摘要
脉搏波是人体心脏有节律的收缩射血,血液流经弹性血管所产生的波动。不同的人在不同的生理状态下的脉搏波波形是不同的,因此脉搏波的特征点识别对于分析人体的生理病理状况、预防诊断心血管疾病是非常有帮助的。本文结合小波分析和脉搏波时域特征,提出了一种从脉搏波预处理到特征点准确识别的综合算法,实验表明该算法能够有效识别处于不同运动状态的脉搏波特征点,为后续相关人体生理病理信息的有效提取创造了条件。
When the blood flow is caused by systolic ejection flows through elastic vessels,the generated rhythmic fluctuation is called a pulse wave. Since pulse wave shapes vary when people in different physiological states,the waveform feature point identification is very helpful in physiological and pathological condition analysis for cardiovascular disease prevention and diagnosis. A comprehensive algorithm is proposed for accurate feature point recognition,which is based on time domain feature and wavelet decomposition. Experimental results show that the presented algorithm could effectively identify pulse wave feature points in different motion states,which can provide accurate data base for further related physiological and pathological information extraction.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2016年第2期379-386,共8页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(81371713)
中央高校基本科研业务费专项(106112015CDJZR235522)项目资助
关键词
脉搏波
预处理
时域特征
小波分解
特征点识别
pulse wave
pretreatment
time domain feature
wavelet decomposition
feature point recognition
