摘要
心电图中QRS波是特征最明显的波形,是医学上诊断症状的重要依据,因此QRS波的正确识别成为心电检测的首要问题。由于心电信号是mV级的微弱信号,易受各种干扰影响;同时,目前常用的小波变换识别QRS波方法,计算量大,对系统要求高。针对这些问题,首先,提出使用双正交B样条小波基对心电信号进行处理,并通过在各尺度波形上检测极大值取代模极大值对的方式,搜索R波;然后,使用MIT-BIH心律失常数据库验证算法效果,并针对验证结果对原始算法进行检测策略的优化,改用自适应阈值的检测方式;同时,引进对部分可疑点搜索模极大值对的检查方法,减少假阳性的情况。算法经MIT-BIH验证,得到98.9%的准确率。
Among ECG signal,QRS wave is the most obvious which is always an important foundation of symptoms diagnosis.So how to detect it effectively and accurately becomes a primary issue of diagnosis of electrocardiogram.Because ECG signal has a small amplitude and is susceptible to noise interference.At the same time,recently the common QRS detector based on wavelet transform has a large computation and a high requirement for system.According to these problems.Firstly,propose using biorthogonal wavelet transform raw electrocardiogram signal in order to reduce noise interference.Then,through detecting maxima feature points of wave signal under each scale,algorithm will find R wave instead of detecting modulus maxima pairs.In the further step,use MIT-BIH electrocardiogram database to verify the method.Regarding these problems in the verification result,propose optimization detection strategies,and adaptive threshold detection take the place of fixed threshold detection.Besides that,introduce some error remedy method.That is to find the module maxima pairs as to those doubtful feature points.This method can effectively locate the position of R wave and the recognition accuracy turns out to be 98.9%,better than some other traditional methods.
出处
《机电一体化》
2014年第5期21-25,61,共6页
Mechatronics
关键词
心电信号
双正交小波变换
R波检测
自适应阈值
ECG signal
biorthogonal wavelet transform
R wave detection
adaptive threshold
