Hossain, farhad and Yaacob, Hamwira Sakti and Nordin, Azlin (2021) Development of Unified Neuro-Affective Classification Tool (UNACT). IOP Conference Series: Materials Science and Engineering, 1077 (1). ISSN 1757-8981 E-ISSN 1757-899X
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Abstract
Brain signals have been analysed to understand the affective state of different cognitive and mental conditions. For example, through the analysis, we can visualize the changes of emotion while driving, identify an autistic kid, understand the conditions that stimulate attention while studying, and many more, because emotion has a strong impact on cognitive processes in humans' activities. This can be done through a machine learning technique, which includes data acquisition, pre-processing, feature extraction, and training. However, no existing tool integrates all supervised machine learning processes for affective state classification, which makes the process tedious and time-consuming for an analyst by doing programming. Therefore, this project aims to develop a brain analysis tool, namely Unified Neuro-Affective Classification Tool (UNACT). It consists of 3 main functions including training, classifying, and analysis. In the study of affective state electroencephalogram (EEG) signals have used, which measures brain signals. UNACT uses the Butterworth Bandpass filter for EEG signal filtering, the Power Spectral Density method for feature extraction, and the Multi-layer perceptron (MLP) for emotion classification. This tool can be used by a non-technical person to perform affective-emotional state analysis without having programming knowledge.
| Item Type: | Article (Journal) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology |
| Depositing User: | Dr Hamwira Yaacob |
| Date Deposited: | 20 Apr 2021 15:00 |
| Last Modified: | 20 Apr 2021 15:01 |
| URI: | http://irep.iium.edu.my/id/eprint/89438 |
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