Model-Based, Multi-Muscle EMG Control of Upper-Extremity Prostheses

  • Sanford G. Meek
  • John E. Wood
  • Stephen C. Jacobsen

Abstract

Mathematical modelling of natural limb motion and actuation can greatly facilitate understanding of the biomechanics and control of a human limb, and can be used in the design of controllers for multi-axis prosthetic arms or the design of functional neuro-stimulators (FNS) for paralyzed limbs. The motion of a human limb involves the simultaneous control of each muscle of the limb. This simultaneous control provides stability, linkage stiffness, and force balance of the entire limb system, if not the entire body, in addition to the primary action of the limb. This idea of synergy of the entire system suggests that a prosthetic limb or a neuro-stimulated paralyzed limb should not be considered as an autonomous system but rather as an integral, dynamically coupled part of the person. Such a control scheme should free functionally sound parts of the body from controlling or actuating prosthetic or stimulated limbs, thus minimizing the conscience effort on the part of the person.

Keywords

Fatigue Torque Covariance Lime Harness 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Basmajian, J.V. and Latif, A. (1957) Integrated Actions and Functions of the Chief Flexors of the Elbow. J. Bone and Joint Surgery, 39-A: 1106–1118.Google Scholar
  2. Cohen, E. and Riesenfield, R. F. (1982) General Matrix Representations for Bezier and B-Spline Curves. Computers in Industry, 3: 9–15.CrossRefGoogle Scholar
  3. Coons, S.A. (1967) Surfaces for Computer-Aided Design of Space Forms. MAC-TR-41, M.I.T.Google Scholar
  4. Crago, P.E., Peckham, P.H. and Thrope, G.B. (1970) Modulation of Muscle Force by Recruitment During Intramuscular Stimulation. IEEE Trans, on Biomed. Eng., BME-27: 679–684.CrossRefGoogle Scholar
  5. Crowninshield, R.D. and Brand, R.A. (1981) A Physiologically Based Criterion of Muscle Force Prediction in Locomotion. J. Biomech. 14: 793–801.CrossRefPubMedGoogle Scholar
  6. DeLuca, C.J. (1979) Physiology and Mathematics of Myoelectric Signals. IEEE Trans, on Biomed. Engng. BME-26:Google Scholar
  7. DeLuca, C.J. (1984) Myoelectric Manifestations of Localized Muscular Fatigue in Humans. CRC Crit. Rev. in Biomed. Engng., Vol. 11, Issue 4.Google Scholar
  8. Dul, J., Townsend, M.A., Shiavi, R. and Johnson, G.E. (1984a) Muscular Synergism — I. On Criteria for Load Sharing Between Synergistic Muscles. J. Biomech. 17: 663–673.CrossRefPubMedGoogle Scholar
  9. Dul, J., Johnson, G.E., Shiavi, R. and Townsend, M.A. (1984b) Muscular Synergism — II. A Minimum- fatigue Criterion for Load Sharing Between Synergistic Muscles. J. Biomech. 17: 675–684.CrossRefPubMedGoogle Scholar
  10. Fu, K.S., Gonzalez, R.C. and Lee, C.S.G. (1987) Robotics Control, Sensing, Vision, and Intelligence. McGraw-Hill.Google Scholar
  11. Fullmer, R.R. (1983) Generation of Postulate-based Controller Equations for a Seven Degree of Freedom Prosthetic Arm. M.S. Thesis, Dept. of M.E., University of Utah, August.Google Scholar
  12. Fullmer, R.R., Meek, S.G. and Jacobsen, S.C. (1984) Optimization of an Adaptive Myoelectric Filter. 6th Conference IEEE/Eng. in Med. and Biol. Soc.Google Scholar
  13. Fullmer, R.R., Meek, S.G., Jacobsen, S.C. (1985) Generation of the 7 Degree of Freedom Controller Equations for a Prosthetic Arm. Conf. on Applied Motion Control, Univ. of Minnesota, Minneapolis.Google Scholar
  14. Heckathome, M.S. and Childress, D.S. (1981) Relationhips of the Surface Electromyogram to the Force, Length, Velocity, and Contraction rate of the Cineplastic Human Biceps. Amer. Jour, of Phys. Med., 60: 1–19.Google Scholar
  15. Hof, A.L. and Van Den Berg, J.W. (1977) Linearity Between the Weighted Sum of the EMGs of the Human Tricepes Surae and the Total Torque. J. Biomech., 10: 529–539.CrossRefPubMedGoogle Scholar
  16. Hollerbach, J.M. (1980) A Recursive Lagrangian Formulation of Manipulator Dynamics and a Comparative Study of Dynamics Formulation Complexity. IEEE Trans, on Sys. Man. and Cybern., SMC-10: 730–736.Google Scholar
  17. Jacobsen, S.C. (1973) Control Systems for Artificial Arms. Doctoral Dissertation, M. I. T., January.Google Scholar
  18. Jacobsen, S.C. and Mann, R.W. (1974) Graphical Representation of the Functional Musculoskeletal Anatomy of the Shoulder and Arm. 27th ACEMB, Philadelphia, PA, 6–10 October.Google Scholar
  19. Jacobsen, S.C., Meek, S.G. and Fullmer, R.R. (1984) An Adaptive Myoelectric Filter. 6th Conf. IEEE/Eng. in Med. and Biol. Soc.Google Scholar
  20. Jerard, R.B. (1976) Application of a Unified Theory for Simultaneous Multiple Axis Artificial Arm Control, Ph.D. Dissertation, University of Utah.Google Scholar
  21. Jerard, R.B. and Jacobsen, S.C. (1980) Laboratory Evaluation of a Unified Theory for multaneous Multiple Axis Artificial Arm Control. Trans, of the ASME, J. Biomech. Engrg. 102 (3): 199–207.CrossRefGoogle Scholar
  22. Kramer, C.G.S., Hagg, T. and Kemp, B (1987) Real-time Measurement of Muscle Fatigue Related Changes in Surface EMG. Medical and Biological Engineering and Computing 25: 627–630.CrossRefPubMedGoogle Scholar
  23. Marquart, D.W. and Snee, R.D. (1975) Ridge Regression in Practice. American Statistician 12 (3): 591–612.Google Scholar
  24. Massy, W.F. (1965) Principal Components Regression in Exploratory Statistical Research. American Statistical Association Journal, pp. 234–256, March.Google Scholar
  25. Meek, S.G. (1982) Command Inputs for a Multiple Degree of Freedom Artificial Arm Controller. Ph.D. Dissertation, University of Utah, December.Google Scholar
  26. Meek, S.G., Fetherston, S., Schoenberg, A. and Milne, K. (1987) Multi-Channel, Adaptive Myoelectric Filtering. 24th Annual Meeting of the Society of Engineering Science, Salt Lake City, Utah, September.Google Scholar
  27. Meek, S.G., Fullmer, R.R., and Jacobsen, S.C. (1984) Control Inputs to a Multiple Degree of Freedom Artificial Arm. IEEE Conference on Engineering in Medicine and Biology, Los Angeles.Google Scholar
  28. Meek, S.G., Jacobsen, S.C. and Goulding, P.P. (1989) Extended Physiologic Taction _ A Proportional Terminal Device Force Feedback System. Journal of Rehabilitation Research and Development 26 (3): 53–62.PubMedGoogle Scholar
  29. Morrison, D.F. (1976) Multivariate Statistical Methods, McGraw-Hill.Google Scholar
  30. Patla, A.E., Hudgins, B.S., Parker, P.A. and Scott, R.N. (1982) Myoelectric Signal as a Quantative Measure of Mechanical Output. Medical Biological Engineer Computers 20: 319–328.CrossRefGoogle Scholar
  31. Sears, H.H. (1983) Evaluation and Development of a New Hook-Type Terminal Device. Ph.D. Dissertation, University of Utah, June.Google Scholar
  32. Seireg, A. and Arvikar, R.J. (1973) A Mathematical Model for Evaluation of Forces in Lower Extremities of the Musculoskeletal System. J. Biomech. 6: 313–326.CrossRefPubMedGoogle Scholar
  33. Seireg, A. and Arvikar, R.J. (1975) The Prediction of Muscular Load Sharing and Joint Forces in the Lower Extremities During Walking. J. Biomech. 8: 89–102.CrossRefPubMedGoogle Scholar
  34. Wood, J.E. and Mann, R.W (1981) A Sliding-Filament Cross-Bridge Ensemble Model of Muscle Contract for Mechanical Transients. Math. Biosci. 57: 211–263.CrossRefGoogle Scholar
  35. Wood, J.E., Meek, S.G. and Jacobsen, S.C. (1989) Quantitation of Human Shoulder Anatomy for Prosthetic Control, Part I. J. of Biomechanics 22 (3): 273–292.CrossRefGoogle Scholar
  36. Wood, J.E., Meek, S.G. and Jacobsen, S.C. (1989) Quantitation of Human Shoulder Anatomy for Prosthetic Control, Part II. J. of Biomechanics 22 (4): 309–326.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 1990

Authors and Affiliations

  • Sanford G. Meek
  • John E. Wood
  • Stephen C. Jacobsen

There are no affiliations available

Personalised recommendations