Now showing items 1-3 of 3
Emotion recognition based on time-frequency distribution of EEG signals using multivariate synchrosqueezing transform
(Academic Press Inc Elsevier Science, 2018)
This paper investigates the feasibility of using time-frequency (TF) representation of EEG signals for emotional state recognition. A recent and advanced TF analyzing method, multivariate synchrosqueezing transform (MSST) ...
Emotion recognition from EEG signals by using multivariate empirical mode decomposition
This paper explores the advanced properties of empirical mode decomposition (EMD) and its multivariate extension (MEMD) for emotion recognition. Since emotion recognition using EEG is a challenging study due to nonstationary ...
Emotion recognition using time-frequency ridges of EEG signals based on multivariate synchrosqueezing transform
(De Gruyter Open Ltd, 2021)
The feasibility of using time-frequency (TF) ridges estimation is investigated on multi-channel electroencephalogram (EEG) signals for emotional recognition. Without decreasing accuracy rate of the valence/arousal recognition, ...