Standardizing Analytic Methods and Reporting in Activity Monitor Validation Studies

Med Sci Sports Exerc. 2019 Aug;51(8):1767-1780. doi: 10.1249/MSS.0000000000001966.

Abstract

Introduction: A lack of standardization with accelerometry-based monitors has made it hard to advance applications for both research and practice. Resolving these challenges is essential for developing methods for consistent, agnostic reporting of physical activity outcomes from wearable monitors in clinical applications.

Methods: This article reviewed the literature on the methods used to evaluate the validity of contemporary consumer activity monitors. A rationale for focusing on energy expenditure as a key outcome measure in validation studies was provided followed by a summary of the strengths and limitations of different analytical methods. The primary review included 23 recent validation studies that collectively reported energy expenditure estimates from 58 monitors relative to values from appropriate criterion measures.

Results: The majority of studies reported weak indicators such as correlation coefficients (87%), but only half (52%) reported the recommended summary statistic of mean absolute percent error needed to evaluate actual individual error. Fewer used appropriate tests of agreement such as equivalence testing (22%).

Conclusions: The use of inappropriate analytic methods and incomplete reporting of outcomes is a major limitation for systematically advancing research with both research grade and consumer-grade activity monitors. Guidelines are provided to standardize analytic methods and reporting in these types of studies to enhance the utility of the devices for clinical mHealth applications.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Accelerometry / instrumentation*
  • Accelerometry / standards*
  • Calibration
  • Data Interpretation, Statistical
  • Energy Metabolism
  • Exercise / physiology
  • Fitness Trackers / standards*
  • Health Behavior / physiology
  • Humans
  • Research Design / statistics & numerical data
  • Validation Studies as Topic