… Emotion recognition based on EEG signals has a broad … drivers' emotional conditions by
analyzing their EEG signals in … progress of emotion recognition based on EEG signals. The …

… emotion detection using EEG signals. To begin with we introduce the theories of emotion
classification, the types of EEG … One study [81] found that the most reliable electrode positions …

… in emotion recognition such as emotion paradigms, EEG and its … have used EEG signals
differently in emotion recognition [58, 59… to the use of only EEG signals in emotions recognition. …

… of DL techniques in emotion recognition from EEG signals and … challenges in emotion
recognition using EEG signals, … employed in the study of emotions are emotion-based and …

… advances in the EEG-based emotion recognition research, we … the scientific basis of
EEG-based emotion recognition in the … It is challenging to represent the emotional EEG signals …

… Our analysis of these studies shows the scientific nature of the emotion classification study's
research through EEG signals. This paper introduces experimental and standard datasets …

… This work reviews emotion recognition advances using EEG signals and BCI to (1) identify
trends in algorithm usage and technology, (2) detect potential errors that must be overcome …

… an automated model for identifying emotions based on EEG signals. The proposed model
… EEG data can be extracted using different systems or devices. In this study, a DEAP dataset …

… In this study, we use 2-second sliding and 1-second overlapping time windows to cut the 60
… of emotion recognition based on EEG signals. The features extraction from EEG signals in …

… RSP, BVP, and TMP signals. This study was applied to the DEAP dataset, which is of interest
to us in this study is the first method based on the EEG signals, they used three consecutive …