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Motor control of voluntary arm movements

Kinematic and modelling study

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Abstract

The motor control of pointing and reaching-to-grasp movements was investigated using two different approaches (kinematic and modelling) in order to establish whether the type of control varies according to modifications of arm kinematics. Kinematic analysis of arm movements was performed on subjects' hand trajectories directed to large and small stimuli located at two different distances. The subjects were required either to grasp and to point to each stimulus. The kinematics of the subsequent movement, during which subject's hand came back to the starting position, were also studied. For both movements, kinematic analysis was performed on hand linear trajectories as well as on joint angular trajectories of shoulder and elbow. The second approach consisted in the parametric identification of the black box (ARMAX) model of the controller driving the arm movement. Such controller is hypothesized to work for the correct execution of the motor act. The order of the controller ARMAX model was analyzed with respect to the different experimental conditions (distal task, stimulus size and distance). Results from kinematic analysis showed that target distance and size influenced kinematic parameters both of angular and linear displacements. Nevertheless, the structure of the motor program was found to remain constant with distane and distal task, while it varied with precision requirements due to stimulus size. The estimated model order of the controller confirmed the invariance of the control law with regard to movement amplitude, whereas it was sensitive to target size.

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References

  • Akaike H (1972) A new look at the statistical model identification. IEEE Trans Autom Contr 19:713–723

    Google Scholar 

  • Astrom KJ (1980) Maximum likelihood and prediction error methods. Automatica, 16:551–574

    Article  Google Scholar 

  • Box GEP, Jenkins GM (1970) Time series analysis, forecasting and control. Holdern-Day, San Erancisco

    Google Scholar 

  • Carter MC, Shapiro DC (1984) Control of sequential movements. J Neurophysiol 52:787–796

    CAS  PubMed  Google Scholar 

  • Chalam VV (1987) Adaptive control systems. Techniques and applications. Dekker, New York

    Google Scholar 

  • D'Amico M, Ferrigno G (1990) A technique for the evaluation of derivatives from noisy biomechanical displacement data by a model-based bandwith-selection procedure. Med Biol Eng Comput 28:407–415

    PubMed  Google Scholar 

  • Drillis R, Contini R (1972) Body segments parameters. Tech. Rep. 1166.03 New York University, School of Engineering and Science, Research Div., New York

    Google Scholar 

  • Ferrigno G, Pedotti A (1985) ELITE: a digital dedicated hardware system for movement analysis via real-time TV signal processing. IEEE Trans Biomed Eng BME-32, 11:943–950

    Google Scholar 

  • Fitts PM (1954) The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 47:381–391

    CAS  PubMed  Google Scholar 

  • Gentilucci M, Castiello U, Corradini ML, Scarpa M, Umilta' C, Rizzolatti G (1991) Influence of different types of grasping on the transport component of prehension movements. Neuropsychologia, 29:361–368

    Article  CAS  PubMed  Google Scholar 

  • Gentilucci M, Chieffi S, Scarpa M, Castiello U (1992) Temporal coupling between transport and grasp components of prehension movements: effects of visual perturbation. Behav Brain Res 47:71–82

    CAS  PubMed  Google Scholar 

  • Goodale MA, Pelisson D, Prablanc C (1986) Large adjustments in visually guided reaching do not depend on vision of the hand of or perception of target displacement. Nature 320:748–750

    Article  CAS  PubMed  Google Scholar 

  • Hoff B, Arbib MA (in press) A model of the effects of speed, accuracy and perturbation on visually guided reaching. In: Caminiti R (ed.) Control of arm movement in space: neurophysiological and computational approaches. Exp Brain Res [Suppl] Series

  • Jeannerod M (1988) The neural and behavioral organization of goal-directed movements. Clarendon Press, Oxford

    Google Scholar 

  • Landau YD (1979) Adaptive control. Dekker, New York

    Google Scholar 

  • Ljung L (1986) System identification — theory for the user. Prentice Hall, Englewood Cliffs, NJ

    Google Scholar 

  • Ljung L, Soderstrom T (1983) Theory and practice of recursive identification. MIT Press, Cambridge

    Google Scholar 

  • Ljung L, Gustavsson I, Soderstrom T (1974) Identification of linear multivariable systems operating under linear feedback control. IEEE Trans Autom Contr, AC-19, 6:836–840

    Article  Google Scholar 

  • Marteniuk RG, MacKenzie CL, Jeannerod M, Athenes S, Dugas C (1987) Constraints on human arm trajectories. Can J Psychol 41:365–378

    CAS  PubMed  Google Scholar 

  • MacKenzie CL, Marteniuk RG, Dugas C, Liske D, Eickmeir B (1987) Three dimensional movement trajectories in Fitts' law: Implication for control. QJ Exp Psychol 39:629–647

    Google Scholar 

  • Megaw ED (1984) Possible modification to a rapid on-going programmed manual response. Brain Res 71:425–441

    Article  Google Scholar 

  • Paulignan Y, MacKenzie C, Marteniuk R, Jennerod M (1990) The coupling of arm and finger movements during prehension. Exp Brain Res 79:431–435

    Article  CAS  PubMed  Google Scholar 

  • Paulignan Y, MacKenzie C, Marteniuk R, Jeannerod M (1991) Selective perturbation of visual input during prehension movements. 1. The effects of changing position. Exp Brain Res 83:502–512

    Article  CAS  PubMed  Google Scholar 

  • Rizzolatti G, Camarda R, Fogassi L, Gentilucci M, Luppino G, Matelli M (1988) Functional organization of inferior area 6 in the macaque monkey. Area F5 and the control of distal movements. Exp Brain Res 71:491–507

    Article  CAS  PubMed  Google Scholar 

  • Schmidt RA (1988) Motor control and learning: a behavioral emphasis. Hum Kinet, Champain, Ill

    Google Scholar 

  • Soechting JF (1984) Effect of target size on spatial and temporal characteristics of a pointing movement in man. Exp Brain Res 54:121–132

    Article  CAS  PubMed  Google Scholar 

  • Soechting JF, Lacquaniti F (1983) Modification of trajectory of a pointing movement in response to a change in target location. J Neurophysiol 49:2,548–564

    CAS  PubMed  Google Scholar 

  • Viviani V, Terzuolo C (1981) Space-time invariance in learned motor skill. In Stelmach GE, Requin J (eds.) Tutorial in motor behavior. North-Holland, Amsterdam, pp 525–533

    Google Scholar 

  • Woodsworth RS (1899) The accuracy of voluntary movements. Psychol Res Monogr [Suppl] 3:1–114

    Google Scholar 

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Corradini, M.L., Gentilucci, M., Leo, T. et al. Motor control of voluntary arm movements. Biol. Cybern. 67, 347–360 (1992). https://doi.org/10.1007/BF02414890

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