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Home-Based Monitor for Gait and Activity Analysis
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Physical sensor difference-based method and virtual sensor difference-based method for visual and quantitative

Kun Liu1, Yoshio Inoue, Kyoko Shibata

  • 1Department of Intelligent Mechanical Systems Engineering, Kochi University of Technology, 185 Miyanokuchi, Tosayamada-cho, Kochi 782-8502, Japan. mikylk@hotmail.com

Computer Methods in Biomechanics and Biomedical Engineering
|December 4, 2010
PubMed
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This study introduces a novel sensor-based algorithm for accurately measuring lower limb joint angles and trajectories. The method demonstrates high correlation with motion capture systems, offering a promising advancement in biomechanical analysis.

Area of Science:

  • Biomechanics
  • Wearable Technology
  • Sensor Fusion

Background:

  • Accurate assessment of lower limb posture is crucial for clinical diagnosis and rehabilitation.
  • Existing motion capture systems can be cumbersome and expensive.
  • Previous sensor-based methods often integrated acceleration or angular velocity, leading to accumulated errors.

Purpose of the Study:

  • To propose and validate a novel sensor-based algorithm for quantitative lower limb posture analysis.
  • To improve upon existing methods by avoiding integration of acceleration or angular velocity.
  • To achieve high accuracy comparable to camera-based motion capture systems.

Main Methods:

  • Utilized three accelerometers and two inertial sensor modules (MAG3) to collect motion data.

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  • Developed physical and virtual sensor difference-based algorithms to calculate hip and knee joint angles (flexion/extension, abduction/adduction, internal/external rotation).
  • Reconstructed knee and ankle joint trajectories using calculated joint angles and segment lengths.

    • Main Results:

    • Achieved high correlation coefficients (above 0.91 for hip, above 0.93 for knee) compared to a camera motion capture system.
    • Demonstrated accurate calculation of hip and knee joint angles, including internal/external rotation of the knee.
    • Successfully obtained knee and ankle joint trajectories without integrating acceleration or angular velocity.

    Conclusions:

    • The proposed sensor-based algorithm provides a non-invasive and accurate method for lower limb posture assessment.
    • This approach offers a significant improvement over previous sensor-based techniques by avoiding error accumulation.
    • The high correlation with motion capture suggests potential for clinical and research applications in biomechanics.