MMFNet: A multi-branch multi-scale framework with adaptive sparse self-attention and cross-modal fusion for sleep stage assessment

Yuan Li; Ningning Wang

doi:10.1371/journal.pone.0353930

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Open Access

Peer-reviewed

Research Article

MMFNet: A multi-branch multi-scale framework with adaptive sparse self-attention and cross-modal fusion for sleep stage assessment

Yuan Li,

Roles Conceptualization, Data curation, Investigation, Methodology, Validation, Visualization, Writing – original draft

Affiliation School of Physics and Electronic-Electrical Engineering, ABA Teachers College, Aba Tibetan and Qiang Autonomous Prefecture, Sichuan, China
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Ningning Wang

Roles Investigation, Supervision, Writing – review & editing

* E-mail: aba_ly@abtu.edu.cn

Affiliation School of Physics and Electronic-Electrical Engineering, ABA Teachers College, Aba Tibetan and Qiang Autonomous Prefecture, Sichuan, China

https://orcid.org/0009-0009-1475-1319

⨯

MMFNet: A multi-branch multi-scale framework with adaptive sparse self-attention and cross-modal fusion for sleep stage assessment

Yuan Li,
Ningning Wang

Published: July 17, 2026
https://doi.org/10.1371/journal.pone.0353930

About the Authors

Yuan Li

Roles Conceptualization, Data curation, Investigation, Methodology, Validation, Visualization, Writing – original draft

Affiliation School of Physics and Electronic-Electrical Engineering, ABA Teachers College, Aba Tibetan and Qiang Autonomous Prefecture, Sichuan, China

Ningning Wang

Roles Investigation, Supervision, Writing – review & editing

* E-mail: aba_ly@abtu.edu.cn

Affiliation School of Physics and Electronic-Electrical Engineering, ABA Teachers College, Aba Tibetan and Qiang Autonomous Prefecture, Sichuan, China

https://orcid.org/0009-0009-1475-1319

Competing Interests

The authors have declared that no competing interests exist.

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Sleep
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Electroencephalography
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Convolution
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Physiological adaptation
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Signal processing
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Machine learning
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Wavelet transforms
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