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Real-Time Control of Quasi-Active Hip Exoskeleton Based on Gaussian Mixture Model Approach

  • Mišel Cevzar
  • Tadej Petrič
  • Marko Jamšek
  • Jan Babič
Conference paper
Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 22)

Abstract

Lower back pain is a major cause of disability and sick day absences. As lower back pain can result in decreased life quality as well as lower industrial productivity, multiple research groups and companies are looking into possible solutions. One of such solutions could be exoskeletons, that engage and disengage the actuators depending on the movements performed by the user. Otherwise we risk hindering the users movements and increasing his metabolic costs. We implemented an exoskeleton control using finite state machine combined with a Gaussian mixture model movement classifier. By conducting a test battery with a subject wearing the exoskeleton we were able to engage the exoskeleton actuators when appropriate and keep them disengaged to allow a full and unhindered range of motion. The results show our exoskeleton control correctly engages and disengages actuators based on the movements being performed by the user.

References

  1. 1.
    Waddell, G., Burton, A.K.: Occupational health guidelines for the management of low back pain at work: evidence review. Occup. Med. 51, 124–135 (2001)CrossRefGoogle Scholar
  2. 2.
    de Rossi, S.M.M., Vitiello, N., Lenzi, T., Ronsse, R., Koopman, B., Persichetti, A., Vecchi, F., Ijspeert, A.J., van der Kooij, H., Carrozza, M.C.: Sensing pressure distribution on a lower-limb exoskeleton physical human-machine interface. Sensors 11(1), 207–227 (2011). http://www.mdpi.com/1424-8220/11/1/207/htmCrossRefGoogle Scholar
  3. 3.
    de Looze, M.P., Bosch, T., Krause, F., Stadler, K.S., O’Sullivan, L.W.: Exoskeletons for industrial application and their potential effects on physical work load. Ergonomics, 1–11 (2015)Google Scholar
  4. 4.
    Yamaguchi, G.T.: Overview of Dynamic Musculoskeletal Modeling, pp. 3–22. Springer, Boston (2001).  https://doi.org/10.1007/978-0-387-28750-8_1CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mišel Cevzar
    • 1
    • 2
  • Tadej Petrič
    • 1
  • Marko Jamšek
    • 1
  • Jan Babič
    • 1
  1. 1.Laboratory of Neuromechanics and Biorobotics, Department for Automation, Biocybernetics and RoboticsJožef Stefan InstituteLjubljanaSlovenia
  2. 2.Jožef Stefan International Postgraduate SchoolLjubljanaSlovenia

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