Electrocardiogram-Based Emotion Recognition Systems and Their Applications in Healthcare—A Review

Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device with affective computing is beneficial for the mental health and wellbeing of individuals that are stressed, anguished, or depressed. Emotion re...

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Published inSensors (Basel, Switzerland) Vol. 21; no. 15; p. 5015
Main Authors Hasnul, Muhammad Anas, Aziz, Nor Azlina Ab, Alelyani, Salem, Mohana, Mohamed, Aziz, Azlan Abd
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 23.07.2021
MDPI
Subjects
affective computing
Biosensors
electrocardiogram (ECG)
Electrocardiography
emotion recognition system
Emotions
healthcare
Heart rate
Influence
Nervous system
Physiology
Review
Online AccessGet full text

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Abstract Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device with affective computing is beneficial for the mental health and wellbeing of individuals that are stressed, anguished, or depressed. Emotion recognition systems are an important technology that enables affective computing. Currently, there are a lot of ways to build an emotion recognition system using various techniques and algorithms. This review paper focuses on emotion recognition research that adopted electrocardiograms (ECGs) as a unimodal approach as well as part of a multimodal approach for emotion recognition systems. Critical observations of data collection, pre-processing, feature extraction, feature selection and dimensionality reduction, classification, and validation are conducted. This paper also highlights the architectures with accuracy of above 90%. The available ECG-inclusive affective databases are also reviewed, and a popularity analysis is presented. Additionally, the benefit of emotion recognition systems towards healthcare systems is also reviewed here. Based on the literature reviewed, a thorough discussion on the subject matter and future works is suggested and concluded. The findings presented here are beneficial for prospective researchers to look into the summary of previous works conducted in the field of ECG-based emotion recognition systems, and for identifying gaps in the area, as well as in developing and designing future applications of emotion recognition systems, especially in improving healthcare.
AbstractList Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device with affective computing is beneficial for the mental health and wellbeing of individuals that are stressed, anguished, or depressed. Emotion recognition systems are an important technology that enables affective computing. Currently, there are a lot of ways to build an emotion recognition system using various techniques and algorithms. This review paper focuses on emotion recognition research that adopted electrocardiograms (ECGs) as a unimodal approach as well as part of a multimodal approach for emotion recognition systems. Critical observations of data collection, pre-processing, feature extraction, feature selection and dimensionality reduction, classification, and validation are conducted. This paper also highlights the architectures with accuracy of above 90%. The available ECG-inclusive affective databases are also reviewed, and a popularity analysis is presented. Additionally, the benefit of emotion recognition systems towards healthcare systems is also reviewed here. Based on the literature reviewed, a thorough discussion on the subject matter and future works is suggested and concluded. The findings presented here are beneficial for prospective researchers to look into the summary of previous works conducted in the field of ECG-based emotion recognition systems, and for identifying gaps in the area, as well as in developing and designing future applications of emotion recognition systems, especially in improving healthcare.
Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device with affective computing is beneficial for the mental health and wellbeing of individuals that are stressed, anguished, or depressed. Emotion recognition systems are an important technology that enables affective computing. Currently, there are a lot of ways to build an emotion recognition system using various techniques and algorithms. This review paper focuses on emotion recognition research that adopted electrocardiograms (ECGs) as a unimodal approach as well as part of a multimodal approach for emotion recognition systems. Critical observations of data collection, pre-processing, feature extraction, feature selection and dimensionality reduction, classification, and validation are conducted. This paper also highlights the architectures with accuracy of above 90%. The available ECG-inclusive affective databases are also reviewed, and a popularity analysis is presented. Additionally, the benefit of emotion recognition systems towards healthcare systems is also reviewed here. Based on the literature reviewed, a thorough discussion on the subject matter and future works is suggested and concluded. The findings presented here are beneficial for prospective researchers to look into the summary of previous works conducted in the field of ECG-based emotion recognition systems, and for identifying gaps in the area, as well as in developing and designing future applications of emotion recognition systems, especially in improving healthcare.Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device with affective computing is beneficial for the mental health and wellbeing of individuals that are stressed, anguished, or depressed. Emotion recognition systems are an important technology that enables affective computing. Currently, there are a lot of ways to build an emotion recognition system using various techniques and algorithms. This review paper focuses on emotion recognition research that adopted electrocardiograms (ECGs) as a unimodal approach as well as part of a multimodal approach for emotion recognition systems. Critical observations of data collection, pre-processing, feature extraction, feature selection and dimensionality reduction, classification, and validation are conducted. This paper also highlights the architectures with accuracy of above 90%. The available ECG-inclusive affective databases are also reviewed, and a popularity analysis is presented. Additionally, the benefit of emotion recognition systems towards healthcare systems is also reviewed here. Based on the literature reviewed, a thorough discussion on the subject matter and future works is suggested and concluded. The findings presented here are beneficial for prospective researchers to look into the summary of previous works conducted in the field of ECG-based emotion recognition systems, and for identifying gaps in the area, as well as in developing and designing future applications of emotion recognition systems, especially in improving healthcare.
Author Mohana, Mohamed
Aziz, Azlan Abd
Aziz, Nor Azlina Ab
Alelyani, Salem
Hasnul, Muhammad Anas
AuthorAffiliation 1 Faculty of Engineering and Technology, Multimedia University, Melaka 75450, Malaysia; 1141126389@student.mmu.edu.my (M.A.H.); azlan.abdaziz@mmu.edu.my (A.A.A.)
2 Center for Artificial Intelligence (CAI), King Khalid University, Abha 61421, Saudi Arabia; s.alelyani@kku.edu.sa (S.A.); mmuhanna@kku.edu.sa (M.M.)
3 College of Computer Science, King Khalid University, Abha 61421, Saudi Arabia
AuthorAffiliation_xml – name: 1 Faculty of Engineering and Technology, Multimedia University, Melaka 75450, Malaysia; 1141126389@student.mmu.edu.my (M.A.H.); azlan.abdaziz@mmu.edu.my (A.A.A.)
– name: 2 Center for Artificial Intelligence (CAI), King Khalid University, Abha 61421, Saudi Arabia; s.alelyani@kku.edu.sa (S.A.); mmuhanna@kku.edu.sa (M.M.)
– name: 3 College of Computer Science, King Khalid University, Abha 61421, Saudi Arabia
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  fullname: Aziz, Azlan Abd
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Snippet Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device...
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SubjectTerms affective computing
Biosensors
electrocardiogram (ECG)
Electrocardiography
emotion recognition system
Emotions
healthcare
Heart rate
Influence
Nervous system
Physiology
Review
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Title Electrocardiogram-Based Emotion Recognition Systems and Their Applications in Healthcare—A Review
URI https://www.proquest.com/docview/2558928112
https://www.proquest.com/docview/2560060962
https://pubmed.ncbi.nlm.nih.gov/PMC8348698
https://doaj.org/article/3a3d6fda27c345079e25eb3eabb19057
Volume 21
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