电子学报 ›› 2020, Vol. 48 ›› Issue (4): 670-674.DOI: 10.3969/j.issn.0372-2112.2020.04.008
石鹏, 张启忠, 张华平, 席旭刚
收稿日期:
2019-01-08
修回日期:
2019-05-24
出版日期:
2020-04-25
作者简介:
基金资助:
SHI Peng, ZHANG Qi-zhong, ZHANG Hua-ping, XI Xu-gang
Received:
2019-01-08
Revised:
2019-05-24
Online:
2020-04-25
Published:
2020-04-25
摘要: 提出了一种基于多元经验模态分解(Multivariate Empirical Mode Decomposition,MEMD)的多元多尺度熵(Multivarite Multiscale Entropy,MMSE)特征提取方法分析多模态信号,进行人体静态平衡能力评估.首先,采集人体多模态信号,采用多元经验模态分解对多通道信号进行自适应分解,得到一系列多元固有模态函数(Intrinsic Mode Functions,IMFs),依据T检验和相关系数从中选取最佳的IMF分量进行信号重构;然后,采用多元多尺度熵算法提取特征,用K-均值与支持向量机对比本文特征提取方法与两种传统特征提取方法在处理人体静态平衡能力评估问题时分类效果,并分析两种分类器的人体静态平衡能力评估效果;最后,得出本文最优的特征为基于多元经验模态分解的多元多尺度熵特征,最优的分类方法为支持向量机.
中图分类号:
石鹏, 张启忠, 张华平, 席旭刚. 基于多元经验模态分解的多元多尺度熵静态平衡能力评估[J]. 电子学报, 2020, 48(4): 670-674.
SHI Peng, ZHANG Qi-zhong, ZHANG Hua-ping, XI Xu-gang. Static Balance Capability Assessment of Multivariate Multiscale Entropy Based on Multivariate Empirical Mode Decomposition[J]. Acta Electronica Sinica, 2020, 48(4): 670-674.
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