Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing Research
Affective computing focuses on instilling emotion awareness in machines. This area has attracted many researchers globally. However, the lack of an affective database based on physiological signals from the Asian continent has been reported. This is an important issue for ensuring inclusiveness and...
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MDPI AG
2023-02-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/16/3/130 |
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| author | Nor Azlina Ab. Aziz Tawsif K. Sharifah Noor Masidayu Sayed Ismail Muhammad Anas Hasnul Kamarulzaman Ab. Aziz Siti Zainab Ibrahim Azlan Abd. Aziz J. Emerson Raja |
| author_facet | Nor Azlina Ab. Aziz Tawsif K. Sharifah Noor Masidayu Sayed Ismail Muhammad Anas Hasnul Kamarulzaman Ab. Aziz Siti Zainab Ibrahim Azlan Abd. Aziz J. Emerson Raja |
| author_sort | Nor Azlina Ab. Aziz |
| collection | DOAJ |
| description | Affective computing focuses on instilling emotion awareness in machines. This area has attracted many researchers globally. However, the lack of an affective database based on physiological signals from the Asian continent has been reported. This is an important issue for ensuring inclusiveness and avoiding bias in this field. This paper introduces an emotion recognition database, the Asian Affective and Emotional State (A2ES) dataset, for affective computing research. The database comprises electrocardiogram (ECG) and photoplethysmography (PPG) recordings from 47 Asian participants of various ethnicities. The subjects were exposed to 25 carefully selected audio–visual stimuli to elicit specific targeted emotions. An analysis of the participants’ self-assessment and a list of the 25 stimuli utilised are also presented in this work. Emotion recognition systems are built using ECG and PPG data; five machine learning algorithms: support vector machine (SVM), k-nearest neighbour (KNN), naive Bayes (NB), decision tree (DT), and random forest (RF); and deep learning techniques. The performance of the systems built are presented and compared. The SVM was found to be the best learning algorithm for the ECG data, while RF was the best for the PPG data. The proposed database is available to other researchers. |
| first_indexed | 2024-03-11T07:02:58Z |
| format | Article |
| id | doaj.art-df1c12f9f1494b1f879af4eb21c506bd |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-11T07:02:58Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-df1c12f9f1494b1f879af4eb21c506bd2023-11-17T09:08:56ZengMDPI AGAlgorithms1999-48932023-02-0116313010.3390/a16030130Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing ResearchNor Azlina Ab. Aziz0Tawsif K.1Sharifah Noor Masidayu Sayed Ismail2Muhammad Anas Hasnul3Kamarulzaman Ab. Aziz4Siti Zainab Ibrahim5Azlan Abd. Aziz6J. Emerson Raja7Faculty of Engineering & Technology, Multimedia University, Bukit Beruang 75450, Melaka, MalaysiaFaculty of Engineering & Technology, Multimedia University, Bukit Beruang 75450, Melaka, MalaysiaFaculty of Information Science & Technology, Multimedia University, Bukit Beruang 75450, Melaka, MalaysiaFaculty of Engineering & Technology, Multimedia University, Bukit Beruang 75450, Melaka, MalaysiaFaculty of Business, Multimedia University, Bukit Beruang 75450, Melaka, MalaysiaSchool of Computing and Informatics, Albukhary International University, Jalan Tun Abdul Razak, Alor Setar 05200, Kedah, MalaysiaFaculty of Engineering & Technology, Multimedia University, Bukit Beruang 75450, Melaka, MalaysiaFaculty of Engineering & Technology, Multimedia University, Bukit Beruang 75450, Melaka, MalaysiaAffective computing focuses on instilling emotion awareness in machines. This area has attracted many researchers globally. However, the lack of an affective database based on physiological signals from the Asian continent has been reported. This is an important issue for ensuring inclusiveness and avoiding bias in this field. This paper introduces an emotion recognition database, the Asian Affective and Emotional State (A2ES) dataset, for affective computing research. The database comprises electrocardiogram (ECG) and photoplethysmography (PPG) recordings from 47 Asian participants of various ethnicities. The subjects were exposed to 25 carefully selected audio–visual stimuli to elicit specific targeted emotions. An analysis of the participants’ self-assessment and a list of the 25 stimuli utilised are also presented in this work. Emotion recognition systems are built using ECG and PPG data; five machine learning algorithms: support vector machine (SVM), k-nearest neighbour (KNN), naive Bayes (NB), decision tree (DT), and random forest (RF); and deep learning techniques. The performance of the systems built are presented and compared. The SVM was found to be the best learning algorithm for the ECG data, while RF was the best for the PPG data. The proposed database is available to other researchers.https://www.mdpi.com/1999-4893/16/3/130affective computingemotion recognition systemphysiological signals |
| spellingShingle | Nor Azlina Ab. Aziz Tawsif K. Sharifah Noor Masidayu Sayed Ismail Muhammad Anas Hasnul Kamarulzaman Ab. Aziz Siti Zainab Ibrahim Azlan Abd. Aziz J. Emerson Raja Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing Research Algorithms affective computing emotion recognition system physiological signals |
| title | Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing Research |
| title_full | Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing Research |
| title_fullStr | Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing Research |
| title_full_unstemmed | Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing Research |
| title_short | Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing Research |
| title_sort | asian affective and emotional state a2es dataset of ecg and ppg for affective computing research |
| topic | affective computing emotion recognition system physiological signals |
| url | https://www.mdpi.com/1999-4893/16/3/130 |
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