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Continuous emotion recognition during music listening using EEG signals: A fuzzy parallel cascades model
, Article Applied Soft Computing ; Volume 101 , 2021 ; 15684946 (ISSN) ; Annabestani, M ; Moghimi, S ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
A controversial issue in artificial intelligence is human emotion recognition. This paper presents a fuzzy parallel cascades (FPC) model for predicting the continuous subjective emotional appraisal of music by time-varying spectral content of electroencephalogram (EEG) signals. The EEG, along with an emotional appraisal of 15 subjects, was recorded during listening to seven musical excerpts. The emotional appraisement was recorded along the valence and arousal emotional axes as a continuous signal. The FPC model was composed of parallel cascades with each cascade containing a fuzzy logic-based system. The FPC model performance was evaluated using linear regression (LR), support vector...
Correction to: How resiliency and hope can predict stress of covid-19 by mediating role of spiritual well-being based on machine learning (Journal of Religion and Health, (2021), 60, 4, (2306-2321), 10.1007/s10943-020-01151-z)
, Article Journal of Religion and Health ; Volume 60, Issue 4 , 2021 , Pages 2322-2323 ; 00224197 (ISSN) ; Hosseinian, S ; Hussain, A. J ; Annabestani, M ; Maadal, A ; Radwin, L ; Hassani Abharian, P ; Ghanbari, N ; Khoshkonesh, A ; Sharif University of Technology
Springer
2021
Abstract
The original version of the article was inadvertently published with the ethical code in Ethical Considerations section. This has been corrected with this erratum. The revised texts are given below. © 2021, Springer Science+Business Media, LLC, part of Springer Nature
How resiliency and hope can predict stress of covid-19 by mediating role of spiritual well-being based on machine learning
, Article Journal of Religion and Health ; Volume 60, Issue 4 , 2021 , Pages 2306-2321 ; 00224197 (ISSN) ; Hosseinian, S ; Hussain, A. J ; Annabestani, M ; Maadal, A ; Radwin, L. E ; Hassani Abharian, P ; Pirkashani, N. G ; Khoshkonesh, A ; Sharif University of Technology
Springer
2021
Abstract
Nowadays, artificial intelligence (AI) and machine learning (ML) are playing a tremendous role in all aspects of human life and they have the remarkable potential to solve many problems that classic sciences are unable to solve appropriately. Neuroscience and especially psychiatry is one of the most important fields that can use the potential of AI and ML. This study aims to develop an ML-based model to detect the relationship between resiliency and hope with the stress of COVID-19 by mediating the role of spiritual well-being. An online survey is conducted to assess the psychological responses of Iranian people during the Covid-19 outbreak in the period between March 15 and May 20, 2020, in...