relatively permanent changes in motor performance through practice or experience. In a series of learning processes, the performance feedback function can be used to modify incorrect motor behaviors and increase motor ability, and cause permanent changes to adapt various complex motor tasks. In addition, clinically improving the motor re-learning ability and motor performance of patients with central nervous system (CNS) injury can significantly increase patients’ quality of life. Therefore, motor learning is a widely studied topic. Somatosensory input plays a very important role in motor learning. Lots of studies suggested that peripheral electrical stimulation can induce motor cortex excitability by generating a large amount of sensory afferent inputs, thereby improving motor performance.
  In recent years, the literature has been pointed out that stochastic resonance electrical stimulation (SRES) can affect the functions of sensory systems such as vision, hearing, or touch. It has been applied to healthy adults and CNS injury patients can improve their motor performance and balance ability. Some scholars have found that SRES to peripheral muscles can simultaneously increase motor performance, power spectral density of motor cortex, and corticomuscular coherence.
  Although there are a large number of studies investigate the effects of electrical stimulation on the excitability of motor cortex and motor performance, but the effects of stochastic resonance electrical stimulation (SRES) on motor learning remained unknown.
Objective
  The purpose of present study is to investigate the effects of SRES on motor learning and brain activity during learning process. The grip force performance of the motor task and the EEG-EMG coherence were used as test methods.
Methods
  A total of 16 healthy adults were recruited to accept the experiment of the effects of SRES on motor learning. The experiment was conducted in 2 days. Subjects randomly participated in the motor learning test in 2 different experimental conditions, including SRES and sham electrical stimulation. The optimal electrical stimulation intensity of each subject was determined before the experiment starts. The optimal intensity SRES was provided during the SRES condition, while the sham electrical stimulation condition had no current output. During the test, the subject produced grip force to match the target force with a continuous sine wave with amplitude of 10, 20 and 30% maximal voluntary isometric contraction (MVIC) and period of 0.5Hz appearing on the screen. The sequence of appearance was 20, 30 and 10%, each force repeat 2 times. Each test is 25 seconds in one round and repeated 4 rounds. There were 2 tests in total. The first test was defined as during motor learning, the second test was defined as after motor learning. The calculation of the error between the actual grip force produced by the subject and the target force represents the force performance. The time required to learn the grip force motor task represents the learning efficiency. The finer force performance and the faster learning efficiency represents the better effectiveness of motor learning. The subjects performed a motor learning test while recording EEG and EMG signals, and analyzed them in EEG power spectrum and EEG-EMG coherence.
Statistical analysis
  Two-way repeated measures ANOVA was used to compare the difference in force performance and changes in brain activity during and after motor learning among 2 conditions. The significant level is set at
α = 0.05.
Results
  SRES significantly increased motor performance during and after motor learning (p=0.001, p=0.002), and the efficiency of motor learning (p=0.038). At brain activity, in the sham electrical stimulation condition, the peak value of γ band and the area value of β band decreased significantly after motor learning (p=0.020, p=0.001). Provided the SRES during motor learning, the peak value of the γ band and the area value of the β band both decrease significantly (p=0.047, p=0.019).
Discussion and conclusion
  We confirm that providing SRES can indeed have better effectiveness of motor learning. We believe that SRES can increase the excitability of the cerebral cortex, enhance force performance during motor learning and have better learning efficiency. After the motor learning, the sensorimotor integration in the activated state or is better, so there is no obvious change in brain activity.
目錄
中文摘要 iv
Abstract vii
圖目錄 x
表目錄 xi
中、英文重要字彙對照表 xii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究假設 4
第四節 重要性 4
第二章 文獻回顧 5
第一節 動作學習 5
第二節 體感覺輸入對動作學習之影響 6
第三節 週邊電刺激對中樞系統之影響 7
第四節 隨機共振刺激之臨床應用 9
第五節 感覺運動系統整合機制 11
第六節 腦波及大腦皮質肌肉共調性 12
第七節 總結 14
第三章 研究方法 15
第一節 研究設計 15
第二節 研究對象 15
第三節 實驗流程 16
第四節 資料蒐集 17
第五節 資料處理 19
3.5.1 力量控制表現 19
3.5.2 動作學習效率 19
3.5.3 皮質肌肉共調性 20
3.5.4 腦波能量頻譜密度 20
3.5.5 資料分析 21
第六節 統計分析 22
第四章 結果 23
第一節 受試者基本資料 23
第二節 力量控制表現及動作學習效率 23
4.2.1 動作學習當下及動作學習後之力量表現 23
4.2.2 動作學習效率 23
第三節 皮質肌肉共調性 24
4.3.1 α頻帶尖峰值 24
4.3.2 β頻帶尖峰值 24
4.3.3 γ頻帶尖峰值 24
第四節 腦波能量頻譜密度 25
4.4.1手部動作之大腦運動皮質區(C3電極) 25
4.4.2 雙側感覺運動皮質區(PCA) 26
第五節 相關性 27
4.5.1 力量表現與共調性之相關性 27
4.5.2 力量表現與腦波能量頻譜密度之相關性 27
第五章 討論 29
第一節 受試者 29
第二節 隨機共振電刺激對力量表現之影響 29
第三節 隨機共振電刺激對共調性之影響 31
第四節 隨機共振電刺激對腦波能量頻譜密度之影響 33
第五節 力量表現與大腦活性變化之相關性 36
第六節 研究限制與未來研究之建議 36
第六章 結論 38
參考文獻 39
附圖 45
附表 52
附錄 56

圖目錄
圖1 傳統電刺激與隨機共振電刺激波型比較 45
圖2 實驗流程 45
圖3 動作學習實驗 46
圖4 握力計 46
圖5 腦波儀 46
圖6 腦波、肌電圖電極位置 47
圖7 無線肌電圖 47
圖8 電刺激儀器 48
圖9 學習效率計算方式 48
圖10 動作學習力量表現比較 49
圖11 動作學習效率比較 49
圖12 皮質肌肉共調性比較 50
圖13 腦波能量頻譜密度(C3)比較 50
圖14 腦波能量頻譜密度(PCA)比較 51
圖15 力量表現與共調性之相關性 51

表目錄
表1 受試者基本資料 52
表2 力量表現比較 53
表3 動作學習效率比較 53
表4 皮質肌肉共調性比較 53
表5 腦波能量頻譜密度(C3)比較 54
表6 腦波能量頻譜密度(PCA)比較 54
表7 力量表現與共調性之相關性 55
表8 力量表現與腦波能量頻譜密度(C3)之相關性 55
表9 力量表現與腦波能量頻譜密度(PCA)之相關性 55
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