The Intensity Inequality Index for Physical Activity: A New Metric for Integrative Analysis of Movement

Background : Wearable sensors recording acceleration provide a powerful tool for analysis of physical activity (PA). Continuous, high-rate data acquisition over extended periods gives highly resolved measurement of movement intensity. While increased complexity of PA analytics allows for deeper insight, it brings a challenge to statistical testing, where commonly used approaches require a single defining metric for PA per participant. Methods : We adapt an econometric measure to obtain a statistical test metric for movement intensity—the intensity inequality index , . This is a “Gini coefficient for movement” that quantifies the inequality in distribution of time spent across a range of activity intensity values. The metric is calculated using a graphical method on plots of cumulative time versus cumulative intensity level. Hypothesis testing of is performed on 24-hour activity traces of 58 children, aged 7–11 years, to assess statistical differences in PA between typically developing children and those suspected of having developmental coordination disorder. Results: The test metric provided high statistical confidence with low sample numbers: P < .05 for n ≥ 30. When differentiating between groups, halved the sample size required for a statistical power of 80% at α = .05, in comparison to the alternative metrics of intensity gradient or log ratio of minutes at low and moderate to high intensity. Conclusions: The inequality index provides a metric that is based on the accumulated time-counts across an activity intensity distribution. This integrative description of the distribution makes it a powerful statistical metric for PA.