Using a standalone ear-EEG device for focal-onset seizure detection.

Ear-EEG Focal epilepsy Long-term EEG Seizure detection Temporal lobe Wearable technologies

Journal

Bioelectronic medicine
ISSN: 2332-8886
Titre abrégé: Bioelectron Med
Pays: England
ID NLM: 101660849

Informations de publication

Date de publication:
07 Feb 2024
Historique:
received: 02 10 2023
accepted: 04 12 2023
medline: 7 2 2024
pubmed: 7 2 2024
entrez: 6 2 2024
Statut: epublish

Résumé

Seizure detection is challenging outside the clinical environment due to the lack of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We developed a novel, discreet, unobstructive in-ear sensing system that enables long-term electroencephalography (EEG) recording. This is the first study we are aware of that systematically compares the seizure detection utility of in-ear EEG with that of simultaneously recorded intracranial EEG. In addition, we present a similar comparison between simultaneously recorded in-ear EEG and scalp EEG. In this foundational research, we conducted a clinical feasibility study and validated the ability of the ear-EEG system to capture focal-onset seizures against 1255 hrs of simultaneous ear-EEG data along with scalp or intracranial EEG in 20 patients with refractory focal epilepsy (11 with scalp EEG, 8 with intracranial EEG, and 1 with both). In a blinded, independent review of the ear-EEG signals, two epileptologists were able to detect 86.4% of the seizures that were subsequently identified using the clinical gold standard EEG modalities, with a false detection rate of 0.1 per day, well below what has been reported for ambulatory monitoring. The few seizures not detected on the ear-EEG signals emanated from deep within the mesial temporal lobe or extra-temporally and remained very focal, without significant propagation. Following multiple sessions of recording for a median continuous wear time of 13 hrs, patients reported a high degree of tolerance for the device, with only minor adverse events reported by the scalp EEG cohort. These preliminary results demonstrate the potential of using ear-EEG to enable routine collection of complementary, prolonged, and remote neurophysiological evidence, which may permit real-time detection of paroxysmal events such as seizures and epileptiform discharges. This study suggests that the ear-EEG device may assist clinicians in making an epilepsy diagnosis, assessing treatment efficacy, and optimizing medication titration.

Sections du résumé

BACKGROUND BACKGROUND
Seizure detection is challenging outside the clinical environment due to the lack of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We developed a novel, discreet, unobstructive in-ear sensing system that enables long-term electroencephalography (EEG) recording. This is the first study we are aware of that systematically compares the seizure detection utility of in-ear EEG with that of simultaneously recorded intracranial EEG. In addition, we present a similar comparison between simultaneously recorded in-ear EEG and scalp EEG.
METHODS METHODS
In this foundational research, we conducted a clinical feasibility study and validated the ability of the ear-EEG system to capture focal-onset seizures against 1255 hrs of simultaneous ear-EEG data along with scalp or intracranial EEG in 20 patients with refractory focal epilepsy (11 with scalp EEG, 8 with intracranial EEG, and 1 with both).
RESULTS RESULTS
In a blinded, independent review of the ear-EEG signals, two epileptologists were able to detect 86.4% of the seizures that were subsequently identified using the clinical gold standard EEG modalities, with a false detection rate of 0.1 per day, well below what has been reported for ambulatory monitoring. The few seizures not detected on the ear-EEG signals emanated from deep within the mesial temporal lobe or extra-temporally and remained very focal, without significant propagation. Following multiple sessions of recording for a median continuous wear time of 13 hrs, patients reported a high degree of tolerance for the device, with only minor adverse events reported by the scalp EEG cohort.
CONCLUSIONS CONCLUSIONS
These preliminary results demonstrate the potential of using ear-EEG to enable routine collection of complementary, prolonged, and remote neurophysiological evidence, which may permit real-time detection of paroxysmal events such as seizures and epileptiform discharges. This study suggests that the ear-EEG device may assist clinicians in making an epilepsy diagnosis, assessing treatment efficacy, and optimizing medication titration.

Identifiants

pubmed: 38321561
doi: 10.1186/s42234-023-00135-0
pii: 10.1186/s42234-023-00135-0
doi:

Types de publication

Journal Article

Langues

eng

Pagination

4

Informations de copyright

© 2024. The Author(s).

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Auteurs

McGregor Joyner (M)

NextSense Inc., Mountain View, CA, USA.

Sheng-Hsiou Hsu (SH)

NextSense Inc., Mountain View, CA, USA.

Stephanie Martin (S)

NextSense Inc., Mountain View, CA, USA.

Jennifer Dwyer (J)

NextSense Inc., Mountain View, CA, USA.

Denise Fay Chen (DF)

Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.

Reza Sameni (R)

Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA.

Samuel H Waters (SH)

Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.

Konstantin Borodin (K)

NextSense Inc., Mountain View, CA, USA.

Gari D Clifford (GD)

Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.

Allan I Levey (AI)

Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.

John Hixson (J)

Department of Neurology, University of California San Francisco, San Francisco, CA, USA.

Daniel Winkel (D)

Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.

Jonathan Berent (J)

NextSense Inc., Mountain View, CA, USA. jb@nextsense.io.

Classifications MeSH