Special Session 1

In developing Passive BCI, the measurand definition is a fundamental issue, because the quantity (e.g., emotion, attention, engagement, stress) is not univocally identified and many relevant theories are incompatible with the adoption of an interval scale (ordered and proportionated). Moreover, experimental reproducibility, as well as cross-subject and within-subject reproducibility are open challenges. In such a context, this special session will host contributions on stimuli standardization procedures aimed to improve experimental reproducibility, psychometry-based methods for sample selection during experimental campaigns, innovative data processing strategies such as domain adaptation and domain generalization, data fusion approaches. Finally, this session aims to discuss the compatibility between the adopted theory for measurand modeling and implemented experimental procedures.

The list of topics includes (but it is not limited to) the following:

• Instrumental solutions and measurement principles for enhancing the accuracy and robustness of BCI systems;
• EEG-based Psychophysical condition monitoring;
• Wearable sensors;
• Accuracy and latency versus wearability;
• Machine learning-based classification;
• Experimental reproducibility enhancement;
• Applications and case-studies.

Dr Naomi du Bois is a Research Associate at Ulster University, Magee campus, with experience in electro- and magneto- encephalography (MEEG) neuroimaging techniques. Her recent research interests are focused on brain-computer interface (BCI) - based solutions to the treatment and management of mental health disorders and cognitive deficits.

Nicola Moccaldi received the M.S. degree in Communication Science at the University of Salerno, the M.Sc. degree in Electronic Engineering and the Ph.D. in Information Technologies and Electrical Engineering at the University of Naples Federico II. His current research interests include biomedical instrumentation and measurement.