Epilepsy
Conditions
Keywords
Epilepsy, Intracranial Electroencephalogram, Seizures, In Ear Device to Detect Seizures, Temporal Lobe, Brain Waves
Brief summary
Determine the safety and feasibility of an in-ear device to measure seizures or suspected seizures compared to the standard scalp-based electroencephalogram (EEG). The study team anticipates enrolling five healthy participants through meeting announcements and a research email list serv in the Neurology Dept. Based on the appropriate positive initial test of healthy individuals, test the in-ear device on 10 participants with seizures or suspected seizures scheduled for a clinical scalp EEG test.
Detailed description
SeizEAR aims to develop an in-ear device for the detection, diagnosis, and management of seizures/epilepsy. In the United States, an estimated 1 in 26 people will develop epilepsy within a lifetime, with 60% of all seizures originating in the temporal region of the brain. Electroencephalogram (EEG) is currently the gold standard for seizure detection, measuring electrical activity of the brain via numerous electrodes placed on the scalp. The demand for EEG has been steadily increasing given its higher accessibility and ability to result in substantial changes to patient management. In particular, pre-surgical evaluation of seizure was studied in the ambulatory setting, with good post-resection outcomes in selected patients with unilateral temporal lobe epilepsy. The EEG technology requires substantial technician training, can lead to patient discomfort, and still incurs high patient costs (roughly 500-3,000$ per order). Furthermore, current EEG interpretation can be complicated by high rates of false detection and poor sensitivity, as signals may be impeded by scalp conditions, the use of hair products, and other concomitant medical devices. SeizEAR will offer a technician-free, easy to use, comfortable, and cost-effective alternative to seizure monitoring. Intra-ear monitoring has been shown to permit real-time detection of seizure activity and allow for prolonged monitoring of abnormal (inter-ictal) discharges. Intra-ear monitoring is particularly suitable for temporal lobe epilepsy, given the proximity of the ear canal to the temporal lobe of the brain. Prior studies have demonstrated that intra-ear monitoring of temporal brain activity can reliably detect temporal lobe seizures with the added benefit of limiting ocular artifact, a common confounder of more traditional scalp EEG. Collaborating with the industry partner, Starkey Hearing Technologies, the researchers aim to prototype SeizEAR with two electrodes targeting the temporal lobe, wired to a signal processor/box. The objective will be to demonstrate the safety and efficacy of a first-generation SeizEAR device to monitor brain waves in healthy controls and participants with seizures or suspected temporal lobe seizures scheduled for a clinical EEG. Long term, the goal will be to validate the clinical efficacy of SeizEAR in detecting seizures
Interventions
DEVICESeizEAR
The in-ear electrode is a two-electrode device that fits snugly into the ear canal of the user. The device electrodes consist of a Ag/AgCl layer over a substrate. In one iteration, the substrate is a silicone rubber. In another iteration, the substrate is copper. The copper iteration consists of a Ag/AgCl ink that is manually applied to the copper, whereas the other iteration is purchased in a finished state with the Ag/Agel already adhered to the silicone. The electrodes are attached to a foam earpiece during the molding process. The foam earbud is made in-house and can be designed to be more firm or less firm.
Sponsors
Icahn School of Medicine at Mount Sinai
Study design
Allocation
NON_RANDOMIZED
Intervention model
SEQUENTIAL
Primary purpose
DEVICE_FEASIBILITY
Masking
NONE
Intervention model description
The study will enroll the healthy participants first to determine any issues with the device pertaining to safety or issues in comparison to the Gold Standard of EEG for testing for seizures. Once the healthy participants cohort completed (5), the study will begin enrolling participants with seizures or suspected seizures who are scheduled for a clinical EEG (10).
Eligibility
Sex/Gender
ALL
Age
18 Years to 70 Years
Healthy volunteers
Yes
Inclusion criteria
Healthy Participants Inclusion Criteria: * Age: \> 18 and \<70 * No History of Seizures or seizure-like activity based on self-report * Normal parameters for vitals, afebrile, blood pressure. * Able to read and write English * Capable of providing informed consent
Exclusion criteria
* History of seizures or seizure-like activity based on self-assessment * Any major health conditions based upon self-report * Concurrent participation in another investigational protocol. * A history of skin sensitivity, or rash on the head, neck or ears. * A history of silver allergy. * Treatment for an ear infection in the previous four-week period * Medications that would be contraindicated to participate in the study that would interfere with the EEG Testing Phase 3 Inclusion/
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity | at week 16 | The sensitivity of ear-EEG will be measured by sensitivity the percentage of ear-EEG predictions that overlap with conventional EEG annotations for at least 1 second per 24 hours accordingly. The ear-EEG annotations will be considered as predictions and the conventional EEG annotations as the truth. Any prediction was deemed true if they overlap at least 1 second with the truth. All seizure annotations were either true positive (TP), false positive (FP), or false negative (FN). |
| F1 score | at week 16 | The Device F1 Score is a metric used to evaluate the performance of the ear-EEG device in detecting seizures. It is the harmonic mean of precision and recall, providing a balance between these two metrics. Precision is the proportion of true positive (TP) predictions out of all positive predictions (TP + FP), while recall (or sensitivity) is the proportion of true positive (TP) predictions out of all actual seizure events. The F1 Score ranges from 0 to 1, with higher scores indicating better performance in accurately detecting seizures. The performance of ear-EEG will be measured by the device F1 score per 24 hours accordingly. |
| Positive predictive value (PPV) | at week 16 | The Device Positive Predictive Value (PPV) is calculated by dividing the number of true positives (TP) by the total number of positive test results (TP + FP), where FP represents false positives. PPV measures the accuracy of the ear-EEG device in predicting seizures, indicating the likelihood that a positive prediction made by the device is a true seizure event. The PPV ranges from 0 to 1, with higher values indicating better accuracy in predicting seizures. The performance of ear-EEG will be measured by the positive predictive value (PPV) per 24 hours accordingly. |
| False detection rate | at week 16 | The Device False Detection Rate is a metric used to evaluate the performance of the ear-EEG device in terms of false positives. It is calculated by dividing the number of false positives (FP) by the total number of test results (TP + FP + FN), where TP represents true positives and FN represents false negatives. The false detection rate is typically expressed as the number of false positive predictions per 24 hours. Lower values indicate better performance, with fewer false alarms generated by the device.. The performance of ear-EEG will be measured by false detection rate per 24 hours accordingly. |
| Comfort Rating Scale | at week 16 | The Comfort Rating Scale is a 6-item questionnaire that asks participants about their comfort with the device. Responses are on a 5-point Likert scale ranging from 0 (not comfortable at all) to 5 (completely comfortable). The items assessed include tightness, weight, security, softness, overall comfort, and overall fit of the device in the ear. Total scores range from 0 to 30, with higher scores indicating greater comfort. |
Countries
United States
Contacts
CONTACTMary Catherine George, PhD
CONTACTToni Kavanagh, NP
PRINCIPAL_INVESTIGATORHo Wing (Andy) Chan, MD
Icahn School of Medicine at Mount Sinai
Outcome results
None listed