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Open Access

Pseudo channel: time embedding for motor imagery decoding

Zhengqing MIAO1,2( )Meirong ZHAO1
State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
Research Group Neuroinformatics, Faculty of Computer Science, University of Vienna, Vienna 1090, Austria
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Abstract

Motor imagery (MI) based electroencephalogram(EEG) represents a frontier in enabling direct neural control of external devices and advancing neural rehabilitation. This study introduces a novel time embedding technique, termed traveling-wave based time embedding, utilized as a pseudo channel to enhance the decoding accuracy of MI-EEG signals across various neural network architectures. Unlike traditional neural network methods that fail to account for the temporal dynamics in MI-EEG in individual difference, our approach captures time-related changes for different participants based on a priori knowledge. Through extensive experimentation with multiple participants, we demonstrate that this method not only improves classification accuracy but also exhibits greater adaptability to individual differences compared to position encoding used in Transformer architecture. Significantly, our results reveal that traveling-wave based time embedding crucially enhances decoding accuracy, particularly for participants typically considered “EEG-illiteracy”. As a novel direction in EEG research, the traveling-wave based time embedding not only offers fresh insights for neural network decoding strategies but also expands new avenues for research into attention mechanisms in neuroscience and a deeper understanding of EEG signals.

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Journal of Measurement Science and Instrumentation
Pages 308-317
Cite this article:
MIAO Z, ZHAO M. Pseudo channel: time embedding for motor imagery decoding. Journal of Measurement Science and Instrumentation, 2024, 15(3): 308-317. https://doi.org/10.62756/jmsi.1674-8042.2024032

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Received: 01 August 2024
Revised: 23 August 2024
Accepted: 09 September 2024
Published: 30 September 2024
© The Author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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