Bruce R. Schatz Publishes New Study in PLOS Digital Health

Professor Bruce R. Schatz has been published in the PLOS Digital Health, a new open access journal emphasizing health equity and unbiased healthcare. This article, “Population Analysis of Mortality Risk: Predictive Models from Passive Monitors Using Motion Sensors for 100,000 UK Biobank Participants,” is a culmination of four years of medical informatics research by Schatz and his colleagues.

Prior to Schatz’s work, studies used measures of physical fitness, such as walk tests and self-reported walk pace, to predict individual mortality risk. Those measures focus on quality of movement rather than movement quantity. However, the prevalence of smartphones and passive smartphone activity monitoring provides a unique method of physical fitness measurement. This monitoring opens up the possibility for population-level analyses of walking activity and offers an opportunity for national screening for health and mortality risk.

For this study, Schatz and other researchers studied 100,000 participants in the UK Biobank national cohort who wore activity monitors with motion sensors for one week. While the wrist sensor is worn differently than how smartphone sensors are carried, their motion sensors can both be used to extract information on walking intensity from short bursts of walking—a daily living version of a walk test.

The research team was able to successfully validate predictive models of mortality risk using only 6 minutes per day of steady walking collected by the sensor, combined with traditional demographic characteristics. The equivalent of gait speed calculated from this passively collected data was a predictor of 5-year mortality independent of age and sex. The predictive models used only walking intensity to simulate smartphone monitors.

“Our results show passive measures with motion sensors can achieve similar accuracy to active measures of gait speed and walk pace,” the authors say. “Our scalable methods offer a feasible pathway towards national screening for health risk.”

This project was awarded the Arnold O. Beckman Award designation by the Campus Research Board in 2019, and was covered by Recognizing Excellence in an earlier post. This award provided funding for the purchase of unique datasets used in the development of predictive models for Schatz’s research.

Schatz is a professor in the University Library and a professor in the Carl R. Woese Institute for Genomic Biology, where this study’s research occurred. He is also a professor and head of the Department of Medical Information Science in the College of Medicine, and a professor of Computer Science in the College of Engineering at Illinois. He was the principal investigator of national flagship NSF projects in digital libraries and in bioinformatics. He is the author of the first technical book on using wearable and mobile devices to revolutionize medicine and public health, Healthcare Infrastructure: Health Systems for Individuals and Populations (2011).

You can find Schatz’s paper here. Read the full AAAS and EurekAlert! news release here.

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