Sentence examples for motor imagery data from inspiring English sources
In this paper, the applications of our method focused on the most popular motor imagery BCI task: the discrimination between right and left hand motor imagery data.
As this study focuses on the two-class (right vs. left hand) problem, it is difficult to compare with BCI competition winners' results (reported based on a four-class problem including tongue and feet motor imagery data) on this dataset.
As the standard evaluation procedures for motor imagery data contained counter measures already (channel rejection and trial rejection based on variance), and the number of training data was considerably large, the overall influence of artifacts on the motor imagery data set probably was small.
The authors thank Martijn Schreuder for his help with recording and preparing the auditory ERP data set, Claudia Sannelli for her help with recording and preparing the RT EEG data set, the authors of [ 33] for providing the motor imagery data set.
This dataset consists of two classes (left vs. right hand) cue-driven motor imagery BCI data from nine subjects.
We apply our method for localizing brain areas involved in different types of motor imagery using real data from Brain Computer Interface (BCI) sessions.
Let us mention that four electrodes (two bipolar channels) are the smallest set of electrodes required for a good performance in left vs. right hand motor imagery discrimination on these data.
In this study, 13 subjects performed tasks of right-hand, right-foot or left-hand movement and motor imagery when EEG and fMRI data were separately collected.
For seven users, previous data with motor imagery performance was available which revealed which two motor imagery tasks should be used.
On data of the motor imagery paradigm, we demonstrate that the discriminant information used for BCI is preserved when removing up to 60% of the most artifactual source components.
In this context, we sought to determine whether we can extract discriminatory error-related activity in the source space, online, and on a trial by trial basis from electroencephalography data recorded during motor imagery.
