نوع مقاله: مقاله کامل پژوهشی

نویسندگان

1 ﺩﺍﻧﺸﺠﻮی ﻛﺎﺭﺷﻨﺎﺳﻰ ﺍﺭﺷﺪ، ﮔﺮﻭﻩ ﺑﻴﻮﺍﻟﻜﺘﺮﻳﮏ، ﺩﺍﻧﺸﻜﺪﻩ ﻣﻬﻨﺪﺳﻰ ﭘﺰﺷﻜﻰ، ﺩﺍﻧﺸﮕﺎﻩ ﺻﻨﻌﺘﻰ ﺍﻣﻴﺮﻛﺒﻴﺮ

2 ﺍﺳﺘﺎﺩ، ﮔﺮﻭﻩ ﺑﻴﻮﺍﻟﻜﺘﺮﻳﮏ، ﺩﺍﻧﺸﻜﺪﻩ ﻣﻬﻨﺪﺳﻰ ﭘﺰﺷﻜﻰ، ﺩﺍﻧﺸﮕﺎﻩ ﺻﻨﻌﺘﻰ ﺍﻣﻴﺮﻛﺒﻴﺮ

10.22041/ijbme.2014.13553

چکیده

ﻟﺮﺯﺵ ﺍﺯ ﺷﺎﻳﻊﺗﺮﻳﻦ ﺍﺧﺘﻼﻻﺕ ﺣﺮﻛﺘﻰ ﺍﻧﺴﺎﻥ ﺍﺳﺖ ﻛﻪ ﺣﺮﻛﺘﻰ ﻏﻴﺮﺍﺭﺍﺩی ﻭ ﺗﻘﺮﻳﺒﺎً ﺳﻴﻨﻮﺳﻰ ﺍﺳﺖ. ﻟﺮﺯﺵ، ﻣﻔﺼﻞﻫﺎی ﻣﺨﺘﻠﻔﻰ ﺩﺭ ﺑﺪﻥ ﺍﺯ ﺟﻤﻠﻪ ﻣﻔﺼﻞ ﺁﺭﻧﺞ ﺭﺍ ﺗﺤﺖ ﺗﺄﺛﻴﺮ ﻗﺮﺍﺭ ﻣﻰﺩﻫﺪ. ﻟﺮﺯﺵ ﻣﻔﺼﻞ ﺁﺭﻧﺞ ﺑﺼﻮﺭﺕ ﺣﺮﻛﺎﺕ ﺑﺎﺯ ﻭ ﺑﺴﺘﻪ ﺷﻮﻧﺪﻩ ﻭ ﭼﺮﺧﺸﻰ ﺳﺎﻋﺪ ﺍﺳﺖ. ﺩﺭﻣﺎﻥﻫﺎی ﻣﺘﻔﺎﻭﺗﻰ ﺑﺮﺍی ﻟﺮﺯﺵ ﻭﺟﻮﺩ ﺩﺍﺭﺩ ﻛﻪ ﻳﻜﻰ ﺍﺯ ﺁﻥﻫﺎ ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺗﺤﺮﻳﮏ ﺍﻟﻜﺘﺮﻳﻜﻰ ﺍﺳﺖ. ﺩﺭ ﺍﻳﻦ ﺭﻭﺵ ﻻﺯﻡ ﺍﺳﺖ ﺑﻪ ﻣﻮﺍﺭﺩی ﺗﻮﺟﻪ ﺷﻮﺩ ﻛﻪ ﻋﺒﺎﺭﺗﻨﺪ ﺍﺯ 1) ﺗﺤﺮﻳﮏ ﻛﻨﻨﺪﮤ ﺍﻟﻜﺘﺮﻳﻜﻰ، ﺑﻤﻨﻈﻮﺭ ﺍﻧﺠﺎﻡ ﺁﺯﻣﺎﻳﺶﻫﺎی ﻭﺍﻗﻌﻰ ﻭ ﺍﻋﺘﺒﺎﺭﺳﻨﺠﻰ ﻣﺪﻝ، 2) ﻣﺪﻝ ﻋﺼﺒﻰ- ﻋﻀﻼﻧﻰ- ﺍﺳﻜﻠﺘﻰ ﺑﺮﺍی ﺑﺮﺭﺳﻰ ﺩﻳﻨﺎﻣﻴﮏ ﻟﺮﺯﺵ ﻭ ﺷﺒﻴﻪﺳﺎﺯی ﺳﻴﺴﺘﻢ، 3) ﺗﻌﻴﻴﻦ ﺍﻟﮕﻮ، ﻧﺤﻮﮤ ﺗﺤﺮﻳﮏ ﻭ ﺭﻭﺵ ﻛﻨﺘﺮﻟﻰ ﻣﻨﺎﺳﺐ ﺑﺮﺍی ﻛﻨﺘﺮﻝ ﭘﺎﺭﺍﻣﺘﺮﻫﺎی ﺗﺤﺮﻳﮏ ﺑﻪ ﻧﺤﻮی ﻛﻪ ﻟﺮﺯﺵ ﻛﺎﻫﺶ ﻳﺎﺑﺪ. ﻳﻜﻰ ﺍﺯ ﺭﻭﺵﻫﺎﻳﻰ ﻛﻪ ﺑﺮﺍی ﺗﺤﺮﻳﮏ ﺍﻟﻜﺘﺮﻳﻜﻰ ﻋﻀﻼﺕ ﻣﺨﺎﻟﻒ ﺑﻤﻨﻈﻮﺭ ﻛﺎﻫﺶ ﻟﺮﺯﺵ ﺍﺳﺘﻔﺎﺩﻩ ﻣﻰﺷﻮﺩ، ﺗﺤﺮﻳﮏ ﺑﻪﺻﻮﺭﺕ ﻓﺎﺯ ﻣﺘﻘﺎﺑﻞ ﺍﺳﺖ. ﺩﺭ ﺍﻳﻦ ﺭﻭﺵ ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﺍﻳﻨﻜﻪ ﺳﻴﺴﺘﻢ ﺩﺍﺭﺍی ﺗﺄﺧﻴﺮ ﺯﻣﺎﻧﻰ، ﺍﻏﺘﺸﺎﺵ، ﺭﻭﺍﺑﻂ ﻏﻴﺮﺧﻄﻰ ﻭ ﻣﺘﻐﻴﺮ ﺑﺎ ﺯﻣﺎﻥ ﺍﺳﺖ، ﻧﻴﺎﺯﻣﻨﺪ ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﻛﻨﺘﺮﻝﻛﻨﻨﺪﻩﺍی ﺗﻮﺍﻧﺎ ﻭ ﻗﺪﺭﺗﻤﻨﺪ ﻫﺴﺘﻴﻢ. ﺩﺭ ﺍﻳﻦ ﭘﮋﻭﻫﺶ ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﻭﻳﮋﮔﻰﻫﺎی ﻛﻨﺘﺮﻝﻛﻨﻨﺪﻩ MPC،  ﺍﺯ ﺍﻳﻦ ﻛﻨﺘﺮﻝﻛﻨﻨﺪﻩ ﺍﺳﺘﻔﺎﺩﻩ ﺷﺪﻩ ﺍﺳﺖ. ﻧﺘﺎﻳﺞ ﺷﺒﻴﻪﺳﺎﺯی ﻧﺸﺎﻥﺩﻫﻨﺪﮤ ﺍﻳﻦ ﺍﺳﺖ ﻛﻪ MPC ﺩﺭ ﻣﻘﺎﻳﺴﻪ ﺑﺎ ﻛﻨﺘﺮﻝﻛﻨﻨﺪﻩ PID ﻭ Fuzzy - ﻛﻪ ﻗﺒﻼ ﺍﺯ ﺁﻧﻬﺎ ﺍﺳﺘﻔﺎﺩﻩ ﺷﺪﻩ ﺍﺳﺖ- ﻋﻤﻠﻜﺮﺩی ﺭﺿﺎﻳﺖﺑﺨﺶ ﺩﺍﺭﺩ ﻭ ﻧﺸﺎﻥﺩﻫﻨﺪﮤ ﺍﻳﻦ ﻣﻮﺿﻮﻉ ﺍﺳﺖ ﻛﻪ ﺑﺼﻮﺭﺕ ﺗﺌﻮﺭی ﻣﻰﺗﻮﺍﻥ ﻟﺮﺯﺵ ﺭﺍ ﺑﺎ ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺗﺤﺮﻳﮏ ﺍﻟﻜﺘﺮﻳﻜﻰ ﻛﺎﻫﺶ ﺩﺍﺩ. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Hand Tremor Suppuration by Muscle Surface Electrical Stimulation

نویسندگان [English]

  • Reza Hajian 1
  • Farzad Towhidkhah 2

1 M.Sc, Bioelectric Department, Faculty of Biomedical Engineering, Amirkabir University of Technology,

2 Professor, Bioelectric Department, Faculty of Biomedical Engineering, Amirkabir University of Technology

چکیده [English]

Tremor is one of the most frequent movement disorders which is involuntary and approximately sinusoidal. It affects various body joints such as elbow. Tremor on an elbow is considered as extension, flection, and rotation of the forearm. There are miscellaneous types of treatments for tremor one of which is electrical stimulation. In this research, we study existing stimulation methods in order to reduce tremor and control stimulation pulses. It should be notified that studying these methods requires 1- an electrical stimulator so that one can run natural experiments and estimate the validity of the model, 2- a skeletal- neuromuscular model in order to study the tremor dynamics and the system simulation, and 3- determining an appropriate stimulation scheme and control method in order that one can control the stimulation parameters to reduce tremor. The antagonist muscle stimulation technique for reducing tremor is in the form of either muscle co-contraction or anti-phase stimulation. In the former method, considering the fact that the time-dependent system has time-delay, disturbance, and non-linearities, a robust controller is needed. Hence, in this study, we take advantage of MPC controller because of its features. The results show that MPC controller is more satisfactory than the PID and fuzzy ones used in previous works and also demonstrate that one can theoretically reduce tremor by applying appropriate electrical stimulation.

کلیدواژه‌ها [English]

  • Tremor suppression
  • Surface functional electrical stimulation
  • MPC controller
  • Out of phase stimulation
  • Muscloskeletal Model

[1]     Z. Dingguo and A. Wei-Tech, "Tremor Suppression of Elbow Joint via Functional Electrical Stimulation: A Simulation Study," in Automation Science and Engineering, 2006. CASE '06. IEEE International Conference on, 2006, pp. 182-187.

[2]     A. P. L. Bo, P. Poignet, Z. Dingguo, and A. Wei-Tech, "FES-controlled co-contraction strategies for pathological tremor compensation," in Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, 2009, pp. 1633-1638.

[3]     D. Zhang, P. Poignet, F. Widjaja, and W. Tech Ang, "Neural oscillator based control for pathological tremor suppression via functional electrical stimulation," Control Engineering Practice, vol. 19, pp. 74-88, 1// 2011.

[4]     A. Prochazka, J. Elek, and M. Javidan, "Attenuation of pathological tremors by functional electrical stimulation I: Method," Annals of Biomedical Engineering, vol. 20, pp. 205-224, 1992/03/01 1992.

[5]     E. Camacho and C. Bordons, "Model predictive control in the process industry, advances in industrial control," ed: Springer, London, 1995.

[6]     F. Allgöwer, T. A. Badgwell, J. S. Qin, J. B. Rawlings, and S. J. Wright, "Nonlinear Predictive Control and Moving Horizon Estimation — An Introductory Overview," in Advances in Control, P. Frank, Ed., ed: Springer London, 1999, pp. 391-449.

[7]     S. Mohammed, P. Poignet, and D. Guiraud, "Closed loop nonlinear model predictive control applied on paralyzed muscles to restore lower limbs functions," in Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on, 2006, pp. 259-264.

[8]     A. Hill, "The heat of shortening and the dynamic constants of muscle," Proceedings of the Royal Society of London. Series B, Biological Sciences, vol. 126, pp. 136-195, 1938.

[9]     A. F. Huxley, "Muscle structure and theories of contraction," Progress in Biophysics and Biophysical Chemistry, vol. 7, pp. 255-318, 1957 1957.

[10] H. E. Makssoud, D. Guiraud, and P. Poignet, "Mathematical muscle model for functional electrical stimulation control strategies," in Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on, 2004, pp. 1282-1287 Vol.2.

[11] R. Riener and T. Fuhr, "Patient-driven control of FES-supported standing up: a simulation study," Rehabilitation Engineering, IEEE Transactions on, vol. 6, pp. 113-124, 1998.

[12] J. M. Winters, "How detailed should muscle models be to understand multi-joint movement coordination?," Human Movement Science, vol. 14, pp. 401-442, 1995.

[13] J. Winters, "An improved muscle-reflex actuator for use in large-scale neuromusculoskeletal models," Annals of Biomedical Engineering, vol. 23, pp. 359-374, 1995/07/01 1995.

[14] H. Hatze, "A myocybernetic control model of skeletal muscle," Biological Cybernetics, vol. 25, pp. 103-119, 1977/06/01 1977.

[15] E. R. Kandel, J. H. Schwartz, and T. M. Jessell, Principles of neural science vol. 4: McGraw-Hill New York, 2000.

[16] J. M. Winters and L. Stark, "Analysis of fundamental human movement patterns through the use of in-depth antagonistic muscle models," Biomedical Engineering, IEEE Transactions on, pp. 826-839, 1985.

[17] J. M. Winters and P. E. Crago, Biomechanics and Neural Control of Posture and Movement. New York: Springer-Verlag, 2000.

[18] S. Jezernik, R. G. V. Wassink, and T. Keller, "Sliding mode closed-loop control of FES controlling the shank movement," Biomedical Engineering, IEEE Transactions on, vol. 51, pp. 263-272, 2004.

[19] R. Riener, J. Quintern, and G. Schmidt, "Biomechanical model of the human knee evaluated by neuromuscular stimulation," Journal of Biomechanics, vol. 29, pp. 1157-1167, 9// 1996.

[20] M. Ferrarin, F. Palazzo, R. Riener, and J. Quintern, "Model-based control of FES-induced single joint movements," Neural Systems and Rehabilitation Engineering, IEEE Transactions on, vol. 9, pp. 245-257, 2001.

[21] M. Benoussaad, M. Hayashibe, C. Fattal, P. Poignet, and D. Guiraud, "Identification and validation of fes physiological musculoskeletal model in paraplegic subjects," in Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, 2009, pp. 6538-6541.

[22] D. Zhang and W. T. Ang, "Reciprocal EMG controlled FES for pathological tremor suppression of forearm," in Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 2007, pp. 4810-4813.