Integration of Human Walking Gyroscopic Data Using Empirical Mode Decomposition
The present study was aimed at evaluating the Empirical Mode Decomposition (EMD) method to estimate the 3D orientation of the lower trunk during walking using the angular velocity signals generated by a wearable inertial measurement unit (IMU) and notably flawed by drift. The IMU was mounted on the...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2013-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/14/1/370 |
| _version_ | 1798002523812921344 |
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| author | Vincent Bonnet Sofiane Ramdani Christine Azevedo-Coste Philippe Fraisse Claudia Mazzà Aurelio Cappozzo |
| author_facet | Vincent Bonnet Sofiane Ramdani Christine Azevedo-Coste Philippe Fraisse Claudia Mazzà Aurelio Cappozzo |
| author_sort | Vincent Bonnet |
| collection | DOAJ |
| description | The present study was aimed at evaluating the Empirical Mode Decomposition (EMD) method to estimate the 3D orientation of the lower trunk during walking using the angular velocity signals generated by a wearable inertial measurement unit (IMU) and notably flawed by drift. The IMU was mounted on the lower trunk (L4-L5) with its active axes aligned with the relevant anatomical axes. The proposed method performs an offline analysis, but has the advantage of not requiring any parameter tuning. The method was validated in two groups of 15 subjects, one during overground walking, with 180° turns, and the other during treadmill walking, both for steady-state and transient speeds, using stereophotogrammetric data. Comparative analysis of the results showed that the IMU/EMD method is able to successfully detrend the integrated angular velocities and estimate lateral bending, flexion-extension as well as axial rotations of the lower trunk during walking with RMS errors of 1 deg for straight walking and lower than 2.5 deg for walking with turns. |
| first_indexed | 2024-04-11T11:53:27Z |
| format | Article |
| id | doaj.art-c7e08c872f9642f1ab1bde601a9a24d4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:53:27Z |
| publishDate | 2013-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c7e08c872f9642f1ab1bde601a9a24d42022-12-22T04:25:15ZengMDPI AGSensors1424-82202013-12-0114137038110.3390/s140100370s140100370Integration of Human Walking Gyroscopic Data Using Empirical Mode DecompositionVincent Bonnet0Sofiane Ramdani1Christine Azevedo-Coste2Philippe Fraisse3Claudia Mazzà4Aurelio Cappozzo5Movement to Health (M2H) Laboratory, EuroMov, University of Montpellier 1, Montpellier 34090, FranceMovement to Health (M2H) Laboratory, EuroMov, University of Montpellier 1, Montpellier 34090, FranceLIRMM, University of Montpellier 2, Montpellier 34090, FranceLIRMM, University of Montpellier 2, Montpellier 34090, FranceDepartment of Mechanical Engineering, University of Sheffield, Sheffield S13JD, UKDepartment of Movement, Human and Health Sciences, University of Rome "Foro Italico", Rome 00135, ItalyThe present study was aimed at evaluating the Empirical Mode Decomposition (EMD) method to estimate the 3D orientation of the lower trunk during walking using the angular velocity signals generated by a wearable inertial measurement unit (IMU) and notably flawed by drift. The IMU was mounted on the lower trunk (L4-L5) with its active axes aligned with the relevant anatomical axes. The proposed method performs an offline analysis, but has the advantage of not requiring any parameter tuning. The method was validated in two groups of 15 subjects, one during overground walking, with 180° turns, and the other during treadmill walking, both for steady-state and transient speeds, using stereophotogrammetric data. Comparative analysis of the results showed that the IMU/EMD method is able to successfully detrend the integrated angular velocities and estimate lateral bending, flexion-extension as well as axial rotations of the lower trunk during walking with RMS errors of 1 deg for straight walking and lower than 2.5 deg for walking with turns.http://www.mdpi.com/1424-8220/14/1/370empirical mode decomposition (EMD)inertial measurement unit (IMU)human walkingmotion analysis |
| spellingShingle | Vincent Bonnet Sofiane Ramdani Christine Azevedo-Coste Philippe Fraisse Claudia Mazzà Aurelio Cappozzo Integration of Human Walking Gyroscopic Data Using Empirical Mode Decomposition Sensors empirical mode decomposition (EMD) inertial measurement unit (IMU) human walking motion analysis |
| title | Integration of Human Walking Gyroscopic Data Using Empirical Mode Decomposition |
| title_full | Integration of Human Walking Gyroscopic Data Using Empirical Mode Decomposition |
| title_fullStr | Integration of Human Walking Gyroscopic Data Using Empirical Mode Decomposition |
| title_full_unstemmed | Integration of Human Walking Gyroscopic Data Using Empirical Mode Decomposition |
| title_short | Integration of Human Walking Gyroscopic Data Using Empirical Mode Decomposition |
| title_sort | integration of human walking gyroscopic data using empirical mode decomposition |
| topic | empirical mode decomposition (EMD) inertial measurement unit (IMU) human walking motion analysis |
| url | http://www.mdpi.com/1424-8220/14/1/370 |
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