Design of BCI motor imagery classification using WPT-CSP and CNN-Reference-Cited by-同舟云学术

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Design of BCI motor imagery classification using WPT-CSP and CNN

Published:2022 Issue: Volume: Page:
ISSN:0094-243X
Container-title:THE 6TH BIOMEDICAL ENGINEERING’S RECENT PROGRESS IN BIOMATERIALS, DRUGS DEVELOPMENT, AND MEDICAL DEVICES: Proceedings of the 6th International Symposium of Biomedical Engineering (ISBE) 2021
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Author:

Pradana Dio Alif,Basari

Publisher

AIP Publishing

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0097976

Reference30 articles.

1. Deep Fusion Feature Learning Network for MI-EEG Classification

2. Y. Liu et al., “Motor Imagery Based Teleoperation of a Dual-arm Robot Performing Manipulation Tasks,” IEEE Trans. Cogn. Dev. Syst., vol. 8920, no. c, 2018.

3. Recursive Bayesian Coding for BCIs

4. EEG Control of a Bionic Hand With Imagination Based on Chaotic Approximation of Largest Lyapunov Exponent: A Single Trial BCI Application Study

5. Three-Dimensional Brain–Computer Interface Control Through Simultaneous Overt Spatial Attentional and Motor Imagery Tasks

Cited by 3 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. Deep learning in motor imagery EEG signal decoding: A Systematic Review;Neurocomputing;2024-09

2. A motor imagery EEG signal optimized processing algorithm;Alexandria Engineering Journal;2024-08

3. Deep Learning in Motor Imagery Eeg Signal Decoding: A Systematic Review;2023

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