Grip Force Dynamics During Exoskeleton-Assisted and Virtual Grasping

Area of Science:

• Neuroscience
• Biomechanics
• Rehabilitation Engineering

Background:

• Grip force dynamics are crucial for assessing sensorimotor control and neurological conditions.
• Grip force profiles can be utilized for assessment and bio-feedback training in neurorehabilitation.
• Advanced neurorehabilitation techniques like exoskeleton-assisted grasping and virtual reality may alter sensorimotor control and grip force characteristics compared to traditional methods.

Purpose of the Study:

• To investigate grip force profile changes during exoskeleton-assisted grasping.
• To examine grip force dynamics when grasping virtual objects with varying weights.
• To assess the adaptability of sensorimotor control in advanced neurorehabilitation contexts.

Main Methods:

• Feasibility study involving six healthy participants.
• Analysis of grip force profiles during grasping tasks with and without a hand exoskeleton.
• Evaluation of grip force adaptation to virtual object weights.

Main Results:

• A lightweight, compliant hand exoskeleton assisted grasping without altering core grip force dynamics.
• Participants rapidly adapted to unknown virtual weights, employing efficient grip forces.
• Predictive overshoot forces were generated, matching inertial forces of virtual objects.

Conclusions:

• Users of advanced neurorehabilitation methods adapt and utilize existing internal forward models for grasping.
• Insights into grip force dynamics can enhance the design and efficacy of neurorehabilitation tools like hand exoskeletons.
• Findings suggest improved usability and rehabilitative function for neurorehabilitation technologies.