A dynamic selection method for reference electrode in SSVEP-based BCI.
In SSVEP-based Brain-Computer Interface (BCI), it is very important to get an evoked EEG with a high signal to noise ratio (SNR). The SNR of SSVEP is fundamentally related to the characteristics of stimulus, such as its intensity and frequency, and it is also related to both the reference electrode...
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doaj-d87c0f6316be4408b6966007cd0ae0592021-03-03T20:13:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0198e10424810.1371/journal.pone.0104248A dynamic selection method for reference electrode in SSVEP-based BCI.Zhenghua WuSheng SuIn SSVEP-based Brain-Computer Interface (BCI), it is very important to get an evoked EEG with a high signal to noise ratio (SNR). The SNR of SSVEP is fundamentally related to the characteristics of stimulus, such as its intensity and frequency, and it is also related to both the reference electrode and the active electrode. In the past, with SSVEP-based BCI, often the potential at 'Cz', the average potential at all electrodes or the average mastoid potential, were statically selected as the reference. In conjunction, a certain electrode in the occipital area was statically selected as the active electrode for all stimuli. This work proposed a dynamic selection method for the reference electrode, in which all electrodes can be looked upon as active electrodes, while an electrode which can result in the maximum sum relative-power of a specific frequency SSVEP can be confirmed dynamically and considered as the optimum reference electrode for that specific frequency stimulus. Comparing this dynamic selection method with previous methods, in which 'Cz', the average potential at all electrodes or the average mastoid potential were selected as the reference electrode, it is demonstrated that the SNR of SSVEP is improved significantly as is the accuracy of SSVEP detection.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25100038/?tool=EBI |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhenghua Wu Sheng Su |
spellingShingle |
Zhenghua Wu Sheng Su A dynamic selection method for reference electrode in SSVEP-based BCI. PLoS ONE |
author_facet |
Zhenghua Wu Sheng Su |
author_sort |
Zhenghua Wu |
title |
A dynamic selection method for reference electrode in SSVEP-based BCI. |
title_short |
A dynamic selection method for reference electrode in SSVEP-based BCI. |
title_full |
A dynamic selection method for reference electrode in SSVEP-based BCI. |
title_fullStr |
A dynamic selection method for reference electrode in SSVEP-based BCI. |
title_full_unstemmed |
A dynamic selection method for reference electrode in SSVEP-based BCI. |
title_sort |
dynamic selection method for reference electrode in ssvep-based bci. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2014-01-01 |
description |
In SSVEP-based Brain-Computer Interface (BCI), it is very important to get an evoked EEG with a high signal to noise ratio (SNR). The SNR of SSVEP is fundamentally related to the characteristics of stimulus, such as its intensity and frequency, and it is also related to both the reference electrode and the active electrode. In the past, with SSVEP-based BCI, often the potential at 'Cz', the average potential at all electrodes or the average mastoid potential, were statically selected as the reference. In conjunction, a certain electrode in the occipital area was statically selected as the active electrode for all stimuli. This work proposed a dynamic selection method for the reference electrode, in which all electrodes can be looked upon as active electrodes, while an electrode which can result in the maximum sum relative-power of a specific frequency SSVEP can be confirmed dynamically and considered as the optimum reference electrode for that specific frequency stimulus. Comparing this dynamic selection method with previous methods, in which 'Cz', the average potential at all electrodes or the average mastoid potential were selected as the reference electrode, it is demonstrated that the SNR of SSVEP is improved significantly as is the accuracy of SSVEP detection. |
url |
https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25100038/?tool=EBI |
work_keys_str_mv |
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