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Human Hand Motor Control Studies

  • Alessandro AltobelliEmail author
Chapter
Part of the Springer Series on Touch and Haptic Systems book series (SSTHS)

Abstract

This chapter aims to give a brief overview on the complexity that is typical of hand motor control studies. Starting from biomechanical hand models to recent theories on motor control in grasping tasks, in this dissertation the important factors which affect grasp proprieties are dealt. The mechanical structure of human hand is extremely complex and difficult to model; its rigid internal framework is made by 27 bones that are moved by 18 intrinsic muscles and 18 extrinsic muscles coupled by a network of tendons. To have a simple hand model, at least 23–24 DoFs are needed: 4 DoFs for each finger, 5 for the thumb, 1 for the radioulnar joint, and 2 at the wrist. In a more detailed model, the number of DoFs increases just taking into account the hand’s capability to create a palmar arch when it closes. A complete biomechanical model includes 36 muscles coupled to the bones by a complex tendons network; moreover, several biomechanical constraints have to be included in the model. Joint limits or finger dimensions are clear examples of constraints which can affect the interaction of the hand with the world, and additional constraints arise from the coupling of tendons and muscles. Some muscles span several phalanges, making it difficult to move only one joint independently; for example, the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC) muscles are divided on each finger; therefore, a contraction of these muscles engages several hand joints. Understanding how humans exploit biomechanics and sensory feedback of hand in everyday tasks is a challenging topic that still is not completely understood. Several studies and theories, focused on kinematic and grasping tasks have been developed. In the next section, I will give an introduction on the most recent studies which focus on important aspects of manipulation: (i) hand control in pre-grasp phase, (ii) grasp force distributions, (iii) muscle activations, and (iv) impedance control.

Keywords

Contact Force Force Distribution Impedance Control Finger Force Force Mode 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    J.F. Soechting and M. Flanders, “Flexibility and repeatability of finger movements during typing: Analysis of multiple degrees of freedom”, Journal of computational neuroscience, vol. 4, no. 1, pp. 29-46, 1997Google Scholar
  2. 2.
    M. Santello, M. Flanders, and J.F. Soechting, “Postural hand synergies for tool use”, The journal of neuroscience, vol. 18, no. 23, pp. 10 105-10 115, 1998Google Scholar
  3. 3.
    M. Santello, M. Flanders, and J.F. Soechting, “Patterns of hand motion during grasping and the influence of sensory guidance”, The journal of neuroscience, vol. 22, no. 4, pp. 1426-1435, 2002Google Scholar
  4. 4.
    R. Gentner, J. Classen, Modular organization of finger movements by the human central nervous system. Neuron 52(4), 731–742 (2006)CrossRefGoogle Scholar
  5. 5.
    A. Bicchi, M. Gabiccini, M. Santello, Modelling natural and artificial hands with synergies. Philosophical transactions of the royal society b: Biological sciences 366(1581), 3153–3161 (2011)CrossRefGoogle Scholar
  6. 6.
    Z.-M. Li, M. Latash, V. Zatsiorsky, Force sharing among fingers as a model of the redundancy problem. Experimental brain research 119(3), 276–286 (1998)CrossRefGoogle Scholar
  7. 7.
    K.T. Reilly and G.R. Hammond, “Independence of force production by digits of the human hand”, Neuroscience letters, vol. 290, no. 1, pp. 53-56, 2000. 21 Human Hand Motor Control StudiesGoogle Scholar
  8. 8.
    V.M. Zatsiorsky, Z.-M. Li, M.L. Latash, Enslaving effects in multi-finger force production. Experimental brain research 131(2), 187–195 (2000)CrossRefGoogle Scholar
  9. 9.
    S.L. Kilbreath, S.C. Gandevia, Limited independent flexion of the thumb and fingers in human subjects. J physiol 543, 289–296 (2002)CrossRefGoogle Scholar
  10. 10.
    M. Santello, J.F. Soechting, Force synergies for multifingered grasping. Experimental brain research 133(4), 457–467 (2000)CrossRefGoogle Scholar
  11. 11.
    M.P. Rearick, A. Casares, M. Santello, Task-dependent modulation of multi-digit force coordination patterns. Journal of neurophysiology 89(3), 1317–1326 (2003)CrossRefGoogle Scholar
  12. 12.
    M.L. Latash, J.F. Scholz, F. Danion, and G. Schöner, “Structure of motor variability in marginally redundant multifinger force production tasks”, Experimental brain research, vol. 141, no. 2, pp. 153-165, 2001Google Scholar
  13. 13.
    H.B. Olafsdottir, M.L. Latash, and V.M. Zatsisorsky, “Is the thumb a fifth finger?”, Studies of digit interaction during force production tasks, 2005Google Scholar
  14. 14.
    F. Gao, S. Li, Z.-M. Li, M.L. Latash, V.M. Zatsiorsky, Matrix analyses of interaction among fingers in static force production tasks. Biological cybernetics 89(6), 407–414 (2003)CrossRefzbMATHGoogle Scholar
  15. 15.
    J.P. Scholz and G. Schöner, “The uncontrolled manifold concept: Identifying control variables for a functional task”, Experimental brain research, vol. 126, no. 3, pp. 289-306, 1999Google Scholar
  16. 16.
    T. Iberall, G. Bingham, M. Arbib, Opposition space as a structuring concept for the analysis of skilled hand movements. Experimental brain research series 15, 158–173 (1986)Google Scholar
  17. 17.
    D.J. Ostry, A.G. Feldman, A critical evaluation of the force control hypothesis in motor control. Experimental brain research 153(3), 275–288 (2003)CrossRefGoogle Scholar
  18. 18.
    M. Gabiccini and A. Bicchi, “On the role of hand synergies in the optimal choice of grasping forces”, in Robotics science and systems, 2010Google Scholar
  19. 19.
    J.-F. Pilon, S.J. De Serres, A.G. Feldman, Threshold position control of arm movement with anticipatory increase in grip force. Experimental brain research 181(1), 49–67 (2007)CrossRefGoogle Scholar
  20. 20.
    M.L. Latash, J. Friedman, S.W. Kim, A.G. Feldman, V.M. Zatsiorsky, Prehension synergies and control with referent hand configurations. Experimental brain research 202(1), 213–229 (2010)CrossRefGoogle Scholar
  21. 21.
    F.J. Valero-Cuevas, F.E. Zajac, C.G. Burgar, Large index-fingertip forces are produced by subject-independent patterns of muscle excitation. Journal of biomechanics 31(8), 693–703 (1998)CrossRefGoogle Scholar
  22. 22.
    F.J. Valero-Cuevas, Predictive modulation of muscle coordination pattern magnitude scales fingertip force magnitude over the voluntary range. Journal of neurophysiology 83(3), 1469–1479 (2000)Google Scholar
  23. 23.
    A. Danna-Dos Santos, B. Poston, M. Jesunathadas, L. R. Bobich, T. M. Hamm, and M. Santello, “Influence of fatigue on hand muscle coordination and emg-emg coherence during threedigit grasping”, Journal of neurophysiology, vol. 104, no. 6, pp. 3576- 3587, 2010Google Scholar
  24. 24.
    B. Poston, A. Danna-Dos Santos, M. Jesunathadas, T. M. Hamm, and M. Santello, “Force-independent distribution of correlated neural inputs to hand muscles during three-digit grasping”, Journal of neurophysiology, vol. 104, no. 2, pp. 1141-1154, 2010. 23 Human Hand Motor Control StudiesGoogle Scholar
  25. 25.
    E.J. Weiss, M. Flanders, Muscular and postural synergies of the human hand. Journal of neurophysiology 92(1), 523–535 (2004)CrossRefGoogle Scholar
  26. 26.
    F.J. Valero-Cuevas, M. Venkadesan, E. Todorov, Structured variability of muscle activations supports the minimal intervention principle of motor control. Journal of neurophysiology 102(1), 59–68 (2009)CrossRefGoogle Scholar
  27. 27.
    S.A. Winges, M. Santello, Common input to motor units of digit flexors during multi-digit grasping. Journal of neurophysiology 92(6), 3210–3220 (2004)CrossRefGoogle Scholar
  28. 28.
    F.A. Mussa-Ivaldi, N. Hogan, E. Bizzi, Neural, mechanical, and geometric factors subserving arm posture in humans. The journal of neuroscience 5(10), 2732–2743 (1985)Google Scholar
  29. 29.
    T. Flash, F. Mussa-Ivaldi, Human arm stiffness characteristics during the maintenance of posture. Experimental brain research 82(2), 315–326 (1990)CrossRefGoogle Scholar
  30. 30.
    T. Tsuji, P.G. Morasso, K. Goto, K. Ito, Human hand impedance characteristics during maintained posture. Biological cybernetics 72(6), 475–485 (1995)CrossRefzbMATHGoogle Scholar
  31. 31.
    A. Ajoudani, N.G. Tsagarakis, A. Bicchi, Tele-Impedance: Teleoperation with impedance regulation using a body-machine interface. International journal of robotics research 31(13), 1642–1655 (2012)CrossRefGoogle Scholar
  32. 32.
    A.M. Smith, The coactivation of antagonist muscles. Canadian journal of physiology and pharmacology 59(7), 733–747 (1981)CrossRefGoogle Scholar
  33. 33.
    D.R. Humphrey, D.J. Reed, Separate cortical systems for control of joint movement and joint stiffness: Reciprocal activation and coactivation of antagonist muscles. Adv neurol 39, 347–372 (1983)Google Scholar
  34. 34.
    A.E. Fiorilla, F. Nori, L. Masia, G. Sandini, Finger impedance evaluation by means of hand exoskeleton. Annals of biomedical engineering 39(12), 2945–2954 (2011)CrossRefGoogle Scholar
  35. 35.
    A.Z. Hajian, R.D. Howe, Identification of the mechanical impedance at the human finger tip. Journal of biomechanical engineering 119(1), 109–114 (1997)CrossRefGoogle Scholar
  36. 36.
    H. Hoppner, D. Lakatos, H. Urbanek, C. Castellini, P. van der Smagt, “The grasp perturbator: Calibrating human grasp stiffness during a graded force task”, in Robotics and automation (icra), ieee international conference on. IEEE 2011, 3312–3316 (2011)Google Scholar
  37. 37.
    T.E. Milner, D.W. Franklin, Characterization of multijoint finger stiffness: Dependence on finger posture and force direction. Biomedical engineering, ieee transactions on 45(11), 1363–1375 (1998)CrossRefGoogle Scholar
  38. 38.
    M. Turvey, Action and perception at the level of synergies. Human movement science 26(4), 657–697 (2007)CrossRefGoogle Scholar
  39. 39.
    M. G. Catalano, G. Grioli, A. Serio, E. Farnioli, C. Piazza, and A. Bicchi, “Adaptive synergies for a humanoid robot hand”, in Ieee-ras international conference on humanoid robots, Osaka, Japan, In PressGoogle Scholar
  40. 40.
    I. Kao, M. R. Cutkosky, and R. S. Johansson, “Robotic stiffness control and calibration as applied to human grasping tasks”, Robotics and automation, ieee transactions on, vol. 13, no. 4, pp. 557-566, 1997. 25 Human Hand Motor Control StudiesGoogle Scholar
  41. 41.
    P. Buttolo, “Characterization of human pen grasp with haptic displays”, PhD thesis, Citeseer, 1996Google Scholar
  42. 42.
    C.L. Van Doren, Grasp stiffness as a function of grasp force and finger span. Motor control 2(4), 352–378 (1998)CrossRefGoogle Scholar
  43. 43.
    J. Friedman, T. Flash, Task-dependent selection of grasp kinematics and stiffness in human object manipulation. Cortex 43(3), 444–460 (2007)CrossRefGoogle Scholar
  44. 44.
    N. Hogan, Impedance control: An approach to manipulation: Part ii?implementation. Journal of dynamic systems, measurement, and control 107(1), 8–16 (1985)MathSciNetCrossRefzbMATHGoogle Scholar
  45. 45.
    S.J. Lederman, R.L. Klatzky, Relative availability of surface and object properties during early haptic processing. Journal of experimental psychology: Human perception and performance 23(6), 1680 (1997)Google Scholar
  46. 46.
    P. Rochat, Mouthing and grasping in neonates: Evidence for the early detection of what hard or soft substances afford for action. Infant behavior and development 10(4), 435–449 (1987)CrossRefGoogle Scholar
  47. 47.
    S.A. Winges, S.E. Eonta, J.F. Soechting, M. Flanders, Effects of object compliance on three-digit grasping. Journal of neurophysiology 101(5), 2447–2458 (2009)CrossRefGoogle Scholar
  48. 48.
    S.L. Gorniak, V.M. Zatsiorsky, M.L. Latash, Manipulation of a fragile object. Experimental brain research 202(2), 413–430 (2010)CrossRefGoogle Scholar
  49. 49.
    H. Hoppner, J. McIntyre, P. van der Smagt, Task dependency of grip stiffness. a study of human grip force and grip stiffness dependency during two different tasks with same grip forces. Plos one 8(12), e80889 (2013)CrossRefGoogle Scholar
  50. 50.
    A. Serio, E. Riccomini, V. Tartaglia, I. Sarakoglou, M. Gabiccini, N. Tsagarakis, and A. Bicchi, “The patched intrinsic tactile object: A tool to investigate human grasps”, 2014Google Scholar
  51. 51.
    J.M. Abu-Khalaf, J.W. Park, D.J. Mascaro, S. Mascaro, “Stretchable fingernail sensors for measurement of fingertip force”, in Eurohaptics conference, et al., and symposium on haptic interfaces for virtual environment and teleoperator systems. world haptics 2009. third joint. IEEE 2009, 625–626 (2009)Google Scholar
  52. 52.

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Research Center “E. Piaggio”University of PisaPisaItaly

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