2022
DOI: 10.48084/etasr.5073
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Human Emotion Detection with Electroencephalography Signals and Accuracy Analysis Using Feature Fusion Techniques and a Multimodal Approach for Multiclass Classification

Abstract: Biological brain signals may be used to identify emotions in a variety of ways, with accuracy depended on the methods used for signal processing, feature extraction, feature selection, and classification. The major goal of the current work was to use an adaptive channel selection and classification strategy to improve the effectiveness of emotion detection utilizing brain signals. Using different features picked by feature fusion approaches, the accuracy of existing classification models' emotion detection is … Show more

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Cited by 2 publications
(1 citation statement)
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“…It is a subjective experience [9,10] that has the capacity to create mental apprehension of the surroundings, both discriminatively and affectively [11]. Visual, auditory, and memory aspect incorporation complementarily contributes to constituting a multimodal system [9] that impacts the emotional, social and cognitive human apprehension [13][14][15]. Understanding the way human senses work, and more particularly how haptic perception functions has become a growing research topic over the recent years [13].…”
Section: Introductionmentioning
confidence: 99%
“…It is a subjective experience [9,10] that has the capacity to create mental apprehension of the surroundings, both discriminatively and affectively [11]. Visual, auditory, and memory aspect incorporation complementarily contributes to constituting a multimodal system [9] that impacts the emotional, social and cognitive human apprehension [13][14][15]. Understanding the way human senses work, and more particularly how haptic perception functions has become a growing research topic over the recent years [13].…”
Section: Introductionmentioning
confidence: 99%