Author ORCID Identifier
ORCiD: 0000-0002-4535-0325
Advisor Information
& Philippe Malcolm
Location
Criss Library, University of Nebraska at Omaha
Presentation Type
Poster
Start Date
1-3-2019 10:45 AM
End Date
1-3-2019 12:00 PM
Abstract
Indirect calorimetry provides the average cost of a stride cycle and prevents from identifying which part of the gait cycle causes increased metabolic cost in patients, however, recent simulation methods allow estimating the time profile of metabolic cost within the stride cycle. In this study, we compare the estimations of the time profile of the metabolic cost of two simulation methods for level and uphill walking. We used kinematic, kinetic and electromyography data from level and uphill walking (one participant) to estimate the time profiles of metabolic cost using the muscle-level metabolic model of Umberger using electromyography and kinematic data into a musculoskeletal simulation. We estimated the time profile of metabolic cost based on the joint moments and joint angular velocities (Roberts et al.). Both methods show a phase of high metabolic cost in the first 10% of the gait cycle. The Umberger method reveals another phase with a high metabolic cost during the second half of stance whereas the Roberts et al. method shows a phase with high metabolic cost in early swing phase. Both methods estimated an increase in metabolic cost with uphill walking, in line with indirect calorimetry measurements. There is no experimental measurement of the time profile of metabolic cost that allows identifying which of the two estimation methods is more accurate. The fact that both methods show moderate similarity and can detect the increase in metabolic cost during uphill walking suggest that they could be useful as an input for optimization methods of assistive devices.
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Estimating variations in metabolic cost within the stride cycle during level and uphill walking
Criss Library, University of Nebraska at Omaha
Indirect calorimetry provides the average cost of a stride cycle and prevents from identifying which part of the gait cycle causes increased metabolic cost in patients, however, recent simulation methods allow estimating the time profile of metabolic cost within the stride cycle. In this study, we compare the estimations of the time profile of the metabolic cost of two simulation methods for level and uphill walking. We used kinematic, kinetic and electromyography data from level and uphill walking (one participant) to estimate the time profiles of metabolic cost using the muscle-level metabolic model of Umberger using electromyography and kinematic data into a musculoskeletal simulation. We estimated the time profile of metabolic cost based on the joint moments and joint angular velocities (Roberts et al.). Both methods show a phase of high metabolic cost in the first 10% of the gait cycle. The Umberger method reveals another phase with a high metabolic cost during the second half of stance whereas the Roberts et al. method shows a phase with high metabolic cost in early swing phase. Both methods estimated an increase in metabolic cost with uphill walking, in line with indirect calorimetry measurements. There is no experimental measurement of the time profile of metabolic cost that allows identifying which of the two estimation methods is more accurate. The fact that both methods show moderate similarity and can detect the increase in metabolic cost during uphill walking suggest that they could be useful as an input for optimization methods of assistive devices.