Assessing the Stress-Reducing Effects of Quranic Listening: An EEG-Based Classification Study

Stress is the sensation of physical or emotional anxiety, arising from various incidents or thoughts that can be frustrating, irritating, or worrisome. Listening to the holy Quran is a method that can help alleviate stress. This research delves into the impact of the Quran on human stress levels by utilizing the Muse2 portable device to record electroencephalogram (EEG) signals. The dataset was collected from 17 participants, comprising 9 males and 8 females aged between 20 and 60 years. This study employed EEG signal processing to identify potential stress responses in individuals when they listen to the holy Quran. A signal pre-processing technique was employed, and various characteristics were extracted to fulfill the research objectives. Additionally, computational machine learning techniques were applied to determine if these signal characteristics are most relevant in detecting changes in adverse situations. Participants' EEG signals were recorded while they listened to the Quran using the portable Muse 2 device. Participants were asked about their stress levels both before and after listening to the Quran. We subsequently employed ANOVA to test the significance of the experiment results, which yielded significant outcomes with P-values of 0.029. Six classifier algorithms were employed to classify the data, with the Conventional Neural Network (CNN) and XGboost classifiers outperforming the others, achieving the highest precision rates of 97.28% and 97.15%, respectively, in the two-level classification. Based on these results, it can be affirmed that listening to the holy Quran effectively reduces stress levels.