Genetic Algorithm based Emotional State Evaluation from Filtered EEG Data

Authors

  • Charu Gitey M.Tech Scholar Department of Computer Science & Engineering SIRT- Excellence, Bhopal
  • Dr. Kamlesh Namdev Associate Professor Department of Computer Science & Engineering SIRT-Excellence,Bhopal. M.P,

DOI:

https://doi.org/10.24113/ijoscience.v5i3.193

Abstract

Emotion plays an important role in the daily life of man and is an important feature of human interaction. Because of its role of adaptation, it motivates people to respond quickly to stimuli in their environment to improve communication, learning and decision making. With the increasing role of the brain-computer interface (BCI) in user-computer interaction, automatic recognition of emotions has become an area of interest in the last decade. The recognition of emotions could be facial expression, gesture, speech and text and could be recorded in different ways, such as electroencephalogram (EEG), positron emission tomography (PET), magnetic resonance imaging (MRI), etc. In this research work, feature extraction feature reduction and classification of emotions have been evaluated on different methods to recognize and classify different emotional states such as fear, sad, frustrated, happy, pleasant and satisfied from inner emotion EEG signals.

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References

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Published

2019-03-28

How to Cite

Gitey, C., & Namdev, D. . K. (2019). Genetic Algorithm based Emotional State Evaluation from Filtered EEG Data. SMART MOVES JOURNAL IJOSCIENCE, 5(3), 18-24. https://doi.org/10.24113/ijoscience.v5i3.193