Determination and classification of human stress index using nonparametric analysis of EEG signals / Norizam Sulaiman
Regardless of type of stress, either mental stress, emotional stress or physical stress, it definitely affects human lifestyle and work performance. There are two prominent methods in assessing stress which are psychological assessment (qualitative method) and physiological assessment (quantitative...
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| Format: | Book Section |
| Language: | en |
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Institute of Graduate Studies, UiTM
2016
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| Online Access: | https://ir.uitm.edu.my/id/eprint/19613/1/ABS_NORIZAM%20SULAIMAN%20TDRA%20VOL%209%20IGS%2016.pdf https://ir.uitm.edu.my/id/eprint/19613/ |
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| _version_ | 1833060628963524608 |
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| author | Sulaiman, Norizam |
| author_facet | Sulaiman, Norizam |
| author_sort | Sulaiman, Norizam |
| building | Tun Abdul Razak Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Mara |
| content_source | UiTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Regardless of type of stress, either mental stress, emotional stress or physical stress, it definitely affects human lifestyle and work performance. There are two prominent methods in assessing stress which are psychological assessment (qualitative method) and physiological assessment (quantitative method). This research proposes a new stress index based on Electroencephalogram (EEG) signals and non-parametric analysis of the signals. In non-parametric method, the EEG features that might relate to stress are extracted in term of Asymmetry Ratio (AR), Relative Energy Ratio (RER), Spectral Centroids (SC) and Spectral Entropy (SE). The selected features are fed to the k-Nearest Neighbor (k- NN) classifier to identify the stressed group among the four experimental groups being tested. The classification results are based on accuracy, sensitivity and specificity. To support the classification results using k-NN classifier, the clustering techniques using Fuzzy C-Means (FCM) and Fuzzy K-Means (FKM) are implemented. To ensure the robustness of the classifier, the cross-validation technique using k-fold and leave-oneout is performed to the classifier… |
| format | Book Section |
| id | my.uitm.ir-19613 |
| institution | Universiti Teknologi Mara |
| language | en |
| publishDate | 2016 |
| publisher | Institute of Graduate Studies, UiTM |
| record_format | eprints |
| spelling | my.uitm.ir-196132018-06-07T02:37:42Z https://ir.uitm.edu.my/id/eprint/19613/ Determination and classification of human stress index using nonparametric analysis of EEG signals / Norizam Sulaiman Sulaiman, Norizam Malaysia Regardless of type of stress, either mental stress, emotional stress or physical stress, it definitely affects human lifestyle and work performance. There are two prominent methods in assessing stress which are psychological assessment (qualitative method) and physiological assessment (quantitative method). This research proposes a new stress index based on Electroencephalogram (EEG) signals and non-parametric analysis of the signals. In non-parametric method, the EEG features that might relate to stress are extracted in term of Asymmetry Ratio (AR), Relative Energy Ratio (RER), Spectral Centroids (SC) and Spectral Entropy (SE). The selected features are fed to the k-Nearest Neighbor (k- NN) classifier to identify the stressed group among the four experimental groups being tested. The classification results are based on accuracy, sensitivity and specificity. To support the classification results using k-NN classifier, the clustering techniques using Fuzzy C-Means (FCM) and Fuzzy K-Means (FKM) are implemented. To ensure the robustness of the classifier, the cross-validation technique using k-fold and leave-oneout is performed to the classifier… Institute of Graduate Studies, UiTM 2016 Book Section PeerReviewed text en https://ir.uitm.edu.my/id/eprint/19613/1/ABS_NORIZAM%20SULAIMAN%20TDRA%20VOL%209%20IGS%2016.pdf Determination and classification of human stress index using nonparametric analysis of EEG signals / Norizam Sulaiman. (2016) In: The Doctoral Research Abstracts. IGS Biannual Publication, 9 (9). Institute of Graduate Studies, UiTM, Shah Alam. |
| spellingShingle | Malaysia Sulaiman, Norizam Determination and classification of human stress index using nonparametric analysis of EEG signals / Norizam Sulaiman |
| title | Determination and classification of human stress index using
nonparametric analysis of EEG signals / Norizam Sulaiman |
| title_full | Determination and classification of human stress index using
nonparametric analysis of EEG signals / Norizam Sulaiman |
| title_fullStr | Determination and classification of human stress index using
nonparametric analysis of EEG signals / Norizam Sulaiman |
| title_full_unstemmed | Determination and classification of human stress index using
nonparametric analysis of EEG signals / Norizam Sulaiman |
| title_short | Determination and classification of human stress index using
nonparametric analysis of EEG signals / Norizam Sulaiman |
| title_sort | determination and classification of human stress index using
nonparametric analysis of eeg signals / norizam sulaiman |
| topic | Malaysia |
| url | https://ir.uitm.edu.my/id/eprint/19613/1/ABS_NORIZAM%20SULAIMAN%20TDRA%20VOL%209%20IGS%2016.pdf https://ir.uitm.edu.my/id/eprint/19613/ |
| url_provider | http://ir.uitm.edu.my/ |