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Related Experiment Video

Updated: Apr 16, 2026

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
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Assessment of Foot Trajectory for Human Gait Phase Detection Using Wireless Ultrasonic Sensor Network.

Yongbin Qi, Cheong Boon Soh, Erry Gunawan

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |March 14, 2015
    PubMed
    Summary

    This study introduces a wearable ultrasonic sensor system for precise gait phase detection, aiding in gait analysis and rehabilitation. The system accurately identifies key walking phases, offering potential for sports and clinical applications.

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    Area of Science:

    • Biomechanics
    • Wearable Technology
    • Sensor Systems

    Background:

    • Gait analysis is crucial for rehabilitation and sports performance.
    • Accurate gait phase detection is essential for effective analysis.
    • Existing methods may have limitations in accuracy or accessibility.

    Purpose of the Study:

    • To develop and validate a highly accurate gait phase detection system using wearable wireless ultrasonic sensors.
    • To assess the system's performance across various walking velocities and subject groups (healthy and injured).
    • To explore the potential clinical applications of the developed system in sports and rehabilitation engineering.

    Main Methods:

    • Utilized foot-mounted ultrasonic sensors and passive anchors for local spherical positioning.
    • Employed a combination of recursive Newton-Gauss method and Kalman Filter to enhance displacement accuracy.
    • Validated the system against a commercial optical motion tracking system with ten healthy and two injured subjects.

    Main Results:

    • Achieved accurate gait cycle estimation with minimal error (-0.02 ±0.01 s).
    • Demonstrated high accuracy in stance (0.04±0.03 s) and swing phase (-0.05±0.03 s) detection.
    • Found no significant difference in performance across varying walking velocities for both systems.

    Conclusions:

    • The proposed wearable ultrasonic sensor system provides highly accurate gait phase detection.
    • The system shows robust performance across different walking speeds and subject conditions.
    • Estimated gait phases hold significant potential as indicators for sports and rehabilitation engineering applications.