Statistics, Data Science, and the Future of Wearable Digital Health Technologies

Wearable digital health technologies (DHTs) include smartphones, wearable sensors, and activity monitors. These wearable DHTs now generate massive, high-frequency streams of physiological, behavioral, and environmental data. These data hold enormous promise for transforming medical research, clinical trials, and public health. However, harnessing the full potential of DHTs raises profound statistical and data science challenges. This session will bring together leaders in statistics and data science to highlight recent methodological advances and applications across the full landscape of wearable DHT modalities, including accelerometry, continuous glucose monitoring, hemodynamics during surgery, and mobile health interventions. In the first part, we will have five 10 min talks that will showcase analytic challenges and methodological solutions across five different DHT modalities. The second part of the session will be devoted to a moderated discussion on "big picture" issues: developing rigorous and generalizable methods, advancing reproducibility, and defining the role of statistics and data science in shaping the future of digital health technologies.