Emotion Recognition Using Narrowband Spatial Features of Electroencephalography-Reference-Cited by-同舟云学术

Emotion Recognition Using Narrowband Spatial Features of Electroencephalography

Published:2023 Issue: Volume:11 Page:44019-44033
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Farhana Iffat¹^ORCID,Shin Jungpil²^ORCID,Mahmood Shabbir³^ORCID,Rabiul Islam Md.⁴,Molla Md. Khademul Islam¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, University of Rajshahi, Rajshahi, Bangladesh

2. School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan

3. Department of Computer Science and Engineering, Bangamata Sheikh Fojilatunnesa Mujib Science and Technology University, Jamalpur, Bangladesh

4. Department of Computer Science and Engineering, Varendra University, Rajshahi, Bangladesh

Funder

Information and Communication Technology Division (ICT Division), Ministry of Posts, Telecommunications and Information Technology, Bangladesh, through the ICT Fellowship

Competitive Research Fund of The University of Aizu, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10107909.pdf?arnumber=10107909

Reference48 articles.

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

2. GCB-Net: Graph Convolutional Broad Network and Its Application in Emotion Recognition

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

4. EEG-based emotion recognition using 4D convolutional recurrent neural network

5. Wavelet-based emotion recognition system using EEG signal

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