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Brain Oscillatory Activity and Neurological Deficit in Hyper-acute Ischemic Stroke: Correlation of EEG Changes with NIHSS

  • Miloš AjčevićEmail author
  • Giovanni Furlanis
  • Lara Stragapede
  • Mariana Ridolfi
  • Paola Caruso
  • Marcello Naccarato
  • Agostino Accardo
  • Paolo Manganotti
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 76)

Abstract

The accurate identification and prediction of cerebral infarct evolution and clinical outcome are of paramount importance in acute ischemic stroke management. Neuroimaging in acute stroke is mandatory to establish the feasibility of reperfusion therapy, but it is not practical to assess the continuous evolution of brain ischemia. EEG could be an applicable instrument to perform functional monitoring in the hyper-acute phase. EEG activity during ischemic stroke has been widely studied in sub-acute and post-acute phase of ischemic stroke. However, only few studies have focused on the early phase of brain ischemia. The aim of this study conducted at the stroke unit was to investigate stroke-related EEG changes during the earliest phase of ischemic stroke within 4.5 h from symptom onset and to correlate these data with neurological deficit in terms of NIHSS score. We studied 12 patients with ischemic stroke, who underwent EEG recordings within 4.5 h from symptom onset. The EEG signals acquisition was performed bedside without delaying reperfusion treatment, using @64 channels Wi-Fi Be Plus LTM amplifier and 19 channel 10–20 Ag/AgCl electrodes wireless prewired headset. The main finding of this study is a significant positive correlation between stroke-related EEG changes measured by DAR and DTABR parameters and the neurological deficit measured by NIHSS score, during the earliest phase of ischemic stroke. The results of this study highlight the importance of EEG as complementary tool in the assessment of stroke severity and its potential role in acute decision-making and monitoring.

Keywords

EEG Ischemic stroke Hyperacute Neurocoupling Biomedical signal processing 

Notes

Acknowledgements

M. Ajčević is supported by AIRAlzh Onlus - (ANCC-COOP). The authors would like to thank Matteo di Franza for editorial assistance. This study was partially supported by Master in Clinical Engineering, University of Trieste.

Conflict of Interest

The authors have no conflict of interest do declare.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Miloš Ajčević
    • 1
    • 2
    • 3
    Email author
  • Giovanni Furlanis
    • 1
  • Lara Stragapede
    • 1
  • Mariana Ridolfi
    • 1
  • Paola Caruso
    • 1
  • Marcello Naccarato
    • 1
  • Agostino Accardo
    • 2
  • Paolo Manganotti
    • 1
  1. 1.Neurology Unit, University Hospital of Trieste, Department of Medicine Surgery and Health SciencesUniversity of TriesteTriesteItaly
  2. 2.Department of Engineering and ArchitectureUniversity of TriesteTriesteItaly
  3. 3.NEUROFARBA Department, Neuroscience SectionUniversity of FlorenceFlorenceItaly

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