Abstracts

Rationale: 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. The investigational Medtronic Summit RC+S 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 such as adaptive neuromodulation or responsive pharmacotherapy. However, these capabilities are not fully accessible without significant software development using the Medtronic Summit libraries and API in custom software. Methods: We describe the architecture and Quality Management System (QMS) of the Mayo Epilepsy Personal Assistant Device (EPAD), a software application running on a Microsoft Surface tablet computer and Windows 10 Pro Operating System. The EPAD has bi-directional connectivity to the implanted investigational Medtronic Summit RC+S device and wearable devices streaming physiological time series signals. The application uses the Medtronic Summit libraries to communicate with the RC+S device and implements the intracranial EEG and physiological monitoring, processing, and control functions of the overall system. Results: The user interface and core logic were developed in C#, and calls compiled python programs to deploy on-tablet seizure detection and forecasting algorithms. Data packets containing EEG and accelerometry from the implanted device are decoded, assembled, and are losslessly compressed using Range Encoded Differences (RED) before being stored in a cloud-synchronized repository in Multiscale Electrophysiology Format (MEF v.3.0). Annotation files in SQL and CSV formats containing device and algorithm parameters, and video files from the tablet’s embedded camera acquired following self-annotated or detected seizures are synchronized with the EEG and accelerometry data and stored in the synchronized repository. Dense behavioral inputs from the patient are acquired through interaction with EPAD and data synchronization between devices, tablet and cloud repository occurs over Wi-Fi or cellular data networks. Stimulation parameters are configured on the EPAD tablet, and a sequence of 24 parameter sets over two different possible electrode combinations can be performed in a hospital environment or under ambulatory conditions, allowing EEG responses to be quantified and used for adaptive stimulation parameter changes.  Conclusions: A QMS system was developed for the EPAD system including Risk Analysis and Verification and Validation testing. An Investigational Device Exemption was granted by the US FDA in 2018 to study modulated responsive and predictive stimulation using the Mayo EPAD and Medtronic Summit RC+S in ten patients with non-resectable dominant or bilateral mesial temporal lobe epilepsy confirmed by intracranial monitoring or evidence of mesial temporal sclerosis on MRI. Funding: This study was funded by the National Institutes of Health (UH2-NS095495). Medtronic Inc. internally supported the development and production of devices and API libraries and supplied these components at no charge.