A Novel Mobile Phone App for Optimizing Dynamic Discrete Data Collection in Pediatric Epilepsy Studies

Mobile technologies, including applications (apps) and wearable devices, are playing an increasingly important role in health monitoring. In particular, apps are becoming a critical component of m-health, which promises to transform personalized care management, optimize clinical outcomes, and improve patient-provider communication. They may also play a central role in research, to facilitate rapid and inexpensive collection of repeated data, such as momentary clinical, physiological, and/or behavioral assessments and optimize their sampling. This is particularly important for measuring systems/processes with characteristic temporal patterns, e.g., circadian rhythms, which need to be adequately sampled in order to be accurately estimated from discrete measurements. Temporal sampling of these patterns may also be critical for elucidating their modulation by pathological events. This paper presents a novel app, developed with the overarching goal to optimize repeated salivary hormone collection in pediatric patients with epilepsy through improved patient-investigator communication and enhanced alerts. The ultimate goal of the app is to maximize regularity of the data collection (up to 8 samples/day for ~4-5 days of hospitalization) while minimizing intrusion on patients during clinical monitoring. In addition, the app facilitates flexible collection of data on stress and seizure symptoms at the time of saliva sampling, which can then be correlated with hormone levels and physiological changes indicating impending seizures.