ABSTRACT
Setting low-cost brain computer interfaces (BCIs) has been a topic of interest in developing countries. There is a variety of EEG equipment, and mathematical techniques that can help achieve this goal, but some of these techniques may have some flaws by their own. A low complexity alternative using an OpenBCI optimized equipment and based on two mathematical techniques here is discussed for an ongoing develoment of a low-cost BCI project. The selected techniques for data analysis inspection are linear discriminant analysis (LDA) and multivariate synchronization index (MSI). The procedure will be shown from the basics, the OpenBCI optimized equipment is validated offline against a g.Nautilus EEG and the performance of the techniques is shown individually. Therefore, it is discussed the possibility of combining both feature extraction techniques (LDA and MSI) for steady state visual evoked potentials (SSVEP), in order to achieve a concept with better performance for an SSVEP BCI.
- E. Quiles, G. Candela, Á. Uriel y M. & S. F. Mellado, «Comparación de estrategias de imaginación motora en interfaces cerebro computador: aplicación al control de una pinza neumática,» Cogn. Area Netw., vol. 4, pp. 31--35, 2017.Google Scholar
- J. Shih y D. & W. J. Krusienski, «Brain-Computer Interface in Medicine,» Mayo Clin. Proc., vol. 87, pp. 268--279, 2012.Google ScholarCross Ref
- J. Gutiérrez-Martínez, J. Cantillo-Negrete y R. & E.-V. D. Cariño-Escobar, «Los Sistemas de Interfaz Cerebro-Computadora: Una Herramienta para Apoyar la Rehabilitación de Pacientes con Discapacidad Motora,» vol. 8, pp. 62--69, 2013.Google Scholar
- G. Gentiletti y C. & A. R. Tabernig, «Interfaz Cerebro - Computadora: Estado del Arte y Desarrollo en Argentina,» vol. 13, n° 9, 2007.Google Scholar
- J. & M. D. Proakis, Digital Signal Processing; 4th ed., New York, 2007.Google Scholar
- P. & M. R. Stoica, Spectral Analysis of Signals, Upper Saddle River, N.J.: 2005, 2005.Google Scholar
- Y. Zhang, P. Xu y K. & Y. D. Cheng, «Multivariate Synchronization Index for Frequency Recognition of SSVEP-Based Brain-Computer Interface,» J. Neurosci. Methods, vol. 221, pp. 32--40, 2014.Google ScholarCross Ref
- C. Carmeli, «Assessing cooperative behavior in dynamical networks with applications to brain data,» 2006.Google Scholar
- C. Carmeli, M. Knyazeva y G. & D. F. O. Innocenti, «Assessment of EEG synchronization based on state-space analysis.,» NeuroImage, vol. 25, pp. 339--354, 2005.Google ScholarCross Ref
- A. Joudaki, N. Salehi y M. & K. M. Jalili, «EEG-Based Functional Brain Networks: Does the Network Size Matter?,» PLOS ONE, vol. 7, n° e35673, 2012.Google Scholar
- D. Walker, C. Carmeli, F. Pérez-Barbería y M. & P.-F. E. Small, «Inferring Networks from Multivariate Symbolic Time Series to Unravel Behavioural Interactions Among Animals.,» Anim. Behav., vol. 79, pp. 351--359, 2010.Google ScholarCross Ref
Index Terms
SSVEP Offline Analysis Procedures for Low Cost BCI Systems
Recommendations
Can I Think of Something Else when Using a BCI?: Cognitive Demand of an SSVEP-based BCI
CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing SystemsBCIs are presumably supposed to require the full attention of their users and to lose accuracy if they pay attention to another task. This assertion has been verified with several BCI paradigms (e.g. P300). But the cognitive demand of the promising ...
Augmented control of an avatar using an SSVEP based BCI
AH '12: Proceedings of the 3rd Augmented Human International ConferenceThe demonstration shows the usage of an EEG-based brain-computer interface (BCI) for the real-time control of an avatar in World of Warcraft. Visitors can test the installation during the conference after about 5 minutes of training time. World of ...
Hybrid SSVEP/P300 BCI Keyboard
BIOSTEC 2016: Proceedings of the International Joint Conference on Biomedical Engineering Systems and TechnologiesThis paper presents a two stage Brain Computer Interface (BCI) keyboard system that consumes Electroencephalography (EEG) signals based on two evoked potential detection methods: P300 and Steady-State Visual Evoked Potential (SSVEP). In order to develop ...
Comments