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A multi-segment modelling approach for foot trajectory estimation using inertial sensors.

Nikiforos Okkalidis1, George Marinakis2, Alfred Gatt3

  • 1Centre for Biomedical Cybernetics, University of Malta, Msida, MSD, 2080, Malta.

Gait & Posture
|October 8, 2019
PubMed
Summary

This study introduces a new method using multiple inertial measurement units (IMUs) for foot motion analysis, improving trajectory estimation and foot clearance accuracy. This approach offers a practical alternative to traditional lab-based systems for real-world gait analysis.

Keywords:
Foot clearanceInertial sensorsKinematic gait analysisMulti-segment analysis

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Area of Science:

  • Biomechanics
  • Human motion analysis
  • Wearable sensor technology

Background:

  • Kinematic gait analysis traditionally relies on optical motion capture systems in laboratory settings.
  • These systems are limited by setup time and restricted capture spaces.
  • A novel procedure using multiple inertial measurement units (IMUs) is proposed to overcome these limitations.

Purpose of the Study:

  • To present a new approach for estimating multi-segment foot model trajectories using multiple IMUs.
  • To evaluate the performance of this novel method against conventional IMU techniques and optical motion capture.

Main Methods:

  • A system with four IMUs was attached to the shank, heel, dorsum, and toes segments.
  • The proposed IMU-based method was compared with a conventional IMU approach.
  • An optical motion capture system served as the reference standard for performance assessment.

Main Results:

  • The proposed method reduced trajectory errors by 8-55% for shank, heel, and dorsum segments, and the Z-axis of the toes segment.
  • An increase in error (17-26%) was observed for the X and Y axes of the toes segment.
  • Estimation of vertical foot displacement (foot clearance) improved across all segments, with mean accuracies between 0.8 ± 0.7 cm and 3.5 ± 2.8 cm.

Conclusions:

  • Fusing multiple IMU measurements via kinematic equations significantly enhances estimated trajectories, particularly vertical foot displacements.
  • This method offers a cost-effective and practical alternative to existing techniques for real-life gait analysis.
  • The proposed approach demonstrates comparable performance to established methods, making it attractive for broader applications.