Haptically Enhanced Motor Variability Shows Contrary Effects on Transfer of Learning

Master Thesis (2022)
Author(s)

W. Arink (TU Delft - Mechanical Engineering)

Contributor(s)

L. M. Marchal Crespo – Mentor (TU Delft - Human-Robot Interaction)

N.W.M. Beckers – Mentor (TU Delft - Human-Robot Interaction)

Faculty
Mechanical Engineering
Copyright
© 2022 Wouter Arink
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Wouter Arink
Graduation Date
04-04-2022
Awarding Institution
Delft University of Technology
Programme
Mechanical Engineering | BioMechanical Design
Faculty
Mechanical Engineering
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Abstract

In order to improve skill acquisition and neurorehabilitation, we need to improve our understanding of human motor learning. It has been shown that innate variability of movements made by an individual when performing a motor task (motor variability) might enhance skill acquisition. Augmenting motor variability could therefore be a promising method to enhance learning. However, current methods that enhance motor variability show divergent results and need to be better understood.
In a lab-based experiment with twenty healthy participants,
we studied the effect of a new method that haptically increases participants’ motor variability in learning a dynamic task, i.e., controlling a pendulum. This new method consisted of applying pseudo-random perturbation forces to the internal degree of freedom of the dynamic system (indirect haptic noise), instead of applying forces directly on the trainee’s hands as previously studied. The main task consisted of swinging a virtual pendulum to hit incoming targets with the pendulum ball. To assess generalization of learning we used two transfer tasks, which consisted of altered target positions or altered task dynamics (i.e., a pendulum with shorter rod length). We evaluated the effect of the new method
on learning by comparing performance gains after training to a control group who trained without perturbations. We found that the perturbations successfully increased participants’ motor variability during training. Although we observed no learning benefits of training with this indirect haptic noise for the trained
task compared to the control group, we observed divergent effects for transfer of learning. Participants that trained with indirect haptic noise seemed to benefit in transfer of learning to altered task dynamics but not in the task with altered target positions. Increasing motor variability by indirect haptic noise is promising for enhancing skill acquisition, specially in transfer of learning, and in tasks that incorporate complex dynamics. However, more research is needed to make indirect haptic noise a valuable tool for real life motor learning situations, e.g., in
robotic neurorehabilitation.

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