Muscle Force Prediction of 2D Gait Using Predictive Dynamics Optimization

2016 ◽  
Author(s):  
Yujiang Xiang
Keyword(s):  
Degrees Of Freedom ◽  
Muscle Force ◽  
Optimal Solution ◽  
Human Motion ◽  
Human Gait ◽  
Predictive Dynamics ◽  
Physical Constraints ◽  
Reaction Forces ◽  
Muscle Groups ◽  
Optimization Schemes

Cyclic human gait is simulated in this work by using a 2D musculoskeletal model with 12 degrees of freedom (DOF). Eight muscle groups are modeled on each leg. Predictive dynamics approach is used to predict the walking motion. In this process, the model predicts joints dynamics and muscle forces simultaneously using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion, ground reaction forces (GRF), and muscle force data during walking task. The proposed optimization algorithm is robust and the optimal solution is obtained in seconds. This can be used in human health domain such as leg prosthesis design.

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.

Human Stair Ascent and Descent Simulations

2014 ◽  
Author(s):  
Yujiang Xiang ◽  
Joo H. Kim ◽  
Hyun-Joon Chung ◽  
James Yang ◽  
Hyun-Jung Kwon
Keyword(s):  
Degrees Of Freedom ◽  
Human Motion ◽  
Stair Climbing ◽  
Human Model ◽  
Physical Constraints ◽  
Digital Human Model ◽  
Stair Ascent ◽  
Reaction Forces ◽  
Optimization Schemes ◽  
Digital Human

Human stair ascent and descent are simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). Hybrid predictive dynamics approach is used to predict the stair climbing motion with weapons and backpacks. 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 stair climbing tasks. This can be used in human health domain such as leg prosthesis design.

Whole-Body Human-to-Humanoid Motion Imitation

2013 ◽  
Vol 479-480 ◽  
pp. 617-621
Author(s):  
Hsien I Lin ◽  
Zan Sheng Chen
Keyword(s):  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Optimal Solution ◽  
Human Motion ◽  
Body Motion ◽  
Upper Body ◽  
Whole Body ◽  
Nao Robot ◽  
Novel Approach ◽  
Intuitive Method

Human-to-Humanoid motion imitation is an intuitive method to teach a humanoid robot how to act by human demonstration. For example, teaching a robot how to stand is simply showing the robot how a human stands. Much of previous work in motion imitation focuses on either upper-body or lower-body motion imitation. In this paper, we propose a novel approach to imitate human whole-body motion by a humanoid robot. The main problem of the proposed work is how to control robot balance and keep the robot motion as similar as taught human motion simultaneously. Thus, we propose a balance criterion to assess how well the root can balance and use the criterion and a genetic algorithm to search a sub-optimal solution, making the root balanced and its motion similar to human motion. We have validated the proposed work on an Aldebaran Robotics NAO robot with 25 degrees of freedom. The experimental results show that the root can imitate human postures and autonomously keep itself balanced.

Efficient Hyper-Volumetric Contact Dynamic Modelling of the Foot Within Human Gait Simulations

2013 ◽  
Author(s):  
Mohammad Sharif Shourijeh ◽  
John McPhee
Keyword(s):  
Rigid Body ◽  
Degrees Of Freedom ◽  
Center Of Pressure ◽  
Dynamic Modelling ◽  
Contact Model ◽  
Human Gait ◽  
Revolute Joints ◽  
Interaction Modelling ◽  
Reaction Forces ◽  
Hind Foot

This study describes the development of a multi-body foot contact model consisting of spherical volumetric models for the surfaces of the foot. The developed model is two-dimensional, and consists of two segments, the hind-foot, mid-foot, and forefoot as one rigid body and the phalanges collectively as the second rigid body. The model has four degrees of freedom: ankle x, y, hind-foot orientation, and metatarsal joint angle. Both ankle and metatarsal joints are assumed to be revolute joints. Three different types of contact elements are targeted: Kelvin-Voigt, linear volumetric, and nonlinear volumetric. The models are kinematically driven at the ankle and the metatarsal joints, and simulated horizontal and vertical ground reaction forces as well as center of pressure location are compared against the measured quantities within a complete human gait cycle. The hyper-volumetric foot contact model was found to be a suitable choice for foot/ground interaction modelling within human gait simulations.

Human Carrying Simulation With Symmetric and Asymmetric Loads Using Optimization

2014 ◽  
Vol 30 (1) ◽  
pp. 140-146 ◽  
Author(s):  
Yujiang Xiang
Keyword(s):  
Degrees Of Freedom ◽  
Human Model ◽  
Physical Constraints ◽  
Digital Human Model ◽  
Load Carrying ◽  
Joint Dynamics ◽  
Asymmetric Load ◽  
Optimization Schemes ◽  
Robust Prediction ◽  
Digital Human

Human carrying is simulated in this work by using a skeletal digital human model with 55 degrees of freedom. An optimization-based approach is used to predict the carrying motion with symmetric and asymmetric loads. In this process, the model predicts joint dynamics using optimization schemes and task-based physical constraints. The results indicate that the model can predict different carrying strategies during symmetric and asymmetric load-carrying tasks. The model can also indicate the risk factors for extreme loading situations. With such robust prediction capability, the model could be used for biomedical and ergonomic studies.

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.

Predictive Simulation of Human Walk-to-Run Transition

2012 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Yujiang Xiang ◽  
Rajan Bhatt ◽  
Jasbir S. Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Optimal Solution ◽  
Joint Torques ◽  
Double Support ◽  
Physical Constraints ◽  
Transition Prediction ◽  
Optimization Formulation ◽  
Reaction Forces ◽  
Step Transition ◽  
Skeletal Model ◽  
Dynamics Method

A general optimization formulation for walk-to-run transition prediction using 3D skeletal model is presented. The walk-to-run transition is used to connect fast walking to slow running by using a step-to-step transition formulation. Walk-to-run transition includes four phases: double support walking phase, single support swinging phase, running phase, and finally single support running phase. The transition task is formulated as an optimization problem in which the dynamic effort is minimized subject to basic physical constraints. The joint torques and ground reaction forces (GRF) are recovered and analyzed from the simulation. The optimal solution of transition simulation is obtained in a few minutes by using predictive dynamics method.

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.

Foot-Ground Interaction for 2D Gait Using Concurrent Optimization

2017 ◽  
Author(s):  
Yujiang Xiang ◽  
Benjamin Ramirez ◽  
Sarah Hoffman ◽  
Tonoy Chowdhury
Keyword(s):  
Degrees Of Freedom ◽  
Equations Of Motion ◽  
Reaction Force ◽  
Optimal Solution ◽  
Optimization Method ◽  
Inverse Optimization ◽  
Human Gait ◽  
Optimization Approach ◽  
Concurrent Optimization ◽  
Skeletal Model

Foot-ground interaction is modeled for a human gait simulation by using a 2D skeletal model with 12 degrees of freedom (DOF). Three contacting elements are attached to the heel, phalangeal, and toe sections respectively. The contacting process is modeled using an inverse optimization approach, in which the contacting force due to the penetration deformation and velocity is equal to the balanced ground reaction force (GRF). This is set as an equality constraint in the walking optimization formulation. A predictive dynamics approach is used to predict the walking motion and to optimize the contacting process. The results indicated that the contacting model can realistically match the GRF, and the resulting gait motion, contacting penetration, and contacting parameters are all optimized simultaneously. The optimal solution is obtained in seconds. This demonstrates an efficient way to model the foot-ground contacting deformation process using an inverse optimization method and eliminates the need for integrating equations of motion (EOM).

scholarly journals Development and Performance Verification of a Motorized Prosthetic Leg for Stair Walking

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Kiwon Park ◽  
Hyoung-Jong Ahn ◽  
Kwang-Hee Lee ◽  
Chul-Hee Lee
Keyword(s):  
Ankle Joint ◽  
Degrees Of Freedom ◽  
Human Motion ◽  
Product Development Process ◽  
Structural Safety ◽  
Human Gait ◽  
Element Analysis ◽  
Stair Walking ◽  
And Performance ◽  
Virtual Product Development

The present study emphasized on the optimal design of a motorized prosthetic leg and evaluation of its performance for stair walking. Developed prosthetic leg includes two degrees of freedom on the knee and ankle joint designed using a virtual product development process for better stair walking. The DC motor system was introduced to imitate gait motion in the knee joint, and a spring system was applied at the ankle joint to create torque and flexion angle. To design better motorized prosthetic leg, unnecessary mass was eliminated via a topology optimization process under a complex walking condition in a boundary considered condition and aluminum alloy for lower limb and plastic nylon through 3D printing foot which were used. The structural safety of a developed prosthetic leg was validated via finite element analysis under a variety of walking conditions. In conclusion, the motorized prosthetic leg was optimally designed while maintaining structural safety under boundary conditions based on the human walking data, and its knee motions were synchronized with normal human gait via a PD controller. The results from this study about powered transfemoral prosthesis might help amputees in their rehabilitation process. Furthermore, this research can be applied to the area of biped robots that try to mimic human motion.

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