The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process.
Multi-segmental movement patterns reflect juggling complexity and skill level / M. Zago, I. Pacifici, N. Lovecchio, M. Galli, P.A. Federolf, C. Sforza. - In: HUMAN MOVEMENT SCIENCE. - ISSN 0167-9457. - 54(2017 Aug 01), pp. 144-153.
|Titolo:||Multi-segmental movement patterns reflect juggling complexity and skill level|
ZAGO, MATTEO (Primo)
PACIFICI, ILARIA (Secondo)
SFORZA, CHIARELLA (Ultimo)
|Parole Chiave:||coordination; motor learning; principal movements; PCA|
|Settore Scientifico Disciplinare:||Settore BIO/16 - Anatomia Umana|
Settore M-EDF/02 - Metodi e Didattiche delle Attivita' Sportive
Settore ING-INF/06 - Bioingegneria Elettronica e Informatica
|Data di pubblicazione:||1-ago-2017|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/j.humov.2017.04.013|
|Appare nelle tipologie:||01 - Articolo su periodico|