TITLE:  Makings Sense of Sensors

ABSTRACT:

The crashing wave of activity tracking “wearables” opens up an opportunity to unveil previously hidden but pivotal signatures of disability and disease. To achieve this promise, the understanding, interpretation and analysis of complex multimodal data produced by such devices becomes crucial. The first part of my talk will provide an overview of the instruments that are available for real-time measurement of physical activity as well as a quick review of the strengths and limitations of current methods for measuring physical activity. In the second part, I will talk about analysis of data collected on 700+ subjects wearing an Actiheart device that collects minute-by-minute activity counts and heart rate for one week as a part of the Baltimore Longitudinal Study of Aging. I will discuss recent multilevel functional data approaches to separate and quantify the systematic and random circadian patterns of physical activity as functions of time of day, age, and gender in this population.

Brief Bio:

Vadim Zipunnikov earned his PhD in Statistics from Cornell University. After three years as a postdoctoral fellow at the Department of Biostatistics at Johns Hopkins University, he joined the department as a faculty. He is deeply involved in analyzing and modeling accelerometry measured physical activity, heart rate, and ecological momentary assessment (EMA) data in large-scale epidemiological studies such as Baltimore Longitudinal Study of Aging (BLSA), NIMH Family Study of Health and Behavior, and National Health and Nutrition Examination Survey (NHANES).