Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25444
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dc.contributor.authorKaiser, M Shamim-
dc.contributor.authorChowdhury, Zamshed Iqbal-
dc.contributor.authorMamun, Shamim Al-
dc.contributor.authorHussain, Amir-
dc.contributor.authorMahmud, Mufti-
dc.date.accessioned2017-08-26T03:45:21Z-
dc.date.issued2016-10-
dc.identifier.urihttp://hdl.handle.net/1893/25444-
dc.description.abstractThis 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.en_UK
dc.language.isoen-
dc.publisherSpringer-
dc.relationKaiser MS, Chowdhury ZI, Mamun SA, Hussain A & Mahmud M (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.-
dc.rightsThe publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.-
dc.subjectSurface EMG signalsen_UK
dc.subjectRehabilitationen_UK
dc.subjectNeuro-fuzzy systemen_UK
dc.subjectSolar-powered wheelchairen_UK
dc.subjectWheelchair navigationen_UK
dc.titleA Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchairen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2999-12-31T00:00:00Z-
dc.rights.embargoreasonThe publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.-
dc.identifier.doihttp://dx.doi.org/10.1007/s12559-016-9398-4-
dc.citation.jtitleCognitive Computation-
dc.citation.issn1866-9956-
dc.citation.volume8-
dc.citation.issue5-
dc.citation.spage946-
dc.citation.epage954-
dc.citation.publicationstatusPublished-
dc.citation.peerreviewedRefereed-
dc.type.statusPublisher version (final published refereed version)-
dc.author.emailahu@cs.stir.ac.uk-
dc.citation.date24/03/2016-
dc.contributor.affiliationJahangirnagar University-
dc.contributor.affiliationJahangirnagar University-
dc.contributor.affiliationJahangirnagar University-
dc.contributor.affiliationComputing Science - CSM Dept-
dc.contributor.affiliationUniversity of Padua-
dc.rights.embargoterms2999-12-31-
dc.rights.embargoliftdate2999-12-31-
dc.identifier.isi000386351500015-
Appears in Collections:Computing Science and Mathematics Journal Articles

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