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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.

Emphasis

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-R21-EB026177-02 Real-time non-intrusive workload monitoring-Integration of human factors in surgery training and assessment Denny Yu Purdue University
5-R21-EB028486-03 Estimating Trajectory of Recovery in Cardiac Rehabilitation using Mobile Health Technology and Personalized Machine Learning Jack Mortazavi Texas Engineering Experiment Station
5-U24-EB028990-03 Accelerating collaborative, cumulative, and open intervention science with an e-intervention authoring platform Steven Ondersma Michigan State University
5-R21-EB027276-03 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-R21-EB028396-03 A wireless fully-passive miniaturized patient-tailored pacemaker Jennifer Blain Christen Arizona State University-Tempe Campus
5-R01-EB027777-03 Achieving Optimal Motor Function in Stroke Survivors via a Human-Centered Approach to Design an mHealth Platform Sunghoon Lee University of Massachusetts Amherst
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
5-R21-EB025525-02 The SPARC App: A Smartphone Application for the Management of Sarcoidosis-Associated Fatigue Walter James Medical University of South Carolina
1-R01-EB032382-01 Smart-phone-integrated, non-invasive, depth-resolved optical spectroscopy for the detection of neonatal jaundice Audrey Bowden Vanderbilt University
1-R01-EB031910-01A1 Smartphone-based wound infection screener and care recommender by combining thermal images and photographs using deep learning methods Emmanuel Agu Worcester Polytechnic Institute