ArticleScientific reports2018
On the coordination of highly dynamic human movements: an extension of the Uncontrolled Manifold approach applied to precision jump in parkour.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Trial
- Imposed versus self-chosen organization during exercise: comparison of two modalities involving randomness, on mental and physical responses.European journal of applied physiology · 2026Article
- Interpretable prediction of knee joint loading during tennis serves based on GNN-GRU model and layer-wise relevance propagation.Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine · 2025Article
- Leveraging graph neural networks and gate recurrent units for accurate and transparent prediction of baseball pitching speed.Scientific reports · 2025Article
- Performance Level and Strike Type during Ground and Pound Determine Impact Characteristics and Net Force Variability.Sports (Basel, Switzerland) · 2022Article
- The kinectome: A comprehensive kinematic map of human motion in health and disease.Annals of the New York Academy of Sciences · 2022Article
- What Makes Parkour Unique? A Narrative Review Across Miscellaneous Academic Fields.Sports medicine (Auckland, N.Z.) · 2022Review
- Influence of Controlled Stomatognathic Motor Activity on Sway, Control and Stability of the Center of Mass During Dynamic Steady-State Balance-An Uncontrolled Manifold Analysis.Frontiers in human neuroscience · 2022Article
- Segmental contribution to whole-body angular momentum during stepping in healthy young and old adults.Scientific reports · 2021Article
- Inverse optimal control with time-varying objectives: application to human jumping movement analysis.Scientific reports · 2020Article
- Theory of Cooperative-Competitive Intelligence: Principles, Research Directions, and Applications.Frontiers in psychology · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
The human body generally has more degrees of freedom than necessary for generating a given movement. According to the motor abundance principle, this redundancy is beneficial as it provides the central nervous system with flexibility and robustness for the generation of movements. Under the hypothesis of the Uncontrolled Manifold, the additional degrees of freedom are used to produce motor solutions by reducing the variability that affects the motion performance across repetitions. In this paper, we present a general mathematical framework derived from robotics to formulate kinematic and dynamic tasks in human movement. On this basis, an extension of the Uncontrolled Manifold approach is introduced to deal with dynamic movements. This extension allows us to present a complex experimental application of the proposed framework to highly dynamic task variables in parkour movements. This experiment involves dynamic tasks expressed in terms of linear and angular momenta. The results show that the central nervous system is able to coordinate such skilled tasks which appear to be preferentially controlled and hierarchically organized. The proposed extension is promising for the study of motion generation in anthropomorphic systems and provides a formal description to investigate kinematics and dynamics tasks in human motions.
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