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How muscles maximize performance in accelerated sprinting

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Marcus G. Pandy
Marcus G. Pandy
Marcus G. Pandy
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Adrian Lai at lululemon
Adrian Lai
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Anthony G. Schache
Anthony G. Schache
Anthony G. Schache
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Yi-Chung Lin at Australian Catholic University
Yi-Chung Lin
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Abstract and Figures

We sought to provide a more comprehensive understanding of how the individual leg muscles act synergistically to generate a ground force impulse and maximize the change in forward momentum of the body during accelerated sprinting. We combined musculoskeletal modelling with gait data to simulate the majority of the acceleration phase (19 foot contacts) of a maximal sprint over ground. Individual muscle contributions to the ground force impulse were found by evaluating each muscle’s contribution to the vertical and fore-aft components of the ground force (termed ‘supporter’ and ‘accelerator/brake’, respectively). The ankle plantarflexors played a major role in achieving maximal-effort accelerated sprinting. Soleus acted primarily as a supporter by generating a large fraction of the upward impulse at each step whereas gastrocnemius contributed appreciably to the propulsive and upward impulses and functioned as both accelerator and supporter. The primary role of the vasti was to deliver an upward impulse to the body (supporter), but these muscles also acted as a brake by retarding forward momentum. The hamstrings and gluteus medius functioned primarily as accelerators. Gluteus maximus was neither an accelerator nor supporter as it functioned mainly to decelerate the swinging leg in preparation for foot contact at the next step. Fundamental knowledge of lower-limb muscle function during maximum acceleration sprinting is of interest to coaches endeavouring to optimize sprint performance in elite athletes as well as sports medicine clinicians aiming to improve injury prevention and rehabilitation practices.
Time histories of the forces calculated for representative muscles at the 1st, 7th and 19th foot contacts (FC1, FC7 and FC19) of the acceleration phase of sprinting. The solid lines represent mean muscle forces for all participants and the shaded areas represent +1 standard deviation from the mean. Muscle forces were normalized by each participant's body weight (BW). Muscle symbols are: ILIOPSOAS, iliacus and psoas combined; GMAX, superior, middle, inferior portions of gluteus maximus combined; GMED, anterior and posterior portions of gluteus medius/minimus combined; HAMS, semimembranosus, semitendinosus, and biceps femoris long head and short head combined; RF, rectus femoris; VAS, vastus medialis, intermedius, and lateralis combined; SOL, soleus; GAS, medial and lateral gastrocnemius combined. Results shown are for the ipsilateral limb
Time histories of the forces calculated for representative muscles at the 1st, 7th and 19th foot contacts (FC1, FC7 and FC19) of the acceleration phase of sprinting. The solid lines represent mean muscle forces for all participants and the shaded areas represent +1 standard deviation from the mean. Muscle forces were normalized by each participant's body weight (BW). Muscle symbols are: ILIOPSOAS, iliacus and psoas combined; GMAX, superior, middle, inferior portions of gluteus maximus combined; GMED, anterior and posterior portions of gluteus medius/minimus combined; HAMS, semimembranosus, semitendinosus, and biceps femoris long head and short head combined; RF, rectus femoris; VAS, vastus medialis, intermedius, and lateralis combined; SOL, soleus; GAS, medial and lateral gastrocnemius combined. Results shown are for the ipsilateral limb
… 
Contributions of individual muscles to the net joint moments exerted about the hip, knee, and ankle for the 1st, 7th and 19th foot contacts (FC1, FC7 and FC19). Moments were normalized by each participant's body mass and averaged across all participants. The shaded regions represent the net joint moments calculated from the experimental gait data using inverse dynamics while the dashed lines are the model‐predicted moments obtained by taking the product of muscle force and moment arm and summing across all the muscles spanning each joint. Hip extension, knee extension and ankle plantarflexion moments are positive. Muscle symbols are defined in Figure 1
Contributions of individual muscles to the net joint moments exerted about the hip, knee, and ankle for the 1st, 7th and 19th foot contacts (FC1, FC7 and FC19). Moments were normalized by each participant's body mass and averaged across all participants. The shaded regions represent the net joint moments calculated from the experimental gait data using inverse dynamics while the dashed lines are the model‐predicted moments obtained by taking the product of muscle force and moment arm and summing across all the muscles spanning each joint. Hip extension, knee extension and ankle plantarflexion moments are positive. Muscle symbols are defined in Figure 1
… 
Contributions of individual muscles to the fore‐aft (A, top two rows) and vertical (B, bottom two rows) components of the GRF for the 1st, 7th and 19th foot contacts (FC1, FC7 and FC19). GRFs were normalized by each participant's body weight (BW) and averaged across all participants. The shaded regions represent the force plate measurements obtained at each foot contact. Muscle symbols are defined in Figure 1
Contributions of individual muscles to the fore‐aft (A, top two rows) and vertical (B, bottom two rows) components of the GRF for the 1st, 7th and 19th foot contacts (FC1, FC7 and FC19). GRFs were normalized by each participant's body weight (BW) and averaged across all participants. The shaded regions represent the force plate measurements obtained at each foot contact. Muscle symbols are defined in Figure 1
… 
Potential muscle contributions to the fore‐aft (A) and vertical (B) GRF impulses for the first 19 foot contacts of the acceleration phase of sprinting. The potential contribution of a muscle to the GRF impulse represents the effect of a unit of force (1.0 N) applied by that muscle in isolation, with all other muscle forces assumed to be zero at that instant. Potential muscle contributions to the GRF impulse were normalized by body mass and averaged across all participants. Muscle symbols are defined in Figure 1
Potential muscle contributions to the fore‐aft (A) and vertical (B) GRF impulses for the first 19 foot contacts of the acceleration phase of sprinting. The potential contribution of a muscle to the GRF impulse represents the effect of a unit of force (1.0 N) applied by that muscle in isolation, with all other muscle forces assumed to be zero at that instant. Potential muscle contributions to the GRF impulse were normalized by body mass and averaged across all participants. Muscle symbols are defined in Figure 1
… 
Actual muscle contributions to the net fore‐aft (A) and vertical (B) GRF impulses for the first 19 foot contacts of the acceleration phase of sprinting. The actual contribution of a muscle considers the magnitude of force developed by that muscle at each instant of the simulated sprint. The top two rows show the muscle contributions to net fore‐aft (propulsive) and vertical (support) GRF impulses generated at each foot contact. The bottom row shows the percentage contributions of individual muscles to the total propulsive and support GRF impulses generated by all the muscles across all 19 foot contacts. Muscle contributions to the GRF impulse were normalized by body mass and averaged across all participants. Muscle symbols are defined in Figure 1
+1
Actual muscle contributions to the net fore‐aft (A) and vertical (B) GRF impulses for the first 19 foot contacts of the acceleration phase of sprinting. The actual contribution of a muscle considers the magnitude of force developed by that muscle at each instant of the simulated sprint. The top two rows show the muscle contributions to net fore‐aft (propulsive) and vertical (support) GRF impulses generated at each foot contact. The bottom row shows the percentage contributions of individual muscles to the total propulsive and support GRF impulses generated by all the muscles across all 19 foot contacts. Muscle contributions to the GRF impulse were normalized by body mass and averaged across all participants. Muscle symbols are defined in Figure 1
… 
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1882
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Scand J Med Sci Sports. 2021;31:1882–1896.
wileyonlinelibrary.com/journal/sms
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INTRODUCTION
The best sprinters run at an average speed of approximately
10 m/s and can reach maximum speeds of nearly 13 m/s
during a 100m race.1 This level of exceptional performance
is achieved by maximally accelerating the body during the
first half of the race and maintaining that momentum there-
after. The force generated on the ground at each foot contact
creates an impulse that causes the necessary increase in for-
ward momentum of the body's center of mass. The lower-
limb muscles together with the actions of gravity and inertia
generate the required ground force impulse, but the overall
contribution from the muscles is by far the greatest.2,3
Many investigators have performed inverse dynamics
analyses to determine the net moments exerted by the lower-
limb joints for sprinting at a steady- state speed.4- 6 Recent
studies also have estimated the forces developed by the leg
muscles for running at various steady- state speeds, including
sprinting.2,3,7 Soleus, gastrocnemius and vasti were found to
be the major contributors to the vertical (support) and fore-
aft (propulsive/braking) components of the ground reaction
force (GRF) at all steady- state running speeds.2,3
Received: 16 May 2021
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Revised: 1 July 2021
|
Accepted: 10 July 2021
DOI: 10.1111/sms.14021
ORIGINAL ARTICLE
How muscles maximize performance in accelerated sprinting
Marcus G.Pandy1
|
Adrian K. M.Lai2
|
Anthony G.Schache1,3
|
Yi- ChungLin1
© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
1Department of Mechanical Engineering,
University of Melbourne, Parkville,
Victoria, Australia
2Department of Biomedical Physiology
and Kinesiology, Simon Fraser
University, Burnaby, Canada
3La Trobe Sport and Exercise Medicine
Research Centre, La Trobe University,
Bundoora, Australia
Correspondence
Marcus G. Pandy, Department of
Mechanical Engineering, University of
Melbourne, Parkville, Victoria 3010,
Australia.
Email: pandym@unimelb.edu.au
Funding information
Australian Research Council, Grant/
Award Number: LP110100262
We sought to provide a more comprehensive understanding of how the individual
leg muscles act synergistically to generate a ground force impulse and maximize the
change in forward momentum of the body during accelerated sprinting. We combined
musculoskeletal modelling with gait data to simulate the majority of the acceleration
phase (19 foot contacts) of a maximal sprint over ground. Individual muscle contribu-
tions to the ground force impulse were found by evaluating each muscle's contribu-
tion to the vertical and fore- aft components of the ground force (termed “supporter”
and “accelerator/brake,” respectively). The ankle plantarflexors played a major role in
achieving maximal- effort accelerated sprinting. Soleus acted primarily as a supporter
by generating a large fraction of the upward impulse at each step whereas gastrocne-
mius contributed appreciably to the propulsive and upward impulses and functioned
as both accelerator and supporter. The primary role of the vasti was to deliver an
upward impulse to the body (supporter), but these muscles also acted as a brake by
retarding forward momentum. The hamstrings and gluteus medius functioned primar-
ily as accelerators. Gluteus maximus was neither an accelerator nor supporter as it
functioned mainly to decelerate the swinging leg in preparation for foot contact at the
next step. Fundamental knowledge of lower- limb muscle function during maximum
acceleration sprinting is of interest to coaches endeavoring to optimize sprint perfor-
mance in elite athletes as well as sports medicine clinicians aiming to improve injury
prevention and rehabilitation practices.
KEYWORDS
gluteal, hamstring, impulse, plantarflexor, propulsion, running
... Furthermore, in the 50-m sprint, the acceleration phase is highly prominent, requiring high levels of propulsive force to achieve greater speeds [22]. In this aspect, the muscles of the lower limbs play a significant role, with muscle mass being essential in this phase, where overcoming inertia and increasing stride length are fundamental [21,33]. Taken together, the associations we found between ML-PhA and 50-m sprint have a sound rationale, as PhA has been shown to reflect muscular and cellular characteristics that positively impact performance, including strength, power, and DXA measures of fat free mass [13,31,[34][35][36]. ...
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Background Raw data obtained through bioelectrical impedance analysis (BIA) have been applied in different populations to assess body fluids and cell integrity. Assessing raw BIA parameters in specific muscles is an emerging method for evaluating muscle function. We investigated the associations of the BIA-derived variables of resistance (R), reactance (Xc) and phase angle (PhA) measured through whole-body (WB) and muscle-localized (ML) methods with performance in the countermovement jump (CMJ) and 50-meter (m) sprint. Methods Thirty-one male track and field athletes (16.5 ± 1.6 years) were assessed. Fat-free mass (FFM) and Fat mass percentage (%FM) were determined by skinfold thickness. BIA at 50 kHz was employed to obtain the WB and ML (right thigh) parameters. The WB and ML-BIA parameters were adjusted by height (R/H, Xc/H) and segment length (R/L, Xc/L). The CMJ assessment was conducted via a contact mat; the software recorded the jump height. The 50-m sprint time was measured via two sets of photocells. Pearson’s correlation and linear multiple regression were performed. Results ML-PhA was inversely related to the 50-m sprint (β=-0.56) and by itself explained 29% of the sprint time variation. It remained a significant predictor even after adjusting for age, height, FFM and peak height velocity (PHV). ML-R/L was directly related to 50-m sprint (β = 0.48) and inversely related to CMJ performance (β=-0.54), explaining 20% and 27% of the variation in 50-m sprint and CMJ performance, respectively. Similarly, it remained a significant predictor in the adjusted models. Correlations between WB-BIA (PhA, R/H) and performance tests were found to be dependent on covariates. Conclusions In this sample, the ML-BIA parameters of R/L and PhA were significantly associated with performance independent of age, height, FFM and PHV. Higher ML-PhA values were associated with better sprint times, whereas higher ML-R/L values were associated with worse sprint times and CMJ performance.
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... Forces produced by the calf muscles were not considerably large. The peak gastrocnemius and soleus forces were substantially smaller than the peak forces required of the calves for accelerated running or sprinting (Dorn et al., 2012;Pandy et al., 2021). Indeed, the gastrocnemius and soleus do not appear to play a major role in decelerating the horizontal velocity of the body, but rather in providing vertical support during ground contact (Hamner & Delp, 2013;Maniar et al., 2019;Mateus et al., 2020). ...
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... However, increased ground reaction force is also a risk factor for the occurrence of HSI (Liu et al., 2017;Clark and Weyand, 2014). Although the hamstrings and Gmax jointly decelerate the swing leg during the late swing phase to control excessive ground reaction forces (Pandy et al., 2021), the results of this study showed low activity of the Gmax on the injured during the late swing phase. The lack of proper Gmax activity indicated that the hamstrings alone would have to decelerate the swing leg. ...
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This study aimed to characterize muscle activity in male soccer players with a history of hamstring strain injuries (HSI) during accelerated sprinting. Thirteen patients each in the HSI group (history of HSI) and in the healthy group (with no history of HSI) were included. 26 male soccer players of which 13 with and 13 without HSI history were included in this study. Ten muscles were evaluated on electromyography activity during overground sprinting. The testing protocol consisted of a maximal sprint over a distance of 30 meters. One running stride was divided into the early stance phase, late stance phase, early swing phase, mid-swing phase, and late swing phase, and the average muscle activity per phase and the timing of the peak root-mean-square value appearance during each stride were calculated. Statistical analysis was performed using repeated-measures two-way ANOVA (group × phase), and multiple comparison tests were performed using the Bonferroni method when the interaction or main effect was significant. The statistical significance level was set at p < 0.05. Gluteus maximus (Gmax), gluteus medius (Gmed), and external oblique (EO) showed activity differences based on HSI history. Gmax was 30% lower, EO was 20% lower, and Gmed was 40% higher in HSI group. This study suggests that, despite previous findings that HSI is most likely during the late swing phase, the HSI group shows a higher injury risk in the early stance phase. This is due to differences in trunk and gluteal muscle activity between the late swing and early stance phases compared to the healthy group. In summary, HSI group had lower activity in the muscles contributing to trunk instability, especially EO and Gmax, before and after ground impact during accelerated sprinting, compared to Healthy.
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... Moreover, by using a cone in the 180° turn test, the technique of the turn could differ from the typically representative 180-degree turn in sports, making the test less sensitive to sport-specific tasks. Furthermore, the plantar flexors of the ankle play a major role in achieving maximal-effort accelerated sprinting (Pandy et al., 2021) which is a vital component of CoD performance tests. In contrast, the hip and knee extensors contribute most to the generation of ground reaction forces during FW squats (Spudić et al., 2020a). ...
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... While knee extension decreased and knee Klexion increased overall while the athletes were wearing CCDRAFOs, these biomechanical changes were not effective in overcoming loss of ankle plantarKlexion. As plantarKlexion is critical in overall sprint performance [6][7][8] , the loss of plantarKlexion by the CCDRAFOs hindered able-bodied athletes' sprinting performance. Therefore, short-term use of CCDRAFOs does not improve ablebodied individuals sprint biomechanics. ...
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... The importance of mobility and stability in running can be seen when the body position maintains the body to stay upright when running, the legs that always move with the knees slightly bent, and the soles of the feet as a fulcrum must remain stable, so it is important to have good stability in running on the spine, ankles, and knees (Angin & Demirbüken, 2020;Ogaya et al., 2021). The drive to run is caused by a strong extension of the hip joint, knees, and ankles, which causes the body to project forward and upward towards the next step (Davis, 2016;Ogaya et al., 2021;Pandy et al., 2021). So it takes good lumbar mobility strength in order to maintain posture so as not to fall. ...
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In human gait analysis studies, the entire foot is typically modeled as a single rigid-body segment; however, this neglects power generated/absorbed within the foot. Here we show how treating the entire foot as a rigid body can lead to misunderstandings related to (biological and prosthetic) foot function, and distort our understanding of ankle and muscle-tendon dynamics. We overview various (unconventional) inverse dynamics methods for estimating foot power, partitioning ankle vs. foot contributions, and computing combined anklefoot power. We present two case study examples. The first exemplifies how modeling the foot as a single rigid-body segment causes us to overestimate (and overvalue) muscle-tendon power generated about the biological ankle (in this study by up to 77%), and to misestimate (and misinform on) foot contributions; corroborating findings from previous multi-segment foot modeling studies. The second case study involved an individual with transtibial amputation walking on 8 different prosthetic feet. The results exemplify how assuming a rigid foot can skew comparisons between biological and prosthetic limbs, and lead to incorrect conclusions when comparing different prostheses/interventions. Based on analytical derivations, empirical findings and prior literature we recommend against computing conventional ankle power (between shank-foot). Instead, we recommend using an alternative estimate of power generated about the ankle joint complex (between shank-calcaneus) in conjunction with an estimate of foot power (between calcaneus-ground); or using a combined anklefoot power calculation. We conclude that treating the entire foot as a rigid-body segment is often inappropriate and ill-advised. Including foot power in biomechanical gait analysis is necessary to enhance scientific conclusions, clinical evaluations and technology development.
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Article
Full-text available
Tendon elastic strain energy is the dominant contributor to muscle-tendon work during steady-state running. Does this behaviour also occur for sprint accelerations? We used experimental data and computational modelling to quantify muscle fascicle work and tendon elastic strain energy for the human ankle plantar flexors (specifically soleus and medial gastrocnemius) for multiple foot contacts of a maximal sprint as well as for running at a steady-state speed. Positive work done by the soleus and medial gastrocnemius muscle fascicles decreased incrementally throughout the maximal sprint and both muscles performed more work for the first foot contact of the maximal sprint (FC1) compared with steady-state running at 5 m s-1 (SS5). However, the differences in tendon strain energy for both muscles were negligible throughout the maximal sprint and when comparing FC1 to SS5. Consequently, the contribution of muscle fascicle work to stored tendon elastic strain energy was greater for FC1 compared with subsequent foot contacts of the maximal sprint and compared with SS5. We conclude that tendon elastic strain energy in the ankle plantar flexors is just as vital at the start of a maximal sprint as it is at the end, and as it is for running at a constant speed.
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Lower-limb joint mechanics during maximum acceleration sprinting
Article
  • Oct 2019
We explored how humans adjust the stance phase mechanical function of their major lower-limb joints (hip, knee, ankle) during maximum acceleration sprinting. Experimental data (motion capture and ground reaction force (GRF)) were recorded from eight participants as they performed overground sprinting trials. Six alternative starting locations were used to obtain a dataset that incorporated the majority of the acceleration phase. Experimental data were combined with an inverse-dynamics-based analysis to calculate lower-limb joint mechanical variables. As forward acceleration magnitude decreased, the vertical GRF impulse remained nearly unchanged whereas the net horizontal GRF impulse became smaller due to less propulsion and more braking. Mechanical function was adjusted at all three joints, although more dramatic changes were observed at the hip and ankle. The impulse from the ankle plantar-flexor moment was almost always larger than those from the hip and knee extensor moments. Forward acceleration magnitude was linearly related to the impulses from the hip extensor moment (R 2 =0.45) and the ankle plantar-flexor moment (R 2 =0.47). Forward acceleration magnitude was also linearly related to the net work done at all three joints, with the ankle displaying the strongest relationship (R 2 =0.64). The ankle produced the largest amount of positive work (1.55±0.17 J/kg) of all the joints, and provided a significantly greater proportion of the summed amount of lower-limb positive work as running speed increased and forward acceleration magnitude decreased. We conclude that the hip and especially the ankle represent key sources of positive work during the stance phase of maximum acceleration sprinting.
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External mechanical work done during the acceleration stage of maximal sprint running and its association with running performance
Article
  • Feb 2019
This study aimed to elucidate how external mechanical work done during maximal acceleration sprint running changes with increasing running velocity and is associated with running performance. In twelve young males, work done at each step over 50 m from the start was calculated from mechanical energy changes in horizontal anterior-posterior and vertical directions and was divided into braking (-Wkap and -Wv, respectively) and propulsive (+Wkap and +Wv, respectively) phases. The maximal running velocity (Vmax) appeared at 35.87±7.76 m and the time required to run 50 m (T50 m) was 7.11±0.54 s. At 80% Vmax or higher, +Wkap largely decreased and -Wkap abruptly increased. The change in the difference between +Wkap and |-Wkap| (ΔWkap) at every step was relatively small at 70% Vmax or lower. Total work done over 50 m was 82.4±7.5 J kg-1 for +Wkap, 36.2±4.4 J kg-1 for |-Wkap|, 14.3±1.9 J kg-1 for +Wv, and 10.4±1.2 J kg-1 for |-Wv|. The total ΔWkap over 50 m was more strongly correlated with T50 m (r=-0.946, P<0.0001) than the corresponding associations for the other work variables. These results indicate that in maximal sprint running over 50 m, work done during the propulsive phase in the horizontal anterior-posterior direction accounts for the majority of the total external work done during the acceleration stage, and maximizing it while suppressing work done during the braking phase is essential to achieve a high running performance.
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Association of Sprint Performance With Ground Reaction Forces During Acceleration and Maximal Speed Phases in a Single Sprint
Article
  • Sep 2017
We aimed to clarify the mechanical determinants of sprinting performance during acceleration and maximal speed phases of a single sprint, using ground reaction forces (GRFs). While 18 male athletes performed a 60-m sprint, GRF was measured at every step over a 50-m distance from the start. Variables during the entire acceleration phase were approximated with a fourth-order polynomial. Subsequently, accelerations at 55%, 65%, 75%, 85%, and 95% of maximal speed, and running speed during the maximal speed phase were determined as sprinting performance variables. Ground reaction impulses and mean GRFs during the acceleration and maximal speed phases were selected as independent variables. Stepwise multiple regression analysis selected propulsive and braking impulses as contributors to acceleration at 55%-95% (β > 0.724) and 75%-95% (β > 0.176), respectively, of maximal speed. Moreover, mean vertical force was a contributor to maximal running speed (β = 0.481). The current results demonstrate that exerting a large propulsive force during the entire acceleration phase, suppressing braking force when approaching maximal speed, and producing a large vertical force during the maximal speed phase are essential for achieving greater acceleration and maintaining higher maximal speed, respectively.
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Why are Antagonist Muscles Co-activated in My Simulation? A Musculoskeletal Model for Analysing Human Locomotor Tasks
Article
  • Sep 2017
Existing “off-the-shelf” musculoskeletal models are problematic when simulating movements that involve substantial hip and knee flexion, such as the upstroke of pedalling, because they tend to generate excessive passive fibre force. The goal of this study was to develop a refined musculoskeletal model capable of simulating pedalling and fast running, in addition to walking, which predicts the activation patterns of muscles better than existing models. Specifically, we tested whether the anomalous co-activation of antagonist muscles, commonly observed in simulations, could be resolved if the passive forces generated by the underlying model were diminished. We refined the OpenSim™ model published by Rajagopal et al. (IEEE Trans Biomed Eng 63:1–1, 2016) by increasing the model’s range of knee flexion, updating the paths of the knee muscles, and modifying the force-generating properties of eleven muscles. Simulations of pedalling, running and walking based on this model reproduced measured EMG activity better than simulations based on the existing model—even when both models tracked the same subject-specific kinematics. Improvements in the predicted activations were associated with decreases in the net passive moments; for example, the net passive knee moment during the upstroke of pedalling decreased from 36.9 N m (existing model) to 6.3 N m (refined model), resulting in a dramatic decrease in the co-activation of knee flexors. The refined model is available from SimTK.org and is suitable for analysing movements with up to 120° of hip flexion and 140° of knee flexion.
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