[A Review on Electroencephalogram Based Channel Selection]

Overview

Journal Sheng Wu Yi Xue Gong Cheng Xue Za Zhi

Specialty Biomedical Engineering

Date 2024 Apr 30

PMID 38686423

Authors

Xiangzhe Li

Dan Wang

Baiwen Zhang

Chaojie Fan

Jiaming Chen

Meng Xu

Yuanfang Chen

Affiliations

Soon will be listed here.

Abstract

The electroencephalogram (EEG) signal is the key signal carrier of the brain-computer interface (BCI) system. The EEG data collected by the whole-brain electrode arrangement is conducive to obtaining higher information representation. Personalized electrode layout, while ensuring the accuracy of EEG signal decoding, can also shorten the calibration time of BCI and has become an important research direction. This paper reviews the EEG signal channel selection methods in recent years, conducts a comparative analysis of the combined effects of different channel selection methods and different classification algorithms, obtains the commonly used channel combinations in motor imagery, P300 and other paradigms in BCI, and explains the application scenarios of the channel selection method in different paradigms are discussed, in order to provide stronger support for a more accurate and portable BCI system.

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