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dc.contributor.author
Abraham, Leandro
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dc.contributor.author
Bromberg, Facundo
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dc.contributor.author
Forradellas, Raymundo Quilez
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dc.date.available
2019-11-07T19:02:59Z
dc.date.issued
2018-04
dc.identifier.citation
Abraham, Leandro; Bromberg, Facundo; Forradellas, Raymundo Quilez; Ensemble of shape functions and support vector machines for the estimation of discrete arm muscle activation from external biceps 3D point clouds; Pergamon-Elsevier Science Ltd; Computers In Biology And Medicine; 95; 4-2018; 129-139
dc.identifier.issn
0010-4825
dc.identifier.uri
http://hdl.handle.net/11336/88221
dc.description.abstract
Background: Muscle activation level is currently being captured using impractical and expensive devices which make their use in telemedicine settings extremely difficult. To address this issue, a prototype is presented of a non-invasive, easy-to-install system for the estimation of a discrete level of muscle activation of the biceps muscle from 3D point clouds captured with RGB-D cameras. Methods: A methodology is proposed that uses the ensemble of shape functions point cloud descriptor for the geometric characterization of 3D point clouds, together with support vector machines to learn a classifier that, based on this geometric characterization for some points of view of the biceps, provides a model for the estimation of muscle activation for all neighboring points of view. This results in a classifier that is robust to small perturbations in the point of view of the capturing device, greatly simplifying the installation process for end-users. Results: In the discrimination of five levels of effort with values up to the maximum voluntary contraction (MVC) of the biceps muscle (3800 g), the best variant of the proposed methodology achieved mean absolute errors of about 9.21% MVC — an acceptable performance for telemedicine settings where the electric measurement of muscle activation is impractical. Conclusions: The results prove that the correlations between the external geometry of the arm and biceps muscle activation are strong enough to consider computer vision and supervised learning an alternative with great potential for practical applications in tele-physiotherapy.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
3D POINT CLOUDS
dc.subject
BICEPS ACTIVATION ESTIMATION
dc.subject
BIOMECHANICS
dc.subject
ENSEMBLE OF SHAPE FUNCTIONS
dc.subject
SUPPORT VECTOR MACHINES
dc.subject
TELE-PHYSIOTHERAPY
dc.subject.classification
Otras Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
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dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
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dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
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dc.title
Ensemble of shape functions and support vector machines for the estimation of discrete arm muscle activation from external biceps 3D point clouds
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-10-23T21:43:51Z
dc.journal.volume
95
dc.journal.pagination
129-139
dc.journal.pais
Países Bajos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Abraham, Leandro. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio DHARMA; Argentina. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
dc.description.fil
Fil: Bromberg, Facundo. Universidad Tecnológica Nacional. Facultad Regional Mendoza. Departamento de Sistemas de Información. Laboratorio DHARMA; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
dc.description.fil
Fil: Forradellas, Raymundo Quilez. Universidad Nacional de Cuyo; Argentina
dc.journal.title
Computers In Biology And Medicine
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.compbiomed.2018.02.011
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0010482518300416
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