Journal ArticleDOI
A novel multiple frequency stimulation method for steady state VEP based brain computer interfaces
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This paper discusses a method to increase the number of commands by using a suitable combination of frequencies for stimulation using a limited number of stimulating frequencies in BCI.Abstract:
The objective is to increase the number of selections in brain computer interfaces (BCI) by recording and analyzing the steady state visual evoked potential response to dual stimulation. A BCI translates the VEP signals into user commands. The frequency band from which stimulation frequency can be selected is limited for SSVEP. This paper discusses a method to increase the number of commands by using a suitable combination of frequencies for stimulation. A biopotential amplifier based on the driven right leg circuit (DRL) is used to record 60 s epochs of the SSVEP (O(z)-A(1)) on 15 subjects using simultaneous overlapped stimulation (6, 7, 12, 13 and 14 Hzs and corresponding half frequencies). The power spectrum of each recording is obtained by frequency domain averaging of 400 ms SSVEPs and the spectral peaks were normalized. The spectral peaks of the combination frequencies of stimulation are predominant compared to individual stimulating frequencies. This method increases the number of selections by using a limited number of stimulating frequencies in BCI. For example, six selections are possible by generating only three frequencies.read more
Citations
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Journal ArticleDOI
Development of an SSVEP-based BCI spelling system adopting a QWERTY-style LED keyboard.
TL;DR: Through preliminary offline experiments and online experiments, it is confirmed that human SSVEPs elicited by visual flickering stimuli with a frequency resolution of 0.1 Hz could be classified with classification accuracy high enough to be used for a practical brain-computer interface (BCI) system.
Journal ArticleDOI
Multivariate synchronization index for frequency recognition of SSVEP-based brain-computer interface.
TL;DR: A novel multivariate synchronization index (MSI) for frequency recognition was proposed and showed better performance than the widely used canonical correlation analysis (CCA) and minimum energy combination (MEC), especially for short data length and a small number of channels.
Journal ArticleDOI
Multiple Frequencies Sequential Coding for SSVEP-Based Brain-Computer Interface
TL;DR: The current study shows that MFSC is feasible and efficient; the performance of SSVEP-based BCI based on MFSC can be comparable to some existed systems; and it is proposed that the SSVEp-basedBCI under MFSC might be a promising choice in the future.
Journal ArticleDOI
Effect of higher frequency on the classification of steady-state visual evoked potentials.
Dong-Ok Won,Han-Jeong Hwang,Sven Dähne,Klaus-Robert Müller,Klaus-Robert Müller,Seong-Whan Lee +5 more
TL;DR: The results suggest that the use of higher frequency visual stimuli is more beneficial for performance improvement and stability as time passes when developing practical SSVEP-based BCI applications.
Journal ArticleDOI
LASSO based stimulus frequency recognition model for SSVEP BCIs
TL;DR: This study proposes a LASSO model using the linear regression between electroencephalogram recordings and the standard square-wave signals of different frequencies to recognize SSVEP without the training stage and can assist to reduce the recording time without sacrificing the classification accuracy.
References
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Book
Medical instrumentation: Application and design
TL;DR: Basic Concepts of Medical Instrumentation (W. Olson).
Book
Human Brain Electrophysiology: Evoked Potentials and Evoked Magnetic Fields in Science and Medicine
TL;DR: In this article, the authors propose an approach to explore the potential of PE in the context of neurophysiologie and psychophysics, and propose a set of criteria for evaluating the applicability of PE.
Journal ArticleDOI
Design and implementation of a brain-computer interface with high transfer rates
TL;DR: A brain-computer interface that can help users to input phone numbers based on the steady-state visual evoked potential (SSVEP), which has noninvasive signal recording, little training required for use, and high information transfer rate.
Journal ArticleDOI
Brain-computer interfaces based on the steady-state visual-evoked response
TL;DR: The Air Force Research Laboratory has implemented and evaluated two brain-computer interfaces that translate the steady-state visual evoked response into a control signal for operating a physical device or computer program.