A Systematic Review on Emotion Recognition System Using Physiological Signals: Data Acquisition and Methodology

Abstract

Emotion recognition systems (ERS) have become a popular research field to contribute to human-machine interaction in different areas. Different kinds of applications on ERS can serve different purposes. Artificial intelligence (AI) and the internet of things (IoT) are the technologies behind such applications. The main objective of this study is to enable researchers and developers to search for the most suitable options to develop an emotional state recognition system. More specifically, this paper presents work on ERS, which is built using physiological signals extracted from biosensors. It also presents details of how the extracted physiological signals are used to identify the user's emotional state. In this review, the sensors are categorized based on their modality: contact-based sensors and contactless sensors. Next, the ERS process is presented together with the reported results for each described technique. Articles from four different research databases were reviewed, of which 147 articles from 2009 to 2021 were referred to that are related to ERS using physiological signals. This paper should be significant for researchers developing systems that integrate human emotion recognition capability. The findings reported here can guide them in choosing suitable methods for their systems. Doi: 10.28991/ESJ-2022-06-05-017 Full Text: PDF

Emotion Recognition From Heart Rate Variability With a Hybrid System Combined Hidden Markov Model and Poincare Plot

“…Among these developments, computer-based human emotion recognition system (ERS) has not been an exception. However, this research area needs to be mature, and a comprehensive ERS has yet to reach total capacity (Tawsif et al, 2022;Mauss & Robinson, 2009).…”

“…Researchers have employed various emotion elicitation protocols, feature extraction techniques, and classification methods to develop an ERS. Many studies have used diverse induction techniques to stimulate emotions, like visual paradigms, auditory stimulation, real-life experiences, computer games, recall, and imagery (Tawsif et al, 2022;Kim & Andre, 2008). However, to reach an optimum ERS, the crucial elements are evaluation methods of emotions and feature extraction and selection.…”

“…In other words, in contrast to facial ERS, a person cannot mask their emotions, and physiological signals can reflect emotional changes with high precision. Many physiological signals have been employed for emotion recognition and classification (Tawsif et al, 2022;Kim et al, 2004). One of the most frequently used physiological signals is Electroencephalogram (EEG).…”

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“…IoT has transformed the way humans interact with devices and systems in their surroundings, ranging from smart homes to autonomous vehicles (6)(7)(8). IoT is often integrated with artificial intelligence (AI) (9). One area where IoT has made a significant contribution is in enhancing comfort and energy efficiency in the environment, especially in regulating room temperature and humidity (10)(11)(12).…”