TY - GEN
T1 - Electroencephalography-Neurofeedback for Decoding and Modulating Human Emotions
AU - Alzahmi, Sara Mohammed
AU - Alyammahi, Bashayer Mohammed
AU - Alyammahi, Maitha Saeed
AU - Alshamsi, Mariam Rashed
AU - Belkacem, Abdelkader Nasreddine
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Emotions play an important role in the health and well-being of humans. It is associated with feedback on human interaction with the surrounding environment, decision-making, and intelligence. Electroencephalography (EEG)-based brain-computer interfaces (BCI) technology can be used to sense the emotional state of humans. Therefore, this research introduces a non-invasive BCI system that provides solutions for psychiatrists to treat patients suffering from chronic sadness, depression, and anxiety without medications. Here, we propose an EEG-based neurofeedback system for decoding and modulating human emotions. This system decodes three emotions: happiness, sadness, and neutral emotions. From the decoded emotion, the system generates visual and auditory feedback to train the patient to regulate his/her brain activity to improve his/her mental health. We collected EEG data corresponding to each emotion from twelve female participants while watching multiple stimuli to develop a support vector machine (SVM) model with a radial basis function (RBF) kernel. The SVM model decoded the desired emotions with 92.3% accuracy. Then, EEG- Neurofeedback sessions decode the patient's emotions in real-time and generate visual and auditory feedback using the decoded emotions.
AB - Emotions play an important role in the health and well-being of humans. It is associated with feedback on human interaction with the surrounding environment, decision-making, and intelligence. Electroencephalography (EEG)-based brain-computer interfaces (BCI) technology can be used to sense the emotional state of humans. Therefore, this research introduces a non-invasive BCI system that provides solutions for psychiatrists to treat patients suffering from chronic sadness, depression, and anxiety without medications. Here, we propose an EEG-based neurofeedback system for decoding and modulating human emotions. This system decodes three emotions: happiness, sadness, and neutral emotions. From the decoded emotion, the system generates visual and auditory feedback to train the patient to regulate his/her brain activity to improve his/her mental health. We collected EEG data corresponding to each emotion from twelve female participants while watching multiple stimuli to develop a support vector machine (SVM) model with a radial basis function (RBF) kernel. The SVM model decoded the desired emotions with 92.3% accuracy. Then, EEG- Neurofeedback sessions decode the patient's emotions in real-time and generate visual and auditory feedback using the decoded emotions.
KW - Brain-Computer Interface
KW - Decode human emotions
KW - Electroencephalography
KW - Emotions
KW - Modulate brain activity
KW - Neurofeedback
KW - Support Vector Machine (SVM)
UR - http://www.scopus.com/inward/record.url?scp=85146728649&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146728649&partnerID=8YFLogxK
U2 - 10.1109/BIBM55620.2022.9995408
DO - 10.1109/BIBM55620.2022.9995408
M3 - Conference contribution
AN - SCOPUS:85146728649
T3 - Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022
SP - 1988
EP - 1993
BT - Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022
A2 - Adjeroh, Donald
A2 - Long, Qi
A2 - Shi, Xinghua
A2 - Guo, Fei
A2 - Hu, Xiaohua
A2 - Aluru, Srinivas
A2 - Narasimhan, Giri
A2 - Wang, Jianxin
A2 - Kang, Mingon
A2 - Mondal, Ananda M.
A2 - Liu, Jin
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022
Y2 - 6 December 2022 through 8 December 2022
ER -
