Survey on Signal Processing and Classification Algorithms for Depression Using Electroencephalogram Signals

This survey paper presents various functional neuro-imaging techniques, revealing the excellence of EEG signals in terms of high temporal resolution, expensiveness, non-invasive, ease of use, flexibility, safety and portable when compared to position emission tomography, magneto encephalogram, functional MRI and transcranial magnetic stimulation methods. It also delves into different frequency bands present in EEG signals. The primary objective of this survey paper is to examine findings, related to depression using EEG signals. Subsequently, it discusses preprocessing methods, extraction of features from the preprocessed signal, post processing and result investigation utilizing classification algorithms and statistical testing methods. Finally it identifies research gaps and outlines, potential future findings in depression-related studies.