SCENE AND OBJECT CLASSIFICATION USING BRAIN WAVES SIGNAL

Darshan A Khade; Ilakiyaselvan N

doi:10.22159/ajpcr.2017.v10s1.19495

Authors

Darshan A Khade School of Computing Science and Engineering, VIT University, Chennai Campus, Tamil Nadu, India
Ilakiyaselvan N School of Computing Science and Engineering, VIT University, Chennai Campus, Tamil Nadu, India

DOI:

https://doi.org/10.22159/ajpcr.2017.v10s1.19495

Keywords:

Support vector machine, Electroencephalograph, Independent component analysis

Abstract

This study aims to classify the scene and object using brain waves signal. The dataset captured by the electroencephalograph (EEG) device by placing the electrodes on scalp to measure brain signals are used. Using captured EEG dataset, classifying the scene and object by decoding the changes in the EEG signals. In this study, independent component analysis, event-related potentials, and grand mean are used to analyze the signal. Machine learning algorithms such as decision tree, random forest, and support vector machine are used to classify the data. This technique is useful in forensic as well as in artificial intelligence for developing future technology.

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