EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and Interpolation
Emotions play a significant role in shaping psychological activities, behaviour, and interpersonal communication. Reflecting this importance, automated emotion classification has become a vital research area in artificial intelligence. Electroencephalogram (EEG)-based emotion recognition is particul...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/13/1/166 |
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| author | Fangyi Li Fusheng Yu Liang Shen Hexi Li Xiaonan Yang Qiang Shen |
| author_facet | Fangyi Li Fusheng Yu Liang Shen Hexi Li Xiaonan Yang Qiang Shen |
| author_sort | Fangyi Li |
| collection | DOAJ |
| description | Emotions play a significant role in shaping psychological activities, behaviour, and interpersonal communication. Reflecting this importance, automated emotion classification has become a vital research area in artificial intelligence. Electroencephalogram (EEG)-based emotion recognition is particularly promising due to its high temporal resolution and resistance to manipulation. This study introduces an advanced fuzzy inference algorithm for EEG data-driven emotion recognition, effectively addressing the ambiguity of emotional states. By combining adaptive fuzzy rule generation, feature evaluation, and weighted fuzzy rule interpolation, the proposed approach achieves accurate emotion classification while handling incomplete knowledge. Experimental results demonstrate that the integrated fuzzy system outperforms state-of-the-art techniques, offering improved recognition accuracy and robustness under uncertainty. |
| format | Article |
| id | doaj-art-ce36551fc3094e718bbd78fe9e790cd5 |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-ce36551fc3094e718bbd78fe9e790cd52025-01-10T13:18:28ZengMDPI AGMathematics2227-73902025-01-0113116610.3390/math13010166EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and InterpolationFangyi Li0Fusheng Yu1Liang Shen2Hexi Li3Xiaonan Yang4Qiang Shen5School of Mathematical Sciences, Beijing Normal University, Beijing 100875, ChinaSchool of Mathematical Sciences, Beijing Normal University, Beijing 100875, ChinaSchool of Information Engineering, Fujian Business University, Fuzhou 350506, ChinaSchool of Artificial Intelligence, Beijing Normal University, Beijing 100875, ChinaSchool of Artificial Intelligence, Beijing Normal University, Beijing 100875, ChinaDepartment of Computer Science, Aberystwyth University, Aberystwyth SY23 3DB, UKEmotions play a significant role in shaping psychological activities, behaviour, and interpersonal communication. Reflecting this importance, automated emotion classification has become a vital research area in artificial intelligence. Electroencephalogram (EEG)-based emotion recognition is particularly promising due to its high temporal resolution and resistance to manipulation. This study introduces an advanced fuzzy inference algorithm for EEG data-driven emotion recognition, effectively addressing the ambiguity of emotional states. By combining adaptive fuzzy rule generation, feature evaluation, and weighted fuzzy rule interpolation, the proposed approach achieves accurate emotion classification while handling incomplete knowledge. Experimental results demonstrate that the integrated fuzzy system outperforms state-of-the-art techniques, offering improved recognition accuracy and robustness under uncertainty.https://www.mdpi.com/2227-7390/13/1/166EEG dataemotion recognitionfuzzy inferencefuzzy rule interpolationfuzzy systems integration |
| spellingShingle | Fangyi Li Fusheng Yu Liang Shen Hexi Li Xiaonan Yang Qiang Shen EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and Interpolation Mathematics EEG data emotion recognition fuzzy inference fuzzy rule interpolation fuzzy systems integration |
| title | EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and Interpolation |
| title_full | EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and Interpolation |
| title_fullStr | EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and Interpolation |
| title_full_unstemmed | EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and Interpolation |
| title_short | EEG-Based Emotion Recognition with Combined Fuzzy Inference via Integrating Weighted Fuzzy Rule Inference and Interpolation |
| title_sort | eeg based emotion recognition with combined fuzzy inference via integrating weighted fuzzy rule inference and interpolation |
| topic | EEG data emotion recognition fuzzy inference fuzzy rule interpolation fuzzy systems integration |
| url | https://www.mdpi.com/2227-7390/13/1/166 |
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