Neuromuscular Systems
David J. Murray-Smith
University of Glasgow, Centre for Systems and Control and Department of Electronics and Electrical Engineering, Scotland, United Kingdom
Search for more papers by this authorDavid J. Murray-Smith
University of Glasgow, Centre for Systems and Control and Department of Electronics and Electrical Engineering, Scotland, United Kingdom
Search for more papers by this authorAbstract
The biological systems involved in the regulation of posture and control of movement are highly complex and have attracted much attention from biomedical engineers and neurophysiologists. As well as offering possibilities for the treatment of neuromuscular diseases, improved understanding of these systems is important for the management of patients who have suffered strokes or spinal injuries. Control theory provides a useful framework for analysis of neuromuscular systems and mathematical modeling and computer simulation techniques used for engineering systems analysis have proved to be of considerable value in this field. Neuromuscular systems are also of considerable interest to those involved in robotics research and biologically-inspired robots that have features similar to those of the neuromuscular system are becoming increasingly important. Techniques applied in biomimetic robots are starting to influence the currently accepted theories about the hierarchical structure of the neuromuscular system.
Bibliography
- 1F. E. Zajac, Muscle and tendon: Properties, models, scaling and applications to biomechanics and motor control. CRC Crit. Rev. Biomed. Eng. 1989; 17: 359–411.
- 2M. Binder and C. Heckman, The physiological control of motoneuron activity. In: L. Rowell and J. Shepherd, eds., Handbook of Physiology, Exercise: Regulation and Integration of Multiple Systems. New York: Oxford Univ. Press, pp. 3–53, 1996.
- 3G. E. Loeb, I. E. Brown, and E. J. Cheng, A hierarchical foundation for models of sensorimotor control. Exp. Brain Res. 1999; 126: 1–18.
- 4A. Prochazka, Proprioceptive feedback and movement regulation. In: L. Rowell and J. Shepherd, eds., Handbook of Physiology, Exercise: Regulation and Integration of Multiple Systems. New York: Oxford Univ. Press, pp. 89–127, 1996.
- 5J. He, M. G. Maltenfort, Q. Wang, and T. M. Hamm, Learning from biological systems: Modeling neural control. IEEE Control Syst. Mag. 2001; 21: 55–69.
- 6L. Schovanec, Modeling human movement systems: Ocular dynamics and skeletal systems. IEEE Control Syst. Mag. 2001; 21: 70–79.
- 7J. Keifer and J. C. Houk, Motor function in the cerebellorobrospinal system. Physiological Reviews 1994: 509–542.
- 8A. V. Hill, The maximum work and mechanical efficiency of human muscles and their most economical speed. J. Physiol. 1922; 56: 19–41.
- 9A. V. Hill, The heat of shortening and dynamic constants of muscle, Proc. Royal Soc., London 1938; B126: 136–195.
10.1098/rspb.1938.0050 Google Scholar
- 10J. M. Ritchie and D. R. Wilkie, Dynamics of muscular contraction. J. Physiol. 1958; 143: 104–113.
- 11B. R. Jewell and D. R. Wilkie, The mechanical properties of relaxing muscle. J. Physiol. 1960; 152: 30–47.
- 12A. J. Fuglevand, D. A. Winter, and A. E. Patla, Models of recruitment and rate coding organization in motor-unit pools. J. Neurophysiol. 1993; 70(6): 2470–2488.
- 13H. Hatze, A myocybernetic control model of skeletal muscle. Biol. Cybernetics. 1977; 25: 103–119.
- 14H. Hatze, A general myocybernetic control model of skeletal muscle. Biol. Cybernetics. 1978; 28: 143–157.
- 15G. I. Zahalak, An overview of muscle modeling. In: R. B. Stein, P. H. Peckham, and D. P. Popović, eds., Neural Prostheses. Replacing Motor Function after Disease or Disability, Oxford, U.K.: Oxford University Press, pp 17–57, 1992.
- 16A. Prochazka and M. Hulliger, The continuing debate about CNS control of proprioception. J. Physiol. 1998; 513(2): 315.
- 17I. A. Boyd, The structure and innervation of nuclear bag muscle fibre system and the nuclear chain muscle fibre system in mammalian muscle spindles. Phil. Trans. Royal Soc. B. 1962; 245: 83–136.
- 18P. B. C. Matthews, The differentiation of two types of fusimotor fibre by their effects on the dynamic response of muscle spindle primary endings. Quart. J. Exp. Physiol. 1962; 47: 324–333.
- 19A. Crowe and P. B. C. Matthews, The effects of stimulation of static and dynamic fusimotor fibres on the response to stretching of the primary endings of muscle spindles. J. Physiol. 1964; 174: 109–131.
- 20F. Emonet-Denand, Y. Laporte, P. B. C. Matthews, and J. Petit, On the subdivision of static and dynamic fusimotor axons on the primary endings of the cat muscle spindle. J. Physiol. 1977; 268: 835–850.
10.1113/jphysiol.1977.sp011884 Google Scholar
- 21A. Prochazka, D. Gillard, and D. J. Bennett, Positive force feedback control in muscles. J. Neurophysiol. 1997; 77: 3237–3251.
- 22P. H. Hammond, P. A. Merton, and G. G. Sutton, Nervous gradation of muscular contraction. Brit. Med. Bull. 1956; 12: 214–218.
- 23C. D. Marsden, P. A. Merton, and H. B. Morton, The sensory mechanism of servo action in human muscle. J. Physiol. 1977; 265(2): 521–535.
- 24A. Prochazka, D. Gillard, and D. J. Bennett, Implications of positive feedback in the control of movement. J. Neurophysiol. 1997; 77: 3237–3251.
- 25A. Prochazka, V. Gritsenko, and S. Yakovenko, Sensory control of locomotion: Reflexes versus higher-level control. In: S. G. Gandevia, U. Proske, and D. G. Stuart, eds., Sensorimotor Control, London, New York: Kluwer Academic/Plenum Publishers, 2002.
- 26C. G. Maclaine, P. N. McWilliam, D. J. Murray-Smith, and J. R. Rosenberg, A possible mode of action of static fusimotor axons as revealed by system identification techniques. Brain Res. 1977; 135: 351–357.
- 27J. C. Houk and W. Simon, Responses of Golgi tendon organs to forces applied to muscle tendon. J. Neurophysiol. 1967; 30: 1466–1481.
- 28P. B. C. Matthews, Mammalian Muscle Receptors and their Central Actions, 1st ed. London: Edward Arnold, 1972.
- 29R. E. Poppele and R. J. Bowman, Quantitative description of linear behavior of mammalian muscle spindles. J. Neurophysiol. 1970; 33: 59–72.
- 30W. J. Chen and R. E. Poppele, Small signal analysis of response of mammalian muscle spindles with fusimotor stimulation and a comparison with large signal responses. J. Neurophysiol. 1978; 41: 15–27.
- 31P. B. C. Matthews and R. B. Stein, The sensitivity of muscle spindle afferents to small sinusoidal changes of length. J. Physiol. 1969; 200: 723–743.
- 32Z. Hasan and J. C. Houk, Transition in sensitivity of spindle receptors that occurs when muscle is stretched more than a fraction of a millimeter. J. Neurophysiol. 1975; 38: 673–689.
- 33 R. Murray-Smith and T. A. Johansen, eds., Multiple Model Approaches to Modeling and Control. New York: Taylor and Francis, 1997.
- 34H. Gollee, D. J. Murray-Smith, and J. C. Jarvis, A nonlinear approach to modeling of electrically stimulated skeletal muscle. IEEE Trans. Biomed. Eng. 2001; 48(4): 406–415.
- 35H. Hulliger, P. B. C. Matthews, and J. Noth, Static and dynamic fusimotor action on the response of Ia fibres to low frequency sinusoidal stretching of widely ranging amplitude. J. Physiol. 1977; 267: 811–838.
- 36J. R. Rosenberg, D. J. Murray-Smith, and A. Rigas, An introduction to the application of system identification techniques to elements of the neuromuscular system. Trans. Institute of Measurement and Control 1982; 4(4): 187–201.
10.1177/014233128200400403 Google Scholar
- 37D. Halliday, D. J. Murray-Smith, and J. R. Rosenberg, A frequency-domain identification approach to the study of neuromuscular systems – a combined experimental and modelling study. Trans. Institute of Measurement and Control 1992; 14(2): 79–90
10.1177/014233129201400204 Google Scholar
- 38D. R. Brillinger, Comparative aspects of the study of ordinary time series and point processes. In: D. R. Brillinger and P. R. Krishnaiah, eds., Developments in Statistics, 1. Amsterdam, Netherlands: Elsevier, pp. 33–134, 1978.
- 39A. M. Amjad, P. Breeze, B. A. Conway, D. M. Halliday, and J. R. Rosenberg, A framework for the analysis of neuronal networks. Prog. in Brain Res. 1989; 80: 243–255.
- 40J. R. Rosenberg, A. M. Amjad, P. Breeze, D. R. Brillinger, and D. M. Halliday, The Fourier approach to the identification of functional coupling between neuronal spike trains. Prog. in Biophys. and Mol. Biol. 1989; 53: 1–31.
- 41Z. Matjačić, K. Hunt, H. Gollee, and T. Sinkjaer, Control of posture with FES systems. Med. Eng. & Physics 2003; 25: 51–62.
- 42J. J. Abbas and J. C. Gilette, Using electrical stimulation to control standing posture. IEEE Control Systems Magazine 2001; 21(4): 80–90.
- 43H. Gollee, K. J. Hunt, and D. E. Wood, New results in feedback control of unsupported standing in paraplegia. IEEE Trans. Neural Syst. & Rehabilitation Eng. 2004; 12(1): 73–80.
- 44W. Holderbaum, K. J. Hunt, and H. Gollee, H-infinity robust control design for paraplegic standing. Control Eng Practice 2002; 10(11): 1211–1222.
- 45F. Previdi, T. Schauer, S. M. Savaresi, and K. J. Hunt, Data-driven control design for neuroprotheses: A virtual reference feedback tuning (VRTF) approach. IEEE Trans. Control Syst. Tech. 2004; 12(1): 176–182.
- 46A. Prochazka, The fuzzy logic of visuomotor control. Can. J. Physiol. Pharmacol. 1996; 74: 456–462.
- 47K. J. Hunt, B. Stone, N.-O. Negård, T. Schauer, M. H. Fraser, A. J. Cathcart, C. Ferrario, S. A. Ward, and S. Grant, Control strategies for integration of electric motor assist and functional electrical stimulation in paraplegic cycling: Utility for exercise testing and mobile cycling. IEEE Trans. Neural Syst. & Rehabilitation Eng. 2004; 12(1): 89–101.
- 48M. B. Popović, D. B. Popović, and R. Tomović, Control of arm movements: Reaching synergies for neuroprosthesis with life-like control. Journal of Automatic Control, University of Belgrade 2002; 12: 9–15.
10.2298/JAC0201009P Google Scholar
- 49N. Wiener, Cybernetics, 2nd ed. Cambridge, MA: MIT Press, 1961.
- 50R. D. Quinn, G. M. Nelson, R. J. Bachmann, D. A. Kingsley, J. T. Offi, and T. J. Allen, Parallel complementary strategies for implementing biological principles into mobile robots. Intl. J. Robotics Research 2003; 22(3): 169–186.
- 51G. M. Nelson and R. D. Quinn, Posture control of a cockroach-like robot. IEEE Control Systems Magazine. 1999; 19: 9–14.