摘要
室颤信号检测能够对心血管疾病起到预防和控制的作用,但是不同类型的室颤信号会对成功率和检测率造成影响,提出了外界干扰下体外自动除颤仪室颤信号高精度检测方法研究。考虑到人体特性会影响体外自动除颤仪室颤信号的质量,将噪声作为室颤信号的外界干扰因素,从肌电噪声、基线漂移、工频干扰和饱和噪声等方面,分析了室颤信号的噪声背景,利用变频滤波算法消除室颤信号的噪声,通过重构室颤信号的能量值,提取出室颤信号的能量特征,利用表征人体心脏状态的特征参数,获得心脏工作状态的相关信息,根据室颤信号的分类,设计了体外自动除颤仪室颤信号高精度检测算法,实现了室颤信号的高精度检测。实验结果表明,外界干扰下体外自动除颤仪室颤信号高精度检测方法能够成功检测到不同类型的室颤信号,在检测率方面也表现出更好的效果。
Ventricular fibrillation signal detection can prevent and control cardiovascular diseases, but different types of ventricular fibrillation signals will affect the success rate and detection rate. A high-precision detection method of ventricular fibrillation signal of external automatic defibrillator under external interference is proposed. Considering that the characteristics of human body will affect the quality of ventricular fibrillation signal of external automatic defibrillator, taking noise as the external interference factor of ventricular fibrillation signal, the noise background of ventricular fibrillation signal is analyzed from the aspects of EMG noise, baseline drift, power frequency interference and saturation noise. The noise of ventricular fibrillation signal is eliminated by frequency conversion filtering algorithm, and the energy value of ventricular fibrillation signal is reconstructed, The energy characteristics of ventricular fibrillation signal are extracted, and the relevant information of heart working state is obtained by using the characteristic parameters representing human heart state. According to the classification of ventricular fibrillation signal, a high-precision detection algorithm of ventricular fibrillation signal of external automatic defibrillator is designed to realize the high-precision detection of ventricular fibrillation signal. The experimental results show that the high-precision detection method of ventricular fibrillation signal of extracorporeal automatic defibrillator under external interference can successfully detect different types of ventricular fibrillation signals, and also shows a better effect in the detection rate.
作者
徐原
王少娜
XU Yuan;WANG Shaona(Shengjing Hospital of China Medical University,Shenyang 110022,China)
出处
《自动化与仪器仪表》
2022年第11期291-295,共5页
Automation & Instrumentation
关键词
外界干扰
室颤信号
噪声背景
高精度检测
体外自动除颤仪
特征提取
external interference
ventricular fibrillation signal
noise background
high precision detection
external automatic defibrillator
feature extraction
