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. 2019 Aug 1;7(8):e11734.
doi: 10.2196/11734.

RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices

Yatharth Ranjan  1 , Zulqarnain Rashid  1 , Callum Stewart  1 , Pauline Conde  1 , Mark Begale  2 , Denny Verbeeck  3 , Sebastian Boettcher  4 ; Hyve  5 ; Richard Dobson  1   6 , Amos Folarin  1   6 ; RADAR-CNS Consortium  7
Collaborators, Affiliations

RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices

Yatharth Ranjan et al. JMIR Mhealth Uhealth. .

Abstract

Background: 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 European Union Innovative Medicines Initiative Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) program is an exemplary project with the requirements to support the collection of high-resolution data at scale; as such, the Remote Assessment of Disease and Relapse (RADAR)-base platform is designed to meet these needs and additionally facilitate a new generation of mHealth projects in this nascent field.

Objective: Wide-bandwidth networks, smartphone penetrance, and wearable sensors offer new possibilities for collecting near-real-time high-resolution datasets from large numbers of participants. The aim of this study was 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.

Methods: 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 2 main mobile apps for data collection, a Passive App and an Active App. Other third-Party Apps and sensors are easily integrated into the platform. Management user interfaces to support data collection and enrolment are also provided.

Results: 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.

Conclusions: 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.

Keywords: mental health; mobile applications; remote sensing technology; telemedicine.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Technical overview of the RADAR-base platform stack.
Figure 2
Figure 2
Current data sources: Empatica E4, Pebble 2, Fitbit, Biovotion, Faros, active Remote Monitoring Questionnaire app, and passive Remote Monitoring app.
Figure 3
Figure 3
Schema overview for the phone acceleration.
Figure 4
Figure 4
Passive Remote Monitoring app user interface. The Device column lists all the devices that are connected to the app and collect data. Device connection/disconnection is shown by green and red icons, respectively. The 3 columns next to “Device show the different values that are being measured on the connected devices. The last column shows the amount of data (or records) that have been collected.
Figure 5
Figure 5
User interface of the active Remote Monitoring app.
Figure 6
Figure 6
Contiguity of phone sensor data over 6 months collected through RADAR-base for aparticipant in the major depressive disorder study. The red line corresponds to the enrollment date, whereas a coloured segment on each row corresponds to recorded data at an hourly resolution.
Figure 7
Figure 7
Participant data view (battery and accelerometer streams).
Figure 8
Figure 8
RADAR-base Management Portal.
Figure 9
Figure 9
User registration workflow.
See this image and copyright information in PMC

References

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