Signal Quality Evaluation of a Wireless Wearable EEG Sensor
Abstract number :
3.149
Submission category :
2. Translational Research / 2B. Devices, Technologies, Stem Cells
Year :
2025
Submission ID :
109
Source :
www.aesnet.org
Presentation date :
12/8/2025 12:00:00 AM
Published date :
Authors :
Presenting Author: Vamshi Muvvala, MS – Epitel, Inc.
Avi Kazen, MS – Epitel, Inc.
Zoë Tosi, PhD – Epitel, Inc.
Tyler Newton, PhD – Epitel, Inc.
Michael Elwood, MS – Epitel, Inc.
Mark lehmkuhle, PhD – Epitel Inc.
Tobias Loddenkemper, MD – Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA
Elijah Simon, BS – Boston Children's Hospital
Edeline Jean Baptiste, BS – Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA
Stephanie Dailey, BA – Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA
Mark Spitz, MD – University of Colorado Anschutz Medical Center
Laura Strom, MD – University of Colorado
Mackenzi Moore, MPH – University of Colorado
Daniel Friedman, MD – Department of Neurology, New York University Grossman School of Medicine, NYU Langone Health
Jay Jeschke, MA – New York University - Langone Health
Mitchell Frankel, PhD – Epitel, Inc.
Rationale: Neurological monitoring in individuals experiencing seizures requires recording brain state activity via electroencephalography (EEG). Due to the infrequent nature of seizures in many patients, capturing even a single event often necessitates extended-duration monitoring spanning weeks to months. Additionally, numerous prior and ongoing studies regarding the chronicity of seizure activity have found them often manifesting on the order of many weeks or more. Traditional wired EEG systems used for ambulatory monitoring are not viable for extended-duration monitoring due to their cumbersome nature and the requirement of trained personnel to operate. Minimally invasive sub-scalp EEG has demonstrated robust long-term recording capabilities, but is currently limited in its recording location and requires surgical placement. A scalp-based, wireless EEG system designed for flexible use across various environments and timeframes may better support extended-duration neuromonitoring. Epitel has developed and commercialized a reduced-channel EEG system that uses disposable, easy-to-apply, single-channel sensors. This study compares the EEG signal quality of these sensors to conventional wired EEG systems.
Methods: Artifacts common to EEG were recorded in four healthy volunteers. These participants wore a full 10-20 conventional wired EEG system (wired-EEG) alongside REMI sensors. Artifacts were evaluated both qualitatively through visual analysis and quantitatively using spectral correlation. Separately, 55 electrographic seizures were extracted from data of 17 participants, which was collected as part of ongoing grant-funded research. These seizure participants similarly wore wired-EEG as part of their standard-of-care monitoring, alongside REMI sensors. Seizure events were determined from standard-of-care EEG review. Typical absence, tonic-clonic, and focal events were extracted from the records for time-domain and frequency comparative analysis.
Results: The common EEG artifacts of chewing, eye blinks, and eye flutter showed strong alignment between REMI EEG and wired-EEG in both visual and quantitative comparison, with spectral Pearson correlations ranging from 0.83 to 0.95. Similarly, visual inspection of electrographic seizures showed strong alignment. Analysis of typical absence seizures indicated no significant difference in relative 2–4 Hz band power with a mean spectral correlation of 0.91. Likewise, the mean spectral correlation for focal and tonic-clonic events was 0.86 and 0.94, respectively.
Conclusions: This preliminary analysis of the REMI sensor demonstrates high visual similarity and spectral correlation to conventional wired EEG when reviewing common EEG artifacts and electrographically-visible seizures. Additional studies, some of which are ongoing, will evaluate utility and signal quality of the REMI sensor and system for extended-duration EEG monitoring. Easy to use and non-invasive, the REMI system may provide a convenient, on-demand solution for extended-duration neural monitoring, addressing constraints associated with short-term recordings.
Funding: NIH 1U44 NS121562
Translational Research