Study Of Signal Processing Algorithms In The Intelligent Heart Function Instrument

The Intelligent Heart Function Analyzing Instrument is a household medical appliance, which can automatically analyze the input Cardiovascular data and make a diagnosis. People who have it at home can use it by themselves, without the inconvenience to go to the medical organizations. Because of the high occurrence rate of Cardiovascular diseases in China, this can be more important. The instrument being developed was sponsored by the Education Department of Henan Province, China. It's mainly about giving a diagnosis report by analyzing the electrocardiogram (ECG) and radial pulse acquired from sensors. It is very useful for the precaution and diagnosis of Cardiovascular disease at home. Besides, people can also use it to nurse people with Cardiovascular disease. The purpose of this thesis is to propose practical information management algorithm. The main tasks of this thesis are as follows:1) pre-process the ECG and extract the character: denoise the Power line interfere by using an Adaptive Nonlinear Dynamic System which can automatically tract a sine wave; use the Wavelet Transform to denoise the ECG; extract the character of ECG with the Wavelet Coefficient Modulus Maxima theory by using the Square Spline Wavelet.2) Pulse Wave collection and character extraction: use the HK2000C integrated digital sensor to gather Pulse Wave data at Arteria Radialis; extract the character of Pulse Wave in time domain, frequency domain and also the Cepstrum domain.3) Probe into the Multiple Physical Character fusion model: design a fusion model by using Database technology, Rough Sets Reduction theory and Artificial Neural Networks; describe how the model functions theoretically.