A Survey on Feature Selection, Classification, and Optimization Techniques for EEG-Based BrainComputer Interface

Title

A Survey on Feature Selection, Classification, and Optimization Techniques for EEG-Based BrainComputer Interface

Creator

Subramanian S.C.; Daniel D.

Description

In braincomputer interface (BCI) systems, the electroencephalography (EEG) signal is extensively utilized, as the recording of EEG brain signals is having relatively low cost, the potentiality for user mobility, high time resolution, and non-invasive nature. The EEG features are extracted by the BCI to execute commands. In the feature set obtained, the computational complexity increases, and poor classifier generalization can be caused by the utilization of a lot of overlapping features. The irrelevant features accumulation could be avoided with the feature selection procedures application. The feature selection algorithms are utilized to select diverse features for each classifier. Classifiers are the algorithms that are run to attain the classification. The researchers have examined diverse classifier implementation techniques to identify the feature vectors class. A review of EEG-BCI techniques available in the literature for feature selection, classifiers, and optimization algorithms is presented in this work. The research challenges, gaps, and limitations are identified in this paper. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Source

Lecture Notes in Networks and Systems, Vol-865, pp. 79-93.

Date

2024-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Algorithms; Braincomputer interface (BCI); Classification; Classifiers; Electroencephalography (EEG); Feature extraction; Feature selection; Optimization techniques

Coverage

Subramanian S.C., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Daniel D., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981999042-9

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-99-9043-6_7

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