Statistical Methods for Real-Time Monitoring of Physical Disability in Multiple Sclerosis

Vadim Zipunnikov (Biostatistics)

Kathleen Zackowski (Motion Analysis Lab)

The lack of sensitive outcomes capable of detecting progression of Multiple Sclerosis (MS) is a primary limitation to the development of newer therapies. Wearables provide real-time objective measurement of physical activity of MS patients in a real-world context. We put forward a novel statistical framework that simultaneously characterizes multiple features of physical activity profiles over the course of a day as well as their day-to-day dynamics. The proposed framework will allow MS researchers to identify physical activity signatures that will distinguish between individuals with different MS types and will help to understand physical activity differences in disability progression.​


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