Related Experiment Video
Updated: May 17, 2026
15:00
The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors
Published on: May 2, 2021
Stroke survivors control the temporal structure of variability during reaching in dynamic environments
Mukul Mukherjee1, Panagiotis Koutakis, Ka-Chun Siu
1Nebraska Biomechanics Core Facility, University of Nebraska at Omaha, Omaha, NE 68182-0216, USA.
Annals of Biomedical Engineering
|October 16, 2012
Summary
Stroke survivors learned to control reaching movements in dynamic environments, making them less repeatable. This learning focused on movement dynamics, not just variability, and was not enhanced by augmented feedback.
Area of Science:
- Neuroscience
- Motor Control
- Rehabilitation Science
Background:
- Force control learning reduces movement variability (SD) and alters temporal structure (ApEn).
- Movement variability control in stroke survivors within dynamic environments remains unexplored.
- The impact of augmented feedback on this control in stroke is unknown.
Purpose of the Study:
- To investigate movement variability control in chronic stroke survivors during reaching in dynamic environments.
- To determine if augmented visual feedback influences variability control and retention.
- To analyze how learning affects movement dynamics and adaptability post-stroke.
Main Methods:
- Chronic stroke survivors were randomly assigned to control (true feedback) or experimental (augmented visual feedback) groups.
- Participants learned reaching movements in a dynamically changing environment.
- Hand movement variability was quantified using standard deviation (SD) and approximate entropy (ApEn).
Main Results:
- A significant increase in approximate entropy (ApEn) was observed, indicating less repeatable movement patterns, with significant retention.
- A decrease in standard deviation (SD) was not retained after one week.
- Augmented visual feedback did not significantly affect the observed changes in movement variability or retention.
Conclusions:
- Stroke survivors can learn to control movement variability in dynamic environments, enhancing flexibility.
- Learning primarily involves controlling nonlinear dynamics, not just reducing overall variability.
- Task- and environment-specific learning suggests limited transfer effects for variability control after stroke.
