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
Titolo: | Simple and efficient methods for steady state visual evoked potential detection in BCI embedded system |
Autori: | |
Data di pubblicazione: | 2014 |
Serie: | |
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 solutions |
Handle: | http://hdl.handle.net/11381/2767529 |
Appare nelle tipologie: | 4.1b Atto convegno Volume |
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