ReviewBiomechanics and muscle coordination of human walking: Part I: Introduction to concepts, power transfer, dynamics and simulations
Introduction
Humans use their legs most frequently to stand and locomote. Walking is a task that we seek to understand well because it is a most relevant task to humans. This two-part review focuses on the biomechanics and muscle coordination of the legs in healthy adults while walking (for standing, see Ref. [1]). Studies of human locomotion have a long history [2], [3] and current understanding results from the ability to measure EMG activity with surface and indwelling electrodes [4], [5], [6], [7] along with the kinematics of the body and the ground reaction force [8]. However, the causal relationships between the measured output variables, such as the kinematics and kinetics, and the measured input variables, such as the pattern of EMG activity, must be determined to further our understanding. Unfortunately, the establishment of these relationships to understand muscle coordination of walking is difficult because many body segments, including the trunk, are being coordinated. Complexity is further enhanced because any one muscle may affect the acceleration and power of all body segments because of dynamical coupling [9].
We and others [10], [11], [12] believe that muscle-based simulations of the walking dynamics are critical to the determination of the causal relationships between EMG patterns and gait kinematics and kinetics. Indeed, simulations have been the cornerstone to the understanding and design of complex multi-input/-output dynamical mechanical systems, such as aircraft, satellites, and weather forecasting. This two-part review emphasizes how simulations of walking from dynamical musculoskeletal models can lead to a comprehension of muscle coordination (see also Ref. [13]).
Before simulation-based coordination principles of walking are reviewed in Part II, this Part I reviews basic kinetic concepts and the advantages and limitations of both traditional Newton–Euler inverse dynamics analyses and dynamical simulations in understanding muscle coordination. Because of the simplicity of the dynamics of pedaling compared to walking, analyses of pedaling simulations are used to show how coordination principles can be deduced from muscle-induced acceleration and segmental power analyses. Emphasis is given to the identification of muscle synergies (i.e. co-excited muscles acting to accelerate the segments differently to accomplish a common task goal), co-functional muscles (i.e. co-excited muscles acting to accelerate the segments similarly), and the redistribution of mechanical energy among the segments caused by individual muscle force generation.
Section snippets
Net joint moment, joint intersegmental force, segmental power
A net joint moment is the sum of the individual moments about a joint from the forces developed by muscles and other structures crossing that joint, such as ligaments, as well as those moments due to bone and cartilage contact between segments. When the net joint moment arises primarily from muscles, it is called the ‘net muscle moment about the joint’. Net joint moments are often used to assess coordination of movement because their genesis is the muscle forces to a large extent.
The joint
Net joint power and individual muscle power
Net joint power is a kinetic quantity computed by multiplying the net joint moment by the joint angular velocity or, equivalently, by the difference in angular velocities of the adjoining segments:whereand ω1, ω2 are the angular velocities of the two segments in an inertial reference frame (Fig. 1).
Net joint power is useful because it represents the summed power by the net joint
Muscle contribution to joint intersegmental force and segmental acceleration and power
The force generated by a muscle acts to accelerate instantaneously not only the segments to which it attaches and the joints that it spans, but also all other segments and joints [9], [21]. For example, when the foot is on the ground, the uniarticular soleus (SOL) acts to accelerate instantaneously the shank and the foot, segments to which it attaches (Fig. 1), and the thigh and trunk, segments to which it does not attach (Fig. 2). Similarly, SOL not only acts to accelerate the spanned ankle
Transfer of power among segments
It is important to recognize that the primary function of a muscle can be to simply redistribute energy among segments rather than produce or dissipate energy. The redistribution of segmental energy results because the force generated by a muscle creates simultaneous segment accelerations and decelerations throughout the body. Muscle force can cause significant segmental energy redistribution irrespective of whether the muscle produces mechanical work output by shortening (acting
Transfer of power from one joint to another by a biarticular muscle: What does it mean?
The concept of a transfer of power by a biarticular muscle from one of its spanned joints to the other [19], [20], [30], [31], [32], [33], which is based on , , , , implies that a biarticular muscle can only accelerate/decelerate the segments of origin and insertion and the segment spanned. However, as noted above, a biarticular muscle, like a uniarticular muscle, affects the power of all the body segments because it contributes to all intersegmental forces. Thus, inferences of muscle
Inverse dynamics to compute net joint moments and powers, joint intersegmental and contact forces, and individual muscle forces
The traditional Newton–Euler inverse dynamics method is commonly employed in locomotion analyses to compute the net joint moments, net joint powers, and net joint intersegmental forces (see reviews [11], [31], [39], [40], [41]). The foot, shank and thigh are assumed to be rigid body segments connected by joint articulations. Measured ground reaction forces and observed or estimated segmental accelerations are inserted into the Newton–Euler equations of motion (), starting at the
Limitation of inverse dynamics in understanding muscle coordination
One limitation of the traditional Newton–Euler inverse dynamics method is the uncertainty in estimates of mechanical energy expenditure by muscles based on segmental energy flow computations. Uncertainty exists because of intercompensation due to biarticular muscles and the recovery of stored elastic energy [81], [82], [83], [84], [85], [86]. Though attempts can be made to account for these effects in the calculation of mechanical energy expenditure [87], [88], substantial problems still exist
Understanding muscle coordination with dynamical models and simulations
The key to understanding muscle coordination is to find the contributions of individual muscles to the movement of the individual body segments and objects in contact with the body. A major step toward fulfilling this objective is to find the instantaneous contributions of individual muscles to the acceleration and power of the segments. Various approaches can be used to find the instantaneous contributions by individual muscles or individual net joint moments. In each of the approaches a
Generating dynamical simulations
One of the most difficult aspects of generating muscle-driven dynamical simulations compatible with experimentally observed kinesiological measurements is finding an appropriate muscle excitation pattern. Using EMG measurements as the excitation inputs is rarely successful due to the lack of fidelity in the EMG measurements and the inaccuracies in the dynamical properties of the musculoskeletal model. Therefore, two primary approaches have been employed to find the muscle excitation
Limitation of dynamical simulations
An important feature of a simulation derived from a dynamical model of the body is the ability to systematically study the sensitivity of the conclusions of an investigation to uncertainty in model parameters, or even in the structure of the model itself. Thus, investigators using simulations have the ability to assess their confidence in the muscle coordination principles advocated.
The importance of performing sensitivity studies to ascertain the level of confidence in the conclusions on
Deducing coordination by analyzing muscle-induced segmental powers and accelerations
A major step toward understanding muscle coordination of a multisegmented body is to analyze the role of individual muscles in accelerating the segments and controlling the energy flow among the segments. In this Part I, we illustrate how muscle-induced accelerations and powers can be analyzed to understand coordination of seated pedaling rather than walking because of the relative dynamic simplicity of pedaling. Pedaling has fewer mechanical degrees-of-freedom because the hips can be
Limitation of muscle-induced acceleration and power analyses
Though segmental acceleration and power found in dynamical simulations can be decomposed into the instantaneous contributions from individual muscle and gravity forces acting on the body segments, for example, the 1st and 2nd terms on the right-hand side of Eq. (5), the deduction of coordination principles from these decompositions must proceed with caution. The muscle-induced accelerations and powers are a snap-shot in time of the contributions of individual forces acting on the body segments
Concluding remarks
The major goals of this Part I review were to critique methods used to deduce muscle coordination principles in human walking, and use pedaling to show how dynamical simulations can elucidate principles of coordination of leg muscles. The utility of a dynamical simulation is not in the simulation per se, but rather in the analyses of the simulation data. Simulation analyses can determine the mechanical energy produced by each muscle, the energy stored in musculotendon elastic elements, and the
Acknowledgements
Supported by the Rehabilitation R&D Service of the Department of Veterans Affairs (VA) and NIH grant NS17662. We thank Scott Delp and Art Kuo for their very constructive comments on an earlier draft.
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