• Analysis of neural signals. Oscillatory neural activity reflects the functional brain architecture in real time. Different pathologies, such as Alzheimer Disease, mild cognitive impairment or schizophrenia, modify brain dynamics. This research line is focused on exploring the alterations in the neural activity associated to the previous pathologies, with a threefold purpose:
• To explore the communication and processing mechanisms of neural information. 
• To identify potential biomarkers. 
• To assess the effectiveness of non-pharmacologic treatments.
  

In order to accomplish these aims, electroencephalographic (EEG) and magnetoencephalographic (MEG) signals are analyzed by means of different advanced signal processing techniques: spectral and nonlinear methods, neural coupling measures and parameters from complex network theory.

• Analysis of polysomnographic signals. Polysomnography is the main source of information to investigate sleep. The automatic analysis of nocturnal cardiorespiratory signals is a very useful approach to detect illnesses such as Sleep Apnea-Hypopnea Syndrome (SAHS) as well as Chronic Obstructive Pulmonary Disease (COPD). The GIB has developed methods to help in their diagnosis by conducting:
• Spectral, non-linear, and time-frequency analyses applied to polysomnographic recordings. 
• Machine-learning model building to automatically predict diseases machine learning.'
• Our research is focused on both adult and children patients. Moreover, we are encouraged in the promotion of interdisciplinary national partnerships in Spain (Hospital Universitario Rio Hortega, Hospital Universitario de Burgos) as well as international collaborations (Charité Universitatsmedizin Berlin, Pritzker School of Medicine of the University of Chicago).

• Brain-Computer Interface systems. Brain-Computer Interface systems (BCI) allow users to control applications using their own brain signals. The main motivation of the BCI systems is focused on increasing the quality of life of those who have a motor disability that limits their ability to communicate by developing asistive applications. In fact, the Biomedical Engineering Group have developed the following projects:
• Domotic control application. 
• Cognitive training platform. 
• Asynchronous web browser application.
  

It is also important to develop and test new real-time signal processing methodologies that favor the generalization and the performance of these systems.