Citation
K., Tawsif and Ab Aziz, Nor Azlina and Emerson Raja, Joseph and Hossen, Md. Jakir and Mohd Zebaral Hoque, Jesmeen (2022) A Systematic Review on Emotion Recognition System Using Physiological Signals: Data Acquisition and Methodology. Emerging Science Journal, 6 (5). pp. 1167-1198. ISSN 2610-9182
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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.
Item Type: | Article |
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Uncontrolled Keywords: | Emotion Recognition System, Biosensors, Physiological Sensors, Physiological Signals |
Subjects: | R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
Divisions: | Faculty of Engineering and Technology (FET) |
Depositing User: | Ms Nurul Iqtiani Ahmad |
Date Deposited: | 06 Oct 2022 03:25 |
Last Modified: | 06 Oct 2022 03:25 |
URII: | http://shdl.mmu.edu.my/id/eprint/10464 |
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