A Review on Classification and Future Extraction Techniques for EEG Signal Processing

Current situation of world most of people affected mental diseases. Depression is most common mental illness. It is vital cause of sickness. Suicide is the main cause of depression. Assessment methods of mental diseases are diagnosing depression exclusive on patient-report clinical judgments of symptom severity. In modern techniques Electroencephalogram (EEG) base emotion recognition is a new arena of this area with challenging issue concerning the induction of emotion state diagnosis. In this paper we conclude the different technology for analysis mental diagnosis which helps to further clinical assessment. The techniques are eye gaze signal tracking, facial expression signal tracking, and Brain Computer interface technogies between humans and machines. EEG signal for tag relevance assessment and effective neuromodulator therapies etc. It is based on statistics tools like Artificial Neural Networked models for brain computer interface and proper detection of emotion classifications reorganize-ation etc.