title: Fuzzy logic for characterizing the moderate intensity of physical activity in children.
abstract: OBJECTIVE
  The 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.
  
  
  METHODS
  Methodological study.
  
  
  METHODS
  Fuzzy 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.
  
  
  RESULTS
  The walking speed during the exercise averaged 6.1±0.6kmh(-1) and the mean HR was 135±14bpm. 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., 3120cpm) had equally 50% of degree of truth to encompass both "light" and "moderate" intensities of PA. Results suggest that the cut-point of >2296cpm covers a low PA at 100% and a moderate PA at 0%.
  
  
  CONCLUSIONS
  Fuzzy 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 2000cpm in children, and linguistic variables should now be preferred to numbered data in defining PA intensities.
authors: EA 2694, Public Health: Epidemiology and Healthcare Quality, University of Lille, Lille, France; Department of Biomathematics of the Faculty of Biological and Pharmaceutical Sciences, University of Lille, Lille, France.
authors: Djamel
authors: D
authors: Zitouni
authors: EA 2694, Public Health: Epidemiology and Healthcare Quality, University of Lille, Lille, France; Faculty for Health Engineering and Management, University of Lille, Loos, France. Electronic address: benjamin.guinhouya@univ-lille2.fr.
authors: Benjamin C
authors: BC
authors: Guinhouya
mesh_terms: D061725:Accelerometry; D002648:Child; D005080:Exercise Test; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D008297:Male; D016138:Walking / Q000502:physiology*
keywords: Accelerometry; Cut-points conundrum; Equations; Pediatric; Zone of possible misclassification