Abstract
Motion capture laboratories can measure multiple variables at high frame rates, but we can only measure the average metabolic rate of a stride using respiratory measurements. Biomechanical simulations with equations for calculating metabolic rate can estimate the time profile of metabolic rate within the stride cycle. A variety of methods and metabolic equations have been proposed, including metabolic time profile estimations based on joint parameters. It is unclear whether differences in estimations are due to differences in experimental data or due to methodological differences. This study aimed to compare two methods for estimating the time profile of metabolic rate, within a single dataset. Knowledge about the consistency of different methods could be useful for applications such as detecting which part of the gait cycle causes increased metabolic cost in patients. Here we compare estimations of metabolic rate time profiles using a musculoskeletal and a joint-space method. The musculoskeletal method was driven by kinematics and electromyography data and used muscle metabolic rate equations, whereas the joint-space method used metabolic rate equations based on joint parameters. Both estimations of changes in stride average metabolic rate correlated significantly with large changes in indirect calorimetry from walking on different grades showing that both methods accurately track changes. However, estimations of changes in stride average metabolic rate did not correlate significantly with more subtle changes in indirect calorimetry due to walking with different shoe inclinations, and both the musculoskeletal and joint-space time profile estimations did not correlate significantly with each other except in the most downward shoe inclination. Estimations of the relative cost of stance and swing matched well with previous simulations with similar methods and estimations from experimental perturbations. Rich experimental datasets could further advance time profile estimations. This knowledge could be useful to develop therapies and assistive devices that target the least metabolically economic part of the gait cycle.
Highlights
Would we be able to detect and understand the effects of gait impairments if we could capture only average metrics instead of time series? Motion capture laboratories can currently perform measurements of a person’s movements, forces, and muscle electromyography (EMG) at hundreds of frames per second, which allows us to analyze the time profiles of these variables within the stride cycle
Respiratory oxygen consumption measurements allow recording of the average metabolic cost of walking, but the slow rate of these measurements prevents assessing which part of the gait cycle has the highest metabolic cost
We compared estimations of the metabolic cost of walking using a method that is based on kinematic and electromyography recordings from participants in conjunction with muscle metabolic rate equations and a method based on joint kinematics and kinetics
Summary
Would we be able to detect and understand the effects of gait impairments if we could capture only average metrics instead of time series? Motion capture laboratories can currently perform measurements of a person’s movements (kinematics), forces (kinetics), and muscle electromyography (EMG) at hundreds of frames per second, which allows us to analyze the time profiles of these variables within the stride cycle. Energy from food is supplied to the human body in the form of chemical energy in the muscles (metabolic energy expenditure) This metabolic energy expenditure is one of the main determinants of the way we walk [1,2,3,4,5], and indirect calorimetry measurements are an important tool for understanding how increases in metabolic cost restrict the mobility of clinical populations [6,7,8]. We cannot directly measure which phases of the stride cycle have an increased metabolic cost in patient populations. Knowing such information would allow the design of assistive devices or therapies that target phases of gait with increased metabolic cost
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