COMPUTER DOMAIN
Published December 27, 2021 | Version v1
Journal article Open

Common Spatial Filter for Improving the Classification of EEG using Artificial Neural Network

Creators

  • 1. Software Engineer, Creencia Technologies Private Limited, Bangalore, India.
  • 2. Department of Computer Science & Engineering, University Visvesvaraya College of Engineering, Bangalore, India.
  • 3. Assistant Professor, School of University, Reva University, Bangalore, India.

Description

Machine learning in motor imagery, the classifier performance of electro-encephalo-graphy (EEG) data varies for different subjects. The performance of classifier is degraded when applied on different subject. To overcome this issue, common spatial pattern (CSP) method is proposed. The dataset contains 9 subjects EEG data. Common spatial pattern is used in feature extraction for the improvement of the classifier of different subjects and tested with artificial neural network (ANN). Based on the classification, random forest is implemented to train the data accuracy. The obtained results show 0.96% of performance improvement compared with existing methodology.

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