A model-based analysis of the mechanical cost of walking on uneven terrain

Human walking on uneven terrain is energetically more expensive than on flat, even ground. This is in part due to increases in, and redistribution of positive work among lower limb joints. To improve understanding of the mechanical adaptations, we performed analytical and computational analyses of simple mechanical models walking over uneven terrain comprised of alternating up and down steps of equal height. We simulated dynamic walking models using trailing leg push-off and/or hip torque to power gait, and quantified the compensatory work costs vs. terrain height. We also examined the effect of swing leg dynamics by including and excluding them from the model. We found that greater work, increasing approximately quadratically with uneven terrain height variations, was necessary to maintain a prescribed average forward speed. Greatest economy was achieved by modulating precisely-timed push-offs for each step height. Least economy was achieved with hip power, which did not require as precise timing. This compares well with observations of humans on uneven terrain, showing similar near-normal push-off but with more variable step timing, and considerably more hip work. These analyses suggest how mechanical work and timing could be adjusted to compensate for real world environments.

[1]  Hakan Temeltas,et al.  Anticipatory Control of Momentum for Bipedal Walking on Uneven Terrain , 2019, bioRxiv.

[2]  R. Kram,et al.  Mechanical and metabolic determinants of the preferred step width in human walking , 2001, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[3]  Arthur D Kuo,et al.  Energetics of actively powered locomotion using the simplest walking model. , 2002, Journal of biomechanical engineering.

[4]  D. Winter,et al.  Kinetic analysis of the lower limbs during walking: what information can be gained from a three-dimensional model? , 1995, Journal of biomechanics.

[5]  Torsten Bumgarner,et al.  Biomechanics and Motor Control of Human Movement , 2013 .

[6]  Hakan Temeltas,et al.  Optimal regulation of bipedal walking speed despite an unexpected bump in the road , 2018, PloS one.

[7]  S E H Davies,et al.  The energetics of walking on sand and grass at various speeds , 2006, Ergonomics.

[8]  Daniel P. Ferris,et al.  Biomechanics and energetics of walking on uneven terrain , 2013, Journal of Experimental Biology.

[9]  Andre Seyfarth,et al.  Does a crouched leg posture enhance running stability and robustness? , 2011, Journal of theoretical biology.

[10]  Andy Ruina,et al.  Energetic Consequences of Walking Like an Inverted Pendulum: Step-to-Step Transitions , 2005, Exercise and sport sciences reviews.

[11]  R. F. Goldman,et al.  Terrain coefficients for energy cost prediction. , 1972, Journal of applied physiology.

[12]  A. Kuo,et al.  Energetic cost of producing cyclic muscle force, rather than work, to swing the human leg , 2007, Journal of Experimental Biology.

[13]  Roland Siegwart,et al.  A MATLAB framework for efficient gait creation , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  Katie Byl,et al.  Metastable Walking Machines , 2009, Int. J. Robotics Res..

[15]  Daniel P. Ferris,et al.  Metabolic and mechanical energy costs of reducing vertical center of mass movement during gait. , 2009, Archives of physical medicine and rehabilitation.

[16]  D. Winter,et al.  Quantitative assessment of co-contraction at the ankle joint in walking. , 1985, Electromyography and clinical neurophysiology.

[17]  K B Pandolf,et al.  Metabolic energy expenditure and terrain coefficients for walking on snow. , 1976, Ergonomics.

[18]  M. Coleman,et al.  The simplest walking model: stability, complexity, and scaling. , 1998, Journal of biomechanical engineering.

[19]  J. Dingwell,et al.  Dynamic stability of passive dynamic walking on an irregular surface. , 2007, Journal of biomechanical engineering.

[20]  R. McN. Alexander,et al.  Simple Models of Human Movement , 1995 .

[21]  John R. Rebula,et al.  The Cost of Leg Forces in Bipedal Locomotion: A Simple Optimization Study , 2015, PloS one.

[22]  A. Kuo A simple model of bipedal walking predicts the preferred speed-step length relationship. , 2001, Journal of biomechanical engineering.

[23]  A. Kuo,et al.  Human walking isn't all hard work: evidence of soft tissue contributions to energy dissipation and return , 2010, Journal of Experimental Biology.

[24]  T. McMahon,et al.  Ballistic walking. , 1980, Journal of biomechanics.

[25]  P. Willems,et al.  Mechanics and energetics of human locomotion on sand. , 1998, The Journal of experimental biology.

[26]  Katie Byl,et al.  Metastable Walking on Stochastically Rough Terrain , 2008, Robotics: Science and Systems.

[27]  L. Koziris,et al.  The American Journal of Sports Medicine , 2004 .

[28]  A. Kuo,et al.  Mechanical and energetic consequences of reduced ankle plantar-flexion in human walking , 2015, Journal of Experimental Biology.

[29]  B Dawson,et al.  The energy cost of running on grass compared to soft dry beach sand. , 2001, Journal of science and medicine in sport.

[30]  Tad McGeer,et al.  Passive Dynamic Walking , 1990, Int. J. Robotics Res..

[31]  Levi J. Hargrove,et al.  Gait Characteristics When Walking on Different Slippery Walkways , 2016, IEEE Transactions on Biomedical Engineering.

[32]  A. Hof Scaling gait data to body size , 1996 .

[33]  Susanne W. Lipfert,et al.  Upright human gait did not provide a major mechanical challenge for our ancestors. , 2010, Nature communications.

[34]  Shawn J. Scott,et al.  Frontal plane dynamic margins of stability in individuals with and without transtibial amputation walking on a loose rock surface. , 2013, Gait & posture.

[35]  Mark Snaterse,et al.  Distinct fast and slow processes contribute to the selection of preferred step frequency during human walking. , 2011, Journal of applied physiology.

[36]  R. Margaria Positive and negative work performances and their efficiencies in human locomotion , 1968, Internationale Zeitschrift für angewandte Physiologie einschließlich Arbeitsphysiologie.