2013 36th International Conference on Telecommunications and Signal Processing (TSP) 2013
DOI: 10.1109/tsp.2013.6614018
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A comparison of success and time consumption of the most common methods for detection of the SSVEP

Abstract: The steady state visual evoked potential (SSVEP) is one of the most discussed method for the brain computer interface (BCI). In this paper, performance of the online SSVEP detection methods was compared. Two parametric and two nonparametric algorithms were used: the classical power spectrum estimation method (PS), the power spectrum estimation using the AR model, the canonical correlation analysis (CCA) and the continuous wavelet transform (CWT). The success of the SSVEP detection and the time consumption of e… Show more

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Cited by 3 publications
(2 citation statements)
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“…Several methods were proposed for SSVEP detection such as power spectral density analysis (PSDA), time domain analysis, Hilbert Huang transform (HHT), autoregressive model (AR model), Wavelet transform and canonical correlation analysis (CCA) [5]- [9]. Both CCA and PSDA are the most widely used frequency detection method in SSVEP-based BCIs and have better performance on SSVEP detection [9].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Several methods were proposed for SSVEP detection such as power spectral density analysis (PSDA), time domain analysis, Hilbert Huang transform (HHT), autoregressive model (AR model), Wavelet transform and canonical correlation analysis (CCA) [5]- [9]. Both CCA and PSDA are the most widely used frequency detection method in SSVEP-based BCIs and have better performance on SSVEP detection [9].…”
Section: Introductionmentioning
confidence: 99%
“…Both CCA and PSDA are the most widely used frequency detection method in SSVEP-based BCIs and have better performance on SSVEP detection [9]. [10] and [11] reported that CCA method outperforms the PSDA.…”
Section: Introductionmentioning
confidence: 99%