Patient-Specific Seizure Prediction via Adder Network and Supervised Contrastive Learning

Patient-Specific Seizure Prediction via Adder Network and Supervised Contrastive Learning

Deep learning (DL) methods have been widely used in the field of seizure prediction from electroencephalogram (EEG) in recent years. However, DL methods usually have numerous multiplication operations resulting in high computational complexity. In addtion, most of the current approaches in this fiel...

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Bibliographic Details
Main Authors: Yuchang Zhao, Chang Li, Xiang Liu, Ruobing Qian, Rencheng Song, Xun Chen
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Deep learning
seizure prediction
electroencephalogram (EEG)
adder network
contrastive learning
adaptive learning rate
Online Access:https://ieeexplore.ieee.org/document/9787538/

Internet

https://ieeexplore.ieee.org/document/9787538/

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