Visualizing Real Time Data from Mobile Health Technologies

Project Summary

Over ten weeks, Computer Science majors Daniel Bass-Blue and Susie Choi joined forces with Biomedical Engineering major Ellie Wood to prototype interactive interfaces from Type II diabetics' mobile health data. Their specific goals were to encourage patient self-management and to effectively inform clinicians about patient behavior between visits.

Themes and Categories
Year
2017
Contact
Ashlee Valente
Center for Applied Genomics and Precision Medicine
ashlee.valente@duke.edu

Project Results: The team worked with patient data from a study that involved readings from a Fitbit, a Bluetooth glucometer, and a Bluetooth scale. Working in Tableau, they created both patient-facing and clinician-facing interactive visualizations. The former allows patients to identify trends of abnormally low or high blood glucose at certain meals or on certain days, and the latter help clinicians identify problematic days/times for specific patients. They also developed an SMS system which notifies clinicians when patients are experiencing dangerous blood glucose levels.

Partially funded by the Duke University School of Nursing and Duke University School of Medicine

Click here for the Executive Summary

Faculty Lead: Ryan Shaw

Project Manager: Michael Lindon

"Walking into Data+, I thought that Data Science research was about just leveraging math and software to make meaning. What I found was that true Data Scientists become enlightened by their data before they try to speak for it." — Ellie Wood, Biomedical Engineering

Related People

Related Projects

A team of students, led by Electrical and Computer Engineering professor Vahid Tarokh, will develop methods to improve the efficiency of information processing with adaptive decisions according to the structure of new incoming data. Students will have the opportunity to explore data-driven adaptive strategies based on neural networks and statistical learning models, investigate trade-offs between error threshold and computational complexity for various fundamental operations, and implement software prototypes. The outcome of this project can potentially speed up many systems and networks involving data sensing, acquisition, and computation.

Project Leads: Yi Feng, Vahid Tarokh

A team of students will explore new ways of reading pre-modern maps and perspectival views through image tagging, annotation and 3D modeling. Each student will build a typology of icons found in these early maps (for example, houses, churches, roads, rivers, etc.). By extracting, modeling, and cataloging these features, the team will create a library of 2D and 3D objects that will be used to (a) identify patterns in how space and power are represented across these maps, and (b) to create a model for “experiencing” these maps in 3D, using the Unity game engine platform. This is a combined Data+ / Bass Connections project that will instruct students in qualitative and quantitative mapping techniques, basic 3D modeling and the history of cartography.

Project Lead: Philip Stern, Ed Triplett

Project Manager: Sam Horewood

A team of students will explore ways in which data science can help support the mission of Rewriting the Code, a national non-profit organization dedicated to empowering a community of college women with a passion for technology.

In particular, students will perform statistical analyzes of past survey data, build out interactive dashboards that help visualize trends in student experience, and help design future survey questions.

Project Lead: Sue Harnett

Faculty Lead: Alexandra Cooper

Project Manager: Imari Smith