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Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans
Published on: January 15, 2018
Reach/Grasp Times with Lateral Reach Obstructions.
Errol R Hoffmann1, Alan H S Chan1, Christy K Y Lam1
1a Department of Systems Engineering and Engineering Management , City University of Hong Kong , Kowloon Tong , Hong Kong.
Grasping objects with limited finger space takes longer. Movement time depends on reach distance and finger space, modeled using a modified Fitts
Area of Science:
- Human motor control
- Robotics
- Biomechanics
Background:
- Reaching and grasping tasks are fundamental to human interaction with the environment.
- Obstacles near a target object can constrain finger placement, affecting movement time.
- Understanding these constraints is crucial for designing assistive technologies and robotic systems.
Purpose of the Study:
- To model the time taken for reach and grasp movements when adjacent obstacles limit finger placement.
- To investigate the relationship between movement time, reach distance, and available finger space.
- To determine if movement is visually controlled and how obstacle proximity influences this control.
Main Methods:
- Development of mathematical models for reach and grasp phases, incorporating obstacle location.
- Analysis of movement data to assess the influence of reach distance and finger space.
- Comparison of movement patterns with established models like Fitts' law under varying obstacle conditions.
Main Results:
- Movement time is dependent on both reach distance and the space available for finger placement.
- Visually-controlled movements are employed, particularly when obstacles are close to the target.
- A modified Fitts' law effectively models visually-controlled movements in the presence of nearby obstacles.
- Reach and grasp phases appear to be independent and linearly additive in terms of time.
Conclusions:
- The time required for reach/grasp tasks is predictable based on reach distance and finger placement constraints.
- Obstacle proximity significantly influences motor control strategies, favoring visual guidance.
- The findings provide a quantitative basis for understanding and predicting human reach/grasp performance in constrained environments.
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