Abstract

Electroencephalogram, or EEG, data have been collected and analyzed for a long time in an effort to gain insight into the electromagnetic activity of the brain. It has survived the test of time because to the fact that it monitors physiological processes despite the fact that these functions fluctuate over the course of time and is reactive to various circumstances. The electroencephalogram (EEG) reflects the electrical activity of the brain with a temporal resolution of milliseconds and is the most direct correlate of on-line brain function that is accessible in a non-invasive manner. Currents are generated everywhere throughout the skull as a result of the electrical activity that is produced by the brain's active nerve cells. These currents also reach the surface of the scalp, and the electroencephalogram, which records the ensuing voltage variations on the scalp, may be described as follows: (EEG). The electroencephalogram (EEG) signal consists of, among other things, four primary spectral components. The wave, with a frequency ranging from 8 to 12 Hz, is the one that is considered to be the most significant.

Keywords

• Data Mining,
• Temporal,
• Frequency,
• Electroencephalogram

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