EEG feature extraction methods in motor imagery brain computer interface

Fengge Bao; Weiheng Liu

doi:10.1117/12.2667875

22 February 2023 EEG feature extraction methods in motor imagery brain computer interface

Fengge Bao, Weiheng Liu

Proceedings Volume 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022); 125871I (2023) https://doi.org/10.1117/12.2667875
Event: Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 2022, Shanghai, China

Abstract

Brain-computer interface (BCI) is a link between the human brain and a computer or other peripheral devices for communication and control. The most frequently utilized BCI paradigms at the time are motor imagination (MI) BCI. In the procedure of MI-BCI, one of the most important roles is the feature extraction of EEG signals. This article examines various feature extraction approaches in four distinct domains: time, frequency, time-frequency, and spatial. Various approaches are introduced in each domain, including the ERD/ERS computation, the FFT method, the Wavelet Transform (WT), the Discrete Wavelet Transform (DWT), Common Spatial Patterns (CSP), and Sub-band Common Spatial Patterns (SBCSP). This paper also compares the advantages and disadvantages of different methods in practical application, which can provide reference for future research.

Citation Download Citation

Fengge Bao and Weiheng Liu "EEG feature extraction methods in motor imagery brain computer interface", Proc. SPIE 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 125871I (22 February 2023); https://doi.org/10.1117/12.2667875

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