Digital Phenotyping of Mental and Physical Conditions: Remote Monitoring of Patients Through RADAR-Base Platform

Abstract

Background:The integration of digital biomarkers and remote patient monitoring offers valuable and timely insights into a patient's management of their condition, including aspects such as disease progression and treatment response. This serves as a complementary resource to traditional healthcare settings leveraging mobile technology to improve scale and lower latency, cost and burden.Objective: Smartphones with embedded and connected sensors have immense potential for improving healthcare through various apps and mHealth (mobile health) platforms. This capability could enable the development of reliable digital biomarkers from long-term longitudinal data collected remotely from patients. Methods:We built an open-source platform, RADAR-base, to support large-scale data collection in remote monitoring studies. RADAR-base is a modern remote data collection platform built around Confluent's Apache Kafka, to support scalability, extensibility, security, privacy and quality of data. It provides support for study design and set-up, active (eg PROMs) and passive (e.g. phone sensors, wearable devices and IoT) remote data collection capabilities with feature generation (e.g. behavioural, environmental and physiological markers). The backend enables secure data transmission, and scalable solutions for data storage, management and data access. Results:The platform has been used to successfully collect longitudinal data for various cohorts in a number of disease areas including Multiple Sclerosis, Depression, Epilepsy, ADHD, Alzheimer, Autism and Lung diseases. Digital biomarkers developed through collected data are providing useful insights into different diseases.Conclusions: RADAR-base offers a contemporary, open-source solution driven by the community for remotely monitoring, collecting data, and digitally characterising both physical and mental health conditions. Clinicians have the ability to enhance their insight through the utilisation of digital biomarkers, enabling improved prevention, personalisation, and early intervention in the context of disease management.