Sergio Romero Lafuente
Investigador
Sergio Romero has been an industrial engineer with a speciality in Automation from the Polytechnic University of Catalonia (UPC) since 2000. In 2010, he obtained his doctorate with a Cum Laude qualification in Biomedical Engineering with the thesis entitled "Reduction of artifacts in electroencephalographic signals using new automatic filtering techniques based on blind source separation. "
In 2001, he joined the UPC as a part-time associate professor, while he joined the Superior Research Technician at the Medicines Research Center (CIM) of the Research Institute of the Hospital de Sant Pau in Barcelona, providing technical support mainly for biomedical signal processing and statistical analysis. During this stage he gained experience in the management of clinical trials, forming part of a large multidisciplinary team. Since 2005 he has been a full-time professor at the UPC, with the category of Associate Professor since 2011.
Her research focuses on the analysis of signals of cerebral origin (EEG / MEG) with the aim of helping the diagnosis and improving the treatment, whether pharmacological or not, of different neurodegenerative diseases. Since 2000, he has participated as a researcher in many projects (around 25) financed by public and private entities.
Related websites
Centre de Recerca en Enginyeria Biomèdica (CREB) UPC 
FUTUR UPC Last Publications
- Tost A, Migliorelli C, Bachiller A, Medina-Rivera IF, Romero S, Garcia-Cazorla A and Mañanas MA Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment ENTROPY . 23(8): 1030.
- Migliorelli C, Bachiller A, Alonso Lopez JF, Romero S, Aparicio J, Jacobs J, Mañanas MA and San Antonio-Arce MV SGM: a novel time-frequency algorithm based on unsupervised learning improves high-frequency oscillation detection in epilepsy. JOURNAL OF NEURAL ENGINEERING . 17(2): 26032-26032.
- Migliorelli C, Bachiller A, Andrade AG, Alonso Lopez JF, Mañanas MA, Borja C, Giménez S, Antonijoan RM, Varga AW, Osorio RS and Romero S Alterations in EEG connectivity in healthy young adults provide an indicator of sleep depth. Sleep . 42(6): .