Automated Video-Based Detection of Nocturnal Motor Seizures in Children
May 13, 2020
Abstract
Key Points
- This team previously demonstrated good performance of their real-time video-based algorithm for detection of nocturnal convulsions in adults
- Researchers validated the algorithm with long-term nightly videos of children with refractory epilepsy at home or in a residential care setting
- The algorithm detected 118 of 125 nocturnal convulsions (median sensitivity per participant = 100%, overall sensitivity = 94%)
- All 135 nocturnal hyperkinetic seizures were detected
- False alarms occurred in six of 22 children (overall false alarm rate = 0.05 per night) and were mostly behavior-related
Seizure detection devices can improve epilepsy care, but wearables are not always tolerated. Previously this team demonstrated good performance of a real-time video-based algorithm for detection of nocturnal convulsive seizures in adults with learning disabilities. The aim of this study is to validate the video algorithm on nocturnal motor seizures in a pediatric population. The researchers retrospectively analyzed the algorithm performance on a database including 1661 full recorded nights of 22 children (age = 3-17 years) with refractory epilepsy at home or in a residential care setting. The algorithm detected 118 of 125 convulsions and identified all 135 hyperkinetic seizures, a type of seizure characterized by intense motor activity involving the extremities and trunk. Most children had no false alarms; although 81 false alarms occurred in six children, most of these (62%) were behavior?related (eg, awake and playing in bed). The researchers state that their noncontact detection algorithm reliably detects nocturnal epileptic events with only a limited number of false alarms and is suitable for real-time use.