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首页> 外文会议>ICME International Conference on Complex Medical Engineering >Denoising and Rhythms Extraction of EEG under +Gz Acceleration Based on Wavelet Packet Transform
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Denoising and Rhythms Extraction of EEG under +Gz Acceleration Based on Wavelet Packet Transform

机译：基于小波包变换的+ GZ加速度的去噪与节奏提取

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摘要

Filtering and feature extraction are very important in the analysis and study of EEG signal under +Gz acceleration. In this study, a new filter of different frequency characteristics of EEG signal under +Gz acceleration is constructed and four kinds of rhythms of EEG signal are extracted by using wavelet packet transformation. EEG under different G loads is analyzed and compared, and then EEG dynamic characteristics are studied in order to analyze its advantages and disadvantages. Experimental results show that wavelet packet method can effectively suppress interference bands in EEG, such as EMG, power and so on, and effectively reflect the dynamic characteristics of different rhythms, exhibiting good characteristics. The proposed method is also applicable for analyzing and studying other dynamic biomedical signals.
机译：过滤和特征提取在+ GZ加速度下的EEG信号的分析和研究中非常重要。在该研究中，构造了+ GZ加速度下的EEG信号的不同频率特性的新滤波器，并且通过使用小波分组变换提取了四种eEG信号的节奏。分析并比较eEG在不同的G负载下进行比较，然后研究了EEG动态特性，以分析其优缺点。实验结果表明，小波包方法可以有效地抑制EEG中的干扰条，如EMG，功率等，有效地反映不同节律的动态特性，表现出良好的特征。所提出的方法也适用于分析和研究其他动态生物医学信号。

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