Tutorial- Wednesday 9:30 AM EDT
Title: Considerations for Analysis of Data Collected by Wearable Digital Health Technology in Clinical Trials
Presenters: Andrew Potter, FDA

Abstract:
This tutorial will discuss statistical issues in the analysis of data collected by wearable sensors including activity monitors and blood pressure. Topics covered include missing data, functional data analysis and longitudinal data analysis for data measuring continuously in time.

References:

Catellier DJ et al, Imputation of missing data when measuring physical activity by accelerometry. Med Sci Sports Exerc. 2005;37(11 Suppl):S555‐S562. doi: 10.1249/01.mss.0000185651.59486.4e
Song J et al, A semiparametric model for wearable sensor-based physical activity monitoring data with informative device wear, Biostatistics, Volume 20, Issue 2, April 2019, Pages 287–298. doi: https://doi.org/10.1093/biostatistics/kxx073
Byrom B and Rowe DA, Measuring free-living physical activity in COPD patients: Deriving methodology standards for clinical trials through a review of research studies, Contemporary Clinical Trials, Volume 47, 2016, Pages 172-184. doi: https://doi.org/10.1016/j.cct.2016.01.006.
Potter A, (2017) Multiscale multivariate functional principal component analysis with an application to multivariate longitudinal cardiac signals. Doctoral Dissertation, University of Pittsburgh. (Unpublished)


Bio:
Andrew Potter is a mathematical statistician in the Division of Biometrics I in CDER supporting the review work in the Division of Psychiatry. His research interests include the use of digital health technologies in clinical trials and the analysis of high frequency outcome data and in involved in working groups at FDA on this topic. He received his PhD in Biostatistics from the University of Pittsburgh an his bachelor’s in physics from Cornell University.