A Model of Human Muscle Energy Expenditure

Umberger, Brian R.; Gerritsen, Karin G.M.; Martin, Philip E.

doi:10.1080/1025584031000091678

Cited by 304 publications

(274 citation statements)

References 75 publications

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“…A Hilltype muscle model (van Soest & Bobbert 1993;Nagano & Gerritsen 2001) was used to model muscle contraction dynamics, along with an additional set of model equations that were used to predict muscle metabolic energy consumption (Umberger et al 2003). The 'standard' muscle model parameters described in Umberger et al (2006) were used in the present study, and represented population averages for muscle fibre type distribution in each muscle.…”

Section: Simulation Modelmentioning

confidence: 99%

“…Some of the limitations of studying muscle function during locomotion experimentally in humans can be overcome by using musculoskeletal modelling and computer simulation techniques (Zajac et al 2003). Musculoskeletal modelling studies of human walking have typically focused on the mechanics and control of locomotion; yet, it is also possible to predict the metabolic cost of muscle actions if an appropriate model is used (Umberger et al 2003;Bhargava et al 2004;Lichtwark & Wilson 2005).…”

Section: Introductionmentioning

confidence: 99%

“…Yet, there is still much uncertainty regarding the associated metabolic costs. Using a model of muscle energy expenditure (Umberger et al 2003), it is possible to derive estimates of the metabolic cost incurred by the muscles during each phase of the gait cycle. Therefore, the purpose of this study was to estimate the metabolic costs of the stance and swing phases in human walking at a single speed and three different stride rates, using a modelling and simulation approach.…”

Section: Introductionmentioning

confidence: 99%

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Stance and swing phase costs in human walking

Umberger

2010

J. R. Soc. Interface.

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Leg swing in human walking has historically been viewed as a passive motion with little metabolic cost. Recent estimates of leg swing costs are equivocal, covering a range from 10 to 33 per cent of the net cost of walking. There has also been a debate as to whether the periods of double-limb support during the stance phase dominate the cost of walking. Part of this uncertainty is because of our inability to measure metabolic energy consumption in individual muscles during locomotion. Therefore, the purpose of this study was to investigate the metabolic cost of walking using a modelling approach that allowed instantaneous energy consumption rates in individual muscles to be estimated over the full gait cycle. At a typical walking speed and stride rate, leg swing represented 29 per cent of the total muscular cost. During the stance phase, the double-limb and single-limb support periods accounted for 27 and 44 per cent of the total cost, respectively. Performing step-to-step transitions, which encompasses more than just the double-support periods, represented 37 per cent of the total cost of walking. Increasing stride rate at a constant speed led to greater double-limb support costs, lower swing phase costs and no change in single-limb support costs. Together, these results provide unique insight as to how metabolic energy is expended over the human gait cycle.

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Section: Simulation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stance and swing phase costs in human walking

Umberger

2010

J. R. Soc. Interface.

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230

228

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“…The CMC algorithm (Thelen and Anderson, 2006) was run for each gait cycle, with a concurrent metabolics probe used to compute the instantaneous metabolic power consumption, E ( t ) , for each muscle in the model. This probe computes the metabolic power consumption according to a muscle energetics model implemented by the OpenSim developers (Uchida et al, 2016a), which in turn is based on a previous model (Umberger et al, 2003).…”

Section: Modelling Metabolic Power Consumptionmentioning

confidence: 99%

Effectively Quantifying the Performance of Lower-Limb Exoskeletons Over a Range of Walking Conditions

2018

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Exoskeletons and other wearable robotic devices have a wide range of potential applications, including assisting patients with walking pathologies, acting as tools for rehabilitation, and enhancing the capabilities of healthy humans. However, applying these devices effectively in a real-world setting can be challenging, as the optimal design features and control commands for an exoskeleton are highly dependent on the current user, task and environment. Consequently, robust metrics and methods for quantifying exoskeleton performance are required. This work presents an analysis of walking data collected for healthy subjects walking with an active pelvis exoskeleton over three assistance scenarios and five walking contexts. Spatial and temporal, kinematic, kinetic and other novel dynamic gait metrics were compared to identify which metrics exhibit desirable invariance properties, and so are good candidates for use as a stability metric over varying walking conditions. Additionally, using a model-based approach, the average metabolic power consumption was calculated for a subset of muscles crossing the hip, knee and ankle joints, and used to analyse how the energy-reducing properties of an exoskeleton are affected by changes in walking context. The results demonstrated that medio-lateral centre of pressure displacement and medio-lateral margin of stability exhibit strong invariance to changes in walking conditions. This suggests that these dynamic gait metrics are optimised in human gait and are potentially suitable metrics for optimising in an exoskeleton control paradigm. The effectiveness of the exoskeleton at reducing human energy expenditure was observed to increase when walking on an incline, where muscles aiding in hip flexion were assisted, but decrease when walking at a slow speed. These results underline the need for adaptive control algorithms for exoskeletons if they are to be used in varied environments.

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“…1a), considering the heat production model proposed by Umberger et al [7]. Parameters for the muscle models are adopted from Gerritsen et al [8].…”

Section: Static Optimization Approachmentioning

confidence: 99%

Sensitivity Analysis of Human Leg Metabolical Costs

Ackermann

Schiehlen

2005

Proc Appl Math and Mech

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The human walking is characterized by skeletal dynamics and muscle excitation patterns minimizing the metabolical energy. This criterion is applied to assess the performance of lower limb prosthetic devices, and to evaluate therapies for patients presenting gait disorders. It is desirable, therefore, to dispose models of the human normal and pathological gaits capable of estimating the metabolical energy expenditure.For the swing phase of normal and pathological gaits a musculoskeletal model of the lower limb is presented to estimate metabolical energy expenditure. The mechanical model has three degrees of freedom and is actuated by eight Hill-type muscle units, and the model for the metabolical costs is adopted from literature. In this paper a combination of inverse and direct dynamics is used, and a sensitivity analysis of the dynamical behavior and the corresponding metabolical costs estimations with respect to parametrized neural excitations is performed. The leg motions are based on experiments in a gait analysis laboratory.

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A Model of Human Muscle Energy Expenditure

Cited by 304 publications

References 75 publications

Stance and swing phase costs in human walking

Stance and swing phase costs in human walking

Effectively Quantifying the Performance of Lower-Limb Exoskeletons Over a Range of Walking Conditions

Sensitivity Analysis of Human Leg Metabolical Costs

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