Digital Health - Mobile Health and Telehealth

This program supports the development of enabling technologies that emphasize the integration of wireless technologies with human and biological interfaces. This program includes the development of software and hardware for telehealth and mobile health studies.


The program includes the input and delivery of healthcare information digitally for the analysis or monitoring of health or disease status.  The emphasis is on developing mobile health technologies driven by clinical needs and integrating these technologies in healthcare delivery, wellness and daily living.

Program priorities and areas of interest:

  • Predictive: digital technologies that automatically capture information to proactively diagnose, manage, and/or deliver preventive and therapeutic care
  • Pre-emptive: designing interconnected, intelligent solutions with the result in mind
  • Preventative: mobile and home-based devices monitor vital signs and activities in real time and communicate with personal health record services, PCs and smartphones, caregivers and healthcare professionals
  • Personalized care accessible to all communities
  • Machine learning: smarter health systems that continually analyze information from multiple devices and other sources to derive insights and recommendations for the individual’s health regimes
  • Artificial intelligence: analytics programs that monitor mobile device data and use rules and logic to compare against targets, track progress, and send alerts
Grant Number Project Title Principal Investigator Institution
5-R01-EB021331-04 FeverPhone: Point of Care Diagnosis of Acute Febrile Illness using a Mobile Device David Erickson Cornell University
5-R24-EB025845-03 Open mHealth: Community-Based Data and Metadata Standards for Mobile Health Ida Sim University of California, San Francisco
5-R21-EB026164-02 A Medical-Grade Smart-Phone Based Monitoring System Antonis Armoundas Massachusetts General Hospital
5-U2C-EB021881-05 The Health ePeople Resource for Mobilized Research Jeffrey Olgin University of California, San Francisco
5-R21-EB022271-02 Improving Calibration of Wearable Blood Pressure Monitoring Quan Zhang Massachusetts General Hospital
5-R21-EB027276-02 Mobile Device-Based Congestion Prediction for Reducing Hospitalizations in Patients with Concomitant Heart Failure and Atrial Fibrillation Mohammed Saeed University of Michigan at Ann Arbor
5-U01-EB023035-04 CPS: Sensing Processing and Action of Biomedical Smart Textiles Kapil Dandekar Drexel University
5-R21-EB025284-03 A wearable mHealth system for the longitudinal monitoring of joint function in patients with knee OA Sunghoon Lee University of Massachusetts Amherst
1-P41-EB028242-01A1 mHealth Center for Discovery, Optimization, and Translation of Temporally-Precise Interventions (mDOT) Santosh Kumar University of Memphis
1-R21-EB025525-01A1 The SPARC App: A Smartphone Application for the Management of Sarcoidosis-Associated Fatigue Walter James Medical University of South Carolina