The mPower study, Parkinson disease mobile data collected using ResearchKit

TLDR

Current health measures are often insensitive, episodic, and subjective, and are not designed to provide meaningful feedback, while the potential of high‑resolution mobile phone activity data is only beginning to be explored. The study presents data from mPower, a purely app‑based observational study of Parkinson disease, and aims to release this data to foster a collaborative community of analysts advancing mobile health research. The study collected data via surveys and frequent sensor‑based recordings from participants with and without Parkinson disease through an iPhone app. The large enrollment and repeated measurements enable baseline variability estimation of real‑world activity and may allow quantification of Parkinson symptom fluctuations, while the open‑source app code facilitates use in other studies.

Abstract

Abstract Current measures of health and disease are often insensitive, episodic, and subjective. Further, these measures generally are not designed to provide meaningful feedback to individuals. The impact of high-resolution activity data collected from mobile phones is only beginning to be explored. Here we present data from mPower, a clinical observational study about Parkinson disease conducted purely through an iPhone app interface. The study interrogated aspects of this movement disorder through surveys and frequent sensor-based recordings from participants with and without Parkinson disease. Benefitting from large enrollment and repeated measurements on many individuals, these data may help establish baseline variability of real-world activity measurement collected via mobile phones, and ultimately may lead to quantification of the ebbs-and-flows of Parkinson symptoms. App source code for these data collection modules are available through an open source license for use in studies of other conditions. We hope that releasing data contributed by engaged research participants will seed a new community of analysts working collaboratively on understanding mobile health data to advance human health.