Modeling and Optimal Control of an Energy-Storing Prosthetic Knee

2012 ◽  
Vol 134 (5) ◽  
Author(s):  
Antonie J. van den Bogert ◽  
Sergey Samorezov ◽  
Brian L. Davis ◽  
William A. Smith
Keyword(s):  
Optimal Control ◽  
Energy Cost ◽  
Human Performance ◽  
Human Subjects ◽  
Metabolic Energy ◽  
Hydraulic Actuator ◽  
Joint Power ◽  
Storage Mechanism ◽  
Prosthetic Knee ◽  
Normal Knee

Advanced prosthetic knees for transfemoral amputees are currently based on controlled damper mechanisms. Such devices require little energy to operate, but can only produce negative or zero joint power, while normal knee joint function requires alternative phases of positive and negative work. The inability to generate positive work may limit the user’s functional capabilities, may cause undesirable adaptive behavior, and may contribute to excessive metabolic energy cost for locomotion. In order to overcome these problems, we present a novel concept for an energy-storing prosthetic knee, consisting of a rotary hydraulic actuator, two valves, and a spring-loaded hydraulic accumulator. In this paper, performance of the proposed device will be assessed by computational modeling and by simulation of functional activities. A computational model of the hydraulic system was developed, with methods to obtain optimal valve control patterns for any given activity. The objective function for optimal control was based on tracking of joint angles, tracking of joint moments, and the energy cost of operating the valves. Optimal control solutions were obtained, based on data collected from three subjects during walking, running, and a sit-stand-sit cycle. Optimal control simulations showed that the proposed device allows near-normal knee function during all three activities, provided that the accumulator stiffness was tuned to each activity. When the energy storage mechanism was turned off in the simulations, the system functioned as a controlled damper device and optimal control results were similar to literature data on human performance with such devices. When the accumulator stiffness was tuned to walking, simulated performance for the other activities was sub-optimal but still better than with a controlled damper. We conclude that the energy-storing knee concept is valid for the three activities studied, that modeling and optimal control can assist the design process, and that further studies using human subjects are justified.

scholarly journals Predictive musculoskeletal simulation using optimal control: effects of added limb mass on energy cost and kinematics of walking and running

2012 ◽  
Vol 226 (2) ◽  
pp. 123-133 ◽  
Author(s):  
Antonie J van den Bogert ◽  
Maarten Hupperets ◽  
Heiko Schlarb ◽  
Berthold Krabbe
Keyword(s):  
Optimal Control ◽  
Design Optimization ◽  
Energy Cost ◽  
Human Performance ◽  
Neuromuscular Control ◽  
Added Mass ◽  
Musculoskeletal Model ◽  
The Body ◽  
Design Parameters ◽  
Underlying Assumption

When designing sports equipment, it is often desirable to predict how certain design parameters will affect human performance. In many instances, this requires a consideration of human musculoskeletal mechanics and adaptive neuromuscular control. Current computational methods do not represent these mechanisms, and design optimization typically requires several iterations of prototyping and human testing. This paper introduces a computational method based on musculoskeletal modeling and optimal control, which has the capability to predict the effect of mechanical equipment properties on human performance. The underlying assumption is that users will adapt their neuromuscular control according to an optimality principle, which balances task performance with a minimization of muscular effort. The method was applied to the prediction of metabolic cost and limb kinematics while running and walking with weights attached to the body. A two-dimensional musculoskeletal model was used, with nine kinematic degrees of freedom and 16 muscles. The optimal control problem was solved for two walking speeds and two running speeds, and at each speed, with 200 g and 400 g masses placed at the thigh, knee, shank and foot. The model predicted an increase in energy expenditure that was proportional to the added mass and the effect was largest for a mass placed on the foot. Specifically, the model predicted an energy cost increase of 0.74% for each 100 g mass added to the foot during running at 3.60 m/s. The model also predicted that stride length would increase by several millimetres in the same condition, relative to the model without added mass. These predictions were consistent with previously published human studies. Peak force and activation remained the same in most muscles, but increased by 26% in the hamstrings and by 17% in the rectus femoris for running at 4.27 m/s with 400 g added mass at the foot, suggesting muscle-specific training effects. This work demonstrated that a musculoskeletal model with optimal control can predict the effect of mechanical devices on human performance, and could become a useful tool for design optimization in sports engineering. The theoretical background of predictive simulation also helps explain why human athletes have specific responses when exercising in an altered mechanical environment.

The limits of human performance

2008 ◽  
Vol 44 ◽  
pp. 11-26 ◽  
Author(s):  
Ralph Beneke ◽  
Dieter Böning
Keyword(s):  
Human Performance ◽  
Safety Margin ◽  
Afferent Input ◽  
Metabolic Energy ◽  
Human Organism ◽  
Mechanical Resistance ◽  
As Doping ◽  
Gene And Protein Expression ◽  
Underlying Mechanisms ◽  
Biochemical Research

Human performance, defined by mechanical resistance and distance per time, includes human, task and environmental factors, all interrelated. It requires metabolic energy provided by anaerobic and aerobic metabolic energy sources. These sources have specific limitations in the capacity and rate to provide re-phosphorylation energy, which determines individual ratios of aerobic and anaerobic metabolic power and their sustainability. In healthy athletes, limits to provide and utilize metabolic energy are multifactorial, carefully matched and include a safety margin imposed in order to protect the integrity of the human organism under maximal effort. Perception of afferent input associated with effort leads to conscious or unconscious decisions to modulate or terminate performance; however, the underlying mechanisms of cerebral control are not fully understood. The idea to move borders of performance with the help of biochemicals is two millennia old. Biochemical findings resulted in highly effective substances widely used to increase performance in daily life, during preparation for sport events and during competition, but many of them must be considered as doping and therefore illegal. Supplements and food have ergogenic potential; however, numerous concepts are controversially discussed with respect to legality and particularly evidence in terms of usefulness and risks. The effect of evidence-based nutritional strategies on adaptations in terms of gene and protein expression that occur in skeletal muscle during and after exercise training sessions is widely unknown. Biochemical research is essential for better understanding of the basic mechanisms causing fatigue and the regulation of the dynamic adaptation to physical and mental training.

Contraction duration affects metabolic energy cost and fatigue in skeletal muscle

1998 ◽  
Vol 274 (3) ◽  
pp. E397-E402 ◽  
Author(s):  
Michael C. Hogan ◽  
Erica Ingham ◽  
S. Sadi Kurdak
Keyword(s):  
Skeletal Muscle ◽  
Short Duration ◽  
Energy Cost ◽  
Lactate Concentration ◽  
Metabolic Energy ◽  
Muscle Lactate ◽  
Contracting Muscle ◽  
Contraction Duration ◽  
Long Duration ◽  
The Difference

It has been suggested that during a skeletal muscle contraction the metabolic energy cost at the onset may be greater than the energy cost related to holding steady-state force. The purpose of the present study was to investigate the effect of contraction duration on the metabolic energy cost and fatigue process in fully perfused contracting muscle in situ. Canine gastrocnemius muscle ( n = 6) was isolated, and two contractile periods (3 min of isometric, tetanic contractions with 45-min rest between) were conducted by each muscle in a balanced order design. The two contractile periods had stimulation patterns that resulted in a 1:3 contraction-to-rest ratio, with the difference in the two contractile periods being in the duration of each contraction: short duration 0.25-s stimulation/0.75-s rest vs. long duration 1-s stimulation/3-s rest. These stimulation patterns resulted in the same total time of stimulation, number of stimulation pulses, and total time in contraction for each 3-min period. Muscle O2 uptake, the fall in developed force (fatigue), the O2 cost of developed force, and the estimated total energy cost (ATP utilization) of developed force were significantly greater ( P < 0.05) with contractions of short duration. Lactate efflux from the working muscle and muscle lactate concentration were significantly greater with contractions of short duration, such that the calculated energy derived from glycolysis was three times greater in this condition. These results demonstrate that contraction duration can significantly affect both the aerobic and anaerobic metabolic energy cost and fatigue in contracting muscle. In addition, it is likely that the greater rate of fatigue with more rapid contractions was a result of elevated glycolytic production of lactic acid.

Exploring the Design Space Using a Surrogate Model Approach With Digital Human Modeling Simulations

2018 ◽  
Author(s):  
Salman Ahmed ◽  
Mihir Sunil Gawand ◽  
Lukman Irshad ◽  
H. Onan Demirel
Keyword(s):  
Human Factors ◽  
Surrogate Model ◽  
Human Performance ◽  
Design Method ◽  
Human Subjects ◽  
Design Stage ◽  
Digital Human Modeling ◽  
Design Variables ◽  
Human Modeling ◽  
Digital Human

Computational human factors tools are often not fully-integrated during the early phases of product design. Often, conventional ergonomic practices require physical prototypes and human subjects which are costly in terms of finances and time. Ergonomics evaluations executed on physical prototypes has the limitations of increasing the overall rework as more iterations are required to incorporate design changes related to human factors that are found later in the design stage, which affects the overall cost of product development. This paper proposes a design methodology based on Digital Human Modeling (DHM) approach to inform designers about the ergonomics adequacies of products during early stages of design process. This proactive ergonomics approach has the potential to allow designers to identify significant design variables that affect the human performance before full-scale prototypes are built. The design method utilizes a surrogate model that represents human product interaction. Optimizing the surrogate model provides design concepts to optimize human performance. The efficacy of the proposed design method is demonstrated by a cockpit design study.

scholarly journals Metabolic energy cost of workers in agriculture, construction, manufacturing, tourism, and transportation industries

2019 ◽  
Vol 57 (3) ◽  
pp. 283-305 ◽  
Author(s):  
Konstantina P. POULIANITI ◽  
George HAVENITH ◽  
Andreas D. FLOURIS
Keyword(s):  
Energy Cost ◽  
Metabolic Energy

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 Muscle Metabolic Energy Costs While Modifying Propulsive Force Generation During Walking

2020 ◽  
Author(s):  
Richard E. Pimentel ◽  
Noah L. Pieper ◽  
William H. Clark ◽  
Jason R. Franz
Keyword(s):  
Young Adults ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Energy Costs ◽  
Joint Power ◽  
Lower Limb Muscles ◽  
Age Related ◽  
Musculoskeletal Models ◽  
Metabolic Costs ◽  
Related Increase

AbstractWe pose that an age-related increase in the metabolic cost of walking arises in part from a redistribution of joint power where muscles spanning the hip compensate for insufficient ankle push-off and smaller peak propulsive forces (FP). Young adults elicit a similar redistribution when walking with smaller FP via biofeedback. We used targeted FP biofeedback and musculoskeletal models to estimate the metabolic costs of operating lower limb muscles in young adults walking across a range of FP. Our simulations support the theory of distal-to-proximal redistribution of joint power as a determinant of increased metabolic cost in older adults during walking.

scholarly journals Energetic consequences of using a prosthesis with adaptive ankle motion during slope walking in persons with a transtibial amputation

2013 ◽  
Vol 38 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Benjamin J Darter ◽  
Jason M Wilken
Keyword(s):  
Mechanical Properties ◽  
Energy Expenditure ◽  
Energy Cost ◽  
Metabolic Energy ◽  
Prosthetic Design ◽  
Transtibial Amputation ◽  
Ankle Motion ◽  
Technological Advances ◽  
Walking Difficulty ◽  
Metabolic Energy Expenditure

Background:Technological advances in prosthetic design include the use of microprocessors that adapt device performance based on user motion. The Proprio ankle unit prepositions the foot to adjust for walking on slopes and increases foot clearance during swing to minimize gait deviations.Study design:Comparative analysis.Objectives:To investigate the effect of a prosthesis with adaptive ankle motion on physiological gait performance during slope walking.Methods:Six persons with a unilateral transtibial amputation completed treadmill walking tests at three slopes (−5°, 0°, and 5°). The participants were tested wearing a customary device, active Proprio (Pon), and an identical inactivated Proprio (Poff).Results:Metabolic energy expenditure, energy cost for walking, and rating of walking difficulty were not statistically different between the Pon and Poff for all tested slopes. However, for slope descent, energy expenditure and energy cost for walking improved significantly by an average of 10%–14% for both the Pon and Poff compared to the customary limb. Rating of walking difficulty also showed an improvement with slope descent for both the Pon and Poff compared to the customary device. An improvement with slope ascent was found for Pon compared to the customary limb only.Conclusions:Adaptive ankle motion provided no meaningful physiological benefit during slope walking. The Proprio was, however, less demanding than the customary device for slope descent. Differences in the mechanical properties of the prosthetic feet likely contributed to the changes.Clinical relevanceWhile the adaptive ankle motion did not affect metabolic energy expenditure or energy cost for walking, the results suggest close attention should be paid to the mechanical properties of the foot component. Assessment of gait on nonlevel surfaces is recommended to better understand the implications of different prosthetic design features.

Sign in / Sign up

Export Citation Format

Share Document