Haptic human–human interaction does not improve individual visuomotor adaptation

Abstract

Haptic interaction between two humans, for example, a physiotherapist assisting a patient regaining the ability to grasp a cup, likely facilitates motor skill acquisition. Haptic human–human interaction has been shown to enhance individual performance improvement in a tracking task with a visuomotor rotation perturbation. These results are remarkable given that haptically assisting or guiding an individual rarely benefits their individual improvement when the assistance is removed. We, therefore, replicated a study that reported that haptic interaction between humans was beneficial for individual improvement for tracking a target in a visuomotor rotation perturbation. In addition, we tested the effect of more interaction time and a stronger haptic coupling between the partners on individual improvement in the same task. We found no benefits of haptic interaction on individual improvement compared to individuals who practised the task alone, independent of interaction time or interaction strength.

Human-machine-human interaction in motor control and rehabilitation: a review

“…Twelve studies showed the effects of different interaction types or interaction characteristics [ 2 , 15 – 19 , 28 , 29 , 36 – 38 , 40 ]. Five out of the twelve studies analyze the effects of the interaction type [ 17 , 19 , 36 , 38 , 40 ], six study the characteristics of physical interaction (i.e., properties of the haptic environment) [ 2 , 15 , 16 , 28 , 29 , 37 ], and one studies the characteristics of non-physical interaction (e.g., auditory vs audio-visual) [ 18 ]. Details of these studies and the summary of their results can be found in Additional file 2 : Tables S2 and S3.…”

“…Eleven studies investigated the effect of dyadic interaction in planar (2D) arm tracking tasks [ 2 , 4 , 6 – 8 , 12 , 15 , 17 , 28 , 36 , 37 ]. These studies were based on moving a cursor to a moving [ 2 , 4 , 7 , 12 , 15 , 37 ] or a stationary [ 6 , 17 , 28 ] target, following a path with a cursor [ 8 ], and maneuvering a virtual object on a confined path while trying to prevent collision with the environment [ 36 ]. Hand-held end-effector-type manipulators or haptic devices were used as input devices for moving the cursors or virtual objects.…”

“…Haptic virtual elements were implemented in task space between the connection points of each user with the robot [ 2 , 4 , 6 – 8 , 12 , 16 , 17 , 19 , 28 , 29 , 36 , 37 , 39 , 40 ] or at the joint level between the joints of users [ 15 ]. While some studies used commercial products and their built-in controllers [ 12 , 17 , 19 , 28 , 36 , 39 , 40 ], others used their own custom robotic devices and controllers [ 2 , 6 – 8 , 15 , 16 , 29 , 38 ].…”

“…In static target-reaching tasks, completion time (i.e., the time spent to reach the target) was a typical metric [ 17 , 28 ]. In tasks involving tracking a trajectory, the root-mean-squared or mean error between the actual trajectory and the target trajectory was typically measured [ 2 , 4 , 7 , 11 , 12 , 15 , 17 , 37 ].…”

“…For tasks that allow one or more people, task performance difference between a specific interaction condition and solo mode was calculated as the difference between the individual performance during interaction and the succeeding solo performance without any interaction [ 2 , 37 ]. For tasks that require multiple people, average dyadic performances of different interaction conditions were compared [ 16 , 17 ].…”