EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.]
Brain Computer Interface or BCI is a technology that creates new communication channel where human brain (via Electroencephalography) can communicate with electronic devices.EEG signal is produced by the neurons, where every thought, emotion and movement can generate different patterns of EEG signal...
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| Format: | Article |
| Language: | English |
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Faculty of Electrical Engineering, Universiti Teknologi MARA, Shah Alam
2017
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/29587/ |
| _version_ | 1848807273896345600 |
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| author | Hamzah, Nabilah Zaini, Norliza Sani, Maizura Ismail, Nurlaila |
| author_facet | Hamzah, Nabilah Zaini, Norliza Sani, Maizura Ismail, Nurlaila |
| author_sort | Hamzah, Nabilah |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | Brain Computer Interface or BCI is a technology that creates new communication channel where human brain (via Electroencephalography) can communicate with electronic devices.EEG signal is produced by the neurons, where every thought, emotion and movement can generate different patterns of EEG signal. There are two objectives defined for this research. The first objective is to compare the EEG data generated for actual and imaginary motor movement when lifting the left and right hand by using Support Vector Machine (SVM).The second objective is to find the correlation in EEG pattern between the actual motor movement and imaginary motor movement data, which is also based on SVM classification analysis. From the classification analysis, the accuracy for actual left and right-hand lifting movement is obtained at 90%. Meanwhile, the accuracy for classifying EEG data of imaginary left and right-hand lifting movement is obtained at 75%. In finding the correlation between the actual and imaginary EEG data, a classification analysis is also done by combining the actual and imaginary data. In this experiment, the accuracy in classifying the left and right-hand lifting activities is obtained at 78.8%. The significant accuracy measures obtained means that there is some correlation in EEG patterns between the actual motor movement and imaginary motor movement of lifting either left or right hand. |
| first_indexed | 2025-11-14T22:40:13Z |
| format | Article |
| id | uitm-29587 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T22:40:13Z |
| publishDate | 2017 |
| publisher | Faculty of Electrical Engineering, Universiti Teknologi MARA, Shah Alam |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-295872020-04-17T13:19:33Z https://ir.uitm.edu.my/id/eprint/29587/ EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.] jeesr Hamzah, Nabilah Zaini, Norliza Sani, Maizura Ismail, Nurlaila Computer engineering. Computer hardware Brain Computer Interface or BCI is a technology that creates new communication channel where human brain (via Electroencephalography) can communicate with electronic devices.EEG signal is produced by the neurons, where every thought, emotion and movement can generate different patterns of EEG signal. There are two objectives defined for this research. The first objective is to compare the EEG data generated for actual and imaginary motor movement when lifting the left and right hand by using Support Vector Machine (SVM).The second objective is to find the correlation in EEG pattern between the actual motor movement and imaginary motor movement data, which is also based on SVM classification analysis. From the classification analysis, the accuracy for actual left and right-hand lifting movement is obtained at 90%. Meanwhile, the accuracy for classifying EEG data of imaginary left and right-hand lifting movement is obtained at 75%. In finding the correlation between the actual and imaginary EEG data, a classification analysis is also done by combining the actual and imaginary data. In this experiment, the accuracy in classifying the left and right-hand lifting activities is obtained at 78.8%. The significant accuracy measures obtained means that there is some correlation in EEG patterns between the actual motor movement and imaginary motor movement of lifting either left or right hand. Faculty of Electrical Engineering, Universiti Teknologi MARA, Shah Alam 2017-06 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/29587/1/29587.pdf Hamzah, Nabilah and Zaini, Norliza and Sani, Maizura and Ismail, Nurlaila (2017) EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.]. (2017) Journal of Electrical and Electronic Systems Research (JEESR) <https://ir.uitm.edu.my/view/publication/Journal_of_Electrical_and_Electronic_Systems_Research_=28JEESR=29.html>, 10. ISSN 1985-5389 https://jeesr.uitm.edu.my/ |
| spellingShingle | Computer engineering. Computer hardware Hamzah, Nabilah Zaini, Norliza Sani, Maizura Ismail, Nurlaila EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.] |
| title | EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.] |
| title_full | EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.] |
| title_fullStr | EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.] |
| title_full_unstemmed | EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.] |
| title_short | EEG analysis on actual and imaginary left and right hand lifting using Support Vector Machine (SVM) / Nabilah Hamzah .. [et al.] |
| title_sort | eeg analysis on actual and imaginary left and right hand lifting using support vector machine (svm) / nabilah hamzah .. [et al.] |
| topic | Computer engineering. Computer hardware |
| url | https://ir.uitm.edu.my/id/eprint/29587/ https://ir.uitm.edu.my/id/eprint/29587/ |