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Movement Systems as Dynamical Systems

Overview of attention for article published in Sports Medicine, January 2003
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
13 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
331 Dimensions

Readers on

mendeley
282 Mendeley
Title
Movement Systems as Dynamical Systems
Published in
Sports Medicine, January 2003
DOI 10.2165/00007256-200333040-00001
Pubmed ID
Authors

Keith Davids, Paul Glazier, Duarte Ara??jo, Roger Bartlett

Abstract

In recent years, concepts and tools from dynamical systems theory have been successfully applied to the study of movement systems, contradicting traditional views of variability as noise or error. From this perspective, it is apparent that variability in movement systems is omnipresent and unavoidable due to the distinct constraints that shape each individual's behaviour. In this position paper, it is argued that trial-to-trial movement variations within individuals and performance differences observed between individuals may be best interpreted as attempts to exploit the variability that is inherent within and between biological systems. That is, variability in movement systems helps individuals adapt to the unique constraints (personal, task and environmental) impinging on them across different timescales. We examine the implications of these ideas for sports medicine, by: (i) focusing on intra-individual variability in postural control to exemplify within-individual real-time adaptations to changing informational constraints in the performance environment; and (ii) interpreting recent evidence on the role of the angiotensin-converting enzyme gene as a genetic (developmental) constraint on individual differences in physical performance. The implementation of a dynamical systems theoretical interpretation of variability in movement systems signals a need to re-evaluate the ubiquitous influence of the traditional 'medical model' in interpreting motor behaviour and performance constrained by disease or injury to the movement system. Accordingly, there is a need to develop new tools for providing individualised plots of motor behaviour and performance as a function of key constraints. Coordination profiling is proposed as one such alternative approach for interpreting the variability and stability demonstrated by individuals as they attempt to construct functional, goal-directed patterns of motor behaviour during each unique performance. Finally, the relative contribution of genes and training to between-individual performance variation is highlighted, with the conclusion that dynamical systems theory provides an appropriate multidisciplinary theoretical framework to explain their interaction in supporting physical performance.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 282 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 3 1%
United Kingdom 3 1%
France 2 <1%
Germany 2 <1%
United States 2 <1%
Ireland 1 <1%
Korea, Republic of 1 <1%
Canada 1 <1%
Singapore 1 <1%
Other 2 <1%
Unknown 264 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 62 22%
Student > Master 52 18%
Researcher 26 9%
Student > Doctoral Student 21 7%
Student > Bachelor 21 7%
Other 73 26%
Unknown 27 10%
Readers by discipline Count As %
Sports and Recreations 124 44%
Medicine and Dentistry 28 10%
Nursing and Health Professions 18 6%
Psychology 11 4%
Engineering 11 4%
Other 44 16%
Unknown 46 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 July 2019.
All research outputs
#1,678,341
of 13,629,017 outputs
Outputs from Sports Medicine
#1,101
of 2,212 outputs
Outputs of similar age
#21,109
of 155,675 outputs
Outputs of similar age from Sports Medicine
#19
of 29 outputs
Altmetric has tracked 13,629,017 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,212 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 32.4. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 155,675 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.