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Improved method of step length estimation based on inverted pendulum model

Author

Listed:
  • Qi Zhao
  • Boxue Zhang
  • Jingjing Wang
  • Wenquan Feng
  • Wenyan Jia
  • Mingui Sun

Abstract

Step length estimation is an important issue in areas such as gait analysis, sport training, or pedestrian localization. In this article, we estimate the step length of walking using a waist-worn wearable computer named eButton. Motion sensors within this device are used to record body movement from the trunk instead of extremities. Two signal-processing techniques are applied to our algorithm design. The direction cosine matrix transforms vertical acceleration from the device coordinates to the topocentric coordinates. The empirical mode decomposition is used to remove the zero- and first-order skew effects resulting from an integration process. Our experimental results show that our algorithm performs well in step length estimation. The effectiveness of the direction cosine matrix algorithm is improved from 1.69% to 3.56% while the walking speed increased.

Suggested Citation

  • Qi Zhao & Boxue Zhang & Jingjing Wang & Wenquan Feng & Wenyan Jia & Mingui Sun, 2017. "Improved method of step length estimation based on inverted pendulum model," International Journal of Distributed Sensor Networks, , vol. 13(4), pages 15501477177, April.
    • Handle: RePEc:sae:intdis:v:13:y:2017:i:4:p:1550147717702914
    DOI: 10.1177/1550147717702914
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