Position Tracking During Human Walking Using an Integrated Wearable Sensing System

Giulio Zizzo, Lei Ren

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Progress has been made enabling expensive, high-end inertial measurement units (IMUs) to be used as tracking sensors. However, the cost of these IMUs is prohibitive to their widespread use, and hence the potential of low-cost IMUs is investigated in this study. A wearable low-cost sensing system consisting of IMUs and ultrasound sensors was developed. Core to this system is an extended Kalman filter (EKF), which provides both zero-velocity updates (ZUPTs) and Heuristic Drift Reduction (HDR). The IMU data was combined with ultrasound range measurements to improve accuracy. When a map of the environment was available, a particle filter was used to impose constraints on the possible user motions. The system was therefore composed of three subsystems: IMUs, ultrasound sensors, and a particle filter. A Vicon motion capture system was used to provide ground truth information, enabling validation of the sensing system. Using only the IMU, the system showed loop misclosure errors of 1% with a maximum error of 4–5% during walking. The addition of the ultrasound sensors resulted in a 15% reduction in the total accumulated error. Lastly, the particle filter was capable of providing noticeable corrections, which could keep the tracking error below 2% after the first few steps.
    Original languageEnglish
    Article number2866
    JournalSensors
    Volume17
    Issue number12
    DOIs
    Publication statusPublished - 10 Dec 2017

    Keywords

    • Kalman filter
    • pedestrian dead reckoning
    • wearable sensors
    • IMU navigation

    Research Beacons, Institutes and Platforms

    • Manchester Institute for Collaborative Research on Ageing

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