| ECG signal is a synthetic reflection of the heart electricity on body surface. It has important significance to the diagnosis of heart disease by clinical ECG examination. At the present time, the techniques of processing ECG signal and automatic analysis have many disadvantages; ECG diagnostic wave analysis and localizing result are not satisfactory. So there is room for innovation in theory. Being the symbol of the most advanced instrument of ECG examination, ECG workstation market popularization is not high, and there are not products with complete intellectual property rights inland. Based on the demands of academic research and market, this dissertation researches on ECG signals processing algorithms, and develops the software and hardware system of ECG workstation. It mainly includes the following distinctive works accomplished:(1) This dissertation has solved the problem by using morphological operation to process one dimension signal, and established one dimension morphological filter model based on image shape transform, which has expanded morphological process from two dimensions to one dimension, so has designed morphological filter. Then this dissertation makes the contrast experiment among morphological filter, FIR filter and wavelet transform filter. To avoid the disadvantages of wavelet transform filter, this dissertation has brought forward synthetic filter model based on wavelet transform and morphological operations. It can avoid the P and T wave distortion that would occur in filter baseline excursion by morphological opening and closing operations. This dissertation also presents the algorithm of this filter and shows the perfect processing results of it.(2) This dissertation has studied ECG signal character wave and its character dots identification problem. Discusses classical difference threshold algorithm, and processed it by self-adaptive optimizing method. Then this dissertation brings forward wavelet and morphological combine QRS complex detection algorithm based on using MRA method for ECG character detection. As wavelet transform, this algorithm also has perfect resolution in frequency domain, but avoids mistake detection result for fake noise by using morphological operations. The experiment results show that this algorithm has the highest exact rate of QRS complex detection.(3) To solve the problem of detecting ECG wave fleetly, this dissertation puts forward the algorithm by fractal character of ECG signal, and has established the localfractal dimension model based on boxes fractal dimension detection. Using this model, we can identify QRS complex fleetly. The results of applying this model show that it has higher veracity than difference threshold algorithm and also has real time detection capability. Finally, by using morphological peak-valley detection sensitivity to singularity dot and the morphological model presented in the second chapter, in combination with local transform method, we can detect P and T wave effectively.(4) This dissertation has brought forward new P and T detection algorithm basing on fuzzy clustering analysis. It has established fuzzy set membership function model in N dimension Euclid-space firstly. Based on the model, by examining the fuzzy relationship between for detecting dot and the P and T wave formed in N dimension Euclid-space, P and T wave can be assorted, then corresponding algorithm and threshold are selected according to wave type. The experiment results show that the algorithm has high stability and veracity to P and T wave detection. (5) Based on the above algorithm models, a greatness workload has been accomplished. Software consisting of fifty thousands code lines has been written, and corresponding hardware has been developed. The workstation product is mature, which has STI analysis function in a class by itself in contrast with other ECG workstations. Furthermore, it also has synchronization 12 leads ECG, VCG, HFECG, HRV, QTd et. al. functions.(6) Power supply of system hardware is driven by the electrical sourc...
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