Application of fuzzy neural network in atherosclerosis

摘要

This paper describes the use of Wavelet Transform interferences rejection in ECG, pulse signals to eliminate baseline drift, power-line interference and muscle electricity, and then based on wavelet singularity theory in electrocardiograph signal to R-wave, QRS complex width T-wave amplitude is detection and orientation, extract characteristic values. Also extract time domain and frequency values In pulse signals. Through fuzzy neural networks is classify the signal to achieve non-destructive diagnosis of arteriosclerosis.