Fuzzy logic for characterizing the moderate intensity of physical activity in children

ObjectivesThe aim of this study was to better characterize the moderate intensity of PA among children by applying fuzzy logic as the most appropriate analytical approach. In this perspective, the 6-MWT was selected as a pertinent exercise modality, which covers as a whole, this intensity level.DesignMethodological study.MethodsFuzzy logic was applied to accelerometer output obtained on 46 children aged 9–11 years. A fuzzy subset A was defined from the reference set E   using a membership function (degree of truth). To adequately tap the moderate PA, a core of X¯±σ and a support of X¯±2σ (with X¯ the mean, and σ the standard deviation of the distribution) were selected.ResultsThe walking speed during the exercise averaged 6.1 ± 0.6 km h−1 and the mean HR was 135 ± 14 bpm. The movement count (419 ± 127 to 433 ± 148 counts) exhibited no significant changes during the test. A value of 260 counts per 5-s (i.e., 3120 cpm) had equally 50% of degree of truth to encompass both “light” and “moderate” intensities of PA. Results suggest that the cut-point of >2296 cpm covers a low PA at 100% and a moderate PA at 0%.ConclusionsFuzzy logic provides a robust basis to processing accelerometer data, and brings a reliable solution to the concern about the in-between of PA intensities. Its application to calibration studies should not support the use of a cut-point of about 2000 cpm in children, and linguistic variables should now be preferred to numbered data in defining PA intensities.