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- W2980067186 abstract "Emotions potentially have a significant impact on human actions and recognizing affective states is an effective way of implementing Brain-Computer Interface (BCI) systems which process brain signals to allow direct communication and interaction with the environment. In this paper, a real-time emotion recognition model was developed on the basis of physiological signals. A sensor fusion method is developed to detect human emotion by using data acquired from ElectroEncephaloGraphy (EEG) and ElectroDermal Activity (EDA) sensors. The proposed physiology-based emotion recognition system using a neural network was implemented and tested on human subjects, and a classification accuracy of 94% on three different emotions was achieved." @default.
- W2980067186 created "2019-10-18" @default.
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- W2980067186 date "2019-07-01" @default.
- W2980067186 modified "2023-10-12" @default.
- W2980067186 title "Emotional State Estimation using Sensor Fusion of EEG and EDA" @default.
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- W2980067186 doi "https://doi.org/10.1109/embc.2019.8856895" @default.
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