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The report is a survey of mathematical model of human gait. The model is based on power developed by muscle joints. Biomechanical modelling requires experimental support in the form of input data and validation of results. As the models become more complex, they are more dependent on advances in experimental methods and transducer development. In this study the regression function and the stochastic approximation function have been used to identify dynamic properties of human gait of normal subjects, patients with spastic diplegia, and subjects with spina bifida.
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Bibliografia
  • 1. Frigo C., Rabuffetti M., Kerrigan C.D., Deming L.C., Pedotti A.: Functionally oriented and clinically feasible quantitative gait analysis method, Medical & Biological Engineering & Computing, 1998, 36, 2, 179-185.
  • 2. Giannini S., Catani F., Bene M.G., Leardini A.: Gait analysis. Methodologies and clinic applications, Bioengineering Technology & Systems, Oxford 1994.
  • 3. Kalicka R.: The identifiability of the single input-single output compartmental systems, Biocybernetics and Biomedical Eng., 1989, 9, 1-4, 79-90.
  • 4. Kalicka R.: Modelling kinematic process in biomedical systems, monograph 18, Gdańsk 2000.
  • 5. Manerowski J.: Identification of model of flying objects, ASKON, Warsaw 1999.
  • 6. Pauk J.: Parametric identification of lower limbs during walking of a man, Conference Proceedings IV World Congress of Biomechanics, Canada 2002, CD-ROM.
  • 7. Pauk J.: Identification of human gait model, Conference Proceedings Biomechanics of man, Cejkovice 2002, 127-129.
  • 8. Pauk J, Jaworek K.: Parametric identification of lower limbs during walking of a man, Design & Nature, WET Press, Southampton 2000, 361-366.
  • 9. Pauk J.: Identification of dynamic models of human gait, Ph.D. Thesis, Warsaw 2005.
  • 10. Whittle M.W.: Clinical gait analysis, A review, Human Movement Science 15, 1996, 369-387.
  • 11. Pauk J.: The mathematical modelling of human movement, Gait and Posture 2005.
  • 12. Pavan E. et al.: Parameter identification for model-based control in functional electrical stimulation system, International Biomechatronics Workshop, Enschede 1999, 66-70.
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bwmeta1.element.baztech-article-BPZ1-0030-0025
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