Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface
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| Main Author: | |
|---|---|
| Publication Date: | 2018 |
| Other Authors: | , , , , |
| Language: | eng |
| Source: | Repositório Institucional da UnB |
| Download full: | http://repositorio.unb.br/handle/10482/34442 |
Summary: | Spinal cord injury (SCI), stroke and other nervous system conditions can result in partial or total paralysis of individual’s limbs. Numerous technologies have been proposed to assist neurorehabilitation or movement restoration, e.g. robotics or neuroprosthesis. However, individuals with tetraplegia often find difficult to pilot these devices. We developed a system based on a single inertial measurement unit located on the upper limb that is able to classify performed movements using principal component analysis. We analyzed three calibration algorithms: unsupervised learning, supervised learning and adaptive learning. Eight participants with tetraplegia (C4-C7) piloted three different postures in a robotic hand. We achieved 89% accuracy using the supervised learning algorithm. Through offline simulation, we found accuracies of 76% on the unsupervised learning, and 88% on the adaptive one. |
| _version_ | 1871442285631111168 |
|---|---|
| author | Fonseca, Lucas |
| author2 | Bó, Antônio Padilha Lanari Guiraud, David Navarro, Benjamin Gélis, Anthony Coste, Christine Azevedo |
| author2_role | author author author author author |
| author_browse | Bó, Antônio Padilha Lanari Coste, Christine Azevedo Fonseca, Lucas Guiraud, David Gélis, Anthony Navarro, Benjamin |
| author_facet | Fonseca, Lucas Bó, Antônio Padilha Lanari Guiraud, David Navarro, Benjamin Gélis, Anthony Coste, Christine Azevedo |
| author_role | author |
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| bitstream.url.fl_str_mv | http://repositorio.unb.br/bitstream/10482/34442/2/license.txt http://repositorio.unb.br/bitstream/10482/34442/1/EVENTO_InvestigatingUpperLimb.pdf |
| collection | Repositório Institucional da UnB |
| dc.contributor.author.fl_str_mv | Fonseca, Lucas Bó, Antônio Padilha Lanari Guiraud, David Navarro, Benjamin Gélis, Anthony Coste, Christine Azevedo |
| dc.date.accessioned.fl_str_mv | 2019-04-26T12:54:21Z |
| dc.date.available.fl_str_mv | 2019-04-26T12:54:21Z |
| dc.date.issued.fl_str_mv | 2018-07 |
| dc.identifier.citation.fl_str_mv | FONSECA, Lucas et al. Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface. In: ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, 40., 2018, Honolulu. |
| dc.identifier.uri.fl_str_mv | http://repositorio.unb.br/handle/10482/34442 |
| dc.language.iso.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | IEEE |
| dc.rights.driver.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:Repositório Institucional da UnB instname:Universidade de Brasília (UnB) instacron:UNB |
| dc.subject.keyword.pt_BR.fl_str_mv | Medula espinhal - ferimentos e lesões Acidentes vasculares cerebrais Lesão cerebral Medicina de reabilitação |
| dc.title.pt_BR.fl_str_mv | Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface |
| dc.type.driver.fl_str_mv | Trabalho apresentado em evento |
| dc.type.status.fl_str_mv | info:eu-repo/semantics/publishedVersion |
| description | Spinal cord injury (SCI), stroke and other nervous system conditions can result in partial or total paralysis of individual’s limbs. Numerous technologies have been proposed to assist neurorehabilitation or movement restoration, e.g. robotics or neuroprosthesis. However, individuals with tetraplegia often find difficult to pilot these devices. We developed a system based on a single inertial measurement unit located on the upper limb that is able to classify performed movements using principal component analysis. We analyzed three calibration algorithms: unsupervised learning, supervised learning and adaptive learning. Eight participants with tetraplegia (C4-C7) piloted three different postures in a robotic hand. We achieved 89% accuracy using the supervised learning algorithm. Through offline simulation, we found accuracies of 76% on the unsupervised learning, and 88% on the adaptive one. |
| eu_rights_str_mv | openAccess |
| id | UNB_3d9ffa486efb366a615ce38b13bccf4f |
| identifier_str_mv | FONSECA, Lucas et al. Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface. In: ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, 40., 2018, Honolulu. |
| instacron_str | UNB |
| institution | UNB |
| instname_str | Universidade de Brasília (UnB) |
| language | eng |
| network_acronym_str | UNB |
| network_name_str | Repositório Institucional da UnB |
| oai_identifier_str | oai:repositorio.unb.br:10482/34442 |
| publishDate | 2018 |
| publishDateSort | 2018 |
| publisher.none.fl_str_mv | IEEE |
| reponame_str | Repositório Institucional da UnB |
| repository.mail.fl_str_mv | repositorio@unb.br |
| repository.name.fl_str_mv | Repositório Institucional da UnB - Universidade de Brasília (UnB) |
| repository_id_str | |
| spelling | Fonseca, LucasBó, Antônio Padilha LanariGuiraud, DavidNavarro, BenjaminGélis, AnthonyCoste, Christine Azevedo2019-04-26T12:54:21Z2019-04-26T12:54:21Z2018-07FONSECA, Lucas et al. Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface. In: ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, 40., 2018, Honolulu.http://repositorio.unb.br/handle/10482/34442IEEEAutorização concedida ao Repositório Institucional da Universidade de Brasília pelo Professor Antônio Padilha Lanari Bó para disponibilizar o trabalho, em 23 de abril de 2019, no site repositorio.unb.br, de acordo com a licença conforme permissões assinaladas, para fins de leitura, impressão e/ou download, a título de divulgação da obra, a partir desta data.info:eu-repo/semantics/openAccessInvestigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interfaceTrabalho apresentado em eventoinfo:eu-repo/semantics/publishedVersionMedula espinhal - ferimentos e lesõesAcidentes vasculares cerebraisLesão cerebralMedicina de reabilitaçãoSpinal cord injury (SCI), stroke and other nervous system conditions can result in partial or total paralysis of individual’s limbs. Numerous technologies have been proposed to assist neurorehabilitation or movement restoration, e.g. robotics or neuroprosthesis. However, individuals with tetraplegia often find difficult to pilot these devices. We developed a system based on a single inertial measurement unit located on the upper limb that is able to classify performed movements using principal component analysis. We analyzed three calibration algorithms: unsupervised learning, supervised learning and adaptive learning. Eight participants with tetraplegia (C4-C7) piloted three different postures in a robotic hand. We achieved 89% accuracy using the supervised learning algorithm. Through offline simulation, we found accuracies of 76% on the unsupervised learning, and 88% on the adaptive one.Instituto de Ciências Biológicas (IB)Departamento de Ecologia (IB ECL)engreponame:Repositório Institucional da UnBinstname:Universidade de Brasília (UnB)instacron:UNBLICENSElicense.txtlicense.txttext/plain102http://repositorio.unb.br/bitstream/10482/34442/2/license.txtaed4704d04bb260d4decd80db311aaa5MD52open accessORIGINALEVENTO_InvestigatingUpperLimb.pdfEVENTO_InvestigatingUpperLimb.pdfapplication/pdf3628402http://repositorio.unb.br/bitstream/10482/34442/1/EVENTO_InvestigatingUpperLimb.pdf220ab78c4bf449bd63bfb7789ee6d65bMD51open access10482/344422025-10-15 14:34:47.255open accessoai:repositorio.unb.br:10482/34442U3VibWlzc8OjbyBlZmV0aXZhZGEgZGUgYWNvcmRvIGNvbSBsaWNlbsOnYSBjb25jZWRpZGEgcGVsbyBhdXRvciBlL291IGRldGVudG9yIGRvcyBkaXJlaXRvcyBhdXRvcmFpcy4KRepositório InstitucionalPUBhttps://repositorio.unb.br/oai/requestrepositorio@unb.bropendoar:2025-10-15T17:34:47Repositório Institucional da UnB - Universidade de Brasília (UnB) |
| spellingShingle | Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface Fonseca, Lucas Medula espinhal - ferimentos e lesões Acidentes vasculares cerebrais Lesão cerebral Medicina de reabilitação |
| status_str | publishedVersion |
| title | Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface |
| title_full | Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface |
| title_fullStr | Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface |
| title_full_unstemmed | Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface |
| title_short | Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface |
| title_sort | Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface |
| topic | Medula espinhal - ferimentos e lesões Acidentes vasculares cerebrais Lesão cerebral Medicina de reabilitação |
| url | http://repositorio.unb.br/handle/10482/34442 |