Multisensor fusion approach: a case study on human physiological factor-based emotion recognition and classification
by A. Reyana; P. Vijayalakshmi; Sandeep Kautish
International Journal of Computer Applications in Technology (IJCAT), Vol. 66, No. 2, 2021

Abstract: In people's daily life human emotion plays an essential role, the mental state accompanied with physiological changes. Experts have always seen that monitoring the perception of emotional changes at an early stage is a matter of concern before becoming serious. Within the next few years, emotion recognition and classification is destined to become an important component in human-machine interaction. Today medical field has a great deal in using physiological signals for detection of heart sounds and identifying heart diseases. Thus the parameters temperature and heartbeat can identify the major health risks. This paper takes a new look at the development of an emotion recognition system using physiological signals. In this context, the signals are obtained from the body sensors such as muscle pressure sensor, heartbeat sensor, accelerometer, and capacitive sensor. The emotions observed are happy (excited), sad, angry, and neutral (relaxed). The results of the proposed system shows an accuracy percentage for the emotional states, happy 80%, sad 70%, angry 90%, and neutral 100%.

Online publication date: Mon, 20-Dec-2021

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