虛擬實境中風復健系統之上肢運動成效評估與運動分析

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馮恒諺(Heng-yan Fong) 查詢紙本館藏

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論文名稱

虛擬實境中風復健系統之上肢運動成效評估與運動分析

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摘要(中)

在這數十年間，中風一直是全球重要的疾病之一，尤其是步入高齡化社會的已開發國家，隨著醫療進步，老年人口漸多，中風問題也日漸受重視。本研究針對上肢中風復健進行各項指標分析，嘗試找出可供治療師進行評估參考的資訊。
研究中分為兩大部分，第一是找出對應到本系統的各項運動指標，並且分析運動指標對於臨床評估量表會有何影響；第二是運動指標建立後，以大量病人的數據做為群體樣本利用圖形識別的方法，如類神經網路與支持向量機進行分類。有別於臨床評估量表必須進行多個測試，才能得知病人的級別分類，我們可以直接透過遊戲的結果與系統所截取的運動數據進行分析即可得到病人的分類狀況。
本研究結果顯示，部分的運動指標確實對於評估成果有著相當程度的影響，並且病人在遊戲後對於運動指標的數值也有著明確的進步。在分類系統模型的建立，以現有的運動數據進行分類，確實也有著一定的辨識率，因此在建立分類系統模型是有一定的可行性的。

摘要(英)

In the past decades, stroke has been one of the world′s major diseases. Especially in the developed countries and aging society, with medical advances, an increasing elderly population, stroke problems are increasingly valued. In this study, we analyzed the different motor index for the stroke rehabilitation with upper extremity, try to find a new indicators information for therapists.
Study is divided into two parts, the first is to identify motor index that correspond to the movement of the system, and analyzed if the motor index would impact result of clinical assessment scale. The second, when found out the motor index, we used large number of patient′s data to classify groups with pattern recognition, like neural network or SVM. Unlike clinical assessment scale multiple tests must be carried out in order to know the patient′s level of classification, we can analyze the patient′s classification status can be obtained directly through the game′s outcome and the motor index of data with system.
The results of this study shows that part of the motor index for assessment scale have a considerable degree of influence. And after rehabilitation, the numerical of motor index also has definite progress. We used motor data that collected in system to establishing classification model also has a certain recognition rate. Thus establishing the classification model is a certain degree of feasibility.

關鍵字(中)

★ 中風復健
★ 虛擬實境
★ 圖形識別
★ 類神經網路
★ 支持向量機
★ 動態追蹤

關鍵字(英)

★ Stroke rehabilitation
★ virtual reality
★ virtual environment
★ pattern recognition
★ neural network
★ support vector machine
★ SVM
★ motor track

論文目次

中文摘要 i
Abstract ii
目錄 iii
圖目錄 vi
表目錄 viii
第一章　緒論 1
1.1　研究背景 1
1.2　研究動機 5
1.3　研究目的 7
第二章　文獻回顧 8
2.1　虛擬實境於中風復健相關研究 8
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中風復健相關研究 10
第三章　研究方法 12
3.1　系統設計 12
3.1.1　肩肘運動－上臂延伸復健系統 12
3.1.2　肩肘運動－上臂雙側協調運動復健系統 14
3.1.3　前臂運動復健系統 15
3.1.4　手腕運動復健系統 17
3.1.5　肩肘運動－上臂對角線往復伸展運動復健遊戲 19
3.2　實驗設計 23
3.2.1　收案標準 23
3.2.2　實驗流程 24
3.3　資料量測內容 25
3.3.1　臨床評估量表 25
3.3.2　運動指標 26
3.4　分析方法(I)：復健成效分析 35
3.5　分析方法(II)：新型運動指標驗證 36
3.5.1　無母數統計分析 36
3.5.2　相關性分析 36
3.6　分析方法(III)：智能運算為基礎之運動功能評估與分級方法 37
3.6.1　群聚分析 38
3.6.2　類神經網路 40
3.6.3　支持向量機(Support Vector Machine, SVM) 41
第四章　分析結果與討論 42
4.1　肩肘運動－上臂延伸復健系統 42
4.1.1　無母數統計分析 42
4.1.2　相關性分析 45
4.1.3　群聚分析 47
4.1.4　類神經網路 48
4.1.5　SVM 49
4.2　肩肘運動－上臂雙側協調運動復健系統 50
4.2.1　無母數統計分析 50
4.2.2　相關性分析 55
4.2.3　群聚分析 57
4.2.4　類神經網路 58
4.2.5　SVM 59
4.3　前臂運動復健系統 60
4.3.1　無母數統計分析 60
4.3.2　相關性分析 62
4.3.3　群聚分析 63
4.3.4　類神經網路 65
4.3.5　SVM 65
4.4　手腕運動復健系統 66
4.4.1　無母數統計分析 66
4.4.2　相關性分析 68
4.4.3　群聚分析 69
4.4.4　類神經網路 71
4.4.5　SVM 71
4.5　肩肘運動－上臂對角線往復伸展運動復健系統 72
4.5.1　無母數統計分析 72
4.5.2　相關性分析 74
4.5.3　群聚分析 75
4.5.4　類神經網路 76
4.5.5　SVM 77
4.6　討論 78
4.6.1　復健系統成效與運動指標相關性 78
4.6.2　群聚分析與辨識模型 79
第五章　結論 81
參考文獻 82

參考文獻

[1] V. L. Feigin, C. M. Lawes, D. A. Bennett, and C. S. Anderson, "Stroke epidemiology: a review of population-based studies of incidence, prevalence, and case-fatality in the late 20th century," Lancet Neurol, vol. 2, pp. 43-53, Jan 2003.
[2] V. L. Feigin, C. M. Lawes, D. A. Bennett, S. L. Barker-Collo, and V. Parag, "Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review," Lancet Neurol, vol. 8, pp. 355-69, Apr 2009.
[3] M. Vestling, B. Tufvesson, and S. Iwarsson, "Indicators for return to work after stroke and the importance of work for subjective well-being and life satisfaction," J Rehabil Med, vol. 35, pp. 127-31, May 2003.
[4] C. Hofgren, A. Bjorkdahl, E. Esbjornsson, and K. S. Sunnerhagen, "Recovery after stroke: cognition, ADL function and return to work," Acta Neurol Scand, vol. 115, pp. 73-80, Feb 2007.
[5] G. Andersen, D. Christensen, M. Kirkevold, and S. P. Johnsen, "Post-stroke fatigue and return to work: a 2-year follow-up," Acta Neurol Scand, vol. 125, pp. 248-53, Apr 2012.
[6] T. Kauranen, K. Turunen, S. Laari, S. Mustanoja, P. Baumann, and E. Poutiainen, "The severity of cognitive deficits predicts return to work after a first-ever ischaemic stroke," J Neurol Neurosurg Psychiatry, vol. 84, pp. 316-21, Mar 2013.
[7] I. Mosley, M. Nicol, G. Donnan, A. G. Thrift, and H. M. Dewey, "What is stroke symptom knowledge?," International Journal of Stroke, vol. 9, pp. 48-52, Jan 2014.
[8] R. Kalawsky, The Science of Virtual Reality and Virtual Environments: Addison-Wesley Longman Publishing Co., Inc., 1993.
[9] K. Laver, S. George, S. Thomas, J. E. Deutsch, and M. Crotty, "Virtual Reality for Stroke Rehabilitation," Stroke, vol. 43, pp. e20-e21, February 1, 2012 2012.
[10] C. J. Bohil, B. Alicea, and F. A. Biocca, "Virtual reality in neuroscience research and therapy," Nat Rev Neurosci, vol. 12, pp. 752-62, Dec 2011.
[11] G. C. Burdea, G. C. Burdea, and C. Burdea, Force and touch feedback for virtual reality: Wiley New York, 1996.
[12] J. J. Hopfield, "Neural networks and physical systems with emergent collective computational abilities," Proceedings of the national academy of sciences, vol. 79, pp. 2554-2558, 1982.
[13] C. Cortes and V. Vapnik, "Support-Vector Networks," Mach. Learn., vol. 20, pp. 273-297, 1995.
[14] A. S. Merians, D. Jack, R. Boian, M. Tremaine, G. C. Burdea, S. V. Adamovich, et al., "Virtual reality-augmented rehabilitation for patients following stroke," Phys Ther, vol. 82, pp. 898-915, Sep 2002.
[15] H. C. Fischer, K. Stubblefield, T. Kline, X. Luo, R. V. Kenyon, and D. G. Kamper, "Hand rehabilitation following stroke: a pilot study of assisted finger extension training in a virtual environment," Top Stroke Rehabil, vol. 14, pp. 1-12, Jan-Feb 2007.
[16] D. Meldrum, A. Glennon, S. Herdman, D. Murray, and R. McConn-Walsh, "Virtual reality rehabilitation of balance: assessment of the usability of the Nintendo Wii((R)) Fit Plus," Disabil Rehabil Assist Technol, vol. 7, pp. 205-10, May 2012.
[17] J. P. Cuthbert, K. Staniszewski, K. Hays, D. Gerber, A. Natale, and D. O′Dell, "Virtual reality-based therapy for the treatment of balance deficits in patients receiving inpatient rehabilitation for traumatic brain injury," Brain Inj, vol. 28, pp. 181-8, 2014.
[18] B. Wiederhold and G. Riva, "Balance recovery through virtual stepping exercises using Kinect skeleton tracking: a follow-up study with chronic stroke patients," Annual Review of Cybertherapy and Telemedicine 2012: Advanced Technologies in the Behavioral, Social and Neurosciences, vol. 181, p. 108, 2012.
[19] H. Sin and G. Lee, "Additional Virtual Reality Training Using Xbox Kinect in Stroke Survivors with Hemiplegia," American Journal of Physical Medicine & Rehabilitation, vol. 92, pp. 871-880 10.1097/PHM.0b013e3182a38e40, 2013.
[20] J. Crosbie, S. Lennon, M. McGoldrick, M. McNeill, and S. McDonough, "Virtual reality in the rehabilitation of the arm after hemiplegic stroke: a randomized controlled pilot study," Clinical Rehabilitation, vol. 26, pp. 798-806, September 1, 2012 2012.
[21] K. H. Cho, K. J. Lee, and C. H. Song, "Virtual-Reality Balance Training with a Video-Game System Improves Dynamic Balance in Chronic Stroke Patients," The Tohoku Journal of Experimental Medicine, vol. 228, pp. 69-74, 2012.
[22] A. Turolla, M. Dam, L. Ventura, P. Tonin, M. Agostini, C. Zucconi, et al., "Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial," Journal of neuroengineering and rehabilitation, vol. 10, p. 85, 2013.
[23] A. Jacobs, A. Timmermans, M. Michielsen, M. V. Plaetse, and P. Markopoulos, "CONTRAST: gamification of arm-hand training for stroke survivors," presented at the CHI ′13 Extended Abstracts on Human Factors in Computing Systems, Paris, France, 2013.
[24] H. M. Hondori, M. Khademi, L. Dodakian, S. C. Cramer, and C. V. Lopes, "A Spatial Augmented Reality rehab system for post-stroke hand rehabilitation," in MMVR, 2013, pp. 279-285.
[25] A. Panarese, R. Colombo, I. Sterpi, F. Pisano, and S. Micera, "Tracking Motor Improvement at the Subtask Level During Robot-Aided Neurorehabilitation of Stroke Patients," Neurorehabilitation and Neural Repair, vol. 26, pp. 822-833, Sep 2012.
[26] Q. Ding, I. H. Stevenson, N. Wang, W. Li, Y. Sun, Q. Wang, et al., "Motion games improve balance control in stroke survivors: A preliminary study based on the principle of constraint-induced movement therapy," Displays, vol. 34, pp. 125-131, 4// 2013.
[27] I. Pastor, H. A. Hayes, and S. J. Bamberg, "A feasibility study of an upper limb rehabilitation system using Kinect and computer games," Conf Proc IEEE Eng Med Biol Soc, vol. 2012, pp. 1286-9, 2012.
[28] S. Hoermann, L. Hale, S. J. Winser, and H. Regenbrecht, "Augmented reflection technology for stroke rehabilitation–a clinical feasibility study," in Proceedings of the 9th International Conference on Disability, Virtual Reality and Associated Technologies (ICDVRAT 2012), Laval, France, 2012, pp. 10-12.
[29] M. Duff, Y. Chen, L. Cheng, S.-M. Liu, P. Blake, S. L. Wolf, et al., "Adaptive Mixed Reality Rehabilitation Improves Quality of Reaching Movements More Than Traditional Reaching Therapy Following Stroke," Neurorehabilitation and Neural Repair, December 3, 2012 2012.
[30] X. Zhang and P. Zhou, "High-density myoelectric pattern recognition toward improved stroke rehabilitation," Biomedical Engineering, IEEE Transactions on, vol. 59, pp. 1649-1657, 2012.
[31] B. Cesqui, P. Tropea, S. Micera, and H. Krebs, "EMG-based pattern recognition approach in post stroke robot-aided rehabilitation: a feasibility study," Journal of NeuroEngineering and Rehabilitation, vol. 10, p. 75, 2013.
[32] 陳佑宗, 以虛擬實境為基礎之上肢中風復健分析與研究: master, Department of Computer Science & Information Engineering, National Central University, 2012.
[33] A. A. Rizzo, T. Bowerly, J. G. Buckwalter, D. Klimchuk, R. Mitura, and T. D. Parsons, "A virtual reality scenario for all seasons: the virtual classroom," CNS Spectr, vol. 11, pp. 35-44, Jan 2006.
[34] J. Edmans, J. Gladman, D. Hilton, M. Walker, A. Sunderland, S. Cobb, et al., "Clinical evaluation of a non-immersive virtual environment in stroke rehabilitation," Clin Rehabil, vol. 23, pp. 106-16, Feb 2009.
[35] L. Piron, P. Tonin, F. Piccione, V. Iaia, E. Trivello, and M. Dam, "Virtual environment training therapy for arm motor rehabilitation," Presence-Teleoperators and Virtual Environments, vol. 14, pp. 732-740, Dec 2005.
[36] D. Jack, R. Boian, A. S. Merians, M. Tremaine, G. C. Burdea, S. V. Adamovich, et al., "Virtual reality-enhanced stroke rehabilitation," IEEE Trans Neural Syst Rehabil Eng, vol. 9, pp. 308-18, Sep 2001.
[37] K. I. Ustinova, W. A. Leonard, N. D. Cassavaugh, and C. D. Ingersoll, "Development of a 3D immersive videogame to improve arm-postural coordination in patients with TBI," J Neuroeng Rehabil, vol. 8, p. 61, 2011.
[38] J. E. Deutsch, M. Borbely, J. Filler, K. Huhn, and P. Guarrera-Bowlby, "Use of a low-cost, commercially available gaming console (Wii) for rehabilitation of an adolescent with cerebral palsy," Phys Ther, vol. 88, pp. 1196-207, Oct 2008.
[39] G. Saposnik, R. Teasell, M. Mamdani, J. Hall, W. McIlroy, D. Cheung, et al., "Effectiveness of virtual reality using Wii gaming technology in stroke rehabilitation: a pilot randomized clinical trial and proof of principle," Stroke, vol. 41, pp. 1477-84, Jul 2010.
[40] B. Lange, C. Y. Chang, E. Suma, B. Newman, A. S. Rizzo, and M. Bolas, "Development and evaluation of low cost game-based balance rehabilitation tool using the Microsoft Kinect sensor," Conf Proc IEEE Eng Med Biol Soc, vol. 2011, pp. 1831-4, 2011.
[41] J. M. Ibarra Zannatha, A. J. Tamayo, A. D. Sanchez, J. E. Delgado, L. E. Cheu, and W. A. Arevalo, "Development of a system based on 3D vision, interactive virtual environments, ergonometric signals and a humanoid for stroke rehabilitation," Comput Methods Programs Biomed, vol. 112, pp. 239-49, Nov 2013.
[42] H. Zhou and H. Hu, "Inertial motion tracking of human arm movements in stroke rehabilitation," in Mechatronics and Automation, 2005 IEEE International Conference, 2005, pp. 1306-1311.
[43] A. Chiri, N. Vitiello, F. Giovacchini, S. Roccella, F. Vecchi, and M. C. Carrozza, "Mechatronic Design and Characterization of the Index Finger Module of a Hand Exoskeleton for Post-Stroke Rehabilitation," Mechatronics, IEEE/ASME Transactions on, vol. 17, pp. 884-894, 2012.
[44] F. Delbressine, A. Timmermans, L. Beursgens, M. de Jong, A. van Dam, D. Verweij, et al., "Motivating arm-hand use for stroke patients by serious games," in 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012.
[45] A. R. Fugl-Meyer, L. Jaasko, I. Leyman, S. Olsson, and S. Steglind, "The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance," Scand J Rehabil Med, vol. 7, pp. 13-31, 1975.
[46] D. M. Morris, G. Uswatte, J. E. Crago, E. W. Cook, 3rd, and E. Taub, "The reliability of the wolf motor function test for assessing upper extremity function after stroke," Arch Phys Med Rehabil, vol. 82, pp. 750-5, Jun 2001.
[47] J. Desrosiers, R. Hébert, E. Dutil, and G. Bravo, "Development and Reliability of an Upper Extremity Function Test for the Elderly: The TEMPA," Canadian Journal of Occupational Therapy, vol. 60, pp. 9-16, April 1, 1993 1993.
[48] F. Wilcoxon, "Individual comparisons by ranking methods," Biometrics bulletin, pp. 80-83, 1945.
[49] C. Spearman, "The proof and measurement of association between two things," The American journal of psychology, vol. 15, pp. 72-101, 1904.
[50] R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis. New Yotk: John Willey & Sons, 1973.
[51] A. K. Jain and R. C. Dubes, Algorithms for clustering data: Prentice-Hall, Inc., 1988.
[52] J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques: Morgan Kaufmann Publishers Inc., 2011.
[53] J. MacQueen, "Some methods for classification and analysis of multivariate observations," in Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, 1967, pp. 281-297.
[54] P. Rousseeuw, "Silhouettes: a graphical aid to the interpretation and validation of cluster analysis," J. Comput. Appl. Math., vol. 20, pp. 53-65, 1987.
[55] S. Haykin, Neural Networks: A Comprehensive Foundation: Prentice Hall PTR, 1994.
[56] R.-E. Fan, P.-H. Chen, and C.-J. Lin, "Working Set Selection Using Second Order Information for Training Support Vector Machines," J. Mach. Learn. Res., vol. 6, pp. 1889-1918, 2005.

指導教授

葉士青(Shih-ching Yeh)

審核日期

2014-7-28

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