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Human motor adaptation in whole body motion

View Article: PubMed Central - PubMed

ABSTRACT

The main role of the sensorimotor system of an organism is to increase the survival of the species. Therefore, to understand the adaptation and optimality mechanisms of motor control, it is necessary to study the sensorimotor system in terms of ecological fitness. We designed an experimental paradigm that exposed sensorimotor system to risk of injury. We studied human subjects performing uncon- strained squat-to-stand movements that were systematically subjected to non-trivial perturbation. We found that subjects adapted by actively compensating the perturbations, converging to movements that were different from their normal unperturbed squat-to-stand movements. Furthermore, the adapted movements had clear intrinsic inter-subject differences which could be explained by different adapta- tion strategies employed by the subjects. These results suggest that classical optimality measures of physical energy and task satisfaction should be seen as part of a hierarchical organization of optimality with safety being at the highest level. Therefore, in addition to physical energy and task fulfillment, the risk of injury and other possible costs such as neural computational overhead have to be considered when analyzing human movement.

No MeSH data available.


Measures used to quantify motor control mechanisms.Trajectory area measure (TA) and predictive component measure (PC) in relation to the active motor control processes during the execution of the motion.
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f10: Measures used to quantify motor control mechanisms.Trajectory area measure (TA) and predictive component measure (PC) in relation to the active motor control processes during the execution of the motion.

Mentions: While the trajectory area is a measure that quantifies the overall motor control process including trajectory planning, feedforward mechanisms and feedback mechanisms; the predictive component measure excludes the feedback mechanism due to the fact that it quantifies the motion of COM before the feedback mechanism could alter the motion. Figure 10 shows the relation between the time of the motion, motor control processes and the measures used.


Human motor adaptation in whole body motion
Measures used to quantify motor control mechanisms.Trajectory area measure (TA) and predictive component measure (PC) in relation to the active motor control processes during the execution of the motion.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5016968&req=5

f10: Measures used to quantify motor control mechanisms.Trajectory area measure (TA) and predictive component measure (PC) in relation to the active motor control processes during the execution of the motion.
Mentions: While the trajectory area is a measure that quantifies the overall motor control process including trajectory planning, feedforward mechanisms and feedback mechanisms; the predictive component measure excludes the feedback mechanism due to the fact that it quantifies the motion of COM before the feedback mechanism could alter the motion. Figure 10 shows the relation between the time of the motion, motor control processes and the measures used.

View Article: PubMed Central - PubMed

ABSTRACT

The main role of the sensorimotor system of an organism is to increase the survival of the species. Therefore, to understand the adaptation and optimality mechanisms of motor control, it is necessary to study the sensorimotor system in terms of ecological fitness. We designed an experimental paradigm that exposed sensorimotor system to risk of injury. We studied human subjects performing uncon- strained squat-to-stand movements that were systematically subjected to non-trivial perturbation. We found that subjects adapted by actively compensating the perturbations, converging to movements that were different from their normal unperturbed squat-to-stand movements. Furthermore, the adapted movements had clear intrinsic inter-subject differences which could be explained by different adapta- tion strategies employed by the subjects. These results suggest that classical optimality measures of physical energy and task satisfaction should be seen as part of a hierarchical organization of optimality with safety being at the highest level. Therefore, in addition to physical energy and task fulfillment, the risk of injury and other possible costs such as neural computational overhead have to be considered when analyzing human movement.

No MeSH data available.