Tim W. Dorn

Muscular strategy shift in human running: dependence of running speed on hip and ankle muscle performance

SUMMARY Humans run faster by increasing a combination of stride length and stride frequency. In slow and medium-paced running, stride length is increased by exerting larger support forces during ground contact, whereas in fast running and sprinting, stride frequency is increased by swinging the legs more rapidly through the air. Many studies have investigated the mechanics of human running, yet little is known about how the individual leg muscles accelerate the joints and centre of mass during this task. The aim of this study was to describe and explain the synergistic actions of the individual leg muscles over a wide range of running speeds, from slow running to maximal sprinting. Experimental gait data from nine subjects were combined with a detailed computer model of the musculoskeletal system to determine the forces developed by the leg muscles at different running speeds. For speeds up to 7 m s–1, the ankle plantarflexors, soleus and gastrocnemius, contributed most significantly to vertical support forces and hence increases in stride length. At speeds greater than 7 m s–1, these muscles shortened at relatively high velocities and had less time to generate the forces needed for support. Thus, above 7 m s–1, the strategy used to increase running speed shifted to the goal of increasing stride frequency. The hip muscles, primarily the iliopsoas, gluteus maximus and hamstrings, achieved this goal by accelerating the hip and knee joints more vigorously during swing. These findings provide insight into the strategies used by the leg muscles to maximise running performance and have implications for the design of athletic training programs.

Effect of Running Speed on Lower Limb Joint Kinetics

PURPOSE Knowledge regarding the biomechanical function of the lower limb muscle groups across a range of running speeds is important in improving the existing understanding of human high performance as well as in aiding in the identification of factors that might be related to injury. The purpose of this study was to evaluate the effect of running speed on lower limb joint kinetics. METHODS Kinematic and ground reaction force data were collected from eight participants (five males and three females) during steady-state running on an indoor synthetic track at four discrete speeds: 3.50±0.04, 5.02±0.10, 6.97±0.09, and 8.95±0.70 m·s. A standard inverse-dynamics approach was used to compute three-dimensional torques at the hip, knee, and ankle joints, from which net powers and work were also calculated. A total of 33 torque, power, and work variables were extracted from the data set, and their magnitudes were statistically analyzed for significant speed effects. RESULTS The torques developed about the lower limb joints during running displayed identifiable profiles in all three anatomical planes. The sagittal-plane torques, net powers, and work done at the hip and knee during terminal swing demonstrated the largest increases in absolute magnitude with faster running. In contrast, the work done at the knee joint during stance was unaffected by increasing running speed, whereas the work done at the ankle joint during stance increased when running speed changed from 3.50 to 5.02 m·s, but it appeared to plateau thereafter. CONCLUSIONS Of all the major lower limb muscle groups, the hip extensor and knee flexor muscles during terminal swing demonstrated the most dramatic increase in biomechanical load when running speed progressed toward maximal sprinting.

Mechanics of the human hamstring muscles during sprinting.

PURPOSE An understanding of hamstring mechanics during sprinting is important for elucidating why these muscles are so vulnerable to acute strain-type injury. The purpose of this study was twofold: first, to quantify the biomechanical load (specifically, musculotendon strain, velocity, force, power, and work) experienced by the hamstrings across a full stride cycle; and second, to determine how these parameters differ for each hamstring muscle (i.e., semimembranosus (SM), semitendinosus (ST), biceps femoris long head (BF), biceps femoris short head (BF)). METHODS Full-body kinematics and ground reaction force data were recorded simultaneously from seven subjects while sprinting on an indoor running track. Experimental data were integrated with a three-dimensional musculoskeletal computer model comprised of 12 body segments and 92 musculotendon structures. The model was used in conjunction with an optimization algorithm to calculate musculotendon strain, velocity, force, power, and work for the hamstrings. RESULTS SM, ST, and BF all reached peak strain, produced peak force, and formed much negative work (energy absorption) during terminal swing. The biomechanical load differed for each hamstring muscle: BF exhibited the largest peak strain, ST displayed the greatest lengthening velocity, and SM produced the highest peak force, absorbed and generated the most power, and performed the largest amount of positive and negative work. CONCLUSIONS As peak musculotendon force and strain for BF, ST, and SM occurred around the same time during terminal swing, it is suggested that this period in the stride cycle may be when the biarticular hamstrings are at greatest injury risk. On this basis, hamstring injury prevention or rehabilitation programs should preferentially target strengthening exercises that involve eccentric contractions performed with high loads at longer musculotendon lengths.

Comparison of different methods for estimating muscle forces in human movement

The aim of this study was to compare muscle-force estimates derived for human locomotion using three different methods commonly reported in the literature: static optimisation (SO), computed muscle control (CMC) and neuromusculoskeletal tracking (NMT). In contrast with SO, CMC and NMT calculate muscle forces dynamically by including muscle activation dynamics. Furthermore, NMT utilises a time-dependent performance criterion, wherein a single optimisation problem is solved over the entire time interval of the task. Each of these methods was used in conjunction with musculoskeletal modelling and experimental gait data to determine lower-limb muscle forces for self-selected speeds of walking and running. Correlation analyses were performed for each muscle to quantify differences between the various muscle-force solutions. The patterns of muscle loading predicted by the three methods were similar for both walking and running. The correlation coefficient between any two sets of muscle-force solutions ranged from 0.46 to 0.99 (p < 0.001 for all muscles). These results suggest that the robustness and efficiency of static optimisation make it the most attractive method for estimating muscle forces in human locomotion.

Estimates of muscle function in human gait depend on how foot-ground contact is modelled

Computational analyses of leg-muscle function in human locomotion commonly assume that contact between the foot and the ground occurs at discrete points on the sole of the foot. Kinematic constraints acting at these contact points restrict the motion of the foot and, therefore, alter model calculations of muscle function. The aim of this study was to evaluate how predictions of muscle function obtained from musculoskeletal models are influenced by the model used to simulate ground contact. Both single- and multiple-point contact models were evaluated. Muscle function during walking and running was determined by quantifying the contributions of individual muscles to the vertical, fore-aft and mediolateral components of the ground reaction force (GRF). The results showed that two factors – the number of foot-ground contact points assumed in the model and the type of kinematic constraint enforced at each point – affect the model predictions of muscle coordination. Whereas single- and multiple-point contact models produced similar predictions of muscle function in the sagittal plane, inconsistent results were obtained in the mediolateral direction. Kinematic constraints applied in the sagittal plane altered the model predictions of muscle contributions to the vertical and fore-aft GRFs, while constraints applied in the frontal plane altered the calculations of muscle contributions to the mediolateral GRF. The results illustrate the sensitivity of calculations of muscle coordination to the model used to simulate foot-ground contact.

Lower-limb muscular strategies for increasing running speed.

SYNOPSIS This clinical commentary discusses the mechanisms used by the lower-limb musculature to achieve faster running speeds. A variety of methodological approaches have been taken to evaluate lower-limb muscle function during running, including direct recordings of muscle electromyographic signal, inverse dynamics-based analyses, and computational musculoskeletal modeling. Progressing running speed from jogging to sprinting is mostly dependent on ankle and hip muscle performance. For speeds up to approximately 7.0 m/s, the dominant strategy is to push on the ground forcefully to increase stride length, and the major ankle plantar flexors (soleus and gastrocnemius) have a particularly important role in this regard. At speeds beyond approximately 7.0 m/s, the force-generating capacity of these muscles becomes less effective. Therefore, as running speed is progressed toward sprinting, the dominant strategy shifts toward the goal of increasing stride frequency and pushing on the ground more frequently. This strategy is achieved by generating substantially more power at the hip joint, thereby increasing the biomechanical demand on proximal lower-limb muscles such as the iliopsoas, gluteus maximus, rectus femoris, and hamstrings. Basic science knowledge regarding lower-limb muscle function during running has implications for understanding why sprinting performance declines with age. It is also of great value to the clinician for designing rehabilitation programs to restore running ability in young, previously active adults who have sustained a traumatic brain injury and have severe impairments of muscle function (eg, weakness, spasticity, poor motor control) that limit their capacity to run at any speed.

Lower-Limb Muscle Function in Human Running

This paper provides a brief summary of work completed to date in our research laboratory investigating lower-limb muscle function during human running. Muscle function has been evaluated using a variety of methods, including muscle electromyography, inverse dynamics, and computational musculoskeletal modeling. It is evident that the coordination amongst the major lower-limb muscles changes considerably when running speed is progressed from jogging through to maximum sprinting. The ankle plantarflexor muscles appear to have a dominant role up to running speeds of around 7 ms− 1. For running speeds beyond 7 ms− 1, the hip flexor and extensor muscles become far more critical. These findings provide insight into the strategies used by the lower-limb muscles to maximize running performance and have implications for the design of injury prevention programs.

Which Muscles Power the Human Running Stride

Running is a physically demanding activity that requires explosive delivery of muscle power to the ground during stance, and precise, yet rapid limb coordination during swing. In particular, as running speed increases, greater metabolic energy in the form of muscle mechanical work is required to power the motion of: i) the center-of-mass (i.e., external power); and ii) the individual limb segments (i.e., internal power) [1,2]. The purpose of this study was to quantify the contributions that individual muscles make to the external and internal power of the body across a range of running speeds so as to identify the key muscle groups in coordinating a full running stride.Copyright