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RADAR-base: A Novel Open Source m-Health Platform

Ranjan, Y; Kerz, M; Rashid, Z; Boettcher, S; Dobson, RJB; Folarin, AA; (2018) RADAR-base: A Novel Open Source m-Health Platform. In: Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers. (pp. pp. 223-226). ACM: New York (NY), USA. Green open access

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Abstract

Smartphones with embedded and connected sensors are playing vital role in healthcare through various apps and mHealth platforms. RADAR-base is a modern mHealth data collection platform built around Confluent and Apache Kafka. RADAR-base enables study design and set up, active and passive remote data collection. It provides secure data transmission, and scalable solutions for data storage, management and access. The application is used presently in RADAR-CNS study to collect data from patients suffering from Multiples Sclerosis, Depression and Epilepsy. Beyond RADAR-CNS, RADAR-base is being deployed across a number of other funded research programmes.

Type: Proceedings paper
Title: RADAR-base: A Novel Open Source m-Health Platform
Event: The 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
Location: Singapore, Singapore
Dates: 8th-12th October 2018
ISBN-13: 978-1-4503-5966-5
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3267305.3267579
Publisher version: https://doi.org/10.1145/3267305.3267579
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: mHealth; mobile context sensing; wearable sensors; data collection platform; mental health
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10087380
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