scholarly journals Muscle mechanics and energy expenditure of the triceps surae during rearfoot and forefoot running

2018 ◽  
Author(s):  
Allison H. Gruber ◽  
Brian R. Umberger ◽  
Ross H. Miller ◽  
Joseph Hamill
Keyword(s):  
Energy Expenditure ◽  
Elastic Energy ◽  
Reaction Force ◽  
Metabolic Cost ◽  
Running Economy ◽  
Mechanical Work ◽  
Triceps Surae ◽  
Metabolic Energy ◽  
Forefoot Running ◽  
Metabolic Energy Expenditure

ABSTRACTForefoot running is advocated to improve running economy because of increased elastic energy storage than rearfoot running. This claim has not been assessed with methods that predict the elastic energy contribution to positive work or estimate muscle metabolic cost. The purpose of this study was to compare the mechanical work and metabolic cost of the gastrocnemius and soleus between rearfoot and forefoot running. Seventeen rearfoot and seventeen forefoot runners ran over-ground with their habitual footfall pattern (3.33-3.68m•s−1) while collecting motion capture and ground reaction force data. Ankle and knee joint angles and ankle joint moments served as inputs into a musculoskeletal model that calculated the mechanical work and metabolic energy expenditure of each muscle using Hill-based muscle models with contractile (CE) and series elastic (SEE) elements. A mixed-factor ANOVA assessed the difference between footfall patterns and groups (α=0.05). Forefoot running resulted in greater SEE mechanical work in the gastrocnemius than rearfoot running but no differences were found in CE mechanical work or CE metabolic energy expenditure. Forefoot running resulted in greater soleus SEE and CE mechanical work and CE metabolic energy expenditure than rearfoot running. The metabolic cost associated with greater CE velocity, force production, and activation during forefoot running may outweigh any metabolic energy savings associated with greater SEE mechanical work. Therefore, there was no energetic benefit at the triceps surae for one footfall pattern or the other. The complex CE-SEE interactions must be considered when assessing muscle metabolic cost, not just the amount of SEE strain energy.

The relationship between mechanical work and energy expenditure of locomotion in horses

1999 ◽  
Vol 202 (17) ◽  
pp. 2329-2338 ◽  
Author(s):  
A.E. Minetti ◽  
L.P. Ardigò ◽  
E. Reinach ◽  
F. Saibene
Keyword(s):  
Energy Expenditure ◽  
Elastic Energy ◽  
Three Dimensional ◽  
Indirect Evidence ◽  
The Body ◽  
Mechanical Work ◽  
Metabolic Energy ◽  
Centre Of Mass ◽  
External Work ◽  
Metabolic Energy Expenditure

Three-dimensional motion capture and metabolic assessment were performed on four standardbred horses while walking, trotting and galloping on a motorized treadmill at different speeds. The mechanical work was partitioned into the internal work (W(INT)), due to the speed changes of body segments with respect to the body centre of mass, and the external work (W(EXT)), due to the position and speed changes of the body centre of mass with respect to the environment. The estimated total mechanical work (W(TOT)=W(INT)+W(EXT)) increased with speed, while metabolic work (C) remained rather constant. As a consequence, the ‘apparent efficiency’ (eff(APP)=W(TOT)/C) increased from 10 % (walking) to over 100 % (galloping), setting the highest value to date for terrestrial locomotion. The contribution of elastic structures in the horse's limbs was evaluated by calculating the elastic energy stored and released during a single bounce (W(EL,BOUNCE)), which was approximately 1.23 J kg(−)(1) for trotting and up to 6 J kg(−)(1) for galloping. When taking into account the elastic energy stored by the spine bending and released as W(INT), as suggested in the literature for galloping, W(EL,BOUNCE) was reduced by 0.88 J kg(−)(1). Indirect evidence indicates that force, in addition to mechanical work, is also a determinant of the metabolic energy expenditure in horse locomotion.

scholarly journals Human walking in the real world: Interactions between terrain type, gait parameters, and energy expenditure

2019 ◽  
Author(s):  
DB Kowalsky ◽  
JR Rebula ◽  
LV Ojeda ◽  
PG Adamczyk ◽  
AD Kuo
Keyword(s):  
Energy Expenditure ◽  
Real World ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Least Squares Regression ◽  
The Real ◽  
Terrain Type ◽  
Gait Parameters ◽  
Surface Irregularities ◽  
Metabolic Energy Expenditure

AbstractHumans often traverse real-world environments with a variety of surface irregularities and inconsistencies, which can disrupt steady gait and require additional effort. Such effects have, however, scarcely been demonstrated quantitatively, because few laboratory biomechanical measures apply outdoors. Walking can nevertheless be quantified by other means. In particular, the foot’s trajectory in space can be reconstructed from foot-mounted inertial measurement units (IMUs), to yield measures of stride and associated variabilities. But it remains unknown whether such measures are related to metabolic energy expenditure. We therefore quantified the effect of five different outdoor terrains on foot motion (from IMUs) and net metabolic rate (from oxygen consumption) in healthy adults (N = 10; walking at 1.25 m/s). Energy expenditure increased significantly (P < 0.05) in the order Sidewalk, Dirt, Gravel, Grass, and Woodchips, with Woodchips about 27% costlier than Sidewalk. Terrain type also affected measures, particularly stride variability and virtual foot clearance (swing foot’s lowest height above consecutive footfalls). In combination, such measures can also roughly predict metabolic cost (adjusted R2 = 0.52, partial least squares regression), and even discriminate between terrain types (10% reclassification error). Body-worn sensors can characterize how uneven terrain affects gait, gait variability, and metabolic cost in the real world.

scholarly journals Metabolic cost calculations of gait using musculoskeletal energy models, a comparison study

2019 ◽  
Author(s):  
Anne D. Koelewijn ◽  
Dieter Heinrich ◽  
Antonie J. van den Bogert
Keyword(s):  
Experimental Data ◽  
Gas Exchange ◽  
Energy Expenditure ◽  
Repeated Measures ◽  
Metabolic Cost ◽  
Pulmonary Gas Exchange ◽  
Metabolic Energy ◽  
Energy Models ◽  
Cost Calculations ◽  
Metabolic Energy Expenditure

AbstractThis paper compares predictions of metabolic energy expenditure in gait using seven metabolic energy expenditure models to assess their correlation with experimental data. Ground reaction forces, marker data, and pulmonary gas exchange data were recorded for six walking trials at combinations of two speeds, 0.8 m/s and 1.3 m/s, and three inclines, −8% (downhill), level, and 8% (uphill). The metabolic cost, calculated with the metabolic energy models was compared to the metabolic cost from the pulmonary gas exchange rates. A repeated measures correlation showed that all models correlated well with experimental data, with correlations of at least 0.9. The model by Bhargava et al. [7] and the model by Lichtwark and Wilson [21] had the highest correlation, 0.96. The model by Margaria [23] predicted the increase in metabolic cost following a change in dynamics best in absolute terms.

scholarly journals Human walking in the real world: Interactions between terrain type, gait parameters, and energy expenditure

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0228682
Author(s):  
Daniel B. Kowalsky ◽  
John R. Rebula ◽  
Lauro V. Ojeda ◽  
Peter G. Adamczyk ◽  
Arthur D. Kuo
Keyword(s):  
Energy Expenditure ◽  
Real World ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Least Squares Regression ◽  
The Real ◽  
Terrain Type ◽  
Gait Parameters ◽  
Surface Irregularities ◽  
Metabolic Energy Expenditure

Humans often traverse real-world environments with a variety of surface irregularities and inconsistencies, which can disrupt steady gait and require additional effort. Such effects have, however, scarcely been demonstrated quantitatively, because few laboratory biomechanical measures apply outdoors. Walking can nevertheless be quantified by other means. In particular, the foot’s trajectory in space can be reconstructed from foot-mounted inertial measurement units (IMUs), to yield measures of stride and associated variabilities. But it remains unknown whether such measures are related to metabolic energy expenditure. We therefore quantified the effect of five different outdoor terrains on foot motion (from IMUs) and net metabolic rate (from oxygen consumption) in healthy adults (N = 10; walking at 1.25 m/s). Energy expenditure increased significantly (P < 0.05) in the order Sidewalk, Dirt, Gravel, Grass, and Woodchips, with Woodchips about 27% costlier than Sidewalk. Terrain type also affected measures, particularly stride variability and virtual foot clearance (swing foot’s lowest height above consecutive footfalls). In combination, such measures can also roughly predict metabolic cost (adjusted R2 = 0.52, partial least squares regression), and even discriminate between terrain types (10% reclassification error). Body-worn sensors can characterize how uneven terrain affects gait, gait variability, and metabolic cost in the real world.

Ambulatory foot contact monitor to estimate metabolic cost of human locomotion

1994 ◽  
Vol 76 (4) ◽  
pp. 1818-1822 ◽  
Author(s):  
R. W. Hoyt ◽  
J. J. Knapik ◽  
J. F. Lanza ◽  
B. H. Jones ◽  
J. S. Staab
Keyword(s):  
Energy Expenditure ◽  
Cross Validation ◽  
Resting Energy Expenditure ◽  
Metabolic Cost ◽  
Human Locomotion ◽  
Metabolic Energy ◽  
Total Rate ◽  
Highly Correlated ◽  
Metabolic Energy Expenditure ◽  
Average Individual

The rate of metabolic energy expenditure during locomotion (Mloco) is proportional to body weight (Wb) divided by the time during each stride that a single foot contacts the ground (tc) (Nature Lond. 346: 265–267, 1990). Using this knowledge, we developed an electronic foot contact monitor. Our objective was to derive and cross-validate an equation for estimation Mloco from Wb/tc. Twelve males were tested [age = 19.4 +/- 1.4 (SD) yr, Wb = 78.4 +/- 8.0 kg] during horizontal treadmill walking (0.89, 1.34, and 1.79 m/s) and running (2.46, 2.91, and 3.35 m/s). Measured Mloco was defined as the total rate of energy expenditure, measured by indirect calorimetry, minus the estimated rate of resting energy expenditure. The equation to estimate Mloco was derived in six randomly selected subjects: Mloco = 3.702.(Wb/tc) - 149.6 (r2 = 0.93). Cross-validation in the remaining six subjects showed that estimated and measured Mloco were highly correlated (r2 = 0.97). The average individual error between estimated and measured Mloco was 0% (range -22 to 29%). In conclusion, Mloco can be accurately estimated from Wb and measurements of tc made by an ambulatory foot contact monitor.

scholarly journals Reduced Achilles Tendon Stiffness Disrupts Calf Muscle Neuromechanics in Elderly Gait

Gerontology ◽  
2021 ◽  
pp. 1-11
Author(s):  
Rebecca L. Krupenevich ◽  
Owen N. Beck ◽  
Gregory S. Sawicki ◽  
Jason R. Franz
Keyword(s):  
Older Adults ◽  
Achilles Tendon ◽  
Metabolic Cost ◽  
Calf Muscle ◽  
Metabolic Energy ◽  
Joint Work ◽  
Tendon Stiffness ◽  
Age Related ◽  
Ankle Muscle ◽  
Metabolic Energy Expenditure

Older adults walk slower and with a higher metabolic energy expenditure than younger adults. In this review, we explore the hypothesis that age-related declines in Achilles tendon stiffness increase the metabolic cost of walking due to less economical calf muscle contractions and increased proximal joint work. This viewpoint may motivate interventions to restore ankle muscle-tendon stiffness, improve walking mechanics, and reduce metabolic cost in older adults.

scholarly journals Elastic energy savings and active energy cost in a simple model of running

2021 ◽  
Vol 17 (11) ◽  
pp. e1009608
Author(s):  
Ryan T. Schroeder ◽  
Arthur D. Kuo
Keyword(s):  
Elastic Energy ◽  
Energy Cost ◽  
Energy Savings ◽  
Mechanical Energy ◽  
Metabolic Cost ◽  
The Body ◽  
Metabolic Energy ◽  
Energetic Cost ◽  
Mass Model ◽  
Human Running

The energetic economy of running benefits from tendon and other tissues that store and return elastic energy, thus saving muscles from costly mechanical work. The classic “Spring-mass” computational model successfully explains the forces, displacements and mechanical power of running, as the outcome of dynamical interactions between the body center of mass and a purely elastic spring for the leg. However, the Spring-mass model does not include active muscles and cannot explain the metabolic energy cost of running, whether on level ground or on a slope. Here we add explicit actuation and dissipation to the Spring-mass model, and show how they explain substantial active (and thus costly) work during human running, and much of the associated energetic cost. Dissipation is modeled as modest energy losses (5% of total mechanical energy for running at 3 m s-1) from hysteresis and foot-ground collisions, that must be restored by active work each step. Even with substantial elastic energy return (59% of positive work, comparable to empirical observations), the active work could account for most of the metabolic cost of human running (about 68%, assuming human-like muscle efficiency). We also introduce a previously unappreciated energetic cost for rapid production of force, that helps explain the relatively smooth ground reaction forces of running, and why muscles might also actively perform negative work. With both work and rapid force costs, the model reproduces the energetics of human running at a range of speeds on level ground and on slopes. Although elastic return is key to energy savings, there are still losses that require restorative muscle work, which can cost substantial energy during running.

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