Research And Implementation Of Sinus Node Electrogram Automatic Analysis

Sinus nod electrogram (SNE) is the direct basis to evaluate of sinus node performance. However,waveform recognition of SNE is carried out manually.To improve the efficiency of clinical diagnosis and to meet the clinical needs, developing the automatic waveform recognition algorithm is needed. The specialized research on SNE automatic recognition algorithm is made in the paper to lay the foundation for the clinical application.In this paper, an SNE signal algorithm based on mathematical morphology and wavelet threshold denoising to suppress baseline and frequency noise was proposed. Based on the proposed algorithm, a preprocessing algorithm circuit based on FPGA was utilized to realize the preprocessing of SNE.Wavelet singularity detection was adopted to recognize S wave and cancellation method was employed to recognize A wave and V wave. At the same time, pre-P wave was recognized by curve fitting and threshold detection. Software was exploited on MFC platform to realize SNE waveform recognition automatically.Practical SNE data was sampled and small sample simulation was carried out by using Matlab code. The experimental results indicate that the proposed algorithm is reasonable and can be put into use.This work lays a good foundation to the further research about SNE.