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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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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. |
format | Online Article Text |
id | pubmed-5751554 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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