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Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems
Inertial measurement units are commonly used to estimate the orientation of sections of sections of human body in inertial navigation systems. Most of the algorithms used for orientation estimation are computationally expensive and it is difficult to implement them in real-time embedded systems with...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387008/ https://www.ncbi.nlm.nih.gov/pubmed/30708957 http://dx.doi.org/10.3390/s19030596 |
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author | Abhayasinghe, Nimsiri Murray, Iain Sharif Bidabadi, Shiva |
author_facet | Abhayasinghe, Nimsiri Murray, Iain Sharif Bidabadi, Shiva |
author_sort | Abhayasinghe, Nimsiri |
collection | PubMed |
description | Inertial measurement units are commonly used to estimate the orientation of sections of sections of human body in inertial navigation systems. Most of the algorithms used for orientation estimation are computationally expensive and it is difficult to implement them in real-time embedded systems with restricted capabilities. This paper discusses a computationally inexpensive orientation estimation algorithm (Gyro Integration-Based Orientation Filter—GIOF) that is used to estimate the forward and backward swing angle of the thigh (thigh angle) for a vision impaired navigation aid. The algorithm fuses the accelerometer and gyroscope readings to derive the single dimension orientation in such a way that the orientation is corrected using the accelerometer reading when it reads gravity only or otherwise integrate the gyro reading to estimate the orientation. This strategy was used to reduce the drift caused by the gyro integration. The thigh angle estimated by GIOF was compared against the Vicon Optical Motion Capture System and reported a mean correlation of 99.58% for 374 walking trials with a standard deviation of 0.34%. The Root Mean Square Error (RMSE) of the thigh angle estimated by GIOF compared with Vicon measurement was 1.8477°. The computation time on an 8-bit microcontroller running at 8 MHz for GIOF is about a half of that of Complementary Filter implementation. Although GIOF was only implemented and tested for estimating pitch of the IMU, it can be easily extended into 2D to estimate both pitch and roll. |
format | Online Article Text |
id | pubmed-6387008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63870082019-02-26 Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems Abhayasinghe, Nimsiri Murray, Iain Sharif Bidabadi, Shiva Sensors (Basel) Article Inertial measurement units are commonly used to estimate the orientation of sections of sections of human body in inertial navigation systems. Most of the algorithms used for orientation estimation are computationally expensive and it is difficult to implement them in real-time embedded systems with restricted capabilities. This paper discusses a computationally inexpensive orientation estimation algorithm (Gyro Integration-Based Orientation Filter—GIOF) that is used to estimate the forward and backward swing angle of the thigh (thigh angle) for a vision impaired navigation aid. The algorithm fuses the accelerometer and gyroscope readings to derive the single dimension orientation in such a way that the orientation is corrected using the accelerometer reading when it reads gravity only or otherwise integrate the gyro reading to estimate the orientation. This strategy was used to reduce the drift caused by the gyro integration. The thigh angle estimated by GIOF was compared against the Vicon Optical Motion Capture System and reported a mean correlation of 99.58% for 374 walking trials with a standard deviation of 0.34%. The Root Mean Square Error (RMSE) of the thigh angle estimated by GIOF compared with Vicon measurement was 1.8477°. The computation time on an 8-bit microcontroller running at 8 MHz for GIOF is about a half of that of Complementary Filter implementation. Although GIOF was only implemented and tested for estimating pitch of the IMU, it can be easily extended into 2D to estimate both pitch and roll. MDPI 2019-01-31 /pmc/articles/PMC6387008/ /pubmed/30708957 http://dx.doi.org/10.3390/s19030596 Text en © 2019 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 Abhayasinghe, Nimsiri Murray, Iain Sharif Bidabadi, Shiva Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems |
title | Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems |
title_full | Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems |
title_fullStr | Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems |
title_full_unstemmed | Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems |
title_short | Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems |
title_sort | validation of thigh angle estimation using inertial measurement unit data against optical motion capture systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387008/ https://www.ncbi.nlm.nih.gov/pubmed/30708957 http://dx.doi.org/10.3390/s19030596 |
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