Sentence examples for eeg sampling from inspiring English sources

The monitor responded with a delay of 48 ms (first deviation from noise, standard deviation less than the EEG sampling interval of 2 ms).

The EEG sampling rate was set to 500 Hz.

Intracranial EEG sampling was guided by analysis of seizure symptoms, fluorodeoxyglucose-PET and MEG data.

Using the EEG sampling rate, we calculated the FFT size necessary for a resolution of 0.5 Hz and selected the nearest higher FFT size available in LabChart.

As stated in the previous section, a P300 detection algorithm built in the BCI2000 system was simply to employ EEG sampling data as the features used for the P300 detection.

Such behavior means that there is a high temporal correlation between a given EEG sample and neighboring EEG samples as well as some relatively distant EEG samples.

A feature vector, consisting of five designated EEG samples (close to the 300 ms) and the correlation coefficient (i.e., the similarity) was used (N = 6).

McSharry et al. [8] discussed and enumerated the nonlinear methods and its relevance to predict epilepsy by considering EEG samples as time series.

Considering (2), we set feature values F1 ~ F5 to the EEG samples as well as F6 to the correlation coefficient R measured between the EEG segment and the P300 template.

Unfortunately, the detection rate did not satisfactorily reach to a sufficiently high accuracy level, thus implying that features directly selected from the raw EEG sample data might be inadequate for such a detection problem.

The features in each vector were EEG samples (sampled at 256 Hz), therefore the number of features in each vector varied as a function of the size of the temporal window, and the number of electrode sites included in the vector.