• A. Inna Reddy
• Prof. G. Narsimha

Emotional state recognition is a crucial task for achieving a new level of Human-Computer Interaction (HCI). Machine Learning applications are penetrating at rapid speed into spheres of everyday life. Recent studies are showing promising results in analyzing physiological signals (EEG, ECG) using Machine Learning for accessing emotional state and its classification. In general, specific emotion is invoked by playing affective videos or sounds. Nevertheless, there is no canonical way for emotional state elucidation. In this study, we present the theories of emotions using discrete model and Valence / Arousal emotion model. The study also emphasized EEG and ECG signals association with human emotions. A series of databases were developed by many researchers to study the classification and correlation of human emotions with physiological signals. The structures of the databases developed by these researchers have variations and each database has oriented in different directions for the sake of elicitation of human emotions.

Human Computer Interaction(HCI), EEG, ECG, Valence / Arousal, HRV, Physiological signal data Datasets, AMIGOS

"A review on human emotions elicitation and association of Physiological signal datasets ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.1862-1873, February-2019, Available :http://www.jetir.org/papers/JETIR1902E62.pdf

"A review on human emotions elicitation and association of Physiological signal datasets ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp1862-1873, February-2019, Available at : http://www.jetir.org/papers/JETIR1902E62.pdf