Multi-Objective Optimization of Human Gait With a Discomfort Function

2016 ◽  
Author(s):  
Hyun-Jung Kwon ◽  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Joint Torque ◽  
Upper Body ◽  
Whole Body ◽  
Human Gait ◽  
Multi Objective Optimization ◽  
Joint Angles ◽  
Backward Walking ◽  
Multi Objective ◽  
Body Model ◽  
Neutral Angle

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 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 dynamic effort is the sum of the joint torque squared. To investigate the efficacy of the proposed MOO method, backward walking simulation was conducted. By minimizing both dynamic effort and the discomfort function, a 3D whole body model with a high DOF upper body for walking was demonstrated successfully.

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 Measurement of Human Gait Symmetry using Body Surface Normals Extracted from Depth Maps

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 891 ◽  
Author(s):  
Trong-Nguyen Nguyen ◽  
Huu-Hung Huynh ◽  
Jean Meunier
Keyword(s):  
Body Surface ◽  
Lower Limbs ◽  
Upper Body ◽  
Whole Body ◽  
Human Gait ◽  
Gait Symmetry ◽  
Symmetry Index ◽  
Depth Maps ◽  
Abnormal Gait ◽  
3D Information

In this paper, we introduce an approach for measuring human gait symmetry where the input is a sequence of depth maps of subject walking on a treadmill. Body surface normals are used to describe 3D information of the walking subject in each frame. Two different schemes for embedding the temporal factor into a symmetry index are proposed. Experiments on the whole body, as well as the lower limbs, were also considered to assess the usefulness of upper body information in this task. The potential of our method was demonstrated with a dataset of 97,200 depth maps of nine different walking gaits. An ROC analysis for abnormal gait detection gave the best result ( AUC = 0.958 ) compared with other related studies. The experimental results provided by our method confirm the contribution of upper body in gait analysis as well as the reliability of approximating average gait symmetry index without explicitly considering individual gait cycles for asymmetry detection.

Multi-objective optimization-based method for kinematic posture prediction: development and validation

Robotica ◽  
2010 ◽  
Vol 29 (2) ◽  
pp. 245-253 ◽  
Author(s):  
Jingzhou (James) Yang ◽  
Tim Marler ◽  
Salam Rahmatalla
Keyword(s):  
Performance Measures ◽  
Human Performance ◽  
Design Tool ◽  
Upper Body ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Validation Criteria ◽  
Posture Prediction ◽  
Development And Validation ◽  
Digital Human

SUMMARYPosture prediction plays an important role in product design and manufacturing. There is a need to develop a more efficient method for predicting realistic human posture. This paper presents a method based on multi-objective optimization (MOO) for kinematic posture prediction and experimental validation. The predicted posture is formulated as a multi-objective optimization problem. The hypothesis is that human performance measures (cost functions) govern how humans move. Twelve subjects, divided into four groups according to different percentiles, participated in the experiment. Four realistic in-vehicle tasks requiring both simple and complex functionality of the human simulations were chosen. The subjects were asked to reach the four target points, and the joint centers for the wrist, elbow, and shoulder and the joint angle of the elbow were recorded using a motion capture system. We used these data to validate our model. The validation criteria comprise R-square and confidence intervals. Various physics factors were included in human performance measures. The weighted sum of different human performance measures was used as the objective function for posture prediction. A two-domain approach was also investigated to validate the simulated postures. The coefficients of determinant for both within-percentiles and cross-percentiles are larger than 0.70. The MOO-based approach can predict realistic upper body postures in real time and can easily incorporate different scenarios in the formulation. This validated method can be deployed in the digital human package as a design tool.

A Body Model Server for Human Motion Capture and Representation

1996 ◽  
Vol 5 (4) ◽  
pp. 381-392 ◽  
Author(s):  
Joshua Bers
Keyword(s):  
Real Time ◽  
Data Streams ◽  
Geometric Model ◽  
Human Motion ◽  
The Body ◽  
Geometric Constraints ◽  
Upper Body ◽  
Accurate Information ◽  
Joint Angles ◽  
Body Model

This paper presents a body model server (BMS) that provides real-time access to the position and posture of a person's torso, arms, hands, head, and eyes. It can be accessed by clients over a network. The BMS is designed to function as a device-independent data-layer between the sensing devices and client applications that require real-time human motion data, such as animation control. It can provide clients with accurate information at up to 40 Hz. For data collection, the model uses four magnetic position/ orientation sensors, two data-gloves, and an eye-tracker. The BMS combines the data-streams from the sensors and transforms them into snapshots of the user's upper-body pose. A geometric model made up of joints and segments structures the input. Posture of the body is represented by joint angles. Two unique characteristics of our approach are the use of the implicit, geometric constraints of the sensed body to simplify the computation of the unmeasured joint angles, and the use of time-stamped data that allow synchronization with other data streams, e.g., speech input. This paper describes the architecture of the BMS, including the management of multiple input devices, the representation and computation of the position and joint angle data, and the client-server interface.

The Implement of Optimization Design of a Car Body Based on VCD-ICAE System

2012 ◽  
Vol 479-481 ◽  
pp. 2577-2581
Author(s):  
Wen Bin Hou ◽  
Zhen Jun Bi ◽  
Hong Zhe Zhang ◽  
Ping Hu
Keyword(s):  
The Body ◽  
Vehicle Body ◽  
Whole Body ◽  
Design Parameters ◽  
Concept Design ◽  
Multi Objective Optimization ◽  
Detailed Model ◽  
Car Body ◽  
Multi Objective ◽  
Body Concept

In order to get the optimistic structure property and design parameters of a car body, the system of vehicle body concept design (VCD-ICAE) was developed by us to make the body design in the conceptual phase in the paper. It can build parametric geometry modeling and FEM model of body-in-white (BIW) automatically, and the structural stiffness was calculated. Based on the former model, a multi-objective optimization of the total body was designed to afford the reasonable parameters for detailed model of BIW, which realized lightweight of the whole body and high stiffness. In the paper, the total theory and flowchart of vehicle body concept design were afforded. An example with real body’s data was shown to prove the validity of the multi-objective optimization module in VCD-ICAE system. Finally, the optimal design scheme of the body was provided.

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