Epilepsy; Seizure, Sleep
Conditions
Keywords
electroencephalography, polysomnography
Brief summary
The goal of this study is to characterize the ability of the NextSense ear-EEG device to detect pathologic electrographic signatures of epilepsy and physiologic signatures of sleep in subjects undergoing simultaneous inpatient continuous EEG monitoring, polysomnography, or ambulatory EEG monitoring at home.
Detailed description
For nearly half a century, conventional electroencephalography (EEG) has been the standard of care for monitoring cerebral activity, particularly in the clinical domains of epilepsy and sleep disorders. Standard EEG involves highly time, labor, and cost intensive processes and typically requires subjects to be monitored by specially trained staff in the inpatient setting. Existing ambulatory EEG options are limited to about 3 days in duration because of decline in electrode fidelity beyond that timeframe. There is a need for unobtrusive, easy to use, longitudinal monitoring solutions that can extend to the ambulatory setting. This study will assess whether novel NextSense EEG Earbuds are able to 1) detect seizures of varying types/localizations as well as interictal epileptiform activity (IEA) waveforms compared to simultaneously recorded conventional scalp EEG, or in some cases, intracranial EEG; and 2) detect characteristic electrographic signatures of AASM defined sleep stages compared to simultaneously recorded polysomnography.
Interventions
Each NextSense EEGBud device includes custom-fit earbuds with biometric sensors to detect EEG, motion (via tri-axial accelerometers), and heart rate. A ring laser scanner is used to capture the unique geometry of each participant's ear and external auditory canal. Digital models of the individual ear scans are generated and used to create custom fit, 3D-printed earbuds. This design process allows for consistent contact with the inner surface of the ear canal, providing high quality signal capture of brain activity, cardiac activity, and eye movements.
Sponsors
Emory University
NextSense, Inc.
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* All patients 18 years of age and older admitted to the Epilepsy Monitoring Unit at Emory University Hospital for long-term inpatient scalp or intracranial cEEG monitoring for diagnostic or pre-surgical evaluation, or patients 18 years and older admitted to the Emory Sleep Center at the Brain Health Center for polysomnography. * To enhance the likelihood of having a sufficient number of enrolled subjects with an adequate number of seizures, investigators may identify patients more likely to have epileptic rather than non-epileptic seizures based on the medical history. * All patients who are undergoing ambulatory EEG monitoring at home.
Exclusion criteria
* Inability to safely tolerate earbuds (e.g. antecedent skin breakdown, recent injury to ear). * Subjects who cannot have all 16 non-midline scalp EEG electrodes placed, since these EEG channels are required to accurately assess the performance of the seizure detection function.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Ease of use and tolerability validation of EEG earbuds for patients undergoing cEEG monitoring or polysomnography. | up to 2 weeks | Individual tolerance success will be the presence of an interpretable EEG record for at 18 hours a day, for at least three consecutive days. Overall tolerance will be a ≥ 75% ongoing participation rate, i.e. ≤ 25% study drop-out rate. Patients will be questioned about the reasons they felt the EEGBuds needed to be removed, in order to improve future tolerance. |
| Performance validation of EEG earbuds for patients undergoing cEEG monitoring or polysomnography | up to 2 weeks | Performance validation is measured as sensitivity (true positive) rate as defined as the total number of true detections divided by the total number of seizures; and specificity (false detection rate \[FDR\]) as defined as 24 x number of false detections divided by the total number of EEG hours, for each test subject. Detections will be classified as true or false based on majority rule by expert reviewers (classified by ≥ 2/3 of reviewers). Criteria for Success: 1. ≥ 90% of EEG segments deemed acceptable quality by expert reviewers 2. Overall seizure detection sensitivity of at least 90% and a mean FDR of no more than 5 per 24 hours 3. Overall spike detection sensitivity of at least 90% and a mean FDR of no more than 3 per hour 4. Overall focal slowing detection sensitivity of at least 75% and a mean FDR of no more than 3 per 24 hours (focal slowing is traditionally more difficult to ascertain so criteria will be slightly less stringent) |
Countries
United States
Outcome results
None listed