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Body-goal Variability Mapping in an Aiming Task

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Abstract

Given the number of joints and muscles in the human body, there are typically an infinite number of ways to perform the same action, a feature of directed movements known as equifinality (Bernstein, The coordination and regulation of movements, Oxford, Pergamon, 1967). Here we present a new type of performance analysis based on the idea of a body-goal variability mapping. We show how this mapping arises naturally from the idea of a goal function that theoretically defines a task and, in the presence of equifinality, determines the set of all possible task solution strategies, the goal equivalent manifold (GEM). The approach also yields estimates of the sensitivity of goal-level errors to body-level perturbations, and we derive a general formula expressing the relationship between the two. We apply these ideas to the analysis of redundant kinematic data from subjects performing an aiming task carried out with and without a laser pointer. It is shown that in order to characterize performance one must consider two factors in addition to the body variability: first, the degree of alignment between body variability and the GEM; and second, the sensitivity parameters that control the degree to which goal-relevant body variability is amplified at the target. Both of these factors can be computed using the estimated body-goal mapping. We show that the performance for three conditions involving two different nominal postures and two different sensory conditions (laser/no laser) can be classified by examining the clustering of data in an orientation- sensitivity parameter plane associated with the map.

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References

  • Balasubramaniam R, Riley M, Turvey M (2000) Specificity of postural sway to the demands of a precision task. Gait Posture 11:12–24

    Article  PubMed  CAS  Google Scholar 

  • Bernstein N (1967) The coordination and regulation of movements. Oxford, Pergamon

    Google Scholar 

  • Chen Y, Ding, M, Kelso JAS (1997) Long memory processes (1/f type) in human coordination. Phys Rev Let 79:4501–4504

    Article  CAS  Google Scholar 

  • Danion F, Varraine E, Bonnard M, Pailhous J (2003) Stride variability in human gait: the effect of stride frequency and stride length. Gait Posture 18:69–77

    Article  PubMed  CAS  Google Scholar 

  • Dingwell JB, Cusumano J (2000) Nonlinear time series analysis of normal and pathological human walking. Chaos 10:848–863

    Article  PubMed  Google Scholar 

  • Domkin D, Laczko J, Jaric S, Johansson H, Latsh M (2002) Structure of joint variability in bimanual pointing task. Exp Brain Res 143:11–23

    Article  PubMed  Google Scholar 

  • Duarte M, Zatsiorsky VM (2000) On the fractal properties of natural human standing. Neurosci Lett 283:173–176

    Article  PubMed  CAS  Google Scholar 

  • Golub G, Van Loan C (1996) Matrix computations. The John Hopkins University Press, Baltimore Marylands

    Google Scholar 

  • Haggard P, Hutchinson K, Stein J (1995) Patterns of coordinated multi-joint movement. Exp Brain Res 107:254–266

    Article  PubMed  CAS  Google Scholar 

  • Hausdorff J, Peng C, Ladin Z, Wei J, Goldberger A (1994) Is walking a random walk? Evidence for long-range correlations. J Appl Physiol 78:349–358

    Google Scholar 

  • Jolliffe I (1986) Principal component analysis. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Kelso JAS, Tuller B, Vatikoitis-Bateson E, Fowler C (1984) Functionally specific cooperation following jaw perturbations during speech: evidence for coordinative structures. J Exp Psychol Hum Percept Perform, 10:812–832

    Article  CAS  Google Scholar 

  • Latash M (2000) There is no motor redundancy in human movements. There is motor abundance. Motor Control, 4:259–260

    CAS  Google Scholar 

  • Mardia K, Kent J, Bibby J (1979) Multivariate analysis. Academic Press, London

    Google Scholar 

  • Masani K, Kouzaki M, Fukunaga T (2002) Variability of ground reaction forces during treadmill walking. J Applied Physiol 92:1885–1890

    Google Scholar 

  • Müller H, Sternad D (2003) A randomization method for the calculation of covariation of multiple non linear relations: illustrated with the example of goal-directed movements. Biol Cybern 89:22–33

    PubMed  Google Scholar 

  • Müller H, Sternad D (2004) Decomposition of variability in the execution of goal-oriented tasks: Three components of skill improvement. J Exp Psychol Hum Percept Perform 30(1):212–233

    Article  PubMed  Google Scholar 

  • Newell K, Corcos D (eds) (1993) Variability and motor control. Human Kinetics, Champaign IL

    Google Scholar 

  • Newell KM, Vaillancourt DE (2001) Dimensional change in motor learning. Hum Mov Sci 20:695–715

    Article  PubMed  CAS  Google Scholar 

  • Owings TM, Grabiner MD (2004) Variability of step kinematics in young and older adults. Gait Posture 20:26–29

    Article  PubMed  Google Scholar 

  • Scholz J, Schöner G (1999) The uncontrolled manifold concept. Exp Brain Res 126:289–306

    Article  PubMed  CAS  Google Scholar 

  • Scholz J, Schöner G, Latash M (2000) Identifying the control structure of multijoint coordination during pistol shooting. Exp Brain Res 135:382–404

    Article  PubMed  CAS  Google Scholar 

  • Slifkin AB, Vaillancourt DE, Newell KM (2000) Intermittency in the control of continuous force production. J Neurophysiol 84:1708–1718

    PubMed  CAS  Google Scholar 

  • Todorov E, Jordan MI (2002) Optimal feedback control as a theory of motor coordination. Nat Neurosci 5:1226–1235

    Article  PubMed  CAS  Google Scholar 

  • Vaillancourt D, Larsson L, Newell K (2003) Effects of aging on force variability, motor unit discharge patterns, and the structure of 10, 20, and 40 hz emg activity. Neurobiol Aging 24:25–35

    Article  PubMed  Google Scholar 

  • Vereijken B, Emmerik R, Whiting H, Newell K (1992) Free(z)ing degrees of freedom in skill acquisition. J Motor Behav 24:133–142

    Article  Google Scholar 

  • Winter DA (1984) Kinematic and kinetic patterns in human gait: variability and compensating effects. Hum Mov Sci 3:51–76

    Article  Google Scholar 

  • Yoshinaga H, Miyazima S, Mitake S (2000) Fluctuation of biological rhythm in finger tapping. Physica A 280:582–586

    Article  Google Scholar 

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Correspondence to Joseph P. Cusumano.

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Cusumano, J.P., Cesari, P. Body-goal Variability Mapping in an Aiming Task. Biol Cybern 94, 367–379 (2006). https://doi.org/10.1007/s00422-006-0052-1

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  • DOI: https://doi.org/10.1007/s00422-006-0052-1

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