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Automatic Emotion Recognition Based on EEG and ECG Signals While Listening to Quranic Recitation Compared with Listening to Music

机译:与EEG和ECG信号的自动情感识别在听古兰经朗诵时,与听音乐相比

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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.
机译:放松和平静是人们不断寻求的两种情绪。人们经常用来减少张力和压力水平的一种流行方法正在听各种类型的放松音乐。然而,古兰经由真主的话语组成,最终赋予人类的利益。穆斯林强烈地认为,听取或阅读古兰经带来了舒适,愉快和信心,否则将避开他们,但是,科学证据仍然需要证明这种信念具有科学依据。最近,研究人员使用电生理学来探索电气现象和身体过程之间的关系。该研究旨在学习和分析听古兰经朗诵时,与聆听放松音乐相比,学习和分析人民大脑和心灵的电力活动。本研究使用两种类型的电生理学读数:脑电图(EEG)和心电图(ECG)。 EEG测量脑电活动,ECG测量心脏电信。从二十五个科目中收集了EEG和ECG数据。然后,将机器学习算法应用于EEG和ECG信号。结果表明,古兰经思想表明了受试者的情绪的积极转变:从消极的前体情绪到平静,幸福条件,由脑电图和心电图信号的正价表示。相比之下,放松音乐表明,关于EEG分析中的价值的阳性变换,然而,关于ECG音乐数据分析,结果显示了大多数音乐轨道的负变换。

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