Modular footwear that partially offsets downhill or uphill grades minimizes the metabolic cost of human walking

Antonellis, Prokopios; Frederick, Cory; Gonabadi, Arash Mohammadzadeh; Malcolm, Philippe

doi:10.1098/rsos.191527

Cited by 4 publications

(11 citation statements)

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“…We conducted analyses on data from a previous experiment that involved walking with different types of modular shoes and at different grades during multiple five-minute conditions [ 36 ] ( Fig 2A ). The metabolic rate was recorded using indirect calorimetry (K5, Cosmed, Rome, Italy).…”

Section: Methodsmentioning

confidence: 99%

“…The shoe inclination conditions allow us to evaluate whether metabolic time profile estimations are sensitive enough to measure more subtle changes in metabolic cost for the stance phase due to the altered muscle configurations. Additional details on the experimental procedure that were used in the present study can be found in the study by Antonellis et al, [ 36 ].…”

Section: Methodsmentioning

confidence: 99%

“… (a) Conditions. We analyzed previously collected data from walking with level shoes at downhill, level and uphill treadmill grades (-6, 0 and +6°), and walking on a level treadmill with shoes with different outsole inclinations (from -7 to +7°) [ 36 ]. The red lines indicate the treadmill grades and shoe inclinations.…”

Section: Methodsmentioning

confidence: 99%

“…In one participant for whom the normalized EMG signals of the soleus and gastrocnemius medialis during the uphill walking trial exceeded the MVC value, we re-normalized those EMGs to the maximum value of this trial [ 19 ]. We filtered the ground reaction forces with a low pass Butterworth filter with a 6 Hz cut-off [ 36 , 45 ]. Motion capture data were processed using OpenSim (version 4.0, SimTK, Santa Clara County, California; [ 46 , 47 ]) with the model from Rajagopal et al, [ 48 ] ( Fig 3A ).…”

Section: Methodsmentioning

confidence: 99%

“…We selected the Umberger metabolic cost equations and the joint-space method because both methods have been introduced specifically for estimating the time profile of metabolic rate in their respective studies [ 20 , 23 ]. Since our goal was not to predict future experimental conditions but instead to use experimental data to estimate a physiological time series (i.e., the time profile of metabolic cost), we used the available EMG data from a recent experiment [ 36 ] to drive the musculoskeletal method. This offers the advantage of capturing the neural drive of the participants more realistically than musculoskeletal simulations that estimate the muscle activation through an optimization [ 37 ].…”

Section: Introductionmentioning

confidence: 99%

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Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles

2020

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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.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles

2020

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A System for Simple Robotic Walking Assistance With Linear Impulses at the Center of Mass

Gonabadi

Antonellis

Malcolm

2020

IEEE Trans. Neural Syst. Rehabil. Eng.

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Walking can be simplified as an inverted pendulum motion where both legs generate linear impulses to redirect the center of mass (COM) into every step. In this work, we describe a system to assist walking in a simpler way than exoskeletons by providing linear impulses directly at the COM instead of providing torques at the joints. We developed a novel waist end-effector and highlevel controller for an existing cable-robot. The controller allows for the application of cyclic horizontal force profiles with desired magnitudes, timings, and durations based on detection of the step timing. By selecting a lightweight rubber series elastic element with optimal stiffness and carefully tuning the gains of the closed-loop proportionalintegral-derivative (PID) controller in a number of singlesubject experiments, we were able to reduce the within-step root mean square error between desired and actual forces up to 1.21% of body weight. This level of error is similar or lower compared to the performance of other robotic tethers designed to provide variable or constant forces at the COM. The system can produce force profiles with peaks of up to 15 ± 2% of body weight within a root mean square error (RMSE) of 2.5% body weight. This system could be used to assist patient populations that require levels of assistance that are greater than current exoskeletons and in a way that does not make the user rely on vertical support. Index Terms-Aiding force, cable robotics, center of mass (COM), rehabilitation, walking. I. INTRODUCTION T HE field of wearable robots for assisting walking has witnessed an evolution from advanced, sophisticated devices that assist multiple joints [1]-[3] towards a greater focus on single-joint exoskeletons [4]-[9] and elegant, simple Manuscript

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Patient-Preferred Prosthetic Ankle-Foot Alignment for Ramps and Level-Ground Walking

Shepherd

Simon

Zisk

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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Patient preference of lower limb prosthesis behavior informally guides clinical decision making, and may become increasingly important for tuning new robotic prostheses. However, the processes for quantifying preference are still being developed, and the strengths and weaknesses of preference are not adequately understood. The present study sought to characterize the reliability (consistency) of patient preference of alignment during level-ground walking, and determine the patient-preferred ankle angle for ascent and descent of a 10° ramp, with implications for the design and control of robotic prostheses. Seven subjects with transtibial amputation walked over level ground, and ascended and descended a 10° ramp on a semi-active prosthetic ankle capable of unweighted repositioning in dorsiflexion and plantarflexion. Preferred ankle angle was measured with an adaptive forced-choice psychophysics paradigm, in which subjects walked on a randomized static ankle angle and reported whether they would prefer the ankle to be dorsiflexed or plantarflexed. Subjects had reliable preferences for alignment during level-ground walking, with deviations of 1.5° from preference resulting in an 84% response rate preferring changes toward the preference. Relative to level walking, subjects preferred 7.8° (SD: 4.8°) of dorsiflexion during ramp ascent, and 5.3° (SD: 3.8°) plantarflexion during ramp descent. As the ankle angle better matched the ramp angle, socket pressures and tibial progression (shank pitch) both more closely mirrored those during level walking. These findings provide baseline behaviors for prosthetic ankles capable of adapting to slopes based on patient preference, and provide strong evidence that people with transtibial amputation can finely perceive ankle alignment.

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Modular footwear that partially offsets downhill or uphill grades minimizes the metabolic cost of human walking

Cited by 4 publications

References 64 publications

Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles

Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles

A System for Simple Robotic Walking Assistance With Linear Impulses at the Center of Mass

Patient-Preferred Prosthetic Ankle-Foot Alignment for Ramps and Level-Ground Walking

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