Can I read Recent Approaches on Classification and Feature Extraction of EEG Signal: A Review on EtoBox?

Recent Approaches on Classification and Feature Extraction of EEG Signal: A Review by Pooja; SK Pahuja; Karan Veer is a Engineering article available to read on EtoBox.

What is Recent Approaches on Classification and Feature Extraction of EEG Signal: A Review about?

## Abstract ## Objective: Electroencephalography (EEG) has an influential role in neuroscience and commercial applications. Most of the tools available for EEG signal analysis use machine learning to extract the required information. So, the study of robust techniques for feature extraction and classification is an important thing to understand the practical use of EEG. The paper aims that if there is any special tool for a particular task. Which feature domain or classifier has a significant role in EEG signal analysis? ## Approach: It presents a detailed report of the current trend for bio-electrical signals classification focusing on various classifiers’ advantages and disadvantages. This study includes literature from 2000 to 2021 with a brief description of EEG signal origin and advancement in classification techniques. ## Results: Randomly used classifiers for EEG signal can be categorized into five classes, namely Linear Classifiers, Nearest Neighbor Classifiers, Nonlinear Bayesian Classifiers, Neural Networks, and Combinations of Classifiers. Approximately 40% of studies use Support Vector Machine, Nearest Neighbor, and their combination with others. For specific tasks, par

Who reads Recent Approaches on Classification and Feature Extraction of EEG Signal: A Review?

Author

Pooja; SK Pahuja; Karan Veer

Publisher

Cambridge University Press (CUP)

Published

2021

Language

EN

Field

Engineering (Physical Sciences)