Progress in motor control : from neuroscience to patient outcomes /
"Movement patterns result from nonlinear interactions among several components (e.g., nervous, cardiovascular, endocrinal, and musculoskeletal) of an action-perception system, which interacts with the environment. To produce functional movement patterns, action-perception systems organize thems...
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| Other Authors: | , , , |
| Format: | eBook |
| Language: | English |
| Published: |
London, United Kingdom ; San Diego, CA :
Academic Press, an imprint of Elsevier,
[2024]
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | "Movement patterns result from nonlinear interactions among several components (e.g., nervous, cardiovascular, endocrinal, and musculoskeletal) of an action-perception system, which interacts with the environment. To produce functional movement patterns, action-perception systems organize themselves in numerous ways within an environment that changes continually. This self-organizing process allows movement patterns to adapt to organismic, environmental, and task constraints in multiple ways. As a result of self-organization, movements reflect the status of the many components involved in their genesis. Therefore, the time evolution of the movements' macrostructure can carry information about the interactions of their many microscopic components. Many studies have been conducted using nonlinear methods to investigate human behavior. These methods have the potential to unveil the movement pattern structure and capture a signature of the status of the action-perception system. Within this reasoning, we have shown that individuals exposed to stressful situations present a reduction in their ability to adapt to changes. This altered behavior indicates modifications of the available components of their biological systems, which may place the individual at risk of injury or performance reduction. Decreases in the system's ability to sustain proper movement patterns in response to perturbations may indicate that the individual is more susceptible to illness. On the other hand, the ability of the individual to recover from stressful situations, such as sleep deprivation or high-demand exercises, may be essential in injury prevention. Therefore, analyzing the time evolution of movement patterns may allow capturing the individual's status and reveal whether they are at risk of injury or have successfully recovered. This paper will demonstrate how entropy methods (sample entropy) can capture individuals' responses to perturbations and be used within the injury prevention or recovery detection framework" -- |
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| Physical Description: | 1 online resource (xvi, 396 pages) : illustrations |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 044323986X 9780443239861 |