# 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  
**arXiv:** [2308.02043](https://arxiv.org/abs/2308.02043)  
**Date:** 2023-08-03  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2308.02043v1/

## Key points

- Digital biomarkers and remote patient monitoring can provide valuable insights into a patient's condition
- They can help with disease progression and treatment response
- Smartphones with embedded sensors and connected devices have the potential to improve healthcare through apps and mobile health platforms
- RADAR-base is an open-source platform built around Confluent's Apache Kafka
- RADAR-base ensures scalability, extensibility, security, privacy, and data quality
- It supports study design, set-up, and remote data collection capabilities
- The platform enables feature generation from collected data, including behavioral, environmental, and physiological markers.

## Summary

Digital biomarkers and remote patient monitoring have the potential to provide valuable insights into a patient's condition, such as disease progression and treatment response. This can complement traditional healthcare settings and improve healthcare outcomes. Smartphones with embedded sensors and connected devices offer immense potential for improving healthcare through various apps and mobile health platforms. To support large-scale data collection in remote monitoring studies, an open-source platform called RADAR-base has been developed. Built around Confluent's Apache Kafka, RADAR-base ensures scalability, extensibility, security, privacy, and data quality. It supports study design and set-up, as well as active (e.g., Patient-Reported Outcome Measures) and passive (e.g., phone sensors, wearable devices, IoT) remote data collection capabilities. The platform also enables feature generation from collected data, including behavioral, environmental, and physiological markers.