Automated non-EEG based seizure detection: Do users have a say?

Area of Science:

• Epilepsy research
• Medical device engineering
• Patient-centered care

Background:

• Epilepsy quality of life is impacted by seizure unpredictability.
• Timely seizure detection can improve patient outcomes.
• Understanding user needs is crucial for developing effective seizure detection systems.

Purpose of the Study:

• To assess the actual need for seizure detection systems.
• To understand user preferences for seizure detection technology.
• To inform the engineering process with user requirements.

Main Methods:

• Surveyed 20 pediatric/young adult patients, 114 caregivers, and 21 medical doctors.
• Analyzed experiences with existing seizure detection systems.
• Compared opinions on usefulness, purpose, and requirements for detection devices.

Main Results:

• 65% of patients/caregivers and 85% of doctors found detection systems useful, especially at night.
• Need for detection increases with seizure frequency and intellectual disability severity.
• Patients/caregivers desire 100% accuracy; doctors accept 90% with varying false alarm tolerance.
• Detection of convulsive seizures and fall detection are priorities for patients/caregivers; doctors prioritize heart rate monitoring for detection and SUDEP prevention.

Conclusions:

• Development of seizure detectors should consider user-driven goals.
• Targeting 90% correct detection and one false alarm per seizure is a key recommendation.
• Incorporating patient and medical professional feedback is vital for successful device implementation.