Annals of Biomedical Engineering

, Volume 22, Issue 6, pp 692–706 | Cite as

Inertial properties of the human trunk of males determined from magnetic resonance imaging

  • D. J. Pearsall
  • J. G. Reid
  • R. Ross
Research Articles


The purpose of this study was to evaluate the segmental parameters of the human trunk of malesin vivo using magnetic resonance imaging (MRI). In addition, the efficacy of volumetric estimation and existing prediction formulas to produce segmental properties similar to those produced by MRI was evaluated. As opposed to finding one representative normal value for these parameters, a range of normal values was defined. For instance, the average trunk mass was 42.2%±3.5% (x±SD) of body mass, but values ranged from 35.8% to 48.0%. To account for segment parameters more accurately, specific anthropometric measures need to be considered in addition to overall measures of body height and mass. These specific measures included segment length, circumference, width, and depth. Studies reporting general percentages based on height and/or mass were found to be inadequate predictors of segmental parameters of the trunk compared with MRI estimates. Volumebased estimates, which assume a uniform density distribution within a segment, were found to correspond closely to MRI values except for the thorax. However, the use of density values reflective of the livingin vivo state would likely alleviate this disparity, thus indicating that the volumetric technique may be effective for deriving segmental parameters for large segments of the trunk. Future research should adopt noninvasive techniques such as MRI and/or volumetric estimation to enhance the predictability of segmental parameters of the body for specific population groups characterized by gender, developmental age, body type, and fitness level. Further efforts should be made to establish standardized boundary definitions for trunk segments to avoid unnecessary confusion, from which substantial errors may be introduced into biomechanical linked-segment analyses of human movement.


Magnetic resonance imaging Segmental parameters Mass Center of mass Moment of inertia Trunk Thorax Abdomen Pelvis 


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  1. 1.
    Ackland, T. R., P. W. Henson, and D. A. Bailey. The uniform density assumption: Its effect upon the estimation of body segment inertial parameters.Int. J. sports Biomech. 4:146–155, 1988.Google Scholar
  2. 2.
    Canada Fitness Survey, Fitness and Lifestyle in Canada (third edition). Ottawa: Fitness and Amateur Sport, 1983, pp. 30–33.Google Scholar
  3. 3.
    Chandler, R. F., C. E. Clauser, J. T. McConville, H. M. Reynolds, and J. W. Young. Investigation of inertial properties of the human body. Technical Report (AMRL-TR-74-137), Wright-Patterson Air Force Base, OH, 1975.Google Scholar
  4. 4.
    Clarys, J. P., A. D. Martin, and D. T. Drinkwater. Gross tissue weights in the human body by cadaver dissection.Hum. Biol. 56(3):459–473, 1984.PubMedGoogle Scholar
  5. 5.
    Clarys, J. P., and M. J. Marfell-Jones. Anatomical segmentation in humans and the prediction of segmental masses from intra-segmental anthropometry.Hum. Biol. 58:771–782, 1986.PubMedGoogle Scholar
  6. 6.
    Clauser, C. E., J. T. McConville, and J. W. Young. Weight, volume and center of mass of segments of the human body. Technical Report (AMRL TR-69-70), Wright-Patterson Air Force Base, OH, 1969.Google Scholar
  7. 7.
    Dempster, W. T. Space requirements of the seated operator. WADC Technical Report (TR-55-159), Wright-Patterson Air Force Base, OH, 1955.Google Scholar
  8. 8.
    Erdmann, W. S., and T. Gos. Density of trunk tissues of young and medium age people.J. Biomech. 23:945–947, 1990.CrossRefPubMedGoogle Scholar
  9. 9.
    Forwood, M. R., R. J. Neal, and B. Wilson. Scaling segmental moments of inertia for individual subjects.J. Biomech. 18(10):755–761, 1985.CrossRefPubMedGoogle Scholar
  10. 10.
    Harless, E. Die statischen momente der menschlichen gliedmassen. Abhandlungen der Mathemat.-Physickalichen Classe der Koeniglichen Bayerischen Akademie der Wissenschaften 8:69–96, 257–294, 1860.Google Scholar
  11. 11.
    Hatze, H. A mathematical model for the computational determination of parameter values of anthropomorphic segments.J. Biomech. 13:833–843, 1980.CrossRefPubMedGoogle Scholar
  12. 12.
    Henkelman, R. M., and M. J. Bronskill. Artifacts in magnetic resonance imaging.Rev. Magn. Reson. Imaging 2:1–126, 1987.Google Scholar
  13. 13.
    Henson, P. W., T. Ackland, and R. A. Fox. Tissue density measurement using CT scanning.Austral. Phys. Eng. Sci. Med. 10(3):162–166, 1987.Google Scholar
  14. 14.
    Hinrichs, R. N. Regression equations to predict segmental moments of inertia from anthropometric measurements: An extension of the data of Chandleret al. J. Biomech. 18(8): 621–624, 1985.CrossRefPubMedGoogle Scholar
  15. 15.
    Hinrichs, R. N. Adjustments to the segment center of mass proportions of Clauseret al. (1969).J. Biomech. 23(9):949–951, 1990.CrossRefPubMedGoogle Scholar
  16. 16.
    Huang, H. K., and F. R. Suarez. Evaluation of crosssectional geometry and mass density distributions of humans and laboratory animals using computerized tomography.J. Biomech. 16(10):821–832, 1983.CrossRefPubMedGoogle Scholar
  17. 17.
    Huang, H. K., and S. C. Wu. The evaluation of mass densities of the human body in vivo from CT scans.J. Biomech. 6:337–343, 1976.Google Scholar
  18. 18.
    Jensen, R. K. Changes in segment inertia proportions between four and twenty year.J. Biomech. 22:529–536, 1989.PubMedGoogle Scholar
  19. 19.
    Kohda, E., and N. Shigematsu. Measurement of lung density by computed tomography: Implication for radiotherapy.Keio J. Med. 38(4):454–463, 1989.PubMedGoogle Scholar
  20. 20.
    Martin, P. E., M. Mungiole, M. W. Marzke, and J. M. Longhill. The use of magnetic resonance imaging for measuring segment inertial properties.J. Biomech. 22(4):367–376, 1989.CrossRefPubMedGoogle Scholar
  21. 21.
    Matsuo, A., T. Fukunaga, and S. Uchino. Estimation of volume, density, mass and location of CG by means of MRI method. In: XIIIth International Congress on Biomechanics (abstracts). Perth: University of Western Australia, 1991, pp. 379–380.Google Scholar
  22. 22.
    Mungiole, M., and P. E. Martin. Estimating segment inertial properties: Comparison of magnetic resonance imaging with existing methods.J. Biomech. 23(10):1039–1046, 1990.CrossRefPubMedGoogle Scholar
  23. 23.
    Pearsall, D. J., L. Livingston, and J. G. Reid. Center of mass of trunk segments relative to the spine as determined by computed tomography. In: Second North American Congress on Biomechanics (abstracts), edited by Wells, Draganich, Bechtold. Chicago: American Society of Biomechanics and Canadian Society of Biomechanics, 1992, pp. 77–78.Google Scholar
  24. 24.
    Pearsall, D. J., and J. G. Reid. The study of human body segment parameters in biomechanics: An historical review and current status report.Sports Med. 18(2):126–140, 1994.PubMedGoogle Scholar
  25. 25.
    Plagenhoef, S., F. G. Evans, and T. Abdelnour. Anatomical data for analyzing human motion.Res. Quart. Exercise Sprot 54(2):169–178, 1983.Google Scholar
  26. 26.
    Reid, J. G. Physical properties of the human trunk as determined by computed tomography.Arch. Phys. Med. Rehab. 65:246–250, 1984.Google Scholar
  27. 27.
    Wilkinson, L. Systat. Evanston, IL: Systat, Inc., 1990, pp. 48–65, 146–189.Google Scholar
  28. 28.
    Woodward, H. Q., and D. R. White. The composition of body tissues.Br. J. Radiol. 59:1209–1219, 1986.Google Scholar
  29. 29.
    Yeadon, M. R., and M. Morlock. The appropriate use of regression equations for the estimation of segmental inertia parameters.J. Biomech. 22(6/7):683–689, 1989.PubMedGoogle Scholar
  30. 30.
    Zatsiorsky, V., and V. Seluyanov. The mass and inertial characteristics of the main segments of the human body. In Biomechanics VIII-B, edited by Matsui and Kobayashi. Human Kinetics, Champagne, IL, 1152–1159, 1983.Google Scholar
  31. 31.
    Zatsiorsky, V., and V. Seluyanov. Estimation of the mass and inertia characteristics of the human body by means of the best predictive regression equations. In Biomechanics IX-B, edited by Winters, Norman, Wells, Hayes, Patla. Human Kinetics, Champagne, IL, 233–239, 1985.Google Scholar

Copyright information

© Biomedical Engineering Society 1994

Authors and Affiliations

  • D. J. Pearsall
    • 1
  • J. G. Reid
    • 1
    • 2
  • R. Ross
    • 2
  1. 1.Department of Anatomy and Cell BiologyQueen's UniversityKingstonCanada
  2. 2.School of Physical Health and EducationQueen's UniversityKingstonCanada

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