Sabino Guglielmini is a doctoral student at the Department of Information Technology and Electrical Engineering, ETHZ. He obtained his master’s degree in Computer Science with a specialization in Computational Intelligence at the University of Salerno (UNISA, Italy) in March 2018. Sabino carried out his master’s thesis as visiting student, on the reduction of false alarm rates in neonatal intensive care units using machine learning techniques, at the Biomedical Optics Research Laboratory (BORL), University Hospital Zurich where he has been working since May 2018. His project, Systemic Physiology Augmented functional Near-Infrared Spectroscopy (SPA-fNIRS) hyperscanning, aims the use of EEG, fNIRS and systemic physiological signals to determine synchronization between brain and body activity of interacting subjects. His research interests include biomedical signal processing, neuroinformatics, and machine learning.
Functional near-infrared imaging (fNIRI) hyperscanning is a promising new method able to asses the brain-to-brain coupling during different inter-personal interactions tasks. fNIRI is an optical neuroimaging method that is able to non-invasively measure changes in cerebral oxygenation and haemodynamics in humans while having the advantages of being easily applicable in a natural context and enabling the measurement of physiological signals that cannot be derived by the classical neuroimaging methods such as functional magnetic resonance imaging (fMRI) or electroencephalography (EEG). My project aims to advance fNIRI hyperscanning approach and in particular investigate the quantitative role and relevance of the different communication channels.