Literature DB >> 12529218

One-Handed Juggling: A Dynamical Approach to a Rhythmic Movement Task.

S. Schaal1, C. G. Atkeson, D. Sternad.   

Abstract

The skill of rhythmically juggling a ball on a racket was investigated from the viewpoint of nonlinear dynamics. The difference equations that model the dynamical system were analyzed by means of local and nonlocal stability analyses. These analyses showed that the task dynamics offer an economical juggling pattern that is stable even for open-loop actuator motion. For this pattern, two types of predictions were extracted: (a) Stable periodic bouncing is sufficiently characterized by a negative acceleration of the racket at the moment of impact with the ball, and (b) a nonlinear scaling relation maps different juggling trajectories onto one topologically equivalent dynamical system. The relevance of these results for the human control of action was evaluated in an experiment in which subjects (N = 6) performed a comparable task of juggling a ball on a paddle. Task manipulations involved different juggling heights and gravity conditions of the ball. The following predictions were confirmed: (a) For stable rhythmic performance, the paddle's acceleration at impact is negative and fluctuations of the impact acceleration follow predictions from global stability analysis; and (b) for each subject, the realizations of juggling for the different experimental conditions are related by the scaling relation. These results permit one to conclude that humans reliably exploit the stable solutions inherent to the dynamics of the given task and do not overrule these dynamics by other control mechanisms. The dynamical scaling serves as an efficient principle for generating different movement realizations from only a few parameter changes and is discussed as a dynamical formalization of the principle of motor equivalence.

Entities:  

Year:  1996        PMID: 12529218     DOI: 10.1080/00222895.1996.9941743

Source DB:  PubMed          Journal:  J Mot Behav        ISSN: 0022-2895            Impact factor:   1.328


  23 in total

1.  Control of ball-racket interactions in rhythmic propulsion of elastic and non-elastic balls.

Authors:  Hiromu Katsumata; Vladimir Zatsiorsky; Dagmar Sternad
Journal:  Exp Brain Res       Date:  2003-01-16       Impact factor: 1.972

2.  Evaluation of negative viscosity as upper extremity training for stroke survivors.

Authors:  Felix C Huang; James L Patton
Journal:  IEEE Int Conf Rehabil Robot       Date:  2011

3.  Manual skill generalization enhanced by negative viscosity.

Authors:  Felix C Huang; James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2010-07-21       Impact factor: 2.714

4.  Bouncing between model and data: stability, passivity, and optimality in hybrid dynamics.

Authors:  Renaud Ronsse; Dagmar Sternad
Journal:  J Mot Behav       Date:  2010-11       Impact factor: 1.328

5.  Control of bimanual rhythmic movements: trading efficiency for robustness depending on the context.

Authors:  Renaud Ronsse; Jean-Louis Thonnard; Philippe Lefèvre; Rodolphe Sepulchre
Journal:  Exp Brain Res       Date:  2008-02-14       Impact factor: 1.972

6.  Optimal control of a hybrid rhythmic-discrete task: the bouncing ball revisited.

Authors:  Renaud Ronsse; Kunlin Wei; Dagmar Sternad
Journal:  J Neurophysiol       Date:  2010-02-03       Impact factor: 2.714

7.  The critical phase for visual control of human walking over complex terrain.

Authors:  Jonathan Samir Matthis; Sean L Barton; Brett R Fajen
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-24       Impact factor: 11.205

8.  Model of rhythmic ball bouncing using a visually controlled neural oscillator.

Authors:  Guillaume Avrin; Isabelle A Siegler; Maria Makarov; Pedro Rodriguez-Ayerbe
Journal:  J Neurophysiol       Date:  2017-08-09       Impact factor: 2.714

9.  The primacy of rhythm: how discrete actions merge into a stable rhythmic pattern.

Authors:  Zhaoran Zhang; Dagmar Sternad
Journal:  J Neurophysiol       Date:  2018-12-19       Impact factor: 2.714

10.  Negative viscosity can enhance learning of inertial dynamics.

Authors:  Felix C Huang; James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  IEEE Int Conf Rehabil Robot       Date:  2009-06
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.