Experimental Study of EMG 8-electrode Active Circuit Placement on Forearm for Gesture Detection
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2020 by IJETT Journal | ||
| Volume-68 Issue-9 |
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| Year of Publication : 2020 | ||
| Authors : Ivan Krechetov, Arkady Skvortsov, Ivan Poselsky |
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| DOI : 10.14445/22315381/IJETT-V68I9P210 |
Citation
MLA Style: Ivan Krechetov, Arkady Skvortsov, Ivan Poselsky "Experimental Study of EMG 8-electrode Active Circuit Placement on Forearm for Gesture Detection" International Journal of Engineering Trends and Technology 68.9(2020):57-63.
APA Style:Ivan Krechetov, Arkady Skvortsov, Ivan Poselsky. Experimental Study of EMG 8-electrode Active Circuit Placement on Forearm for Gesture Detection International Journal of Engineering Trends and Technology, 68(9),57-63.
Abstract
This paper presents the results of experimental studies of developed active digital electrodes for surface electromyogram. Two layouts of 8 electrodes on the forearms of the test subjects have been investigated. Factors affecting the quality of the gesture recognition system by electromyogram have been considered. It has been demonstrated that the ring layout of electrodes around the forearm can be used in the manufacture of universal prosthetic sockets of upper-limb prostheses and makes it possible to achieve high accuracy of gesture detection. Recommendations on the use of specific motor gestures (up to 8 pcs.) to control different operation modes of the bionic prosthesis have been provided. The developed three-pin active electrodes operate according to the bipolar circuit and make it possible to use them without the necessity of the skin cover pre-treatment.
Reference
[1] G. Li, Y. Li and L. Yu, “Conditioning and sampling issues of EMG signals in motion recognition of multifunctional myoelectric prostheses”, Annals of biomedical engineering, vol.39, no. 6, pp. 1779-1787.
[2] A. Hiraiwa, N. Uchida, N. Sonehara, and K. Shimohara, “EMG pattern recognition by neural networks for prosthetic fingers control-Cyber finger,” in Proc. Int`l. Symp. Measurement and control in Robotics, 1992, pp. 535-542.
[3] M. Zardoshti-Kermani, B. C. Wheeler, K. Badie, R. M. Hashemi “EMG feature evaluation for movement control of upper extremity prostheses,” IEEE Transactions on Rehabilitation Engineering, vol. 3, no. 4, pp. 324-333, Dec. 1995.
[4] H. P. Huang and C. Y. Chen, “Development of a myoelectric discrimination system for a multi-degree prosthetic hand,” in Proc. 1999 IEEE International Conference on Robotics and Automation (Cat. No. 99CH36288C), vol. 3, pp. 2392-2397, May 1999.
[5] R. Boostani and M. H. Moradi, “Evaluation of the forearm EMG signal features for the control of a prosthetic hand,” Physiological Measurement, vol. 24, no. 2, p. 309, May 2003.
[6] M. Zardoshti-Kermani, B. C. Wheeler, K. Badie, and R. M. Hashemi, “EMG feature evaluation for movement control of upper extremity prostheses,” IEEE Transactions on Rehabilitation Engineering, vol. 3, no. 4, pp. 324-333, Dec. 1995.
[7] P. Shenoy, K. Miller, B. Crawford, and R. P. Rao, “Online electromyographic control of a robotic prosthesis,” IEEE Transactions on Biomedical Engineering, vol. 55, no. 3, pp. 1128-1135, March 2008.
[8] G. N. Saridis and T. P. Gootee, “EMG pattern analysis and classification for a prosthetic arm,” IEEE Transactions on Biomedical Engineering, vol. 6, pp. 403-412, Jan 1982.
[9] S. Benatti, E. Farella, L. Benini and E. Gruppioni, “Analysis of robust implementation of an EMG pattern recognition based control,” in International Conference on Bio-inspired Systems and Signal Processing 2014 (BIOSIGNALS 2014)., Angers, France, pp. 45-54.
[10] C. Castellini and P. van der Smagt, “Surface EMG in advanced hand prosthetics,” Biological Cybernetics, vol. 100, no. 1, pp. 35-47, Feb. 2009.
[11] B. Bigland and O. C. J. Lippold, “The relation between force, velocity and integrated electrical activity in human muscles,” The Journal of Physiology, vol. 123, no. 1, pp. ?. 214-224, Jan. 1954.
[12] A. A. Travill, “Electromyographic study of the extensor apparatus of the forearm,” The Anatomical Record, vol.144, no.4, pp. 373-376, Dec. 1962.
[13] C. Castellini, A. Davaslli, G. Sandini, and E. Gruppioni, “Fine detection of grasp force and posture by amputees via surface electromyography,” Journal of Physiology-Paris, vol.103, no.3-5, pp. 255-262, Sept. 2009.
[14] J.Hashemi, K. Hashtrudi-Zaad, E. Morin and P. Mousavi, “Enhanced dynamic EMG-force estimation through calibration and PCI modeling,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.23, no.1, pp.41-50, May 2014.
[15] L. C. Brereton and S. M. McGill, “Frequency response of spine extensors during rapid isometric contractions: effects of muscle length and tension,” Journal of Electromyography and Kinesiology, vol. 8, no. 4, pp. 227- 232, Aug. 1998.
[16] J. R. Potvin and S. H. M. Brown, “Less is more: high pass filtering, to remove up to 99% of the surface EMG signal power, improves EMG-based biceps brachii muscle force estimates,” Journal of Electromyography and Kinesiology. vol. 14, no. 3, pp. 389-399, Aug.1998.
[17] P. Madeleine, K. Sogaard, P. Bajaj, and L. Arend-Nielsen, “Mechanomyography and electromyography force relationships during concentric, isometric and eccentric contractions,” Journal of Electromyography and Kinesiology, vol. 11, no. 2, pp. 113-121, May 2001.
[18] J. R. Potvin, R. W. Norman and S. M. McGill, “Mechanically corrected EMG for the continuous estimation of erector spinae muscle loading during repetitive lifting,” European Journal of Applied Physiology and Occupational Physiology, vol. 74, no. 1-2, pp. 119- 132, Aug. 1996.
[19] D. Staudenmann, D. F. Stegeman, J.V. Dieen, and I. Kingma, “Towards optimal multi-channel EMG electrode configurations in muscle force estimation: a high density EMG study,” Journal of Electromyography and Kinesiology, vol. 15, no. 1, pp. 1-11, March 2005.
[20] P. R. Cavanagh and Komi P. V. “Electromechanical delay in human skeletal muscle under concentric and eccentric contractions,” European Journal of applied Physiology and Occupational Physiology, vol. 42, no. 3, pp. 159-163. Nov. 1979.
[21] D. A. Gabriel and J. P. Boucher, “Effects of repetitive dynamic contractions upon electromechanical delay,” European Journal of applied Physiology and Occupational Physiology, vol. 79, no. 1, pp. 37-40, Jan. 1998.
[22] H. J. Hermens, C. Disselhorst-Klug, B. Freriks, and G.Rau, “Development of recommendations for SEMG sensors and sensor placement procedures,” Journal of electromyography and Kinesiology, vol. 10, no. 5, pp. 361-374, Oct. 2000.
[23] H. Ghapanchizadeh, S. Ahmad, A. J. Ishak and M. S. Al- Quraishi, “Review of surface electrode placement for recording electromyography signals,” Biomedical Research - India, Special Issue, pp.S1-S7, 2017.
[24] E. Criswell, “Cram`s Introduction to Surface Electromyography”, 2nd ed., Burlington, Massachusetts: Jones & Bartlett Publishers, 2010.
Keywords
electromyogram (EMG), pattern recognition, bionic hand control, electromyography, biosignal amplifier.