Literature DB >> 29096220

Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy - A comparison with scalp EEG monitoring.

I C Zibrandtsen1, P Kidmose2, C B Christensen2, T W Kjaer3.   

Abstract

OBJECTIVE: Ear-EEG is recording of electroencephalography from a small device in the ear. This is the first study to compare ictal and interictal abnormalities recorded with ear-EEG and simultaneous scalp-EEG in an epilepsy monitoring unit.
METHODS: We recorded and compared simultaneous ear-EEG and scalp-EEG from 15 patients with suspected temporal lobe epilepsy. EEGs were compared visually by independent neurophysiologists. Correlation and time-frequency analysis was used to quantify the similarity between ear and scalp electrodes. Spike-averages were used to assess similarity of interictal spikes.
RESULTS: There were no differences in sensitivity or specificity for seizure detection. Mean correlation coefficient between ear-EEG and nearest scalp electrode was above 0.6 with a statistically significant decreasing trend with increasing distance away from the ear. Ictal morphology and frequency dynamics can be observed from visual inspection and time-frequency analysis. Spike averages derived from ear-EEG electrodes yield a recognizable spike appearance.
CONCLUSIONS: Our results suggest that ear-EEG can reliably detect electroencephalographic patterns associated with focal temporal lobe seizures. Interictal spike morphology from sufficiently large temporal spike sources can be sampled using ear-EEG. SIGNIFICANCE: Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis.
Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Ear-EEG; Long-term monitoring; Mobile EEG; Temporal lobe epilepsy; Ultra-long term monitoring; Wearable EEG

Mesh:

Year:  2017        PMID: 29096220     DOI: 10.1016/j.clinph.2017.09.115

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  14 in total

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4.  Effects of Different Re-referencing Methods on Spontaneously Generated Ear-EEG.

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6.  Classification with a Deferral Option and Low-Trust Filtering for Automated Seizure Detection.

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7.  The Individual Ictal Fingerprint: Combining Movement Measures With Ultra Long-Term Subcutaneous EEG in People With Epilepsy.

Authors:  Troels W Kjaer; Line S Remvig; Asbjoern W Helge; Jonas Duun-Henriksen
Journal:  Front Neurol       Date:  2021-12-23       Impact factor: 4.003

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Authors:  Sigge Weisdorf; Ivan C Zibrandtsen; Troels W Kjaer
Journal:  Case Rep Neurol Med       Date:  2020-01-28

9.  The Sensitivity of Ear-EEG: Evaluating the Source-Sensor Relationship Using Forward Modeling.

Authors:  Arnd Meiser; Francois Tadel; Stefan Debener; Martin G Bleichner
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10.  Performance of ECG-based seizure detection algorithms strongly depends on training and test conditions.

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