Integrating wearable data into circadian models

Authors: HANNAY, KEVIN - University Of Michigan; MORENO, JENNETTE - Children'S Nutrition Research Center (CNRC)

Submitted to: Current Opinion in Systems Biology
Publication Type: Review Article
Publication Acceptance Date: 6/30/2020
Publication Date: 8/21/2020
Citation: Hannay, K.M., Moreno, J.P. 2020. Integrating wearable data into circadian models. Current Opinion in Systems Biology. 22:32-38. https://doi.org/10.1016/j.coisb.2020.08.001.
DOI: https://doi.org/10.1016/j.coisb.2020.08.001

Interpretive Summary:

Technical Abstract: The emergence of wearable health sensors in the last decade has the potential to revolutionize the study of sleep and circadian rhythms. In particular, recent progress has been made in the use of mathematical models in the prediction of a patient's internal circadian state using data measured by wearable devices. This is a vital step in our ability to identify optimal circadian timing for health interventions. We review the available data for fitting circadian phase models with a focus on wearable data sets. Finally, we review the current modeling paradigms and explore avenues for developing personalized parameter sets in limit cycle oscillator models to further improve prediction accuracy.