A Novel Classification Strategy to Distinguish Five Levels of Pain Using the EEG Signal Features-Reference-Cited by-同舟云学术

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A Novel Classification Strategy to Distinguish Five Levels of Pain Using the EEG Signal Features

Published:2021-01-01 Issue:1 Volume:12 Page:131-140
ISSN:1949-3045
Container-title:IEEE Transactions on Affective Computing
language:
Short-container-title:IEEE Trans. Affective Comput.

Author:

Nezam T.¹^ORCID,Boostani R.²^ORCID,Abootalebi V.¹^ORCID,Rastegar K.³

Affiliation:

1. Electrical and Computer Engineering Department, Yazd University, Yazd, Iran

2. CSE & IT Department, ECE Faculty, Biomedical Group, Shiraz University, Shiraz, Iran

3. Department of Neurophysiology, Shiraz University of Medical Sciences, Shiraz, Iran

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Software

Link

http://xplorestaging.ieee.org/ielx7/5165369/9364368/08399510.pdf?arnumber=8399510

Cited by 28 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cleanformer: A Confident Learning Based ERP Label Denoising Framework for Public Attitude Assessment to Recycled Water;Water Resources Management;2024-09-07

2. Unraveling the physiological and psychosocial signatures of pain by machine learning;Med;2024-08

3. A Spatiotemporal Deep Learning Framework for Scalp EEG-Based Automated Pain Assessment in Children;IEEE Transactions on Biomedical Engineering;2024-06

4. Comparing multimodal physiological responses to social and physical pain in healthy participants;Frontiers in Public Health;2024-04-03

5. Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals;Cognitive Neurodynamics;2024-02-28

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