A time segment adaptive optimization method based on separability criterion and correlation analysis for motor imagery BCIs-Reference-Cited by-同舟云学术

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A time segment adaptive optimization method based on separability criterion and correlation analysis for motor imagery BCIs

Published:2024-01-09 Issue: Volume: Page:1-14
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Zhu Lei¹,Xu Mengxuan¹,Zhu Jieping¹,Huang Aiai¹,Zhang Jianhai²³

Affiliation:

1. School of Automation, Hangzhou Dianzi University, Hangzhou, China

2. School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China

3. Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou, China

Funder

the Key Research and Development Project of Zhejiang Province

Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2023.2301421

Reference31 articles.

1. Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: a review

2. Mutual information-based selection of optimal spatial–temporal patterns for single-trial EEG-based BCIs

3. The BCI competition III: validating alternative approaches to actual BCI problems

4. Combination of Brain-Computer Interface Training and Goal-Directed Physical Therapy in Chronic Stroke: A Case Report

5. BCI competition 2008–Graz data set A;Brunner C;Institute for Knowledge Discovery (Laboratory of Brain-Computer Interfaces), Graz University of Technology,2008

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