The document analyzes epilepsy using the Approximate Entropy (ApEn) algorithm. ApEn is used to measure irregularity and unpredictability in EEG signals. The study applies the ApEn algorithm to EEG data from 4 subjects - 2 non-epileptic and 2 epileptic. For each subject, EEG data was recorded under different conditions, such as eyes open/closed, during seizures, etc. Integrated ApEn waveforms were generated for 4 selected data sets to analyze and distinguish epileptic from non-epileptic EEG signals. The results showed that the integrated ApEn waveform had minimal variation for the non-epileptic subject with eyes closed, and slightly more variation for the non-epileptic subject with eyes