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http://hdl.handle.net/10261/150052
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dc.contributor.author | Nogueira, Samuel L. | - |
dc.contributor.author | Lambrecht, Stefan | - |
dc.contributor.author | Inoue, Roberto S. | - |
dc.contributor.author | Bortole, Magdo | - |
dc.contributor.author | Montagnoli, Arlindo N. | - |
dc.contributor.author | Moreno, Juan Camilo | - |
dc.contributor.author | Rocón, Eduardo | - |
dc.contributor.author | Terra, Marco H. | - |
dc.contributor.author | Siqueira, Adriano A. G. | - |
dc.contributor.author | Pons Rovira, José Luis | - |
dc.date.accessioned | 2017-05-21T03:33:38Z | - |
dc.date.available | 2017-05-21T03:33:38Z | - |
dc.date.issued | 2017-05-16 | - |
dc.identifier.citation | BioMedical Engineering OnLine, 16(1): 58 (2017) | - |
dc.identifier.issn | 1475-925X | - |
dc.identifier.uri | http://hdl.handle.net/10261/150052 | - |
dc.description.abstract | [Background] In this paper we propose the use of global Kalman filters (KFs) to estimate absolute angles of lower limb segments. Standard approaches adopt KFs to improve the performance of inertial sensors based on individual link configurations. In consequence, for a multi-body system like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank) are not taken into account in other link angle estimations (e.g., foot). Global KF approaches, on the other hand, correlate the collective contribution of all signals from lower limb segments observed in the state-space model through the filtering process. We present a novel global KF (matricial global KF) relying only on inertial sensor data, and validate both this KF and a previously presented global KF (Markov Jump Linear Systems, MJLS-based KF), which fuses data from inertial sensors and encoders from an exoskeleton. We furthermore compare both methods to the commonly used local KF. | - |
dc.description.abstract | [Results] The results indicate that the global KFs performed significantly better than the local KF, with an average root mean square error (RMSE) of respectively 0.942° for the MJLS-based KF, 1.167° for the matrical global KF, and 1.202° for the local KFs. Including the data from the exoskeleton encoders also resulted in a significant increase in performance. | - |
dc.description.abstract | [Conclusion] The results indicate that the current practice of using KFs based on local models is suboptimal. Both the presented KF based on inertial sensor data, as well our previously presented global approach fusing inertial sensor data with data from exoskeleton encoders, were superior to local KFs. We therefore recommend to use global KFs for gait analysis and exoskeleton control. | - |
dc.description.sponsorship | This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), under Grant 2012/05552–9; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), under Grant 456089/2014–4; the HYPER project of the CONSOLIDER-INGENIO 2010 program of Spain, under Grant CSD2009–00067; the XoSoft project, Soft modular biomimetic exoskeleton to assist people with mobility impairments, contract H2020– ICT24–2016–688175; and by a grant from the Flemish agency for Innovation by Science and Technology (MIRAD, IWT–SBO 120057). | - |
dc.publisher | BioMed Central | - |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/688175 | - |
dc.relation.isversionof | Publisher's version | - |
dc.rights | openAccess | - |
dc.subject | Exoskeleton | - |
dc.subject | Inertial sensors | - |
dc.subject | Kalman filter | - |
dc.subject | Markovian jump systems | - |
dc.subject | Wearable robots | - |
dc.title | Global Kalman filter approaches to estimate absolute angles of lower limb segments | - |
dc.type | artículo | - |
dc.identifier.doi | 10.1186/s12938-017-0346-7 | - |
dc.description.peerreviewed | Peer reviewed | - |
dc.relation.publisherversion | http://dx.doi.org/10.1186/s12938-017-0346-7 | - |
dc.date.updated | 2017-05-21T03:33:38Z | - |
dc.language.rfc3066 | en | - |
dc.rights.holder | The Author(s) | - |
dc.rights.license | http://creativecommons.org/licenses/by/4.0/ | - |
dc.contributor.funder | Fundação de Amparo à Pesquisa do Estado de São Paulo | - |
dc.contributor.funder | Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil) | - |
dc.contributor.funder | Ministerio de Economía y Competitividad (España) | - |
dc.contributor.funder | European Commission | - |
dc.contributor.funder | Flemish Department of Economy, Science and Innovation (Belgium) | - |
dc.relation.csic | Sí | - |
dc.identifier.funder | http://dx.doi.org/10.13039/501100001807 | es_ES |
dc.identifier.funder | http://dx.doi.org/10.13039/501100003593 | es_ES |
dc.identifier.funder | http://dx.doi.org/10.13039/501100003329 | es_ES |
dc.identifier.funder | http://dx.doi.org/10.13039/501100000780 | es_ES |
dc.identifier.pmid | 28511658 | - |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | es_ES |
item.openairetype | artículo | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
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12938_2017_Article_346.pdf | 2,42 MB | Adobe PDF | Visualizar/Abrir |
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