UVM’s Participation in Medidata’s Groundbreaking Sensor Network Could Lead to Better Patient Care
A reduction in the number of falls that multiple sclerosis patients experience could someday be among the outcomes of the University of Vermont’s participation in Medidata’s Sensor Cloud Network.
“We are leveraging the tools and technology available in the Medidata Sensor Cloud Network to advance and accelerate our work in the development of fall risk detection algorithms in the multiple sclerosis population, a disease that affects 2.3 million patients worldwide, 50% of whom will experience a fall that negatively impacts their quality of life,” said Ryan McGinnis, director of UVM’s M-Sense Research Group, which develops innovative health technologies with partners in engineering, medicine, mental health and movement science.
UVM, along with eight other highly innovative organizations, is joining the Sensor Cloud Network as part of Medidata’s rapidly expanding approach to patient care. Medidata, a Dassault Systèmes company, has announced that AliveCor, Aural Analytics, Biobeat, Blue Spark Technologies, Glooko, Indie Health, University of Arizona, Carnegie Mellon University, University of Rochester, and University of Vermont are now part of the first cross-sector collaboration focused on solving the challenges related to sensor integrations, standardization of sensor data, and the development of novel digital biomarkers and algorithms. These will help to create new digital endpoints that could translate into more effective treatments and better healthcare for patients.
The Sensor Cloud Network, which includes contract research organizations (CROs), device manufacturers, drug and vaccine developers, analytics companies, and academic institutions, creates opportunities for data scientists to refine, test and deliver physiological algorithms with clinical meaning at scale. Examples include refined motion parameters like gait, cardiovascular metrics, metabolic insights, and clinical grade speech analytics.
“The Sensor Cloud Network is allowing us to explore the combination of patient reported outcomes and medical grade wearables data in remote settings at scale to better understand this problem and to develop a digital intervention,” McGinnis said. McGinnis is an associate professor in the Department of Electrical and Biomedical Engineering in UVM’s College of Engineering and Mathematical Sciences.