Precision Health at the University of Michigan is happy to announce 10 recipients of its Investigators Awards: grants of up to $300,000 each over two years. The grants, totaling nearly $3 million, will support research in a spectrum of precision health fields, including wearable technology, machine learning, predictive modeling, genetic analysis, imaging, and social science. View a full list of awardees and their topics.
Awardees were chosen from among an initial pool of more than 100 applicants with significant research projects.
“It was exciting to learn about the breadth of activities proposed across the many strong grant applications, and challenging to choose the 10 that were eventually funded,” said U-M Precision Health Co-Director Mike Boehnke. “We look forward to learning from these projects, and to seeing the next round of proposals in 2019.”
Emily Mower Provost, Ph.D., Associate Professor, Electrical Engineering and Computer Science, is a collaborator on the Prechter Bipolar Research team and one of the 10 awardees. Her project title is “Measuring and Interpreting the Relationship Between an Individual’s Social Environment and Mood.”
Here's her project description:
Individuals with mood disorders require regular clinical monitoring to promote long-term health. Yet, current resource-intense and clinic-based methods are costly and inefficient. Clinical observations and evaluations of speech and social interaction patterns are essential to psychiatric evaluation, but few reliable methods to measure, compare, and document changes exist beyond the opinion of the clinical observer (variable) and the memory of the patient (unreliable). These clinical challenges have significantly hampered the development of objective biomarkers.
Dr. Mower Provost and her team propose novel technology, data collection, and computational models that will provide objective assessments of an individual’s behavior and social environment based on analyses of comprehensive mobile data that includes ambient speech recordings. This will provide an ecologically valid context in which to study how an individual’s behavior and social environment impact his/her wellness.
The result will be new measurement methods to determine how moods and mood episodes shape and are shaped by both the behavior of an individual and daily interactions over time, leading to individualized early warning signs (EWS) for mood disorders. Establishing the EWS is key in determining the need for and nature of an actionable intervention.
These methods will be ultimately deployed beyond mood disorders, focusing on individuals at risk for opiate abuse, post-traumatic stress disorder, anxiety, and suicidality. “Our goal is to establish reliable methods for the study of social and personal parameters, fundamental to the success of the precision medicine initiative,” says Dr. Mower Provost.
The original press release can be found here.