Your English writing platform
Discover LudwigSimilar(60)
In this paper we aim to classify the finger-, elbow- and shoulder-classification along with left- and right-hand classification to move a simulated robot arm in 3D space towards a target of known location.
Table 1 shows frequency bands chosen to build off-line classifiers and the corresponding classification accuracy between the right hand MI and the baseline.
This can be seen on the right hand side of Figure 2, where more accurate classification was obtained when the fraction-size information was combined with disease information.
Li et al. [67] proposed a method for selecting suitable channels for classification of two motor imagery tasks: right hand and right foot based on a common spatial pattern algorithm as shown in Fig. 12.
We performed classification between the following two tasks: right hand vs left hand, right hand vs feet and left hand vs feet.
Wei and Wang [53] presented a method for channel selection during the classification of motor imagery of left hand, right hand, and foot based on a binary multi-objective particle swarm optimization algorithm.
While CSP classification (on the x-axis) shows a good separability of the data into positive and negative values (for right hand and left hand movement, respectively), the Zero-Training classifier assigns negative values to almost every point, resulting in a poor classification rate (near 50%, corresponding to chance level accuracy).
Right hand, left hand.
Like my right hand.
"I thought, 'Right hand?
Right hand, thwock!
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com