Pulse Information Collection And Analysis Methods

Pulse is a common physiological phenomenon, it can depict the heart and blood vessel state through its wave. Diagnosis by feeling the pulse of Chinese medicine through more than 2600 year practice, it has been accumulated abundant clinical experience, and it had developed into a kinds of the remarkable unique to diagnose skill, it is " Chinese medicine diagnosis by feeling the pulse" and it has been paid attention to in the world. For various reasons, the resolution standard of the diagnosis by feeling of Chinese medicine still stays subjectively, so that the studying that the diagnosis by feeling the pulse of Chinese objectifying an important respect becoming modern traditional Chinese medicine .This thesis has studied base on the computer gather the pulse signal of the real time, deals with and it's analysis system. The main result and innovation of research work in this paper can be summed up as follows:The first that we studied the design of the circuit about the pulse signal collecting. In this parts we analysis and research PVDF piezoelectricity membrane and it's equation of piezoelectricity, we designed to the parts of sensitive for the circuit that it can very easy to imitate Chinese medicine fetch the pulse. According to the characteristic of the human pulse signal, we designed to the circuit for gathering to the pulse signal. And we analyzed which the noise to be lead into gather and get rid of it using corresponding measure based on different noises.The second that we deeply researched the wavelet transform filtering for pulse signal. We farther filtered the noise that the hardware didn't filter to use the mould maximum filtering method and have get well result. We have get of the characteristic value of the pulse signal using the wavelet transform. We analyzed the pulse signal of the normal person's wavelet domain characteristic and find that between the pulse time domain characteristic and the wavelet transform zero-crossing-was that the absolute corresponding. So we advanced the algorithm that analyzed the pulse signal used the wavelet transform zero-crossing. This method better solved that the pulse signal have a lots of characteristic parameter in time domain and it was complicated when we analyzed it and being biggish error. Go on, we analyzed normal people pulse signal and...