Current Research projects:
PSADAS: Patient Specific Advanced Driver Assisted Systems
Driving performance dramatically worsens in those people suffering Parkinsons Disease (PD). This neurological disease involves functional lacks that can endanger the ability to drive since the disease includes motor and cognitive symptoms, and impairment of visual-spatial perception. Our principal goal is to identify the impairments of a PD patient for driving in order to recommend some Patient Specific Advanced Driver Assisted Systems (PSADAS). For that, we will previously develop image processing and computer vision tools for exploring the potential of human behaviour analysis methods (which involves detection and recognition of gestures, pose, face and gaze) and we will extract risk behaviour parameters. These tools will be embedded in a simulator platform which will serve to assess the ability to drive of PD patients by means of a simulated driving exam.
Finished Research projects:
MIOCARDIA: Definition of an integrated model of the Functionality and Muscular Anatomy of the Left Ventricle
The Left Ventricle (LV) dynamics (motion and deformation) reflects, to a major or minor extend, most of the cardiovascular diseases and, thus, plays a significant role in their diagnosis and treatment. Recent advances in tomographic devices (such as magnetic resonance or TAC) are generating large volumes of data on dynamic processes, which have encourage, in the last years, development of 3D computational models of LV dynamics.
This project addresses the development of an Integrative Model of the Functionality and Muscular Anatomy of the Left Ventricle merging the 3D motion (functionality) with the spatial disposition of the muscular band (anatomy) and allowing the estimation of the electromechanical activation sequence for each patient.
Arterial Dynamics and Structures in IntraVascular Ultrasound Sequences
IntraVascular UltraSound (IVUS) has become a usual imaging technique for the diagnosis and follow up of arterial diseases. IVUS is a catheter-based imaging technique which shows a sequence of cross sections of the artery under study. Inspection of a single image gives information about the percentage of stenosis. Meanwhile, inspection of longitudinal views provides information about artery bio-mechanical properties, which can prevent a fatal outcome of the cardiovascular disease.
This project proposes several image processing tools for exploring vessel dynamics and structures by means of IVUS Sequences processing: a physics-based model to extract, analyze and correct vessel in-plane rigid dynamics and to retrieve cardiac phase and a deterministic-statistical method for automatic vessel borders detection.