Within every heartbeat, breath and thought, there is a secret story told by biosignals. These signals hide information about how human beings respond internally to the various external stimuli to which they are subjected. Thanks to technological innovation, we can now decode this information using sensors and devices in a wide range of contexts, from clinical conditions, such as mental health, to daily physical activity. This seminar aims to introduce biosignals and their analysis, demonstrating how they can be used in the investigation of psychophysiological phenomena and processes. Using examples from literature and projects developed at the Laboratory of Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys), the presentation will address the fundamental principles of biosignals, emphasizing their importance and meaning. Potential applications and challenges in the field of psychology will also be explored, such as recognizing emotions, assessing mental health and measuring stress in everyday situations. The presentation will draw on relevant concepts and methods from the areas of engineering, neuroscience and psychology, offering an interdisciplinary approach to the study of biosignals.
Bibliographic references:
Carrle, F. F., Hollenbenders, Y., & Reichenbach, A. (2023). Generation of synthetic EEG data for training algorithms supporting the diagnosis of major depressive disorder. Frontiers. Advance online publication. https://doi.org/10.3389/fnins.2023.1219133
Freismuth, D., & TaheriNejad, N. (2022). On the treatment and diagnosis of attention deficit hyperactivity disorder with EEG Assistance. Electronics, 11(4), 606.
https://doi.org/10.3390/electronics11040606
Ancillon, L., Elgendi, M., & Menon, C. (2022). Machine Learning for Anxiety Detection Using Biosignals: A Review. Diagnostics, 12(8), 1794. https://doi.org/10.3390/diagnostics12081794