Journal ArticleDOI
Application of a reconstruction technique in detection of dominant SSVEP frequency
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TLDR
The results show that the RE method can be adopted in a real-time SSVEP-based brain–computer interface (BCI) system, and the detection accuracy is similar to the CCA method, although it is higher than that of the PS method in situations where theSSVEP has low strength.About:
This article is published in Biomedical Signal Processing and Control.The article was published on 2018-02-01. It has received 3 citations till now.read more
Citations
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Journal ArticleDOI
Multiscale noise suppression and feature frequency extraction in SSVEP based on underdamped second-order stochastic resonance.
Pulin Yao,Guanghua Xu,Linshan Jia,Jinjin Duan,Chengcheng Han,Tangfei Tao,Yi Wang,Sicong Zhang +7 more
TL;DR: A novel method based on underdamped second-order stochastic resonance (USSR) is proposed, which effectively improves the information transmission rate (ITR) of SSVEP-based BCI and is compared with the widely-used canonical coefficient analysis and multivariate synchronization index.
Journal ArticleDOI
Detection of SSVEP based on empirical mode decomposition and power spectrum peaks analysis
TL;DR: A novel method for the detection of SSVEP that combines the empirical mode decomposition (EMD) and a power spectral peak analysis (PSPA) is proposed that was evaluated with two EEG datasets, and was compared with the widely used FB and CCA.
Proceedings ArticleDOI
A brain computer interface control system based on cloud platform for Minitype UAVs
TL;DR: A design scheme that the brain controls UAVs system based on cloud platform using brainwaves collected by visual evoked and a fixed encoding format is used to control the flight of the aircraft.
References
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Journal ArticleDOI
Brain-computer interfaces for communication and control.
Jonathan R. Wolpaw,Jonathan R. Wolpaw,Niels Birbaumer,Niels Birbaumer,Dennis J. McFarland,Gert Pfurtscheller,Theresa M. Vaughan +6 more
TL;DR: With adequate recognition and effective engagement of all issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
Journal ArticleDOI
Brain-computer interfaces for communication and control
TL;DR: The brain's electrical signals enable people without muscle control to physically interact with the world through the use of their brains' electrical signals.
Journal ArticleDOI
Steady-state visually evoked potentials: focus on essential paradigms and future perspectives.
TL;DR: The steady-state evoked activity, its properties, and the mechanisms behind SSVEP generation are investigated and future research directions related to basic and applied aspects of SSVEPs are outlined.
Journal ArticleDOI
Frequency Recognition Based on Canonical Correlation Analysis for SSVEP-Based BCIs
TL;DR: A recognition approach is proposed based on the extracted frequency features for an SSVEP-based brain computer interface (BCI) that were higher than those using a widely used fast Fourier transform (FFT)-based spectrum estimation method.
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.