Examinando por Autor "Florez, Julian"
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Ítem Optical Enhancement of Exoskeleton-Based Estimation of Glenohumeral Angles(Hindawi Publishing Corp., 2016-05-16) Florez, Julian; Cortéz, Camilo; Unzueta, Luis; De los Reyes-Guzmán, Ana; Ruíz, Óscar E.; Universidad EAFIT. Departamento de Ingeniería Mecánica. Grupo de Investigación CAD CAM CAE, Carrera 49 7 Sur-50, Medellín, Colombia.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEIn Robot-Assisted Rehabilitation (RAR) the accurate estimation of the patient limb joint angles is critical for assessing therapy efficacy. In RAR, the use of classic motion capture systems (MOCAPs) (e.g., optical and electromagnetic) to estimate the Glenohumeral (GH) joint angles is hindered by the exoskeleton body, which causes occlusions and magnetic disturbances. Moreover, the exoskeleton posture does not accurately reflect limb posture, as their kinematic models differ. To address the said limitations in posture estimation, we propose installing the cameras of an optical marker-based MOCAP in the rehabilitation exoskeleton. Then, the GH joint angles are estimated by combining the estimated marker poses and exoskeleton Forward Kinematics. Such hybrid system prevents problems related to marker occlusions, reduced camera detection volume, and imprecise joint angle estimation due to the kinematic mismatch of the patient and exoskeleton models. This paper presents the formulation, simulation, and accuracy quantification of the proposed method with simulated human movements. In addition, a sensitivity analysis of the method accuracy to marker position estimation errors, due to system calibration errors and marker drifts, has been carried out. The results show that, even with significant errors in the marker position estimation, method accuracy is adequate for RAR.Ítem Robust CT to US 3D-3D Registration by using Principal Component Analysis and Kalman Filtering(2015-01-01) Echeverría, Rebeca; Cortes, Camilo; Bertelnsen, Alvaro; Ruiz OE; Macia, Ivan; Florez, Julian; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEÍtem Ultrasound Image Dataset for Image Analysis Algorithms Evaluation(Springer Verlag, 2015) Cortes, Camilo; Kabongo, Luis; Macia, Ivan; Ruíz, Óscar E.; Florez, Julian; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThe use of ultrasound (US) imaging as an alternative for real-time computer assisted interventions is increasing -- Growing usage of US occurs de-spite of US lower imaging quality compared to other techniques and its diffi-culty to be used with image analysis algorithms -- On the other hand, it is still difficult to find sufficient data to develop and assess solutions for navigation, registration and reconstruction at medical research level -- At present, manually acquired available datasets present significant usability obstacles due to their lack of control of acquisition conditions, which hinders the study and correction of algorithm design parameters -- To address these limitations, we present a data-base of robotically acquired sequences of US images from medical phantoms, ensuring the trajectory, pose and force control of the probe -- The acquired data-set is publicly available, and it is specially useful for designing and testing reg-istration and volume reconstruction algorithmsÍtem Ultrasound Image Dataset for Image Analysis Algorithms Evaluation(Springer Verlag, 2016) Cortes, Camilo; Kabongo, Luis; Macia, Ivan; Ruíz, Óscar E.; Florez, Julian; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThe use of ultrasound (US) imaging as an alternative for real-time computer assisted interventions is increasing -- Growing usage of US occurs despite of US lower imaging quality compared to other techniques and its difficulty to be used with image analysis algorithms -- On the other hand, it is still difficult to find sufficient data to develop and assess solutions for navigation, registration and reconstruction at medical research level -- At present, manually acquired available datasets present significant usability obstacles due to their lack of control of acquisition conditions, which hinders the study and correction of algorithm design parameters -- To address these limitations, we present a database of robotically acquired sequences of US images from medical phantoms, ensuring the trajectory, pose and force control of the probe -- The acquired dataset is publicly available, and it is specially useful for designing and testing registration and volume reconstruction algorithmsÍtem Ultrasound Image Dataset for Image Analysis Algorithms Evaluation(Springer International Publishing, 2015-08-12) Cortés, C.; Kabongo, Luis; Macia, Ivan; Florez, Julian; Ruiz, Oscar Eduardo; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThe use of ultrasound (US) imaging as an alternative for real-time computer assisted interventions is increasing. Growing usage of US occurs despite of US lower imaging quality compared to other techniques and its difficulty...Ítem Upper Limb Posture Estimation in Robotic and Virtual Reality-based Rehabilitation.(Hindawi Publishing Corp., 2014-07-08) Cortez, Camilo; Ardanza, Aitor; Molina Rueda, F.; Cuesta Gomez, A.; Unzueta, L.; Epelde, G.; Ruiz Salguero, Oscar; De Mauro, A.; Florez, Julian; Universidad EAFIT. Departamento de Ingeniería Mecánica. Grupo de Investigación CAD CAM CAE, Carrera 49 7 Sur-50, Medellín, Colombia.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAENew motor rehabilitation therapies include virtual reality (VR) and robotic technologies. In limb rehabilitation, limb posture is required to (1) provide a limb realistic representation in VR games and (2) assess the patient improvement. When exoskeleton devices are used in the therapy, the measurements of their joint angles cannot be directly used to represent the posture of the patient limb, since the human and exoskeleton kinematic models differ. In response to this shortcoming, we propose a method to estimate the posture of the human limb attached to the exoskeleton. We use the exoskeleton joint angles measurements and the constraints of the exoskeleton on the limb to estimate the human limb joints angles. This paper presents (a) the mathematical formulation and solution to the problem, (b) the implementation of the proposed solution on a commercial exoskeleton system for the upper limb rehabilitation, (c) its integration into a rehabilitation VR game platform, and (d) the quantitative assessment of the method during elbow and wrist analytic training. Results show that this method properly estimates the limb posture to (i) animate avatars that represent the patient in VR games and (ii) obtain kinematic data for the patient assessment during elbow and wrist analytic rehabilitation.