Wearable activity tracker data can be used to obtain metrics associated with the user's physical health

Wearable activity tracker data can be used to obtain metrics associated with the user’s physical health

A new study from Johns Hopkins shows that data collected from wearable activity trackers can be used to obtain several metrics associated with a user’s general physical health and cardiovascular health status. Although these sensors are typically marketed as daily step counters, the Johns Hopkins research team believe they could potentially serve a larger purpose: supporting the clinical care of patients with pulmonary arterial hypertension (PAH). and other chronic diseases.

The study was published in npj Digital Medicine in Nov 9.

The purpose of this study was to show that clinically relevant metrics beyond daily step count can be derived from these wearable activity monitors. Historically, monitoring a patient’s physical condition remotely has been difficult. We wanted to take on this challenge and see what kind of untapped information is contained in these devices that could help us support PAH patients. »

Zheng “Peter” Xu, Ph.D., study first author and postdoctoral fellow for inHealth, a strategic initiative to advance precision medicine at Johns Hopkins University

The Cleveland Clinic provided the Johns Hopkins research team with activity tracker data for 22 people with PAH who wore activity trackers between clinic visits. During the two clinic visits, healthcare professionals at the Cleveland Clinic recorded 26 measures of each participant’s health, including health-related quality of life, heart rate measurements and test results. commonly used aerobic capacity and endurance test, known as the six-minute walking distance (6MWD) test.

Using minute-by-minute data on each participant’s step rate and heart rate, the Johns Hopkins team determined several metrics widely associated with physical health and cardiovascular function. These included the distribution of heart rate, intensity and frequency of walking instances throughout each week, as well as results from an analog version of the 6MWD test which the team dubbed the test. six-minute walking distance in free life. This data allowed the team to understand the health status of each participant and identify subgroups among the participants with similar parameters to each other.

To demonstrate that this data has potential for clinical use, the team also compared the activity tracking parameters with the 26 health parameters recorded during the two clinic visits -; and found unexpected correlations. For example, an assessment of physical fitness measured by an activity tracker (based on step count and heart rate data) correlated with clinically measured levels of NT-proBNP, a blood biomarker used to assess the risk of heart failure. Among the 22 participants, the research team found statistically significant differences in 18 of these measures.

Finding so many statistically significant differences in a relatively small cohort suggests to us that activity tracking data may help identify surrogate markers of disease severity that can be monitored remotely. This data could potentially help identify patients who would benefit from more frequent clinic visits or specific medications.”

Peter Searson, Ph.D., study lead author and Joseph R. and Lynn C. Reynolds Professor at Johns Hopkins University Whiting School of Engineering

“We also believe that health parameters measured by activity tracking could serve as proxies for clinically measured health parameters of patients with chronic diseases,” adds Searson.

Next, the research team is studying whether these devices could support clinical care for patients with chronic obstructive pulmonary disease (COPD) and scleroderma. In collaboration with the Johns Hopkins COPD Precision Medicine Center of Excellence, they will investigate whether signals derived from activity trackers can be used to predict the risk of a COPD flare-up.


Journal reference:

Xu, Z. et al. (2022) Assessing physical health status beyond daily step count using a wearable activity sensor. npj Digital medicine. doi.org/10.1038/s41746-022-00696-5.

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