Abstracts

Rationale: Electrical brain stimulation is an effective therapy for people with drug-resistant epilepsy. New implantable devices and therapies have emerged in recent years, but accurate long-term tracking of seizures, behavior, and comorbidities remains challenging. Furthermore, treatment optimization is still difficult due to inaccurate seizure diaries. We developed a digital health system enabling management of multiple patients with drug-resistant epilepsy streaming physiological data from implanted and wearable devices. Real-time analytics provide seizure diaries, dense behavioral tracking, and automated patient-specific adaptive stimulation. Methods: Thirteen canines were implanted with the Medtronic Plc. investigational Summit RC+S system (bilateral hippocampus & anterior nucleus of the thalamus or cortical electrodes), which interfaces with a mobile computational device, Epilepsy Patient Assist Device (EPAD), to acquire iEEG data from the implant. The data is synchronized on a cloud-based digital health system providing large-scale data management and analytics where physicians can remotely review real-time ambulatory data and create gold standard diaries to retrain algorithms. Results: Thirteen canines underwent monitoring using the system (average ~ 400 days) with an average of ~90% of iEEG data wirelessly telemetered and received. Using this system, we previously demonstrated real-time seizure detection system (average accuracy ~ 97%, sensitivity 100%), real-time seizure forecasting (~90% sensitivity, 8% time in warning) and tracking evoked responses to classify wake and sleep for brain-state adaptive brain stimulation. We created a new Digital Dashboard that provides a seamless interface between patient and physician for behavioral data, patient annotations, automated seizure diaries, tracking brain state and tuning adaptive stimulation. The system has been deployed to optimize electrical stimulation in pet dogs with epilepsy. Conclusions: The Digital Health System provides a personalized epilepsy approach to adaptively optimize epilepsy treatments in a population of patients. Funding: This research was supported by National Institutes of Health (UH2&3-NS95495, R01-NS092882), LQ1605 from the National Program of Sustainability II (MEYS CR, Czech Republic), and institutional resources from Mayo Clinic, Rochester MN USA, Medtronic, Minneapolis, MN, USA, and Czech Technical University in Prague, Czech Republic.