Walking Speed at Self-Selected Exercise Pace Is Lower but Energy Cost Higher in Older Versus Younger Women

2009 ◽  
Vol 6 (3) ◽  
pp. 327-332 ◽  
Author(s):  
Lynnette M. Jones ◽  
Debra L. Waters ◽  
Michael Legge
Keyword(s):  
Older Women ◽  
Energy Cost ◽  
Walking Speed ◽  
Metabolic Cost ◽  
Energetic Cost ◽  
Energy Costs ◽  
Energy Equivalent ◽  
Younger Women ◽  
Exercise Modality ◽  
Walking Speeds

Background:Walking is usually undertaken at a speed that coincides with the lowest metabolic cost. Aging however, alters the speed–cost relationship, as preferred walking speeds decrease and energy costs increase. It is unclear to what extent this relationship is affected when older women undertake walking as an exercise modality. The aim of this study was to compare the energetic cost of walking at a self-selected exercise pace for 30 min in older and younger women.Methods:The energetic cost of walking was assessed using the energy equivalent of oxygen consumption measured in 18 young (25 to 49 y) and 20 older (50 to 79 y) women who were asked to walk at their “normal” exercise pace on a motorized treadmill for 30 min.Results:The mass-specific net cost of walking (Cw) was 15% higher and self-selected walking speed was 23% lower in the older women than in the younger group. When speed was held constant, the Cw was 0.30 (J · .kg−1 · m−1) higher in the older women.Conclusions:Preferred exercise pace incurs a higher metabolic cost in older women and needs be taken into consideration when recommending walking as an exercise modality.

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.

scholarly journals Optimized hip–knee–ankle exoskeleton assistance at a range of walking speeds

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Gwendolyn M. Bryan ◽  
Patrick W. Franks ◽  
Seungmoon Song ◽  
Alexandra S. Voloshina ◽  
Ricardo Reyes ◽  
...  
Keyword(s):  
Walking Speed ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Positive Power ◽  
Fast Walking ◽  
Slow Walking ◽  
Limited Success ◽  
Ankle Exoskeleton ◽  
Walking Speeds ◽  
The Relationship

Abstract Background Autonomous exoskeletons will need to be useful at a variety of walking speeds, but it is unclear how optimal hip–knee–ankle exoskeleton assistance should change with speed. Biological joint moments tend to increase with speed, and in some cases, optimized ankle exoskeleton torques follow a similar trend. Ideal hip–knee–ankle exoskeleton torque may also increase with speed. The purpose of this study was to characterize the relationship between walking speed, optimal hip–knee–ankle exoskeleton assistance, and the benefits to metabolic energy cost. Methods We optimized hip–knee–ankle exoskeleton assistance to reduce metabolic cost for three able-bodied participants walking at 1.0 m/s, 1.25 m/s and 1.5 m/s. We measured metabolic cost, muscle activity, exoskeleton assistance and kinematics. We performed Friedman’s tests to analyze trends across walking speeds and paired t-tests to determine if changes from the unassisted conditions to the assisted conditions were significant. Results Exoskeleton assistance reduced the metabolic cost of walking compared to wearing the exoskeleton with no torque applied by 26%, 47% and 50% at 1.0, 1.25 and 1.5 m/s, respectively. For all three participants, optimized exoskeleton ankle torque was the smallest for slow walking, while hip and knee torque changed slightly with speed in ways that varied across participants. Total applied positive power increased with speed for all three participants, largely due to increased joint velocities, which consistently increased with speed. Conclusions Exoskeleton assistance is effective at a range of speeds and is most effective at medium and fast walking speeds. Exoskeleton assistance was less effective for slow walking, which may explain the limited success in reducing metabolic cost for patient populations through exoskeleton assistance. Exoskeleton designers may have more success when targeting activities and groups with faster walking speeds. Speed-related changes in optimized exoskeleton assistance varied by participant, indicating either the benefit of participant-specific tuning or that a wide variety of torque profiles are similarly effective.

ACCELEROMETER-DETERMINED INTENSITY AND DURATION OF HABITUAL PHYSICAL ACTIVITY AND WALKING PERFORMANCE IN WELL-FUNCTIONING MIDDLE-AGED AND OLDER WOMEN: A CROSS-SECTIONAL STUDY

2019 ◽  
pp. 1-5
Author(s):  
R.S. Thiebaud ◽  
T. Abe ◽  
M. Ogawa ◽  
J.P. Loenneke ◽  
N. Mitsukawa
Keyword(s):  
Physical Activity ◽  
Older Women ◽  
Walking Speed ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Knee Extension ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Knee Extension Strength ◽  
Walking Speeds

ackground: The association of physical activity (PA) intensities and duration spent in those activities with different walking tasks remains unclear. Objectives: To examine the association between the duration of PA intensities and three walking speeds (usual walking speed, maximal walking speed and zig-zag walking speed). Design: Multiple linear regression analysis was used to estimate the association of age, BMI, maximum knee extension strength, light PA, moderate PA and vigorous PA with walking speeds. Setting: University lab. Participants: Eighty-six older women (67 ± 7 years). Measurements: PA was measured for 30 consecutive days using the Lifecorder-EX accelerometer. Exercise intensity was categorized as light (levels 1-3), moderate (levels 4-6) and vigorous (levels 7-9) based on the manufacturer algorithms. Usual straight walking speed (20 m), maximal straight walking speed (20 m) and zig-zag walking speed tests (10 m) were performed by each participant. Results: For the usual straight walking speed model (R2 = 0.296, SEE = 0.15 m/s), the significant predictors were BMI, knee extension strength, light PA and vigorous PA. For the maximal straight walking speed model (R2 = 0.326, SEE = 0.20 m/s), only age was a significant predictor. For the zig-zag walking speed model (R2=0.417, SEE = 0.14 m/s), age and maximum knee strength were significant predictors in the model. Conclusions: Overall, the results of this study suggest that vigorous PA and maximal knee extension strength are two important factors that are associated with different walking speeds in older women.

Influences of age and gender on human thermoregulatory responses to cold exposures

1985 ◽  
Vol 58 (1) ◽  
pp. 180-186 ◽  
Author(s):  
J. A. Wagner ◽  
S. M. Horvath
Keyword(s):  
Older Women ◽  
Body Fat ◽  
Young Women ◽  
Cold Exposure ◽  
Physiological Responses ◽  
Metabolic Cost ◽  
Older Men ◽  
Age And Gender ◽  
Younger Women ◽  
And Gender

To delineate age- and gender-related differences in physiological responses to cold exposure, men and women between the ages of 20 and 29 yr and 51 and 72 yr, wearing minimal clothing, were exposed at rest for 2 h to 28, 20, 15, and 10 degrees C room temperatures with 40% relative humidity. During the coldest exposure, the rates of increase in metabolic rate (W X m-2 or ml X kg lean body mass-1 X min-1 were similar for all groups. However, older women (n = 7) may have benefited from a larger (P less than 0.05) early metabolic (M) increase (40% within 15 min) than young men (18%) (n = 10), young women (5%) (n = 10), or older men (5%) (n = 10). A similar rapid M response in older women occurred during the 15 degrees C exposure. During all cold exposures, older women maintained constant rectal temperature (Tre) and young women maintained Tre only during the 20 degrees C exposures, whereas Tre of the men declined during all cold exposures (P less than 0.01). Changes in Tre and mean skin temperature (Ts) during cold exposure were largely related to body fat, although age and surface area/mass modified the changes in men. The data suggest that older men are more susceptible to cold ambients than younger people, since they did not prevent a further decline in their initially relatively low Tre. Despite greater insulation from body fat, the older women maintained a constant Tre at greater metabolic cost than men or younger women.

Individual Leg Muscle Contributions to the Cost of Walking: Effects of Age and Walking Speed

2017 ◽  
Vol 25 (2) ◽  
pp. 295-304 ◽  
Author(s):  
Patricio A. Pincheira ◽  
Lauri Stenroth ◽  
Janne Avela ◽  
Neil J. Cronin
Keyword(s):  
Energy Cost ◽  
Young Group ◽  
Energetic Cost ◽  
Elderly Subjects ◽  
Older Individuals ◽  
Cost Of Transport ◽  
Leg Muscles ◽  
Lower Limb Muscles ◽  
Walking Speeds ◽  
The Cost

This study examined the contributions of individual muscles to changes in energetic cost of transport (COT) over seven walking speeds, and compared results between healthy young and elderly subjects. Twenty six participants (13 young aged 18–30; 13 old aged 70–80) were recruited. COT (O2/kg body mass/km) was calculated by standardizing the mean oxygen consumption recorded during steady state walking. Electromyography signals from 10 leg muscles were used to calculate the cumulative activity required to traverse a unit of distance (CMAPD) for each muscle at each speed. In the old group CMAPD was correlated with COT, presented higher and more variable values, and showed greater increases around optimal speed for all studied muscles. Soleus CMAPD was independent of speed in the young group, but this was not evident with aging. Greater energy cost of walking in older individuals seems to be attributable to increased energy cost of all lower limb muscles.

scholarly journals Quantifying Cause-Effect Relations Between Walking Speed, Propulsive Force, and Metabolic Cost

2021 ◽  
Author(s):  
Richard Pimentel ◽  
Jordan N Feldman ◽  
Michael D Lewek ◽  
Jason R Franz
Keyword(s):  
Young Adults ◽  
Health Status ◽  
Time Course ◽  
Walking Speed ◽  
Metabolic Cost ◽  
Propulsive Force ◽  
Metabolic Power ◽  
Cost Of Transport ◽  
Walking Speeds ◽  
Variance Explained

Walking speed is a useful surrogate for health status across the population. Walking speed appears to be governed in part by propulsive force (FP) generated during push-off and simultaneously optimized to minimize metabolic cost. However, no study to our knowledge has established empirical cause-effect relations between FP, walking speed, and metabolic cost, even in young adults. To overcome the potential linkage between these factors, we used a self-paced treadmill controller and real-time biofeedback to independently prescribe walking speed or FP across a range of condition intensities. Walking with larger and smaller FP led to instinctively faster and slower walking speeds, respectively, with about 80% of variance explained between those outcomes. We also found that comparable changes in either FP or walking speed elicited predictable and relatively uniform changes in metabolic cost, each explaining about ~53% of the variance in net metabolic power and ~15% of the variance in cost of transport, respectively. These findings build confidence that interventions designed to increase FP will translate to improved walking speed. Repeating this protocol in other populations may identify additional cause-effect relations that could inform the time course of gait decline due to age and disease.

scholarly journals Latent power of basking sharks revealed by exceptional breaching events

2018 ◽  
Vol 14 (9) ◽  
pp. 20180537 ◽  
Author(s):  
Emmett M. Johnston ◽  
Lewis G. Halsey ◽  
Nicholas L. Payne ◽  
Alison A. Kock ◽  
Gil Iosilevskii ◽  
...  
Keyword(s):  
Energy Cost ◽  
Mechanical Energy ◽  
Metabolic Cost ◽  
White Shark ◽  
Energetic Cost ◽  
Data Logger ◽  
Filter Feeding ◽  
Video Footage ◽  
Great White Shark ◽  
Basking Shark

The fast swimming and associated breaching behaviour of endothermic mackerel sharks is well suited to the capture of agile prey. In contrast, the observed but rarely documented breaching capability of basking sharks is incongruous to their famously languid lifestyle as filter-feeding planktivores. Indeed, by analysing video footage and an animal-instrumented data logger, we found that basking sharks exhibit the same vertical velocity (approx. 5 m s −1 ) during breach events as the famously powerful predatory great white shark. We estimate that an 8-m, 2700-kg basking shark, recorded breaching at 5 m s −1 and accelerating at 0.4 m s −2 , expended mechanical energy at a rate of 5.5 W kg −1 ; a mass-specific energetic cost comparable to that of the great white shark. The energy cost of such a breach is equivalent to around 1/17th of the daily standard metabolic cost for a basking shark, while the ratio is about half this for a great white shark. While breaches by basking sharks must serve a different function to white shark breaches, their similar breaching speeds questions our perception of the physiology of large filter-feeding fish.

scholarly journals Pre-crastination: time uncertainty increases walking effort

2020 ◽  
Author(s):  
E Hong Tiew ◽  
Nidhi Seethapathi ◽  
Manoj Srinivasan
Keyword(s):  
Energy Cost ◽  
High Probability ◽  
Time Estimation ◽  
Optimal Feedback Control ◽  
Time Constraints ◽  
Energy Costs ◽  
Time Duration ◽  
Time Uncertainty ◽  
Walking Speeds ◽  
The Given

AbstractIn many circumstances, humans walk in a manner that approximately minimizes energy cost. Here, we performed human subject experiments to examine how having a time constraint affects the speeds at which humans walk. First, we measured subjects’ preferred walking speeds to travel a given distance in the absence of any time constraints. Then, we asked subjects to travel the same distance under different time constraints. That is, they had to travel the given distance within the time duration provided – they can arrive early, but not late. Under these constraints, subjects systematically arrived earlier than necessary. Surprisingly, even when the time duration provided was large enough to walk at their unconstrained preferred speeds, subjects walked systematically faster than their unconstrained preferred speed. We propose that this faster-than-energy optimal speeds may be due to human uncertainty in time estimation. We show that a model assuming that humans perform stochastic optimal feedback control to arrive on time with high probability while minimizing expected energy costs predicts walking speeds higher than energy optimal, as observed in experiment.

The Cost of Gait Slowness: Can Persons with Parkinson’s Disease Save Energy by Walking Faster?

2021 ◽  
Vol 11 (4) ◽  
pp. 2073-2084
Author(s):  
Purnima Padmanabhan ◽  
Keerthana Sreekanth Rao ◽  
Anthony J. Gonzalez ◽  
Alexander Y. Pantelyat ◽  
Vikram S. Chib ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Energy Cost ◽  
Walking Speed ◽  
Patient Specific ◽  
Dopaminergic Medication ◽  
Gait Parameters ◽  
Save Energy ◽  
Walking Speeds ◽  
The Cost

Background: Gait slowing is a common feature of Parkinson’s disease (PD). Many therapies aim to improve gait speed in persons with PD, but goals are often imprecise. How fast should each patient walk? And how do persons with PD benefit from walking faster? There is an important need to understand how walking speed affects fundamental aspects of gait—including energy cost and stability—that could guide individualized therapy decisions in persons with PD. Objective: We investigated how changes in walking speed affected energy cost and spatiotemporal gait parameters in persons with PD. We compared these effects between dopaminergic medication states and to those observed in age-matched control participants. Methods: Twelve persons with PD and twelve control participants performed treadmill walking trials spanning at least five different speeds (seven speeds were desired, but not all participants could walk at the fastest speeds). Persons with PD participated in two walking sessions on separate days (once while optimally medicated, once after 12-hour withdrawal from dopaminergic medication). We measured kinematic and metabolic data across all trials. Results: Persons with PD significantly reduced energy cost by walking faster than their preferred speeds. This held true across medication conditions and was not observed in control participants. The patient-specific walking speeds that reduced energy cost did not significantly affect gait variability metrics (used as proxies for gait stability). Conclusion: The gait slowing that occurs with PD results in energetically suboptimal walking. Rehabilitation strategies that target patient-specific increases in walking speed could result in a less effortful gait.

Fast visual prediction and slow optimization of preferred walking speed

2012 ◽  
Vol 107 (9) ◽  
pp. 2549-2559 ◽  
Author(s):  
Shawn M. O'Connor ◽  
J. Maxwell Donelan
Keyword(s):  
Nervous System ◽  
Healthy Subjects ◽  
Walking Speed ◽  
Prior Experience ◽  
Sensory Information ◽  
Energetic Cost ◽  
The Subject ◽  
Walking Speeds ◽  
Visual Speed ◽  
Direction Opposite

People prefer walking speeds that minimize energetic cost. This may be accomplished by directly sensing metabolic rate and adapting gait to minimize it, but only slowly due to the compounded effects of sensing delays and iterative convergence. Visual and other sensory information is available more rapidly and could help predict which gait changes reduce energetic cost, but only approximately because it relies on prior experience and an indirect means to achieve economy. We used virtual reality to manipulate visually presented speed while 10 healthy subjects freely walked on a self-paced treadmill to test whether the nervous system beneficially combines these two mechanisms. Rather than manipulating the speed of visual flow directly, we coupled it to the walking speed selected by the subject and then manipulated the ratio between these two speeds. We then quantified the dynamics of walking speed adjustments in response to perturbations of the visual speed. For step changes in visual speed, subjects responded with rapid speed adjustments (lasting <2 s) and in a direction opposite to the perturbation and consistent with returning the visually presented speed toward their preferred walking speed, when visual speed was suddenly twice (one-half) the walking speed, subjects decreased (increased) their speed. Subjects did not maintain the new speed but instead gradually returned toward the speed preferred before the perturbation (lasting >300 s). The timing and direction of these responses strongly indicate that a rapid predictive process informed by visual feedback helps select preferred speed, perhaps to complement a slower optimization process that seeks to minimize energetic cost.

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