Publications

Over the last decade, 3D-printed porous calcium phosphates have emerged in the market for customized bone reconstruction. However, despite their excellent biological properties, the inherent brittleness is an obstacle that limits their clinical applications, as the scaffolds must withstand the surgical procedures and the mechanical stresses once implanted. Low-temperature self-hardening calcium phosphate inks offer unique possibilities to be reinforced with polymers, as they do not require high-temperature treatments. This study compares two routes for incorporating poly (lactic-co-glycolic acid) (PLGA) into 3D-printed calcium phosphate scaffolds: i) the use of a PLGA solution as a binder in an alpha-tricalcium phosphate self-hardening ink; ii) the infiltration of a PLGA solution into previously hardened 3D-printed calcium-deficient hydroxyapatite scaffolds. The influence of the added PLGA on the physical-chemical properties, mechanical performance and in vitro biological properties is assessed using a commercially available biomimetic calcium phosphate scaffold as a control. The addition of PLGA increases the plastic deformation capacity and the strength, both in compression and bending, and significantly improves the work of fracture of the scaffolds, up to an 8-fold in compression when PLGA is incorporated as a binder in the ink. Moreover, screwability tests demonstrate the enhanced fixability of the composite scaffolds in a knife-edge ridge indication with challenging fixation in the jaw. Importantly, the improvement of the mechanical properties by the addition of PLGA does not impair the good cytocompatibility of the material. Regarding the two routes studied, the PLGA incorporation in the ink is the best option in terms of overall improvement of the mechanical performance and osteogenic cell response.

JTD Keywords: Alkaline-phosphatase, B. composites, C. mechanical properties, Composite scaffold, D. apatite, Differentiation, E. biomedical application, In-vivo, Join, Regeneration

Very recently, the controlled release of dopamine (DA), a neurotransmitter whose deficiency is associated with Parkinson's disease, has been postulated as a good alternative to the oral administration of levodopa (L-Dopa), a dopamine precursor, to combat the effects of said disease. However, this is still a very little explored field and there are very few carriers that are capable of releasing DA, a small and water-soluble molecule, in an efficient and controlled manner. In this work, we report a carrier based on a conductive hydrogel capable of loading DA and releasing it progressively and efficiently (100 % release) in a period of five days by applying small electrical stimuli (-0.4 V) daily for a short time (1 min). The hydrogel (CMC/PEDOT), which is electrically active, has been prepared from sodium carboxymethylcellulose and poly(3,4-ethylenedioxythiophene) microparticles, using citric acid as a cross-linking agent. Furthermore, the results have shown that when relatively hydrophobic small molecules, such as chloramphenicol, are loaded, the electrostimulated release is significantly less efficient, demonstrating the usefulness of CMC/PEDOT as a carrier for neurotransmitters.

JTD Keywords: Amines, Carboxymethyl cellulose, Carboxymethylcellulose, Conducting hydrogels, Conducting polymers, Controlled release, Crosslinking, Dopamine, Drug-delivery system, Electrostimulation, Hydrogels, Joining, Levodopa, Loading, Molecules, Neurophysiology, Neurotransmitter release, Neurotransmitters release, Oral administration, Parkinson's disease, Parkinsons-disease, Poly(3,4-ethylenedioxythiophene), Release, Sodium, Transport, Water-soluble molecule

Cardiovascular diseases are the first cause of death in developed countries. Using electrocardiographic (ECG), blood pressure (BP) and respiratory flow signals, we obtained parameters for classifying cardiomyophaty patients. 42 patients with ischemic (ICM) and dilated (DCM) cardiomyophaties were studied. The left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF>35%, 14 patients) and high risk (HR: LVEF≤ 35%, 28 patients) of heart attack. RR, SBP and T_Tot time series were extracted from the ECG, BP and respiratory flow signals, respectively. The time series were transformed to a binary space and then analyzed using Joint Symbolic Dynamic with a word length of three, characterizing them by the probability of occurrence of the words. Extracted parameters were then reduced using correlation and statistical analysis. Principal component analysis and support vector machines methods were applied to characterize the cardiorespiratory and cardiovascular interactions in ICM and DCM cardiomyopaties, obtaining an accuracy of 85.7%.

JTD Keywords: Blood pressure, Electrocardiography, Joints, Kernel, Principal component analysis, Support vector machines, Time series analysis

An automatic gait initialization strategy based on user intention sensing in the context of rehabilitation with a lower-limb wearable robot is proposed and evaluated. The proposed strategy involves monitoring the human-orthosis interaction torques and initial position deviation to determine the gait initiation instant and to modify orthosis operation for gait assistance, when needed. During gait, the compliant control algorithm relies on the adaptation of the joints' stiffness in function of their interaction torques and their deviation from the desired trajectories, while maintaining the dynamic stability. As a reference input, the average of a set of recorded gaits obtained from healthy subjects is used. The algorithm has been tested with five healthy subjects showing its efficient behavior in initiating the gait and maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from incomplete Spinal cord injury and Stroke.

JTD Keywords: Biomedical monitoring, Exoskeletons, Joints, Knee, Legged locomotion, Trajectory, Exoskeleton, adaptive control, gait assistance, gait initiation, rehabilitation, wearable robot

In this paper, we propose a new approach to domestic action recognition based on a set of features which describe the relation between poses and movements of both hands. These features represent a set of basic actions in a kitchen in terms of the mimics of the hand movements, without needing information of the objects present in the scene. They address specifically the intra-class dissimilarity problem, which occurs when the same action is performed in different ways. The goal is to create a generic methodology that enables a robotic assistant system to recognize actions related to daily life activities and then, be endowed with a proactive behavior. The proposed system uses depth and color data acquired from a Kinect-style sensor and a hand tracking system. We analyze the relevance of the proposed hand-based features using a state-space search approach. Finally, we show the effectiveness of our action recognition approach using our own dataset.

JTD Keywords: Histograms, Joints, Robot sensing systems, Thumb, Tracking, Human activity recognition, Disable and elderly assistance

AbstractBackground Hip arthritis is a pathology linked to hip-cartilage degeneration. Although the aetiology of this disease is not well defined, it is known that age is a determinant risk factor. However, hip arthritis in young patients could be largely promoted by biomechanical factors. The objective of this paper is to analyze the impact of some normal anatomical variations on the cartilage stress distributions numerically predicted at the hip joint during walking. Methods A three-dimensional finite element model of the femur and the pelvis with the most relevant axial components of muscle forces was used to simulate normal walking activity. The hip anatomical condition was defined by: neck shaft angle, femoral anteversion angle, and acetabular anteversion angle with a range of 110-130º, 0-20º, and 0-20º, respectively. The direct boundary method was used to simulate the hip contact. Findings The hydrostatic stress found at the cartilage and labrum showed that a ± 10º variation with respect to the reference brings significant differences between the anatomic models. Acetabular anteversion angle of 0º and femoral anteversion angle of 0º were the most affected anatomical conditions with values of hydrostatic stress in the cartilage near 5 MPa under compression. Interpretation Cartilage stresses and contact areas were equivalent to the results found in literature and the most critical anatomical regions in terms of tissue loads were in a good accordance with clinical evidence. Altogether, results showed that decreasing femoral or acetabular anteversion angles isolately causes a dramatic increase in cartilage loads.

JTD Keywords: Hip arthritis, Neck shaft angle, Femoral and acetabular anteversions, Cartilage load, Hip joint contact, Finite element analysis

Classification algorithms with unbalanced datasets tend to produce high predictive accuracy over the majority class, but poor predictive accuracy over the minority class. This problem is very common in biomedical data mining. This paper introduces a Support Vector Machine (SVM)-based optimized feature selection method, to select the most relevant features and maintain an accurate and well-balanced sensitivity–specificity result between unbalanced groups. A new metric called the balance index (B) is defined to implement this optimization. The balance index measures the difference between the misclassified data within each class. The proposed optimized feature selection is applied to the classification of patients' weaning trials from mechanical ventilation: patients with successful trials who were able to maintain spontaneous breathing after 48 h and patients who failed to maintain spontaneous breathing and were reconnected to mechanical ventilation after 30 min. Patients are characterized through cardiac and respiratory signals, applying joint symbolic dynamic (JSD) analysis to cardiac interbeat and breath durations. First, the most suitable parameters (C+,C−,σ) are selected to define the appropriate SVM. Then, the feature selection process is carried out with this SVM, to maintain B lower than 40%. The best result is obtained using 6 features with an accuracy of 80%, a B of 18.64%, a sensitivity of 74.36% and a specificity of 82.42%.

JTD Keywords: Support vector machines, Balance index, Sensitivity-specificity balance, Cardiorespiratory interaction, Joint symbolic dynamics, Feature selection, Weaning procedure

The design of mechanical joints that kinematically behave as their biological counterparts is a challenge that if not addressed properly can cause inadequate forces transmission between robot and patient. This paper studies the interaction forces in rehabilitation therapies of the elbow joint. To measure the effect of orthosis-patient misalignments, a force sensor with a novel distributed architecture has been designed and used for this study. A test-bed based on an industrial robot acting as a virtual exoskeleton that emulates the action of a therapist has been developed and the interaction forces analyzed.

JTD Keywords: Force, Force measurement, Force sensors, Joints, Medical treatment, Robot sensing systems, Force sensors, Medical robotics, Patient rehabilitation, Biological counterparts, Distributed architecture, Elbow joint, Force sensor, Inadequate forces transmission, Industrial robot, Mechanical joints design, Orthosis-patient misalignments, Patient-orthosis interaction forces, Rehabilitation therapies, Robot, Test-bed, Virtual exoskeleton

This paper presents a novel teleoperation paradigm, the Virtual Robot (VR), focused on facilitating the surgeon tasks in minimally invasive robotic surgery. The VR has been conceived to increase the range of applicability of traditional master slave teleoperation architectures by means of an automatic cooperative behavior that assigns the execution of the ongoing task to the most suitable robot. From the user's point of view, the VR internal operation must be automatic and transparent. A set of evaluation indexes have been developed to obtain the suitability of each robot as well as an algorithm to determine the optimal instant of time to execute a task transfer. Several experiments demonstrate the usefulness of the VR, as well as indicates the next steps of the research.

JTD Keywords: Cameras, Collision avoidance, Indexes, Joints, Robots, Surgery, Trajectory, Medical robotics, Surgery, Telerobotics, VR internal operation, Automatic cooperative behavior, Evaluation indexes, Master slave teleoperation architectures, Minimally invasive robotic surgery, Task transfer, Virtual robot

Most exoskeleton designs rely on structures and mechanical joints that do not guarantee the right match between the orthosis and the user. This paper proposes a virtual joint model based on three active degrees of freedom aimed to emulate a human joint. This joint is capable of performing a dynamic servo-adaptation in real-time to avoid misalignments and to provide a flexible adjustment to different users' sizes in order to avoid undesirable interaction forces.

JTD Keywords: Actuators, Elbow, Exoskeletons, Joints, Knee, Medical treatment

Traditional time-domain techniques of data analysis are often not sufficient to characterize the complex dynamics of the cardiorespiratory interdependencies during the weaning trials. In this paper, the interactions between the heart rate (HR) and the breathing rate (BR) were studied using joint symbolic dynamic analysis. A total of 133 patients on weaning trials from mechanical ventilation were analyzed: 94 patients with successful weaning (group S) and 39 patients that failed to maintain spontaneous breathing (group F). The word distribution matrix enabled a coarse-grained quantitative assessment of short-term nonlinear analysis of the cardiorespiratory interactions. The histogram of the occurrence probability of the cardiorespiratory words presented a higher homogeneity in group F than in group S, measured with a higher number of forbidden words in group S as well as a higher number of words whose probability of occurrence is higher than a probability threshold in group S. The discriminant analysis revealed the best results when applying symbolic dynamic variables. Therefore, we hypothesize that joint symbolic dynamic analysis provides enhanced information about different interactions between HR and BR, when comparing patients with successful weaning and patients that failed to maintain spontaneous breathing in the weaning procedure.

JTD Keywords: Dynamical nonlinearities analysis, Cardiorespiratory interdependencies, Joint symbolic dynamic, Weaning procedure

The process of discontinuing mechanical ventilation is called weaning and is one of the most challenging problems in intensive care. An unnecessary delay in the discontinuation process and an early weaning trial are undesirable. This study aims to characterize the respiratory pattern through features that permit the identification of patients' conditions in weaning trials. Three groups of patients have been considered: 94 patients with successful weaning trials, who could maintain spontaneous breathing after 48 h ( GSucc ); 39 patients who failed the weaning trial ( GFail ) and 21 patients who had successful weaning trials, but required reintubation in less than 48 h ( GRein ). Patients are characterized by their cardiorespiratory interactions, which are described by joint symbolic dynamics (JSD) applied to the cardiac interbeat and breath durations. The most discriminating features in the classification of the different groups of patients ( GSucc , GFail and GRein ) are identified by support vector machines (SVMs). The SVM-based feature selection algorithm has an accuracy of 81% in classifying GSucc versus the rest of the patients, 83% in classifying GRein versus GSucc patients and 81% in classifying GRein versus the rest of the patients. Moreover, a good balance between sensitivity and specificity is achieved in all classifications.

JTD Keywords: Mechanical ventilation, Weaning, Support vector machines, Joint symbolic dynamics