A neuro-fuzzy control system based on feature extraction of surface electromyogram signal for solar-powered wheelchair

Kaiser, MS, Chowdhury, ZI, Mamun, SA, Hussain, A and Mahmud, M ORCID logoORCID: https://orcid.org/0000-0002-2037-8348, 2016. A neuro-fuzzy control system based on feature extraction of surface electromyogram signal for solar-powered wheelchair. Cognitive Computation, 8 (5), pp. 946-954. ISSN 1866-9956

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Abstract

This paper presents the design and implementation of a low-cost solar-powered wheelchair for physically challenged people. The signals necessary to maneuver the wheelchair are acquired from different muscles of the hand using surface electromyography (sEMG) technique. The raw sEMG signals are collected from the upper limb muscles which are then processed, characterized, and classified to extract necessary features for the generation of control signals to be used for the automated movement of the wheelchair. An artificial neural network-based classifier is constructed to classify the patterns and features extracted from the raw sEMG signals. The classification accuracy of the extracted parameters from the sEMG signals is found to be relatively high in comparison with the existing methods. The extracted parameters used to generate control signals that are then fed into a microcomputer-based control system (MiCS). A solar-powered wheelchair prototype is developed, and the above MiCS is introduced to control its maneuver using the sEMG signals. The prototype is then thoroughly tested with sEMG signals from patients of different age groups. Also, the life cycle cost analysis of the proposed wheelchair revealed that it is financially feasible and cost-effective.

Item Type: Journal article
Publication Title: Cognitive Computation
Creators: Kaiser, M.S., Chowdhury, Z.I., Mamun, S.A., Hussain, A. and Mahmud, M.
Publisher: Springer
Date: October 2016
Volume: 8
Number: 5
ISSN: 1866-9956
Identifiers:
Number
Type
10.1007/s12559-016-9398-4
DOI
9398
Publisher Item Identifier
Divisions: Schools > School of Science and Technology
Record created by: Linda Sullivan
Date Added: 23 Jul 2018 15:24
Last Modified: 23 Jul 2018 15:24
URI: https://irep.ntu.ac.uk/id/eprint/34137

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