Dynamic Optimization of Human Running With Analytical Gradients

2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Hyun-Joon Chung ◽  
Jasbir S. Arora ◽  
Karim Abdel-Malek ◽  
Yujiang Xiang
Keyword(s):  
Human Subjects ◽  
Reaction Force ◽  
Performance Measure ◽  
Joint Torque ◽  
Upper Body ◽  
Human Model ◽  
Dynamic Prediction ◽  
Foot Strike ◽  
Analytical Gradients ◽  
Human Running

The optimization-based dynamic prediction of 3D human running motion is studied in this paper. A predictive dynamics method is used to formulate the running problem, and normal running is formulated as a symmetric and cyclic motion. Recursive Lagrangian dynamics with analytical gradients for all the constraints and objective function are incorporated in the optimization process. The dynamic effort is used as the performance measure, and the impulse at the foot strike is also included in the performance measure. The joint angle profiles and joint torque profiles are calculated for the full-body human model, and the ground reaction force (GRF) is determined. Several cause-and-effect cases are studied, and the formulation for upper-body yawing motion is proposed and simulated. Simulation results from this methodology show good correlation with experimental data obtained from human subjects and the existing literature.

Optimization-based dynamic 3D human running prediction: effects of foot location and orientation

Robotica ◽  
2014 ◽  
Vol 33 (2) ◽  
pp. 413-435 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Human Subjects ◽  
Reaction Force ◽  
Three Dimensional ◽  
Performance Measure ◽  
Joint Torque ◽  
Upper Body ◽  
Human Model ◽  
Curved Paths ◽  
Dynamics Method ◽  
Human Running

SUMMARYThis paper presents optimization-based dynamic three-dimensional (3D) human running prediction. A predictive dynamics method is used to formulate the running problem, and normal running is formulated as a symmetric and cyclic motion. In addition, a slow jog along curved paths has been formulated. It is a non-symmetric running motion, so a stride formulation has been used. The dynamic effort and impulse are used as the performance measure, and the upper body yawing moment is also included in the performance measure. The joint angle profiles and joint torque profiles are calculated for the full-body human model, and the ground reaction force is determined. The effects of foot location and orientation on the running motion prediction are simulated and studied. Simulation results from this methodology show good correlation with experimental data obtained from human subjects.

Effect of Foot Location on Human Running Prediction

2014 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Rajan Bhatt ◽  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Degrees Of Freedom ◽  
Reaction Force ◽  
Performance Measure ◽  
Joint Torque ◽  
Upper Body ◽  
Human Model ◽  
Digital Human Model ◽  
Digital Human ◽  
Dynamics Method ◽  
Human Running

Human running is simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). A predictive dynamics method is used to formulate the running problem, and normal running is formulated as a symmetric and cyclic motion. The dynamic effort and impulse are used as the performance measure, and the upper body yawing moment is also included in the performance measure. The joint angle profiles and joint torque profiles are calculated for the full-body human model, and the ground reaction force is determined. The effect of foot location on the running motion prediction are simulated and studied.

scholarly journals Humanoid standing control: learning from human demonstration

2002 ◽  
Vol 12 (1) ◽  
pp. 16-22 ◽  
Author(s):  
Andreas Hofmann ◽  
Marko Popovic ◽  
Hugh Herr
Keyword(s):  
Ground Reaction Force ◽  
Center Of Pressure ◽  
Human Subjects ◽  
Reaction Force ◽  
Morphological Data ◽  
Human Model ◽  
Joint Torques ◽  
Double Support ◽  
High Level ◽  
Force Data

A three-dimensional numerical model of human standing is presented that reproduces the dynamics of simple swaying motions while in double-support. The human model is structurally realistic, having both trunk and two legs with segment lengths and mass distributions defined using human morphological data from the literature. In this investigation, model stability in standing is achieved through the application of a high-level reduced-order control system where stabilizing forces are applied to the model's trunk by virtual spring- damper elements. To achieve biologically realistic model dynamics, torso position and ground reaction force data measured on human subjects are used as demonstration data in a supervised learning strategy. Using Powell's method, the error between simulation data and measured human data is minimized by varying the virtual high-level force field. Once optimized, the model is shown to track torso position and ground reaction force data from human demonstrations. With only these limited demonstration data, the humanoid model sways in a biologically realistic manner. The model also reproduces the center-of-pressure trajectory beneath the foot, even though no error term for this is included in the optimization algorithm. This indicates that the error terms used (the ones for torso position and ground reaction force) are sufficient to compute the correct joint torques such that independent metrics, like center-of-pressure trajectory, are correct.

scholarly journals Evaluation of 3-Axial Knee Joint Torques Produced by Compression Sports Tights in Running Motion

Proceedings ◽  
2020 ◽  
Vol 49 (1) ◽  
pp. 69
Author(s):  
Taisei Mori ◽  
Yohei Ogino ◽  
Akihiro Matsuda ◽  
Yumiko Funabashi
Keyword(s):  
Computer Graphics ◽  
Knee Joint ◽  
Numerical Simulations ◽  
Human Subjects ◽  
Joint Torque ◽  
Human Model ◽  
Joint Torques ◽  
3 Dimensional ◽  
Flexion Extension ◽  
Fabric Materials

In this paper, 3-axial knee joint torques given by compression sports tights were performed by numerical simulations using 3-dimensional computer graphics of a human model. Running motions of the human model were represented as the 3-dimensional computer graphics, and the running motions were determined by the motion capturing system of human subjects. Strain distribution on the surface of the 3-dimentional computer graphics of the human model was applied to the boundary conditions of the numerical simulations. An anisotropic hyperelastic model considering stress softening of fabric materials was implemented to reproduce the mechanical characteristics of the compression sports tights. Based on the strain-time relationships, knee joint torques in 3-dimentional coordinates given by the compression sports tights were calculated. As a result, the three types of knee joint torque generated by the compression sports tights in running motions were calculated. From the calculated results, the maximum value of flexion/extension, varus/valgus, and internal/external knee joint torques were given as 2.52, 0.59, and 0.31 Nm, respectively. The effect of compression sports tights on the knee joint was investigated.

A NEW STABILITY CRITERION FOR HUMAN SEATED TASKS WITH GIVEN POSTURES

2012 ◽  
Vol 09 (03) ◽  
pp. 1250015 ◽  
Author(s):  
BRADLEY HOWARD ◽  
JINGZHOU YANG
Keyword(s):  
Stability Analysis ◽  
Stability Criterion ◽  
Center Of Mass ◽  
Reaction Force ◽  
Joint Torque ◽  
Human Model ◽  
Digital Human Model ◽  
Applied Forces ◽  
The Stability ◽  
Digital Human

In digital human modeling (DHM), the analysis of postural stability has five main goals: to determine if a posture is stable or unstable through an explicit criterion; to quantify the level of stability or provide a margin of stability that accounts for the height of the center of mass (COM) above the support plane(s); to be valid in the presence of externally applied forces and moments; be able to assess stability when multiple noncoplanar support planes exist, as is the case with seated postures; and to give insight into the support reaction force (SRF) distribution. To date, there is not a method for analyzing stability that can effectively meet each goal. This paper presents a new stability criterion and stability analysis that accomplishes each intended goal. The stability analysis is derived from the calculation of joint torque using the recursive Lagrangian dynamic formulation. A 56-degree-of-freedom (DOF) articulated digital human model is used to model seated postures to demonstrate the proposed stability criterion. Different given postures with different external load cases are presented.

OPTIMIZATION-BASED DYNAMIC PREDICTION OF HUMAN POSTURAL RESPONSE UNDER TILTING OF BASE OF SUPPORT

2012 ◽  
Vol 09 (02) ◽  
pp. 1250011
Author(s):  
DAVOOD NADERI ◽  
MOHSEN SADEGHI-MEHR ◽  
BEHNAM MIRIPOUR FARD
Keyword(s):  
Optimization Problem ◽  
Sagittal Plane ◽  
Base Plate ◽  
Performance Measure ◽  
Joint Torque ◽  
Skeletal Structure ◽  
Data Simulation ◽  
Dynamic Prediction ◽  
Computational Procedures ◽  
Base Of Support

The purpose of this paper is to study formulations and computational procedures for prediction of natural human response to tilting of its base of support. The human skeletal structure is modeled as a five-segment, four-degree-of-freedom mechanical system standing on sinusoidally driven tilting platform in the sagittal plane. The problem is formulated based on predictive dynamics method that leads to an optimization problem. The joint torque square is included in the performance measure and the dynamic stability is achieved by satisfying the vertical forces criterion. The constrained nonlinear optimization problem is solved using an algorithm based on the sequential quadratic programming (SQP) approach. The results which are joint trajectories and torques are characterized in terms of two main types of movement strategies observed in humans, namely, the ankle and hip strategies. Moreover, the effect of arms on the stability of the model is studied. The results obtained with the formulation are validated with the experimental data. Simulation results demonstrate the effectiveness of the proposed formulation in prediction of natural motion of human in response to tilting of the base plate.

Development of 3D Equipment Interaction With Predictive Dynamics in Human Motion Simulation

2016 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Human Body ◽  
Degrees Of Freedom ◽  
Reaction Force ◽  
Human Motion ◽  
The Body ◽  
Joint Torque ◽  
Human Model ◽  
Motion Simulation ◽  
Predictive Dynamics ◽  
Human Motion Simulation

3D equipment interaction module in human motion simulation is developed in this paper. A predictive dynamics method is used to simulate human motion, and a helmet is modeled as the equipment that is attached to the human body. We then implement this method using the predictive dynamics task of walking. A mass-spring-damper system is attached at the top of the head as a helmet model. The equations of motion for the helmet are also derived in a recursive Lagrangian formulation within the same inertial reference frame as the human model’s. The total number of degrees of freedom for the human model is 55 — 6 degrees of freedom for global translation and rotation, and 49 degrees of freedom for the body. The helmet has 7 degrees of freedom, but 6 of them are dependent to the human model. The movement of the helmet is analyzed due to the human motion. Then, the reaction force between the human body and the equipment is calculated. Once the reaction force is obtained, it is applied to the human body as an external force in the predictive dynamics optimization process. Results include the motion of equipment, the force acting on body at the attachment point, the joint torque profiles, and the ground reaction force profiles at the foot contacting point.

Optimal Posture and Supporting Hand Force Prediction for Common Automotive Assembly One-Handed Tasks

2014 ◽  
Vol 6 (2) ◽  
Author(s):  
Bradley Howard ◽  
James Yang ◽  
Burak Ozsoy
Keyword(s):  
Stability Analysis ◽  
Degrees Of Freedom ◽  
Human Performance ◽  
Performance Measure ◽  
Joint Torque ◽  
External Support ◽  
Human Model ◽  
Automotive Assembly ◽  
External Forces ◽  
Hand Forces

People often complete tasks using one hand for the task and one hand for support. These one-handed support tasks can be found in many different types of jobs, such as automotive assembly jobs. Optimization-based posture prediction has proven to be a valid tool in predicting the postures necessary to complete the tasks, but the related external support forces have been prescribed and not predicted. This paper presents a method in which the optimal posture and related supporting hand forces can be predicted simultaneously using optimization and stability analysis techniques. Postures are evaluated using a physics-based human performance measure (HPM) while external forces are assessed using stability analysis. The physics-based performance measures are based on joint torque. Stability is analyzed using criteria based on a 3D zero moment point (ZMP). The human model used in the prediction contains 56 degrees of freedom and is based on a 50th percentile female in stature. Tasks based on common automotive assembly one-handed tasks found in literature are considered as examples to test the proposed method. Overall, the predicted supporting hand forces have good correlation with experimentally measured forces.

Human Gait Prediction with a High DOF Upper Body: A Multi-Objective Optimization of Discomfort and Energy Cost

2017 ◽  
Vol 14 (01) ◽  
pp. 1650025
Author(s):  
Hyun-Jung Kwon ◽  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Human Motion ◽  
Performance Measure ◽  
Joint Torque ◽  
Upper Body ◽  
Whole Body ◽  
Multi Objective Optimization ◽  
Backward Walking ◽  
Multi Objective ◽  
Body Model ◽  
Neutral Angle

To predict the 3D walking pattern of a human, a detailed upper body model that includes the spine, shoulders, and neck must be made, which is challenging because of the coupling relations of degrees of freedom (DOF) in these body sections. The objective of this study was to develop a discomfort function for including a high DOF upper body model during walking. A multi-objective optimization (MOO) method was formulated by minimizing dynamic effort (DE) and the discomfort function simultaneously. The discomfort function is defined as the sum of the squares of deviation of joint angles from their neutral angle positions. The neutral angle position is defined as a relaxed human posture without actively applied external forces. The DE is the sum of the joint torque squared. To illustrate the capability of including a high DOF upper body, backward walking is used as an example. By minimizing both DE and the discomfort function, a 3D whole-body model with a high DOF upper body for walking was simulated successfully. The proposed MOO is a promising human performance measure to predict human motion using a high DOF upper body with full range of motion. This has been demonstrated by simulating backward walking, lifting, and ingress motions.

scholarly journals Running ground reaction forces across footwear conditions are predicted from the motion of two body mass components

2019 ◽  
Vol 126 (5) ◽  
pp. 1315-1325 ◽  
Author(s):  
Andrew B. Udofa ◽  
Kenneth P. Clark ◽  
Laurence J. Ryan ◽  
Peter G. Weyand
Keyword(s):  
Ground Reaction Force ◽  
Lower Limb ◽  
Reaction Force ◽  
Ground Reaction Forces ◽  
Vertical Ground Reaction Force ◽  
Time Patterns ◽  
Foot Strike ◽  
Reaction Forces ◽  
Vertical Ground ◽  
Force Time

Although running shoes alter foot-ground reaction forces, particularly during impact, how they do so is incompletely understood. Here, we hypothesized that footwear effects on running ground reaction force-time patterns can be accurately predicted from the motion of two components of the body’s mass (mb): the contacting lower-limb (m1 = 0.08mb) and the remainder (m2 = 0.92mb). Simultaneous motion and vertical ground reaction force-time data were acquired at 1,000 Hz from eight uninstructed subjects running on a force-instrumented treadmill at 4.0 and 7.0 m/s under four footwear conditions: barefoot, minimal sole, thin sole, and thick sole. Vertical ground reaction force-time patterns were generated from the two-mass model using body mass and footfall-specific measures of contact time, aerial time, and lower-limb impact deceleration. Model force-time patterns generated using the empirical inputs acquired for each footfall matched the measured patterns closely across the four footwear conditions at both protocol speeds ( r2 = 0.96 ± 0.004; root mean squared error  = 0.17 ± 0.01 body-weight units; n = 275 total footfalls). Foot landing angles (θF) were inversely related to footwear thickness; more positive or plantar-flexed landing angles coincided with longer-impact durations and force-time patterns lacking distinct rising-edge force peaks. Our results support three conclusions: 1) running ground reaction force-time patterns across footwear conditions can be accurately predicted using our two-mass, two-impulse model, 2) impact forces, regardless of foot strike mechanics, can be accurately quantified from lower-limb motion and a fixed anatomical mass (0.08mb), and 3) runners maintain similar loading rates (ΔFvertical/Δtime) across footwear conditions by altering foot strike angle to regulate the duration of impact. NEW & NOTEWORTHY Here, we validate a two-mass, two-impulse model of running vertical ground reaction forces across four footwear thickness conditions (barefoot, minimal, thin, thick). Our model allows the impact portion of the impulse to be extracted from measured total ground reaction force-time patterns using motion data from the ankle. The gait adjustments observed across footwear conditions revealed that runners maintained similar loading rates across footwear conditions by altering foot strike angles to regulate the duration of impact.

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