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Further Developing Duke's Wearable Infection Detection Platform (2024-2025)

This project team built on previous teams to refine an online infection detection platform that collects and translates wearable health data from multiple sources into a user-friendly format. Designed to track the onset and progression of illnesses such as COVID-19 and influenza, the platform also supports studies on how comorbidities and demographics influence disease outcomes. Central to the effort was the integration of a custom wearable device and companion iOS/web app with health anomaly detection algorithms, enabling early alerts for physiological changes that could indicate infection.

Over the course of the year, the team advanced the hardware, software and data infrastructure supporting the system. The hardware group finalized a compact, custom sensor device, designing its printed circuit board, casing and microcontroller code. The frontend team developed an iOS app for real-time data collection and a web application to visualize health metrics. The data science and cloud engineering team built automated pipelines on Google Cloud to process raw sensor inputs, extract features like heart rate and step count, and validate data accuracy.

These efforts produced a fully functional prototype capable of collecting, processing and visualizing high-frequency physiological data. The team’s work culminated in a live demonstration at the 2024 IEEE-EMBS International Conference on Body Sensor Networks in Chicago, where attendees wore the device and viewed their live health data through the apps. The platform’s continued development is expected to enhance disease monitoring and contribute to future public health research.

Timing

Summer 2024 – Spring 2025

Team Outputs

Custom wearable device

Web app for online infection detection

Visualization dashboards

Showcased Device at the IEEE-EMBS International Conference on Body Sensory Networks, Chicago, Illinois, October 2024

Further Developing Duke's Wearable Infection Detection Platform (Interactive display and poster presented at the Fortin Foundation Bass Connections Showcase, Duke University, April 16, 2025)

See related Data+ summer project, Further Developing Duke’s Wearable Infection Detection Platform, and earlier related team, Refining and Expanding Duke’s Wearable Infection Detection Platform (2023-2024).

 

Image: Video still from CovIdentify website

Team Leaders

  • Jessilyn Dunn, Pratt School of Engineering: Biomedical Engineering
  • Ali Roghanizad, Pratt School of Engineering: Biomedical Engineering

Graduate Team Members

  • Jamee Krzanich, Electrical/Computer Engg-MS
  • Lauren Lederer, Biomedical Engineering-PHD
  • Naomi Patel, Electrical/Computer Engg-MS
  • Cindy Wang, Master of Egr Biomedical Egr

Undergraduate Team Members

  • Krish Bansal, Computer Science (BS); Statistical Science (BS2)
  • Amy Duan, Computer Science (BS); Statistical Science (BS2)
  • Aayush Goyal, Electrical & Computer Egr(BSE); Computer Science (BS2)
  • Amy Liu, Computer Science (BS)