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研究生:韓紹禮
研究生(外文):Shao-Li Han
論文名稱:以慣性感測器量化中風病患下肢運動能力暨功能分級之研究
指導教授:潘敏俊
學位類別:博士
校院名稱:國立中央大學
系所名稱:機械工程學系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:83
中文關鍵詞:功能量表步態分析穿戴式裝具腦中風慣性感測器臨床評估
外文關鍵詞:functional assessmentgait analysiswearable devicestrokeinertial sensorclinical assessment
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本論文在探討使用穿戴式裝具來量化中風受試者的神經恢復等級與日常生活失能的程度,目的在使用穿戴式裝具以達成降低醫療專業人員評估病患的負擔。論文分為兩大部分,一是使用整合表面肌電圖與慣性感測器來預測神經的分級,另一部分則是使用慣性感測器來推論中風受試者神經恢復分級與生活功能的等級。
第一部份先使用不同機器學習演算法,結合表面肌電圖與慣性感測器,分類神經恢復的等級;其次基於此研究結果,嘗試使用一顆放在足背的慣性感測器,作為預測神經恢復分級的方式;第二部分則是使用4顆慣性感測器來擷取運動學資料,並進行臨床常用的10公尺步行測試,推論運動學與神經恢復等級以及日常生活能力障礙相關性,同時也提出新的步態對稱指標,使用受試者身高來修正對稱指數,用來推論受試者的失能與恢復狀況。
第一部分的試驗結果顯示,結合表面肌電圖與慣性感測器的演算法中,無論是支援向量機(Support Vector Machine, SVM)、k-近鄰演算法(k-Nearest Neighbor, k-NN)以及類神經網路(Artificial Neural Network, ANN)均可達不錯的分級能力,正確率範圍在82.86%到100%;其中以支援向量機的正確性最佳,高達92.5%到100%;最後使用單一顆慣性感測器結合運動生理學的演算法,正確率從86.8%到100%。
第二部分,結果顯示平均步行測試與傅格-梅爾量表下肢部分及伯格平衡量表均存在中度的正相關,相關係數分別為0.62與0.68;使用修正後步態對稱指數,與傅格-梅爾量表下肢部分和伯格平衡量表則呈現中度的負相關,相關係數傅格-梅爾量表下肢部分為-0.51,而伯格平衡量表為-0.52,顯示修正後步態對稱指數,具有可推論神經學與平衡恢復的能力。
綜上所述,從結合兩種感測器到最後使用4顆慣性感測器的研究,可以看出使用慣性感測器結合中風生理學的恢復特性,有機會用來推論受試者的神經恢復與日常失能的等級。修正後步態對稱指數則值得進一步探討與中風病患日常生活功能缺陷的關係。
In this thesis, two serial studies attempted to quantify neurological and functional defects by correlating clinical assessment scales and kinematics obtained from wearable devices, including surface electromyography and inertial sensors. This thesis contains two domains. One includes classifying neurological recovery status by integrating surface electromyography and inertial sensors to classify clinical Brunnstrom stages. Then, we managed to classify the neurological level through a single inertial sensor.
The results explore that the Support Vector Machine has the best accuracy in classifying the Brunnstrom stage than k-Nearest Neighbor and the Artificial Neural Network. The overall accuracy ranges from 82.86% to 100%, while the Support Vector Machine owns an accuracy ranging from 92.5% to 100%. Additionally, after adopting the threshold values, we get a good accuracy, ranging from 86.78% to 100% among different stages, to classify the Brunnstrom stages, by using a single inertial sensor on the subjects’ feet. This system has been proven feasible for predicting the lower limb Brunnstrom stage for hemiparetic and hemiplegic patients.
The other domain correlates clinical assessment scales and gait parameters from a 10-m walk test. In addition to gait parameters, we also set up a modified gait symmetric index to infer functional recovery results, the Fugl-Meyer assessment scale, and the Berg balance scale. These results explore only the average walking speeds correlate moderately with these two scales (γ = 0.62, 0.68, n = 23), while the modified gait symmetry index owns the moderate negative correlation(γ =-0.51, -0.52, n=23).
Conclusively, with appropriate algorithms and suitable locations to deploy inertial sensors, inertial-based wearable devices demonstrate promising applications in classifying neuromotor and functional recovery among patients after stroke. The modified gait symmetry index warrants further exploring the possibility of inferring functional recovery.
中文摘要 i
Abstract ii
致謝 iii
表目錄 vii
圖目錄 viii
一、 緒論 1
1-1 研究動機與目的 1
1-2 文獻探討 2
1-3 論文主題與研究方向 6
二、 理論基礎 8
2-1 中風恢復的神經學順序 8
2-2 評估量表的建立 8
2-3 現行臨床評估工具的優缺點 10
2-3-1 肌肉力量 10
2-3-2 活動角度 11
2-3-3 肌肉痙攣測試 12
2-3-4 布朗氏神經肌肉恢復分級 13
2-3-5 傅格-梅爾評估量表 14
2-3-6 伯格平衡量表 15
2-3-7 步行測試 17
2-4 動作分析常見的感測器以及原理 19
2-4-1 攝影機與力板 19
2-4-2 表面肌電圖 20
2-4-3 慣性感測器 21
2-5 整合感測器與臨床測試量表 22
2-5-1 神經恢復量表來推論運動學 22
2-5-2 運動學來推論神經恢復量表 23
2-6 目前的趨勢與優缺點 23
三、 運動訊號與神經學分級的關係 25
3-1 結合表面肌電圖與慣性感測器 25
3-2 試驗架構 25
3-3 設計的動作 26
3-3-1 慣性感測器模組 28
3-3-2 表面肌電圖儀器以及相關參數 29
3-3-3 受試對象 31
3-4 研究倫理 32
3-5 相關演算法 32
3-6 結果分析與討論 35
四、 單顆慣性感測器用於神經學分級 37
4-1 運動資料擷取與流程 37
4-2 演算模式的原理 37
4-3 尋找閥值與數據分析 39
4-4 統計結果 40
4-5 討論 41
五、 運動學資料推論功能量表 43
5-1 建立新的感測器模組與驗證 43
5-1-1 慣性感測器模組 43
5-1-2 資料傳輸 45
5-1-3 測量角度驗證 45
5-1-4 臨床實際測試 48
5-1-5 實驗流程 48
5-1-6 大域座標系與局部座標系 49
5-1-7 穿戴感測器 50
5-1-8 關節活動角度計算 51
5-1-9 運動學參數 53
5-2 收案對象 55
5-3 檢定樣本數與統計分析方式 55
5-4 測試方法 56
5-5 研究倫理 57
5-6 統計結果 57
5-7 結果分析與討論 61
六、 結論與未來展望 64
七、 參考文獻 66
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