A Digital Intervention for Capturing Real-Time Health Data for Epilepsy Seizure Forecasting: Protocol for the...

Area of Science:

• Neurology
• Medical Technology
• Artificial Intelligence

Background:

• Epilepsy is a chronic neurological disorder characterized by unpredictable seizures, impacting quality of life.
• Seizure prediction is a research priority to mitigate risks associated with epilepsy.
• The ATMOSPHERE project aims to develop personalized seizure forecasting using mobile technology and machine learning.

Purpose of the Study:

• Conduct a feasibility study to test and refine clinical trial methods.
• Evaluate and improve data collection technology for usability and performance.
• Collect longitudinal data to enhance seizure forecasting accuracy.

Main Methods:

• Single-arm, mixed-methods feasibility study with 60 adult participants with epilepsy.
• Testing a prototype and minimum viable product of data collection technology over 6 months.
• Collecting patient-reported and clinical-reported outcomes, alongside qualitative interviews.

Main Results:

• Recruitment is planned for Q1 2026, with data collection concluding in Q2 2027.
• Data analysis and results publication are scheduled for Q3 and Q4 2027, respectively.
• Study outcomes will inform iterative development cycles for the seizure forecasting intervention.

Conclusions:

• The project aims to enhance clinical outcomes for epilepsy patients via seizure forecasting.
• This feasibility study is crucial for optimizing trial methodology and refining the forecasting intervention.
• Successful implementation will lead to a future full-scale clinical trial.