Jess Selinger of Queens University presents her research study using big data from wearables and in-lab energetics data to explain running speeds in the wild. She found that free-living runners, most often out for a jog and not a race, prefer a particular running speed largely independent of run distance. Moreover, these preferred speeds are remarkably consistent with the objective of minimizing energy expenditure. These findings offer insight into the biological objectives that shape human running preferences in the real world—an important consideration when examining human ecology or creating training strategies to improve performance and prevent injury.

This webinar is offered jointly with the Restore Center (https://restore.stanford.edu/), an NIH-funded Medical Rehabilitation Research Resource Network Center at Stanford University.

Watch part 2 of this webinar – best practices for analyzing large scale wearable data:    • Webinar: Energetics and Big Data Appr...  

Learn more:
Read the associated publication:
https://www.cell.com/current-biology/...
Read about best practices for analyzing wearable data:
https://www.nature.com/articles/s4174...