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Medical & Biological Engineering & Computing

, Volume 46, Issue 1, pp 43–53 | Cite as

Immediate effects of a controllable knee ankle foot orthosis for functional compensation of gait in patients with proximal leg weakness

  • Juan C. MorenoEmail author
  • Fernando Brunetti
  • Eduardo Rocon
  • José L. Pons
Original Article

Abstract

Application of intermittent control of the knee joint stiffness in a knee ankle foot orthosis (KAFO) during gait is proposed. The approach combines inertial sensors and an actuator system in order to apply compensation in quadriceps weakness with a wearable device. Two methods, segment-angular rotation based and segment-angular velocity based, are analysed for the control of the knee joint state (intermittent stiffness) based on the inertial sensors signals. Protocolled tests are developed with two post-polio syndrome patients (PPS). In this study, the cases of gait with free-swinging leg and safe stance with the orthotic system are presented in terms of quantified kinematics (average peak angle of knee flexion of 50°) and evidences of reduction of frequent compensations (e.g. leg lateral movement) in post-polio syndrome patients. The results from immediate inspection indicate an important improvement of the gait patterns in two patients with proximal leg weakness by means of compensations applied by the wearable orthosis.

Keywords

Inertial sensing KAFO Gait Actuator Joints disorders 

Notes

Acknowledgments

The authors would like to thank L. Bueno for his work and assistance in the development of the control architecture and J. Baydal, W. de Vries and V. Erren, for their enormous contributions in testing and experimentation. The work presented in this paper has been partially founded through grant IST-2001-37751 of the European Commission.

References

  1. 1.
    Baten C et al (2004) Use of inertial sensing in an intelligent orthosis. A feasibility study, presented at the Esmac Conference. Warswaw, PolandGoogle Scholar
  2. 2.
    Baydal JM et al (2006) Performance validation of an innovative orthotic knee joint based on an optimal four bar linkage. Orthopadie-Technik Quarterly 2:6–11Google Scholar
  3. 3.
    Blaya J, Herr H (2004) Adaptive control of a variable-impedance anklefoot orthosis to assist drop foot gait. IEEE Trans Neural Syst Rehabil Eng 12:24–31CrossRefGoogle Scholar
  4. 4.
    Ferris D et al (2006) An improved powered ankle foot orthosis using proportional myoelectric control. Gait Posture 23:425–428CrossRefGoogle Scholar
  5. 5.
    Franken HM (1995) Cycle to cycle control of swing phase of paraplegic gait induced by surface electrical stimulation. Med Biol Eng Comput 33:440–451CrossRefGoogle Scholar
  6. 6.
    Gharooni S, Heller B, Tokhi M (2000) A new hybrid spring brake orthosis for controlling hip and knee flexion in the swing phase. IEEE Trans Rehabil Eng 9:106–107Google Scholar
  7. 7.
    Goldfarb M, Durfee WK (1996) Design of a controlled-brake orthosis for FES-aided gait. IEEE Trans Rehabil Eng 4:13–24CrossRefGoogle Scholar
  8. 8.
    Hornby T, Zemon D, Campbell D (2005) Robotic-assisted, body-weight-supported treadmill training in individuals following motor incomplete spinal cord injury. Phys Ther 85:52–66Google Scholar
  9. 9.
    Irby S, et al (1999) Optimization and application of a wrap-spring clutch to a dynamic knee-ankle-foot orthosis. IEEE Trans Rehabil Eng 7:130–134CrossRefGoogle Scholar
  10. 10.
    Kameyama O, Suga T (1998) Newly designed computer controlled knee-ankle-foot orthosis. Prosthet Orthot Int 22:230–239Google Scholar
  11. 11.
    Kaufman KR, Irby SE, Mathewson J, Wirta RW, Sutherland DH (2006) Energy-efficient knee-ankle foot orthosis: a case study. J Prosthet Orthot 8(3):79–85CrossRefGoogle Scholar
  12. 12.
    Kazerooni H, Steger R, Huang L (2003) Hybrid control of the berkeley lower extremity exoskeleton. Int J Robotics Res 25(5–6):561–573Google Scholar
  13. 13.
    Kazerooni H, Steger R, Huang L (2003) Hybrid control of the Berkeley lower extremity exoskeleton. Int J Robotics Res 25:561–573Google Scholar
  14. 14.
    Kirtley C (2003) Automated diagnosis of gait abnormalities. Presented at biomechanics of the lower limb in health, disease and rehabilitation, ManchesterGoogle Scholar
  15. 15.
    Luinge HJ, Veltink PH (2005) Measuring orientation of human body segments using miniature gyroscopes and accelerometers. Med Biol Eng Comput 43(2):273–282CrossRefGoogle Scholar
  16. 16.
    Meijer K, Moreno JC, Savelberg H (2005) Biomimetics—biologically inspired technologies. Chapter 2: biological mechanisms as models for mimicking—sarcomere design, arrangement and muscle function. CRC, Boca RatonGoogle Scholar
  17. 17.
    Moreno JC et al (2006) Simulation Of knee function during gait with an orthosis by means of two springs of different stifnesses. Gait Posture 21:S140CrossRefGoogle Scholar
  18. 18.
    Moreno JC et al (2006) Design and implementation of an inertial measurement unit for control of artificial limbs: application on leg orthoses. Sens Actuators B Chem 118:333–337CrossRefMathSciNetGoogle Scholar
  19. 19.
    Perry J (1999) Gait analysis: normal and pathological function, McGraw-Hill IncGoogle Scholar
  20. 20.
    Veltink PH et al (1996) Detection of static and dynamic activities using uniaxial accelerometers. IEEE Trans Neural Syst Rehabil Eng 4:375–385CrossRefGoogle Scholar
  21. 21.
    Williamson R, Andrews BJ (2001) Detecting absolute human knee angle and angular velocity using accelerometers and rate gyroscopes. Med Biol Eng Comput 39(3):294–302CrossRefGoogle Scholar
  22. 22.
    Winter D (1991) The biomechanics and motor control of human movement. University of WaterlooGoogle Scholar
  23. 23.
    Yakimovich T, Kofman J, Lemaire ED (2006) Design and evaluation of a stance-control knee-ankle-foot orthosis knee joint. IEEE Trans Neural Syst Rehabil Eng 14(3):361–369CrossRefGoogle Scholar

Copyright information

© International Federation for Medical and Biological Engineering 2007

Authors and Affiliations

  • Juan C. Moreno
    • 1
    Email author
  • Fernando Brunetti
    • 1
  • Eduardo Rocon
    • 1
  • José L. Pons
    • 1
  1. 1.Bioengineering GroupIndustrial Automation Institute of the Spanish National Research Council, CSICMadridSpain

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