Examinando por Autor "Scorza, D."

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    Inverse Kinematics for Upper Limb Compound Movement Estimation in Exoskeleton-Assisted Rehabilitation
    (HINDAWI PUBLISHING CORPORATION, 2016-06-15) Cortés, C.; De Los Reyes-Guzmán, A.; Scorza, D.; Bertelsen, A.; Carrasco, E.; Gil-Agudo, A.; Ruiz-Salguero, O.; Flórez, J.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAE
    Robot-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.
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    Upper Limb Robot Assisted Rehabilitation Platform Combining Virtual Reality, Posture Estimation and Kinematic Indices
    (Springer International Publishing AG, 2017-01-01) Scorza, D.; de Los Reyes, A.; Cortes, C.; Ardanza, A.; Bertelsen, A.; Ruiz, O. E.; Gil, A.; Florez, J.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAE
    Upper limb rehabilitation is critical for patients affected by spinal cord injury (SCI). Currently, robotics and Virtual Reality (VR) have changed the way in which rehabilitation therapies are provided. However, a still unreached precondition for these systems is the precise and practical estimation of limb posture and an objective evaluation of patient's improvement. In this manuscript we present an upper limb rehabilitation platform combining VR, patient posture estimation and objective kinematic indices. This manuscript describes the software platform and criteria which integrate the modules of the system. We report preliminary results of the kinematic indices and platform usability by practitioners.