Electroencephalography (EEG) from scalp potentials is of crucial importance both as a diagnostic and brain imaging tool and as the key technology for developing Brain Computer Interfaces (BCIs). However, the fundamental difference between these two application scenarios is that while in imaging/diagnostics, EEG-related computations can be potentially done offline, i.e. after the EEG scalp measuring, for BCI applications the majority of EEG imaging computation must be done runtime since an immediate feedback is required. As a consequence, this rules out some powerful and highly resolving, but computational expensive techniques that can be used in EEG brain imaging, but become unaffordable in a BCI contest. This is highly lamentable and unfortunate given that higher resolution imaging has been proved to give rise to better performing BCIs.

SABRE will focus on filling this gap and in making available runtime techniques that are usually affordable only by relying on offline computations. The idea to achieve this is based on a double-sided investigation strategy:

  • On one hand SABRE will investigate innovative EEG solution methods that will operate in linear-instead-of-cubic complexity with respect to the physical degrees of freedom. This will already result in huge savings in terms of computational time and complexity. 
  • On the other hand these EEG solution methods will further be empowered and speeded-up by ad-hoc, transistor-level, implementations of their key algorithmic operations.

In other words, in a synergy between a computational and on-chip hardware research expertise, a completely new family of fully-hardware-integrated, new computational EEG imaging methods will be developed that are expected to speed up the imaging process of an EEG device of several orders of magnitude in real case scenarios. This will be the enabling technology for runtime applications of highly resolving EEG approaches in BCI.

This notwithstanding, this project will implement and validate the new EEG technology within a cutting edge BCI environment. A leading research expertise in the field will investigate and develop an ad-hoc, but user-ready, BCI framework that will ensure convincing evidences of practical relevance of the new EEG technology at each and every stage of its development. In other words the final outcome of this project will be a fully functioning, deeply innovative, and user-ready BCI technology that will be entirely and convincingly validated both as of performance and applicability in cutting-edge BCI real case scenarios.