An Experimental Method to Estimate Upper Limbs Inertial Parameters During Handcycling

in Journal of Applied Biomechanics
View More View Less
  • 1 University of Brescia
  • 2 Casa di Cura Domus Salutis
Restricted access

Purchase article

USD  $24.95

Student 1 year online subscription

USD  $88.00

1 year online subscription

USD  $118.00

Student 2 year online subscription

USD  $168.00

2 year online subscription

USD  $224.00

This study proposes an experimental method to estimate personalized inertial parameters of upper limbs during handcycling by using a planar dynamic model. The handle forces are expressed as a product of a matrix describing the kinematics terms and a vector of inertial parameters of arm and forearm. The parameters are estimated by measuring the handle forces during a suitable “passive test” and inverting the mentioned matrix. The data were acquired while an operator actuated the handle and the subject’s muscles were relaxed. To validate the estimation procedure, it was applied to a custom-made artificial arm mechanism, and the results were compared with its known parameters. The method was then used to estimate the inertial parameters of 6 human subjects. The estimated parameters were used to compute the exchanged forces and compared with the measured ones obtaining an average error of 14% both for Fx and Fy. These errors are significantly smaller than those obtained using dynamic parameters extracted from the literature to compute the forces, which were 50% for Fx and 19% for Fy. An individual evaluation of inertial parameters better describes interaction forces during handcycling, especially for subjects whose body structures are different from the average population.

Azizpour, Lancini, Incerti, and Legnani are with the Department of Mechanical and Industrial Engineering (DIMI), University of Brescia, Brescia, Italy. Gaffurini is with LARIN: Neuromuscular and Adapted Physical Activity Laboratory, Rehabilitation Service, Casa di Cura Domus Salutis, Brescia, Italy.

Azizpour (g.azizpour@unibs.it) is corresponding author.
  • 1.

    Nigg BM, Herzog W. Biomechanics of the Musculo-Skeletal System. Chichester, England: John Wiley & Sons; 2007.

  • 2.

    Winter DA. Biomechanics and Motor Control of Human Movement. Vol 2. New York, NY: Wiley; 2009. doi:10.1002/9780470549148

  • 3.

    Kodek T, Munih M. An identification technique for evaluating body segment parameters in the upper extremity from manipulator-hand contact forces and arm kinematics. JCLB Clin Biomech. 2006;21(7):710716. doi:10.1016/j.clinbiomech.2006.02.006

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4.

    Martin PE, Mungiole M, Marzke MW, Longhill JM. The use of magnetic resonance imaging for measuring segment inertial properties. J Biomech. 1989;22(4):367376. doi:10.1016/0021-9290(89)90051-1

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    De Leva P. Adjustments to Zatsiorsky–Seluyanov’s segment inertia parameters. J Biomech. 1996;29(9):12231230. doi:10.1016/0021-9290(95)00178-6

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Huang HK, Suarez FR. Evaluation of cross-sectional geometry and mass density distributions of humans and laboratory animals using computerized tomography. J Biomech. 1983;16(10):821832. doi:10.1016/0021-9290(83)90006-4

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Zatsiorski V. In vivo body segment inertial parameters determination using gamma-scanner method. In: Berme N, Cappozzo A, eds. Biomechanics of Human Movement: Applications in Rehabilitation, Sports and Ergonomics. Worthington, OH: Bertec Corporation; 1990:186202.

    • Search Google Scholar
    • Export Citation
  • 8.

    Chandler RF. Investigation of Inertial Properties of the Human Body : Final Report. Washington, DC/Springfield, VA: National Highway Traffic Safety Administration; Available through the National Technical Information Service; 1975.

    • Search Google Scholar
    • Export Citation
  • 9.

    Armstrong HG, Haley J. Anthropometry and Mass Distribution for Human Analogues. Volume I: Military Aviators. Final Report. New Orleans, LA: Naval Biodynamics Laboratory; 1988.

    • Search Google Scholar
    • Export Citation
  • 10.

    Clauser CE, McConville JT, Young JW. Weight, Volume, and Center of Mass of Segments of the Human Body; Wright-Patterson Air Force Base, Ohio: Aerospace Medical Research Laboratory; 1970.

    • Search Google Scholar
    • Export Citation
  • 11.

    Xu Y, Hollerbach JM. A robust ensemble data method for identification of human joint mechanical properties during movement. IEEE Trans Biomed Eng. 1999;46(4):409419. doi:10.1109/10.752938

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Xu Y, Hollerbach JM. Identification of human joint mechanical properties from single trial data. IEEE Trans Biomed Eng. 1998;45(8):10511060. PubMed ID: 9691580 doi:10.1109/10.704874

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Kodek T. An identification technique for evaluating static body segment parameters in the upper extremity. Clin Biomech. 2004;21(April):47474752.

    • Search Google Scholar
    • Export Citation
  • 14.

    Kodek T, Munih M. An analysis of static and dynamic joint torques in elbow flexion–extension movements. Simul Model Pract Theor. 2003;11(3–4):297311. doi:10.1016/S1569-190X(03)00063-7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Valent LJ, Dallmeijer AJ, Houdijk H, Slootman HJ, Post MW, van der Woude LH. Influence of hand cycling on physical capacity in the rehabilitation of persons with a spinal cord injury: a longitudinal cohort study. Arch Phys Med Rehabil. 2008;89(6):10161022. PubMed ID: 18503794 doi:10.1016/j.apmr.2007.10.034

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Faupin A, Gorce P, Meyer C. Effects of type and mode of propulsion on hand-cycling biomechanics in nondisabled subjects. J Rehabil Res Dev. 2011;48(9):10491060. PubMed ID: 22234710 doi:10.1682/JRRD.2010.19.0199

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Mukherjee G, Samanta A. Physiological response to the ambulatory performance of hand-rim and arm-crank propulsion systems. J Rehabil Res Dev. 2001;38(4):391399. PubMed ID: 11563492

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Arnet U, Drongelen S, Scheel-Sailer A, Woude L, Veeger D. Shoulder load during synchronous handcycling and handrim wheelchair propulsion in persons with paraplegia. J Rehabil Med. 2012;44(3):222228. PubMed ID: 22367531 doi:10.2340/16501977-0929

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Arnet U, Van Drongelen S, Veeger DJ, van der Woude LHV. Force application during handcycling and handrim wheelchair propulsion: an initial comparison. J Appl Biomech. 2013;29(6):687695. PubMed ID: 23343659 doi:10.1123/jab.29.6.687

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Goosey-Tolfrey VL, Alfano H, Fowler N. The influence of crank length and cadence on mechanical efficiency in hand cycling. Eur J Appl Physiol. 2008;102(2):189194. PubMed ID: 17909841 doi:10.1007/s00421-007-0576-7

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Abel T, Burkett B, Thees B, Schneider S, Askew CD, Struder HK. Effect of three different grip angles on physiological parameters during laboratory handcycling test in able-bodied participants. Front Physiol. 2015;6:331. doi:10.3389/fphys.2015.00331

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Arnet U, van Drongelen S, Schlüssel M, Lay V, van der Woude LH, Veeger HEJ. The effect of crank position and backrest inclination on shoulder load and mechanical efficiency during handcycling. Scand J Med Sci Sports. 2014;24(2):386394. doi:10.1111/j.1600-0838.2012.01524.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    van Drongelen S, van den Berg J, Arnet U, Veeger DJ, van der Woude LH. Development and validity of an instrumented handbike: initial results of propulsion kinetics. Med Eng Phys. 2011;33(9):11671173. PubMed ID: 21636309 doi:10.1016/j.medengphy.2011.04.018

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24.

    Jacquier-Bret J, Faupin A, Rezzoug N, Gorce P. A new postural force production index to assess propulsion effectiveness during handcycling. J Appl Biomech. 2013;29(6):798803. doi:10.1123/jab.29.6.798

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Azizpour G, Ousdad A, Legnani G, Incerti G, Lancini M, Gaffurini P. Dynamic analysis of handcycling: mathematical modelling and experimental tests. In: Boschetti G, Gasparetto A, eds. Mechanisms and Machine Science. Vol 47. Vicenza, Italy: Springer International Publishing; 2017:3340. doi:10.1007/978-3-319-48375-7_4

    • Search Google Scholar
    • Export Citation
  • 26.

    Villagrossi E, Legnani G, Pedrocchi N, et al. Robot dynamic model identification through excitation trajectories minimizing the correlation influence among essential parameters. Paper presented at: 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO); September 1–3, 2014; Vienna, Austria. doi:10.5220/0005060704750482

    • Search Google Scholar
    • Export Citation
  • 27.

    Asadi Nikooyan A, Veeger HEJ, Chadwick EKJ, et al. Development of a comprehensive musculoskeletal model of the shoulder and elbow. Med Biol Eng Comput. 2011;49:14251435. doi:10.1007/s11517-011-0839-7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28.

    van der Helm FC. Analysis of the kinematic and dynamic behavior of the shoulder mechanism. J Biomech. 1994;27(5):527550. PubMed ID: 8027089 doi:10.1016/0021-9290(94)90064-7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29.

    Zadravec M, Matjačić Z. Planar arm movement trajectory formation: an optimization based simulation study. Biocybern Biomed Eng. 2013;33(2):106117. doi:10.1016/j.bbe.2013.03.006

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30.

    Stefanescu DM. Handbook of Force Transducers: Principles and Components. Heidelberg, Germany: Springer Science & Business Media; 2011.

  • 31.

    Ometto M. Strumentazione Di Una Handbike Per Misure Biomeccaniche. [Master thesis (in Italian)]. Brescia, Italy: Università degli Studi di Brescia; 2008.

    • Search Google Scholar
    • Export Citation
  • 32.

    Ometto M, Sistemi E. Modelli Per La Biomeccanica Del Corpo Umano. [PhD Thesis (in Italian)]. Brescia, Italy: Università degli Studi di Brescia; 2012.

    • Search Google Scholar
    • Export Citation
  • 33.

    Pasinetti S, Lancini M, Bodini I, Docchio F. A novel algorithm for EMG signal processing and muscle timing measurement. IEEE Trans Instrum Meas. 2015;64(11):29953004. doi:10.1109/TIM.2015.2434097

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34.

    Veeger HEJ, Yu B, An KN, Rozendal RH. Parameters for modeling the upper extremity. J Biomech. 1997;30(6):647652. doi:10.1016/S0021-9290(97)00011-0

All Time Past Year Past 30 Days
Abstract Views 179 116 5
Full Text Views 4 1 0
PDF Downloads 2 0 0