Projects

Use the knowledge in digital signal processing and machine learning to develop algorithms that extract relevant information from biomedical signals such as electromiography or electroencephalography. This information is intended to be used to control devices that may be used as rehabilitation or assistive technology.

It is known that different factors such as age, stress, and lifestyle influence cognitive decline. As life expectancy increases, this situation becomes more important, so it is necessary to continue to delve deeper into the understanding of this process. In this sense, the analysis of electroencephalography signals related to cognitive events is very useful, as it provides quantitative information that could be linked to these processes.

Knowing the relationship between brain activity and a continuous external stimulus in healthy people can help to decipher the changes in brain activity in a person with some damage to the neuromuscular system. In this project, the brain activity generated by a mechanical disturbance in the wrist is modeled.   https://doi.org/10.1007/s13246-024-01427-8