Eyeblink Detection Algorithm Based on Joint Optimization of VME and Morphological Feature Extraction-Reference-Cited by-同舟云学术

Eyeblink Detection Algorithm Based on Joint Optimization of VME and Morphological Feature Extraction

Published:2023-09-15 Issue:18 Volume:23 Page:21374-21384
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Jiang Yining¹^ORCID,Wu Duanpo²^ORCID,Cao Jiuwen³^ORCID,Jiang Lurong⁴^ORCID,Zhang Shuchang¹,Wang Danping⁵

Affiliation:

1. School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China

2. School of Communication Engineering and the Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou, China

3. Machine Learning and I-health International Cooperation Base of Zhejiang Province and the Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou, China

4. School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China

5. Machine Learning and I-health International Cooperation Base of Zhejiang Province, Hangzhou Dianzi University, Hangzhou, China

Funder

National Key Research and Development Program

Joint Fund of Zhejiang Provincial Natural Science Foundation of China

Fundamental Research Funds for the Provincial Universities of Zhejiang

NSFC–Zhejiang Integration Joint Fund

Open Research Projects of Zhejiang Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10251409/10224814.pdf?arnumber=10224814

Reference43 articles.

1. Automated Classification and Removal of EEG Artifacts With SVM and Wavelet-ICA

2. Variational Mode Extraction: A New Efficient Method to Derive Respiratory Signals from ECG

3. ICA With CWT and k-means for Eye-Blink Artifact Removal From Fewer Channel EEG

4. Exploring the Intrinsic Features of EEG Signals via Empirical Mode Decomposition for Depression Recognition

5. An improved algorithm for efficient ocular artifact suppression from frontal EEG electrodes using VMD