eprintid: 15457
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/54/57
datestamp: 2023-11-10 03:30:05
lastmod: 2023-11-10 03:30:05
status_changed: 2023-11-10 01:59:32
type: conference_item
metadata_visibility: show
creators_name: Al-Quraishi, M.S.
creators_name: Elamvazuthi, I.
creators_name: Tang, T.B.
creators_name: Al-Qurishi, M.
creators_name: Parasuraman, S.
creators_name: Borboni, A.
title: Detection of Lower Limb Movements using Sensorimotor Rhythms
ispublished: pub
keywords: Brain; Brain computer interface; Brain mapping; Electroencephalography; Joints (anatomy), Ankle joints; Brain activity; ERD; High temporal resolution; Joint movement; Limb movements; Lower limb; Motor-cortex; Movement; Sensorimotors, Electrophysiology
note: cited By 0; Conference of 8th International Conference on Intelligent and Advanced Systems, ICIAS 2021 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:175661
abstract: 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.
date: 2021
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124162289&doi=10.1109%2fICIAS49414.2021.9642696&partnerID=40&md5=c46ca53d1bdad9f47203815faeceb0ae
id_number: 10.1109/ICIAS49414.2021.9642696
full_text_status: none
publication: International Conference on Intelligent and Advanced Systems: Enhance the Present for a Sustainable Future, ICIAS 2021
refereed: TRUE
isbn: 9781728176666
citation:   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.