Assistance or challenge? Filling a gap in user-cooperative control

Rauter,; Sigrist,; Marchal–Crespo, Laura; Riener,; Wolf, Jason

doi:10.1109/iros.2011.6048504

Cited by 4 publications

(5 citation statements)

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“…This study was performed using our custom-made rowing simulator ( Figure 1) (Rauter et al, 2011). This rowing simulator contains a trimmed rowing boat placed in the middle of a Cave Automated Virtual Environment (CAVE).…”

Section: Apparatusmentioning

confidence: 99%

Visual error amplification showed no benefit for non-naïve subjects in trunk-arm rowing

Gerig

Basalp

Sigrist

et al. 2019

CISS

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Motor learning is assumed to be a partly error driven process. Motor learning studies on simple movements have shown that skilled subjects benefit from training with error amplification. Findings of studies with simple movements do not necessarily transfer to complex sport movements. The goal of this work was to determine the benefit of visual error amplification for non-naïve subjects in learning a fast rowing movement.We conducted a study comparing non-naïve subjects receiving a fading, visual feedback with visual error amplification against a control group receiving the same visual feedback without error amplification. Separate outcome metrics were applied for the domains of spatial and velocity magnitude errors. Besides error metrics, variability metrics were evaluated for both domains, such that they could be interpreted in quantitative relation to each other.The implemented error amplification did not cause group differences in any variable. Subjects with or without error amplification reached similar absolute levels in error and variability. Possible reasons remain speculative. For implementing error amplification to the training of complex movements design decisions must be made for which an informative basis is missing, e.g. the error amplification gains.

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Section: Apparatusmentioning

confidence: 99%

Visual error amplification showed no benefit for non-naïve subjects in trunk-arm rowing

Gerig

Basalp

Sigrist

et al. 2019

CISS

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“…Path controllers have been successfully employed in rehabilitation robotics (Duschau-Wicke et al 2010) and sport training (Rauter et al 2011). an artificial potential field based on the obstacle-avoidance approach described in (Khatib 1985) was designed to allow subjects to try the task by themselves.…”

Section: Path Controllermentioning

confidence: 99%

The effect of haptic guidance and visual feedback on learning a complex tennis task

et al. 2013

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While haptic guidance can improve ongoing performance of a motor task, several studies have found that it ultimately impairs motor learning. However, some recent studies suggest that the haptic demonstration of optimal timing, rather than movement magnitude, enhances learning in subjects trained with haptic guidance. Timing of an action plays a crucial role in the proper accomplishment of many motor skills, such as hitting a moving object (discrete timing task) or learning a velocity profile (time-critical tracking task). The aim of the present study is to evaluate which feedback conditions-visual or haptic guidance-optimize learning of the discrete and continuous elements of a timing task. The experiment consisted in performing a fast tennis forehand stroke in a virtual environment. A tendon-based parallel robot connected to the end of a racket was used to apply haptic guidance during training. In two different experiments, we evaluated which feedback condition was more adequate for learning: (1) a time-dependent discrete task-learning to start a tennis stroke and (2) a tracking task-learning to follow a velocity profile. The effect that the task difficulty and subject's initial skill level have on the selection of the optimal training condition was further evaluated. Results showed that the training condition that maximizes learning of the discrete time-dependent motor task depends on the subjects' initial skill level. Haptic guidance was especially suitable for less-skilled subjects and in especially difficult discrete tasks, while visual feedback seems to benefit more skilled subjects. Additionally, haptic guidance seemed to promote learning in a time-critical tracking task, while visual feedback tended to deteriorate the performance independently of the task difficulty and subjects' initial skill level. Haptic guidance outperformed visual feedback, although additional studies are needed to further analyze the effect of other types of feedback visualization on motor learning of time-critical tasks.

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“…In contrast to first concepts of automated human motor learning in the field of behavioral research e.g. [2], the M 3 -trainer will not only be able to apply visual and auditory feedback [4], but also haptic feedback [6,5] on the actual motor performance. Furthermore, the feedback modality and strategy will automatically be adapted to the individual performance and perception of each athlete.…”

Section: Automated Human Motor Learning With the M 3 -Trainermentioning

confidence: 99%

“…Furthermore, also the feedback modality will be adapted in order to maximize the overall performance under consideration of the individual maximal capability of the athlete. As a first application, the M 3 -trainer will be tested on a high fidelity rowing simulator in a CAVE (Cave Augmented Virtual Environment) [10,7,11,9,6,12,5] (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

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A virtual trainer concept for robot-assisted human motor learning in rowing

Rauter

Sigrist

Baur

et al. 2011

BIO Web of Conferences

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Keeping the attention level and observing multiple physiological and biomechanical variables at the same time at high precision is very challenging for human trainers. Concurrent augmented feedback, which is suggested to enhance motor learning in complex motor tasks, can also hardly be provided by a human trainer. Thus, in this paper, a concept for a virtual trainer is presented that may overcome the limits of a human trainer. The intended virtual trainer will be implemented in a CAVE providing auditory, visual and haptic cues. As a first application, the virtual trainer will be used in a realistic scenario for sweep rowing. To provide individual feedback to each rower, the virtual trainer quantifies errors and provides concurrent auditory, visual, and haptic feedback. The concurrent feedback will be adapted according to the actual performance, individual maximal rowing velocity, and the athlete's individual perception.

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Assistance or challenge? Filling a gap in user-cooperative control

Cited by 4 publications

References 0 publications

Visual error amplification showed no benefit for non-naïve subjects in trunk-arm rowing

Visual error amplification showed no benefit for non-naïve subjects in trunk-arm rowing

The effect of haptic guidance and visual feedback on learning a complex tennis task

A virtual trainer concept for robot-assisted human motor learning in rowing

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