Exploring CEEMDAN and LMD Domains Entropy Features for Decoding EEG-Based Emotion Patterns-Reference-Cited by-同舟云学术

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Exploring CEEMDAN and LMD Domains Entropy Features for Decoding EEG-Based Emotion Patterns

Published:2024 Issue: Volume:12 Page:103606-103625
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Pusarla Nalini¹^ORCID,Singh Anurag¹^ORCID,Tripathi Shrivishal¹^ORCID,Vujji Avinash²^ORCID,Bilas Pachori Ram³^ORCID

Affiliation:

1. Department of Electronics and Communication Engineering, International Institute of Information Technology, Naya Raipur, Naya Raipur, Chhattisgarh, India

2. Department of Electrical and Electronics Engineering, Vignan’s Institute of Engineering for Women, Visakhapatnam, Andhra Pradesh, India

3. Department of Electrical Engineering, Indian Institute of Technology Indore, Indore, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10613917.pdf?arnumber=10613917

Reference64 articles.

1. Estimation of task workload from EEG data: New and current tools and perspectives

2. EEG-based vigilance estimation using extreme learning machines

3. Multimodal Emotion Recognition in Response to Videos

4. Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications

5. Learning deep physiological models of affect

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