Multimodal Analysis of Human Fear
Swagata Sarkar, Assistant Professor, Sri Sairam Engineering College, Chennai, India.
Manuscript received on 26 August 2019. | Revised Manuscript received on 08 September 2019. | Manuscript published on 30 September 2019. | PP: 3654-3659 | Volume-8 Issue-11, September 2019. | Retrieval Number: K19090981119/2019©BEIESP | DOI: 10.35940/ijitee.K1909.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Human emotion detection is very much relevant in today’s scenario. Human life become fast due to modernisation. People like to lead sophisticated, peaceful and healthy life. Human emotion plays a vital role in present scenario. Six basic emotions are considered for research purpose. Those are happy, sad, fear, anger, disgust and boredom. In this paper, human fear is analysed based on Electroencephalogram (EEG) signal, physical parameters and facial images. Statistical parameters both from time and frequency domain are used as feature set. Own database is used for the analysis. It is seen from the result that the efficiency is enhanced significantly after multimodal analysis of human fear. The classification results for discrete wavelet transform and logistic regression model are improved by 8.33% and 8.33% respectively.
Keywords: EEG signal, Emotion, Facial Images, Physical Parameters
Scope of the Article: Human Computer Interaction (HCI)