In this study, EEG nonlinear features, power spectrum entropy and correlation dimension, were extracted to differentiate emotions. International Affective ...
Nov 30, 2022 · This paper proposes three non-linear features (Higuchi fractal dimension, sample entropy, and permutation entropy) and eight ensemble learning approaches to ...
This paper proposes three non-linear features (Higuchi fractal dimension, sample entropy, and permutation entropy) and eight ensemble learning approaches to ...
EEG-based human emotion recognition using entropy as a feature extraction measure · Emotion recognition through EEG phase space dynamics and Dempster-Shafer ...
Aug 23, 2023 · The feature extraction technique transforms inputs to new dimensions, which are different (linear, nonlinear, directed, etc.) combinations of ...
... Meanwhile, since EEG is generated by the brain system supposed to be highly complex, the acquired signals indicate nonlinearity, non-stationary and chaotic ...
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May 18, 2024 · This paper provides a comprehensive study of different methods for extracting electroencephalography (EEG) features for emotion recognition ...
Dec 15, 2021 · The relation of EEG signal with emotion is highly nonlinear. It requires a nonlinear process for prediction. Search for a relevant vector is the ...
Our proposed EER model (EEG-based Emotion Recognition Model) could identify 20 types of emotions based on 32 EEG channels, and the average recognition accuracy ...
May 18, 2024 · This paper provides a comprehensive study of different methods for extracting electroencephalography (EEG) features for emotion recognition from four different ...