单心动周期分割及MFCC特征提取系统  

Single heart period segmentation and MFCC feature extraction system

作　　者：李昊宇 张荣芬 刘宇红 Li Haoyu;Zhang Rongfen;Liu Yuhong(College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China)

机构地区：[1]贵州大学大数据与信息工程学院,贵州贵阳550025

出　　处：《电子技术应用》2020年第12期121-128,133,共9页Application of Electronic Technique

基　　金：黔科合基础([2019]1099号)。

摘　　要：目前,在基于医疗大数据与机器学习的心音识别系统研究中,对于单心动周期的提取大多依赖人工截取或基于同步心电信号进行分割,大大降低了整个系统的实用性和易用性。针对以上问题提出了一种基于低频提取的单心动周期分割及MFCC(Mel Frequency Cepstral Coefficients)特征提取的嵌入式硬件系统,能够更高效地实现单心动周期分割并计算其MFCC特征参数,综合分割准确率达98.3%,解决了单心音周期分割中对心音信号纯净度要求较高和没有成熟系统的问题,并且降低了数据存储成本,具有较好的实用性和潜在的应用前景。At present,in the research of heart sound recognition system based on medical big data and machine learning,the extraction of single cardiac cycle mostly relies on manual interception or segmentation based on synchronous ECG signals,which greatly reduces the practicability and ease of use of the whole system.In view of this,a hardware system with the function of singlecardiac periodic segmentation based on low-frequency extraction and MFCC(Mel Frequency Cepstral Coefficients)feature extraction is proposed,which realizes the single-cardiac periodic segmentation of heart sound and gives MFCC features more efficiently,and comprehensive segmentation accuracy reaches 98.3%,solves the problem of high purity of heart sound signal and no mature system in the segmentation of single heart sound cycle,meanwhile reduces the data storage cost,increases the system practicability and has potential application prospect.

关 键 词：心动周期 低频提取 MFCC特征提取 嵌入式系统 

分 类 号：TP368[自动化与计算机技术—计算机系统结构]