Emotion recognition from EEG signal and health status assessment based on the intensity of the emotional impact99 views
Keywords:Recognition; Emotion; EEG; Wavelet entropy; DEAP.
Each person's emotional state is an important factor reflecting the subject's health and psycho-physiological condition; psychological disturbances that produce negative emotions along with feelings of resentment, hostility, and fatigue. Along with headaches, psychological disorders are the second most common phenomenon in the world in terms of prevalence. Emotions with a strong impact over a long period of time can predict for us the impending behaviors and state of the subject. Many research works have focused on detecting emotions by different methods. However, most of the topics only focus on detecting specific emotions; In fact, whether emotions are positive or negative if the impact is large enough over time, it can have an impact on people's health and behavior. In this study, we approach the method of assessing the subject's state based on the intensity of the emotional stimulus.
. B. A. Scott and T. A. Judge, “Insomnia, Emotions, and Job Satisfaction: A Multilevel Study”, Journal of Management, Vol. 32, No. 5, pp. 622-645, (2006). DOI: https://doi.org/10.1177/0149206306289762
. Emmady PD, Anilkumar AC. “EEG Abnormal Waveforms”. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; (2023). Available from: https://www.ncbi.nlm.nih.gov/books/NBK557655/.
. Camaioni M, Scarpelli S, Gorgoni M, Alfonsi V, De Gennaro L. “EEG Patterns Prior to Motor Activations of Parasomnias: A Systematic Review”. Nat Sci Sleep. 13:713-728 (2021)
. Lefter, R.; Cojocariu, R.O.; Ciobica, A.; Balmus, I.-M.; Mavroudis, I.; Kis, A. “Interactions between Sleep and Emotions in Humans and Animal Models”. Medicina 58 (2): 274 (2022) DOI: https://doi.org/10.3390/medicina58020274
. S. Koelstra, C. Muehl, M. Soleymani, J.-S. Lee, A. Yazdani, T. Ebrahimi, T. Pun, A. Nijholt and I. Patras “A Database for Emotion Analysis using Physiological Signals” IEEE Transactions on Affective Computing, vol. 3, pp. 18-31, (2012). DOI: https://doi.org/10.1109/T-AFFC.2011.15
. A. Apicella, P. Arpaia, F. Isgrò, G. Mastrati, N. Moccaldi, "A Survey on EEG-Based Solutions for Emotion Recognition With a Low Number of Channels", IEEE Access, vol.10, pp.117411-117428, (2022). DOI: https://doi.org/10.1109/ACCESS.2022.3219844
. Dwivedi D, Chamoli A, Rana SK. “Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data”. Entropy; 25(2):240 (2023). https://doi.org/10.3390/e2502024. DOI: https://doi.org/10.3390/e25020240
. Maëva Moyne, Guillaume Legendre, Luc Arnal, Samika Kumar, Virginie Sterpenich, Margitta Seeck, Didier Grandjean, Sophie Schwartz, Patrik Vuilleumier, Judith Domínguez-Borràs, “Brain reactivity to emotion persists in NREM sleep and is associated with individual dream recall”, Cerebral Cortex Communications, Vol.3, No. 1, (2022). DOI: https://doi.org/10.1093/texcom/tgac003
. Vandekerckhove M, Wang YL. “Emotion, emotion regulation and sleep: An intimate relationship”. AIMS Neurosci, 5(1):1-17 (2018). doi: 10.3934/Neuroscience.2018.1.1. PMID: 32341948; PMCID: PMC7181893. DOI: https://doi.org/10.3934/Neuroscience.2018.5.1
. Yanjing Wang, Cimin Dai, Yongcong Shao, Chuan Wang, Qianxiang Zhou, “Changes in ventromedial prefrontal cortex functional connectivity are correlated with increased risk-taking after total sleep deprivation”. Behavioural Brain Research, Vol. 418 (2022). DOI: https://doi.org/10.1016/j.bbr.2021.113674