SDREAMER: Self-distilled Mixture-of-Modality-Experts Transformer for Automatic Sleep Staging
Research output: Contribution to conference › Paper › Research › peer-review
Automatic sleep staging based on electroencephalography (EEG) and electromyography (EMG) signals is an important aspect of sleep-related research. Current sleep staging methods suffer from two major drawbacks. First, there are limited information interactions between modalities in the existing methods. Second, current methods do not develop unified models that can handle different sources of input. To address these issues, we propose a novel sleep stage scoring model sDREAMER, which emphasizes cross-modality interaction and per-channel performance. Specifically, we develop a mixture-of-modality-expert (MoME) model with three pathways for EEG, EMG, and mixed signals with partially shared weights. We further propose a self-distillation training scheme for further information interaction across modalities. Our model is trained with multi-channel inputs and can make classifications on either single-channel or multi-channel inputs. Experiments demonstrate that our model outperforms the existing transformer-based sleep scoring methods for multi-channel inference. For single-channel inference, our model also outperforms the transformer-based models trained with single-channel signals.
Original language | English |
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Publication date | 2023 |
Number of pages | 12 |
DOIs | |
Publication status | Published - 2023 |
Event | 2023 IEEE International Conference on Digital Health, ICDH 2023 - Hybrid, Chicago, United States Duration: 2 Jul 2023 → 8 Jul 2023 |
Conference
Conference | 2023 IEEE International Conference on Digital Health, ICDH 2023 |
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Country | United States |
City | Hybrid, Chicago |
Period | 02/07/2023 → 08/07/2023 |
Sponsor | IEEE Computer Society |
Bibliographical note
Funding Information:
ACKNOWLEDGMENTS Research reported in this publication was supported by the National Institutes of Health under Award Number U19NS128613. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2023 IEEE.
- distillation, mixture-of-modality experts, sleep scoring, transformer
Research areas
ID: 373667363