【摘要】 心音是人体心脏搏动产生的具有个体特征的生理参数。实验利用小波变换实现对心音信号的去噪处理,选择Mel频率倒谱系数(MFCC)作为特征参量,并经过主成分分析(PCA)降维处理后用于个体分类识别中。旨在对心音作为生物识别特征参数可行性和识别方法做一个初步研究。实验结果显示,在选定的实验条件下,系统可以达到90%以上的识别率。可以为心音识别技术的进一步研究提供参考。更多还原

【Abstract】 Heart sound is a physiological parameter with individual characteristics generated by heart beat.To do the individual classification and recognition,in this paper,we present our study of using wavelet transform in the signal denoising,with the Mel-Frequency cepstrum coefficients(MFCC) as the feature parameters,and propose a research of reducing the dimensionality through principal components analysis(PCA).We have done the preliminary study to test the feasibility of biometric identification method using heart sound.The results showed that under the selected experimental conditions,the system could reach a 90% recognition rate.This study can provide a reference for further research.更多还原