on 12-12-2023
Brain-computer interfaces (BCIs) are a novel means of human-computer interaction relying on the direct measurement of brain signals. Possible applications consist of replacing, restoring, improving, enhancing, and supplementing the natural outputs of the central nervous system, as well as for brain functions investigation. In considering daily-life constraints, researchers are exploring the possibility of integrating extended reality (XR) and electroencephalography (EEG). Nevertheless, those studies were more application-oriented and they did not deal with a metrological characterization of the stimulation and detection equipment.
In this 1-hour webinar, we will analyse the importance of a metrological characterization in investigating the harmonic components of visually-evoked brain potentials. This will be done by discussing methods for characterizing the different blocks of a neural interface.
Bio
Antonio Esposito received his MSc degree in electronic engineering at the University of Naples Federico II (Italy) in 2017 and the Ph.D. in Metrology at Polytechnic of Turin (Italy) in 2022 with a doctoral thesis on “Instrumentation for daily-life brain-computer interfaces: applied metrology for assistive devices relying on steady-state visually evoked potentials and motor imagery”.
He has been working with visually evoked potentials elicited through extended reality glasses and he participated in the development of a prototype for industrial and healthcare applications. Currently, he also investigates neurofeedback for motor imagery-based interfaces in telerehabilitation with a focus on neurodegenerative diseases.
Antonio was designated “Distinguished Lecturer 2023-2025” for the Instrumentation and Measurement Society of IEEE on the topic “Applied metrology for novel human-computer interactions” and he is the Operational Chair of the IEEE MetroXRAINE International Conference.
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