Detecting signal quality by ensemble empirical mode decomposition and Monte Carlo verification

作者：Lee Yun Kai; Tang Sung Chun; Yeh Jia Rong; Shieh Jiann Shing^*

来源：Biomedical Signal Processing and Control, 2015, 20: 10-15.

DOI：10.1016/j.bspc.2015.01.010

• Bio-signal
• Ensemble empirical mode decomposition (EEMD)
• Intrinsic mode functions (IMFs)
• Monte Carlo verification
• White noise

The measurements of bio-signals are always subject to interference from noise, which would be able to affect the research results. In the present study, we introduce a technique to detect the signal quality by using ensemble empirical mode decomposition (EEMD) and Monte Carlo verification. We first decompose the original signals into several intrinsic mode functions (IMFs) and calculate the average distances between the signal IMFs and the negative (-1) slope line in Monte Carlo verification. Then, the approximate amount of white noise percent level in original signal could be obtained via corresponding to the created curve of distance and noise percent. This new proposed technique makes the approximate white noise percent level could be obtained much easier via a simple distance index through the EEMD and Monte Carlo verification methods.

• 出版日期2015-7
• 单位中央民族大学