中風後導致患者身體產生各種障礙，進一步影響身體失能的原因，包括張力不平衡、肌肉無力、協同動作…等等。在一般情況下，中風後都需要積極復健，而復健是個非常漫長的過程，需要密集而直接的指導。身體的關節活動度是復健成效中很重要的評估項目之一，其量測方式在目前臨床上大多仰賴治療師透過目視或使用量角器輔助，然而此種方式會由於治療師的經驗與量測基準點的不同而有所差異；且在量測的進行上僅能得知單一平面的動作角度，無法確實掌握患者執行功能動作時在其他平面角度的偏移量，可能因此造成患者的代償動作無法得到改善。
為了改善現有復健的缺點，本論文建構出一套符合臨床使用需求的復健動作監控系統，不僅提供各平面完整的動作角度資訊，降低傳統使用目視、量角器量測之誤差，同時協助提高復健效益。此系統最終的目的是希望能加強居家復健，讓患者在無治療師監督的環境下，由系統輔助復健治療的進行，經由系統即時判斷患者復健動作角度，以語音方式配合虛擬人體動畫引導患者執行正確動作。而治療師可透過本系統建構之遠端平台，遠距即時觀察患者之復健數據，適時調整復健運動處方參數，實現居家遠距復健之願景。
此穿戴式復健裝置在經過光學立體攝影系統(VICON)比對後，結果顯示三個軸向的旋轉角度平均均方根差(RMSE)約為1°。且人體動作判斷驗證結果顯示本系統可提供可靠的動作判斷。此外，在臨床實驗結果中，兩位患者都完成15次復健系統介入實驗，介入後成效良好，顯示本系統對中風患者執行復建動作有確實之幫助。

Stroke is a major cause for severe physical disabilities, which always leads to many kinds of impairments such as tension imbalance, muscle weakness, synergy, and etc. To assist patients fully recover from sequela of stroke; a long-term and intensive rehabilitation process with directly guiding from the therapists is required. Range of motion (ROM) is a fundamental indicator to evaluate the effectiveness of rehabilitation. Nowadays, the clinically measurement is generally relied on visual inspection or goniometry. However, the obtained results are diverse depend on different therapists with different experience and measuring datum. Furthermore, it is hard to assess two or more plane angles simultaneously during exercising with visual examine or goniometry. Instead, only monoplane angles can be obtained, which therefore the synergy cannot be improved.
To ameliorate the defects of current rehabilitation equipment, this thesis presents a rehabilitation movement monitoring system for physical therapy treatment. The system can automatically provide the overall rehabilitation information including multiplane angles data, which allow decreasing the deviation of exploiting visual inspection and manual measurement. Besides, with the assist of the proposed system, users are able to conduct the physical treatment at home. A voice and animated guidance are developed to demonstrate the accurate exercise movements for users. The corresponding data during the rehabilitation can be recorded and uploaded to the built-in remote monitoring platform. Therapist can receive the prompt information to understand the rehabilitation status of each patient. If necessary, the prescription parameters can be regulated instantaneously to harmonize with user’s improvement.
The wearable device used for rehabilitation in the proposed system has been verified with VICON Bonita optical system. The results indicate that the average root mean square error (RMSE) among three axes is approximately 1 degree. Besides, with human experiment validation, the proposed system provides useful and accurate analyzing results. Finally, through involving 15-time clinical experiment for each subject, the proposed system is recognized as a friendly and efficient platform for helping stroke patients in rehabilitation.

[1]"International Cardiovascular Disease Statistics", American Heart Association, 2004.
[2]行政院衛生福利部, [Online] Available http://www.mohw.gov.tw/cht/DOS。
[3]T. Truelsen, S. Begg and C. Mathers, "The global burden of cerebrovascular disease," Cerebrovascular Disease 21-06-06, Global Burden of Disease, 2000.
[4]C. C. Norkin and D. J. White, "Measurement of joint motion a guide to goniometry," 4th Edition : F.A. Davis Company, 2003.
[5]C. Anderson, C. N. Mhurchu, S. Rubenach, M. Clark, C. Spencer, and A. Winsor, "Home or Hospital for Stroke Rehabilitation? Results of a Randomized Controlled Trial : II: Cost Minimization Analysis at 6 Months, Stroke," American Heart Association, pp. 1032-1037, 2000.
[6]J. M. Geddes and M. A. Chamberlain, "Home-based rehabilitation for people with stroke: a comparative study of six community services providing co-ordinated, multidisciplinary treatment," Clinical Rehabilitation, vol. 15, pp. 589-599, 2001.
[7]H. Sveistrup, "Motor rehabilitation using virtual reality," Journal of NeuroEngineering and Rehabilitation, vol. 1, pp. 1-10, Dec. 2004.
[8]H. Zhou and H. Hu, "Inertial sensors for motion detection of human upper limbs," Sensor Review, vol. 27, pp. 151-158, Feb. 2007.
[9]W. C. Hsu, T. M. Wang, M. W. Liu, C. F. Chang, H. L. Chen, and T. W. Lu, "Control of body's center of mass motion during level walking and obstacle crossing in older patients with knee osteoarthritis," Journal of Mechanics, vol. 26, pp. 229-237, Jun. 2010.
[10]W. C. Hsu, T. W. Lu, and M. W. Liu, "Lower limb joint position sense in patients with type II diabetes mellitus," Biomedical Engineering: Applications, Basis and Communications, vol. 21, pp. 271-278, Feb. 2009.
[11]H. Zhou and H. Hu, "Human motion tracking for rehabilitation - a survey," Biomedical Signal Processing and Control, vol. 3, pp. 1-18, 2007.
[12]T. Hester, R. Hughes, D. M. Sherrill, B. Knorr M. Akay, J. Stein and P. Bonato, "Using Wearable Sensors to Measure Motor Abilities following Stroke," Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks, pp. 4-8, Apr. 2006.
[13]D. M. Karantonis, M. R. Narayanan, N. H. Lovell and B. G. Celler, "Implementation of a Real-Time Human Movement Classifier Using a Triaxial Accelerometer for Ambulatory Monitoring," IEEE Transactions on information technology in Biomedicine, vol. 10, pp. 156-167, Jan. 2006.
[14]J. Brutovsky and D. Novak, "Low-cost motivated rehabilitation system for post-operation exercises," Proceedings of the International Conference on Medicine and Biology Society, pp. 6663-6666, Aug. 2006.
[15]J. Pang and I. Singh, "Accelerometer based real-time remote detection and monitoring of hand motion," Proceedings of The World Congress on Engineering and Computer Science, pp. 744-747, Oct. 2011.
[16]B. C. Lee, S. Chen, and K. H. Sienko, "A wearable device for real-time motion error detection and vibrotactile instructional cuing," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 19, pp. 374-381, Aug. 2011.
[17]C. M. N. Brigante, N. Abbate, A. Basile, A. C. Faulisi, and S. Sessa, "Towards miniaturization of a MEMS-based wearable motion capture system," IEEE Transactions on Industrial Electronics, vol. 58, pp. 3234-3241, Aug. 2011.
[18]Z. Q. Ding, Z. Q. Luo, A. Causo, I. M. Chen, K. X. Yue, S. H. Yeo, and K. V. Ling, "Inertia sensor-based guidance system for upperlimb posture correction," Medical Engineering and Physics, vol. 35, pp. 269-276, Jun. 2011.
[19]M. E. Gohary and J. McNames, "Shoulder and elbow joint angle tracking with inertial sensors," IEEE Transactions on Biomedical Engineering, vol. 59, pp. 2635-2641, Sep. 2012.
[20]J. I. Pan, H. W. Chung, and J. J. Huang, "Intelligent frozen shoulder self-home rehabilitation monitoring system," Proceedings of the International Conference on Information Science and Technology, vol. 23, pp. 265-270, 2013.
[21]許原彰, "嵌入式復健動作監控系統之設計與評估", 台灣科技大學碩士論文，2013.
[22]M. C. Huang, S. H. Lee, S. C. Yeh, R. C. Chan, A. Rizzo, W. Xu, W. H. Lin and L. S. Hui, "Intelligent Frozen Shoulder Rehabilitation," IEEE Transactions on Intelligent System, vol. 29, pp. 22-28, Jun. 2014.
[23]M. D. Plessis, E. Eksteen, A. Jenneker, E. Kriel, C. Mentoor, T. Stucky, D. V. Staden, and L. M. Division, "The effectiveness of continuous passive motion on range of motion, pain and muscle strength following rotator cuff repair a systematic review, " Clinical Rehabilitation, vol. 25, pp. 291-302, Oct. 2010.
[24]D. O. Draper, EdD, ATC, and FNATA, "Ultrasound and joint mobilizations for achieving normal wrist range of motion after injury or surgery a case series," Athletic Training, vol. 45, pp. 486-491. Oct. 2010.
[25]C. C. Norkin and D. J. White, "Measurement of joint motion a guide to goniometry," 4th Edition.: F.A. Davis Company, 2003.
[26]張哲豪, "手腕功能障礙復健活動之運動學分析與療效研究：電腦遊戲與傳統治療活動", 成功大學學術研究鼓勵專題研究計畫, 2007.
[27]S. O. Madgwick, A. J. Harrison, and R. Vaidyanathan, "Estimation of IMU and MARG orientation using a gradient descent algorithm," IEEE International Conference on Rehabilitation Robotics, pp. 1-7, Jun. 2011.
[28]X. Yun and E. R. Bachmann, "Design, Implementation, and Experimental Results of a Quaternion-Based Kalman Filter for Human Body Motion Tracking," IEEE Transactions on Robotics, vol. 22, pp. 1216-1227. Dec. 2006.
[29]J. B Kuipers, "Quaternion and Rotation Sequence," Princeton university press, Sep. 1999.
[30]W. R. Hamilton, "On quaternions; or on a new system of imagniaries in algebra," London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, pp. 489-495, Jul. 1844.
[31]J. M. Cooke, M. J. Zyda, D. R. Pratt and R. B. McGhee, "Npsnet: Flight simulation dynamic modelling using quaternions," Presence, vol. 1, pp. 404-420, Jan. 1994.