A computational model for stress intervention using affective brain-computer interfaces

Abdul Rahim Dapit, Ain Shaheada and Othman, Marini and Azuddin, Muna and Ahmad Puzi, Asmarani and Rahardja, Untung (2025) A computational model for stress intervention using affective brain-computer interfaces. In: 2025 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), 26-28 August 2025, KOTA KINABALU, SABAH.

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Abstract

Stress is a growing public health concern that negatively impacts individual well-being, making accurate detection of stress emotions essential yet challenging due to the limitations of self-reporting and the complexity of emotional states. Electroencephalography (EEG) offers an objective means to monitor brain activity related to stress emotions, but effective interpretation requires advanced analytical methods. This research aims to develop a reliable EEG-based model for stress emotion detection by collecting EEG data from participants exposed to stress-inducing stimuli and applying machine learning techniques for classification. The expected outcome is an improved stress detection model that augments traditional subjective measures. By advancing EEG-based stress emotion detection, this study seeks to contribute to better mental health interventions and more effective management of stress-related conditions.

Item Type:	Proceeding Paper (Other)
Uncontrolled Keywords:	Stress, Electroencephalography (EEG), Emotion, Machine Learning
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	MARINI OTHMAN
Date Deposited:	13 May 2026 13:09
Last Modified:	13 May 2026 13:09
Queue Number:	2026-05-Q3261
URI:	http://irep.iium.edu.my/id/eprint/128698

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