Disease Insight through Digital Biomarkers Developed by Remotely
Collected Wearables and Smartphone Data
- URL: http://arxiv.org/abs/2308.02043v1
- Date: Thu, 3 Aug 2023 22:44:48 GMT
- Title: Disease Insight through Digital Biomarkers Developed by Remotely
Collected Wearables and Smartphone Data
- Authors: Zulqarnain Rashid, Amos A Folarin, Yatharth Ranjan, Pauline Conde,
Heet Sankesara, Yuezhou Zhang, Shaoxiong Sun, Callum Stewart, Petroula Laiou,
Richard JB Dobson
- Abstract summary: RADAR-base is a modern remote data collection platform built around Confluent's Apache Kafka.
It provides support for study design and set-up, active (eg PROMs) and passive (eg. phone sensors, wearable devices and IoT) remote data collection capabilities.
The platform has successfully collected longitudinal data for various cohorts in a number of disease areas including Multiple Sclerosis, Depression, Epilepsy, ADHD, Alzheimer, Autism and Lung diseases.
- Score: 3.9411499615751113
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Digital Biomarkers and remote patient monitoring can provide valuable and
timely insights into how a patient is coping with their condition (disease
progression, treatment response, etc.), complementing treatment in traditional
healthcare settings.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. 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
(eg. phone sensors, wearable devices and IoT) remote data collection
capabilities with feature generation (eg. behavioural, environmental and
physiological markers). The backend enables secure data transmission, and
scalable solutions for data storage, management and data access. The platform
has successfully collected 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.
RADAR-base provides a modern open-source, community-driven solution for remote
monitoring, data collection, and digital phenotyping of physical and mental
health diseases. Clinicians can use digital biomarkers to augment their
decision making for the prevention, personalisation and early intervention of
disease.
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