Human Emotions Classification using EEG Signals in Virtual Instrumentation Platform
Ch. Kusma Kumari1, K. Prem Sai2, K. Mounika Satya Gowri3, K. Srujan Kumar4, K. Naveen Murthy5
1Kusma Kumari Cheepurupalli, Associate Professor Department of Ece Gayatri Vidya Parishad College of Engineering (A)Visakhapatnam India.
2K. PremSai, UG Students Department of Ece Gayatri Vidya Parishad College Of Engineering (A) Visakhapatnam India.
3K. Mounika Satya Gowri, UG Students Department of Ece Gayatri Vidya Parishad College Of Engineering (A) Visakhapatnam India.
4K. Srujan Kumar, UG Students Department of Ece Gayatri Vidya Parishad College Of Engineering (A) Visakhapatnam India.
5K. Naveen Murthy, UG Students Department of Ece Gayatri Vidya Parishad College Of Engineering (A) Visakhapatnam India.

Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 12104-12107 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8598118419/2019©BEIESP | DOI: 10.35940/ijrte.D8598.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: 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.
Keywords: EEG, FFT, LabVIEW tools, Preprocessing.
Scope of the Article: Classification.