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Automated detection of dynamical change in EEG signals based on a new rhythm measure

  • Published:2020-07 Issue: Volume:107 Page:101920
  • ISSN:0933-3657
  • Container-title:Artificial Intelligence in Medicine
  • language:en
  • Short-container-title:Artificial Intelligence in Medicine

Author:

Lu Guoliang,Chen Guangyuan,Shang Wei,Xie Zhaohong

Funder

This study is supported by the Shandong Provincial Natural Science Foundation, China

undamental Research Funds of Shandong University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference43 articles.

1. Method for detection of changes in the EEG induced by the presence of sensory stimuli;Carrubba;J Neurosci Methods,2008

2. Change point detection of EEG signals based on particle swarm optimization;Mohamed Saaid;5th Kuala Lumpur international conference on biomedical engineering 2011,2011

3. Detecting the early drop of attention using EEG signal.;Gunawan,2017

4. Automatic change detection for real-time monitoring of EEG signals;Gao;Front Physiol,2018

5. Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis;Gajic;Front Comput Neurosci,2015

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