Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Abhayasinghe, Nimsiri, Murray, Iain, Sharif Bidabadi, Shiva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
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
_version_ 1783397474260484096
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
work_keys_str_mv AT abhayasinghenimsiri validationofthighangleestimationusinginertialmeasurementunitdataagainstopticalmotioncapturesystems
AT murrayiain validationofthighangleestimationusinginertialmeasurementunitdataagainstopticalmotioncapturesystems
AT sharifbidabadishiva validationofthighangleestimationusinginertialmeasurementunitdataagainstopticalmotioncapturesystems