A neuroengineering solution to the optimal tracking problem

Human Movement Science

Volumn 18, Issue 2-3, 1999, Pages 155-183

  Neilson, Peter D ^a,b   Neilson, Megan D ^a,b  

^a Univ N   (Australia)

^b Institute of Neurological Sciences   (Australia)

Author keywords

Motor processes; Motor skills; Perceptual motor coordination; Visual tracking

Indexed keywords

EID: 0000504762     PISSN: 01679457     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9457(99)00006-8     Document Type: Article

References (45)

1. Anderson, B. D. O., & Moore, J. B. (1990). Optimal control: Linear quadratic methods. Englewood Cliffs, NJ: Prentice-Hall.
2. Baron, S., & Kleinman, D.L. (1969). The human as an optimal controller and information processor. IEEE Transactions on Man-Machine Systems, 10, 9-17.
3. Berardelli, A., Hallett, M., Rothwell, J. C., Agostino, R., Manfredi, M., Thompson, P. D., & Marsden, C. D. (1996). Single-joint rapid arm movements in normal subjects and in patients with motor disorders (Review article). Brain, 119, 661-674.
4. Bernstein, N. A. (1967). The coordination and regulation of movement. Oxford: Pergamon.
5. Box, G. E. P., & Jenkins, G. M. (1976). Time series analysis: Forecasting and control. San Francisco: Holden-Day.
6. Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47, 381-391.
7. Fitts, P. M., & Peterson, J. R. (1964). The information capacity of discrete motor responses. Journal of Experimental Psychology, 67, 103-112.
8. Flash, T., & Hogan, N. (1995). Optimizing principles in motor control. In M. A. Arbib, The handbook of brain theory and neural networks (pp. 682-685). Cambridge, MA: MIT Press.
9. Freund, H.-J. (1983). Motor unit and muscle activity in voluntary motor control. Physiological Reviews, 63, 387-436.
10. Freund, H.-J., & Büdingen, H. J. (1978). The relationship between speed and amplitude of the fastest voluntary contractions of human arm muscles. Experimental Brain Research, 31, 1-12.
11. Gandevia, S. C. (1987). Roles for perceived voluntary motor commands in motor control. Trends in Neurosciences, 10, 81-85.
12. Haykin, S. (1986). Adaptive filter theory. Englewood Cliffs, NJ: Prentice-Hall.
13. von Holst, E., & Mittelstaedt, H. (1950). Das Reafferenzprinzip. Naturwissenschaften, 37, 464-476.
14. Kawato, M. (1993). Optimization and learning in neural networks for formation and control of coordinated movement. In: D. E. Meyer, & S. Kornblum, Synergies in experimental psychology, artificial intelligence, and cognitive neuroscience. (Attention and Performance XIV) (pp. 820-849). Cambridge, MA: MIT Press.
15. Khalil, K. (1996). Nonlinear systems (2nd ed.). Upper Saddle River, NJ: Prentice-Hall.
16. Kleinman, D. L., Baron, S., & Levison, W. H. (1970). An optimal control model of human response, parts 1 and 2. Automatica, 6, 357-369, 371-383.
17. Kleinman, D. L., Baron, S., & Levison, W. H. (1971). A control theoretic approach to manned-vehicle systems analysis. IEEE Transactions on Automatic Control, 16, 824-832.
18. Lewis, F.L. (1992). Applied optimal control and estimation. Englewood Cliffs, NJ: Prentice-Hall.
19. Ljung, L. (1981). System identification: Theory for the user. Englewood Cliffs, NJ: Prentice-Hall.
20. Marmarelis, V. Z. (1994). Advanced methods of physiological system modeling (Vol. 3). New York: Plenum Press.
21. Marmarelis, P. Z., & Marmarelis, V. Z. (1978). Analysis of physiological systems: The white-noise approach. New York: Plenum Press.
22. McCloskey, D. I. (1981). Corollary discharges: Motor commands and perception. In V. B. Brooks, Handbook of physiology: Sec. 1. The nervous system: Vol. II. Motor control, Part 2 (pp. 1415-1447). Bethesda, MD: American Physiological Society.
23. Meyer, D. E., Abrams, R. E., Wright, C. E., & Smith, J. E. K. (1988). Optimality in human motor performance: Ideal control of rapid aimed movements. Physiological Reviews, 95, 340-370.
24. Neilson, P. D. (1993a). The problem of redundancy in movement control: The adaptive model approach. Psychological Research, 55, 99-106.
25. Neilson, P. D. (1993b). Tonic stretch reflexes in normal subjects and in cerebral palsy. In S. C. Gandevia, D. Burke, & M. Anthony, Science and practice in clinical neurology (pp. 169-190). London: Cambridge University Press.
26. Neilson, P. D., Neilson, M. D., & O'Dwyer, N. J. (1985). Acquisition of motor skills in tracking tasks: Learning internal models. In D. G. Russell, & B. Abernethy, Motor memory and control (pp. 25-36). Dunedin: Human Performance Associates.
27. Neilson, P. D., Neilson, M. D., & O'Dwyer, N. J. (1988). Internal models and intermittency: A theoretical account of human tracking behavior. Biological Cybernetics, 58, 101-112.
28. Neilson, P. D., Neilson, M. D., & O'Dwyer, N. J. (1992). Adaptive model theory: Application to disorders of motor control. In J. J. Summers, Approaches to the study of motor control and learning (pp. 495-548). Amsterdam: Elsevier.
29. Neilson, P. D., Neilson, M. D., & O'Dwyer, N. J. (1995). Adaptive optimal control of human tracking. In D. J. Glencross, & J. P. Piek, Motor control and sensory motor integration: Issues and directions (pp. 97-140). Amsterdam: Elsevier.
30. Neilson, P. D., Neilson, M. D., & O'Dwyer, N. J. (1997). Adaptive model theory: Central processing in acquisition of skill. In K. J. Connolly, & H. Forssberg, Neurophysiology and psychology of motor development. Clinics in developmental medicine (pp. 346-370). London: MacKeith Press.
31. Neilson, P. D., Neilson, M. D., & O'Dwyer, N. J. (1998). Evidence for rapid switching of sensory-motor models. In J. P. Piek, Motor behavior and human skill: A multidisciplinary approach (pp. 105-126). Champaign, IL: Human Kinetics.
32. Neilson, P. D., O'Dwyer, N. J., & Neilson, M. D. (1988). Stochastic prediction in pursuit tracking: An experimental test of adaptive model theory. Biological Cybernetics, 58, 113-122.
33. Nikias, C. L., & Petropulu, A. P. (1993). Higher-order spectral analysis. Englewood Cliffs, NJ: Prentice-Hall.
34. Noble, B., & Daniel, J. W. (1988). Applied linear algebra (3rd ed.). Englewood Cliffs, NJ: Prentice-Hall.
35. O'Dwyer, N., & Neilson, P. D. (1995). Learning a dynamic limb synergy. In D. J. Glencross, & J. P. Piek, Motor control and sensory motor integration: Issues and directions (pp. 289-317). Amsterdam: Elsevier.
36. O'Dwyer, N. J., & Neilson, P. D. (in press). Sense of effort and levels of muscle and cardiorespiratory activation related to metabolic energy expenditure in movement. In W. A. Sparrow, Metabolic energy expenditure and the learning and control of movement. Champaign, IL: Human Kinetics.
37. Ogata, K. (1987). Discrete-time control systems. Englewood Cliffs, NJ: Prentice-Hall.
38. Oytam, Y. (1993). Human eye-hand coordination (etch-a-sketch mode). Undergraduate Thesis, School of Electrical Engineering, University of New South Wales.
39. Pitman, E. (1995). Control strategies employed by human subjects performing tracking tasks: Investigtion using phase lead and non-minimum phase tracking systems. Master of Biomedical Engineering Thesis, University of New South Wales.
40. Quiring, D. P., & Warfel, J. H. (1967). The extremities (3rd ed.). Philadelphia: Lea and Febiger.
41. Sperry, R. W. (1950). Neural basis of the spontaneous optokinetic response produced by visual neural inversion. Journal of Comparative and Physiological Psychology, 43, 482-489.
42. Sriharan, A. (1997). Mathematical modelling of the human operator control system through tracking studies. Master of Engineering Thesis, University of New South Wales.
43. Widrow, B., & Stearns, S. D. (1985). Adaptive signal processing. Englewood Cliffs, NJ: Prentice-Hall.
44. Williams, K. J. (1997). Studies in eye-hand coordination. Finding evidence for synergy formation. Undergraduate Thesis, School of Electrical Engineering, University of New South Wales.
45. Wu, J. Z. (1992). Real-time modelling of nonlinear systems with non-white, non-Gaussian inputs. Master of Engineering Science Thesis, School of Electrical Engineering, University of New South Wales.