All joint moments significantly contribute to trunk angular acceleration.

Computationally advanced biomechanical analyses of gait demonstrate the often counter-intuitive roles of joint moments on various aspects of gait such as propulsion, swing initiation, and balance. Each joint moment can produce linear and angular acceleration of all body segments (including those on which the moment does not directly act) due to the dynamic coupling inherent in the interconnected musculoskeletal system. This study presents quantitative relationships between individual joint moments and trunk control with respect to balance during gait to show that the ankle, knee, and hip joint moments all affect the angular acceleration of the trunk. We show that trunk angular acceleration is affected by all joints in the leg with varying degrees of dependence during the gait cycle. Furthermore, it is shown that inter-planar coupling exists and a two-dimensional analysis of trunk balance neglects important out-of-plane joint moments that affect trunk angular acceleration.

Merging of healthy motor modules predicts reduced locomotor performance and muscle coordination complexity post-stroke.

Evidence suggests that the nervous system controls motor tasks using a low-dimensional modular organization of muscle activation. However, it is not clear if such an organization applies to coordination of human walking, nor how nervous system injury may alter the organization of motor modules and their biomechanical outputs. We first tested the hypothesis that muscle activation patterns during walking are produced through the variable activation of a small set of motor modules. In 20 healthy control subjects, EMG signals from eight leg muscles were measured across a range of walking speeds. Four motor modules identified through nonnegative matrix factorization were sufficient to account for variability of muscle activation from step to step and across speeds. Next, consistent with the clinical notion of abnormal limb flexion-extension synergies post-stroke, we tested the hypothesis that subjects with post-stroke hemiparesis would have altered motor modules, leading to impaired walking performance. In post-stroke subjects (n = 55), a less complex coordination pattern was shown. Fewer modules were needed to account for muscle activation during walking at preferred speed compared with controls. Fewer modules resulted from merging of the modules observed in healthy controls, suggesting reduced independence of neural control signals. The number of modules was correlated to preferred walking speed, speed modulation, step length asymmetry, and propulsive asymmetry. Our results suggest a common modular organization of muscle coordination underlying walking in both healthy and post-stroke subjects. Identification of motor modules may lead to new insight into impaired locomotor coordination and the underlying neural systems.

Gait deviations associated with post-stroke hemiparesis: improvement during treadmill walking using weight support, speed, support stiffness, and handrail hold.

By comparing treadmill walking in hemiparetic and non-disabled individuals at matched speeds, Chen et al. [Chen G, Patten C, Kothari DH, Zajac FE. Gait differences between individuals with post-stroke hemiparesis and non-disabled controls at matched speeds. Gait Posture (2004)] identified gait deviations that were consistent with impaired swing initiation and single limb support in the paretic limb and related compensatory strategies. Treadmill training with harness support is a promising, task-oriented approach to restoring locomotor function in individuals with post-stroke hemiparesis. To provide a rationale for the proper selection of training parameters, we assessed the potential of body weight support, treadmill speed, support stiffness, and handrail hold to improve the identified gait deviations associated with hemiparesis during treadmill walking. In the six hemiparetic subjects studied, the adjustment of each training parameter was found to improve a specific set of the gait deviations. With increased body weight support or the addition of handrail hold, percentage single limb support time on the paretic limb increased and temporal symmetry improved. With increased treadmill speed, leg kinetic energy at toe-off in the paretic limb increased but remained low relative to values in the non-paretic limb. With increased support stiffness, the exaggerated energy cost associated with raising the trunk during pre-swing and swing of the paretic limb was improved. We conclude that the proper selection of training parameters can improve the gait pattern practiced by individuals with hemiparesis during treadmill training and may improve treatment outcome.

Gait differences between individuals with post-stroke hemiparesis and non-disabled controls at matched speeds.

Treadmill walking was used to assess the consistent gait differences between six individuals with post-stroke hemiparesis and six non-disabled, healthy controls at matched speeds. The hemiparetic subjects walked on the treadmill at their comfortable speeds, while each control walked at the same speed as the hemiparetic subject with whom he or she was matched. Kinematic and insole pressure data were collected from multiple, steady-state gait cycles. A large set of gait differences found between hemiparetic and non-disabled subjects was consistent with impaired swing initiation in the paretic limb (i.e., inadequate propulsion of the leg during pre-swing, increased percentage swing time, and reduced knee flexion at toe-off and mid-swing in the paretic limb) and related compensatory strategies (i.e., pelvic hiking and swing-phase propulsion and circumduction of the paretic limb). Exaggerated positive work associated with raising the trunk during pre-swing and swing of the paretic limb, consistent with pelvic hiking, contributed to increased mechanical energetic cost during walking. A second set of gait differences found was consistent with impaired single limb support on the paretic limb (i.e., shortened support time on the paretic limb) and related compensatory strategies (i.e., exaggerated propulsion of the non-paretic limb during pre-swing to shorten its swing time). Other significant gait differences included asymmetry in step length and increased step width. We conclude that consistent gait differences exist between hemiparetic and non-disabled subjects walking at matched speeds. The differences provide insights, concerning hemiparetic impairment and related compensatory strategies, that are in addition to the observation of slow walking speed.

Biomechanics and muscle coordination of human walking: part II: lessons from dynamical simulations and clinical implications.

Principles of muscle coordination in gait have been based largely on analyses of body motion, ground reaction force and EMG measurements. However, data from dynamical simulations provide a cause-effect framework for analyzing these measurements; for example, Part I (Gait Posture, in press) of this two-part review described how force generation in a muscle affects the acceleration and energy flow among the segments. This Part II reviews the mechanical and coordination concepts arising from analyses of simulations of walking. Simple models have elucidated the basic multisegmented ballistic and passive mechanics of walking. Dynamical models driven by net joint moments have provided clues about coordination in healthy and pathological gait. Simulations driven by muscle excitations have highlighted the partial stability afforded by muscles with their viscoelastic-like properties and the predictability of walking performance when minimization of metabolic energy per unit distance is assumed. When combined with neural control models for exciting motoneuronal pools, simulations have shown how the integrative properties of the neuro-musculo-skeletal systems maintain a stable gait. Other analyses of walking simulations have revealed how individual muscles contribute to trunk support and progression. Finally, we discuss how biomechanical models and simulations may enhance our understanding of the mechanics and muscle function of walking in individuals with gait impairments.

Biomechanics and muscle coordination of human walking. Part I: introduction to concepts, power transfer, dynamics and simulations.

Current understanding of how muscles coordinate walking in humans is derived from analyses of body motion, ground reaction force and EMG measurements. This is Part I of a two-part review that emphasizes how muscle-driven dynamics-based simulations assist in the understanding of individual muscle function in walking, especially the causal relationships between muscle force generation and walking kinematics and kinetics. Part I reviews the strengths and limitations of Newton-Euler inverse dynamics and dynamical simulations, including the ability of each to find the contributions of individual muscles to the acceleration/deceleration of the body segments. We caution against using the concept of biarticular muscles transferring power from one joint to another to infer muscle coordination principles because energy flow among segments, even the adjacent segments associated with the joints, cannot be inferred from computation of joint powers and segmental angular velocities alone. Rather, we encourage the use of dynamical simulations to perform muscle-induced segmental acceleration and power analyses. Such analyses have shown that the exchange of segmental energy caused by the forces or accelerations induced by a muscle can be fundamentally invariant to whether the muscle is shortening, lengthening, or neither. How simulation analyses lead to understanding the coordination of seated pedaling, rather than walking, is discussed in this first part because the dynamics of pedaling are much simpler, allowing important concepts to be revealed. We elucidate how energy produced by muscles is delivered to the crank through the synergistic action of other non-energy producing muscles; specifically, that a major function performed by a muscle arises from the instantaneous segmental accelerations and redistribution of segmental energy throughout the body caused by its force generation. Part II reviews how dynamical simulations provide insight into muscle coordination of walking.

Understanding muscle coordination of the human leg with dynamical simulations.

Muscles coordinate multijoint motion by generating forces that cause reaction forces throughout the body. Thus, a muscle can redistribute existing segmental energy by accelerating some segments and decelerating others. In the process, a muscle may also produce or absorb energy, in which case its summed energetic effect on the segments is positive or negative, respectively. This Borelli Lecture shows how dynamical simulations derived from musculoskeletal models reveal muscle-induced segmental energy redistribution and muscle co-functions and synergies. Synergy occurs when co-excited muscles distribute segmental energy differently to execute the motor task. In maximum height jumping, high vertical velocity at lift-off occurs desirably at full body extension because biarticular leg muscles redistribute the energy produced by the uniarticular leg muscles. In pedaling, synergistic ankle plantarflexor force generation during leg extension allows the high energy produced by the uniarticular hip and knee extensors to be delivered to the crank. An analogous less-powerful flexor synergy exists during leg flexion. Hamstrings reduce crank deceleration during the leg extension-to-flexion transition by not only producing energy but delivering it to the crank through its contribution to the tangential (accelerating) crank force, though this hamstrings function occurs at the opposite (flexion-extension) transition when pedaling backwards. In walking, the eccentric quadriceps activity in early stance not only decelerates the leg but also accelerates the trunk. In mid-stance, the uni- and biarticular plantarflexors, by having opposite segmental energetic effects, act in synergy to support the whole body, so segmental potential and kinetic energy exchange can occur. To conclude, the extraction of unmeasurable variables from dynamical simulations emulating task kinematics, kinetics, and EMGs shows how the production of force and energy by individual muscles contribute to the energy flow among the individual segments during task execution.

Nonuniform shortening in the biceps brachii during elbow flexion.

This study tested the common assumption that skeletal muscle shortens uniformly in the direction of its fascicles during low-load contraction. Cine phase contrast magnetic resonance imaging was used to characterize shortening of the biceps brachii muscle in 12 subjects during repeated elbow flexion against 5 and 15% maximum voluntary contraction (MVC) loads. Mean shortening was relatively constant along the anterior boundary of the muscle and averaged 21% for both loading conditions. In contrast, mean shortening was nonuniform along the centerline of the muscle during active elbow flexion. Centerline shortening in the distal region of the biceps brachii (7.3% for 5% MVC and 3.7% for 15% MVC) was significantly less (P < 0.001) than shortening in the muscle midportion (26.3% for 5% MVC and 28.2% for 15% MVC). Nonuniform shortening along the centerline was likely due to the presence of an internal aponeurosis that spanned the distal third of the longitudinal axis of the biceps brachii. However, muscle shortening was also nonuniform proximal to the centerline aponeurosis. Because muscle fascicles follow the anterior contour and centerline of the biceps brachii, our results suggest that shortening is uniform along anterior muscle fascicles and nonuniform along centerline fascicles.