The Research of Kinematic Model in the Rehabilitative Training System

Abstract:

This paper provided a new method of controlling the rehabilitative training system for the patients with upper limb movement disorder. On the basis of the computer through the patient's healthy limb motion gesture motion parameters, analyzed the kinematic model of human upper limb joints, obtained the kinematic parameters of upper body. Study the establishment of different categories of patients with upper limb virtual computer model system for the detection of relevant parameters. And according to the requirements of upper limb rehabilitation training for patients with upper limb rehabilitative training system, researched the dynamics model of human upper limb, and indicated a method which may provide scientific and effective training methods to recover function rehabilitation for patients.

• Periodical: Applied Mechanics and Materials (Volume 607)
• Pages: 764-767
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.607.764
• Online since: July 2014
• Authors: Qiang Wang*, Run Ji
• Keywords: Control Strategy of System, Kinematic Model, Rehabilitative Training System, Virtual Computer Model

References

[1] E. Chauvet,O. Fokapu, andJ. Y Hogrel, etc: A method of EMG decomposition based on fuzzy logic. Engineering in Medicine and Biology Society, 2001[C]. Proceedings of the 23rd Annual International Conference of the IEEE. Vo1. 2: pp.25-8 Oct, (2001).

DOI: 10.1109/iembs.2001.1020609

[2] Qiang WANG, Zhi Lan, and Xiufeng Zhang, etc: The Research of the Rehabilitative Exercises System of Residual Limbs Based on EMG Sensor, Applied Mechanics and Materials Vols. 365-366 (2013) pp.1332-1335.

DOI: 10.4028/www.scientific.net/amm.365-366.1332

[3] Xitai WANG, Qiang WANG, Xiaoyu ZHANG, etc: The Research of Pattern Recognition in the Rehabilitative Exercises of Lower Residual Limbs Based on EMG Sensor, Chinese Journal of Rehabilitation Theory and Practice, 15(1), pp.90-92, (2009).

[4] Juntao Ye, Robert E. Webber, Yangsheng Wang: A reduced unconstrained system for the cloth dynamics solver. The Visual Computer 25(10): 959-971, (2009).

DOI: 10.1007/s00371-008-0307-z

[5] Xiaolong Zheng, Yangsheng Wang, Liang Zheng: A Comprehensive Approach for Fingerprint Alignment. Intelligent Networks and Intelligent Systems, (2009).

DOI: 10.1109/icinis.2009.104

[6] Mingcai Zhou, Yangsheng Wang, Xiaoyan Wang, Xuetao Feng: Real-time view-based face alignment using an extended AAM, Intelligent Computing and Intelligent Systems, (2009).

DOI: 10.1109/icicisys.2009.5357612

[7] Huiwen Cai, Xiaoyan Wang, Yangsheng Wang: Entropy-Based Maximally Stable Extremal Regions for Robust Feature Detection. Mathematical Problems in Engineering, Volume (2012).

DOI: 10.1155/2012/857210

[8] Lei Shi, Yangsheng Wang, Jituo L: A Real Time Vision-Based Hand Gestures Recognition System. The 5th International Symposium on Intelligence Computation and Applications (1) 2010: 349-358.

DOI: 10.1007/978-3-642-16493-4_36

[9] Guoqing Xu, Yangsheng Wang: Real Time Detection of Eye Corners and Iris Center from Images Acquired by Usual Camera, International Journal of Intelligent Engineering and Systems, Vol. 3, No. 1: 25-32, (2010).

DOI: 10.1109/icinis.2009.109

[10] M.H. Chong, H. Jaafar, W.Z.W. Hasan, S. Shafie, M.N. Hamidun, M.M. Isa, A.F. Hawary: An Ecperiment Of Thick Film Force Sensor Using Mems Simulation Software. Journal of Theoretical and Applied Information Technology, Vol. 47. No. 3, 2013, pp.902-910.

[11] Jungwon Yoon, Bondhan Novandy, Chul-Ho Yoon, and Ki-Jong Park: A 6-DOF Gait Rehabilitation Robot With Upper and Lower Limb Connections That Allows Walking Velocity Updates on Various Terrains. IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 15, NO. 2, April, (2010).

DOI: 10.1109/tmech.2010.2040834

[12] Huiwen Cai, Xiaoyan Wang, Yangsheng Wang: Compact and robust fisher descriptors for large-scale image retrieval, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

DOI: 10.1109/mlsp.2011.6064624