Long-Term EEG Monitoring for Epilepsy
(REMI Trial)
Recruiting in Palo Alto (17 mi)
+1 other location
Age: 18+
Sex: Any
Travel: May be covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: Epitel, Inc.
Disqualifiers: Allergies, Enrolled in other trials, others
No Placebo Group
Trial Summary
What is the purpose of this trial?The goal of this clinical trial is to test Epitel's™ Remote EEG Monitoring System's (REMI™) ability to record electroencephalography (EEG) of seizure events in an ambulatory setting for extended periods (14 - 28 days) in patients presenting with questionable seizure characterization. The main questions it aims to answer are: • Can more seizure events be recorded in fourteen (14) days than can be recorded in three (3) days? • Do treating clinicians find clinical value in extended fourteen (14) - twenty-eight (28) days of EEG? Participants will wear a portable EEG device (REMI) for fourteen (14) to twenty-eight (28) days in their home/community setting.
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications. It seems likely that you can continue your medications, as the focus is on monitoring seizures with a portable EEG device.
What data supports the effectiveness of the treatment Remote EEG Monitoring System, REMI, for epilepsy?
The REMI system, which uses Epilog sensors, was shown to have a high accuracy in detecting seizures remotely, with epileptologists achieving 90% sensitivity and specificity in identifying patients experiencing seizures. Additionally, the automated seizure detection algorithm demonstrated 100% sensitivity in identifying seizure activity, indicating REMI's potential as an effective tool for remote epilepsy monitoring.
12345Is long-term EEG monitoring for epilepsy safe for humans?
The studies on remote EEG monitoring systems, like Epitel's REMI, show that they are generally safe for human use. These systems have been tested for accuracy and reliability in detecting seizures, and no significant safety concerns have been reported in the available research.
12467How does the Remote EEG Monitoring System differ from other epilepsy treatments?
The Remote EEG Monitoring System (REMI) is unique because it allows for long-term, remote monitoring of brain activity using wearable sensors, which can be administered by non-specialized medical personnel. This system provides comprehensive spatial EEG recordings and includes an automated seizure detection algorithm, making it distinct from traditional in-clinic EEG monitoring.
12348Eligibility Criteria
This trial is for adults aged 18-70 with a history of seizures, who can consent to the study and follow procedures. They must be willing to wear an EEG device almost all day (20+ hours) for up to 30 days and have at least one seizure every two weeks. It's not suitable for those in other trials, allergic to certain medical materials, without stable housing or power supply.Inclusion Criteria
I have a history of seizures.
I (or my caregiver) can follow all the study's instructions.
I am between 18 and 70 years old.
I experience at least one seizure every two weeks.
Participant Groups
The REMI™ system by Epitel is being tested to see if it can capture more seizure events over a longer period (14-28 days) compared to traditional methods. The study will evaluate whether extended EEG monitoring provides valuable information for clinicians treating epilepsy.
Remote EEG Monitoring System is already approved in United States for the following indications:
🇺🇸 Approved in United States as REMI for:
- Detection of electrographic seizures
- Ambulatory EEG monitoring
Find A Clinic Near You
Research locations nearbySelect from list below to view details:
University of South FloridaTampa, FL
Medical University of South CarolinaCharleston, SC
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Who is running the clinical trial?
Epitel, Inc.Lead Sponsor
References
Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring. [2023]Ambulatory EEGs began emerging in the healthcare industry over the years, setting a new norm for long-term monitoring services. The present devices in the market are neither meant for remote monitoring due to their technical complexity nor for meeting clinical setting needs in epilepsy patient monitoring. In this paper, we propose an ambulatory EEG device, OptiEEG, that has low setup complexity, for the remote EEG monitoring of epilepsy patients. OptiEEG's signal quality was compared with a gold standard clinical device, Natus. The experiment between OptiEEG and Natus included three different tests: eye open/close (EOC); hyperventilation (HV); and photic stimulation (PS). Statistical and wavelet analysis of retrieved data were presented when evaluating the performance of OptiEEG. The SNR and PSNR of OptiEEG were slightly lower than Natus, but within an acceptable bound. The standard deviations of MSE for both devices were almost in a similar range for the three tests. The frequency band energy analysis is consistent between the two devices. A rhythmic slowdown of theta and delta was observed in HV, whereas photic driving was observed during PS in both devices. The results validated the performance of OptiEEG as an acceptable EEG device for remote monitoring away from clinical environments.
Wearable Reduced-Channel EEG System for Remote Seizure Monitoring. [2022]Epitel has developed Epilog, a miniature, wireless, wearable electroencephalography (EEG) sensor. Four Epilog sensors are combined as part of Epitel's Remote EEG Monitoring platform (REMI) to create 10 channels of EEG for remote patient monitoring. REMI is designed to provide comprehensive spatial EEG recordings that can be administered by non-specialized medical personnel in any medical center. The purpose of this study was to determine how accurate epileptologists are at remotely reviewing Epilog sensor EEG in the 10-channel "REMI montage," with and without seizure detection support software. Three board certified epileptologists reviewed the REMI montage from 20 subjects who wore four Epilog sensors for up to 5 days alongside traditional video-EEG in the EMU, 10 of whom experienced a total of 24 focal-onset electrographic seizures and 10 of whom experienced no seizures or epileptiform activity. Epileptologists randomly reviewed the same datasets with and without clinical decision support annotations from an automated seizure detection algorithm tuned to be highly sensitive. Blinded consensus review of unannotated Epilog EEG in the REMI montage detected people who were experiencing electrographic seizure activity with 90% sensitivity and 90% specificity. Consensus detection of individual focal onset seizures resulted in a mean sensitivity of 61%, precision of 80%, and false detection rate (FDR) of 0.002 false positives per hour (FP/h) of data. With algorithm seizure detection annotations, the consensus review mean sensitivity improved to 68% with a slight increase in FDR (0.005 FP/h). As seizure detection software, the automated algorithm detected people who were experiencing electrographic seizure activity with 100% sensitivity and 70% specificity, and detected individual focal onset seizures with a mean sensitivity of 90% and mean false alarm rate of 0.087 FP/h. This is the first study showing epileptologists' ability to blindly review EEG from four Epilog sensors in the REMI montage, and the results demonstrate the clinical potential to accurately identify patients experiencing electrographic seizures. Additionally, the automated algorithm shows promise as clinical decision support software to detect discrete electrographic seizures in individual records as accurately as FDA-cleared predicates.
Twenty-four hour ambulatory EEG monitoring: development and applications. [2019]Since 1975 four-channel ambulatory monitoring has been available as a technique for prolonged EEG recording in an unrestricted environment. This increases EEG sampling time so that attacks can be recorded and enables the differentiation of epileptic and non-epileptic attacks. In recent years an eight-channel system has become available which provides greater scalp coverage and allows better localization of attacks and EEG abnormalities. Four-channel recording has been widely used to assess the efficacy of anticonvulsant medication in patients with absence seizures. It has also been used to investigate the effect of the environment on discharges, as well as any circadian variations in discharges. Ambulatory monitoring provides a useful alternative to sleep recording in the laboratory, both for the detection of abnormalities during sleep and for experimental sleep studies. Automated analysis techniques have so far been confined to the analysis of spike and wave activity and to the scoring of sleep stages.
Epilepsy Personal Assistant Device-A Mobile Platform for Brain State, Dense Behavioral and Physiology Tracking and Controlling Adaptive Stimulation. [2022]Epilepsy is one of the most common neurological disorders, and it affects almost 1% of the population worldwide. Many people living with epilepsy continue to have seizures despite anti-epileptic medication therapy, surgical treatments, and neuromodulation therapy. The unpredictability of seizures is one of the most disabling aspects of epilepsy. Furthermore, epilepsy is associated with sleep, cognitive, and psychiatric comorbidities, which significantly impact the quality of life. Seizure predictions could potentially be used to adjust neuromodulation therapy to prevent the onset of a seizure and empower patients to avoid sensitive activities during high-risk periods. Long-term objective data is needed to provide a clearer view of brain electrical activity and an objective measure of the efficacy of therapeutic measures for optimal epilepsy care. While neuromodulation devices offer the potential for acquiring long-term data, available devices provide very little information regarding brain activity and therapy effectiveness. Also, seizure diaries kept by patients or caregivers are subjective and have been shown to be unreliable, in particular for patients with memory-impairing seizures. This paper describes the design, architecture, and development of the Mayo Epilepsy Personal Assistant Device (EPAD). The EPAD has bi-directional connectivity to the implanted investigational Medtronic Summit RC+STM device to implement intracranial EEG and physiological monitoring, processing, and control of the overall system and wearable devices streaming physiological time-series signals. In order to mitigate risk and comply with regulatory requirements, we developed a Quality Management System (QMS) to define the development process of the EPAD system, including Risk Analysis, Verification, Validation, and protocol mitigations. Extensive verification and validation testing were performed on thirteen canines and benchtop systems. The system is now under a first-in-human trial as part of the US FDA Investigational Device Exemption given in 2018 to study modulated responsive and predictive stimulation using the Mayo EPAD system and investigational Medtronic Summit RC+STM in ten patients with non-resectable dominant or bilateral mesial temporal lobe epilepsy. The EPAD system coupled with an implanted device capable of EEG telemetry represents a next-generation solution to optimizing neuromodulation therapy.
Review on the current long-term, limited lead electroencephalograms. [2023]In the last century, 10-20 lead EEG recordings became the gold standard of surface EEG recordings, and the 10-20 system provided comparability between international studies. With the emergence of advanced EEG sensors, that may be able to record and process signals in much more compact units, this additional sensor technology now opens up opportunities to revisit current ambulatory EEG recording practices and specific patient populations, and even electrodes that are embedded into the head surface. Here, we aim to provide an overview of current limited sensor long-term EEG systems. We performed a literature review using Pubmed as a database and included the relevant articles. The review identified several systems for recording long-term ambulatory EEGs. In general, EEGs recorded with these modalities can be acquired in ambulatory and home settings, achieve good sensitivity with low false detection rates, are used for automatic seizure detection as well as seizure forecasting, and are well tolerated by patients, but each of them has advantages and disadvantages. Subcutaneous, subgaleal, and subscalp electrodes are minimally invasive and provide stable signals that can record ultra--long-term EEG and are in general less noisy than scalp EEG, but they have limited spatial coverage and require anesthesia, a surgical procedure and a trained surgeon to be placed. Behind and in the ear electrodes are discrete, unobtrusive with a good sensitivity mainly for temporal seizures but might miss extratemporal seizures, recordings could be obscured by muscle artifacts and bilateral ictal patterns might be difficult to register. Finally, recording systems using electrodes in a headband can be easily and quickly placed by the patient or caregiver, but have less spatial coverage and are more prone to movement because electrodes are not attached. Overall, limited EEG recording systems offer a promising opportunity to potentially record targeted EEG with focused indications for prolonged periods, but further validation work is needed.
Ultra-long-term subcutaneous home monitoring of epilepsy-490 days of EEG from nine patients. [2021]To explore the feasibility of home monitoring of epilepsy patients with a novel subcutaneous electroencephalography (EEG) device, including clinical implications, safety, and compliance via the first real-life test.
Clinical utility of a video/audio-based epilepsy monitoring system Nelli. [2022]The aim of this study was to evaluate the clinical utility of a semi-automated hybrid video/audio-based epilepsy monitoring system (Nelli®) in a home setting.
Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic. [2021]It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by infrequent seizures based on patient or caregiver reports and limited duration clinical testing. The poor reliability of self-reported seizure diaries for many people with epilepsy is well-established, but these records remain necessary in clinical care and therapeutic studies. A number of wearable devices have emerged, which may be capable of detecting seizures, recording seizure data, and alerting caregivers. Developments in non-invasive wearable sensors to measure accelerometry, photoplethysmography (PPG), electrodermal activity (EDA), electromyography (EMG), and other signals outside of the traditional clinical environment may be able to identify seizure-related changes. Non-invasive scalp electroencephalography (EEG) and minimally invasive subscalp EEG may allow direct measurement of seizure activity. However, significant network and computational infrastructure is needed for continuous, secure transmission of data. The large volume of data acquired by these devices necessitates computer-assisted review and detection to reduce the burden on human reviewers. Furthermore, user acceptability of such devices must be a paramount consideration to ensure adherence with long-term device use. Such devices can identify tonic-clonic seizures, but identification of other seizure semiologies with non-EEG wearables is an ongoing challenge. Identification of electrographic seizures with subscalp EEG systems has recently been demonstrated over long (>6 month) durations, and this shows promise for accurate, objective seizure records. While the ability to detect and forecast seizures from ambulatory intracranial EEG is established, invasive devices may not be acceptable for many individuals with epilepsy. Recent studies show promising results for probabilistic forecasts of seizure risk from long-term wearable devices and electronic diaries of self-reported seizures. There may also be predictive value in individuals' symptoms, mood, and cognitive performance. However, seizure forecasting requires perpetual use of a device for monitoring, increasing the importance of the system's acceptability to users. Furthermore, long-term studies with concurrent EEG confirmation are lacking currently. This review describes the current evidence and challenges in the use of minimally and non-invasive devices for long-term epilepsy monitoring, the essential components in remote monitoring systems, and explores the feasibility to detect and forecast impending seizures via long-term use of these systems.