Analysis of Different Algorithms for EEG Signal Feature Extraction in BCI

Xinyi Jiang

2025

Abstract

Brain-Computer interface (BCI) technology has made important breakthroughs in neuroscience and human-computer interaction in recent years, allowing the brain to communicate directly with external devices. In recent years, advances in feature extraction algorithms, signal processing methods, and deep learning models have greatly improved the effectiveness of BCI in medical rehabilitation, cognitive enhancement, and neuroprosthetics. However, bidirectional BCI (BBCI) is still in its infancy and research content is limited, which limits its application in sports rehabilitation and cognitive intervention. In this paper, the algorithms commonly used to extract EEG signal features in the field of BCI are discussed, and combined with the experiments of several researchers, the key algorithms in time-frequency analysis, deep learning, and spatial feature extraction are analysed, and their effects on BCI performance are analysed. The results show that Short Time Fourier Transform (STFT), Tunable Q-Factor Wavelet Transform (TQWT), Long-Short-Term Memory (LSTM), BiLSTM and Filter Bank Common Spatial Pattern (FBCSP) have significant accuracy advantages. This paper also expected that BBCI would have promising applications in the fields of neural rehabilitation, cognitive enhancement. Future research should focus on solving the individual differences of EEG signals, optimization of denoising technology and real-time computing efficiency, to further improve the practicability of BBCI. At the same time, the data privacy and neurosecurity of brain-computer interfaces also need to receive more attention to ensure the safety and ethical compliance of BBCI technology.

Paper Citation

in Harvard Style

Jiang X. (2025). Analysis of Different Algorithms for EEG Signal Feature Extraction in BCI. In Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS; ISBN 978-989-758-789-4, SciTePress, pages 58-63. DOI: 10.5220/0014399200004933

in Bibtex Style

@conference{befs25,
author={Xinyi Jiang},
title={Analysis of Different Algorithms for EEG Signal Feature Extraction in BCI},
booktitle={Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS},
year={2025},
pages={58-63},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014399200004933},
isbn={978-989-758-789-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS
TI - Analysis of Different Algorithms for EEG Signal Feature Extraction in BCI
SN - 978-989-758-789-4
AU - Jiang X.
PY - 2025
SP - 58
EP - 63
DO - 10.5220/0014399200004933
PB - SciTePress