EEG Reconstruction With a Dual-Scale CNN-LSTM Model for Deep Artifact Removal-Reference-Cited by-同舟云学术

EEG Reconstruction With a Dual-Scale CNN-LSTM Model for Deep Artifact Removal

Published:2023-03 Issue:3 Volume:27 Page:1283-1294
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Gao Tengfei¹,Chen Dan¹^ORCID,Tang Yunbo²,Ming Zhekai¹,Li Xiaoli³^ORCID

Affiliation:

1. National Engineering Research Center for Multimedia Software, School of Computer Science and Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China

2. College of Computer and Data Science, Fuzhou University, Fuzhou, China

3. National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China

Funder

Scientific and Technological Innovation 2030

National Natural Science Foundation of China

Science & Technology Major Project of Hubei Province

Next-Generation AI Technologies

National Defence Basic Scientific Research Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10063192/09973303.pdf?arnumber=9973303

Reference30 articles.

1. Artifact removal in EEG using Morphological Component Analysis

2. Subject sensitive EEG discrimination with fast reconstructable CNN driven by reinforcement learning: A case study of ASD evaluation

3. Review of challenges associated with the EEG artifact removal methods

4. Dual-CNN based multi-modal sleep scoring with temporal correlation driven fine-tuning

5. A semi-simulated EEG/EOG dataset for the comparison of EOG artifact rejection techniques

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