position tracking during human walking using an integrated wearable sensing system

Clicks: 298
ID: 168031
2017
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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.
Reference Key
zizzo2017sensorsposition Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Giulio Zizzo, Lei Ren
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Journal ekonomiczne problemy usług
Year 2017
DOI
10.3390/s17122866
URL
https://www.mdpi.com/1424-8220/17/12/2866
Keywords
kalman filter wearable sensors pedestrian dead reckoning

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