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Double Threshold Method for EMG-based Human-Computer Interface  

Lee Myungjoon (Korea Orthopedics & Rehabilitation Engineering Center (KOREC))
Moon Inhyuk (Korea Orthopedics & Rehabilitation Engineering Center (KOREC))
Mun Museong (Korea Orthopedics & Rehabilitation Engineering Center (KOREC))
Publication Information
Journal of Biomedical Engineering Research / v.25, no.6, 2004 , pp. 471-478 More about this Journal
Abstract
Electromyogram (EMC) signal generated by voluntary contraction of muscles is often used in a rehabilitation devices such as an upper limb prosthesis because of its distinct output characteristics compared to other bio-signals. This paper proposes an EMG-based human-computer interface (HCI) for the control of the above-elbow prosthesis or the wheelchair. To control such rehabilitation devices, user generates four commands by combining voluntary contraction of two different muscles such as levator scapulae muscles and flexor-extensor carpi ulnaris muscles. The muscle contraction is detected by comparing the mean absolute value of the EMG signal with a preset threshold value. However. since the time difference in muscle firing can occur when the patient tries simultaneous co-contraction of two muscles, it is difficult to determine whether the patient's intention is co-contraction. Hence, the use of the comparison method using a single threshold value is not feasible for recognizing such co-contraction motion. Here, we propose a novel method using double threshold values composed of a primary threshold and an auxiliary threshold. Using the double threshold method, the co-contraction state is easily detected, and diverse interface commands can be used for the EMG-based HCI. The experimental results with real-time EMG processing showed that the double threshold method is feasible for the EMG-based HCI to control the myoelectric prosthetic hand and the powered wheelchair.
Keywords
Electromyogram; Human-computer interface; Double threshold value; Myoelectric prosthetic hand;
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  • Reference
1 M. Nader, 'The substitution of missing hands with myoelectric prostheses', Clin. Orthop. Related Res., 9-17, 1990
2 D. Nishikawa, W. Yu, H. Yokoi, and Y. Kakazu, 'EMG Prosthetic Hand Controller Using Real-Time Learning Method', Proc. of IEEE Int'l Conf. on Systems, Man and Cybernetics, 1999   DOI
3 S. Schulz, C Pylatiuk, and G. Bretthauer, 'A New Ultralight Anthropomorphic Hand', Proc of Int'l Conf. on Robotics and Automation, 2001   DOI
4 D.J. Kim, W.K. Song, and Z.N. Bien, 'Effective Intention Reading in Rehabilitation Robots', Proc. of 2nd Int'l Workshop on Human-friendly Welfare Robotic Systems, pp. 179-184, 2001
5 http://www.delsys.com
6 E. Kevin, and H. Bernard, 'A Robust, Real-time Control Scheme for Multifunction Myoelectric Control', IEEE Transactions on biomedical engineering, Vol. 50, No.7, 2003   DOI   PUBMED   ScienceOn
7 R. Sorbye, ,'Myoelectric Controlled Hand Prostheses in Children, Clinical Consultations', Proc. 2nd European Conf. of Rehabilitation International, 1978
8 A. Barreto, S. Scargle, and M. Adjouadi, 'A practical EMG-based human-computer interface for users with motor disabilities', J. of Rehabilitation Research and Development, Vol. 37, no. 1 , 2000   PUBMED
9 Gips and P. Oliviere, 'EagleEyes: An Eye Control System for Persons with Disabilities', Proc. of int'l Cong. on Technologyand Persons with Disabilities, 1996
10 CJ. De Luca, 'The Use of Surface Electromyography in Biomechanics,' Journal of Applied Biomechanics, Vol. 13, No.2, pp. 135-163, 1997   DOI
11 http://www.ottobock.com
12 H. Schmidl, The INAIL-CECA prostheses, Centro Protesi INAIL di Budrio, 1983
13 R.C Simpson and S.P. Levine,'Voice Control of a Powered Wheelchair,' IEEE Trans. on Neural Systems and Rehabilitation Engineering, Vol. 10, No.2, 2002   DOI   ScienceOn
14 I. Moon, S. Joung, and Y. Kum, 'Safe and Reliable Intelligent Wheelchair' Robot with Human Robot Interaction,' Proc. of IEEE Int'l Conf. on Robotics and Automation, 2002   DOI
15 L. Kirup, A. Searle, A. Craig, P. Mcisaac, and P. Moses, 'EEG-based system for rapid on-off switching without prior learning', Medical and Biological Engineering and Computing, Vol. 35, pp. 504-509, 1997   DOI   ScienceOn
16 H. Huang and C Chiang, 'DSP-Based Controller for a Multi-Degree Prosthetic Hand', Proc. of IEEE Int'l Conf. on Robotics and Automation, pp. 1378-1383, 2000   DOI
17 B. Claudio, D. Angelo, F. Cesare, S. Rinaldo, and S. Terenzi, 'Automatic tuning of myoelectric prostheses', Journal of Rehabilitation Research and Development, Vol. 35, No.3, pp. 294-304, 1998
18 CJ. De Luca, Surface Electromyography: Detection and Recording, Report of Delsys Incorporated, 2002