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Development of an IMU-based foot-ground contact detection (FGCD) algorithm.

Myeongkyu Kim1, Donghun Lee1

  • 1a School of Mechanical Engineering , Soongsil University , Seoul , Republic of Korea.

Ergonomics
|April 13, 2016
PubMed
Summary

This study developed an Inertial Measurement Unit (IMU)-based algorithm for foot-ground contact detection (FGCD). The algorithm accurately identifies four distinct foot-ground contact phases across various terrains and speeds without extra sensors.

Keywords:
Foot-ground contactIMUdetection criteriongait analysiswalking speedwalking terrains

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Area of Science:

  • Biomechanics
  • Sensor Technology
  • Human Locomotion Analysis

Background:

  • Accurate human localization in GPS-denied environments often relies on lower limb kinematics.
  • Traditional methods utilize Inertial Measurement Units (IMUs), force plates, and pressure insoles for foot-ground contact detection.
  • Minimizing sensor count is crucial for practical applications.

Purpose of the Study:

  • To develop a robust foot-ground contact detection (FGCD) algorithm using only IMU data.
  • To ensure the algorithm's effectiveness across diverse walking terrains and speeds.
  • To validate the performance of the proposed IMU-based FGCD algorithm.

Main Methods:

  • Experiments were conducted across five different walking terrains.
  • IMU data was analyzed to identify significant output changes during foot-ground contact phases.
  • Walking speeds were varied on each terrain to assess their correlation with FGCD parameters.

Main Results:

  • An IMU-based FGCD algorithm successfully identifying four distinct contact phases was developed.
  • The algorithm demonstrated independence from variations in walking speed.
  • Performance validation confirmed the algorithm's effectiveness across different terrains.

Conclusions:

  • The developed IMU-based FGCD algorithm reliably detects four key foot-ground contact phases: Heel strike/Toe strike, Full contact, Heel off, and Toe off.
  • Detection accuracy is maintained irrespective of walking speed and terrain.
  • This offers a simplified, sensor-efficient solution for lower limb kinematic analysis.