A spatiotemporal attention multitasking sleep staging method based on ECG signal

Yixin Zhao; Yiling Ran; Xiang An; Yunfeng Zheng

doi:10.1117/12.3051768

18 November 2024 A spatiotemporal attention multitasking sleep staging method based on ECG signal

Yixin Zhao, Yiling Ran, Xiang An, Yunfeng Zheng

Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 134031C (2024) https://doi.org/10.1117/12.3051768
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China

Abstract

Sleep staging is a complex process that necessitates precise and robust analysis of polysomnographic signals. In this study, we introduce a novel approach aimed at effectively extracting crucial information from both the time and frequency domains of the signal. Our method is composed of three primary components: a multi-head spatiotemporal attention mechanism, and a module for multi-task learning. The spatiotemporal attention mechanism concurrently concentrates on various spatial locations and frequency ranges of the signal, enhancing the model’s attention allocation efficiency and precision. The multi-task learning-based module effectively leverages the correlation between sleep stages and can perform sleep staging and transition tasks simultaneously, thereby boosting the model’s learning capability and adaptability. The hyperparameter optimization method, which is based on the loss function, strikes a balance between the significance of the primary and secondary tasks to achieve optimal learning outcomes. By conducting a comprehensive analysis of various modules and hyperparameters, we examined the model’s performance and influencing factors, and validated the model’s rationality and robustness. The findings of this study offer significant support and direction for the ongoing advancement of sleep staging tasks.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yixin Zhao, Yiling Ran, Xiang An, and Yunfeng Zheng "A spatiotemporal attention multitasking sleep staging method based on ECG signal", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 134031C (18 November 2024); https://doi.org/10.1117/12.3051768

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KEYWORDS

Electrocardiography

Machine learning

Performance modeling

Deep learning

Polysomnography

Data modeling

Databases

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