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Newsletter Volume 7 - 3rd Quarter 2005

Evaluation of a Computer-Simulation Model for Human Ambulation on Stilts

CONTENTS

Case Study: Evaluation of a Computer-Simulation Model for Human Ambulation on Stilts

Software: LifeMOD™ v2005.1 New Product Release!

Other News: New Book Chapter: "The Virtual Knee" in Total Knee Arthroplasty, Springer pub.



This issue presents a study of the biomechanics of human locomotion while attached to stilts. It is based on the collaborative work between BRG, and the National Institute for Occupational Safety and Health, [Pan, 04].


Also in this issue, learn how BRG.LifeMOD™ makes this technology accessible to all researchers and students of biomechanics. Additionally, we are pleased to announce the release of LifeMOD Version 2005.1 with many new functions and features including a new scalable muscle geometry database for the entire body and scaling muscle graphics. We invite you to download a free trial version of the software; try out one of our 17 easy-to-follow tutorials and begin building physics-based human models today.



EVALUATION OF A COMPUTER SIMULATION MODEL
FOR HUMAN AMBULATION ON STILTS

Introduction

Stilts are elevating tools that are frequently used by construction workers to raise themselves 18 to 40 inches above the ground without the burden of erecting scaffolding or a ladder. Some previous studies [Pan, 00, Pan 99] indicate that construction workers perceive an increased risk of injury when working on stilts. Walking on stilts has raised a number of concerns in the construction industry including slipping, tripping and falling. These concerns have led researchers to look into the design safety of stilts. Do stilts pose an unnecessary risk to construction workers? Do stilts contribute to any chronic injuries and lead to long-term medical problems?

These questions can be examined through many means, including human subject testing, subjective questionnaires and computer modeling. Computer modeling offers some advantages that the other do not. First of all, computer modeling generates more reproducible results [Van Den Bogert, 94] and is inexpensive compared to human subject testing. Computer modeling also enables the user to easily implement many parameters to look at different variables, such as tripping hazards and joint forces. In this way cause-and-effect simulation can be conducted efficiently [Gerristen, 95, Stacoff, 01, Van Den Bogert 94, Van Den Bogert, 02].

To date, there is little data and no in-depth biomechanical analysis which has been conducted to examine the fall risk associated with the use of stilts. Additionally, although computer simulations of human walking are well known [Anderson, 99, Ashkenazy, 02, Chung, 99, Mun, O'Riordain, 03, Scheiner, 95, Van Den Bogert, 02], there is no published literature on computer simulations of human walking on stilts.

The objective of this study is to evaluate and validate a computer simulation stilts model. Once validated, the model can be used to analyze the mechanical stability and to evaluate the joint reaction forces of users during stilt walking, especially when results are analyzed along with findings from a current laboratory study with human subject tests at NIOSH [Miller, 03]. By comparing the ground reaction forces and the body composite center-of-mass of stilt walking to normal walking, the effects on joint loads and mechanical stability can be assessed and higher functioning activities such as trips and falls can be evaluated.

Data Collection

Three male construction workers between the ages of 34 and 40 with at least 12 months of experience in the use of stilts were recruited for walking tasks on 24-inch stilts. Twenty-two reflective markers were placed on the subject's body (figure 1), and eight markers were placed on the stilts (figure 2). A motion analysis system (Motus™, PEAK Performance Technologies, Inc.) with six integrated cameras was used to capture the three-dimensional position of the reflective markers at a rate of 60 frames/sec. The Motus system was also used to collect force data from the force plates (Kistler™ Instrument Corporation). The time-synchronized records of both kinetic and kinematic measures were saved to a file (SLF) to be input into BRG.LifeMOD™.


Figure 1. Twenty-two reflective markers were placed on the subject's anatomical landmarks.Figure 1. Twenty-two reflective markers were placed on the subject's anatomical landmarks.
Figure 2. Stilts used for the present study. Four reflective markers (A, B, C, D) were attached to each stilt for this study experiment. Marker A was used to replace the ankle once the subject donned the stilts. Marker B was used to represent the shoe plate. Markers C and D were used to identify the floor plate.Figure 2. Stilts used for the present study. Four reflective markers (A, B, C, D) were attached to each stilt for this study experiment. Marker A was used to replace the ankle once the subject donned the stilts. Marker B was used to represent the shoe plate. Markers C and D were used to identify the floor plate.

Model Development

BRG.LifeMOD [McGuan, 04] was used to develop the 18 segment model with appropriate biofidelity for this task. The BRG.LifeMOD anthropometric database library was drawn upon to generate the mass properties and dimensions of each segment for each particular human subject. CAD models of the stilts were imported into the program and attached to the feet using bushing stiffness/damping properties derived from laboratory data. Contact forces were created between the base of the stilt and the floor using laboratory derived stiffness, damping and friction properties.

BRG.LifeMOD motion agents are automatically created at each reflective marker location. Motion agents are parts which will be driven using the recorded trajectory information from the experiment. They are attached to the appropriate human/stilt landmark using a spring force. Each motion agent spring forces is normalized to the relative accuracy of the specific reflective marker, thereby allowing for the most accurate reflective marker to contribute most to the model motion.


Figure 3. Human model developed for each subject. Motion agents are automatically created at the reflective marker locations in the experiment. They will drive the model to capture joint motion patterns to be used in a subsequent forward dynamics analysis.Figure 3. Human model developed for each subject. Motion agents are automatically created at the reflective marker locations in the experiment. They will drive the model to capture joint motion patterns to be used in a subsequent forward dynamics analysis.

By creating a true physics-based model, BRG.LifeMOD does not require experimental ground reaction force to run a forward dynamics simulation. The method the program employs is to create the ground reaction forces using physics-based equations to be compared later to experiment force plate data if available. If the predicted ground reaction force differed greatly from the measured ground reaction force, the model may be tuned by altering various parameters.


Figure 4. Physics of the contact force. BRG.LifeMOD calculates the penetration of the blue section of the stilt into ground and generates normal (contact) and transverse (friction) forces.Figure 4. Physics of the contact force. BRG.LifeMOD calculates the penetration of the blue section of the stilt into ground and generates normal (contact) and transverse (friction) forces.

With the human model created and attached to the stilts, and the motion agents positioned at each reflective marker location, the model is now ready for inverse-dynamics analysis. During this dynamic simulation, the three-dimensional joint angle at each anatomical joint is recorded throughout the walking motion.

In a second simulation, the motion agents are removed and proportional-derivative controllers are used to create torques which minimize the error between the desired angle and the instantaneous angle. At this stage the model is fully dynamic and will produce contact forces with the ground which will later be compared to the experiment forces derived from the force plate. Figure 5 depicts the modeling process.


Figure 5. Flow diagram of the stilts model building process in BRG.LifeMOD.Figure 5. Flow diagram of the stilts model building process in BRG.LifeMOD.

Results

The whole body center of mass was used as a comparison data point between the data output from BRG.LifeMOD and the PEAK Motus system. Equation 1 below displays the comparison method between the experiment whole-body center of mass provided by PEAK Motus and the BRG.LifeMOD prediction.

The next series of figures displays a comparison between the experimental data reported from the PEAK Motus system and the BRG.LifeMOD model prediction for one subject in the experiment. Figure 6 displays the whole-body center of mass position comparison in the X (medial-lateral), Y (vertical) and Z (horizontal) axes. Figure 7 displays this data using equation 1 below to further compare the differences. Figure 8 compares the vertical component and the resultant of the left foot ground reaction forces between the experiment and the model prediction.


Equation 1. Absolute and relative whole body center of mass differences between the experiment and the BRG.LifeMOD prediction. The data is reported in the X (medial-lateral), Y (vertical) and Z (horizontal).Equation 1. Absolute and relative whole body center of mass differences between the experiment and the BRG.LifeMOD prediction. The data is reported in the X (medial-lateral), Y (vertical) and Z (horizontal).
Figure 6. Time-histories of COM positions. Solid lines represent BRG.LifeMOD estimation values, dotted lines represent actual measurements from the PEAK motion system.Figure 6. Time-histories of COM positions. Solid lines represent BRG.LifeMOD estimation values, dotted lines represent actual measurements from the PEAK motion system.
Figure 7. Relative position differences of COM for the three coordinates from the results of Equation 1 for the three test subjects.Figure 7. Relative position differences of COM for the three coordinates from the results of Equation 1 for the three test subjects.
Table 1. Relative position differences of the COM for the X and Y coordinates.Table 1. Relative position differences of the COM for the X and Y coordinates.
Figure 8. Vertical component (left) and resultant of ground reaction force (N) for the left foot. Solid lines represent BRG.LifeMOD estimation values, dotted lines represent actual measurements form the PEAK motion system.Figure 8. Vertical component (left) and resultant of ground reaction force (N) for the left foot. Solid lines represent BRG.LifeMOD estimation values, dotted lines represent actual measurements form the PEAK motion system.

Discussion and Conclusions

The model's calculated value for the whole-body center of mass is an important metric for this study. Plotting the center of mass of the BRG.LifeMOD model and the center of mass of the experiment data on the same graph, as shown in figure 6, indicates that these two data look similar; there does not appear to be any large discrepancies between the two sets of data. The positive results of the correlation analyses indicated that these two data significantly correlated to each other and show the same trend. The pattern of the differences of the distance (or absolute position difference) also show very similar results among test subjects (figure 7).

An estimation of ground reaction force is an invaluable indicator of the predictive capabilities of the model, especially if the model is going to be used to determine forces or torques. For the left foot (figure 8), the ground reaction forces obtained from the BRG.LifeMOD model are very similar to the data measured via the force plates. One difference between the model prediction and the measured data is that the force is shifted forward by approximately 0.1 second relative to the measured force when the ground reaction force undergoes sudden changes. These differences are likely due to the inertial effects of the motion upon soft tissues, which are distributed masses that are not rigidly connected to the body (wobbling masses). Liu and Nigg [Liu, 00] indicated that these wobbling masses have remarkable influence on impact force. The wobbling masses are not included in this current, preliminary model, and will be included in the refined model in the future.

In summary, the BRG.LifeMOD model of a person walking on stilts was within acceptable correlation with experiment for three different test subjects. Using this type of evaluated model of a person walking on stilts, researchers will be able to further examine whether stilt walking will result in an increase in joint loading of the legs or back. The model can also provide a useful tool to evaluate slips, falls, sudden stops/starts and tripping hazards associated with the use of stilts.

References

  • []Anderson FC, Pandy MG, Three-dimensional computer simulation of gait, ASME, Bioengineering Division (Publication) BED 42:419 420, 1999.
  • [] Ashkenazy Y, Hausdorff JM, Ivanov PC, Eugene SH, A stochastic model of human gait dynamics, Physica A: Statistical Mechanics and its Applications 316:662-670, 2002.
  • [] Chung S, Hahn JK, in Proc. Computer Animation Conference, Animation of human walking in virtual environments, Geneva, Switzerland, pp. 4-15, 1999.
  • [] Gerritsen KG, Van Den Bogert AJ, Nigg BM, Direct dynamics simulation of the impact phase in heel-toe running, J Biomech 4:181-193, 1995.
  • []Liu W, Nigg BM, A mechanical model to determine the influence of masses and mass distribution on the impact force during running, J Biomech 33:219-224, 2000.
  • []
  • McGuan, S. 2004 BRG.LifeMOD™ 2004 Users Manual, Biomechanics Research Group, Inc.
  • [] Mun JH, Freeman JS, Lim OK, Rim K, New three dimensional kinematic and dynamic model of lower limb, ASME, Bioengineering Division (Publication) BED 35:233-234.
  • []O'Riordain K, Thomas PM, Philips JP, Gilchrist MD, Reconstruction of real world head injury accidents resulting from falls using multibody dynamics, Clin Biomech 18:590--600, 2003.
  • [] Pan CS, Miller, KM, Chiou S, Wu JZ, Evaluation of a computer simulation model for human ambulation on stilts, Journal of Mechanics in Medicine and Biology Vol. 4, No. 3, 2004.
  • []Pan CS, Chiou SS, Hsiao H, Becker P, Akladios M, Assessment of perceived traumatic injury hazards during drywall taping and sanding, Int J Ind Ergon 25:621-631, 2000.
  • [] Pan CS, Chiou SS, Hsaio H, Wassell JT, Keane PR, Assessment of perceived traumatic injury hazards during drywall hanging, Int J Ind Eryon 25:29-37, 1999.
  • [] Scheiner A, Ferencz DC, Qhizeck HJ, Quantitative measurement of stability in human gait through computer simulation and Floquet analysis, Annual International Conference of the IEEE Engineering in Medicine and Biology-Proceedings 17:1489-1490, 1995.
  • [] Stacoff A, Reinschillidt C, Nigg BM, Van Den Bogert AJ, Effects of shoe sole construction on skeletal motion during running, Med Sci Sports Exerc 33:311-319, 2001.
  • [] Van Den Bogert AJ, Analysis and simulation of mechanical loads on the human musculoskeletal system: A methodological overview, Exerc Sport Sci Rev 22:23-51, 1994.
  • []Van Den Bogert AJ, Pavol MJ, Grabiner MD, Response time is more important than walking speed for the ability of older adults to avoid a fall after a trip, J Biomech 35:199-205, 2002.


SOFTWARE

The BRG is pleased to announce the release of LifeMOD™ version 2005.1. This new release makes state-of-the-art human modeling accessible to every investigator interested in the physics behind human motion. The release includes a new muscle parameters library which includes data on physiological cross sectional areas, maximum tissue stresses, etc. for each of the 212 muscles included in LifeMOD. These properties also scale based on body size, weight, age and gender. In addition, the user may affect the muscle output from 5 times normal to 0 to perform muscle imbalance or weakened studies.

A new graphical animation feature has been introduced which allows for the scaling of the muscle graphics and joint graphics based on force and torque magnitudes.

A new generalized contact algorithm which permits general contact between any two surfaces has been introduced. This allows for sophisticated modeling of knee joints, as well as external contacts between the body and the environment.

Due to the tremendous response we received from our users for our "trainable" muscles, we have introduced several more muscle groups to ensure LifeMOD's position as the most powerful, versatile and ease-to-use full-body human modeling package available today.

This new version is a direct result of an ongoing and rigorous user dialogue, partnerships with our research community, and the inclusion of much functionality developed by our professional staff to solve the world's most demanding biomechanics issues. View Examples...



SERVICES

The Biomechanics Research Group Inc. is a service-based organization chartered to empower our customers to capture a level of ROI from their technology investment in ways they've never imagined. We are committed to customer service, product excellence and continuous quality improvement in all we do. We provide training, modeling and simulation expertise. Contact us for more information.



OTHER NEWS

New publication: "Chapter 24: The Virtual Knee" in Total Knee Arthoplasty, Springer 2005. See PDF


2005 Korean Cad/Cam Conference Keynote Address "Achieving Commercial Success in Biomechanics Simulation" by Shawn McGuan President/CEO of BRG


Recorded webinar: "Virtual Product Development for Biomechanics Applications" by Shawn McGuan


Check out our new model repository! We would like to sincerely thank those who have contributed to the LifeMOD™ body of knowledge. We pledge to do our best to increase the technical capabilities of LifeMOD while developing new ways to educate the community.



If you would like further information on our software and services, please contact us.


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