Using Autoencoders to Denoise Cross-Session Non-Stationarity in EEG-Based Motor-Imagery Brain-Computer Interfaces

A major problem in brain-computer interfaces (BCIs) relates to the non-stationarity of brain signals. Consequently, the performance of a classification algorithm trained for an individual subject on a certain day deteriorates during the following days. The traditional approach is to recalibrate the...

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Veröffentlicht in:	2022 IEEE 16th International Scientific Conference on Informatics (Informatics) S. 24 - 29
Hauptverfasser:	Almagor, Ophir, Avin, Ofer, Rosipal, Roman, Shriki, Oren
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 23.11.2022
Schlagworte:	autoencoders brain-computer interface Brain-computer interfaces Classification algorithms Convolutional neural networks Decoding deep learning electroencephalogram Electroencephalography Limiting motor-imagery non-stationarity Recording
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