Emotion Recognition Based on EEG Brain Rhythm Sequencing Technique-Reference-Cited by-同舟云学术

Emotion Recognition Based on EEG Brain Rhythm Sequencing Technique

Published:2023-03 Issue:1 Volume:15 Page:163-174
ISSN:2379-8920
Container-title:IEEE Transactions on Cognitive and Developmental Systems
language:
Short-container-title:IEEE Trans. Cogn. Dev. Syst.

Author:

Li Jia Wen¹^ORCID,Barma Shovan²^ORCID,Pun Sio Hang³^ORCID,Vai Mang I.¹,Mak Peng Un⁴^ORCID

Affiliation:

1. State Key Laboratory of Analog and Mixed-Signal VLSI, and the Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China

2. Department of Electronics and Communication Engineering, Indian Institute of Information Technology Guwahati, Guwahati, India

3. State Key Laboratory of Analog and Mixed-Signal VLSI, University of Macau, Macau, China

4. Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China

Funder

National Key Research and Development Program of China

Shenzhen-Hong Kong-Macau S&T Program (Category C) of SZSTI

University of Macau

The Science and Technology Development Fund, Macau SAR

SKL-AMSV(FDCT-funded), Grant SKLAMSV-ADDITIONAL FUND

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Software

Link

http://xplorestaging.ieee.org/ielx7/7274989/10061504/09707481.pdf?arnumber=9707481

Reference55 articles.

1. DEAP: A Database for Emotion Analysis ;Using Physiological Signals

2. High-frequency broadband modulation of electroencephalographic spectra

3. Investigating Critical Frequency Bands and Channels for EEG-Based Emotion Recognition with Deep Neural Networks

4. Frontal EEG Asymmetry of Emotion for the Same Auditory Stimulus

5. Employing PCA and t-statistical approach for feature extraction and classification of emotion from multichannel EEG signal

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