Inverse Kinematics for Upper Limb Compound Movement Estimation in Exoskeleton-Assisted Rehabilitation

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dc.citation.journalTitleBIOMED RESEARCH INTERNATIONALeng
dc.contributor.authorCortés, C.
dc.contributor.authorDe Los Reyes-Guzmán, A.
dc.contributor.authorScorza, D.
dc.contributor.authorBertelsen, A.
dc.contributor.authorCarrasco, E.
dc.contributor.authorGil-Agudo, A.
dc.contributor.authorRuiz-Salguero, O.
dc.contributor.authorFlórez, J.
dc.contributor.departmentUniversidad EAFIT. Departamento de Ingeniería Mecánicaspa
dc.contributor.researchgroupLaboratorio CAD/CAM/CAEspa
dc.date.accessioned2021-04-16T21:59:57Z
dc.date.available2021-04-16T21:59:57Z
dc.date.issued2016-06-15
dc.description.abstractRobot-Assisted Rehabilitation (RAR) is relevant for treating patients affected by nervous system injuries (e.g., stroke and spinal cord injury). The accurate estimation of the joint angles of the patient limbs in RAR is critical to assess the patient improvement. The economical prevalent method to estimate the patient posture in Exoskeleton-based RAR is to approximate the limb joint angles with the ones of the Exoskeleton. This approximation is rough since their kinematic structures differ. Motion capture systems (MOCAPs) can improve the estimations, at the expenses of a considerable overload of the therapy setup. Alternatively, the Extended Inverse Kinematics Posture Estimation (EIKPE) computational method models the limb and Exoskeleton as differing parallel kinematic chains. EIKPE has been tested with single DOF movements of the wrist and elbow joints. This paper presents the assessment of EIKPE with elbow shoulder compound movements (i.e., object prehension). Ground-truth for estimation assessment is obtained from an optical MOCAP (not intended for the treatment stage). The assessment shows EIKPE rendering a good numerical approximation of the actual posture during the compound movement execution, especially for the shoulder joint angles. This work opens the horizon for clinical studies with patient groups, Exoskeleton models, and movements types.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=3709
dc.identifier.doi10.1155/2016/2581924
dc.identifier.issn23146133
dc.identifier.issn23146141spa
dc.identifier.otherWOS;000378700700001
dc.identifier.otherPUBMED;27403420
dc.identifier.otherSCOPUS;2-s2.0-84976639463
dc.identifier.urihttp://hdl.handle.net/10784/29533
dc.languageeng
dc.publisherHINDAWI PUBLISHING CORPORATION
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84976639463&doi=10.1155%2f2016%2f2581924&partnerID=40&md5=c97cec9cfd649c763efc94c2d7bf904a
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/2314-6133
dc.sourceBIOMED RESEARCH INTERNATIONAL
dc.subject.keywordCARRYING ANGLEeng
dc.subject.keywordELBOW JOINTeng
dc.subject.keywordSTROKEeng
dc.subject.keywordREDUNDANCYeng
dc.subject.keywordROBOTeng
dc.titleInverse Kinematics for Upper Limb Compound Movement Estimation in Exoskeleton-Assisted Rehabilitationeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localArtículospa

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