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Cognitive depression detection methodology using EEG signal analysis
S.P. Bobde, , D.D. Patil, V. Wadhai
Published in Springer Verlag
Volume: 673
Pages: 557 - 566
This paper illustrates a new method for depression detection using EEG recordings of a subject. It is meant to be used as a computerised aid by psychiatrists to provide objective and accurate diagnosis of a patient. First, data from the occipital and parietal regions of the brain is extracted and different channels are fused to form one wave. Then DFT, using FFT, is applied on the occipito-parietal wave to perform spectral analysis and the fundamental is selected from the spectrum. The fundamental is the wave with the maximum amplitude in the spectrum. Then classification of the subject is made based on the frequency of the fundamental using rule-based classifier. Detailed analysis of the output has been carried out. It has been noted that lower frequency of the fundamental tends to show hypoactivation of the lobes. Moreover, low-frequency characteristics have also been observed in depressed subjects. In this research, 37.5% of the subjects showed Major Depressive Disorder (MDD) and in all 80% of the subjects showed some form of depression. © 2018, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Verlag