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Artificial Neural Network Analysis On Motor Imagery Electroencephalogram

Research on brain signal analysis has been performed decades ago. This research field has benefited other industries such as health and analytics. Various analysis methods either conventional or intelligent methods had been explored in ensuring the best application was produced. In this project, a s...

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Main Authors: Suhaimi, N.S., Yusoff, M.Z., Saad, M.N.M.
Format: Conference or Workshop Item
Published: 2022
Online Access:http://scholars.utp.edu.my/id/eprint/33982/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141618666&doi=10.1109%2fROMA55875.2022.9915671&partnerID=40&md5=f501946da66d945f3ceae1d7d1413440
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id oai:scholars.utp.edu.my:33982
record_format eprints
spelling oai:scholars.utp.edu.my:339822022-12-20T04:01:26Z http://scholars.utp.edu.my/id/eprint/33982/ Artificial Neural Network Analysis On Motor Imagery Electroencephalogram Suhaimi, N.S. Yusoff, M.Z. Saad, M.N.M. Research on brain signal analysis has been performed decades ago. This research field has benefited other industries such as health and analytics. Various analysis methods either conventional or intelligent methods had been explored in ensuring the best application was produced. In this project, a secondary dataset from motor cortex brain signals had been utilized and the dataset is captured by a non-invasive method using an electroencephalogram (EEG) tool. The dataset is then proposed to be extracted and classified using the Deep Learning Neural Network method. High accuracy and sensitivity of model analysis are expected as the outcome of the project. Besides, statistical analysis had been conducted to observe the significance between electrode placement and the output of the dataset. Thus, the Artificial Neural Network model was observed as the final finding. © 2022 IEEE. 2022 Conference or Workshop Item NonPeerReviewed Suhaimi, N.S. and Yusoff, M.Z. and Saad, M.N.M. (2022) Artificial Neural Network Analysis On Motor Imagery Electroencephalogram. In: UNSPECIFIED. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141618666&doi=10.1109%2fROMA55875.2022.9915671&partnerID=40&md5=f501946da66d945f3ceae1d7d1413440 10.1109/ROMA55875.2022.9915671 10.1109/ROMA55875.2022.9915671 10.1109/ROMA55875.2022.9915671
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Research on brain signal analysis has been performed decades ago. This research field has benefited other industries such as health and analytics. Various analysis methods either conventional or intelligent methods had been explored in ensuring the best application was produced. In this project, a secondary dataset from motor cortex brain signals had been utilized and the dataset is captured by a non-invasive method using an electroencephalogram (EEG) tool. The dataset is then proposed to be extracted and classified using the Deep Learning Neural Network method. High accuracy and sensitivity of model analysis are expected as the outcome of the project. Besides, statistical analysis had been conducted to observe the significance between electrode placement and the output of the dataset. Thus, the Artificial Neural Network model was observed as the final finding. © 2022 IEEE.
format Conference or Workshop Item
author Suhaimi, N.S.
Yusoff, M.Z.
Saad, M.N.M.
spellingShingle Suhaimi, N.S.
Yusoff, M.Z.
Saad, M.N.M.
Artificial Neural Network Analysis On Motor Imagery Electroencephalogram
author_facet Suhaimi, N.S.
Yusoff, M.Z.
Saad, M.N.M.
author_sort Suhaimi, N.S.
title Artificial Neural Network Analysis On Motor Imagery Electroencephalogram
title_short Artificial Neural Network Analysis On Motor Imagery Electroencephalogram
title_full Artificial Neural Network Analysis On Motor Imagery Electroencephalogram
title_fullStr Artificial Neural Network Analysis On Motor Imagery Electroencephalogram
title_full_unstemmed Artificial Neural Network Analysis On Motor Imagery Electroencephalogram
title_sort artificial neural network analysis on motor imagery electroencephalogram
publishDate 2022
url http://scholars.utp.edu.my/id/eprint/33982/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141618666&doi=10.1109%2fROMA55875.2022.9915671&partnerID=40&md5=f501946da66d945f3ceae1d7d1413440
_version_ 1753790763330699264
score 13.222552

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