Detection of Lower Limb Movements using Sensorimotor Rhythms

In contrast to other brain imaging methods, electroencephalography (EEG) has become a feasible method for investigating brain activity and is an interesting modality for brain-machine interfaces (BMIs) due to its portability and high temporal resolution. In this work, sensorimotor rhythms (SMR) sign...

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Main Authors: Al-Quraishi, M.S., Elamvazuthi, I., Tang, T.B., Al-Qurishi, M., Parasuraman, S., Borboni, A.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.29189 /
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124162289&doi=10.1109%2fICIAS49414.2021.9642696&partnerID=40&md5=c46ca53d1bdad9f47203815faeceb0ae
http://eprints.utp.edu.my/29189/
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spelling utp-eprints.291892022-03-25T01:11:27Z Detection of Lower Limb Movements using Sensorimotor Rhythms Al-Quraishi, M.S. Elamvazuthi, I. Tang, T.B. Al-Qurishi, M. Parasuraman, S. Borboni, A. In contrast to other brain imaging methods, electroencephalography (EEG) has become a feasible method for investigating brain activity and is an interesting modality for brain-machine interfaces (BMIs) due to its portability and high temporal resolution. In this work, sensorimotor rhythms (SMR) signal was utilized to classify ankle joint movements. To achieve this goal the EEG signal in the motor cortex area was measured using 21 electrodes during the motor execution task of ankle joint movements. The event-related (de)synchronization (ERD/ ERS) technique was utilized to quantify the event-related in relation to EEG power changes. Inter and intralimb ankle movements were detected and classified. The results show interlimb movements can be recognized better than intralimb movements. Where the average classification accuracy of the interlimb movements was 89.44 ± 10.26 and 84.83 ± 13.65 for the intralimb movements. © 2021 IEEE. Institute of Electrical and Electronics Engineers Inc. 2021 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124162289&doi=10.1109%2fICIAS49414.2021.9642696&partnerID=40&md5=c46ca53d1bdad9f47203815faeceb0ae Al-Quraishi, M.S. and Elamvazuthi, I. and Tang, T.B. and Al-Qurishi, M. and Parasuraman, S. and Borboni, A. (2021) Detection of Lower Limb Movements using Sensorimotor Rhythms. In: UNSPECIFIED. http://eprints.utp.edu.my/29189/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description In contrast to other brain imaging methods, electroencephalography (EEG) has become a feasible method for investigating brain activity and is an interesting modality for brain-machine interfaces (BMIs) due to its portability and high temporal resolution. In this work, sensorimotor rhythms (SMR) signal was utilized to classify ankle joint movements. To achieve this goal the EEG signal in the motor cortex area was measured using 21 electrodes during the motor execution task of ankle joint movements. The event-related (de)synchronization (ERD/ ERS) technique was utilized to quantify the event-related in relation to EEG power changes. Inter and intralimb ankle movements were detected and classified. The results show interlimb movements can be recognized better than intralimb movements. Where the average classification accuracy of the interlimb movements was 89.44 ± 10.26 and 84.83 ± 13.65 for the intralimb movements. © 2021 IEEE.
format Conference or Workshop Item
author Al-Quraishi, M.S.
Elamvazuthi, I.
Tang, T.B.
Al-Qurishi, M.
Parasuraman, S.
Borboni, A.
spellingShingle Al-Quraishi, M.S.
Elamvazuthi, I.
Tang, T.B.
Al-Qurishi, M.
Parasuraman, S.
Borboni, A.
Detection of Lower Limb Movements using Sensorimotor Rhythms
author_sort Al-Quraishi, M.S.
title Detection of Lower Limb Movements using Sensorimotor Rhythms
title_short Detection of Lower Limb Movements using Sensorimotor Rhythms
title_full Detection of Lower Limb Movements using Sensorimotor Rhythms
title_fullStr Detection of Lower Limb Movements using Sensorimotor Rhythms
title_full_unstemmed Detection of Lower Limb Movements using Sensorimotor Rhythms
title_sort detection of lower limb movements using sensorimotor rhythms
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124162289&doi=10.1109%2fICIAS49414.2021.9642696&partnerID=40&md5=c46ca53d1bdad9f47203815faeceb0ae
http://eprints.utp.edu.my/29189/
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score 11.62408