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Related Experiment Video

Updated: Dec 29, 2025

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
06:37

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

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Stroke identification using a portable EEG device - A pilot study.

Matan Gottlibe1, Oren Rosen2, Boaz Weller3

  • 1Bruce and Ruth Rappaport Faculty of Medicine, Technion, Haifa, Israel.

Neurophysiologie Clinique = Clinical Neurophysiology
|February 5, 2020
PubMed
Summary
This summary is machine-generated.

A short electroencephalogram (EEG) recording using a portable device can differentiate stroke patients from healthy individuals. This method offers a faster alternative to traditional EEG tests for stroke detection.

Keywords:
EEGIdentificationPortableRsBSIStroke

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Area of Science:

  • Neurology
  • Biomedical Engineering

Background:

  • Electroencephalogram (EEG) changes occur rapidly after stroke.
  • Traditional EEG assessments are time-consuming and require specialized personnel.
  • Portable EEG devices offer a potential solution for rapid stroke detection.

Purpose of the Study:

  • To evaluate the efficacy of a short, portable EEG recording in distinguishing stroke patients from healthy controls.
  • To assess the feasibility of using a portable EEG device for acute stroke diagnosis.

Main Methods:

  • Collected EEG data from patients with acute ischemic stroke and healthy volunteers.
  • Utilized a portable brain wave sensor device for EEG recordings.
  • Quantified hemispheric spectral power symmetry using the Revised Brain Symmetry Index (rsBSI).

Main Results:

  • The study included 33 ischemic stroke patients (mean age 72) and 25 healthy controls.
  • A significant difference in rsBSI scores was found between stroke patients (M=0.363, SD=0.25) and non-stroke individuals (M=0.1686, SD=0.10).
  • The findings indicate a clear distinction in EEG patterns between the two groups.

Conclusions:

  • A brief EEG recording with a portable device can statistically differentiate stroke patients from healthy controls.
  • This approach shows promise for quicker and more accessible stroke diagnosis.
  • Portable EEG technology may enhance early stroke detection and management.