Research On ST Segment Of ECG Signal And Implementation Of Android Platform

ECG ST segment is an important part of the ECG waveform,the occurrence of heart disease is often accompanied by changes in the ST segment waveform.Because the amplitude of ST is small and has lower frequency,the shape is easy to be disturbed by the external noise.Therefore,timely and accurate detection of the location of ST segment,and the waveform of the measurement and analysis of the corresponding cardiac disease diagnosis is very important.At present,there are many algorithms for classification and recognition of ECG signals,but the automatic recognition of ST segment waveform has Low maturity.It is difficult to accurately locate the starting and ending points of ST segment,and to analyze the morphological characteristics of ST segments,it is an urgent need for the joint efforts of engineering technicians and medical workers to seek new effective treatment methods.In this paper,the characteristics and difficulties of ST segment of ECG signal are discussed and studied.This paper first briefly introduces the basic knowledge of ECG and ST waveform.By using the wavelet algorithm,according to the frequency domain characteristics of ST segment waveform,wavelet decomposition reconstruction and threshold method are used to filter the ECG signals.The experimental results show that the wavelet algorithm has good de-noising effect,and the waveform of the ECG signal is not distorted,and the shape of ST is not affected.On the basis of this,the characteristic points of ST segment are located and detected.Firstly we use the differential threshold method and the slope method to locate the R wave,and to exclude false detections.Then combined with the use of time moving window function,adaptive local transformation and other methods to detect the start point and end point of the ST segment,complete the ST segment waveform positioning.Aiming at the difficulty of ST segment degeneration morphology,this paper extracts three indicators from the ST waveform information as a parameter,put forward the ST classification method based on support vector machine.And the simulation experiment is done by using the data in the CSE ECG database,the classification results show that the average accuracy rate of more than 84%.After that,according to the extraction of the three parameters,this paper designs an algorithm based on the Android platform to achieve real-time processing of ST segment of ECG signal in Android system.The ECG signal collected by hardware is processed by digital filter,and the preprocessing is done.And locate the feature points by using the derivative method,labeled QRS wave group,real-time display ECG waveform to extract.Combined with the window function to locate the ST segment waveform,extract the index parameters,and classify them.Experimental results show that the system can complete the basic classification of ST segment in real time.ECG data can be stored in TXT format through the interface of the save button,convenient data storage call,Strong practicability,and have a certain improvement on the third chapter of the MATLAB platform algorithm is poor portability defects.