Wearable sensors enable personalized predictions of clinical laboratory measurements.

ABSTRACT: Vital signs, including heart rate and body temperature, are useful in detecting or monitoring medical conditions, but are typically measured in the clinic and require follow-up laboratory testing for more definitive diagnoses. Here we examined whether vital signs as measured by consumer wearable devices (that is, continuously monitored heart rate, body temperature, electrodermal activity and movement) can predict clinical laboratory test results using machine learning models, including random forest and Lasso models. Our results demonstrate that vital sign data collected from wearables give a more consistent and precise depiction of resting heart rate than do measurements taken in the clinic. Vital sign data collected from wearables can also predict several clinical laboratory measurements

SUBMITTER: Dunn J 

PROVIDER: S-EPMC8293303 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature