Emotion Classification Using Physiological Signals

Abstract

The interpretation of an individual's conduct is significantly influenced by their emotions, or affects. It plays an
important role in our daily life because it greatly aids in cognitive functions such as perception, interaction, problemsolving,
and decision-making. It is a complex psychological state that involves a behavioral reaction, a physiological
reaction, and a subjective journey (the individual's feelings). Affect recognition is a technique that aids in determining
the kind of emotion a person is experiencing. Affective Computing (AC) is a well-established field within computer
science that seeks to identify, model, and synthesize human emotions by utilizing technical tools and approaches to
bridge the gap between computing systems and human affect. It is clear in the field of AC that a person's personality,
character, and mood are among the many other personal characteristics that impact their emotions (Park et al., 2007).
Predicting these variables, with a focus on personality, is important for a variety of applications, including social
media, entertainment, healthcare, education, and virtual worlds, to enhance people's everyday activities.