Simple and efficient methods for steady state visual evoked potential detection in BCI embedded system

Author

Mora, Nicolas ; Bianchi, Valentina ; De Munari, Ilaria ; Ciampolini, P.

Author_Institution

Inf. Eng. Dept., Univ. of Parma, Parma, Italy

fYear

2014

fDate

4-9 May 2014

Firstpage

2044

Lastpage

2048

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.

Keywords

brain-computer interfaces; embedded systems; reliability; visual evoked potentials; BCI embedded modules; SSVEP processing algorithms; brain computer interfaces; calibration-free operation; communication paths; computational efficiency; reliability; steady state visual evoked potential detection; user brain activity; Accuracy; Algorithm design and analysis; Classification algorithms; Electrodes; Electroencephalography; Signal processing; Signal processing algorithms; AMCC; Brain Computer Interface (BCI); CCA; MEC; SSVEP;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on

Conference_Location

Florence

Type

conf

DOI

10.1109/ICASSP.2014.6853958

Filename

6853958