A hybrid Spiking Neural Network–Transformer architecture for motor imagery and sleep apnea detection

This work highlights the potential of neuromorphic-inspired architectures for robust and efficient biomedical signal processing across diverse physiological tasks.

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Publication Details

Journal
Frontiers in Neuroscience
Published
2025-12-12
DOI
https://doi.org/10.3389/fnins.2025.1716204
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00
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article

A hybrid Spiking Neural Network–Transformer architecture for motor imagery and sleep apnea detection

Frontiers in Neuroscience
EEG and Brain-Computer Interfaces
article

A hybrid Spiking Neural Network–Transformer architecture for motor imagery and sleep apnea detection

article en

Abstract

This work highlights the potential of neuromorphic-inspired architectures for robust and efficient biomedical signal processing across diverse physiological tasks.

Frontiers in NeuroscienceVol. 19
University of West Bohemia in Pilsen (CZ)
Affordable and clean energy
Openalex Percentile: Top 36%
EEG and Brain-Computer Interfaces
DOIOpen Access PDFOpenAlex
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