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Feature extraction

A project log for Brainmotic

EEG to control a Smart house. Oriented to persons with disabilities.

Daniel Felipe Valencia VDaniel Felipe Valencia V 10/03/2016 at 07:020 Comments

We have begun to ask what signal characteristics we recognize? And we decided to do an analysis of EEG frequencies. But what the waveforms and frequency of status or physical activity of a person say ?. We have found the following:

Author: [1]

Name

frequencies [Hz]

When

alpha

8

13

evident during the absence of visual stimuli

beta

12

30

seen in the frontal region of the brain and are observed during concentration

gamma

30

100

seen during motor activities

delta

0.5

4

observed at stage 3 and 4 of sleep

theta

4

8

occur during light sleep and are observed during hypnosis

mu

8/12

Motor Imagery (MI) BCI paradigm

Author: [1]

The lines of the next figure 1. are the FFT (Fast Fourier Transform) of the 59 channels database of BCI Competition IV, dataset 1 during the second 2 after a visual stimulus and the second one after removing the stimulus Visual. It seems that you can see the visual image stimuli right, because there is a lot of energy between 8-13 Hz frequency bands, and the Figure 2. there appears to be an absence of visual stimulation.

Figure 1.

Figure 2.

[1] S. Sanei and J. Chambers, EEG signal processing. John Wiley & Sons, 2007.

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