This observational study focuses on validating the use of the Eysz mHealth App - a smartphone-based tool for guided Hyperventilation (HV) and data collection - to aid clinicians in identifying absence seizures in people at risk for childhood absence epilepsy (CAE). The Eysz mHealth app will guide users through HV via interactive graphics while capturing audio and video data using smartphone sensors (e.g., camera, microphone) from which eye movements, facial biometrics/ expressions, number and length of exhales will be extracted.
The goal of this observational study is to determine an epileptologist's performance in identifying HV-induced absence seizures using video data collected from a smartphone when compared to the gold standard interpretation of the EEG. The exploratory goal is to develop machine learning based algorithms to identify HV-induced seizures.
