title: Automatic detection and quantification of growth spurts.
abstract: Growth phenomena are often nonlinear and may contain spurts, characterized by a local increase in the rate of growth. Because measurement error and noise may produce apparent spurts, it is important to identify systematic and reliable spurts. We describe a system, automatic maxima detection (AMD), for statistically identifying significant spurts and computing (1) point of maximal velocity, when the spurt was most intense; (2) start, when the spurt started; (3) amplitude, the intensity of the spurt; and (4) duration, the length of the spurt. We also introduce a software implementation of AMD in MATLAB. In growth of height data, AMD showed a reliable pubertal growth spurt for most children and a reliable prepubertal spurt for some children. In simulated growth of vocabulary, AMD showed a large global spurt and several minispurts. In real vocabulary growth, AMD showed a few spurts. Advantages of AMD include improvements in objectivity, automaticity, quantification, and comprehensiveness.
authors.affiliation: CNRS and Aix-Marseille University, Marseille, France. frederic.dandurand@gmail.com
authors.forename: Frédéric
authors.initials: F
authors.lastname: Dandurand
authors.forename: Thomas R
authors.initials: TR
authors.lastname: Shultz
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D001331:Automation; D001827:Body Height; D002648:Child; D002657:Child Development / Q000502:physiology*; D003625:Data Collection; D003627:Data Interpretation, Statistical; D005260:Female; D006128:Growth / Q000502:physiology*; D006801:Humans; D007804:Language Development; D008297:Male; D009010:Monte Carlo Method; D012727:Sex Characteristics; D014825:Vocabulary