Squeeze-excite fusion based multimodal neural network for sleep stage classification with flexible EEG/ECG signal acquisition circuit

Squeeze-excite fusion based multimodal neural network for sleep stage classification with flexible EEG/ECG signal acquisition circuit

This paper presents a multimodal fusion strategy for sleep stage classification using polysomnography (PSG) with elec troencephalogram (EEG) and Electrocardiogram (ECG) data. The Squeeze-Excite (SE) Fusion mechanism is implemented to enhance the collaborative impact of EEG and ECG signals on neural...

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Bibliographic Details
Main Authors: Tao, Shuailin, Hu, Jinhai, Goh, Wang Ling, Gao, Yuan
Other Authors: Interdisciplinary Graduate School (IGS)
Format: Conference Paper
Language:English
Published: 2024
Subjects:
Computer and Information Science
Sleep stage classification
Channel attention
Multimodal neural network
Flexible circuit and system
Online Access:https://hdl.handle.net/10356/175631
https://ieeexplore.ieee.org/document/10557984

Internet

https://hdl.handle.net/10356/175631
https://ieeexplore.ieee.org/document/10557984

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