The mPower study, Parkinson disease mobile data collected using ResearchKit

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.

Mobile and pervasive computing technologies and the future of Alzheimer’s clinical trials

“…This registry was recently used successfully to recruit and conduct a purely online randomized clinical trial of cognitive training. 12 Research apps such as Apple's Research Kit now also allow participants a simple way to consent, participate, and share their data, 13 and these apps can be adapted for consenting caregivers and legal representatives. Ultimately, it is hoped such registries do not exist in silos, are able to recruit samples representative of the population, and keep subjects engaged over long periods to minimize selection and attrition biases.…”

A dataset of human decision-making in teamwork management

“…It is developed and operated by Sage Bionetworks. Many scientific datasets collected using similar approaches to ours, such as the mPower dataset 20 , adopt Synapse for data storage and distribution.…”

Implementing ethics for a mobile app deployment

“…Similarly, Böhmer et al (2011) and Sahami et al (2013; deployed apps in order to understand how the device as a whole is used. Beyond HCI, there is a growing body of health research using app store releases, for example Bot et al's (2016) collection of data for a study of Parkinson Disease. The preference in HCI is generally for collecting data on 'naturalistic engagement', whereas health research often requires users to comply with a specific regime for generating data.…”