Depression Is An Important Type Of Mood Disorder With Prominent, Prolonged, And Depressed Moods As The Main Clinical Features. Depression Has Become A Serious Disease That Affects People’s Mental Health. How To Detect It Promptly And Accurately Is A Difficult Task. Electroencephalogram Can Reflect The Spontaneous Biological Potential Signals In The Cerebral Cortex And Is Widely Used In The Prediction And Diagnosis Of Depression. With Electroencephalogram, The Key And Most Difficult Challenge Is To Find The Brain Regions And Frequencies Associated With Depression. The Linear And Nonlinear Methods Are Effective In Identifying The Changes In EEG Signals For The Detection Of Depression. Linear Methods Do Not Exhibit The Complex Dynamical Variations In The EEG Signals. Hence, Chaos Theory And Nonlinear Dynamic Methods Are Widely Used In Extracting The EEG Signal Features For Computer-aided Diagnosis (CAD) Of Depression.
