ANN ARBOR—The University of Michigan is one of a dozen centers sharing a $10.8 million grant from the National Institutes of Health aimed at developing innovative tools to gather, analyze and interpret health data generated by mobile and wearable sensors.
The Mobile Sensor Data-to-Knowledge team consists of computer scientists, engineers and statistical and biomedical researchers working together to turn the wealth of mobile sensor data available through new and rapidly evolving wearable sensors into reliable and actionable health information.
“We are going to be developing Just-in-Time Adaptive Intervention methods,” said Susan Murphy, a statistician who heads the U-M team. “In particular, we will develop data analysis methods that will continually analyze and re-analyze individual responses to cell phone interventions. Our data analysis methods will incorporate how individuals respond to the intervention to individualize when, where and what interventions will be most effective.”
“Although we will focus on supportive interventions for reducing smoking relapse, our goal is to develop methodologies that can be useful across a wide variety of health behaviors, including weight loss, physical activity and managing mental illness,” said U-M team member Inbal (Billie) Nahum-Shani, a researcher behavioral scientist affiliated with the Quantitative Methodology Program at the U-M Institute for Social Research.
According to Nahum-Shani, the methods the U-M team will develop build on the idea that the needs of a specific person might differ from the needs of someone else, and might also change over time.
One person might benefit from receiving a supportive message via cell phone, for example, while another might not. And for that same person, receiving a supportive message might be helpful in the morning, but not in the evening.
“To help people adopt and maintain healthy behaviors, it is important to accommodate their unique and changing needs by supporting them in a timely and adaptive manner,” Nahum-Shani said.
“Mobile sensors offer tremendous opportunities for accelerating biomedical discovery and optimizing care delivery,” said University of Memphis computer scientist Santosh Kumar, who heads the multi-site project. “By resolving significant technological and scientific challenges related to the complexities of mobile sensor data, our team aims to…usher in the next generation of health care.”
In addition to researchers from Michigan and Memphis, the MD2K team consists of leading scientists from Cornell, Georgia Tech, Northwestern, Ohio State, Rice, UCLA, UC-San Diego, UC-San Francisco, Massachusetts and Open mHealth, a nonprofit organization.
The Mobile Sensor Data-to-Knowledge Center is part of the NIH Big Data to Knowledge initiative, designed to support advances in research, policy and training that are needed for the effective use of Big Data in biomedical research.
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