Epilepsy Personal Assistant Device-A Mobile Platform for Brain State, Dense Behavioral and Physiology Tracking and...

Area of Science:

• Neurology
• Biomedical Engineering
• Medical Device Development

Background:

• Epilepsy affects 1% of the global population, with many patients experiencing persistent seizures despite current treatments.
• Unpredictable seizures, cognitive issues, and psychiatric comorbidities significantly reduce the quality of life for epilepsy patients.
• Existing neuromodulation devices and subjective seizure diaries offer limited objective data on brain activity and treatment efficacy.

Purpose of the Study:

• To describe the design, architecture, and development of the Mayo Epilepsy Personal Assistant Device (EPAD).
• To enable seizure prediction and objective, long-term monitoring of brain electrical activity for optimized epilepsy management.
• To enhance neuromodulation therapy by providing real-time data for responsive and predictive stimulation.

Main Methods:

• Developed the Mayo Epilepsy Personal Assistant Device (EPAD) with bi-directional connectivity to the Medtronic Summit RC+S™ investigational device.
• Implemented intracranial EEG and physiological monitoring, processing, and control for wearable devices streaming physiological data.
• Established a Quality Management System (QMS) for risk mitigation, verification, and validation, including extensive testing in canines and benchtop systems.

Main Results:

• The EPAD system successfully integrated intracranial EEG and physiological monitoring capabilities.
• Verification and validation testing confirmed system functionality and safety in preclinical models.
• The system is currently undergoing a first-in-human trial under FDA Investigational Device Exemption for responsive and predictive stimulation.

Conclusions:

• The EPAD system, combined with an implanted EEG telemetry device, represents a significant advancement in epilepsy neuromodulation therapy.
• This next-generation solution offers the potential for objective, long-term data acquisition to optimize treatment efficacy and patient outcomes.
• Seizure prediction and personalized neuromodulation aim to improve the quality of life for individuals living with epilepsy.