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 as...

Full description

Bibliographic Details
Published in:Advances in Science, Technology and Engineering Systems
Main Author: Kamaruddin N.; Nasir M.H.M.; Wahab A.
Format: Article
Language:English
Published: ASTES Publishers 2019
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071358566&doi=10.25046%2faj040424&partnerID=40&md5=ee81e9cb32bbf811e79141743794b881
id 2-s2.0-85071358566
spelling 2-s2.0-85071358566
Kamaruddin N.; Nasir M.H.M.; Wahab A.
Dysphoria detection using EEG signals
2019
Advances in Science, Technology and Engineering Systems
4
4
10.25046/aj040424
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071358566&doi=10.25046%2faj040424&partnerID=40&md5=ee81e9cb32bbf811e79141743794b881
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. © 2019 ASTES Publishers. All rights reserved.
ASTES Publishers
24156698
English
Article
All Open Access; Gold Open Access
author Kamaruddin N.; Nasir M.H.M.; Wahab A.
spellingShingle Kamaruddin N.; Nasir M.H.M.; Wahab A.
Dysphoria detection using EEG signals
author_facet Kamaruddin N.; Nasir M.H.M.; Wahab A.
author_sort Kamaruddin N.; Nasir M.H.M.; Wahab A.
title Dysphoria detection using EEG signals
title_short 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_sort Dysphoria detection using EEG signals
publishDate 2019
container_title Advances in Science, Technology and Engineering Systems
container_volume 4
container_issue 4
doi_str_mv 10.25046/aj040424
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071358566&doi=10.25046%2faj040424&partnerID=40&md5=ee81e9cb32bbf811e79141743794b881
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. © 2019 ASTES Publishers. All rights reserved.
publisher ASTES Publishers
issn 24156698
language English
format Article
accesstype All Open Access; Gold Open Access
record_format scopus
collection Scopus
_version_ 1812871799993532416