Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sens...

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Main Authors: Elena Bergamini, Gabriele Ligorio, Aurora Summa, Giuseppe Vannozzi, Aurelio Cappozzo, Angelo Maria Sabatini
Format: Article
Language:English
Published: MDPI AG 2014-10-01
Series:Sensors
Subjects:
IMU
Online Access:http://www.mdpi.com/1424-8220/14/10/18625
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spelling doaj-228362d7b59749f5bf34e365cf44d0282020-11-25T02:16:04ZengMDPI AGSensors1424-82202014-10-011410186251864910.3390/s141018625s141018625Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion TasksElena Bergamini0Gabriele Ligorio1Aurora Summa2Giuseppe Vannozzi3Aurelio Cappozzo4Angelo Maria Sabatini5Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", P.zza Lauro de Bosis 15, 00135 Roma, ItalyThe BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56124 Pisa, ItalyInteruniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", P.zza Lauro de Bosis 15, 00135 Roma, ItalyInteruniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", P.zza Lauro de Bosis 15, 00135 Roma, ItalyInteruniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", P.zza Lauro de Bosis 15, 00135 Roma, ItalyThe BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56124 Pisa, ItalyMagnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.http://www.mdpi.com/1424-8220/14/10/186253-D orientationaccuracywearable sensorsIMUMIMUKalman filteringgaitupper bodybiomechanicshuman
collection DOAJ
language English
format Article
sources DOAJ
author Elena Bergamini
Gabriele Ligorio
Aurora Summa
Giuseppe Vannozzi
Aurelio Cappozzo
Angelo Maria Sabatini
spellingShingle Elena Bergamini
Gabriele Ligorio
Aurora Summa
Giuseppe Vannozzi
Aurelio Cappozzo
Angelo Maria Sabatini
Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks
Sensors
3-D orientation
accuracy
wearable sensors
IMU
MIMU
Kalman filtering
gait
upper body
biomechanics
human
author_facet Elena Bergamini
Gabriele Ligorio
Aurora Summa
Giuseppe Vannozzi
Aurelio Cappozzo
Angelo Maria Sabatini
author_sort Elena Bergamini
title Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks
title_short Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks
title_full Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks
title_fullStr Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks
title_full_unstemmed Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks
title_sort estimating orientation using magnetic and inertial sensors and different sensor fusion approaches: accuracy assessment in manual and locomotion tasks
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2014-10-01
description Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.
topic 3-D orientation
accuracy
wearable sensors
IMU
MIMU
Kalman filtering
gait
upper body
biomechanics
human
url http://www.mdpi.com/1424-8220/14/10/18625
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