簡易檢索 / 詳目顯示

研究生: 陳永洪
Yung-Hung Chen
論文名稱: 下肢外骨骼機器人基於Load cell 之復健分析
Analysis of Rehabilitation in Lower Extremity Exoskeleton Robots based on Load cells
指導教授: 蘇順豐
Shun-feng Su
口試委員: 陶金旺
Chin-wang Tao
黃有評
Yo-ping Huang
郭重顯
Chung-hsien Kuo
王乃堅
Nai-Jian Wang
學位類別: 碩士
Master
系所名稱: 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 53
中文關鍵詞: Load cell壓力感測器下肢外骨骼機器人下肢標準運動分析.
外文關鍵詞: Load cell, pressure sensor, the lower extremity exoskeleton, the standard of motion analysis of lower extremi
相關次數: 點閱:201下載:8
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

本篇論文提供一種方法在下肢外骨骼機器人的腳底安裝load cell壓力感測器進行偵測腳底壓力的變化結合下肢標準運動分析了解對於錯誤軌跡的判斷規則,利用錯誤軌跡的判斷規則也能幫助下肢外骨骼機器人矯正錯誤的軌跡。本篇論文中也介紹了下肢標準運動分析,包含臀部、膝蓋、脛骨、腳及腳踝,不僅可以了解對於錯誤軌跡的判斷也是復健師在對病人進行復健時最需要的依據。如果能夠結合具有腿部壓力感測器的下肢外骨骼機器人,那就更能了解下肢的肌肉部分哪裡缺乏足夠的力量可以藉由下肢外骨骼機器人來使這些肌肉加強復健並且強化力量。此外,在本論文還介紹一個下肢外骨骼機器人,是由另外一個實驗室完成,因原本想裝在此下肢外骨骼機器人進行分析,不過此下肢外骨骼機器人已被拆解,所以只簡單利用壓克力來模擬腳底部來進行實驗。


This study proposes an idea about consider load cells on the bottom of foot of exoskeleton robot and combine with the motion analysis of lower extremity to have the rules which can judge whether the trajectory is correct or not. Load cells can detect the change of pressure on the bottom of foot. Such an implemented idea can help patients and physical therapists to realize the change of pressure on the bottom of foot. Load cells can be used not only to compare the bottom of patients and the bottom of normal human beings with the change of pressure but also to combine with the lower extremity exoskeleton which has pressure sensors on the legs. Load cells are the way that we can realize where the lack of enough force is by using the approach to utilize the lower extremity exoskeleton to make the muscle strong and powerful. We also propose some rules to let the lower extremity exoskeleton to help the patients rehabilitate by using the rules. When the rehabilitation is discussed, we introduce the standard of motion analysis of lower extremity, including Hip, Knee, Tibia, foot and ankle. In addition, we also introduce the lower extremity exoskeleton which is built by the other lab. In the beginning, we want to install Load cell to have analysis, but the lower extremity exoskeleton is taken apart. We just use acrylic sheet to have experiment.

中文摘要 Abstract List of Figures List of Tables Chapter 1 Introduction 1.1 Research Motivation and Objective 1.2 Related work 1.3 Ideas in Our Study 1.4 Organization Chapter 2 Basic Concepts 2.1 Problem Description 2.2 Gait Cycle Pattern 2.3 The Structure of Exoskeleton 2.3.1 Tendon-Driven Module 2.3.2 Robotic Exoskeleton Design 2.3.3 Locomotion and Control System Chapter 3 Architecture and Design 3.1 The Arduino MEGA 2560 Board R3 3.2 Load Cell 31 3.3 AMP03 Differential Amplifier 3.4 Trajectory of Rehabilitation Chapter 4 Experiment Results 4.1 Results 4.2 Simulation of Load cell Chapter 5 Conclusions and Future Work 5.1 Conclusions 5.2 Future Work References

[1] K.S. Oie, T. Kiemel and J.J. Jeka, “Multisensory fusion: simultaneous re-weighting of vision and touch for the control of human posture.” Brain Res Cogn Brain Res. 14(1):pp. 164-76, Jun. 2002.
[2] S.K. Sabut, R. Kumar, and M. Mahadevappa, "Design of an insole embedded foot pressure sensor controlled FES system for foot drop in stroke patients." 2010 International Conference on Systems in Medicine and Biology. pp. 237-241. 16-18, December 2010.
[3] A.J. Churchill, P.W. Halligan, and D.T. Wade, “RIVCAM: a simple video-based kinematic analysis for clinical disorders of gait.” Comput Methods Programs Biomed. ; 69(3):pp. 197-209. November 2002.
[4] S. Ramsay, “The effects of foot orthoses on the ground reaction forces during walking. Part 1.” The Foot, pp. 205–214, November 2001.
[5] A. Stacoff, I. K.-d. Quervain, M. Dettwyler, P. Wolf, R. List, T. Ukelo, and E. Stussi, “Biomechanical effects of foot orthoses during walking.” The Foot Volume 17, Issue 3, pp. 143–153, September 2007.
[6] C.J. Nester, M.L. van der Linden, and P. Bowker, “Effect of foot orthoses on the kinematics and kinetics of normal walking gait.” Gait Posture, 17(2):pp. 180-7, April 2003.
[7] J.-L. C. Racine, and H. Kazerooni, Control of a lower extremity exoskeleton for human performance amplification. University of California, Berkeley, 2003.
[8] R.-J. Wang, and H.-P. Huang, “AVSER—Active Variable Stiffness Exoskeleton Robot System: Design and Application for Safe Active-Passive Elbow Rehabilitation.” 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 220- 225.
[9] K. Kong, and J. Doyoung, “Design and control of an exoskeleton for the elderly and patients,” IEEE/ASME Trans. Mechatronics, vol. 11, no. 4, pp. 428–432, August 2006.
[10] E. Rocon, J. M. Belda-Lois, A. F. Ruiz, M. Manto, J. C. Moreno, and J. L. Pons, “Design and validation of a rehabilitation robotic exoskeleton for tremor assessment and suppression,” IEEE Trans. Neural Syst. Rehab. Eng., vol. 15, no. 3, pp. 367–378, September 2007.
[11] K. Kyoungchul, M. Hyosang, J. Doyoung, and M. Tomizuka, “Control of an Exoskeleton for Realization of Aquatic Therapy Effects,” IEEE/ASME Trans. on Mechatronics, vol. 15, no. 2, pp. 191–200, 2010.
[12] D.J. Magee, Orthopedic physical assessment, 5th ed., Saunders Elsevier, D.J. Magee, 2006.
[13] Z. Li, C.-Y. Su, A. Xue, “Development and Learning Control of a Human Limb With a Rehabilitation Exoskeleton,” Industrial Electronics, IEEE Transactions Volume 61 , Issue 7, pp. 3776 – 3785, January 2014.
[14] A. Erhan, and A. A. Mehmet "The design and control of a therapeutic exercise robot for lower limb rehabilitation: Physiotherabot," Mechatronics, vol. 21, no. 3, pp.509 -522, 2011.
[15] S. Hong, Y. Oh, D. Kim, and B. You "Real-time walking pattern generation method for humanoid robots by combining feedback and feed-forward controller," IEEE Trans. Ind. Electron., vol. 61, no. 1, pp.355 -364, 2014.
[16] X. Zhang, Q. Guo, C. Zhao, Y. Zhang, and X. Luo “Development of a lower extremity exoskeleton suit actuated by hydraulic,” 2012 International Conference on Mechatronics and Automation (ICMA), pp. 587-591, August 2012.
[17] T. Yoshimitsu, and K. Yamamoto, “Development of a power assist suit for nursing work,” SICE 2004 Annual Conference, vol.1, pp. 577-580, August 2004.
[18] Y.H. Yin, Y.J. Fan, and L.D. Xu, “EMG and EPP-Integrated Human–Machine Interface between the Paralyzed and Rehabilitation Exoskeleton,” IEEE Transactions on Information Technology in Biomedicine Volume 16, Issue 4, pp. 542-549, January 2012.
[19] J. Veneman, R. Kruidhof, E. Hekman, R. Ekkelenkamp, E. van Asseldonk, and H. van der Kooij "Design and evaluation of the LOPES exoskeleton robot for interactive gait rehabilitation," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 15, no. 3, pp.379 -386, 2007.
[20] P. Artemiadis, and K. Kyriakopoulos "An EMG-based robot control scheme robust to time-varying EMG signal features," IEEE T. Inf. Technol. Biomed., vol. 14, no. 3, pp.582 -588, 2010.

QR CODE