These results suggest that the performance of muscle artifact correction methods strongly depend on the level of data contamination, and of the source configuration underlying EEG signals.
Since our study demonstrates that the performance of muscle artifact correction methods significantly depend on the level of data contamination, and of the source configuration underlying EEG signals, the four algorithms may also perform differently on other type of data.
The performance of the artifact detection strategy is demonstrated on real single-trial EP ensembles and it is shown that the strategy is quite effective in identifying atypical EPs.
In short, the two respondent groups only exhibited notable diversity in their respective opinions on the engineering dimension; the two groups held consistent opinions towards the attractiveness, beauty, creativity, delicacy, and overall performance of the seven artifacts examined (Table 5).
The impact of the latest signal processing techniques and reflectance technology on improving the performance of pulse oximeters during motion artifact and low perfusion conditions is critically examined.
Aesthetic intention consists of the production, presentation, or performance of an aesthetic entity or artifact with conscious regard for its potential for evaluation by another individual.
Since three separate correction techniques are proposed here for the three types of artifacts, the overall performance of the correction algorithm is certainly improved.
If the low-resolution images are undersampled and have aliasing artifacts, the performance of standard registration algorithms decreases.
To estimate the influence of the artifact reduction step on BCI performance, we compared the classification performance with artifact reduction (depending on the number of selected sources) with the standard CSP procedure using no artifact reduction.
