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.

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.

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.

WORKSPACE OF DIGITAL HUMAN LOWER EXTREMITIES

2009 ◽  
Vol 06 (02) ◽  
pp. 291-306 ◽  
Author(s):  
JINGZHOU (JAMES) YANG
Keyword(s):  
Degrees Of Freedom ◽  
Virtual Prototyping ◽  
Lower Extremities ◽  
Complete Information ◽  
Upper Body ◽  
Human Model ◽  
Singular Surfaces ◽  
Rank Deficiency ◽  
Digital Human Model ◽  
Digital Human

This paper presents an applicable formula for determining the workspace of digital human lower extremities. The digital human model has over 100 degrees of freedom (DOF): 94 in the upper body, 14 in the lower extremities, 5 in the neck, 4 in the eyes, and 25 for each hand. The Jacobian row rank deficiency criteria are implemented to determine the singular surfaces that finally form the workspace. The use of this digital human model for determining workspace offers several advantages over direct measurement: (1) the workspace can be visualized in real-time based on offline computation, (2) the workspace can be used for the ergonomic design of products in the virtual prototyping stage, and (3) the calculated workspace includes complete information about the envelope and inside characteristics.

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.

The Hybrid Predictive Dynamics Method for Analysis, Simulation and Prediction of Human Motion

2016 ◽  
Author(s):  
Mahdiar Hariri
Keyword(s):  
Motion Capture ◽  
Degrees Of Freedom ◽  
Human Motion ◽  
Human Model ◽  
Coordinate Frame ◽  
Optimization Approach ◽  
Predictive Dynamics ◽  
Digital Human Model ◽  
Digital Human ◽  
Dynamics Method

The ‘Hybrid Predictive Dynamics Method for Digital Human Modeling’ is analyzed in this work. The ‘Hybrid’ prefix mentioned in the literature recently [1], refers to the use of motion capture data for improving human motion simulations. This use of motion capture compensates for the inherent weaknesses of purely theoretical motion prediction due to deficiencies in computational power or available theoretical backgrounds. In this work, it is shown that while using the ‘Hybrid’ the more precisely and finely the human motion is modeled (if computational and theoretical limitations allow), the less will be the need for the ‘Hybrid’ method and the more will the human model be able to change the prediction if the inputs are varied (cause and effect). Several human motion scenarios are mentioned in this work. These motion tasks are: “Jogging around Markers”, “Rolling Over”, “Getting up from Prone”, “Vertical Jumping” and “Kneeling and Aiming”. The digital human model is a full-body, three dimensional model with 55 degrees of freedom. Six degrees of freedom specify the global position and orientation of the coordinate frame attached to the pelvic point of the digital human and 49 degrees of freedom represent the revolute joints which model the human joints and determine the kinematics of the entire digital human. Motion is generated by a multi-objective optimization approach. The optimization problem is subject to constraints which represent the limitations of the environment, the digital human model and the motion task. Design variables are the joint angle profiles. All the forces, inertial, gravitational as well as external, are known, except the ground reaction forces. The feasibility of the generation of that arbitrary motion by using the given ground contact areas is ensured by using the well-known Zero Moment Point (ZMP) constraint.

Human Carrying Simulation With Symmetric and Asymmetric Loads

2012 ◽  
Author(s):  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Salam Rahmatalla ◽  
Hyun-Joon Chung ◽  
Rajan Bhatt ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Human Motion ◽  
Human Model ◽  
Physical Constraints ◽  
Digital Human Model ◽  
Load Carrying ◽  
Reaction Forces ◽  
Asymmetric Load ◽  
Optimization Schemes ◽  
Digital Human

Human carrying is simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). Predictive dynamics approach is used to predict the carrying motion with symmetric and asymmetric loads. In this process, the model predicts joints dynamics using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion and ground reaction forces data during symmetric and asymmetric load carrying task. With such prediction capability the model could be used for biomedical and ergonomic studies.

Optimization-based posture prediction for human upper body

Robotica ◽  
2009 ◽  
Vol 27 (4) ◽  
pp. 607-620 ◽  
Author(s):  
Zan Mi ◽  
Jingzhou (James) Yang ◽  
Karim Abdel-Malek
Keyword(s):  
Performance Measures ◽  
Degrees Of Freedom ◽  
Human Performance ◽  
Computational Algorithm ◽  
Performance Measure ◽  
Upper Body ◽  
Cost Functions ◽  
Posture Prediction ◽  
Joint Limits ◽  
Digital Human

SUMMARYA general methodology and associated computational algorithm for predicting postures of the digital human upper body is presented. The basic plot for this effort is an optimization-based approach, where we believe that different human performance measures govern different tasks. The underlying problem is characterized by the calculation (or prediction) of the human performance measure in such a way as to accomplish a specified task. In this work, we have not limited the number of degrees of freedom associated with the model. Each task has been defined by a number of human performance measures that are mathematically represented by cost functions that evaluate to a real number. Cost functions are then optimized, i.e., minimized or maximized, subject to a number of constraints, including joint limits. The formulation is demonstrated and validated. We present this computational formulation as a broadly applicable algorithm for predicting postures using one or more human performance measures.

Optimization-Based Digital Human Dynamics: Santos™ Walking Backwards

2007 ◽  
Author(s):  
Hyun Jung Kwon ◽  
Yujiang Xiang ◽  
Salam Rahmatalla ◽  
R. Timothy Marler ◽  
Karim Abdel-Malek ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Joint Angle ◽  
Spline Interpolation ◽  
Performance Measure ◽  
Degree Of Freedom ◽  
Human Model ◽  
Entire Body ◽  
Joint Torques ◽  
Digital Human

An objective of this study is to simulate the backward walking motion of a full-body digital human model. The model consists of 55 degree of freedom – 6 degrees of freedom for global translation and rotation and 49 degrees of freedom representing the kinematics of the entire body. The resultant action of all the muscles at a joint is represented by the torque for each degree of freedom. The torques and angles at a joint are treated as unknowns in the optimization problem. The B-spline interpolation is used to represent the time histories of the joint angles and the well-established robotics formulation of the Denavit-Hartenberg method is used for kinematics analysis of the mechanical system. The recursive Lagrangian formulation is used to develop the equations of motion, and was chosen because of its known computational efficiency. The backwards walking problem is formulated as a nonlinear optimization problem. The control points of the B-splines for the joint angle profiles are treated as the design variables. For the performance measure, total dynamic effort that is represented as the integral of the sum of the squares of all the joint torques is minimized using a sequential quadratic programming algorithm. The solution is simulated in the Santos™ environment. Results of the optimization problem are the torque and joint angle profiles. The torques at the key joints and the ground reaction forces are compared to those for the forward walk in order to study the differences between the two walking patterns. Simulation results are approximately validated with the experimental data which is motion captured in the VSR Lab at the University of Iowa.

Optimization-Based Prediction of Aiming and Kneeling Military Tasks Performed by a Soldier

2012 ◽  
Author(s):  
Mahdiar Hariri ◽  
Jasbir Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Human Model ◽  
Ground Reaction Forces ◽  
Optimization Approach ◽  
Ground Contact ◽  
Digital Human Model ◽  
Reaction Forces ◽  
Digital Human ◽  
The Given

The objective of this study is to predict the “Aiming While Standing” and “Aiming While Kneeling” motion tasks for a soldier (human) using a full-body, three dimensional digital human model. The digital human is modeled as a 55 degree of freedom branched mechanism. Six degrees of freedom specify the global position and orientation of the coordinate frame attached to the pelvis of the digital human and 49 degrees of freedom represent the revolute joints which model the human joints and determine the kinematics of the entire digital human. Motion is generated by a multi-objective optimization approach minimizing the mechanical energy and joint discomfort simultaneously. A sequential quadratic programming (SQP) algorithm in SNOPT is used to solve the nonlinear optimization problem. The optimization problem is subject to constraints which represent the limitations of the environment, the digital human model and the motion task. Design variables are the joint angle profiles. All the forces, inertial, gravitational as well as external, are known, except the ground reaction forces. The feasibility of the generation of that arbitrary motion by using the given ground contact areas is ensured by using the well known Zero Moment Point (ZMP) constraint. During the kneeling motion, different parts of the body come in contact and lose contact with the ground which is modeled using a general approach. The ground reaction force on each transient ground contact area is determined using the equations of motion. It is assumed that enough friction exists that allow the human to generate reaction forces as determined by the ZMP constraint. Using these ground reaction forces, the required torques at all joints are calculated by the recursive Lagrangian formulation. Using the given method, we can predict realistic motions for the “Aiming While Standing” and “Aiming While Kneeling” tasks. The optimization approach is able to very well predict the “Natural Point of Aim” which is a well known concept for soldiers. In other words, the approach is able to predict the most comfortable final orientation of the feet on the ground for engaging a specific target. We also predict cases where the orientation of the soldier’s feet are enforced. Many virtual experiments have been conducted by changing the target location in the 3D space, changing the anthropometry of the soldier, adding armor to different joints, changing the variable parameters of the rifle, adding backpack and using different weapons.

Degrees of freedom coupling adapted to the upper limb of a digital human model

2017 ◽  
Vol 5 (4) ◽  
pp. 314
Author(s):  
Pierre Olivier Lemieux ◽  
Arnaud Barré ◽  
Nicola Hagemeister ◽  
Rachid Aissaoui
Keyword(s):  
Upper Limb ◽  
Degrees Of Freedom ◽  
Human Model ◽  
Digital Human Model ◽  
Digital Human
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