Dysphoria detection using EEG signals
Dysphoria is a state faced when one experienced disappointment. If it is not handled properly, dysphoria may trigger acute stress, anxiety and depression. Typically, the individual who experienced dysphoria are in-denial because dysphoria is always being associated with negative connotations such...
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| Format: | Article |
| Language: | English English |
| Published: |
ASTES Publishers
2019
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| Online Access: | http://irep.iium.edu.my/79846/ http://irep.iium.edu.my/79846/1/79846_Dysphoria%20Detection%20using%20EEG%20Signals_article.pdf http://irep.iium.edu.my/79846/2/79846_Dysphoria%20Detection%20using%20EEG%20Signals_scopus.pdf |
| _version_ | 1848788855762714624 |
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| author | Kamaruddin, Norhaslinda Mohd Nasir, Mohd Hafiz Abdul Rahman, Abdul Wahab |
| author_facet | Kamaruddin, Norhaslinda Mohd Nasir, Mohd Hafiz Abdul Rahman, Abdul Wahab |
| author_sort | Kamaruddin, Norhaslinda |
| building | IIUM Repository |
| collection | Online Access |
| description | Dysphoria is a state faced when one experienced disappointment. If it is not handled
properly, dysphoria may trigger acute stress, anxiety and depression. Typically, the
individual who experienced dysphoria are in-denial because dysphoria is always being
associated with negative connotations such as incompetency to handle pressure, weak
personality and lack of will power. To date, there is no accurate instrument to measure
dysphoria except using questionnaire by psychologists, such as: Depression, Anxiety and
Stress Scale (DASS) and Nepean Dysphoria Scale (NDS-24). Participants may suppress or
exaggerate their answers resulting in misdiagnosis. In this work, a theoretical Dysphoria
Model of Affect (DMoA) is developed for dysphoria detection. Based on the hypothesis that
dysphoria is related to negative emotion, the input from brain signal is captured using
electroencephalogram (EEG) device to detect negative emotions. The results from
analyzing the EEG signals were compared with DASS and NDS questionnaires for
correlation analysis. It is observed that the proposed DMoA approach can identify negative
emotions ranging from 55% to 77% accuracy. In addition, the NDS questionnaire seems to
provide better distinction for dysphoria as compared to DASS and is similar to the result
yielded by DMoA in detecting dysphoria. Thus, DMoA approach can be used as an
alternative for early dysphoria detection to assist early intervention in identifying the
patients’ mental states. Subsequently, DMoA approach can be implemented as another
possible solution for early detection of dysphoria thus providing an enhancement to the
present NDS instruments providing psychologists and psychiatrists with a quantitative tool
for better analysis of the patients’ state. |
| first_indexed | 2025-11-14T17:47:28Z |
| format | Article |
| id | iium-79846 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:47:28Z |
| publishDate | 2019 |
| publisher | ASTES Publishers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-798462020-06-25T08:42:28Z http://irep.iium.edu.my/79846/ Dysphoria detection using EEG signals Kamaruddin, Norhaslinda Mohd Nasir, Mohd Hafiz Abdul Rahman, Abdul Wahab T Technology (General) Dysphoria is a state faced when one experienced disappointment. If it is not handled properly, dysphoria may trigger acute stress, anxiety and depression. Typically, the individual who experienced dysphoria are in-denial because dysphoria is always being associated with negative connotations such as incompetency to handle pressure, weak personality and lack of will power. To date, there is no accurate instrument to measure dysphoria except using questionnaire by psychologists, such as: Depression, Anxiety and Stress Scale (DASS) and Nepean Dysphoria Scale (NDS-24). Participants may suppress or exaggerate their answers resulting in misdiagnosis. In this work, a theoretical Dysphoria Model of Affect (DMoA) is developed for dysphoria detection. Based on the hypothesis that dysphoria is related to negative emotion, the input from brain signal is captured using electroencephalogram (EEG) device to detect negative emotions. The results from analyzing the EEG signals were compared with DASS and NDS questionnaires for correlation analysis. It is observed that the proposed DMoA approach can identify negative emotions ranging from 55% to 77% accuracy. In addition, the NDS questionnaire seems to provide better distinction for dysphoria as compared to DASS and is similar to the result yielded by DMoA in detecting dysphoria. Thus, DMoA approach can be used as an alternative for early dysphoria detection to assist early intervention in identifying the patients’ mental states. Subsequently, DMoA approach can be implemented as another possible solution for early detection of dysphoria thus providing an enhancement to the present NDS instruments providing psychologists and psychiatrists with a quantitative tool for better analysis of the patients’ state. ASTES Publishers 2019 Article NonPeerReviewed application/pdf en http://irep.iium.edu.my/79846/1/79846_Dysphoria%20Detection%20using%20EEG%20Signals_article.pdf application/pdf en http://irep.iium.edu.my/79846/2/79846_Dysphoria%20Detection%20using%20EEG%20Signals_scopus.pdf Kamaruddin, Norhaslinda and Mohd Nasir, Mohd Hafiz and Abdul Rahman, Abdul Wahab (2019) Dysphoria detection using EEG signals. Advances in Science, Technology and Engineering Systems, 4 (4). pp. 197-205. ISSN 2415-6698 https://astesj.com/v04/i04/p24/ 10.25046/aj040424 |
| spellingShingle | T Technology (General) Kamaruddin, Norhaslinda Mohd Nasir, Mohd Hafiz Abdul Rahman, Abdul Wahab Dysphoria detection using EEG signals |
| title | Dysphoria detection using EEG signals |
| title_full | Dysphoria detection using EEG signals |
| title_fullStr | Dysphoria detection using EEG signals |
| title_full_unstemmed | Dysphoria detection using EEG signals |
| title_short | Dysphoria detection using EEG signals |
| title_sort | dysphoria detection using eeg signals |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/79846/ http://irep.iium.edu.my/79846/ http://irep.iium.edu.my/79846/ http://irep.iium.edu.my/79846/1/79846_Dysphoria%20Detection%20using%20EEG%20Signals_article.pdf http://irep.iium.edu.my/79846/2/79846_Dysphoria%20Detection%20using%20EEG%20Signals_scopus.pdf |