[show abstract][hide abstract] ABSTRACT: An accumulation of evidence suggests that the force-velocity relationship (FVR) of skeletal muscle plays a major role in limiting maximum human sprinting speed. However, most of the theories on this limiting role have been non-specific as to how the FVR limits speed. The FVR is characterized by three parameters that each have a different effect on its shape, and could thus limit sprinting speed in different ways: the maximum shortening velocity V(max), the shape parameter A(R), and the eccentric plateau C(ecc). In this study, we sought to determine how specifically the FVR limits sprinting speed using forward dynamics simulations of human locomotion to examine the sensitivity of maximum speed to these three FVR parameters. Simulations were generated by optimizing the model's muscle excitations to maximize the average horizontal speed. The simulation's speed, temporal stride parameters, joint angles, GRF, and muscle activity in general compared well to data from human subjects sprinting at maximum effort. Simulations were then repeated with incremental and isolated adjustments in V(max), A(R), and C(ecc) across a physiological range. The range of speeds (5.22-6.91 m s⁻¹) was most sensitive when V(max) was varied, but the fastest speed of 7.17 m s⁻¹ was attained when A(R) was set to its maximum value, which corresponded to all muscles having entirely fast-twitch fibers. This result was explained by the muscle shortening velocities, which tended to be moderate and within the range where A(R) had its greatest effect on the shape of the FVR. Speed was less sensitive to adjustments in C(ecc), with a range of 6.23-6.70 m s⁻¹. Increases in speed with parameter changes were due to increases in stride length more so than stride frequency. The results suggest that the shape parameter A(R), which primarily determines the amount of muscle force that can be produced at moderate shortening velocities, plays a major role in limiting the maximum sprinting speed. Analysis of muscle force sensitivity indicated support for previous theories on the time to generate support forces in stance (Weyand et al., 2000, Journal of Applied Physiology, 89, 1991-1999) and energy management of the leg in swing (Chapman & Caldwell, 1983, Journal of Biomechanics 16, 79-83) as important factors in limiting maximum speed. However, the ability of the knee flexors to slow the rotational velocity of the leg in preparation for footstrike did not appear to play a major role in limiting speed.
Journal of biomechanics 03/2012; 45(8):1406-13. · 2.66 Impact Factor
[show abstract][hide abstract] ABSTRACT: This paper determines if the leveling off ('plateau/inverted-U' phenomenon) of vertical ActiGraph activity counts during running at higher speeds is attributable to the monitor's signal filtering and acceleration detection characteristics. Ten endurance-trained male participants (mean (SD) age = 28.2 (4.7) years) walked at 3, 5 and 7 km h(-1), and ran at 8, 10, 12, 14, 16, 18 and 20 km h(-1) on a force treadmill while wearing an ActiGraph GT3X monitor at the waist. Triaxial accelerations of the body's center of mass (CoM) and frequency content of these accelerations were computed from the force treadmill data. GT3X vertical activity counts demonstrated the expected 'plateau/inverted-U' phenomenon. In contrast, vertical CoM accelerations increased with increasing speed (1.32 ± 0.26 g at 10 km h(-1) and 1.68 ± 0.24 g at 20 km h(-1)). The dominant frequency in the CoM acceleration signals increased with running speed (14.8 ± 3.2 Hz at 10 km h(-1) and 24.8 ± 3.2 Hz at 20 km h(-1)) and lay beyond the ActiGraph band-pass filter (0.25 to 2.5 Hz) limits. In conclusion, CoM acceleration magnitudes during walking and running lie within the ActiGraph monitor's dynamic acceleration detecting capability. Acceleration signals of higher frequencies that are eliminated by the ActiGraph band-pass filter may be necessary to distinguish among exercise intensity at higher running speeds.
[show abstract][hide abstract] ABSTRACT: Redundancy in the human muscular system makes it challenging to assess age-related changes in muscle mechanical properties in vivo, as ethical considerations prohibit direct muscle force measurement. We overcame this by using a hybrid approach that combined magnetic resonance and ultrasound imaging, dynamometer measurements, muscle modeling, and numerical optimization to obtain subject-specific estimates of the mechanical properties of tibialis anterior, gastrocnemius, and soleus muscles from young and older adults. We hypothesized that older subjects would have lower maximal isometric forces, slower contractile and stiffer elastic characteristics, and that subject-specific muscle properties would give more accurate joint torque predictions compared to generic properties. Unknown muscle model parameters were obtained by minimizing the difference between simulated and actual subject torque-time histories under both isometric and isovelocity conditions. The resulting subject-specific models showed age- and gender-related differences, with older adults displaying reduced maximal isometric forces, slower force-velocity and altered force-length properties and stiffer elasticity. Tibialis anterior was least affected by aging. Subject-specific models gave good predictions of experimental concentric torque-time histories (10-14% error), but were less accurate for eccentric conditions. With generic muscle properties prediction errors were about twice as large. For maximum predictive power, musculoskeletal models should be tailored to individual subjects.
Annals of biomedical engineering 12/2011; 40(5):1088-101. · 2.41 Impact Factor
[show abstract][hide abstract] ABSTRACT: A popular hypothesis for human running is that gait mechanics and muscular activity are optimized in order to minimize the cost of transport (CoT). Humans running at any particular speed appear to naturally select a stride length that maintains a low CoT when compared with other possible stride lengths. However, it is unknown if the nervous system prioritizes the CoT itself for minimization, or if some other quantity is minimized and a low CoT is a consequential effect. To address this question, we generated predictive computer simulations of running using an anatomically inspired musculoskeletal model and compared the results with data collected from human runners. Three simulations were generated by minimizing the CoT, the total muscle activation or the total muscle stress, respectively. While all the simulations qualitatively resembled real human running, minimizing activation predicted the most realistic joint angles and timing of muscular activity. While minimizing the CoT naturally predicted the lowest CoT, minimizing activation predicted a more realistic CoT in comparison with the experimental mean. The results suggest a potential control strategy centred on muscle activation for economical running.
Proceedings of the Royal Society B: Biological Sciences 11/2011; 279(1733):1498-505. · 5.68 Impact Factor
[show abstract][hide abstract] ABSTRACT: It has been suggested that the force-velocity relationship of skeletal muscle plays a critical limiting role in the maximum speed at which humans can sprint. However, this theory has not been tested directly, and it is possible that other muscle mechanical properties play limiting roles as well. In this study, forward dynamics simulations of human sprinting were generated using a 2D musculoskeletal model actuated by Hill muscle models. The initial simulation results compared favorably to kinetic, kinematic, and electromyographic data recorded from sprinting humans. Muscle mechanical properties were then removed in isolation to quantify their effect on maximum sprinting speed. Removal of the force-velocity, excitation-activation, and force-length relationships increased the maximum speed by 15, 8, and 4%, respectively. Removal of the series elastic force-extension relationship decreased the maximum speed by 26%. Each relationship affected both stride length and stride frequency except for the force-length relationship, which mainly affected stride length. Removal of all muscular properties entirely (optimized joint torques) increased speed (+22%) to a greater extent than the removal of any single contractile property. The results indicate that the force-velocity relationship is indeed the most important contractile property of muscle regarding limits to maximum sprinting speed, but that other muscular properties also play important roles. Interactions between the various muscular properties should be considered when explaining limits to maximal human performance.
Journal of biomechanics 10/2011; 45(6):1092-7. · 2.66 Impact Factor
[show abstract][hide abstract] ABSTRACT: Magnetic resonance imaging (MRI) enables accurate in vivo quantification of human muscle volumes, which can be used to estimate subject-specific muscle force capabilities. An important consideration is the amount of contractile and non-contractile tissue in the muscle compartment, which will influence force capability. We quantified age-related differences in the proportion and distribution of contractile and non-contractile tissue in the dorsiflexor and plantar flexor (soleus, and medial and lateral heads of gastrocnemius) muscles, and examined how well these volumes can be estimated from single MRI cross-sections. Axial MRIs of the left leg for 12 young (mean age 27 years) and 12 older (72 years) healthy, active adults were used to compute muscle volumes. Contractile tissue distribution along the leg was characterized by mathematical functions to allow volume prediction from single-slice cross-sectional area (CSA) measurements. Compared to young, older adults had less contractile volume and a greater proportion of non-contractile tissue. In both age groups the proportion of non-contractile tissue increased distally, with the smallest proportion near the maximum compartment CSA. A single CSA measurement predicted contractile volume with 8-11% error, with older adults in the higher end of this range. Using multiple slices improved volume estimates by roughly 50%, with average errors of about 3-4%. These results demonstrate significant age-related differences in non-contractile tissue for the dorsi- and plantar-flexor muscles. Although estimates of contractile volume can be obtained from single CSA measurements, multiple slices are needed for increased accuracy due to inter-individual variations in muscle volume and composition.
Journal of biomechanics 06/2011; 44(12):2299-306. · 2.66 Impact Factor
[show abstract][hide abstract] ABSTRACT: The purpose of this study was to investigate age-related differences in contractile and elastic properties of both dorsi- (DF) and plantarflexor (PF) muscles controlling the ankle joint in young and older adults. Experimental data were collected while twelve young and twelve older male and female participants performed maximal effort isometric and isovelocity contractions on a dynamometer. Equations were fit to the data to give torque-angle (Tθ) and torque-angular velocity (Tω) relations. Muscle series-elasticity was measured during ramped dynamometer contractions using ultrasonography to measure aponeurosis extension as a function of torque; second order polynomials were used to characterize the torque-extension (TΔL) relation. The results showed no age differences in DF maximal torque and none for female PF; however, older males had smaller maximal PF torques compared to young males. In both muscle groups and genders, older adults had decreased concentric force capabilities. Both DF and PF TΔL relations were more nonlinear in the older adults. Older PF, but not DF muscles, were stiffer compared to young. A simple antagonism model suggested age-related differences in Tθ and Tω relations would be magnified if antagonistic torque contributions were included. This assessment of static, dynamic, and elastic joint properties affords a comprehensive view of age-related modifications in muscle function. Although many clinical studies use maximal isometric strength as a marker of functional ability, the results demonstrate that there are also significant age-related modifications in ankle muscle dynamic and elastic properties.
PLoS ONE 01/2011; 6(1):e15953. · 3.73 Impact Factor
[show abstract][hide abstract] ABSTRACT: The objective of this study was to determine the association between biomechanical and neuromuscular factors of clinically diagnosed mild to moderate knee osteoarthritis (OA) with radiographic severity and pain severity separately.
Three-dimensional gait analysis and electromyography were performed on a group of 40 participants with clinically diagnosed mild to moderate medial knee OA. Associations between radiographic severity, defined using a visual analog radiographic score, and pain severity, defined with the pain subscale of the WOMAC osteoarthritis index, with knee joint kinematics and kinetics, electromyography patterns of periarticular knee muscles, BMI and gait speed were determined with correlation analyses. Multiple linear regression analyses of radiographic and pain severity were also explored.
Statistically significant correlations between radiographic severity and the overall magnitude of the knee adduction moment during stance (r²=21.4%, P=0.003) and the magnitude of the knee flexion angle during the gait cycle (r²=11.4%, P=0.03) were found. Significant correlations between pain and gait speed (r²=28.2%, P<0.0001), the activation patterns of the lateral gastrocnemius (r²=16.6%, P=0.009) and the medial hamstring (r²=10.3%, P=0.04) during gait were found. The combination of the magnitude of the knee adduction moment during stance and BMI explained a significant portion of the variability in radiographic severity (R(2)=27.1%, P<0.0001). No multivariate model explained pain severity better than gait speed alone.
This study suggests that some knee joint biomechanical variables are associated with structural knee OA severity measured from radiographs in clinically diagnosed mild to moderate levels of disease, but that pain severity is only reflected in gait speed and neuromuscular activation patterns. A combination of the knee adduction moment and BMI better explained structural knee OA severity than any individual factor alone.
Osteoarthritis and Cartilage 11/2010; 19(2):186-93. · 4.26 Impact Factor
[show abstract][hide abstract] ABSTRACT: The role of arm swing in running has been minimally described, and the contributions of arm motion to lower extremity joint kinematics and external force generation are unknown. These contributions may have implications in the design of musculoskeletal models for computer simulations of running, since previous models have usually not included articulating arm segments. 3D stance phase lower extremity joint angles and ground reaction forces (GRFs) were determined for seven subjects running normally, and running under two conditions of arm restraint. When arm swing was suppressed, the peak vertical GRF decreased by 10-13% bodyweight, and the peak lateral GRF increased by 4-6% bodyweight. Changes in peak joint angles on the order of 1-5 deg were observed for hip flexion, hip adduction, knee flexion, knee adduction, and ankle abduction. The effect sizes (ES) were small to moderate (ES<0.8) for most of the peak GRF differences, but large (ES>0.8) for most of the peak joint angle differences. These changes suggest that suppression of arm swing induces subtle but statistically significant changes in the kinetic and kinematic patterns of running. However, the salient features of the GRFs and the joint angles were present in all conditions, and arm swing did not introduce any major changes in the timing of these data, as indicated by cross correlations. The decision to include arm swing in a computer model will likely need to be made on a case-by-case basis, depending on the design of the study and the accuracy needed to answer the research question.
Journal of Biomechanical Engineering 12/2009; 131(12):124502. · 1.52 Impact Factor
[show abstract][hide abstract] ABSTRACT: In this study, we describe and compare the compensatory responses of healthy young and older adults to sequentially increasing upper-body perturbations. The scaling of plantarflexor muscular activity and minimum time-to-contact (TtC(MIN)) was examined, and we determined whether TtC(MIN) predictions of instability (stepping transitions) for the older subjects were similar to those we previously reported for younger subjects (Hasson et al. in J Biomech 41:2121-2129, 2008). We found that the older subjects stepped at a lower perturbation level than the younger subjects; however, this response was appropriate based on their greater center of mass (CoM) accelerations, which may have been caused by differences in pre-perturbation states between the age groups. Although the CoM acceleration increased linearly with perturbation magnitude, the amount of gastrocnemius and soleus muscular activity increased nonlinearly in both age groups. There were no differences in the maximum plantarflexor torque responses, suggesting that the maximum torque capabilities of the older subjects were not limiting factors. As previously demonstrated in the younger subjects, the older subjects showed a quadratic decrease in TtC(MIN) with increasing perturbation magnitude. The vertices of the quadratics gave accurate predictions of stepping transitions in both age groups, even though the older subjects stepped at lower perturbation magnitudes. By probing the postural system's behavior through sequentially increasing upper-body perturbations, we observed a complementary nonlinear scaling of muscle activity and TtC(MIN), which suggests that subjects could use TtC or a correlate as an informational variable to help determine whether a step is necessary.
Experimental Brain Research 08/2009; 196(3):413-27. · 2.22 Impact Factor
[show abstract][hide abstract] ABSTRACT: Muscle forces during locomotion are often predicted using static optimisation and SQP. SQP has been criticised for over-estimating force magnitudes and under-estimating co-contraction. These problems may be related to SQP's difficulty in locating the global minimum to complex optimisation problems. Algorithms designed to locate the global minimum may be useful in addressing these problems. Muscle forces for 18 flexors and extensors of the lower extremity were predicted for 10 subjects during the stance phase of running. Static optimisation using SQP and two random search (RS) algorithms (a genetic algorithm and simulated annealing) estimated muscle forces by minimising the sum of cubed muscle stresses. The RS algorithms predicted smaller peak forces (42% smaller on average) and smaller muscle impulses (46% smaller on average) than SQP, and located solutions with smaller cost function scores. Results suggest that RS may be a more effective tool than SQP for minimising the sum of cubed muscle stresses in static optimisation.
Computer Methods in Biomechanics and Biomedical Engineering 10/2008; 12(2):217-25. · 1.39 Impact Factor
[show abstract][hide abstract] ABSTRACT: Recurrence quantification analysis (RQA) can extract the dynamics of postural control from center of pressure (CoP) data by quantifying the system's repeatability, complexity, and local dynamic stability through several variables. Computation of these variables requires the selection of suitable embedding parameters for state space reconstruction (i.e. time delay and embedding dimension); however, it is unclear how the parameters influence RQA variables when examining noisy CoP data. This study evaluated the sensitivity of RQA variables to embedding parameter values and noise level, and assessed methods of selecting embedding parameters for CoP data. Five healthy male subjects maintained quiet stance for 30s while the anterior-posterior CoP was measured. The effect of noise was evaluated by adding uniform white noise of increasing amplitude to the raw CoP signal. The magnitude of all RQA variables decreased with increasing noise amplitude for all subjects. A sensitivity analysis was performed by systematically altering the embedding parameters for the raw data with and without a selected level of added noise. The key result was that, for all subjects, the RQA variables were sensitive to the embedding parameter values and the level of noise in the CoP data. Finally, the performance of false nearest neighbors and average displacement algorithms for choosing embedding parameters was evaluated. Both methods gave clear and consistent results for all subjects with either raw or noisy data. The results suggest that careful selection of embedding parameters is essential when using RQA to examine postural control based on noisy CoP data.
[show abstract][hide abstract] ABSTRACT: While it has been suggested that bi-articular muscles have a specialized role in directing external reaction forces, it is unclear how humans learn to coordinate mono- and bi-articular muscles to perform force-directing tasks. Participants were asked to direct pedal forces in a specified target direction during one-legged cycling. We expected that with practice, performance improvement would be associated with specific changes in joint torque patterns and mono- and bi-articular muscular coordination. Nine male participants practiced pedaling an ergometer with only their left leg, and were instructed to always direct their applied pedal force perpendicular to the crank arm (target direction) and to maintain a constant pedaling speed. After a single practice session, the mean error between the applied and target pedal force directions decreased significantly. This improved performance was accompanied by a significant decrease in the amount of ankle angular motion and a smaller increase in knee and hip angular motion. This coincided with a re-organization of lower extremity joint torques, with a decrease in ankle plantarflexor torque and an increase in knee and hip flexor torques. Changes were seen in both mono- and bi-articular muscle activity patterns. The mono-articular muscles exhibited greater alterations, and appeared to contribute to both mechanical work and force-directing. With practice, a loosening of the coupling between bi-articular thigh muscle activation and joint torque co-regulation was observed. The results demonstrated that participants were able to learn a complex and dynamic force-directing task by changing the direction of their applied pedal forces through re-organization of joint torque patterns and mono- and bi-articular muscle coordination.
Human Movement Science 05/2008; 27(4):590-609. · 2.06 Impact Factor
[show abstract][hide abstract] ABSTRACT: Mechanical factors have been implicated in the progression of knee osteoarthritis (OA). Understanding how these factors change as the condition progresses would elucidate their role and help in developing interventions that could delay the progress of knee OA. In this cross-sectional study, we identified kinematic and kinetic variables at the hip, knee, and ankle joints that change between three clinically distinct levels of knee OA disease severity: asymptomatic, moderate OA, and severe OA. The severity level was based on a combined radiographic/symptomatic clinical decision for treatment with (severe) or without (moderate) total knee replacement surgery. Gait variables that changed between groups were categorized as: those that differed between the asymptomatic group and both OA groups, those that differed between the asymptomatic group and the severe OA group only, or those that changed progressively, that is, the asymptomatic differed from the moderate OA, and the moderate OA differed from the severe OA group. Changes seen in both OA subject groups compared to asymptomatic included increased mid-stance knee adduction moments, decreased peak knee flexion moments, decreased peak hip adduction moments, and decreased peak hip extension moments. Changes found only in the severe knee OA group included multiple kinematic and kinetic differences at the hip, knee, and ankle joints. Gait differences that progressed with OA severity included decreased stance phase knee flexion angles, decreased early stance knee extension moments, decreased peak stance phase hip internal rotation moments, and decreased peak ankle dorsiflexion moments.
Journal of Orthopaedic Research 04/2008; 26(3):332-41. · 2.88 Impact Factor
[show abstract][hide abstract] ABSTRACT: Knee osteoarthritis (OA) is a multifactoral, progressive disease process of the musculoskeletal system. Mechanical factors have been implicated in the progression of knee OA, but the role of altered joint mechanics and neuromuscular control strategies in progressive mechanisms of the disease have not been fully explored. Previous biomechanical studies of knee OA have characterized changes in joint kinematics and kinetics with the disease, but it has been difficult to determine if these biomechanical changes are involved in the development of disease, are in response to degenerative changes in the joint, or are compensatory mechanisms in response to these degenerative changes or other related factors as joint pain. The goal of this study was to explore the association between biomechanical changes and knee OA severity in an effort to understand the changing role of biomechanical factors in the progression of knee OA. A three-group cross-sectional model was used that included asymptomatic subjects, subjects clinically diagnosed with moderate knee OA and severe knee OA subjects just prior to total joint replacement surgery. Principal component analysis and discriminant analysis were used to determine the combinations of electromyography, kinematic and kinetic waveform pattern changes at the knee, hip and ankle joints during gait that optimally separated the three levels of severity. Different biomechanical mechanisms were important in discriminating between severity levels. Changes in knee and hip kinetic patterns and rectus femoris activation were important in separating the asymptomatic and moderate OA gait patterns. In contrast, changes in knee kinematics, hip and ankle kinetics and medial gastrocnemius activity were important in discriminating between the moderate and severe OA gait patterns.
Journal of Biomechanics 02/2008; 41(4):868-76. · 2.72 Impact Factor
[show abstract][hide abstract] ABSTRACT: Our purpose was to determine whether spatiotemporal measures of center of mass motion relative to the base of support boundary could predict stepping strategies after upper-body postural perturbations in humans. We expected that inclusion of center of mass acceleration in such time-to-contact (TtC) calculations would give better predictions and more advanced warning of perturbation severity. TtC measures were compared with traditional postural variables, which do not consider support boundaries, and with an inverted pendulum model of dynamic stability developed by Hof et al. [2005. The condition for dynamic stability. Journal of Biomechanics 38, 1-8]. A pendulum was used to deliver sequentially increasing perturbations to 10 young adults, who were strapped to a wooden backboard that constrained motion to sagittal-plane rotation about the ankle joint. Subjects were instructed to resist the perturbations, stepping only if necessary to prevent a fall. Peak center of mass and center of pressure velocity and acceleration demonstrated linear increases with postural challenge. In contrast, boundary-relevant minimum TtC values decreased nonlinearly with postural challenge, enabling prediction of stepping responses using quadratic equations. When TtC calculations incorporated center of mass acceleration, the quadratic fits were better and gave more accurate predictions of the TtC values that would trigger stepping responses. In addition, TtC minima occurred earlier with acceleration inclusion, giving more advanced warning of perturbation severity. Our results were in agreement with TtC predictions based on Hof's model, and suggest that TtC may function as a control parameter, influencing the postural control system's decision to transition from a stationary base of support to a stepping strategy.
Journal of Biomechanics 02/2008; 41(10):2121-9. · 2.72 Impact Factor