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Foot force direction in an isometric pushing task: prediction by kinematic and musculoskeletal models

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Abstract

The abilities of a kinematic model and a muscle model of the human lower limb to predict the stereotyped direction of the muscular component of foot force produced by seated subjects in a static task were tested and compared. Human subjects (n=11) performed a quasi-static, lower-limb pushing task against an instrumented bicycle pedal, free to rotate about its own axis, but with the crank fixed. Each pushing trial consisted of applying a force from the resting level to a force magnitude target with the right foot. Ten force target magnitudes were used (200, 250, …, 650 N) along with 12 pedal positions. For each pushing effort, the muscular contribution to the measured foot force was determined from push onset to peak attained force. This segment was well characterized by a straight line across subjects, pedal positions, and force target magnitudes. The linear nature of the muscular component allowed a characteristic direction to be determined for each trial. A three-joint (hip, knee, and ankle) and a two-joint (hip and knee) net joint torque optimization was applied to a sagittal-plane kinematic model to predict the characteristic force direction. A musculoskeletal model was also used to create a feasible force space (FFS) for the lower limb. This FFS represents the range of possible forces the lower limb could theoretically produce. From this FFS, the direction of the maximum feasible foot force was determined and compared with the characteristic direction of subject performance. The muscle model proved to be the most effective in predicting subject force direction, followed by the three-joint and two-joint net joint torques optimizations. Similarities between the predictions of the kinematic and muscle model were also found.

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References

  • Anderson FC, Pandy MG (2001) Static and dynamic optimization solutions for gait are practically equivalent. J Biomech 34:153–161

    CAS  PubMed  Google Scholar 

  • Andrews JG (1983) Biomechanical measures of muscular effort. Med Sci Sports Exerc 15:199–207

    CAS  PubMed  Google Scholar 

  • Bernstein NA (1967) The co-ordination and regulation of movements. Pergamon Press, Oxford

  • Brand RA, Pedersen DR, Friederich JA (1986) The sensitivity of muscle force prediction to changes in physiologic cross-sectional area. J Biomech 19:589–596

    CAS  PubMed  Google Scholar 

  • Buchanan TS, Shreeve DA (1996) An evaluation of optimization techniques for the prediction of muscle activation patterns during isometric tasks. J Biomech Eng 118:565–574

    CAS  PubMed  Google Scholar 

  • Chang YH, Huang HW, Hamerski CM, Kram R (2000) The independent effects of gravity and inertia on running mechanics. J Exp Biol 203:229–238

    PubMed  Google Scholar 

  • Fisher LD, Belle G van (1993) Principal component analysis and factor analysis. Biostatistics: a methodology for the health sciences. Wiley, New York

  • Friederich JA, Brand RA (1990) Muscle fiber architecture in the human lower limb. J Biomech 23:91–95

    CAS  PubMed  Google Scholar 

  • Gribble PL, Ostry DJ (1996) Origins of the power law relation between movement velocity and curvature: modeling the effects of muscle mechanics and limb dynamics. J Neurophysiol 76:2853–2860

    CAS  PubMed  Google Scholar 

  • Gruben KG, López-Ortiz C (2000) Characteristics of the force applied to a pedal during human pushing efforts: Emergent linearity. J Mot Behav 32:151–162

    CAS  PubMed  Google Scholar 

  • Gruben KG, Lopez-Ortiz C, Schmidt MW (2003) The control of foot force during pushing efforts against a moving pedal. Exp Brain Res 148:50–61

    Article  PubMed  Google Scholar 

  • Hogan N, Bizzi E, Mussa-Ivaldi FA, Flash T (1987) Controlling multijoint motor behavior. Exerc Sport Sci Rev 15:153–190

    CAS  PubMed  Google Scholar 

  • Hollerbach JM, Flash T (1982) Dynamic interactions between limb segments during planar arm movements. Biol Cybern 44:67–77

    CAS  PubMed  Google Scholar 

  • Hull ML, Gonzalez H (1988) Bivariate optimization of pedalling rate and crank arm length in cycling. J Biomech 21: 839–849

    CAS  PubMed  Google Scholar 

  • Hull ML, Gonzalez HK, Redfield R (1988) Optimization of pedalling rate in cycling using a muscle stress-based objective function. Int J Sport Biomech 4:1-20

    Google Scholar 

  • Jacobs R, Ingen Schenau GJ van (1992) Control of an external force in leg extensions in humans. J Physiol (Lond) 457:611–626

    Google Scholar 

  • Kautz SA, Hull ML (1993) A theoretical basis for interpreting the force applied to the pedal during cycling. J Biomech 26:155–165

    CAS  PubMed  Google Scholar 

  • Kuo AD, Zajac FE (1993) A biomechanical analysis of muscle strength as a limiting factor in standing posture. J Biomech 26 (Suppl 1):137–150

    PubMed  Google Scholar 

  • Massey JT, Lurito JT, Pellizzer G, Georgopoulos AP (1992) Three-dimensional drawings in isometric conditions: relation between geometry and kinematics. Exp Brain Res 88:685–690

    CAS  PubMed  Google Scholar 

  • Morasso P (1981) Spatial control of arm movements. Exp Brain Res 42:223–227

    CAS  PubMed  Google Scholar 

  • Plagenhoef S, Evans FG Abdelnour T (1983) Anatomical data for analyzing human motion. Res Q Exerc Sport 54:169–178

    Google Scholar 

  • Prilutsky BI (2000) Coordination of two- and one-joint muscles: functional consequences and implications for motor control. Motor Control 4:1-44

    CAS  PubMed  Google Scholar 

  • Prilutsky BI, Gregor RJ (1997) Strategy of coordination of two- and one-joint leg muscles in controlling an external force. Motor Control 1:92–116

    Google Scholar 

  • Prilutsky BI, Gregor RJ (2000) Analysis of muscle coordination strategies in cycling. IEEE Trans Rehab Eng 8:362–370

    Article  CAS  Google Scholar 

  • Raasch CC, Zajac FE (1999) Locomotor strategy for pedaling: muscle groups and biomechanical functions. J Neurophysiol 82:515–525

    CAS  PubMed  Google Scholar 

  • Redfield R, Hull ML (1986a) On the relation between joint moments and pedalling rates at constant power in bicycling. J Biomech 19:317–329

    CAS  PubMed  Google Scholar 

  • Redfield R, Hull ML (1986b) Prediction of pedal forces in bicycling using optimization methods. J Biomech 19:523–540

    CAS  PubMed  Google Scholar 

  • Rugg SG, Gregor RJ, Mandelbaum BR, Chiu L (1990) In vivo moment arm calculations at the ankle using magnetic resonance imaging (MRI). J Biomech 23:495–501

    CAS  PubMed  Google Scholar 

  • Valero-Cuevas FJ (2000) Predictive modulation of muscle coordination pattern magnitude scales fingertip force magnitude over the voluntary range. J Neurophysiol 83:1469–1479

    CAS  PubMed  Google Scholar 

  • Van Bolhuis BM, Gielen CCAM (1999) A comparison of models explaining muscle activation patterns for isometric contractions. Biol Cybern 81:249–261

    Article  PubMed  Google Scholar 

  • Visser JJ, Hoogkamer JE, Bobbert MF, Huying PA (1990) Length and moment arm of human leg muscles as a function of knee and hip joint angles. Eur J Appl Physiol 61:451–460

    Google Scholar 

  • Wickiewicz TL, Roy RR, Powell PL, Edgerton VR (1983) Muscle architecture of the human lower-limb. Clin Orthop Rel Res 275–283

  • Winter DA (1990) Biomechanics and motor control of human movement, 2nd Edn. Wiley, New York

  • Yang JF, Winter DA, Wells RP (1990) Postural dynamics of walking in humans. Biol Cybern 62:321–330

    CAS  PubMed  Google Scholar 

  • Zajac FE (1989) Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit Rev Biomed Eng 17:359–411

    CAS  PubMed  Google Scholar 

  • Zajac FE, Neptune RR, Kautz SA (2002) Biomechanics and muscle coordination of human walking. Part I: Introduction to concepts, power transfer, dynamics and simulations. Gait Posture 16:215–232

    Article  PubMed  Google Scholar 

  • Zajac FE, Neptune RR, Kautz SA (2003) Biomechanics and muscle coordination of human walking. Part II: Lessons from dynamical simulations and clinical implications. Gait Posture 17:1–17

    Article  PubMed  Google Scholar 

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Acknowledgements

This study was supported in part by the Virginia Horne Henry Fund. The authors would like to acknowledge the help of Jo-Anne Lazarus, Victoria Moerchen, and Mitch Tyler.

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Correspondence to M. W. Schmidt.

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Schmidt, M.W., López-Ortiz, C., Barrett, P.S. et al. Foot force direction in an isometric pushing task: prediction by kinematic and musculoskeletal models. Exp Brain Res 150, 245–254 (2003). https://doi.org/10.1007/s00221-003-1462-0

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