Abstract

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.

Highlights

  • Drug-resistant epilepsy is one of the most common neurological disorders, affecting almost 1% of the population worldwide [1, 2]

  • The integration of implanted neuromodulation devices, external wearable sensors, and dense behavioral sampling with cloud data storage and computational capabilities represents a potentially transformative advancement toward fully integrated digital medicine

  • To investigate circadian and multidian cycles our group characterized these in 16 dogs with naturally occurring focal epilepsy that were continuously monitored with the investigational Medtronic Summit RC+STM combined with the EPAD system [10]

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Summary

INTRODUCTION

Drug-resistant epilepsy is one of the most common neurological disorders, affecting almost 1% of the population worldwide [1, 2]. Neuromodulation therapy for epilepsy has grown in prevalence following FDA approvals for responsive neurostimulation (RNS) [5] in 2013 and deep brain stimulation (DBS) [6] in 2018 While these approaches effectively reduce seizures, long-term seizure freedom is rare with these methods. An experimental device (NeuroVista SAS) was preclinically trialed provided clear proof of concept and validation of the value of long-term objective EEG data and seizure forecasts [13,14,15]. The investigational Medtronic Summit RC+STM system was developed to telemeter EEG, provide on-device seizure detections, and modulate stimulation therapy based on either on-board EEG analytics or analytics on an associated mobile computer. The investigational Medtronic Summit RC+STM neuromodulation device offers a unique combination of near-real-time intracranial EEG telemetry, on-device analytics, and modulated stimulation therapy that could enable therapies not previously possible.

DESIGN AND DEVELOPMENT
DISCUSSION
Findings
ETHICS STATEMENT
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