Page 327 - Biomedical Engineering and Design Handbook Volume 1, Fundamentals
P. 327

304  BIOMECHANICS OF THE HUMAN BODY

                       (2006), the gastrocnemius muscles are treated as both plantar flexors of the ankle and flexors of the
                       knee, and the ankle function and knee function can be modeled simultaneously.
                         This model can also be used to estimate individual muscle forces and joint moments of different
                       populations, including healthy subjects, poststroke patients, osteoarthritis patients, etc. (Buchanan
                       et al., 2005; Bassett et al., 2006). This approach may reveal underlying neuromuscular principles that
                       are important for clinicians and physical therapists. Since EMG-driven models can be used to pre-
                       dict novel trials, they can be employed to calculate the muscle activation patterns for a stroke patient
                       needed to achieve a desired healthy joint moment profile (Shao and Buchanan, 2006). These calcu-
                       lated corrective changes in muscle activation patterns can be used as reference data to derive appro-
                       priate stimulation patterns, which can be applied in stroke patients’ gait training with functional
                       electrical stimulation.
                         This modeling approach has also been used to study the contribution of soft tissues to knee
                       varus/valgus moment during static tasks (Lloyd and Buchanan, 1996). In the future, a ligament
                       model can be incorporated into the EMG-driven model to study ligament forces and joint contact
                       forces during dynamic movements. This may give us more information about the knee mechanics of
                       healthy subjects, anterior cruciate ligament deficient patients, or osteoarthritis patients.



           REFERENCES

                       Basmajian, J. V., and C. J. De Luca (1985), Muscles Alive: Their Functions Revealed by Electromyography.
                         Baltimore, Williams & Wilkins.
                       Bassett, D. N., J. D. Gardinier, et al. (2006), Estimation of muscle forces about the ankle during gait in healthy
                         and neurologically impaired subjects. In: Computational Intelligence for Movement Sciences. Begg, R. K.
                         and M. Palaniswami (eds.). Hershey, PA, Idea Group, pp. 320–347.
                       Bassett, D. N., K. Manal, et al. (2006), Single joint versus multiple joint modeling using a hybrid EMG-driven
                         approach. Proc Am Soc Biomech, 30, (CD).
                       Bouisset, S., and F. Goubel (1971), Interdependence of relations between integrated EMG and diverse biome-
                         chanical quantities in normal voluntary movements. Act Nerv Super (Praha), 13(1):23–31.
                       Buchanan, T. S., D. G. Lloyd, et al. (2004), Neuromusculoskeletal modeling: estimation of muscle forces and
                         joint moments and movements from measurements of neural command. J Appl Biomech, 20(4):367–395.
                       Buchanan, T. S., D. G. Lloyd, et al. (2005), Estimation of muscle forces and joint moments using a forward-
                         inverse dynamics model. Med Sci Sports Exerc, 37(11):1911–1916.
                       Buchanan, T. S., M. J. Moniz, et al. (1993), Estimation of muscle forces about the wrist joint during isometric
                         tasks using an EMG coefficient method. J Biomech, 26(4–5):547–560.
                       Buchanan, T. S., and D. A. Shreeve (1996), An evaluation of optimization techniques for the prediction of muscle
                         activation patterns during isometric tasks. J Biomech Eng, 118(4):565–574.
                       Cram, J. R., and A. Garber (1986), The relationship between narrow and wide bandwidth filter settings during an
                         EMG scanning procedure. Biofeedback and Self-Regulation, 11(2):105–114.
                       Crowninshield, R. D. (1978), Use of optimization techniques to predict muscle forces. J Biomech Eng-Trans
                         Asme, 100(2):88–92.
                       Crowninshield, R. D., and R. A. Brand (1981), A physiologically based criterion of muscle force prediction in
                         locomotion. J Biomech, 14(11):793–801.
                       De Duca, C. J., and W. J. Forrest (1973), Force analysis of individual muscles acting simultaneously on the shoulder
                         joint during isometric abduction. J Biomech, 6(4):385–393.
                       De Luca, C. J. (1997), The use of surface electromyography in biomechanics. J Appl Biomech, 13(2):135–163.
                       De Luca, C. J., and E. J. Vandyk (1975), Derivation of some parameters of myoelectric signals recorded during
                         sustained constant force isometric contractions. Biophys J, 15(12):1167–1180.
                       Delp, S. L., J. P. Loan, et al. (1990), An interactive graphics-based model of the lower extremity to study
                         orthopaedic surgical procedures. IEEE Trans Biomed Eng, 37(8):757–767.
                       Dul, J., G. E. Johnson, et al. (1984), Muscular synergism .2. A minimum-fatigue criterion for load sharing
                         between synergistic muscles. J Biomech, 17(9):675–684.
   322   323   324   325   326   327   328   329   330   331   332