Brain Computer Interfaces (BCI) can provide severely impaired users with alternative communication paths, by means of interpretation of the user's brain activity. Among BCI operating paradigms, SSVEP is largely exploited for its potentially high throughput and reliability. In this paper, two novel SSVEP processing algorithms are presented, focused on calibration-free operation and computational efficiency, targeted for development of BCI embedded modules. A comparison with other popular SSVEP signal processing algorithm (MEC, AMCC, CCA) is also made; results demonstrate the feasibility and effectiveness of the proposed solutions
Simple and efficient methods for steady state visual evoked potential detection in BCI embedded system / Mora, Niccolo'; Bianchi, Valentina; DE MUNARI, Ilaria; Ciampolini, Paolo. - 1:(2014), pp. 2044-2048. (Intervento presentato al convegno IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) tenutosi a Firenze nel May 4-9, 2014) [10.1109/ICASSP.2014.6853958].
Simple and efficient methods for steady state visual evoked potential detection in BCI embedded system
MORA, Niccolo';BIANCHI, Valentina;DE MUNARI, Ilaria;CIAMPOLINI, Paolo
2014-01-01
Abstract
Brain Computer Interfaces (BCI) can provide severely impaired users with alternative communication paths, by means of interpretation of the user's brain activity. Among BCI operating paradigms, SSVEP is largely exploited for its potentially high throughput and reliability. In this paper, two novel SSVEP processing algorithms are presented, focused on calibration-free operation and computational efficiency, targeted for development of BCI embedded modules. A comparison with other popular SSVEP signal processing algorithm (MEC, AMCC, CCA) is also made; results demonstrate the feasibility and effectiveness of the proposed solutionsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
