Physical activity (PA) in daily life could be evaluated by accelerometer. Multiple algorithms have been validated to classify activity counts along several time intervals (epoch length), and with several set of cut-points. For children, three algorithms are the most frequently used by researchers in order to define the time spent in sedentary (SED) and in moderate to vigorous physical activity (MVPA). The aim of this study was to determine the more appropriate accelerometer based classification algorithms for children with CP.

Participants were children and adolescents with CP (n=20, age 10–18 y), with Gross Motor Function Classification System (GMFCS) levels I–III. Daily PA was measured with an Actigraph GT3X accelerometer over 7 consecutive days in free-living environment. Data collection protocols were the same for all children. The results of three different algorithms, Puyau (2002), Freedson (2005), Evenson (2008), were compared by ANOVA followed by multiple t-test after Bonferroni's corrections: The results were also compared to qualitative data from the written diaries of daily PA completed by children and parents.

There is a significant difference between the results of physical activity, depending on the algorithm used (F=16.88, P=1.53×10⁻¹⁵). The average time spent in MVPA is 2.6 times higher with Freedson's algorithm than with Puyau's algorithm, whereas the Puyau and Evenson algorithms are comparable. The qualitative informations collected with the daily diary indicated that Freedson's algorithm over-estimated PA among children with CP.

The harmonisation of the methods regarding accelerometer's data collection and processing is necessary. Especially to compare the level of PA of a specific patient to the World Health Organization recommendations. For children with CP, the more appropriate algorithm is based on Evenson's cut-points.