Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

Research article (Journal of Neural Engineering, 2018) · cited 194× · AI/ML
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Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

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Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-learning-for-hybrid-eeg-fnirs-braincomputer-interface-application-to-motor-imagery-classification
MLA “Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-learning-for-hybrid-eeg-fnirs-braincomputer-interface-application-to-motor-imagery-classification.
BibTeX @misc{4ortxyz_deep-learning-for-hybrid-eeg-fnirs-braincomputer-interface-application-to-motor-imagery-classification_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification}}, year = {2026}, url = {https://4ort.xyz/entity/deep-learning-for-hybrid-eeg-fnirs-braincomputer-interface-application-to-motor-imagery-classification}, note = {Accessed: 2026-05-24}}
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