Analysis of center of pressure signals using Empirical Mode Decomposition and Fourier-Bessel expansion

R. B. Pachori, D. Hewson, H. Snoussi, J. Duchêne
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引用次数: 25

Abstract

Center of pressure (COP) measurements are often used to identify balance problems. A new method for analysis of COP signals using empirical mode decomposition (EMD) and Fourier-Bessel (FB) expansion is proposed in this paper. The EMD decomposes a COP signal into a finite set of band-limited signals termed intrinsic mode functions (IMFs), before FB expansion is applied on each IMF to compute mean frequency. The FB expansion based representation is suitable for use in non-stationary and very short duration signals. Seventeen subjects were tested under eyes open (EO) and eyes closed (EC) conditions, with different vibration frequencies applied for EC condition to further perturb sensory information. Mean frequency as calculated by FB expansion for the first three IMFs was able to distinguish between EO and EC conditions (p < 0.05), while only first IMF was able to detect a vibration effect.
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用经验模态分解和傅里叶-贝塞尔展开分析压力信号中心
压力中心(COP)测量通常用于识别平衡问题。提出了一种利用经验模态分解(EMD)和傅里叶-贝塞尔(FB)展开对COP信号进行分析的新方法。EMD将COP信号分解为一组有限的带限信号,称为内禀模态函数(IMFs),然后对每个IMF应用FB展开以计算平均频率。基于FB展开的表示法适用于非平稳和极短持续时间的信号。17名被试分别在睁眼和闭眼状态下进行测试,在闭眼状态下使用不同的振动频率进一步扰动感官信息。前三个IMF的FB扩展计算的平均频率能够区分EO和EC条件(p < 0.05),而只有第一个IMF能够检测到振动效应。
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