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The increasing instance of negative emotion reduce the performance of emotion recognition

INTRODUCTION: Emotion recognition plays a crucial role in affective computing. Recent studies have demonstrated that the fuzzy boundaries among negative emotions make recognition difficult. However, to the best of our knowledge, no formal study has been conducted thus far to explore the effects of i...

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Detalles Bibliográficos
Autores principales: Wang, Xiaomin, Zhao, Shaokai, Pei, Yu, Luo, Zhiguo, Xie, Liang, Yan, Ye, Yin, Erwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611512/
https://www.ncbi.nlm.nih.gov/pubmed/37900730
http://dx.doi.org/10.3389/fnhum.2023.1180533
Descripción
Sumario:INTRODUCTION: Emotion recognition plays a crucial role in affective computing. Recent studies have demonstrated that the fuzzy boundaries among negative emotions make recognition difficult. However, to the best of our knowledge, no formal study has been conducted thus far to explore the effects of increased negative emotion categories on emotion recognition. METHODS: A dataset of three sessions containing consistent non-negative emotions and increased types of negative emotions was designed and built which consisted the electroencephalogram (EEG) and the electrocardiogram (ECG) recording of 45 participants. RESULTS: The results revealed that as negative emotion categories increased, the recognition rates decreased by more than 9%. Further analysis depicted that the discriminative features gradually reduced with an increase in the negative emotion types, particularly in the θ, α, and β frequency bands. DISCUSSION: This study provided new insight into the balance of emotion-inducing stimuli materials.