Publication Type : Conference Paper
Publisher : 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings
Source : 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., p.169-172 (2017)
Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015917873&doi=10.1109%2fDISCOVER.2016.7806239&partnerID=40&md5=cc6d09778fa9722ecc1c0fa9e3d88932
ISBN : 9781509016235
Keywords : Application systems, Biomedical signal processing, Classification (of information), Computer circuits, Cost effective design, Cost effectiveness, Costs, Distributed computer systems, Electric network parameters, Electromyography, Feature classification, Feature extraction, Feature parameters, noise, Prosthetic hands, Prosthetics, Robotics, Signal acquisitions, Signal amplifications, Signal processing, VLSI circuits
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Mechanical Engineering
Verified : Yes
Year : 2017
Abstract : Electromyography (EMG) signals have been extensively used as a control signal in robotics, rehabilitation and health care. In this paper, cost effective design of prosthetic hand using EMG control is presented. Signal amplification and filtering is the primary step in surface EMG signal processing and application systems. Quality of the acquired EMG signal depends on the amplifiers and filters employed. Single channel continuous EMG signal has been acquired from the users arm for various hand movements. The acquired signal is passed through various stages of filters and amplifiers for amplification and noise reduction. The conditioned analog signal is converted into digital samples. After the signal acquisition process, features are extracted from the acquired signal and the extracted features are reduced to minimize the number of computations. These reduced feature parameters are used to classify the signal for different hand movements. Once the classifier identifies the intended motion, the control signal will be generated and given to the motors in the prosthetic hand to perform the intended movements. Experiments were done to find the efficiency of the developed system and it is found that this system can give basic movements at a very low cost. © 2016 IEEE.
Cite this Research Publication : K. Sharmila, Sarath, T. V., and Dr. K. I. Ramachandran, “EMG controlled low cost prosthetic arm”, in 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings, 2017, pp. 169-172.