研究生: |
高元亞 Yuan-ya Kao |
---|---|
論文名稱: |
基於智慧型手機之復健動作監控系統設計 A Smartphone-Based Rehabilitative Movement Monitoring System |
指導教授: |
林淵翔
Yuan-hsiang Lin |
口試委員: |
許孟超
Mon-chau Shie 郭重顯 Chung-hsien Kuo 許維君 Wei-chun Hsu |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電子工程系 Department of Electronic and Computer Engineering |
論文出版年: | 2013 |
畢業學年度: | 101 |
語文別: | 中文 |
論文頁數: | 108 |
中文關鍵詞: | 智慧型手機 、陀螺儀 、人體關節活動範圍量測 、遠距復健與監控 |
外文關鍵詞: | Smartphone, gyroscope, range of motion (ROM), tele-rehabilitation and monitoring |
相關次數: | 點閱:549 下載:7 |
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本論文使用智慧型手機和其內建的陀螺儀開發一套復健動作監控系統。主要功能如下:(1)判斷病患復健動作狀況(如正確與錯誤動作、動作次數);(2)語音提示及螢幕顯示相關資訊達到即時回饋;(3)隨時隨地能透過網路連線上傳復健資訊置資料庫,或更新處方箋;(4)治療師使用資料庫監控病患狀況並設定參數達到遠端更新處方功能。
關於手機陀螺儀在量測動作角度之準確度方面,馬達驗證部分在三種轉速下(20.8°/s、60.9°/s與112.1°/s),三個軸向的平均誤差分別為0.1°±0.2°、0.4°±0.1°與0.3°±0.1°,皆在1°以內;人體動作驗證與光學立體攝影系統作比較,髖關節屈曲、膝關節伸直及走路主要平面誤差在6°以內。另外,本系統能夠即時判斷復健動作正確與否,可協助病患確保動作正確性,避免錯誤動作造成二次傷害。
In this thesis, we developed a remote rehabilitation movement monitoring system based on the smartphone and its built-in gyroscope. The main functions of this system are as follows, (1) to assess patient’s movement status (such as correct or wrong movement and number of movements). (2) Voice guidance and information display on the screen for real-time feedback. (3) To upload and download data from database via wireless network. (4) The therapist can assess the status of patient via database and update the parameter of prescription.
The accuracy of the angle measurement of smartphone and the built-in gyroscope was verified in the experiments of motor movement. The mean error were 0.1°±0.2°, 0.4°±0.1° and 0.3°±0.1° at the angular velocity 20.8°/s, 60.9°/s and 112.1°/s separately. In human motion experiment, the mean errors are less than 6° at hip flexion, knee extension and walking by comparing with a 3D stereophotographic system. In addition, this system can assess rehabilitation movement in real time to help patients to ensure correct movement and avoid damage again.
[1] 行政院衛生署國民健康局,「2009年國民健康訪問調查」,臺灣(2009)。
[2] 行政院衛生署,「101年國人主要死因統計結果」,臺灣(2012)。
[3] C. Anderson, “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.
[4] J. M. Geddes and M. A. Chamberlain, “Home-based rehabilitation for people with stroke a comparative study of six community services providing coordinated, multidisciplinary treatment,” Clinical Rehabilitation, vol. 15, pp. 589-599, Jun 1 2001.
[5] C. C. Norkin and D. J. White, Measurement of Joint Motion: A guide to Goniometry, 3 ed.: F. A. Davis company. Philadelphia, 2003.
[6] Wikipedia “Goniometer”, [Online] Available: http://en.wikipedia.org/wiki/Goniometer
[7] H. Zhou and H. Hu, “Human motion tracking for rehabilitation-A survey,” Biomedical Signal Processing and Control, May 2007.
[8] Our Mobile Planet, [Online] Available: http://www.thinkwithgoogle.com/mobileplanet/zh-tw/
[9] G. Kiss, “Using smartphones in healthcare and to save lives,” IEEE International Conference on and 4th International Conference on Cyber, Physical and Social Computing, pp. 614-619, 2011.
[10] S. Almer, J. Kolbitsch, J. Oberzaucher, and M. Ebner, “Assessment Test Framework for Collecting and Evaluating Fall-Related Data Using Mobile Devices,” ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part II, pp. 83-90, 2012.
[11] S. Mellone, C. Tacconi, L. Schwickert, J. Klenk, C. Becker, and L. Chiari, “Smartphone-based solutions for fall detection and prevention: the FARSEEING approach,” Zeitschrift fur Gerontologie und Geriatrie, vol 45, Issue 8 , pp. 722-727, 2012.
[12] B. S. Beauvais, V. Rialle, and J. Sablier, “MyVigi : An Android Application to Detect Fall and Wandering,” UBICOMM 2012 : The Sixth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, pp. 156-160, 2012.
[13] AKM J. A. Majumder, F. Rahman, I. Zerin, E. Jr. William, and S. I. Ahamed, “iPrevention: Towards a Novel Real-time Smartphone-based Fall Prevention System,” SAC '13 Proceedings of the 28th Annual ACM Symposium on Applied Computing, pp. 513-518, 2013.
[14] W. Wu, S. Dasgupta, E. E Ramirez, C. Peterson, and G. J Norman, “Classification Accuracies of Physical Activities Using Smartphone Motion Sensors,” Journal of Medical Internet Research , vol. 14, No 5, 2012.
[15] S. Kaghyan, H. Sarukhanyan, and D. Akopian, “Human Movement Activity Classification Approaches that use Wearable Sensors and Mobile Devices,” SPIE vol. 8667, Multimedia Content and Mobile Devices, Mar 26 2013.
[16] Y. He, and Y. Li, “Physical Activity Recognition Utilizing the Built-in Kinematic Sensors of a Smartphone,” International Journal of Distributed Sensor Networks, vol. 2013, 10 pages, 2013.
[17] A. Bujari, B. Licar, and C. E. Palazzi, “Movement Pattern Recognition through Smartphone’s Accelerometer,” Consumer Communications and Networking Conference (CCNC), 2012 IEEE, pp. 502-506, Jan 14-16 2012.
[18] Y. Yu, X. Zhao, and J. Ou, “A New Idea: Mobile Structural Health Monitoring Using Smart Phones,” Intelligent Control and Information Processing (ICICIP), 2012 Third International Conference on IEEE, pp. 714-716, Jul 15-17 2012.
[19] H. Lee, S. Lee, Y. S. Choi, Y. Seo, and E. Shim, “A New Posture Monitoring System for Preventing Physical Illness of Smartphone,” Consumer Communications and Networking Conference (CCNC), 2013 IEEE, pp. 821-825, Jan 11-14 2013.
[20] M. Milosevic, E. Jovanov, and A. Milenkovic, “Quantifying Timed-Up-and-Go Test: A Smartphone Implementation,” Body Sensor Networks Conference, 6 pages, May 6-9, 2013.
[21] B. C. Lee, J. Kim, S. Chen, and K. H Sienko, “Cell phone based balance trainer,” Journal of NeuroEngineering and Rehabilitation, vol. 9, 14 pages, 2012.
[22] C. Franco, A. Fleury, P. Y. Gumery, B. Diot, J. Demongeot, and N. Vuillerme, “iBalance-ABF: A Smartphone-Based Audio-Biofeedback Balance System,” Biomedical Engineering, IEEE Transactions on, vol. 60, Issue 1, pp. 211-215, Jan 2013.
[23] K. Huang, P. Sparto, S. Kiesler, D. Siewiorek, and A. Smailagic, “iPod for Home Balance Rehabilitation Exercise Monitoring,” Wearable Computers (ISWC), 2012 16th International Symposium on IEEE, pp. 116-117, Jun 18-22 2012.
[24] G. Ferriero, F. Sartorio, C. Foti, D. Primavera, E. Brigatti, and S. Vercelli, “Reliability of a New Application for Smartphones(DrGoniometer) for Elbow Angle Measurement,” PM&R vol. 3, Issue 12, pp. 1153–1154, Dec 2011.
[25] S. H. Shin, D. H. Ro, O-S. Lee, J. H. Oh, and S. H. Kim, “Within-day reliability of shoulder range of motion measurement with a smartphone,” Manual Therapy, vol. 17, Issue 4, pp. 298–304, Aug 2012.
[26] J.-Y. Jenny, “Measurement of the Knee Flexion Angle With a Smartphone-Application is Precise an Accurate,” The Journal of Arthroplasty, vol. 28, Issue 5, pp. 784–787, May 2013.
[27] T. S. Kim, D. D. H. Park, Y. B. Lee, D. G. Han, J. S. Shim, Y. J. Lee, and P. C. W. Kim, “A study on the Measurement of Wrist Motion Range Using iPhone 4 Gyroscope Application,” Annals of Plastic Surgery, 4 pages, Jul 1 2013.
[28] D. Deponti, D. Maggiorini, and C. E. Palazzi, “Smartphone’s Physiatric Serious Game,” Serious Games and Applications for Health (SeGAH), 2011 IEEE 1st International Conference on, pp. 1-8, Nov 16-18 2011.
[29] J.-I Pan, H.-W. Chung, and J.-J. Huang, “Intelligent Frozen Shoulder Self-Home Rehabilitation Monitoring System,” IST 2013, Advanced Science and Technology Letters, vol. 23, pp. 265-270, 2013.
[30] E. H.-k. Wu, C. Y. Chen, S. S. Yen, Z. Y. Chen, X. Y. Lin, C. N. Change, J. R. Yang, Y. Y. Yang, and Yu-Wei Chen, “Is-STROKE ER: Innovative Social-based Stroke Evaluation and Rehabilitation System for New Generation Pervasive Healthcare,” TANET 2012, Talwan Academic Network Conference, 2012.
[31] 有健康-關節活動度, [Online] Available: http://www.uuuwell.com/mytag.php?id=73031
[32] 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, 2010.
[33] 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, Oct 2010.
[34] C. C. Norkin and D. J. White, Measurement of Joint Motion: A guide to Goniometry, 3 ed.: F.A. Davis company, Philadelphia, 2003.
[35] Wikipedia “Gyroscope”, [Online] Available: http://en.wikipedia.org/wiki/Gyroscope
[36] InvenSense “MPU-300/MPU-3050 Product Specification”, [Online] Available: http://invensense.com/mems/gyro/documents/PS-MPU-3000A-00_v2.5.pdf
[37] 2008 Google I/O Session Videos and Slides, [Online] Available: https://sites.google.com/site/io/
[38] Android, [Online] Available: http://www.android.com/
[39] Wikipedia “Android”, [Online] Available: https://zh.wikipedia.org/zh-tw/Android
[40] Samsung, [Online] Available: http://www.samsung.com/
[41] Wikipedia “Speech synthesis”, [Online] Available: https://en.wikipedia.org/wiki/Speech_synthesis.
[42] 語音語音互動處理技術網, [Online] Available: http://atc.ccl.itri.org.tw/speech/
[43] C. Barthold, K. P. Subbu, and R. Dantu, “Evaluation of Gyroscope-embedded Mobile Phones,” Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on, pp. 1632-1638, Oct 9-12 2011.