Study Of Detective And Compress The ECG Signal Algorithm Based On EMD

With the arrival of the population of aging society, the number of patients withheart disease will hasten to add, heart health care and heart disease symptoms inadvance of anticipation will become a social problem. Remote ECG signaltransmission can do a lot to the patient’s real-time monitoring, and can be helpful fordiagnosis and first aid guide. Especially along with the development of moderncommunication network, for all sorts of reasons not to hospital patients provides greatconvenience condition. ECG signal of the real-time process and data compression canimprove the transmission efficiency, save time and reduce the cost has importantsignificance. This topic research has the very good social benefits and economicbenefits.Through a lot of reading literature, and current signal processing center in the fieldof my understanding, and analysis the practicality and the inadequacies of thedomestic and the international situation,mainly is aiming at in QRS complex group offast and accurate testing, and the reasonable and efficient of ECG signal compressionon basic research. This paper studies the Huang proposed empirical modedecomposition, through the study and analysis empirical mode decomposition indifferent areas of application, and its advantages and disadvantages, put it into theECG signal processing areas, and put forward ECG signal detection algorithm basedon empirical mode decomposition. After ECG signal has been decomposed byalgorithm of EMD, energy is relatively concentrated embodied in QRS compositewave group, so the QRS composite wave detection is better than the P, T wavedetection. In the meantime, empirical mode decomposition algorithm as the premiseof compressed tools, introduced to the compression algorithm. Put it with the classicand commonly used compression such as discrete cosine compression algorithm, FFTalgorithm and wavelet compression. Through simulation used by the Matlab, that our algorithms performance are be certificated. And use the Compression Ratio(Compression Ratio) and the mean square error Percentage (PercentageRoot-mean-square Difference) two compressed indexes, the Compression of therebuilding after the signal quality evaluation, two indexes are better than the originalalgorithm was improved, we can draw the conclusion that: the improved compressionalgorithm has a higher compression ratio than the original algorithm,the PRD of thenew algorithm perform good than the original,namely the new one not only canimprove the CR, but the rebuild signal loss small information that compared with theoriginal one. So as to further verify that the proposed the new algorithm in certaincondition is feasible and efficient.