Research Areas

  • Artificial intelligence for biomedical and health applications: This line of research is dedicated to the use of artificial intelligence and signal processing for the automatic analysis of biomedical signals, with an emphasis on the investigation of pathological states. Several types of biological registers such as voice, speech, oculographic signals, X-ray images, EGG, etc. are studied in relation to diverse pathological states, in order to better understanding the effect of the pathological processes in the studied biosignal; to design and study objective biomarkers serving to characterize and assess the pathological state and its severity; and to help in decision making procedures in clinical scenarios.
  • Artificial intelligence and signal processing for the evaluation of neurodegenerative disorders:This line of research is dedicated to the use of artificial intelligence techniques to investigate neurodegenerative disorders such as the idiopathic Parkinson's disease and parkinsonisms such as the progressive supranuclear palsy or the multisystemic atrophy. Analyses are carried out in a non-invasive manner from signals recorded from affected patients. A great deal of interest has been put into the design of automatic systems that provide early and differential diagnosis, that serve to improve the diagnostic procedures in the clinics of these pathologies.
  • Artificial intelligence and image processing for the evaluation of COVID-19 disease: This novel and highly relevant line of research is dedicated to the study of computational methodologies for the automatic analysis of COVID-19 using medical images such as x-ray and computer tomography, in order to evaluate the presence of the disease and assess the severity of infection. A great focus of interest is in the interpretability and correlation of the results to the pathological processes present in the COVID-19 infection.
  • Complexity analysis of biomedical signals: This line of research is dedicated to the study of biomedical registers, making use of nonlinear analysis techniques, complexity and/or regularity measures, for the characterization of the underlying complexity of signals. The changes in complexity, considering different groups of registers (for instance controls vs. pathological patients), are then used to provide discrimination between groups and correlate to biological processes. 
  • Radar technology for monitoring biomedical signs in biomedical and health applications: This line of research is dedicated to the novel use of radar technologies for the investigation of different types of health disorders. This technology is used to record different types of biosignals, which are then studied using signal processing and artificial intelligence techniques for characterization and decision making purposes. 
Other lines of research
  • Mobile Services for people with disabilities.
  • Accessible Information Systems with an interface adapted for disabled users.
  • Medical Image Processing.
  • Speech, electrocardiogram and phonocardiogram signal processing. 
  • Light interaction with biological tissues.
  • Training methods in medicine.
  • Data Mining
  • e-Health
  • m-Health
  • Polarimetry with nonuniformly polarized beams
  • Coherence and partially coherent sources

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