Channel Division Based Multiple Classifiers Fusion for Emotion Recognition Using EEG signals Article Swipe

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YOU? · · 2017 · Open Access · · DOI: https://doi.org/10.1051/itmconf/20171107006

With the rapid development of computer technology, pervasive computing and wearable devices, EEG-based emotion recognition has gradually attracted much attention in affecting computing (AC) domain. In this paper, we propose an approach of emotion recognition using EEG signals based on the weighted fusion of multiple base classifiers. These base classifiers based on SVM are constructed using a channel division mechanism according to the neuropsychological theory that different brain areas are differ in processing intensity of emotional information. The outputs of channel base classifiers are integrated by a weighted fusion strategy which is based on the confidence estimation on each emotional label by each base classifier. The evaluation on the DEAP dataset shows that our proposed multiple classifiers fusion method outperforms individual channel base classifiers and the feature fusion method for EEG-based emotion recognition.

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Computer Science

Artificial Intelligence

Electroencephalography

Support Vector Machine

Jazz Fusion

Division (Mathematics)

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Computer science Pattern recognition (psychology) Artificial intelligence Classifier (UML) Electroencephalography Support vector machine Emotion recognition Random subspace method Speech recognition Fusion Channel (broadcasting) Emotion classification Division (mathematics) Machine learning Psychology Mathematics Computer network Linguistics Arithmetic Philosophy Psychiatry

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Type: article
Language: en
Landing Page: https://doi.org/10.1051/itmconf/20171107006
PDF: https://www.itm-conferences.org/articles/itmconf/pdf/2017/03/itmconf_ist2017_07006.pdf
OA Status: diamond
Cited By: 18
References: 23
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DOI: https://doi.org/10.1051/itmconf/20171107006

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Title: Channel Division Based Multiple Classifiers Fusion for Emotion Recognition Using EEG signals

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Language: en

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Publication year: 2017

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Publication date: 2017-01-01

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Authors: Xian Li, Jianzhuo Yan, Jianhui Chen

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Landing page: https://doi.org/10.1051/itmconf/20171107006

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Concepts: Computer science, Pattern recognition (psychology), Artificial intelligence, Classifier (UML), Electroencephalography, Support vector machine, Emotion recognition, Random subspace method, Speech recognition, Fusion, Channel (broadcasting), Emotion classification, Division (mathematics), Machine learning, Psychology, Mathematics, Computer network, Linguistics, Arithmetic, Philosophy, Psychiatry

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Cited by: 18

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