Optimization-based dynamic motion simulation and energy expenditure prediction for a digital human

Joo Hyun Kim, Karim Abdel-Malek, Jingzhou Yang, Kimberly Farrell, Kyle Nebel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an optimization-based algorithm for simulating the dynamic motion of a digital human. We also formulate the metabolic energy expenditure during the motion, which is calculated within our algorithm. This algorithm is implemented and applied to Santos, an avatar developed at The University of Iowa. Santos is a part of a virtual environment for conducting digital human analysis consisting of posture prediction, motion prediction, and physiology studies. This paper demonstrates our dynamic motion algorithm within the Santos virtual environment. Mathematical evaluations of human performance are essential to any effort to compare various ergonomic designs. In fact, the human factors design process can be formulated as an optimization problem that maximizes human performance. In particular, an optimal design must be found while taking into consideration the effects of different motions and hand loads corresponding to a number of tasks. To evaluate these motions, we propose formulating an optimization problem for motion and posture prediction. Metabolic energy expenditure, where total muscle energy is decomposed as mechanical work and heat, is used to evaluate human performance. Thus, dynamic motion is calculated by minimizing energy expenditure subject to several physical and physiological constraints, then solving for the joint torques and kinematic profiles. The results of the generalized torque at each joint will be useful in future studies of muscle stress prediction during a given task.

Original languageEnglish (US)
Title of host publicationDigital Human Modeling for Design and Engineering Symposium
StatePublished - 2005
EventDigital Human Modeling for Design and Engineering Symposium - Iowa City, IA, United States
Duration: Jun 14 2005Jun 16 2005

Other

OtherDigital Human Modeling for Design and Engineering Symposium
CountryUnited States
CityIowa City, IA
Period6/14/056/16/05

Fingerprint

Virtual reality
Muscle
Torque
Physiology
Ergonomics
Human engineering
Kinematics
Energy Metabolism
Hot Temperature
Optimal design

Keywords

  • dynamics
  • heat
  • human performance measures
  • joint torque
  • Keywords energy
  • motion/posture prediction
  • optimization
  • power
  • task-based

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

Cite this

Kim, J. H., Abdel-Malek, K., Yang, J., Farrell, K., & Nebel, K. (2005). Optimization-based dynamic motion simulation and energy expenditure prediction for a digital human. In Digital Human Modeling for Design and Engineering Symposium

Optimization-based dynamic motion simulation and energy expenditure prediction for a digital human. / Kim, Joo Hyun; Abdel-Malek, Karim; Yang, Jingzhou; Farrell, Kimberly; Nebel, Kyle.

Digital Human Modeling for Design and Engineering Symposium. 2005.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kim, JH, Abdel-Malek, K, Yang, J, Farrell, K & Nebel, K 2005, Optimization-based dynamic motion simulation and energy expenditure prediction for a digital human. in Digital Human Modeling for Design and Engineering Symposium. Digital Human Modeling for Design and Engineering Symposium, Iowa City, IA, United States, 6/14/05.
Kim JH, Abdel-Malek K, Yang J, Farrell K, Nebel K. Optimization-based dynamic motion simulation and energy expenditure prediction for a digital human. In Digital Human Modeling for Design and Engineering Symposium. 2005
Kim, Joo Hyun ; Abdel-Malek, Karim ; Yang, Jingzhou ; Farrell, Kimberly ; Nebel, Kyle. / Optimization-based dynamic motion simulation and energy expenditure prediction for a digital human. Digital Human Modeling for Design and Engineering Symposium. 2005.
@inproceedings{063df8fe16174177b9ee6da485f12ccc,
title = "Optimization-based dynamic motion simulation and energy expenditure prediction for a digital human",
abstract = "This paper presents an optimization-based algorithm for simulating the dynamic motion of a digital human. We also formulate the metabolic energy expenditure during the motion, which is calculated within our algorithm. This algorithm is implemented and applied to Santos™, an avatar developed at The University of Iowa. Santos™ is a part of a virtual environment for conducting digital human analysis consisting of posture prediction, motion prediction, and physiology studies. This paper demonstrates our dynamic motion algorithm within the Santos™ virtual environment. Mathematical evaluations of human performance are essential to any effort to compare various ergonomic designs. In fact, the human factors design process can be formulated as an optimization problem that maximizes human performance. In particular, an optimal design must be found while taking into consideration the effects of different motions and hand loads corresponding to a number of tasks. To evaluate these motions, we propose formulating an optimization problem for motion and posture prediction. Metabolic energy expenditure, where total muscle energy is decomposed as mechanical work and heat, is used to evaluate human performance. Thus, dynamic motion is calculated by minimizing energy expenditure subject to several physical and physiological constraints, then solving for the joint torques and kinematic profiles. The results of the generalized torque at each joint will be useful in future studies of muscle stress prediction during a given task.",
keywords = "dynamics, heat, human performance measures, joint torque, Keywords energy, motion/posture prediction, optimization, power, task-based",
author = "Kim, {Joo Hyun} and Karim Abdel-Malek and Jingzhou Yang and Kimberly Farrell and Kyle Nebel",
year = "2005",
language = "English (US)",
booktitle = "Digital Human Modeling for Design and Engineering Symposium",

}

TY - GEN

T1 - Optimization-based dynamic motion simulation and energy expenditure prediction for a digital human

AU - Kim, Joo Hyun

AU - Abdel-Malek, Karim

AU - Yang, Jingzhou

AU - Farrell, Kimberly

AU - Nebel, Kyle

PY - 2005

Y1 - 2005

N2 - This paper presents an optimization-based algorithm for simulating the dynamic motion of a digital human. We also formulate the metabolic energy expenditure during the motion, which is calculated within our algorithm. This algorithm is implemented and applied to Santos™, an avatar developed at The University of Iowa. Santos™ is a part of a virtual environment for conducting digital human analysis consisting of posture prediction, motion prediction, and physiology studies. This paper demonstrates our dynamic motion algorithm within the Santos™ virtual environment. Mathematical evaluations of human performance are essential to any effort to compare various ergonomic designs. In fact, the human factors design process can be formulated as an optimization problem that maximizes human performance. In particular, an optimal design must be found while taking into consideration the effects of different motions and hand loads corresponding to a number of tasks. To evaluate these motions, we propose formulating an optimization problem for motion and posture prediction. Metabolic energy expenditure, where total muscle energy is decomposed as mechanical work and heat, is used to evaluate human performance. Thus, dynamic motion is calculated by minimizing energy expenditure subject to several physical and physiological constraints, then solving for the joint torques and kinematic profiles. The results of the generalized torque at each joint will be useful in future studies of muscle stress prediction during a given task.

AB - This paper presents an optimization-based algorithm for simulating the dynamic motion of a digital human. We also formulate the metabolic energy expenditure during the motion, which is calculated within our algorithm. This algorithm is implemented and applied to Santos™, an avatar developed at The University of Iowa. Santos™ is a part of a virtual environment for conducting digital human analysis consisting of posture prediction, motion prediction, and physiology studies. This paper demonstrates our dynamic motion algorithm within the Santos™ virtual environment. Mathematical evaluations of human performance are essential to any effort to compare various ergonomic designs. In fact, the human factors design process can be formulated as an optimization problem that maximizes human performance. In particular, an optimal design must be found while taking into consideration the effects of different motions and hand loads corresponding to a number of tasks. To evaluate these motions, we propose formulating an optimization problem for motion and posture prediction. Metabolic energy expenditure, where total muscle energy is decomposed as mechanical work and heat, is used to evaluate human performance. Thus, dynamic motion is calculated by minimizing energy expenditure subject to several physical and physiological constraints, then solving for the joint torques and kinematic profiles. The results of the generalized torque at each joint will be useful in future studies of muscle stress prediction during a given task.

KW - dynamics

KW - heat

KW - human performance measures

KW - joint torque

KW - Keywords energy

KW - motion/posture prediction

KW - optimization

KW - power

KW - task-based

UR - http://www.scopus.com/inward/record.url?scp=84877481811&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84877481811&partnerID=8YFLogxK

M3 - Conference contribution

BT - Digital Human Modeling for Design and Engineering Symposium

ER -