Open AccessHuman Emotions Classification using EEG Signals in Virtual Instrumentation Platform
Author(s) -
Kusma Kumari Cheepurupalli,
Kacem Saï,
K. Sri Gowri,
K. S. P. Kumar,
K. Narasimha Murthy
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d8598.118419
Subject(s) - preprocessor , computer science , instrumentation (computer programming) , signal (programming language) , electroencephalography , virtual instrumentation , feature extraction , artificial intelligence , noise (video) , workbench , feature (linguistics) , fast fourier transform , pattern recognition (psychology) , signal processing , speech recognition , software , computer hardware , digital signal processing , visualization , psychology , linguistics , philosophy , algorithm , psychiatry , image (mathematics) , programming language , operating system
This article presents the frequency band classification of emotions and detection of emotional condition of a person. This is done by the analysis of the biological signal, EEG (Electroencephalogram). The EEG is considered as the main biological signal, which signifies the electrical activity of the human brain and hence becomes main source of information for studying the neurological disorders. This analysis is done using one of the popular virtual instrumentation platform LabVIEW (Laboratory Virtual Instrumentation Engineering workbench) software. The EEG signals that are used for the analysis are taken from the open source database and are undergone different stages like preprocessing for noise elimination, classification and feature extraction. The feature extraction is done by performing Fast Fourier Transform (FFT) of the signal. This analysis helps us to identify the abnormality of the person (if any) from whom the signal is taken