Psychophysical Evaluation of Human Motor Adaptation and Skill Retention in Rhythmic Tasks

Virtual fixtures, shared controllers and other haptic guidance schemes have been supplement with virtual motor tasks in order to improve performance and skill retention and to reduce training duration and user workload. In an error-reducing shared controller implemented in our lab, the performance of a manual task was influenced by participants’ ability to identify and then excite a virtual two-mass system at the natural frequency of the system. In a series of experiments, we explore if parameters of the dynamic system influence human perception as well as increase the rate of task performance.

We first determined a human’s ability to discriminate the natural frequency of the two-mass system by either actively exciting the system at its natural frequency or passively perceiving the interaction forces through the handle of a one-dof haptic device. We determined the influence of natural frequency (1, 2, 4 and 8 Hz), excitation mode (active and passive) and sensory modality (visual-, haptics- and visual+haptics). The natural frequency Weber fractions are in the 0.04 to 0.08 range. Next, we determined if changing the dynamic parameters of the two-mass system affected human’s adaptation to a rhythmic motor task. We trained our participants to excite the system at a nominal natural frequency. Then in a “catch trail” paradigm, we changed one or more system parameters of the system in a randomly selected trail. Our results showed that participants were able to identify and excite the system at the natural frequency when either magnitude or phase cues were shifted, although the performance was slightly better when both cues were changed simultaneously. Results also showed that changing either the magnitude or phase cues did not influence the adaptation to the nominal dynamic system. In the next phase, we will investigate the influence of parameters to rate of adaptation. Our goal is to determine if participants tends to converge faster to a new system dynamics by manipulation of magnitude and phase cue. This will lead us to a better shared controller and haptic guidance schemes for training of manual control tasks.

In collaboration with Dr. Volkan Potaglu, Sabanci University, Turkey.