A computationally efficient algorithm to obtain an accurate and interpretable model of the effect of circadian rhythm on resting heart rate

Objective : Wrist-worn wearable devices equipped with heart rate (HR) sensors have become
increasingly popular. The ability to correctly interpret the collected data is fundamental to
analyse user ’s well-being and perform early detection of abnormal physiological data. Circadian
rhythm is a strong factor of variability in HR, yet few models attempt to accurately model its
effect on HR. Approach : In this paper we present a mathematical derivation of the single-component
cosinor model with multiple components that fits user data to a predetermined arbitrary function
(the expected shape of the circadian effect on resting HR (RHR)), thus permitting us to predict the
user ’s circadian rhythm component (i.e. MESOR, Acrophase and Amplitude) with a high accuracy. Main
results : We show that our model improves the accuracy of HR prediction compared to the single
component cosinor model (10% lower RMSE), while retaining the readability of the fitted model of the
single ...

Source: Physiological Measurement - September 28, 2019 Category: Physiology Authors: Davide Morelli, Leonardo Bartoloni, Alessio Rossi and David A Clifton Source Type: research