WASH: Warfighter Analytics for Smartphone Healthcare
Worcester Polytechnic Institute
"The technology we are creating through WASH, which will discover predictive patterns in massive data sets in real time, is bound to be transformative."

-Prof. Elke Rundensteiner
Overview
Warfighters face an increased exposure to various ailments such as Traumatic Brain Injury (TBI) and infectious diseases. Digital biomarkers are smartphone-sensable user behaviors that can reliably indicate the health status, ailment symptoms and condition of the smartphone user. For example, an ailing smartphone user may exhibit reduced daily step counts or stay longer in sedentary activity states during their day.

Funded by the DARPA Warfighter Analytics using Smartphones for Health (WASH) project, our team is researching and developing machine/deep learning algorithms that synthesize reliable smartphone biomarkers that enable continuous, real-time assessment of TBI and infectious diseases afflicting warfighters by leveraging data unobtrusively captured from smartphone sensors.
Our approach includes:


Feature engineering of smartphone sensor data

Statistical modeling of personalized behavior typical of a smartphone user

Detection of higher-order activity states from low-level signals

Machine/Deep learning of robust outliers or deviations from normal, healthy behavior

Inference of classes of diseases affecting a smartphone user

Empirical study and evaluation of robustness of biomarker detectors

People
Faculty
Prof Emmanuel Agu (PI)
Prof Elke A Rundensteiner
Students
Abdulaziz Alajaji
PhD, Data Science
Walter Gerych
PhD, Data Science
Hamid Mansoor
PhD, Computer Science
Luke Buquicchio
PhD, Data Science
Kavin Chandrasekaran
PhD, Data Science
Medical Collaborators
Dr Richard Ellison
Infectious Diseases
UMass Medical School
Dr Mark Johnson
Head of Neurology Dept
UMass Medical School
Dr Suzanne Muehlschegel
Dept of Neurology
UMass Medical School
Joan Swearer, PhD
Professor of Neuropsychology
UMass Medical School
Results
News
Contact
WPI WASH Project Team
Prof Emmanuel Agu
Prof Elke A Rundensteiner