基于脑电图的驾驶疲劳实时检测，采用新型半干电极，可自我补充导电液。

IF 1.7 4区医学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-11-04 DOI:10.1080/10255842.2024.2423268

Fuwang Wang, Anni Luo, Daping Chen

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引用次数: 0

摘要

本研究提出了一种可实现导电液体自我补充的新型半干电极。通过提取该电极采集的脑电图（EEG）信号中的精炼复合多尺度波动离散熵（RCMFDE）特征来检测驾驶疲劳。结果表明，新型半干电极可根据自身湿度条件自动完成导电液的补充，不仅显著提高了有效工作时间，还大大降低了皮肤阻抗。与经典的熵算法相比，RCMFDE 方法的计算速度和稳定性都得到了大幅提升。

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Real-time EEG-based detection of driving fatigue using a novel semi-dry electrode with self-replenishment of conductive fluid.

A novel semi-dry electrode that can realize self-replenishment of conductive liquid is proposed in this study. Driving fatigue is detected by extracting the refined composite multiscale fluctuation dispersion entropy (RCMFDE) features in electroencephalogram (EEG) signals collected by this electrode. The results show that the new semi-dry electrode can automatically complete the conductive fluid supplement according to its own humidity conditions, which not only notably improves the effective working time, but also significantly reduces the skin impedance. By comparing with the classical entropy algorithms, the computational speed and the stability of the RCMFDE method are Substantially enhanced.

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来源期刊

Computer Methods in Biomechanics and Biomedical Engineering 工程技术-工程：生物医学

CiteScore

4.10

自引率

6.20%

发文量

179

审稿时长

4-8 weeks

期刊介绍： The primary aims of Computer Methods in Biomechanics and Biomedical Engineering are to provide a means of communicating the advances being made in the areas of biomechanics and biomedical engineering and to stimulate interest in the continually emerging computer based technologies which are being applied in these multidisciplinary subjects. Computer Methods in Biomechanics and Biomedical Engineering will also provide a focus for the importance of integrating the disciplines of engineering with medical technology and clinical expertise. Such integration will have a major impact on health care in the future.