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http://dx.doi.org/10.5391/JKIIS.2012.22.5.533

The Implementation of the Intelligent Exoskeleton Robot Arm Using ElectroMiogram(EMG) vital Signal  

Jeon, Bu-Il (한국기술교육대학교 전기전자통신공학부)
Cho, Hyun-Chan (한국기술교육대학교 전기전자통신공학부)
Jeon, Hong-Tae (중앙대학교 전자전기공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.22, no.5, 2012 , pp. 533-539 More about this Journal
Abstract
The purpose of this study is to estimate a validity of control signal through a design of Exoskeleton Robot Arm's capable of intelligent recognition as a human arm's motion by using realtime processed data of generated EMG signals. By an intelligent algorithm, the EMG output value of human biceps and triceps muscles contraction can be recognized and used for the control over exoskeleton arm corresponding to human's recognition and judgement. The EMG sensing data of muscles contraction and relaxation are used as the input signal from human's body to operate the Exoskeleton Robot Arm thus copying human arm motion. An intelligent control of Exoskeleton Robot Arm is to design the analog control circuit which processes the input data, and then to manufacture an integrated control board. And then abstracted signal is passed by DSP signal processing, Fuzzy logic algorithm is designed for a accurate prediction of weight or load through the intelligent algorithm, and design an Exoskeleton Robot Arm to express a human's intention.
Keywords
EMG signal; Fuzzy Logic Algorithm; DSP; Filter; Exoskeleton Robot Arm;
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  • Reference
1 http://www.seedtech.co.kr, "SEED Technology"
2 Bok-Hee Jin, Electromyography, Korea Medical Science, 2007.
3 A.M. Trzynadlowski, DSP controllers-An emerging tool forelectric motor drives, IEEE Ind. Electron. Soc. Newslett, pp. 2-13, 2006.
4 K. Ooe and T. Fukuda, "Development of the artificial larynx with neck EMG signal control," Int. Symposium on Micro-NanoMechatronics and Human Science, 2010.
5 http://www.laxtha.com, "LAXTHA"
6 Artemiadis, "An EMG-Based Robot Control Scheme Robust to Time-Varying EMG Signal Features," IEEE Transactions on Information Technology in Biomedicine, vol. 14, Issue 3, pp. 582-588, 2010.   DOI
7 R. M. Tong, "The Evaluation of Fuzzy Models Derived from Experimental Data," Fuzzy Sets and Systems, vol. 4, pp. 1-12, 1980.   DOI   ScienceOn
8 Witold Pedrycz and Fernando Gomide, Fuzzy Systems Engineering, Wiley Interscience, 2007.
9 Heng Cao, "Design frame of a leg exoskeleton for load-carrying augmentation," IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 426-431, 2009.
10 A. Zoss, H. Kazerooni, A. Chu. "On the mechanical design of theBerkeley Lower Extremity Exoskeleton (BLEEX)," in Proc. IEEE Int.Conf. Intell. Robots Syst., Edmonton, pp. 3465-3472, 2005.
11 A. B. Ajiboye, and R. F. Weir, "A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 13, no. 3, pp. 280-291, 2005.   DOI