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Modulation of sensorimotor rhythms for brain-computer interface using motor imagery with online feedback

Abdalsalam, E. and Yusoff, M.Z. and Malik, A. and Kamel, N.S. and Mahmoud, D. (2018) Modulation of sensorimotor rhythms for brain-computer interface using motor imagery with online feedback. Signal, Image and Video Processing, 12 (3). pp. 557-564.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

This research studies the impact of the imagination of movements and associated feedbacks on the modulation of sensorimotor electroencephalographic (EEG) rhythms, for the online controls of a brain-computer interface (BCI). Nine subjects with no physical or mental impairments were selected. The number of sessions was five: one calibration and four feedback sessions. A computer screen�s cursor movement was controlled in one dimension using EEG-based four-class BCI involving motor imagery tasks of moving the right hand, the left hand, both hands, or both feet. Our findings reveal that the visual feedback applied during motor imagery movement modulates sensorimotor EEG rhythms clearly in the mu and beta bands. The analyses of event-related desynchronization/synchronization (ERD/ERS) suggest significant differences between brain activities in the calibration and feedback sessions; large ERDs during the online feedback sessions compared to that in the calibration session have been observed. The increasing ERDs in the online feedback session were noticed over the mu1 (8�10 Hz) and upper beta (18�24 Hz) rhythms, resulting in the cursor control success rate at 73.3. © 2017, Springer-Verlag London Ltd.

Item Type:Article
Impact Factor:cited By 0
Uncontrolled Keywords:Brain; Calibration; Electroencephalography; Feedback; Information dissemination; Interfaces (computer); Modulation; Visual communication, Electroencephalographic (EEG); ERD/ERS; Event related desynchronization; Imagination of movements; Mental impairments; Motor imagery; Motor imagery tasks; Sensorimotor rhythm (SMR), Brain computer interface
Departments / MOR / COE:Research Institutes > Institute for Health Analytics
ID Code:21737
Deposited By: Ahmad Suhairi
Deposited On:01 Aug 2018 02:06
Last Modified:16 Nov 2018 08:37

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