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Journal Articles Behavior Research Methods Year : 2010

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.

Domains

Psychology

Dates and versions

hal-01440462 , version 1 (19-01-2017)

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Frédéric Dandurand, Thomas R. Shultz. Automatic detection and quantification of growth spurts. Behavior Research Methods, 2010, 42 (3), pp.809-823. ⟨10.3758/BRM.42.3.809⟩. ⟨hal-01440462⟩

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CNRS UNIV-AMU LPC
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