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Updated: May 2, 2026

Efficiently Recording the Eye-Hand Coordination to Incoordination Spectrum
Published on: March 21, 2019
Effects of angular gain transformations between movement and visual feedback on coordination performance in unimanual
Martina Rieger1, Sandra Dietrich2, Wolfgang Prinz3
1Department of Psychology, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany ; Department for Medical Sciences and Management, Institute for Psychology, University for Health Sciences, Medical Informatics and Technology Hall in Tirol, Austria.
Angular gain transformations between movement and visual feedback significantly impact coordination performance. Performance is optimal with a gain of 1, with deviations leading to coordination errors and reduced awareness.
Area of Science:
- Human-computer interaction
- Motor control
- Cognitive psychology
Background:
- Tool use involves transformations between movements and environmental consequences.
- These transformations affect movement planning, execution, and overall performance.
- Understanding these transformations is crucial for designing effective human-machine interfaces.
Purpose of the Study:
- To investigate the impact of angular gain transformations on coordination performance.
- To determine how varying gain factors affect the relationship between movement and visual feedback.
- To assess the influence of transformation presence and magnitude on user awareness and performance.
Main Methods:
- Participants performed circling movements, coordinating visual feedback with a stimulus dot.
- Movement angle was multiplied by a gain factor (0.5-2) for visual feedback.
- Coordination performance and awareness of the transformation were measured across nine gain levels.
Main Results:
- Coordination performance was optimal at a gain of 1, with deviations causing feedback to lead or lag.
- Anchoring, or reduced movement variability, occurred when movement and feedback trajectories were closely aligned.
- Awareness of the angular gain transformation was dependent on the deviation of the gain from 1.
Conclusions:
- The magnitude and presence of angular gain transformations significantly influence performance in tasks with non-constant movement-to-feedback mappings.
- Even small deviations from a gain of 1 can lead to performance decrements.
- Designers of tools and machines should consider the potential for performance flaws due to angular gain transformations.
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