Efficient Observer Design for Ambulatory Estimation of Body Centre of Mass Position
Complementary Linear Filter (CLF) is a common techinque employed for estimating the ground projection of body Centre of Mass starting from ground reaction forces. This method fuses centre of pressure position and double integration of horizontal forces, selecting best cut-off frequencies for low-pas...
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IEEE
2023-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/10059179/ |
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| author | Marco Maddalena Mozafar Saadat |
| author_facet | Marco Maddalena Mozafar Saadat |
| author_sort | Marco Maddalena |
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| description | Complementary Linear Filter (CLF) is a common techinque employed for estimating the ground projection of body Centre of Mass starting from ground reaction forces. This method fuses centre of pressure position and double integration of horizontal forces, selecting best cut-off frequencies for low-pass and high-pass filters. Classical Kalman filter is a substantially equivalent approach, as both methods rely on an overall quantification of error/noise and don’t analyze its origin and time-dependence. In order to overcome such limitations, a Time-Varying Kalman Filter (TVKF) is proposed in this paper: the effect of unknown variables is directly taken into account by employing a statistical description which is obtained from experimental data. To this end, in this paper we have employed a dataset of 8 walking healthy subjects: beside supplying gait cycles at different speeds, it deals with subjects in age of development and provides a wide range of body sizes, allowing therefore to assess the observers’ behaviour under different conditions. The comparison carried out between CLF and TVKF appears to highlight several advantages of the latter method in terms of better average performance and smaller variability. Results presented in this paper suggest that a strategy which incorporates a statistical description of unknown variables and a time-varying structure can yield a more reliable observer. The demonstrated methodology sets a tool that can undergo a broader investigation to be carried out including more subjects and different walking styles. |
| format | Article |
| id | doaj-art-b92f8907f24d475da1d9070c6f69fa6b |
| institution | OA Journals |
| issn | 1534-4320 1558-0210 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | IEEE |
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| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj-art-b92f8907f24d475da1d9070c6f69fa6b2025-08-20T01:52:10ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1534-43201558-02102023-01-01311594160110.1109/TNSRE.2023.325305110059179Efficient Observer Design for Ambulatory Estimation of Body Centre of Mass PositionMarco Maddalena0https://orcid.org/0000-0002-2749-1116Mozafar Saadat1https://orcid.org/0000-0002-6622-4715Department of Mechanical Engineering, University of Birmingham, Birmingham, U.KDepartment of Mechanical Engineering, University of Birmingham, Birmingham, U.KComplementary Linear Filter (CLF) is a common techinque employed for estimating the ground projection of body Centre of Mass starting from ground reaction forces. This method fuses centre of pressure position and double integration of horizontal forces, selecting best cut-off frequencies for low-pass and high-pass filters. Classical Kalman filter is a substantially equivalent approach, as both methods rely on an overall quantification of error/noise and don’t analyze its origin and time-dependence. In order to overcome such limitations, a Time-Varying Kalman Filter (TVKF) is proposed in this paper: the effect of unknown variables is directly taken into account by employing a statistical description which is obtained from experimental data. To this end, in this paper we have employed a dataset of 8 walking healthy subjects: beside supplying gait cycles at different speeds, it deals with subjects in age of development and provides a wide range of body sizes, allowing therefore to assess the observers’ behaviour under different conditions. The comparison carried out between CLF and TVKF appears to highlight several advantages of the latter method in terms of better average performance and smaller variability. Results presented in this paper suggest that a strategy which incorporates a statistical description of unknown variables and a time-varying structure can yield a more reliable observer. The demonstrated methodology sets a tool that can undergo a broader investigation to be carried out including more subjects and different walking styles.https://ieeexplore.ieee.org/document/10059179/Locomotioncenter of massground projectionobserverestimationground reaction forces |
| spellingShingle | Marco Maddalena Mozafar Saadat Efficient Observer Design for Ambulatory Estimation of Body Centre of Mass Position IEEE Transactions on Neural Systems and Rehabilitation Engineering Locomotion center of mass ground projection observer estimation ground reaction forces |
| title | Efficient Observer Design for Ambulatory Estimation of Body Centre of Mass Position |
| title_full | Efficient Observer Design for Ambulatory Estimation of Body Centre of Mass Position |
| title_fullStr | Efficient Observer Design for Ambulatory Estimation of Body Centre of Mass Position |
| title_full_unstemmed | Efficient Observer Design for Ambulatory Estimation of Body Centre of Mass Position |
| title_short | Efficient Observer Design for Ambulatory Estimation of Body Centre of Mass Position |
| title_sort | efficient observer design for ambulatory estimation of body centre of mass position |
| topic | Locomotion center of mass ground projection observer estimation ground reaction forces |
| url | https://ieeexplore.ieee.org/document/10059179/ |
| work_keys_str_mv | AT marcomaddalena efficientobserverdesignforambulatoryestimationofbodycentreofmassposition AT mozafarsaadat efficientobserverdesignforambulatoryestimationofbodycentreofmassposition |