WHAT is FLASH?

The Free Living Activity Study for Health (FLASH) is an ongoing study focused on understanding the agreement (or lack thereof) among different monitor-based studies. Participants wear different combinations of monitors over a 24 hour period and then complete a 24 hour recall to report the behaviors performed. Unique aspects of the study are the student-led data collection, the integration with the Act24 measure and the sharing of the data through GitHub. We have published the protocol and the open access process in a paper by Dr. Paul Hibbing (2021). Examples of applications of FLASH to advance research on activity assessment are provided in papers led Dr. Nick Lamoureux and Jimmy Duhamahoro. or the separate tab on FLASH access).  The current focus in FLASH is described below along with information on accessing the FLASH data.  

Published Research 

  1. Duhamahoro, J., Lamoureux, N. R., Hibbing, P. R., Taylor, M. A., & Welk, G. J. (2025). Comparative Validity of Two Thigh-Worn Activity Monitors in Free-Living Conditions. Journal for the Measurement of Physical Behaviour, 8(1).
  2. Lamoureux NR, Hibbing PR, Matthews CE, Welk GJ. (2022) Integration of report-based methods to enhance the interpretation of monitor-based research: Results from the FLASH Project, Journal for the Measurement of Physical Behavior. 5(1), 42-48.
  3. Hibbing PR, Lamoureux NR, Matthews CE, & Welk GJ. (2021 Protocol and data description: The free-living activity study for health (FLASH). Journal for the Measurement of Physical Behaviour, 1 (aop), 1-8.​

Current Focus in FLASH

The FLASH project provides a systematic way to study the relative agreement among different monitors and metrics across 24 hours under free-living conditions. Current interests focus on evaluating agreement between different research grade devices and different consumer smartwatches.

Open-Source Accelerometer Research Tools

Our lab supports open-source processing methods and will be posting regular updates on our data processing workflows online so they can be easily accessed and reused.
•     📦 We have developed an open-source raw data processing workflow "Universalaccel", an R package available on GitHub. This package allows researchers to process their own data using the same reproducible methods we apply in our lab.
•     📊 To help demonstrate practical applications, we also provide a Shiny app showcasing example analyses. You can explore interactive visualizations and workflows directly at Shiny App Link.
 
Together, these resources make it simple for collaborators and the broader research community to engage with our methods, adapt them to their own projects, and contribute to ongoing improvements.