Toward consistency between humans and classifiers: Improved performance of a real-time brain–computer interface using a mutual learning system-Reference-Cited by-同舟云学术

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Toward consistency between humans and classifiers: Improved performance of a real-time brain–computer interface using a mutual learning system

Published:2023-09 Issue: Volume:226 Page:120205
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Lin Chun-Yi^ORCID,Lu Chia-Feng^ORCID,Jao Chi-Wen,Wang Po-Shan,Wu Yu-Te^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference32 articles.

1. Co-adaptive training improves efficacy of a multi-day EEG-based motor imagery BCI training;Abu-Rmileh;Frontiers in Human Neuroscience,2019

2. Signal processing techniques for motor imagery brain computer interface: A review;Aggarwal;Array,2019

3. Deep learning for motor imagery EEG-based classification: A review;Al-Saegh;Biomedical Signal Processing and Control,2021

4. Automatic detection of abnormal EEG signals using wavelet feature extraction and gradient boosting decision tree;Albaqami;Biomedical Signal Processing and Control,2021

5. Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning;Alkoby;Neuroscience,2018

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