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研究生: 黃宗玄
Huang, Zong-Syuan
論文名稱: 運用三維光流虛擬實境系統於帕金森患者之動作訓練與評估
3D Virtual Reality with Optical Flow for Movement Training and Assessment of Subjects with Parkinson's Disease
指導教授: 陳家進
Chen, Jia-Jin
學位類別: 碩士
Master
系所名稱: 工學院 - 生物醫學工程學系
Department of BioMedical Engineering
論文出版年: 2013
畢業學年度: 101
語文別: 英文
論文頁數: 37
中文關鍵詞: 帕金森氏症虛擬實境平衡光流
外文關鍵詞: Parkinson’s disease, virtual reality, balance, optical flow
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  • 平衡能力的受損對於帕金森氏症患者來說是一項挑戰,例如病患無法保持穩定及姿勢轉移困難。接球任務訓練的特點是提供兼具眼手腳共同協調的動作,以提供帕金森氏症患者合宜的訓練計畫。最近的研究指出光流回饋能夠提供給受試者更多的視覺動態感並影響動作的表現。此發現引發我們運用光流刺激以協助帕金森氏症患者平衡能力的動機。因此,本研究之主要目的是發展一整合三維虛擬實境技術與視感覺資訊的光流回饋下,透過包含站立和跨前一步的接球任務以訓練帕金森氏症患者。另藉由放置在手腕、手肘和第三腰椎的慣性感測系統進行即時監控受測者的動作與姿勢變化以作為光流成效的驗證。此研究共收取了十五位奇美醫院復健部的帕金森氏症患者進行為期兩個月的實驗收案。並運用手臂軀幹動作及軀幹動作兩部分的參數作為平衡和姿勢控制的評判標準。實驗結果顯示:在站立前傾接球的任務下呈現較佳地手臂軀幹協調 (去協調指數: -79.2%)、較高地手臂對稱性 (相似性: +9.4%;疊合程度: +3.7%) 。另外,更平順地動作型態 (動作平順程度: +71.9%)、更大地軀幹前傾 (移動面積: +69.1%) 和較佳地姿勢穩定指數 (前傾角: +67.2%;維持時間: +23.7%) 等參數方面都獲得了顯著地改善。但針對兩組間軀幹前傾地移動方向並無顯著差異。此外,於跨前一步任務方面,帕金森氏症患者縮短了跨步時預期性姿勢調整的時間 (-30.1%),並且達到更大的前傾角度 (+55.8%),顯示了較佳的下肢移動之姿勢控制能力。此研究指出,光流的效果對於帕金森氏症患者而言,能夠提昇手臂軀幹的控制與平衡的動作表現。

    Impaired balance including inability to maintain stability and difficulty in postural transition is challenging in patients with Parkinson’s disease (PD). Ball catching movements are characterized by eye-hand-foot coordination, which are suitable training programs for PD patients. Recent studies have shown the benefits of optical flow to provide the PD subjects with motion perceptions and improve movement performance. The purpose of this study was to develop a 3D virtual reality (VR) training system for providing optical flow information during catching virtual balls under standing and one-step forward movements for subjects with PD. First, inertial motion sensors were attached on bilateral wrist, elbow and waist of subject to record the limb movement and the postural changes. Fifteen PD participants were recruited by the Chi Mei Medical Center. The arm-trunk movement and trunk movement were utilized as the assessment indices of balance and postural control. The derived parameters were compared between baseline data and those with optical flow. Our results showed significantly better arm-trunk coordination (Desynchrony score: -79.2%) and higher similarity of arm symmetry (Correlation coefficient: +9.4%; Matching area: +3.7%). Smoother movement pattern (Normalized Integrated Jerk: -71.9%), greater trunk sway (Elliptical area: +69.1%), and better postural stability index (Inclination angle: +67.2; Maintaining period: +23.7%) were also found during standing task. However, the differences in rotation angle of ellipse between assessments with and without optical flow conditions were not significant. In addition, PD subjects spent substantially less duration prior to gait initiation (Duration of the anticipatory postural adjustments: -30.1%) and achieved greater inclination angle (Inclination angle: +55.8%) on one-step forward task as well. This study indicated that inertial motion sensors with optical flow of VR could improve both arm-trunk control and balance on ball catching performance which has great potential as balance training system as well as assessment tool for PD subjects.

    摘要---- i Abstract------- ii 符號表-- iv 致謝--- v Contents------- vi List of Figures-------- viii List of Tables- x Chapter 1 Introduction- 1 1.1 Background- 1 1.2 Optical flow manipulation for treatment---- 2 1.3 Ball catching movement for postural evaluation----- 4 1.4 Inertial motion sensors for movement assessing----- 5 1.5 The aims of study-- 7 Chapter 2 Materials and Methods- 8 2.1 Development of 3D VR motor training system- 8 2.1.1 Design of VR testing environment- 8 2.1.2 DLP 3D projection system- 10 2.1.3 Inertial motion sensors-- 10 2.2 Movement data analysis using inertial motion sensors---- 11 2.2.1 Arm-trunk movement------- 12 2.2.2 Trunk movement--- 14 2.3 Experimental design-17 2.3.1 Subjects- 17 2.3.2 Experimental procedure--- 17 2.3.3 Statistical analysis----- 19 Chapter 3 Results------ 20 3.1 Participants recruitment--- 20 3.2 Arm-trunk movement analysis in standing task------- 20 3.2.1 Assessment using arm-trunk coordination-- 20 3.2.2 Assessment using arm symmetry---- 21 3.3 Trunk movement analysis in standing task--- 22 3.3.1 Assessment using movement smoothness----- 22 3.3.2 Assessment using trunk sway------ 23 3.3.3 Assessment using postural stability index of standing- 25 3.4 Trunk movement analysis in one-step forward task-- 26 3.4.1 Assessment using postural stability index of one-step- 26 3.5 Statistical analysis------- 27 Chapter 4 Discussion and Conclusion---- 29 4.1 Arm-trunk movement parameters in standing task----- 29 4.2 Trunk movement parameters in standing task- 30 4.3 Trunk movement parameters in one-step forward task- 32 4.4 Study limitation--- 32 4.5 Conclusion- 33 References----- 34

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