Automatic emotion recognition based on EEG and ECG signals while listening to quranic recitation compared with listening to music

• Main Authors: Ahmed Yahya Al-Galal, Sabaa, Taha Alshaikhli, Imad Fakhri, Abdul Rahman, Abdul Wahab
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2016
• Subjects: T Technology (General)
• Online Access: http://irep.iium.edu.my/56058/1/56058-updated.pdf; http://irep.iium.edu.my/56058/2/56058-Automatic%20emotion%20recognition%20based%20on%20EEG%20and%20ECG%20signals%20while%20listening%20to%20quranic%20recitation%20compared%20with%20listening%20to%20music_SCOPUS.pdf; http://irep.iium.edu.my/56058/; http://ieeexplore.ieee.org/document/7814915/
• Institution: Universiti Islam Antarabangsa Malaysia

Relaxation and calmness are two emotions that people continually seek. One popular method people frequently use to reduce their tension and pressure levels is listening to various types of relaxing music. However, the Quran is composed of Allah’s words, which were ultimately given for the benefit of humanity. Muslims strongly believe that listening to or reading the Quran brings them comfort, pleasure and confidence that would otherwise elude them; however, scientific evidence is still required to prove that this belief has a scientific basis. Recently, researchers have used electrophysiology to explore the relationships between electrical phenomena and body processes. This research aims to study and analyse the electrical activity of people's brains and hearts when listening to Quranic recitation compared with listening to relaxing music. Two types of electrophysiology readings are used in this research: electroencephalograms (EEGs) and electrocardiograms (ECGs). An EEG measures brain electrical activity, and an ECG measures heart electrical activity. EEG and ECG data were collected from twenty-five subjects. Then, machine learning algorithms were applied to the EEG and ECG signals. The result showed that Quranic recitation demonstrated a positive transformation of the subjects' emotions: from negative precursor emotions to calmness and happiness conditions denoted by a positive valence for the EEG and ECG signals. In contrast, relaxing music showed a positive transformation with regard to the valence in the EEG analysis; however, with respect to the ECG music data analysis, the results revealed a negative transformation for most of the music tracks.