A Method for Removing ECG Interference From Lumbar EMG Based on Signal Segmentation and SSA

Abstract

The lumbar EMG(Electromyography) can effectively reflect the current activity state of human lumbar muscles; however, cardiac signals in the EMG significantly impacts the accuracy of lumbar EMG analysis. Currently, there are some problems in the research of EMG signal interference removal, such as poor removal effects and low operation efficiencies, which do not meet the requirement of real-time signal processing. To solve this problem, this paper proposes a method for removing ECG(Electrocardiogram) interference from lumbar EMG signals based on signal segmentation and SSA(Singular Spectrum Analysis), which first, reduces the amount of data for SSA by detecting and segmenting the ECG interference signal segments and then separating the ECG signals present in the EMG signals through four steps of embedding, decomposition, grouping and reconstruction using SSA, effectively removing the ECG signals present in the EMG signals. Finally, a complete lumbar surface EMG signal without ECG interference was obtained by using the recombination method. The method not only provides a better removal effect but can also greatly improve the computing efficiency of the algorithm. It was proven that the method can improve the computing efficiency by 50-80%, and for signals with obvious ECG interference, the computing speed of the algorithm can be increased to the millisecond level, thus achieving real-time processing.