Literature DB >> 25974949

Learning of Temporal and Spatial Movement Aspects: A Comparison of Four Types of Haptic Control and Concurrent Visual Feedback.

Georg Rauter, Roland Sigrist, Robert Riener, Peter Wolf.   

Abstract

In literature, the effectiveness of haptics for motor learning is controversially discussed. Haptics is believed to be effective for motor learning in general; however, different types of haptic control enhance different movement aspects. Thus, in dependence on the movement aspects of interest, one type of haptic control may be effective whereas another one is not. Therefore, in the current work, it was investigated if and how different types of haptic controllers affect learning of spatial and temporal movement aspects. In particular, haptic controllers that enforce active participation of the participants were expected to improve spatial aspects. Only haptic controllers that provide feedback about the task's velocity profile were expected to improve temporal aspects. In a study on learning a complex trunk-arm rowing task, the effect of training with four different types of haptic control was investigated: position control, path control, adaptive path control, and reactive path control. A fifth group (control) trained with visual concurrent augmented feedback. As hypothesized, the position controller was most effective for learning of temporal movement aspects, while the path controller was most effective in teaching spatial movement aspects of the rowing task. Visual feedback was also effective for learning temporal and spatial movement aspects.

Entities:  

Mesh:

Year:  2015        PMID: 25974949     DOI: 10.1109/TOH.2015.2431686

Source DB:  PubMed          Journal:  IEEE Trans Haptics        ISSN: 1939-1412            Impact factor:   2.487


  2 in total

1.  Rowing Simulator Modulates Water Density to Foster Motor Learning.

Authors:  Ekin Basalp; Laura Marchal-Crespo; Georg Rauter; Robert Riener; Peter Wolf
Journal:  Front Robot AI       Date:  2019-08-21

2.  Real-time motion onset recognition for robot-assisted gait rehabilitation.

Authors:  Roushanak Haji Hassani; Mathias Bannwart; Marc Bolliger; Thomas Seel; Reinald Brunner; Georg Rauter
Journal:  J Neuroeng Rehabil       Date:  2022-01-28       Impact factor: 4.262

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.