Spiking neural networks for EEG signal analysis using wavelet transform

These findings indicate that SpikeWavformer can address the key limitations of existing BCI methods and holds promise for practical deployment in portable, resource-constrained scenarios.

Authors

Ying Liu (ORCID: https://orcid.org/0000-0001-9319-5940)
Yuan Li (ORCID: https://orcid.org/0000-0002-4958-6132)
Wei Jian

Publication Details

Journal: Frontiers in Neuroscience
Published: 2025-10-16
DOI: https://doi.org/10.3389/fnins.2025.1652274
Citations: 1
Primary Topic: EEG and Brain-Computer Interfaces
Type: article
Field-Weighted Citation Impact: 1.43

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article

Spiking neural networks for EEG signal analysis using wavelet transform

Ying Liu, Yuan Li, Wei Jian

Oct 16, 2025

1 citations

Frontiers in Neuroscience

EEG and Brain-Computer Interfaces

1.43

article

Spiking neural networks for EEG signal analysis using wavelet transform

Ying Liu, Yuan Li, Wei Jian

October 16, 2025article en

1 citations

Abstract

These findings indicate that SpikeWavformer can address the key limitations of existing BCI methods and holds promise for practical deployment in portable, resource-constrained scenarios.

Frontiers in NeuroscienceVol. 19

Openalex Percentile: Top 15%

EEG and Brain-Computer Interfaces

1.43

DOI Open Access PDF OpenAlex

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