ĭepression is a mental disorder characterized by persistent occurrences of lower mood states in the affected person and is usually perceived by friends or relatives. According to the 65th World Health Assembly (WHA) organized in 2012, the global burden of depression disorder is increasing and there is a need for a comprehensive, coordinated response from all health and social sectors at the country level. Untreated depression may lead to suicidal attempts. Depression can be treated using available effective treatments, but due to ignorance, untimely detection, misdiagnosis or improper medication people suffer from the disease worldwide. In women, pregnancy and menopause are the main causes for depression. It is estimated that the largest proportion of people suffering from depression are women aged between 18 and 45 years. It should be of a particular value to enable the early detection of depression.Īccording to the latest WHO report, depression affects more than 350 million people of all ages, making it as one of the most prevalent global diseases. Such a CAD system is simple to use and may be used by the clinicians as a tool to confirm their diagnosis. Hence, this article presents the recent efforts on CAD of depression using EEG signals with a focus on using nonlinear methods. Hence, chaos theory and nonlinear dynamic methods are widely used in extracting the EEG signal features for computer-aided diagnosis (CAD) of depression. Linear methods do not exhibit the complex dynamical variations in the EEG signals. The linear and nonlinear methods are effective in identifying the changes in EEG signals for the detection of depression. The complex, nonlinear and non-stationary electroencephalogram (EEG) signals are very tedious to interpret visually and highly difficult to extract the significant features from them.

What is eeg test used to diagnose