Automatic Change Detection for Real-Time Monitoring of EEG Signals-Reference-Cited by-同舟云学术

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Automatic Change Detection for Real-Time Monitoring of EEG Signals

Published:2018-04-04 Issue: Volume:9 Page:
ISSN:1664-042X
Container-title:Frontiers in Physiology
language:
Short-container-title:Front. Physiol.

Author:

Gao Zhen,Lu Guoliang,Yan Peng,Lyu Chen,Li Xueyong,Shang Wei,Xie Zhaohong,Zhang Wanming

Funder

National Natural Science Foundation of China

Publisher

Frontiers Media SA

Subject

Physiology (medical),Physiology

Reference37 articles.

1. Brain computer interfacing: applications and challenges;Abdulkader;Egypt. Inform. J.,2015

2. Continuous EEG monitoring enhances multimodal outcome prediction in hypoxic–ischemic brain injury;Amorim;Resuscitation,2016

3. Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients;Andrzejak;Phys. Rev. E,2012

4. Principles of time–frequency feature extraction for change detection in non-stationary signals: applications to newborn EEG abnormality detection;Boashash;Patt. Recogn.,2015

5. A wban-based real-time electroencephalogram monitoring system: design and implementation;Chen;J. Med. Syst.,2010

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5. Machine Learning Algorithms for Epilepsy Detection Based on Published EEG Databases: A Systematic Review;IEEE Access;2023

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