2016-10-212016-05-162314-6141http://hdl.handle.net/10784/9529Robot-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 DOFmovements of the wrist and elbow joints -- This paper presents the assessment of EIKPEwith elbow-shoulder compoundmovements (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 compoundmovement execution, especially for the shoulder joint angles -- This work opens the horizon for clinical studies with patient groups, Exoskeleton models, and movements types --application/pdfenginfo:eu-repo/semantics/openAccessinfo:eu-repo/semantics/articleROBÓTICAREHABILITACIÓN MÉDICABIOMECÁNICAEXTREMIDADES SUPERIORESEXOESQUELETOELECTROMIOGRAFÍARoboticsMedical rehabilitationBiomechanicsExtremities, upperExoskeletonElectromyographyRoboticsMedical rehabilitationBiomechanicsExtremitiesupperExoskeletonElectromyographyCinemática inversaAcceso abierto2016-10-21Cortés, CamiloDe los Reyes-Guzmán, AnaScorza, DavideBertelsen, ÁlvaroCarrasco, EduardoGil-Agudo, ÁngelRuíz-Salguero, ÓscarFlórez, Julián10.1155/2016/2581924