www.radar-cns.orginfo@radar-cns.org

This communication reflects the views of the RADAR-CNS consortium and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein.

This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking 2 (RADAR-CNS grant No 115902) www.imi.europa.eu

The RADAR platform:an open source generalised mHealth infrastructure

Rashid Z1, Ranjan Y1, Kerz M1, Nobilia F1, Borgdorff J3, Campos H4, Moinat M3, Mahasivam N3, Boettcher S 7, Begale M5, Dobson R12

Folarin AA12, The RADAR-CNS Consortium6

1 Department of Biostatistics and Health Informatics, Institute of Psychiatry Psychology and Neuroscience, King’s College London, Box P092, De Crespigny Park, SE5 8AF, UK

2 Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, London WC1E 6BT, UK.

3 The Hyve, Arthur van Schendelstraat 650, 3511 MJ Utrecht, The Netherlands

4 Goldenarm, 20 Jay Street, Suite 840, Brooklyn, NY, 11201

5 Vibrent Health, 12015 Lee Jackson Memorial Highway, Suite 13, Fairfax, VA, 2203, United States

6 The RADAR-CNS Consortium, http://www.radar-cns.org/partners

7 Epilepsy Center, Department of Neurosurgery, University of Hospital Freiburg

By leveraging open source data streaming technologies, an end-to-end system was built with generalized data aggregation capabilities. The platform will focus on

classes of data rather than specific devices, in doing so it will enhance modularity and adaptability as new devices become available. The platform is delivered under

an Apache 2 open source licence in order to create a legacy for downstream RADAR projects and the wider mHealth community. The key components of our software

stack include: Data Ingestion and Schematisation (using Apache AVRO), Database Storage and Data Interface, Data Analytics, Front-end Ecosystem, Privacy and

Security.

AIMS

The €22m IMI2 Remote Assessment of Disease and Relapse – Central Nervous System (RADAR-CNS; http://radar-cns.org) initiative is a new research programme aimed

at developing novel methods and infrastructure for monitoring major depressive disorder, epilepsy, and multiple sclerosis using wearable devices and smartphone

technologies. While a number of commercial mHealth solutions are available to aggregate sensor data, there is a lack of an open source software stack that provides

end-to-end data collection functionality for research, clinical trials and real-world applications. The RADAR platform aims to fill this gap, providing a generalised,

scalable, fault tolerant, high-throughput, low-latency data collection solution.

THE RADAR-CNS PROJECT

FIGURE 1: Detailed schema of RADAR-CNS platform

DATA SOURCES

SmartphoneWearable device

Apps

DeviceMiddleware

3˚ PartyAPI

AUTHENTICATION

REST Proxy

3˚ Party Middleware

Device Topics

Business Topics

Realtime Analytics

HotStorage

File ManagerSchema Library

Historical Analytics

Kafka Connector

ColdStorage

Kafka Connector

Rest API

StorageREST ApiSchemas

Real-time AnalyserBatch Analyser

CORE

AUTHENTICATION

DATA VISUALISATION

DashboardsApps

HOW IT WORKSThe Confluent Platform is a key component in the datapipeline architecture, this open source suite ofstreaming tools is built around Apache Kafka. Patientdata is collected from passive (e.g. hardware sensorstreams) and active (e.g. questionnaires, digital assayapps) data sources. These data payloads are theningested via an HTTPS interface which translates RESTcalls into native Kafka calls. After a restructuring phase,data are simultaneously analysed and persisted. Twodifferent data warehouse layers (cold and hot storage)are deployed to provide low latency and highperformance data access via controlled interfaces.RADAR-CNS Platform runs on Docker to obtainextremely light and easy to deploy infrastructure.

EPILEPSY, DEPRESSION & MULTIPLE SCLEROSIS STUDY

• Epilepsy patients are undergoing study at KCL and

Freiburg.

• Depressions patients are enrolled and undergoing

study at KCL.

• 200 patients will be enrolled for Epilepsy study 1.

• 600 patients will be enrolled for the depression

study.

• Multiple Sclerosis study will target 640 patients.

• Other IMI studies using the platform:

• Alzheimer's study is envisioned with RADAR-AD

platform.

• BigData@Heart.

RESULTS AND VISIONThe catalog of currently integrated devices include on-board Android smartphone sensors along withEmpatica E4 Wristband, Pebble 2 Smartwatch,Biovotion VSM, Faros 180, Fitbit devices. Capability areprovided to integrate all wearable devices offering anative SDK to passively collect RAW data or throughVendor REST-API data access. Beside the pRMT app(passive data source), a questionnaire app built withCordova (aRMT) offers an active remote monitoringdata source which can render questionnaires from asimple JSON configuration file.

RADAR-CNS aims to stimulate the field of mHealth byproviding an off-the-shelf platform for general datacollection. The project has long term goals to improvepatient care by predicting and pre-empting relapseswith the use of remote assessment technologies in awide variety of disorder areas.

FIGURE 2: RADAR-CNS Overview