Basic and Clinical Neuroscience، جلد ۱۴، شماره ۵، صفحات ۰-۰

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عنوان انگلیسی EEG Emotion Classification Using a Novel Adaptive Ensemble Classifier Considering Personality Traits
چکیده انگلیسی مقاله Electroencephalograph (EEG) signals reveal much of human brain states and this method can widely use in emotion classification. Although, the classification of emotion recognition is not almost ideal mainly due to the following reasons: (i) the features extracted from EEG signals may not solely reflect emotional patterns of a person and is affected by some time-varying factor and noise; and (ii) higher-level cognitive factor such as personality, mood, past experiences, etc.  The dynamic properties of EEG data in relation to time series may affect the variability of feature distribution and interclass discrimination at different time stages. In this paper, we suggest a new adaptive ensemble classification method to alleviate the problems mentioned above. Specifically, we propose a new method for providing emotional stimuli. The Stimuli were sorted incrementally based on their valence- arousal score in three groups (sadness, neutral, and happiness).60 subjects 19–30 years of age (mean 25.01 and SD 3.13) participated in this study. The results show that the performance of emotion classifiers in this study has significantly improved compared to conventional classifiers. The classification accuracy elicited by the proposed method is 87.96 %.
کلیدواژه‌های انگلیسی مقاله Adaptive ensemble learning, EEG emotion classification, Personality traits

نویسندگان مقاله | Mohammad Saleh Khajeh Hosseini
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.


| Mohammad Pourmir Firoozabadi
Department of Medical Physics, Tarbiat Modares, Tehran, Iran.


| Kambiz Badie
University of Tehran & ITRC, Tehran, Iran.


| Parviz Azad Fallah
Department of Psychology, Tarbiat Modares, Tehran, Iran.



نشانی اینترنتی http://bcn.iums.ac.ir/browse.php?a_code=A-10-3830-2&slc_lang=en&sid=1
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زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده Cognitive Neuroscience
نوع مقاله منتشر شده Original
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