dDream: A Smartphone-Based Comprehensive and Scalable Multi-Parameter Physiological Monitoring Platform

Abstract

Continuous, real-time monitoring of cardiovascular conditions, diabetes, and nephropathy facilitates the early detection of potential complications or changes in a person’s condition. Timely insights from parameters such as heart rate, blood pressure, Oxygen saturation, respiration rate, hemoglobin, creatinine, hbA1c, and glucose enable healthcare providers to adjust treatments and interventions promptly, improving patient outcomes. Monitoring these vital signs provides a comprehensive view of a patient’s health, enabling the identification of subtle physiological changes that can act as early biomarkers for critical conditions, thus supporting timely medical interventions and personalized care strategies. We have developed an end to end, integrated vital signs monitoring system comprising of mobile applications for Android and iOS. These apps capture user facial or fingertip videos under specific lighting conditions and transmit the recordings to the server for analysis. The mobile apps also display real-time health insights derived from the server’s analysis of the captured video data. We propose an optimized Django server application to manage the storage and retrieval of the vital monitoring system dealing with massive amounts of health data in a secure, state-of-the-art pipeline. Our approach is expected to improve scalability and reduce costs by offloading suitable workloads.