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San Sebastián de los Reyes, Spain

Echeverria R.,EHealth and Biomedical Applications | Echeverria R.,Public University of Navarra | Cortes C.,EHealth and Biomedical Applications | Cortes C.,EAFIT University | And 4 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016

Algorithms based on the unscented Kalman filter (UKF) have been proposed as an alternative for registration of point clouds obtained from vertebral ultrasound (US) and computerised tomography (CT) scans, effectively handling the US limited depth and low signal to-noise ratio. Previously proposed methods are accurate, but their convergence rate is considerably reduced with initial misalignments of the datasets greater than 30º or 30 mm. We propose a novel method which increases robustness by adding a coarse alignment of the datasets’ principal components and batch-based point inclusions for the UKF. Experiments with simulated scans with full coverage of a single vertebra show the method’s capability and accuracy to correct misalignments as large as 180º and 90 mm. Furthermore, the method registers datasets with varying degrees of missing data and datasets with outlier points coming from adjacent vertebrae. © Springer International Publishing Switzerland 2016.


Cortes C.,EHealth and Biomedical Applications | Cortes C.,EAFIT University | Unzueta L.,EHealth and Biomedical Applications | De Los Reyes-Guzman A.,National Hospital for Spinal Cord Injury | And 2 more authors.
Applied Bionics and Biomechanics | Year: 2016

In 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. © 2016 Camilo Cortés et al.


Cortes C.A.,EHealth and Biomedical Applications | Cortes C.A.,EAFIT University | Barandiaran I.,EHealth and Biomedical Applications | Ruiz O.E.,EAFIT University | De Mauro A.,EHealth and Biomedical Applications
Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2013 | Year: 2013

In the context of surgery, it is very common to face challenging scenarios during the preoperative plan implementation. The surgical technique's complexity, the human anatomical variability and the occurrence of unexpected situations generate issues for the intervention's goals achievement. To support the surgeon, robotic systems are being integrated to the operating room. However, current commercial solutions are specialized for a particular technique or medical application, being difficult to integrate with other systems. Thus, versatile and modular systems are needed to conduct several procedures and to help solving the problems that surgeons face. This article aims to describe the implementation of a robotic research platform prototype that allows novel applications in the field of image-guided surgery. In particular, this research is focused on the topics of medical image acquisition during surgery, patient registration and surgical/medical equipment operation. In this paper, we address the implementation of the general purpose teleoperation and path following modes of the platform, which constitute the base of future developments. Also, we discuss relevant aspects of the system, as well as future directions and application fields to investigate.


Epelde G.,EHealth and Biomedical Applications | Valencia X.,University of the Basque Country | Ardanza A.,EHealth and Biomedical Applications | Fanchon E.,EHealth and Biomedical Applications | And 4 more authors.
NEUROTECHNIX 2013 - Proceedings of the International Congress on Neurotechnology, Electronics and Informatics | Year: 2013

The use of technology in rehabilitation therapies targets the sustainability of health systems and the improvement of quality of life of the user (therapists, patients and informal carers). Robot or exoskeleton assisted rehabilitation systems, which are based on neurorehabilitation principles, are tools that not only help patients move the arm with precision; they also help reduce the fatigue of the therapist during the process. One of the challenges of the virtual reality based robot assisted upper limb rehabilitation is patients' immersion within the therapy to achieve an improved progress of the rehabilitation. This paper, presents a new virtual reality therapy that has been created using the Armeo Spring exoskeleton. A 3D representation of the arm serves as an interaction mechanism with the virtual world. This makes the user more aware of the movements that he/she is making and improves the rehabilitation outcomes. It also encourages the user motivation and engagement to the therapy. Additionally, an application for the multimodal monitoring of the patient has been developed, together with tools for the online assessment of patients. These developments allow the physician to review the therapy without being in the same place and time, optimizing the use of hospital's human resources.


Cortes C.,EHealth and Biomedical Applications | Cortes C.,EAFIT University | Ardanza A.,EHealth and Biomedical Applications | Molina-Rueda F.,Rey Juan Carlos University | And 6 more authors.
BioMed Research International | Year: 2014

New 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. © 2014 Camilo Cortés et al.

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