Optimizing learning of a locomotor task: Amplifying errors as needed

Marchal–Crespo, Laura; López-Olóriz, Jorge; Jaeger, Lukas; Riener, Robert

doi:10.1109/embc.2014.6944823

Cited by 28 publications

(20 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, the unexpected limitation of the mixed guidance controller might originate from the fact that the tasks to be learned were too difficult (Marchal-Crespo et al, 2015a,b). This is in line with previous studies that showed that error amplification seemed to be particularly helpful for initially more skilled subjects (Milot et al, 2010;Marchal-Crespo et al, 2014a) and for specially simple tasks (Marchal-Crespo et al, 2014b). This can be explained by the Challenge Point Theory, which states that optimal learning is achieved when the difficulty of the task is appropriate for the individual subject's level of expertise (Guadagnoli and Lee, 2004).…”

Section: Discussionsupporting

confidence: 90%

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

et al. 2017

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionsupporting

confidence: 90%

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

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…This is also supported by the observation that random perturbations (and not just feedback related error augmenting forces) can facilitate performance improvement (Marchal-Crespo et al, 2014a) and motor learning of spatial movement characteristics (Lee and Choi, 2010). …”

Section: Discussionmentioning

confidence: 74%

“…In addition, if we look outside the realm of upper-extremity movements, studies have also shown some benefits of error augmentation in comparison to no robot assistance for a simple locomotor task, particularly for initially less skilled learners (Marchal-Crespo et al, 2014b). However, for a more complex locomotor task, it was found that error augmentation reduced errors from baseline immediately after training for initially more skilled learners while random noise-like perturbation reduced errors for both skilled and unskilled participants (Marchal-Crespo et al, 2014a). …”

Section: Introductionmentioning

confidence: 99%

It Pays to Go Off-Track: Practicing with Error-Augmenting Haptic Feedback Facilitates Learning of a Curve-Tracing Task

2016

View full text Add to dashboard Cite

Researchers in the domain of haptic training are now entering the long-standing debate regarding whether or not it is best to learn a skill by experiencing errors. Haptic training paradigms provide fertile ground for exploring how various theories about feedback, errors and physical guidance intersect during motor learning. Our objective was to determine how error minimizing, error augmenting and no haptic feedback while learning a self-paced curve-tracing task impact performance on delayed (1 day) retention and transfer tests, which indicate learning. We assessed performance using movement time and tracing error to calculate a measure of overall performance – the speed accuracy cost function. Our results showed that despite exhibiting the worst performance during skill acquisition, the error augmentation group had significantly better accuracy (but not overall performance) than the error minimization group on delayed retention and transfer tests. The control group’s performance fell between that of the two experimental groups but was not significantly different from either on the delayed retention test. We propose that the nature of the task (requiring online feedback to guide performance) coupled with the error augmentation group’s frequent off-target experience and rich experience of error-correction promoted information processing related to error-detection and error-correction that are essential for motor learning.

show abstract

“…Augmenting errors with forces proportional to errors did not enhance learning to track a 2D figure (Lee and Choi 2010). Amplifying errors during training how to synchronize the legs to track a Lissajous figure resulted in better learning in initially more skilled subjects, but limited transfer of learning (Marchal-Crespo et al 2014a, 2017. These contradictory results suggest that error amplification might limit learning of some specific motor tasks, such as figure tracking.…”

Section: Introductionmentioning

confidence: 92%

The effectiveness of robotic training depends on motor task characteristics

2017

Self Cite

View full text Add to dashboard Cite

Previous research suggests that the effectiveness of robotic training depends on the motor task to be learned. However, it is still an open question which specific task's characteristics influence the efficacy of error-modulating training strategies. Motor tasks can be classified based on the time characteristics of the task, in particular the task's duration (discrete vs. continuous). Continuous tasks require movements without distinct beginning or end. Discrete tasks require fast movements that include well-defined postures at the beginning and the end. We developed two games, one that requires a continuous movement-a tracking task-and one that requires discrete movements-a fast reaching task. We conducted an experiment with thirty healthy subjects to evaluate the effectiveness of three error-modulating training strategies-no guidance, error amplification (i.e., repulsive forces proportional to errors) and haptic guidance-on self-reported motivation and learning of the continuous and discrete games. Training with error amplification resulted in better motor learning than haptic guidance, besides the fact that error amplification reduced subjects' interest/enjoyment and perceived competence during training. Only subjects trained with error amplification improved their performance after training the discrete game. In fact, subjects trained without guidance improved the performance in the continuous game significantly more than in the discrete game, probably because the continuous task required greater attentional levels. Error-amplifying training strategies have a great potential to provoke better motor learning in continuous and discrete tasks. However, their long-lasting negative effects on motivation might limit their applicability in intense neurorehabilitation programs.

show abstract

Optimizing learning of a locomotor task: Amplifying errors as needed

Cited by 28 publications

References 17 publications

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

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

It Pays to Go Off-Track: Practicing with Error-Augmenting Haptic Feedback Facilitates Learning of a Curve-Tracing Task

The effectiveness of robotic training depends on motor task characteristics

Contact Info

Product

Resources

About