Validation of Hill-type muscle models in relation to neuromuscular recruitment and force-velocity properties: predicting patterns of in vivo muscle force.

We review here the use and reliability of Hill-type muscle models to predict muscle performance under varying conditions, ranging from in situ production of isometric force to in vivo dynamics of muscle length change and force in response to activation. Muscle models are frequently used in musculoskeletal simulations of movement, particularly when applied to studies of human motor performance in which surgically implanted transducers have limited use. Musculoskeletal simulations of different animal species also are being developed to evaluate comparative and evolutionary aspects of locomotor performance. However, such models are rarely validated against direct measures of fascicle strain or recordings of muscle-tendon force. Historically, Hill-type models simplify properties of whole muscle by scaling salient properties of single fibers to whole muscles, typically accounting for a muscle's architecture and series elasticity. Activation of the model's single contractile element (assigned the properties of homogenous fibers) is also simplified and is often based on temporal features of myoelectric (EMG) activation recorded from the muscle. Comparison of standard one-element models with a novel two-element model and with in situ and in vivo measures of EMG, fascicle strain, and force recorded from the gastrocnemius muscles of goats shows that a two-element Hill-type model, which allows independent recruitment of slow and fast units, better predicts temporal patterns of in situ and in vivo force. Recruitment patterns of slow/fast units based on wavelet decomposition of EMG activity in frequency-time space are generally correlated with the intensity spectra of the EMG signals, the strain rates of the fascicles, and the muscle-tendon forces measured in vivo, with faster units linked to greater strain rates and to more rapid forces. Using direct measures of muscle performance to further test Hill-type models, whether traditional or more complex, remains critical for establishing their accuracy and essential for verifying their applicability to scientific and clinical studies of musculoskeletal function.

[1]  Full,et al.  Static forces and moments generated in the insect leg: comparison of a three-dimensional musculo-skeletal computer model with experimental measurements , 1995, The Journal of experimental biology.

[2]  Matthew Millard,et al.  Flexing computational muscle: modeling and simulation of musculotendon dynamics. , 2013, Journal of biomechanical engineering.

[3]  R. Baudinette,et al.  In vivo muscle force and elastic energy storage during steady-speed hopping of tammar wallabies (Macropus eugenii) , 1995, The Journal of experimental biology.

[4]  G J Ettema,et al.  A simulation of rat edl force output based on intrinsic muscle properties. , 1988, Journal of biomechanics.

[5]  M. Pandy,et al.  Individual muscle contributions to support in normal walking. , 2003, Gait & posture.

[6]  C. Heckman,et al.  Hill muscle model errors during movement are greatest within the physiologically relevant range of motor unit firing rates. , 2003, Journal of biomechanics.

[7]  D. Thelen Adjustment of muscle mechanics model parameters to simulate dynamic contractions in older adults. , 2003, Journal of biomechanical engineering.

[8]  C. Heckman,et al.  Force from cat soleus muscle during imposed locomotor-like movements: experimental data versus Hill-type model predictions. , 1997, Journal of neurophysiology.

[9]  Vinzenz von Tscharner,et al.  Intensity analysis in time-frequency space of surface myoelectric signals by wavelets of specified resolution , 2000 .

[10]  R R Neptune,et al.  Relationships between muscle contributions to walking subtasks and functional walking status in persons with post-stroke hemiparesis. , 2011, Clinical biomechanics.

[11]  N. Emery,et al.  Tyrannosaurus was not a fast runner , 2002 .

[12]  Ajay Seth,et al.  Muscle contributions to propulsion and support during running. , 2010, Journal of biomechanics.

[13]  James M Wakeling,et al.  Motor unit recruitment patterns 2: the influence of myoelectric intensity and muscle fascicle strain rate , 2008, Journal of Experimental Biology.

[14]  Andrew H Hansen,et al.  Response of able-bodied persons to changes in shoe rocker radius during walking: changes in ankle kinematics to maintain a consistent roll-over shape. , 2010, Journal of biomechanics.

[15]  A. McComas,et al.  A comparison of the contractile properties of the human gastrocnemius and soleus muscles , 2004, European Journal of Applied Physiology and Occupational Physiology.

[16]  J. Reinbolt,et al.  Mechanisms of improved knee flexion after rectus femoris transfer surgery. , 2009, Journal of biomechanics.

[17]  T. Roberts,et al.  Variable gearing in pennate muscles , 2008, Proceedings of the National Academy of Sciences.

[18]  Jeffery W. Rankin,et al.  INTEGRATING EXPERIMENTAL AND COMPUTER SIMULATION METHODS TO RECONSTRUCT THE EVOLUTION OF AVIAN BIPEDALISM , 2014 .

[19]  Maarten F. Bobbert,et al.  The contribution of muscle properties in the control of explosive movements , 1993, Biological Cybernetics.

[20]  A. Biewener,et al.  Patterns of strain and activation in the thigh muscles of goats across gaits during level locomotion , 2005, Journal of Experimental Biology.

[21]  Benno M. Nigg,et al.  Surface EMG shows distinct populations of muscle activity when measured during sustained sub-maximal exercise , 2001, European Journal of Applied Physiology.

[22]  James M Wakeling,et al.  Motor units are recruited in a task-dependent fashion during locomotion , 2004, Journal of Experimental Biology.

[23]  James M Wakeling,et al.  Wave properties of action potentials from fast and slow motor units of rats , 2002, Muscle & nerve.

[24]  Emanuel Azizi,et al.  Muscle performance during frog jumping: influence of elasticity on muscle operating lengths , 2010, Proceedings of the Royal Society B: Biological Sciences.

[25]  A. A. Biewener,et al.  The effect of fast and slow motor unit activation on whole-muscle mechanical performance: the size principle may not pose a mechanical paradox , 2014, Proceedings of the Royal Society B: Biological Sciences.

[26]  David V. Lee,et al.  Dynamics of goat distal hind limb muscle–tendon function in response to locomotor grade , 2009, Journal of Experimental Biology.

[27]  Andrew A Biewener,et al.  Recruitment of faster motor units is associated with greater rates of fascicle strain and rapid changes in muscle force during locomotion , 2013, Journal of Experimental Biology.

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

[29]  Richard R Neptune,et al.  Muscle work is increased in pre-swing during hemiparetic walking. , 2011, Clinical biomechanics.

[30]  James M. Wakeling,et al.  A Muscle’s Force Depends on the Recruitment Patterns of Its Fibers , 2012, Annals of Biomedical Engineering.

[31]  E. Otten A myocybernetic model of the jaw system of the rat , 1986, Journal of Neuroscience Methods.

[32]  James M Wakeling,et al.  Patterns of motor recruitment can be determined using surface EMG. , 2009, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[33]  E Henneman,et al.  Rank order of motoneurons within a pool: law of combination. , 1974, Journal of neurophysiology.

[34]  Scott L Delp,et al.  Generating dynamic simulations of movement using computed muscle control. , 2003, Journal of biomechanics.

[35]  Andrew A Biewener,et al.  EMG analysis tuned for determining the timing and level of activation in different motor units. , 2011, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[36]  C. Maganaris,et al.  In vivo measurements of the triceps surae complex architecture in man: implications for muscle function , 1998, The Journal of physiology.

[37]  William J Kargo,et al.  Jumping in frogs: assessing the design of the skeletal system by anatomically realistic modeling and forward dynamic simulation. , 2002, The Journal of experimental biology.

[38]  Sabrina S. M. Lee,et al.  Movement mechanics as a determinate of muscle structure, recruitment and coordination , 2011, Philosophical Transactions of the Royal Society B: Biological Sciences.

[39]  Ayman Habib,et al.  OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement , 2007, IEEE Transactions on Biomedical Engineering.

[40]  J M Wakeling,et al.  Variations in motor unit recruitment patterns occur within and between muscles in the running rat (Rattus norvegicus) , 2007, Journal of Experimental Biology.

[41]  Philip E. Martin,et al.  A Model of Human Muscle Energy Expenditure , 2003, Computer methods in biomechanics and biomedical engineering.

[42]  Andrew A Biewener,et al.  Accuracy of gastrocnemius muscles forces in walking and running goats predicted by one-element and two-element Hill-type models. , 2013, Journal of biomechanics.

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

[44]  James M. Wakeling,et al.  Motor unit recruitment for dynamic tasks: current understanding and future directions , 2008, Journal of Comparative Physiology B.

[45]  James M Wakeling,et al.  Spectral properties of myoelectric signals from different motor units in the leg extensor muscles , 2004, Journal of Experimental Biology.