EEG Signal Feature Extraction Using Principal Component Analysis and Power Spectral Entropy for Multiclass Emotion Prediction

Author:

Babeetha S.,Sridhar S. S.

Publisher

Springer Nature Singapore

Reference20 articles.

1. George FP, Shaikat IM, Hossain PSF, Parvez MZ, Uddin J (2019) Recognition of emotional states using EEG signals based on time-frequency analysis and SVM classifier. Int J Electr Comput Eng 9:1012–1020

2. Alhagry S, Aly A, Reda A (2017) Emotion recognition based on EEG using LSTM recurrent neural network. Int J Adv Comput Sci Appl 8:8–11

3. Yin Y, Zheng X, Hu B, Zhang Y, Cui X (2020) EEG emotion recognition using fusion model of graph convolutional neural networks and LSTM. Appl Soft Comput 100:106954

4. Cimtay Y, Ekmekcioglu E (2020) Investigating the use of pretrained convolutional neural network on cross-subject and cross-dataset EEG emotion recognition. Sensors 20:2034

5. Wei C, Chen L-L, Song Z-Z, Lou X-G, Li D-D (2020) EEG-based emotion recognition using simple recurrent units network and ensemble learning. Biomed Sig Process Control 58:101756

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