Literature DB >> 26192105

Robot assistance of motor learning: A neuro-cognitive perspective.

Herbert Heuer1, Jenna Lüttgen2.   

Abstract

The last several years have seen a number of approaches to robot assistance of motor learning. Experimental studies have produced a range of findings from beneficial effects through null-effects to detrimental effects of robot assistance. In this review we seek an answer to the question under which conditions which outcomes should be expected. For this purpose we derive tentative predictions based on a classification of learning tasks in terms of the products of learning, the mechanisms involved, and the modulation of these mechanisms by robot assistance. Consistent with these predictions, the learning of dynamic features of trajectories is facilitated and the learning of kinematic and dynamic transformations is impeded by robotic guidance, whereas the learning of dynamic transformations can profit from robot assistance with error-amplifying forces. Deviating from the predictions, learning of spatial features of trajectories is impeded by haptic guidance, but can be facilitated by divergent force fields. The deviations point to the existence of additional effects of robot assistance beyond the modulation of learning mechanisms, e.g., the induction of a passive role of the motor system during practice with haptic guidance.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Error amplification; Error-based learning; Haptic guidance; Observational learning; Trajectory learning; Transformation learning

Mesh:

Year:  2015        PMID: 26192105     DOI: 10.1016/j.neubiorev.2015.07.005

Source DB:  PubMed          Journal:  Neurosci Biobehav Rev        ISSN: 0149-7634            Impact factor:   8.989


  12 in total

1.  Development of an MR-compatible hand exoskeleton that is capable of providing interactive robotic rehabilitation during fMRI imaging.

Authors:  Sangjoon J Kim; Yeongjin Kim; Hyosang Lee; Pouya Ghasemlou; Jung Kim
Journal:  Med Biol Eng Comput       Date:  2017-07-15       Impact factor: 2.602

2.  Human social motor solutions for human-machine interaction in dynamical task contexts.

Authors:  Patrick Nalepka; Maurice Lamb; Rachel W Kallen; Kevin Shockley; Anthony Chemero; Elliot Saltzman; Michael J Richardson
Journal:  Proc Natl Acad Sci U S A       Date:  2019-01-07       Impact factor: 11.205

Review 3.  Upper Limb Home-Based Robotic Rehabilitation During COVID-19 Outbreak.

Authors:  Hemanth Manjunatha; Shrey Pareek; Sri Sadhan Jujjavarapu; Mostafa Ghobadi; Thenkurussi Kesavadas; Ehsan T Esfahani
Journal:  Front Robot AI       Date:  2021-05-24

4.  Robot-Assisted Proprioceptive Training with Added Vibro-Tactile Feedback Enhances Somatosensory and Motor Performance.

Authors:  Anna Vera Cuppone; Valentina Squeri; Marianna Semprini; Lorenzo Masia; Jürgen Konczak
Journal:  PLoS One       Date:  2016-10-11       Impact factor: 3.240

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

Authors:  Camille K Williams; Luc Tremblay; Heather Carnahan
Journal:  Front Psychol       Date:  2016-12-26

6.  Self-Control of Haptic Assistance for Motor Learning: Influences of Frequency and Opinion of Utility.

Authors:  Camille K Williams; Victrine Tseung; Heather Carnahan
Journal:  Front Psychol       Date:  2017-12-04

7.  Exploring disturbance as a force for good in motor learning.

Authors:  Jack Brookes; Faisal Mushtaq; Earle Jamieson; Aaron J Fath; Geoffrey Bingham; Peter Culmer; Richard M Wilkie; Mark Mon-Williams
Journal:  PLoS One       Date:  2020-05-20       Impact factor: 3.240

8.  Neural circuits activated by error amplification and haptic guidance training techniques during performance of a timing-based motor task by healthy individuals.

Authors:  Marie-Hélène Milot; Laura Marchal-Crespo; Louis-David Beaulieu; David J Reinkensmeyer; Steven C Cramer
Journal:  Exp Brain Res       Date:  2018-08-21       Impact factor: 1.972

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

Authors:  Laura Marchal-Crespo; Panagiotis Tsangaridis; David Obwegeser; Serena Maggioni; Robert Riener
Journal:  Front Neurosci       Date:  2019-02-19       Impact factor: 4.677

10.  Improving short-term retention after robotic training by leveraging fixed-gain controllers.

Authors:  Dylan P Losey; Laura H Blumenschein; Janelle P Clark; Marcia K O'Malley
Journal:  J Rehabil Assist Technol Eng       Date:  2019-09-06
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