博碩士論文 102522086 詳細資訊




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姓名 闕裕柏(Yu-Bo Que)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 虛擬實境肩關節復健系統之復健成效分析與預測
(The Performance Analysis and Prediction of a VR-based Shoulder Joint Rehabilitation System)
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摘要(中) 冰凍肩是臨床上常見的一種肩部疾病,其症狀主要是病患的肩關節活動度受限與肩部疼痛,導致日常生活功能受到影響。傳統評估冰凍肩需要依靠治療師對患者肩部及手臂進行各項目量測才能了解患者的狀況,受科技進步所賜,我們藉由結合虛擬實境、感測儀器等開發出的肩關節遊戲復健系統計紀錄患者的運動資訊,希望利用這些資訊,可以方便地讓治療師評估病患的情況,以及讓患者了解自己未來復健效果可能如何。
本研究將針對冰凍肩患者復健時的運動歷程進行分析,找出具有評估功能的運動指標,以及冰凍肩患者在整個復健療程上是否存在一定的特徵,找出模型並預測其未來進步幅度與角度。
實驗結果顯示,部分的運動指標的確對於傳統評估量表有著相當程度的關聯;在預測系統模型的建立,以現有的運動數據、臨床資料作訓練,最後確實也有著一定的準確率及辨識率,因此在建立預測系統模型是有一定的可行性的。
摘要(英) Frozen shoulder is a clinically common shoulder disease, and its main symptoms are the limit in the mobility of the shoulder joint of the patient and shoulder pain, resulting in daily living are affected. Traditionally, the assessment of frozen shoulder patients need to rely on the therapist for measuring each projects of shoulder and arm in order to understand the patient′s condition. By scientific and technological progress, we analyzed the patients’rehabilitation data recorded by the shoulder joint rehabilitation system which combining virtual reality and sensing instruments, etc. We hope to use this information, then we can easily make the therapist understand patients’ status, and make patients know what their future rehabilitation effects may be.
This study will find the motion index with evaluation capability. And if there are certain pattern in patients with frozen shoulder over the entire rehabilitation course, identifying the model and predicting their the future rate of progress and angle of the shoulder joint.
Experimental results show that part of the motion indices are indeed related to the traditional assessment scale; the establishment of forecasting model by training the existing motion data and clinical data has a certain accuracy and recognition rate, Therefore, the establishment of forecasting model is a certain degree of feasibility
關鍵字(中) ★ 虛擬實境
★ 冰凍肩
★ 肩關節復健
關鍵字(英) ★ Frozen shoulder
★ virtual reality
★ shoulder joint rehabilitation
論文目次 目 錄
中文摘要 i
英文摘要 ii
目 錄 iii
圖 目 錄 vii
表 目 錄 vii
第一章、緒論 1
1-1 背景介紹 1
1-1-1 冰凍肩的介紹與治療 1
1-1-2 虛擬實境 3
1-1-3 機器學習 3
1-2 研究動機 4
1-3 研究目的 6
第二章、文獻回顧 7
2-1 虛擬實境在醫療復健之應用 7
2-2 復健與運動指標相關研究 9
2-3 智能評估系統運用於復健相關研究 10
第三章、研究方法:系統設計 11
3-1 系統架構 11
3-2 Kinect版肩關節復健系統 11
3-3 IMU版肩關節復健系統 15
第四章、研究方法:實驗設計 21
4-1 收案對象與收案標準 21
4-2 實驗流程 22
4-3 實驗量測資料 22
4-3-1 臨床評估 22
4-3-2運動指標 23
4-4 分析方法(I) 運動指標有效性的評估 32
4-4-1 類神經網路 33
4-4-2 支持向量機(Support Vector Machine,SVM) 35
4-5 分析方法(II) 冰凍肩復健成效的預測 36
第五章、分析結果與討論 38
5-1系統復健成效及運動指標有效性的評估 38
5-2冰凍肩復健成效的預測 52
5-3冰凍肩復健成效預測的改良 67
第六章、結論 76
參考文獻 77
附錄一、Constant-Murley score(CMS) 85
附錄二、Thera-Band Color Progression (取自[51]) 86


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Available:http://slingshotforum.com/topic/39-thera-band-and-tube-resistance-elongation-chart/
指導教授 蘇木春(Mu-Chun Su) 審核日期 2015-7-29
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