| ECG (electrocardiogram) signal is the synthetical response to the electrical motion transported to the surface of human body, it contains a large amount of message and knowledge related to the physical conditions of people. It seems that ECG signal analysis and diagnosis has vital meaning to the heart-related disease research, defence, diagnosis. However, compared to some European countries and America, our first research of heart diseases is really late and started at 1970’s. It is no exaggeration to say that there are many restrictions to the ECG automobile analysis and diagnosis, especially wave form analysis and position tracking. In the modern explosion development of mobile Internet, the ECG signal analysis and diagnosis system can’t meet the demands of countless users of mobile internet device.AMI (acute myocardial infarction) is one of main clinical manifestation of coronary heart disease, it has high threat to health of human beings (especially the aging groups). Therefore, this thesis researches the design of ECG signal analysis and diagnosis system based on it. At first, this thesis has mainly introduced the basic knowledge of ECG signal. Then, it has put stress on the research of base line drifting of ECG wave in usual ECG noises. In case that traditional wavelet decomposition filter is expert in filtering the high frequency than low frequency noises, this thesis has adopted a wavelet decomposition filter based on the self-adaptation technique which is demonstrated that it a better appearance both on high frequency and low frequency noise filtering through realted experiments. Based on these, this thesis has analysised the feature points of ECG signal with clinical character of AMI ECG wave, and pointed out the wave parameter and standard of AMI diagnosis. Due to the RAM restriction of mobile operation, this thesis has applied some fast and efficient approaches (e.g median filter, local transformation and so on) to extract such as R wave, Q wave and ST wave exactly.Based on the supports of above theories, this thesis has applied a distinguish and unique expert system frame on Android programming designing — JBPM, an effective and light-weight work-flow engine, based on rule engine—Drools, which is designed by Jboss community and sperated the analysised and designed stuff into some continous and compact modules. In case that the usual deploy environment of JBPM is web ralted project based on Java, I never remain suspicious that this thesis has applied JBPM to mobile application development on Android is innovative and original development. At the same time, in case that Android can’t support BPMN 2.0(a module language rule), there exists some restrictions on visualization character of JBPM. At last, this thesis introduces the wide-range applied operation system—Android and the IDE—Eclipse. Based on that environment, I explain the entire frame of my designed system and the function of every module in detail, besides, in order to fillful the original and core goal and values of thesis, I also illustrate the experiment which exams the diagnosis and analysis result of both the signal collected from ECG aquisition system based on LPC2132 mirco-chip and the ECG data of MIT-BIH arrhythmia database. The result shows that the AMI analysis and diagnosis system on Android can exactly extract the feature point of and diagnosis the AMI illness risk of ECG wave signal, which reaches the initial design goal of this thesis unsuspiciously. |
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