Human Gait Feature Detection Using Inertial Sensors Wavelets

Conference paper
Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 16)

Abstract

The human gait analysis by using wavelets transform of signal obtained from six inertial ProMove mini sensors is proposed in this work. The angular velocity data measured by the gyro sensors is used to estimate the translational acceleration in the gait analysis. As a result, the flexion–extension, the adduction–abduction joint angles of the hips, flexion–extension of the knees and dorsi and plantar flexion of the ankle are calculated. After measurements we propose to use one of wavelet transform (wavelet type) in order to analyze the signals, indicate a characteristic feature and compare them.

References

  1. 1.
    Glowinski, S., Krzyzynski, T., Pecolt, S., Maciejewski, I.: Design of motion trajectory of an arm exoskeleton. Arch. Appl. Mech. 85, 75–87 (2015)CrossRefGoogle Scholar
  2. 2.
    Glowinski, S., Krzyzynski, T.: An Inverse Kinematic Algorithm for Human leg. J. Theor. Appl. Mech. 54(1), 53–61 (2016)CrossRefGoogle Scholar
  3. 3.
    Chen, X.: Human Motion Analysis with Wearable Inertial Sensors. University of Tennessee, Knoxville, Doctoral Dissertation (2013)Google Scholar
  4. 4.
    Zhu, R., Zhou, Z.A.: A real-time articulated human motion tracking using tri-axis inertial/magnetic sensors package. IEEE Trans. Neural Syst. Rehabil. Eng. 12, 295–302 (2004)CrossRefGoogle Scholar
  5. 5.
    ProMove wireless inertial sensing platform. http://www.inertia-technology.com/promove-mini
  6. 6.
    Mallat, S.: A Wavelet Tour of Signal Processing. Academic Press, San Diego, CA (1998)MATHGoogle Scholar
  7. 7.
    Torrence, C., Compo, G.P.: A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79, 61–78 (1998)CrossRefGoogle Scholar
  8. 8.
    Daubechies, I.: Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics (SIAM), Philadelphia (1992)CrossRefMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Koszalin University of TechnologyKoszalinPoland

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