Dynamic optimization of human walking.

A three-dimensional, neuromusculoskeletal model of the body was combined with dynamic optimization theory to simulate normal walking on level ground. The body was modeled as a 23 degree-of-freedom mechanical linkage, actuated by 54 muscles. The dynamic optimization problem was to calculate the muscle excitation histories, muscle forces, and limb motions subject to minimum metabolic energy expenditure per unit distance traveled. Muscle metabolic energy was calculated by slimming five terms: the basal or resting heat, activation heat, maintenance heat, shortening heat, and the mechanical work done by all the muscles in the model. The gait cycle was assumed to be symmetric; that is, the muscle excitations for the right and left legs and the initial and terminal states in the model were assumed to be equal. Importantly, a tracking problem was not solved. Rather only a set of terminal constraints was placed on the states of the model to enforce repeatability of the gait cycle. Quantitative comparisons of the model predictions with patterns of body-segmental displacements, ground-reaction forces, and muscle activations obtained from experiment show that the simulation reproduces the salient features of normal gait. The simulation results suggest that minimum metabolic energy per unit distance traveled is a valid measure of walking performance.

[1]  J. Saunders,et al.  The major determinants in normal and pathological gait. , 1953, The Journal of bone and joint surgery. American volume.

[2]  W. Mommaerts Energetics of muscular contraction. , 1969, Physiological reviews.

[3]  D. Jacobson,et al.  Studies of human locomotion via optimal programming , 1971 .

[4]  R L Waters,et al.  Electrical activity of muscles of the trunk during walking. , 1972, Journal of anatomy.

[5]  E. Homsher,et al.  Energetics of Shortening Muscles in Twitches and Tetanic Contractions , 1973, The Journal of general physiology.

[6]  Energetics of Shortening Muscles in Twitches and Tetanic Contractions , 1973, The Journal of general physiology.

[7]  H. Ralston Energetics of Human Walking , 1976 .

[8]  C. E. Clauser,et al.  Anthropometric Relationships of Body and Body Segment Moments of Inertia , 1980 .

[9]  S R Simon,et al.  An evaluation of the approaches of optimization models in the prediction of muscle forces during human gait. , 1981, Journal of biomechanics.

[10]  R. Crowninshield,et al.  A physiologically based criterion of muscle force prediction in locomotion. , 1981, Journal of biomechanics.

[11]  R. Burdett,et al.  Comparison of mechanical work and metabolic energy consumption during normal gait , 1983, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[12]  G. Cavagna,et al.  Mechanical work, oxygen consumption, and efficiency in isolated frog and rat muscle. , 1987, The American journal of physiology.

[13]  M L Audu,et al.  A dynamic optimization technique for predicting muscle forces in the swing phase of gait. , 1987, Journal of biomechanics.

[14]  F. Zajac Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. , 1989, Critical reviews in biomedical engineering.

[15]  F.E. Zajac,et al.  Restoring unassisted natural gait to paraplegics via functional neuromuscular stimulation: a computer simulation study , 1990, IEEE Transactions on Biomedical Engineering.

[16]  M G Pandy,et al.  A parameter optimization approach for the optimal control of large-scale musculoskeletal systems. , 1992, Journal of biomechanical engineering.

[17]  T. Hulland CHAPTER 2 – Muscle and Tendon , 1993 .

[18]  M G Pandy,et al.  Application of high-performance computing to numerical simulation of human movement. , 1995, Journal of biomechanical engineering.

[19]  P. Huijing,et al.  Parameter interdependence and success of skeletal muscle modelling , 1995 .

[20]  W Baumann,et al.  The three-dimensional determination of internal loads in the lower extremity. , 1997, Journal of biomechanics.

[21]  R. Brand,et al.  Pelvic muscle and acetabular contact forces during gait. , 1997, Journal of biomechanics.

[22]  M. Pandy,et al.  A Dynamic Optimization Solution for Vertical Jumping in Three Dimensions. , 1999, Computer methods in biomechanics and biomedical engineering.

[23]  M. Pandy,et al.  The Obstacle-Set Method for Representing Muscle Paths in Musculoskeletal Models , 2000, Computer methods in biomechanics and biomedical engineering.

[24]  M G Pandy,et al.  Computer modeling and simulation of human movement. , 2001, Annual review of biomedical engineering.

[25]  M G Pandy,et al.  Static and dynamic optimization solutions for gait are practically equivalent. , 2001, Journal of biomechanics.