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Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans
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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.

Journal of Motor Behavior
|August 17, 2018
PubMed
Summary
This summary is machine-generated.

Grasping objects with limited finger space takes longer. Movement time depends on reach distance and finger space, modeled using a modified Fitts

Keywords:
graspingmodels of movementobstacle avoidanceprehensionreaching

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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.