Study On QRS Complex Detection In Ecg Signals Using Teager-kaiser Weighted Denoising Algorithm

Cardiovascular disease has become one of the most common diseases that threaten the safety of human life with the increase of life,work stress and employment.According to statistics,human mortality caused by cardiovascular diseases,especially heart diseases,still occupies the first place in the world,which is worrying.Therefore,to strengthen the prevention,treatment and diagnosis of cardiac diseases and reduce the mortality caused by cardiac diseases is the first problem that the medical field needs to face.But electrocardiogram(ECG)is a biological signal,which is especially vulnerable to noise,such as electromyoelectric noise,baseline drift,power frequency interference,poor electrode contact and so on.Only by improving the accuracy of detection can the algorithm have higher practical significance.However,how to effectively remove all kinds of noise in ECG signal and improve the purity of ECG signal is still a"bottleneck" problem to be solved in the current QRS detection algorithm.The proposed QRS detection algorithm based on Teager-Kaiser weight denoising is simple in calculation and can improve the detection rate of QRS to a certain extent.First of all,the linear FIR bandpass filter designed by Remez algorithm is aimed at the phenomenon of power frequency interference caused by the capacitance distributed in the human body during the detection of ECG signal.The linear FIR bandpass filter is used to remove the power frequency interference and electromyoelectric noise instead of the original Butterworth band-pass filter,which makes up for the distortion of the Butterworth band-pass filter,and to a certain extent saved the use of the cost.Secondly,in order to suppress P wave and T wave better and highlight QRS wave,we use Teager-Kaiser to calculate the weight of P wave and T wave to make the amplitude of P wave and T wave as 0 as possible,while the waveform of QRS is preserved,which lays the foundation for the subsequent QRS detection.Thirdly,for irregular ECG signals,in order to prevent the occurrence of false negative because the amplitude of R wave is too low,the method of combining with logarithmic transformation is used to make R wave with higher amplitude and R wave with lower amplitude.To a certain extent,the balance is achieved,in order to improve the accuracy of QRS waveform detection,the probability of false negative caused by false detection of Rand false negative can be reduced.Finally,by using twice sliding window filtering methods,this paper can further increase the slope of the R wave,highlight the QRS wave,and lay the foundation for the back threshold detection part.In the threshold detection,the dual threshold detection algorithm is used to locate the QRS waveform,thus providing the basis for the detection of the heart rate and so on.Enough to prevent and diagnose cardiovascular diseases.Experimental results show that the proposed QRS detection algorithm based on Teager-Kaiser weight denoising makes up for the shortcomings of large computation and low accuracy in the classical Pan-Tompkins algorithm and the maximum and minimum difference algorithm.It not only effectively reduces the average error rate of QRS complex wave detection,but also provides technical support for the development of QRS detection system with high accuracy,strong robustness and good anti-counterfeiting performance in clinical medicine and practical applications.