Empirical Mode Decomposition for Deep Learning-Based Epileptic Seizure Detection in Few-Shot Scenario-Reference-Cited by-同舟云学术

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Empirical Mode Decomposition for Deep Learning-Based Epileptic Seizure Detection in Few-Shot Scenario

Published:2024 Issue: Volume:12 Page:86583-86595
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Pan Yayan¹^ORCID,Dong Fangying²^ORCID,Yao Wei³,Meng Xiaoqin⁴,Xu Yongan¹^ORCID

Affiliation:

1. Department of Emergency Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, China

2. The Fourth Affiliated Hospital Zhejiang University School of Medicine, Yiwu, China

3. Department of Thoracic Surgery, The Second Hospital of Jiaxing, Jiaxing, China

4. Department of Cardiology Medicine, The Second Hospital of Jiaxing, Jiaxing, China

Funder

National Natural Science Foundation of China

Key Research and Development Program of Zhejiang Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10559822.pdf?arnumber=10559822

Reference41 articles.

1. Epilepsy and Cognitive Impairments in Alzheimer Disease

2. On the nature of seizure dynamics

3. EEG in the diagnosis, classification, and management of patients with epilepsy

4. A Review on BCI Emotions Classification for EEG Signals Using Deep Learning

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Channel swapping of EEG signals for deep learning‐based seizure detection;Electronics Letters;2024-07

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