Experimental Evaluation of a Mixed Controller That Amplifies Spatial Errors and Reduces Timing Errors

Abstract

Research on motor learning suggests that training with haptic guidance enhances learning of the timing components of motor tasks, whereas error amplification is better for learning the spatial components. We present a novel mixed guidance controller that combines haptic guidance and error amplification to simultaneously promote learning of the timing and spatial components of complex motor tasks. The controller is realized using a force field around the desired position. This force field has a stable manifold tangential to the trajectory that guides subjects in velocity-related aspects. The force field has an unstable manifold perpendicular to the trajectory, which amplifies the perpendicular (spatial) error. We also designed a controller that applies randomly varying, unpredictable disturbing forces to enhance the subjects' active participation by pushing them away from their "comfort zone." We conducted an experiment with thirty-two healthy subjects to evaluate the impact of four different training strategies on motor skill learning and selfreported motivation: (i) No haptics, (ii) mixed guidance, (iii) perpendicular error amplification and tangential haptic guidance provided in sequential order, and (iv) randomly varying disturbing forces. Subjects trained two motor tasks using ARMin IV, a robotic exoskeleton for upper limb rehabilitation: follow circles with an ellipsoidal speed profile, and move along a 3D line following a complex speed profile. Mixed guidance showed no detectable learning advantages over the other groups. Results suggest that the effectiveness of the training strategies depends on the subjects' initial skill level. Mixed guidance seemed to benefit subjects who performed the circle task with smaller errors during baseline (i.e., initially more skilled subjects), while training with no haptics was more beneficial for subjects who created larger errors (i.e., less skilled subjects). Therefore, perhaps the high functional difficulty of the tasks limited the potential benefit of mixed guidance. Adding random disturbing forces during training reduced the learning effect size compared to no haptics. The unanticipated forces also decreased the subjects' feelings of competence while did not increase their effort and interest. Further studies with mildly affected neurologically patients employing easier tasks need to be performed in order to evaluate the applicability of our approaches in rehabilitation.

Haptic Error Modulation Outperforms Visual Error Amplification When Learning a Modified Gait Pattern

“…A decrease of perceived competence during training with haptic disturbance was also observed in a previous study (Marchal-Crespo et al, 2017a). Adding randomly varying disturbance torques during training complex 3D arm movements hampered learning and resulted in a decrease of feeling of competence when the haptic disturbance was applied.…”

“…Nevertheless, in a recent experiment we found that the most effective robotic training condition depended on the characteristics of the task to be learned. We employed a similar haptic error amplification strategy in a 7 DoF robotic exoskeleton for upper limb rehabilitation (Marchal-Crespo et al, 2017a). In an experiment with thirty healthy participants, we evaluated the effectiveness of three error-modulating training strategies -no guidance, haptic error amplification and haptic guidance- on self-reported motivation and learning of continuous and discrete tasks.…”

“…Here, only a brief summary is given for completeness. Similar haptic disturbance (Marchal-Crespo et al, 2017a) and error modulating controllers (Marchal-Crespo et al, 2017c) were developed to perform motor learning experiments with ARMin, a 7 degree-of-freedom (DoF) robotic exoskeleton for upper limb rehabilitation. The haptic controllers employed in the present experiment, however, were developed in joint coordinates and were not based on the end-effector trajectories.…”

Effect of immersive visualization technologies on cognitive load, motivation, usability, and embodiment

“…Questionnaires measuring the self-reported cognitive load, such as the NASA Task Load Index might be unsuited in a brain-injured population as they might lack the full awareness of their cognitive limitation (Cyr et al 2009). As stroke patients might suffer from sensorimotor deficits that prevent them from performing unsupported reaching movements, we need to adapt our experimental setup to interface the developed VR reaching task with an upper-arm assisting rehabilitation device (e.g., Marchal-Crespo et al 2017;Özen et al 2020). A study with patients might also result in higher variance in our measurements due to the wide range of potential motor and cognitive disabilities.…”

Haptic Training: Which Types Facilitate (re)Learning of Which Motor Task and for Whom? Answers by a Review

“…A second limitation of Williams and Carnahan [15] work, already stated by the authors, is that the proposed haptic classification does not capture how the haptic guiding forces can be provided without interfering with the haptic rendering of task-related elements, e.g., task dynamics [51]. Providing haptic guiding forces simultaneously to haptic rendering may create confusion [52], [53] and hamper motor learning [50], [54]. An initial body of research studied how haptic assisting forces can be separated from inherent task forces spatiallye.g., using different channels (end-effectors) -, or temporallyi.e., allocating time between the provision of training and task forces [53].…”