Currently accepted at: JMIR mHealth and uHealth
Date Submitted: Aug 29, 2018
Open Peer Review Period: Sep 11, 2018 - Oct 12, 2018
Date Accepted: Dec 9, 2018
(closed for review but you can still tweet)
RADAR-base: An Open Source mHealth Platform for Collecting, Monitoring and Analyzing Data Using Sensors, Wearables, and Mobile Devices
With a wide range of use cases in both research and clinical domains, collecting continuous mobile health (mHealth) streaming data from multiple sources in a secure, highly scalable and extensible platform is of high interest to the open source mHealth community. The EU IMI RADAR-CNS program is an exemplar project with the requirements to support collection of high resolution data at scale; as such, the RADAR-base platform is designed to meet these needs and additionally facilitate a new generation of mHealth projects in this nascent field.
Wide-bandwidth networks, smartphone penetrance and wearable sensors offer new possibilities for collecting (near) real-time high resolution datasets from large numbers of participants. We aimed to build a platform that would cater for large scale data collection for remote monitoring initiatives. Key criteria are around scalability, extensibility, security and privacy.
RADAR-base is developed as a modular application, the backend is built on a backbone of the highly successful Confluent/Apache Kafka framework for streaming data. To facilitate scaling and ease of deployment, we use Docker containers to package the components of the platform. RADAR-base provides two main mobile apps for data collection, a Passive App and an Active App. Other 3rd Party Apps and sensors are easily integrated into the platform. Management user interfaces to support data collection and enrolment are also provided.
General principles of the platform components and design of RADAR-base are presented here, with examples of the types of data currently being collected from devices used in RADAR-CNS projects: Multiple Sclerosis, Epilepsy and Depression cohorts.
RADAR-base is a fully functional, remote data collection platform built around Confluent/Apache Kafka and provides off-the-shelf components for projects interested in collecting mHealth datasets at scale.
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