Abstract
This paper presents a method using genetic programming
for automatic detection of 3 Hz spike-and-slow- wave
complexes, that are a characteristic of typical
absences, in electroencephalogram (EEG) signals.
Training features are extracted from 1s EEG frames,
randomly chosen from pre-recorded files. The frames are
visually classified as spike-and-slow-wave complexes
(SASWC) or non-spike- and-slow-wave complexes (NSASWC).
Genetic programming techniques are then applied to
these data to build a program capable of recognizing
such complexes.
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