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 investigation of brain functions. In considering daily-life constraints, researchers are exploring the possibility to provide visual stimuli by means of smart glasses or visors, which are increasingly exploited in extended reality (XR). Moreover, to detect the elicited potential, commercial devices for electroencephalography (EEG) are considered. Nevertheless, those studies were more application-oriented, and they did not deal with a metrological characterization of stimulation and detection equipment.
In bridging this gap, applied metrology was considered for a significant enhancement of the BCI systems both in terms of designing and in operational understanding. It was demonstrated that, although often overlooked, metrological characterization plays an important role in this field. Indeed, if the stimulation and detection equipment is not fully characterized, the measures of interest for the brain-computer interface system may result in misleading interpretation of the brain functioning. Instead, by means of the mentioned results, one can compare the measured brain signals with the behavior of the equipment in the time and frequency domains, so as to correctly identify the contribution of the “human transducer” in the BCI measurement chain. This was particularly applied to the investigation of amplitude spectra for generated stimuli and latency measurement related to EEG acquisitions.
