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Position Tracking During Human Walking Using an Integrated Wearable Sensing System

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 con...

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Detalles Bibliográficos
Autores principales: Zizzo, Giulio, Ren, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751554/
https://www.ncbi.nlm.nih.gov/pubmed/29232869
http://dx.doi.org/10.3390/s17122866
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author Zizzo, Giulio
Ren, Lei
author_facet Zizzo, Giulio
Ren, Lei
author_sort Zizzo, Giulio
collection PubMed
description 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.
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spelling pubmed-57515542018-01-10 Position Tracking During Human Walking Using an Integrated Wearable Sensing System Zizzo, Giulio Ren, Lei Sensors (Basel) Article 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. MDPI 2017-12-10 /pmc/articles/PMC5751554/ /pubmed/29232869 http://dx.doi.org/10.3390/s17122866 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zizzo, Giulio
Ren, Lei
Position Tracking During Human Walking Using an Integrated Wearable Sensing System
title Position Tracking During Human Walking Using an Integrated Wearable Sensing System
title_full Position Tracking During Human Walking Using an Integrated Wearable Sensing System
title_fullStr Position Tracking During Human Walking Using an Integrated Wearable Sensing System
title_full_unstemmed Position Tracking During Human Walking Using an Integrated Wearable Sensing System
title_short Position Tracking During Human Walking Using an Integrated Wearable Sensing System
title_sort position tracking during human walking using an integrated wearable sensing system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751554/
https://www.ncbi.nlm.nih.gov/pubmed/29232869
http://dx.doi.org/10.3390/s17122866
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