Research on Accelerometry-based Activity Monitors

Overview

One of the main focuses of our lab is to improve the accuracy, feasibility and utility of different types of accelerometry-based activity monitors. We have conducted research with most of the commonly used activity monitors that are available and have contributed to research guidelines for effective collection, processing and interpretation of data from these monitors.

Research with Sensewear

The SenseWear armband monitor utilizes multiple heat detecting sensors in addition to a tri-axial accelerometer to assess physical activity, which considerably enhances its accuracy in comparison to other commonly used monitors. We conducted foundational research with the Sensewear and documented the advantages of this technology over other monitors using the doubly-labelled method as well as with portable indirect calorimetry methods.  The Sensewear became accepted as perhaps the most valid research grade tool. While it is no longer commercially available, our lab still uses it in studies as a de-facto "alloyed standard" for comparisons with other monitors and assessments.

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 8 different 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 (See Hibbing et al. 2021 or the separate tab on FLASH access).    

Published Research 

  1. Hibbing PR, Lamoureux NR, Matthews CE, & Welk GJ. (in Press) Protocol and data description: The free-living activity study for health (FLASH). Journal for the Measurement of Physical Behaviour.
  2. Welk, G. J., Beyler, N. K., Kim, Y., & Matthews, C. E. (2017). Calibration of Self-Report Measures of Physical Activity and Sedentary Behavior. Medicine and science in sports and exercise.
  3. Ellingson, L. D., Hibbing, P. R., Kim, Y., Frey-Law, L. A., Saint-Maurice, P. F., & Welk, G. J. (2017). Lab-based validation of different data processing methods for wrist-worn ActiGraph accelerometers in young adults. Physiological Measurement, 38(6), 1045.
  4. Kim, Y., Hibbing, P., Saint-Maurice, P. F., Ellingson, L. D., Hennessy, E., Wolff-Hughes, D. L., & Welk, G. J. (2017). Surveillance of youth physical activity and sedentary behavior with wrist accelerometry. American Journal of Preventive Medicine, 52(6), 872-879.
  5. Ellingson, L. D., Schwabacher, I. J., Kim, Y., Welk, G. J., & Cook, D. B. (2016). Validity of an Integrative Method for Processing Physical Activity Data. Medicine and Science in Sports and Exercise, 48(8):1629-38.
  6. Hibbing, P. R., Kim, Y., Saint-Maurice, P. F., & Welk, G. J. (2016). Impact of activity outcome and measurement instrument on estimates of youth compliance with physical activity guidelines: a cross-sectional study. BMC Public Health, 16(1), 1.
  7. Tucker, J. M., Welk, G. J., Beyler, N. K., & Kim, Y. (2016). Associations Between Physical Activity and Metabolic Syndrome: Comparison Between Self-Report and Accelerometry. American Journal of Health Promotion, 30(3):155-62.
  8. Lee, J. M., Kim, Y., Bai, Y., Gaesser, G. A., & Welk, G. J. (2016). Validation of the SenseWear Mini Armband in Children during Semi-Structure Activity Settings. Journal of Science and Medicine in Sport, 19(1):41-5. PMID: 25459233
  9. Kim, Y., Welk, G. J., Braun, S. I., & Kang, M. (2015). Extracting objective estimates of sedentary behavior from accelerometer data: measurement considerations for surveillance and research applications. PloS one, 10(2), e0118078.
  10. Kim, Y., & Welk, G. J. (2015). Criterion Validity of Competing Accelerometry-based Activity Monitoring Devices. Medicine and Science in Sports and Exercise. 47(11):2456-63.
  11. Laurson, K. R., Welk, G. J., & Eisenmann, J. C. (2015). Estimating physical activity in children: impact of pedometer wear time and metric. Journal of Physical Activity & Health, 12(1), 124-131.
  12. Kim, Y., Crouter, S. E., Lee, J. M., Dixon, P. M., Gaesser, G. A., & Welk, G. J. (2014). Comparisons of prediction equations for estimating energy expenditure in youth. Journal of Science and Medicine in Sport. doi: 10.1016/j.jsams.2014.10.002. PMID: 25459235
  13. Calabro, M. A., Kim, Y., Franke, W. D., Stewart, J. M., & Welk, G. J. (2014). Objective and subjective measurement of energy expenditure in older adults: a doubly labeled water study. European Journal of Clinical Nutrition. doi:10.1038/ejcn.2014.241 PMID: 25351651
  14. Calabró, M. A., Lee, J. M., Saint-Maurice, P. F., Yoo, H., & Welk, G. J. (2014). Validity of physical activity monitors for assessing lower intensity activity in adults. International Journal of Behavioral Nutrition and Physical Activity, 11(1), 119. PMID: 25260625
  15. Calabro, M.A., Stewart, J.M., Welk, G.J. (2013). Validation of pattern-recognition monitors in children using doubly labeled water. Medicine and Science in Sports and Exercise. 45(7): 1313-1322. PMID: 23299766
  16. Smith KM, Lanningham-Foster LM, Welk GJ, Campbell CG. (2012). Validity of the SenseWear® Armband to predict energy expenditure in pregnant women. Medicine and Science in Sports and Exercise. 2012 Oct;44(10):2001-8. PMID: 22617395
  17. Welk, G.J., McClain, J., & Ainsworth, B.E. (2012). Protocols for evaluating equivalency of accelerometry-based activity monitors. Medicine and Science in Sports and Exercise. 44: S39-49. PMID: 22157773.
  18. Tucker J.M., Welk, G.J. & Beyler, N.K. (2011). Physical activity in U.S.: adults compliance with the Physical Activity Guidelines for Americans. American Journal of Preventive Medicine. 40(4):454-61. PMID:  21406280.
  19. Harrington, D.M., Welk, G.J. & Donnelly, A.E. (2011). Validation of MET estimates and step measurement using the ActivPAL physical activity logger. Journal of Sports Science. 29(6):627-33. PMID: 21360402
  20. Rowe, D. A., Welk, G. J., Heil, D. P., Mahar, M. T., Kemble, C. D., Calabro, M. A. et al. (2011). Stride rate recommendations for moderate-intensity walking. Medicine and Science in Sports and Exercise. 43, 312-318. PMID: 20543754
  21. Johannsen, D.L., Calabro, M.A., Stewart, J., Franke, W., Rood, J.C. and Welk, G.J. (2010). Accuracy of armband monitors for measuring daily energy expenditure in healthy adults. Medicine and Science in Sports and Exercise. Vol. 42, No. 11, pp. 2134-2140, PMID: 20386334
  22. Calabro, M.A., Welk, G.J., Eisenmann. (2009). Validation of the Sensewear Pro armband monitor algorithms in children. Medicine and Science in Sports and Exercise. Sep;41(9):1714-20.PMID: 19657300
  23. Welk, G.J., Eisenmann, J.C., Trost, S., Schaben, J.W., Dale, D.D. (2007) Calibration of the Biotrainer Pro Activity Monitor for Youth using Receiver Operator Characteristic (ROC) Curves. Pediatric Exercise Science, 19, 145-158. PMID: 17603138
  24. Welk, G.J., McClain, J., Eisenmann, J.C., Wickel, E.E., Beier, S. & Flakol, P. (2007). Field Validation of the MTI and BodyMedia monitors usingthe IDEEA monitor. Obesity, 15, 918-928. PMID: 17426327
Click here for ISU news story on monitors