How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy
In human movement analysis, 3D body segment orientation can be obtained through the numerical integration of gyroscope signals. These signals, however, are affected by errors that, for the case of micro-electro-mechanical systems, are mainly due to: constant bias, scale factor, white noise, and bias...
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MDPI AG
2015-09-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/15/9/23983 |
| _version_ | 1797999871617138688 |
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| author | Ilaria Pasciuto Gabriele Ligorio Elena Bergamini Giuseppe Vannozzi Angelo Maria Sabatini Aurelio Cappozzo |
| author_facet | Ilaria Pasciuto Gabriele Ligorio Elena Bergamini Giuseppe Vannozzi Angelo Maria Sabatini Aurelio Cappozzo |
| author_sort | Ilaria Pasciuto |
| collection | DOAJ |
| description | In human movement analysis, 3D body segment orientation can be obtained through the numerical integration of gyroscope signals. These signals, however, are affected by errors that, for the case of micro-electro-mechanical systems, are mainly due to: constant bias, scale factor, white noise, and bias instability. The aim of this study is to assess how the orientation estimation accuracy is affected by each of these disturbances, and whether it is influenced by the angular velocity magnitude and 3D distribution across the gyroscope axes. Reference angular velocity signals, either constant or representative of human walking, were corrupted with each of the four noise types within a simulation framework. The magnitude of the angular velocity affected the error in the orientation estimation due to each noise type, except for the white noise. Additionally, the error caused by the constant bias was also influenced by the angular velocity 3D distribution. As the orientation error depends not only on the noise itself but also on the signal it is applied to, different sensor placements could enhance or mitigate the error due to each disturbance, and special attention must be paid in providing and interpreting measures of accuracy for orientation estimation algorithms. |
| first_indexed | 2024-04-11T11:11:37Z |
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| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:11:37Z |
| publishDate | 2015-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-4382c1c4f9b1466e813029d5062c7cdb2022-12-22T04:27:28ZengMDPI AGSensors1424-82202015-09-01159239832400110.3390/s150923983s150923983How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation AccuracyIlaria Pasciuto0Gabriele Ligorio1Elena Bergamini2Giuseppe Vannozzi3Angelo Maria Sabatini4Aurelio Cappozzo5Interuniversity Center of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Piazza Lauro de Bosis 15, 00135 Roma, ItalyThe BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56124 Pisa, ItalyInteruniversity Center of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Piazza Lauro de Bosis 15, 00135 Roma, ItalyInteruniversity Center of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Piazza Lauro de Bosis 15, 00135 Roma, ItalyThe BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56124 Pisa, ItalyInteruniversity Center of Bioengineering of the Human Neuromusculoskeletal System, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Piazza Lauro de Bosis 15, 00135 Roma, ItalyIn human movement analysis, 3D body segment orientation can be obtained through the numerical integration of gyroscope signals. These signals, however, are affected by errors that, for the case of micro-electro-mechanical systems, are mainly due to: constant bias, scale factor, white noise, and bias instability. The aim of this study is to assess how the orientation estimation accuracy is affected by each of these disturbances, and whether it is influenced by the angular velocity magnitude and 3D distribution across the gyroscope axes. Reference angular velocity signals, either constant or representative of human walking, were corrupted with each of the four noise types within a simulation framework. The magnitude of the angular velocity affected the error in the orientation estimation due to each noise type, except for the white noise. Additionally, the error caused by the constant bias was also influenced by the angular velocity 3D distribution. As the orientation error depends not only on the noise itself but also on the signal it is applied to, different sensor placements could enhance or mitigate the error due to each disturbance, and special attention must be paid in providing and interpreting measures of accuracy for orientation estimation algorithms.http://www.mdpi.com/1424-8220/15/9/239833D orientationMEMS gyroscopesnoise sourcesmotion analysisgaitbiomechanicshumannumerical integrationinertial sensors |
| spellingShingle | Ilaria Pasciuto Gabriele Ligorio Elena Bergamini Giuseppe Vannozzi Angelo Maria Sabatini Aurelio Cappozzo How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy Sensors 3D orientation MEMS gyroscopes noise sources motion analysis gait biomechanics human numerical integration inertial sensors |
| title | How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy |
| title_full | How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy |
| title_fullStr | How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy |
| title_full_unstemmed | How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy |
| title_short | How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy |
| title_sort | how angular velocity features and different gyroscope noise types interact and determine orientation estimation accuracy |
| topic | 3D orientation MEMS gyroscopes noise sources motion analysis gait biomechanics human numerical integration inertial sensors |
| url | http://www.mdpi.com/1424-8220/15/9/23983 |
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