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Negotiated control between the manual and visual systems for visually guided hand reaching movements.
K Han Kim, R Brent Gillespie, Bernard J Martin1
1Department of Industrial and Operations Engineering, The University of Michigan, Address: 1205 Beal Avenue, Ann Arbor, MI 48109-2117, USA. martinbj@umich.edu.
Journal of Neuroengineering and Rehabilitation
|June 13, 2014
Summary
Human movement control involves negotiating shared resources between gaze and hand actions. Redundancy in movement allows for balancing conflicting demands without compromising goals, improving prediction accuracy.
Area of Science:
- Biomechanics
- Neuroscience
- Robotics
Background:
- Controlling reaching movements for tasks like driving or using interfaces requires coordinating hand and gaze.
- Conflicting demands on shared body segments (e.g., torso) between visual (gaze) and manual (hand) systems necessitate negotiation strategies.
- Movement system redundancy (multiple possible configurations) may enable resolving conflicting demands without sacrificing primary goals.
Purpose of the Study:
- To model how simultaneous control of manual reach and gaze is achieved during seated reaching movements.
- To investigate if a negotiation strategy, utilizing movement redundancy, can resolve competing demands for shared resources.
- To evaluate the accuracy of a model incorporating negotiation compared to models with only manual or visual control.
Main Methods:
- Simulated simultaneous manual reach and gaze control using inverse kinematics.
- Introduced a 'negotiation function' to model the balancing of independent goals for shared resources like torso movement.
- Compared model predictions of joint trajectories with recorded movements from ten participants, assessing accuracy using root-mean-square errors (RMSE).
Main Results:
- Including the negotiation function improved prediction accuracy, reducing RMSE by 16% for manual control and 30% for visual control.
- The negotiated control system's RMSE tended to decrease as torso movement amplitude increased.
- The model demonstrated that redundancy allows for resolving competing demands without compromising movement goals.
Conclusions:
- The developed model explains how multiple systems cooperate in goal-directed human movement when utilizing shared resources.
- Resource allocation can be managed through a negotiation process that leverages redundancy and multiple solution possibilities.
- This negotiation strategy is crucial for efficient and goal-achieving human motor control.
