Improvement of a Forward Dynamic Predictive Human Gait Model

2019 ◽  
Author(s):  
Jessica B. Thayer ◽  
Philip A. Voglewede
Keyword(s):  
Predictive Control ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Performance Criteria ◽  
Human Gait ◽  
Optimization Criteria ◽  
Optimization Framework ◽  
Normal Gait ◽  
The Central Nervous System ◽  
Improved Performance

Abstract Lack of understanding of human gait is detrimental to the development of gait related treatments and devices. This study improves a dynamic, predictive model of human gait which uses model predictive control (MPC) to replicate the control of the central nervous system (CNS). In this work, improved performance criteria, including metabolic cost and dynamic effort, are developed using an existing optimization framework to better mimic control of the CNS. Consistent with existing literature, incorporating dynamic effort and COM energy into the objective function improved gait simulations. This study also demonstrates COM energy and dynamic effort can both be used to predict metabolic energy consumption, which is likely the primary optimization criteria in normal gait generation.

scholarly journals Contributions of metabolic and temporal costs to human gait selection

2018 ◽  
Vol 15 (143) ◽  
pp. 20180197 ◽  
Author(s):  
Erik M. Summerside ◽  
Rodger Kram ◽  
Alaa A. Ahmed
Keyword(s):  
Movement Time ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Human Gait ◽  
Cost Of Transport ◽  
Relative Value ◽  
Weighted Combination

Humans naturally select several parameters within a gait that correspond with minimizing metabolic cost. Much less is understood about the role of metabolic cost in selecting between gaits. Here, we asked participants to decide between walking or running out and back to different gait specific markers. The distance of the walking marker was adjusted after each decision to identify relative distances where individuals switched gait preferences. We found that neither minimizing solely metabolic energy nor minimizing solely movement time could predict how the group decided between gaits. Of our twenty participants, six behaved in a way that tended towards minimizing metabolic energy, while eight favoured strategies that tended more towards minimizing movement time. The remaining six participants could not be explained by minimizing a single cost. We provide evidence that humans consider not just a single movement cost, but instead a weighted combination of these conflicting costs with their relative contributions varying across participants. Individuals who placed a higher relative value on time ran faster than individuals who placed a higher relative value on metabolic energy. Sensitivity to temporal costs also explained variability in an individual's preferred velocity as a function of increasing running distance. Interestingly, these differences in velocity both within and across participants were absent in walking, possibly due to a steeper metabolic cost of transport curve. We conclude that metabolic cost plays an essential, but not exclusive role in gait decisions.

Dynamic Simulation of Human Gait Using a Combination of Model Predictive and PID Control

2014 ◽  
Author(s):  
Jinming Sun ◽  
Philip A. Voglewede
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Pid Control ◽  
Muscle Activity ◽  
A Priori ◽  
Human Gait ◽  
Proportional Integral Derivative ◽  
Biomechanical Models ◽  
Long Period ◽  
The Central Nervous System

Human gait studies have not been applied frequently to the prediction of the performance of medical devices such as prostheses and orthoses. The reason is most biomechanics simulations require experimental data such as muscle activity or joint moment information a priori. In addition, biomechanical models are normally too complicated to be adjusted and these simulations normally take a long period of time to be performed which makes testing of various possibilities time consuming; therefore they are not suitable for prediction purpose. The objective of this research is to develop a control oriented human gait model that is able to predict the performance of prostheses and orthoses before they are experimentally tested. This model is composed of two parts. The first part is a seven link nine degree-of-freedom (DOF) plant to represent the forward dynamics of human gait. The second part is a control system which is a combination of Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) control. The purpose of this control system is to simulate the central nervous system (CNS). This model is sufficiently simple that it can be simulated and adjusted in a reasonable time, while still representing the essential principles of human gait.

scholarly journals Model Predictive Control for Modeling Human Gait Motions Assisted by Vicon Technology

2020 ◽  
Vol 53 (5) ◽  
pp. 589-600
Author(s):  
Vu Trieu Minh ◽  
Mart Tamre ◽  
Victor Musalimov ◽  
Pavel Kovalenko ◽  
Irina Rubinshtein ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Human Motion ◽  
Human Gait ◽  
Movement Trajectory ◽  
Tracking Errors ◽  
Human Movements ◽  
Study Results ◽  
The Central Nervous System ◽  
Human Muscles

Human muscles and the central nervous system (CNS) play the key role to control the human movements and activities. The human CNS determines each human motion following three steps: estimation of the movement trajectory; calculation of required energy for muscles; then perform the motion. In these three step tasks, the human CNS determines the first two steps and the human muscles conduct the third one. This paper efforts the use of model predictive control (MPC) algorithm to simulate the human CNS calculation in the case of gait motion. We first build up the human gait motion mathematical model with 5-link mechanism. This allows us to apply MPC to calculate the optimal torques at each joint and optimal trajectory for muscles. Outcomes of simulations simultaneously are compared with the real human movements captured by the Vicon motion capture technology which is the novelty of this study. Results show that tracking errors are not excessed 7%.

Dynamic Simulation of Human Gait Model With Predictive Capability

2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Jinming Sun ◽  
Shaoli Wu ◽  
Philip A. Voglewede
Keyword(s):  
Feedback Control ◽  
Predictive Control ◽  
Degrees Of Freedom ◽  
Human Subjects ◽  
Human Gait ◽  
Control Input ◽  
Plant Model ◽  
Control Approach ◽  
The Central Nervous System ◽  
Using Data

In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

scholarly journals Reduced Achilles Tendon Stiffness Disrupts Calf Muscle Neuromechanics in Elderly Gait

Gerontology ◽  
2021 ◽  
pp. 1-11
Author(s):  
Rebecca L. Krupenevich ◽  
Owen N. Beck ◽  
Gregory S. Sawicki ◽  
Jason R. Franz
Keyword(s):  
Older Adults ◽  
Achilles Tendon ◽  
Metabolic Cost ◽  
Calf Muscle ◽  
Metabolic Energy ◽  
Joint Work ◽  
Tendon Stiffness ◽  
Age Related ◽  
Ankle Muscle ◽  
Metabolic Energy Expenditure

Older adults walk slower and with a higher metabolic energy expenditure than younger adults. In this review, we explore the hypothesis that age-related declines in Achilles tendon stiffness increase the metabolic cost of walking due to less economical calf muscle contractions and increased proximal joint work. This viewpoint may motivate interventions to restore ankle muscle-tendon stiffness, improve walking mechanics, and reduce metabolic cost in older adults.

scholarly journals Reducing the metabolic energy of walking and running using an unpowered hip exoskeleton

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Tiancheng Zhou ◽  
Caihua Xiong ◽  
Juanjuan Zhang ◽  
Di Hu ◽  
Wenbin Chen ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Design Method ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Spring Stiffness ◽  
Spatiotemporal Parameters ◽  
The Common ◽  
Hip Flexion ◽  
Optimal Stiffness ◽  
Insight Into

Abstract Background Walking and running are the most common means of locomotion in human daily life. People have made advances in developing separate exoskeletons to reduce the metabolic rate of walking or running. However, the combined requirements of overcoming the fundamental biomechanical differences between the two gaits and minimizing the metabolic penalty of the exoskeleton mass make it challenging to develop an exoskeleton that can reduce the metabolic energy during both gaits. Here we show that the metabolic energy of both walking and running can be reduced by regulating the metabolic energy of hip flexion during the common energy consumption period of the two gaits using an unpowered hip exoskeleton. Methods We analyzed the metabolic rates, muscle activities and spatiotemporal parameters of 9 healthy subjects (mean ± s.t.d; 24.9 ± 3.7 years, 66.9 ± 8.7 kg, 1.76 ± 0.05 m) walking on a treadmill at a speed of 1.5 m s−1 and running at a speed of 2.5 m s−1 with different spring stiffnesses. After obtaining the optimal spring stiffness, we recruited the participants to walk and run with the assistance from a spring with optimal stiffness at different speeds to demonstrate the generality of the proposed approach. Results We found that the common optimal exoskeleton spring stiffness for walking and running was 83 Nm Rad−1, corresponding to 7.2% ± 1.2% (mean ± s.e.m, paired t-test p < 0.01) and 6.8% ± 1.0% (p < 0.01) metabolic reductions compared to walking and running without exoskeleton. The metabolic energy within the tested speed range can be reduced with the assistance except for low-speed walking (1.0 m s−1). Participants showed different changes in muscle activities with the assistance of the proposed exoskeleton. Conclusions This paper first demonstrates that the metabolic cost of walking and running can be reduced using an unpowered hip exoskeleton to regulate the metabolic energy of hip flexion. The design method based on analyzing the common energy consumption characteristics between gaits may inspire future exoskeletons that assist multiple gaits. The results of different changes in muscle activities provide new insight into human response to the same assistive principle for different gaits (walking and running).

scholarly journals Using a simple rope-pulley system that mechanically couples the arms, legs, and treadmill reduces the metabolic cost of walking

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Daisey Vega ◽  
Christopher J. Arellano
Keyword(s):  
Metabolic Cost ◽  
Metabolic Energy ◽  
Metabolic Effects ◽  
Whole Body ◽  
Walking Ability ◽  
Arm Swing ◽  
Pulley System ◽  
Young Subjects ◽  
Walking Recovery ◽  
Set Up

Abstract Background Emphasizing the active use of the arms and coordinating them with the stepping motion of the legs may promote walking recovery in patients with impaired lower limb function. Yet, most approaches use seated devices to allow coupled arm and leg movements. To provide an option during treadmill walking, we designed a rope-pulley system that physically links the arms and legs. This arm-leg pulley system was grounded to the floor and made of commercially available slotted square tubing, solid strut channels, and low-friction pulleys that allowed us to use a rope to connect the subject’s wrist to the ipsilateral foot. This set-up was based on our idea that during walking the arm could generate an assistive force during arm swing retraction and, therefore, aid in leg swing. Methods To test this idea, we compared the mechanical, muscular, and metabolic effects between normal walking and walking with the arm-leg pulley system. We measured rope and ground reaction forces, electromyographic signals of key arm and leg muscles, and rates of metabolic energy consumption while healthy, young subjects walked at 1.25 m/s on a dual-belt instrumented treadmill (n = 8). Results With our arm-leg pulley system, we found that an assistive force could be generated, reaching peak values of 7% body weight on average. Contrary to our expectation, the force mainly coincided with the propulsive phase of walking and not leg swing. Our findings suggest that subjects actively used their arms to harness the energy from the moving treadmill belt, which helped to propel the whole body via the arm-leg rope linkage. This effectively decreased the muscular and mechanical demands placed on the legs, reducing the propulsive impulse by 43% (p < 0.001), which led to a 17% net reduction in the metabolic power required for walking (p = 0.001). Conclusions These findings provide the biomechanical and energetic basis for how we might reimagine the use of the arms in gait rehabilitation, opening the opportunity to explore if such a method could help patients regain their walking ability. Trial registration: Study registered on 09/29/2018 in ClinicalTrials.gov (ID—NCT03689647).

Improvement of a Forward Dynamic MPC Based Human Gait Model

2016 ◽  
Author(s):  
Shaoli Wu ◽  
Philip A. Voglewede
Keyword(s):  
Predictive Control ◽  
Ground Reaction Force ◽  
Reaction Force ◽  
Human Gait ◽  
Mechanical Parameters ◽  
Anthropometric Parameters ◽  
Robust Controller ◽  
Central Tenet ◽  
Human Joints ◽  
Improved Model

This paper develops an improvement to an existing forward dynamic human gait model. A human gait model was developed previously to assist virtual testing prostheses and orthoses. The model consists of a plant model and a controller model. The central tenet to the model is the model predictive control (MPC) algorithm, which is a highly robust controller. In the previous model, however, there are several drawbacks. First, the anthropometric and mechanical parameters in the parts of the model are specific to one person. Second, the simulation result of ground reaction force (GRF) is not realistic. In this paper, the anthropometric parameters are calculated based on commonly used models that approximate an average person’s size. As for the mechanical parameters, the spring and damper coefficients in the human joints and ground reaction force (GRF) system are estimated by using the parameter estimation module in MATLAB based on the experimental subject data. The paper concludes with a simulation results between the new improved model and the previous developed model.

scholarly journals Walking in simulated reduced gravity: mechanical energy fluctuations and exchange

1999 ◽  
Vol 86 (1) ◽  
pp. 383-390 ◽  
Author(s):  
Timothy M. Griffin ◽  
Neil A. Tolani ◽  
Rodger Kram
Keyword(s):  
Kinetic Energy ◽  
Potential Energy ◽  
Gravitational Potential ◽  
Inverted Pendulum ◽  
Mechanical Energy ◽  
Center Of Mass ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Gravitational Potential Energy ◽  
Reduced Gravity

Walking humans conserve mechanical and, presumably, metabolic energy with an inverted pendulum-like exchange of gravitational potential energy and horizontal kinetic energy. Walking in simulated reduced gravity involves a relatively high metabolic cost, suggesting that the inverted-pendulum mechanism is disrupted because of a mismatch of potential and kinetic energy. We tested this hypothesis by measuring the fluctuations and exchange of mechanical energy of the center of mass at different combinations of velocity and simulated reduced gravity. Subjects walked with smaller fluctuations in horizontal velocity in lower gravity, such that the ratio of horizontal kinetic to gravitational potential energy fluctuations remained constant over a fourfold change in gravity. The amount of exchange, or percent recovery, at 1.00 m/s was not significantly different at 1.00, 0.75, and 0.50 G (average 64.4%), although it decreased to 48% at 0.25 G. As a result, the amount of work performed on the center of mass does not explain the relatively high metabolic cost of walking in simulated reduced gravity.

Sign in / Sign up

Export Citation Format

Share Document