TY - JOUR
T1 - Comparing dynamics of fluency and inter-limb coordination in climbing activities using multi-scale Jensen–Shannon embedding and clustering
AU - Herault, Romain
AU - Orth, Dominic
AU - Seifert, Ludovic
AU - Boulanger, Jeremie
AU - Lee, John Aldo
PY - 2017/11
Y1 - 2017/11
N2 - This paper reports the results of two studies carried out in a controlled environment aiming to understand relationships between movement patterns of coordination that emerge during climbing and performance outcomes. It involves a recent method of nonlinear dimensionality reduction, multi-scale Jensen–Shannon neighbor embedding (Lee et al., 2015), which has been applied to recordings of movement sensors in order to visualize coordination patterns adapted by climbers. Initial clustering at the climb scale provides details linking behavioral patterns with climbing fluency/smoothness (i.e., the performance outcome). Further clustering on shorter time intervals, where individual actions within a climb are analyzed, enables more detailed exploratory data analysis of behavior. Results suggest that the nature of individual learning curves (the global, trial-to-trial performance) corresponded to certain behavioral patterns (the within trial motor behavior). We highlight and discuss three distinctive learning curves and their corresponding relationship to behavioral pattern emergence, namely: no improvement and a lack of new motor behavior emergence; sudden improvement and the emergence of new motor behaviors; and gradual improvement and a lack of new motor behavior emergence.
AB - This paper reports the results of two studies carried out in a controlled environment aiming to understand relationships between movement patterns of coordination that emerge during climbing and performance outcomes. It involves a recent method of nonlinear dimensionality reduction, multi-scale Jensen–Shannon neighbor embedding (Lee et al., 2015), which has been applied to recordings of movement sensors in order to visualize coordination patterns adapted by climbers. Initial clustering at the climb scale provides details linking behavioral patterns with climbing fluency/smoothness (i.e., the performance outcome). Further clustering on shorter time intervals, where individual actions within a climb are analyzed, enables more detailed exploratory data analysis of behavior. Results suggest that the nature of individual learning curves (the global, trial-to-trial performance) corresponded to certain behavioral patterns (the within trial motor behavior). We highlight and discuss three distinctive learning curves and their corresponding relationship to behavioral pattern emergence, namely: no improvement and a lack of new motor behavior emergence; sudden improvement and the emergence of new motor behaviors; and gradual improvement and a lack of new motor behavior emergence.
KW - Climbing patterns dynamics
KW - Climbing skills profile
KW - Non-linear dimension reduction
KW - Performance management
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U2 - 10.1007/s10618-017-0522-1
DO - 10.1007/s10618-017-0522-1
M3 - Article
AN - SCOPUS:85021086910
SN - 1384-5810
VL - 31
SP - 1758
EP - 1792
JO - Data Mining and Knowledge Discovery
JF - Data Mining and Knowledge Discovery
IS - 6
ER -