Abstracts

Rationale:
Electrical stimulation of the brain (ESB) is an emerging therapy for diseases of the brain and mind. Although ESB is FDA approved for patients with  drug resistant epilepsy (DRE), current neuromodulatory approaches  are largely palliative and do not target psychiatric or cognitive comorbidities. We have developed a digital health system that should accelerate treatment optimization for DRE. The system enables management of patients by streaming physiological data from implanted and wearable devices coupled with direct queries to the patient triggered by system analytics and scheduled queries for measures of sleep quality, cognition, and mood. Real-time analytics of physiological data streams provide accurate seizure diaries, dense behavioral tracking and patient interactions, and automated patient specific adaptive stimulation.
Method:
Initial pre-clinical work has been performed in canines with epilepsy implanted with the investigational Medtronic Summit RC+S (TM) system (sense and stimulation electrodes in the hippocampus & anterior nucleus of the thalamus bilaterally). The system has wireless connectivity with Epilepsy Patient Assistant Device, a mobile device, which enables continuous acquisition of intracranial EEG data, wearable device data, and patient annotations. The data are synchronized on a cloud-based digital health system providing AI-powered large-scale data management and analytics for physicians to review recordings, create gold standard labels, and automatically retrain algorithms.
Results:
Thirteen canines have undergone monitoring using the system (average per subject 760 days), including two pet dogs with naturally occurring epilepsy living with their owners. Two human subjects with DRE have been enrolled with one subject participating in over 240 days of monitoring. We have successfully implemented real-time seizure detection, forecasting, and tracking of limbic system evoked potentials to classify brain-states. We have collected over 6 months of sleep quality and mood self-reports. The Digital Epilepsy Dashboard provided a seamless interactive interface between the patient, engineers, and physicians for tracking behavioral data, brain state, and tuning adaptive ESB to optimize therapy. The system is currently deployed in 2 pet dogs with naturally occurring epilepsy living with their owners and one human subject with DRE ( >240 days).
Conclusion:
The Digital Health System provides a personalized approach to adaptively optimize and track epilepsy treatments in a population of patients, and in the future should prove useful for a wide range of neurological and psychiatric diseases.
Funding:
:NIH Brain Initiative: UH2/3 NS095495 NIH R01NS092882