The Research Of Atrial Fibrillation Signal Processing With Its Application In Clinical Medicine

Atrial fibrillation (AF) is the most common sustained arrhythmias encountered byclinicians and occurs in approximately 0.4%-1.0% of the general population.Itsprevalence increases with age.There is increasing awareness that AF is major cause ofemolic events and cerebrovascular accidents.Symptoms such as occasionally disablinghaemo-dynamic impairment and a decrease in life expectancy are among the untowardeffects of AF,resulting in an important morbidity and mortality.In this respect,theclinic AF patient monitor and its treatment has been the subject of arousing interest andintensive clinical research in recent years.In clinic patient monitor,the non-invasive approach for the AA estimation in AFepisodes is a key step in the analysis and characterization of AF.In clinical treatment,safety and efficacy of radiofrequency catheter ablation (RFCA) guided by 3-dimension(3-D) mapping system in patients with AF have been verified in the past ten years.However,the civil market of RFCA machines has been 100% penetrated by foreignproducts,i.e.,Ensite3000 and Carto system.It has been in great need to develop RFCAsystem with our own intellectual property rights.This dissertation,focused on AF monitor and treatment,includes the following twoparts:the AF signal extraction from surface 12-lead Electrocardiograph (ECG) and theimage registration in the software of RFCA system.The main contents are organized asfollows:1 A second order statistics (SOS) based blind source extraction (BSE) algorithm ispresented to extract AF signal.The early method based on BSS utilized all theinformation from 12 lead,and could obtain 12 source signals including AF signal.Thenthe AF signal would be selected with the help of power spectrum analysis.However,theselection sometimes goes wrong and may not work well in monitor.Here we presente anew method based on BSE to settle this problem.The efficacy is verified by theoreticalanalysis and simulation results.2 A fourth order statistics (FOS) based BSE algorithm is proposed to extract AFsignal.Note that the 12-lead ECG of AF patients are composed of the independent sources of atrial activiey (AA),ventricular activity (VA) and other nuisance signals.With respect to non-Gaussianity,VA presents high values within the heart beat (QRScomplex) and low values in the rest of the cardiac cycle.Hence,the histogram analysisof VA reveals a super-Gaussian behavior with high positive kurtosis value.On the otherhand,AA behaves as a sub-Gaussian random process with low negative kurtosis value.The other nuisance signals whose kurtosis approximates zero can be regarded asGaussian noises.Then we can use the HOS based BSE algorithm to extract AF signal.The validity and performance of this algorithm are confirmed by extensive computersimulations and experiments on real-world data.Compared with BSS,BSE onlyextracts one desired signal,and thus is more suitable to clinical monitor.3 Regarding the research of the image registrastion in the RFCA system,some resultsof how we do the RFCA system with the civil company are presented.In thecooperation,we focused on how to show and registrate the images in software.Regarding the registration,we introduced affine transformation model using twelve freedegrees and the corresponding iterative closest point algorithm.We also did research onhow incorporate the registration algorithm into the clinical operations.With the help ofOpenGL,the algorithm was realized via Visual C++ 6.0.Simulation results and theanimal experiment verified this algorithm.