Title :
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
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;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
DOI :
10.1109/ICASSP.2014.6853958
