Human Health Analysis And Diagnosis System Based On Pulse Detection

As a treasure of Chinese medicine,traditional diagnosis especially pulse-taking diagnosis plays an important role in breeding and development of the nation.Getting body pathological information through pulse signals,pulse-taking diagnosis has became a effective means for traditional Chinese doctor's treatment.Unfortunately,With the passage of time,the pulse diagnosis culture has not been well inherited now.So the modern testing instruments are needed to make pulse-taking diagnosis more objective and accurate in qualitative and quantitative aspects.In terms of design,understanding the generation principle and waveform characteristics of pulse wave,combined with the diagnostic criteria of Chinese medicine,the data pulse signal collected by the instrument can make a diagnostic conclude.Based on this,the human health status analysis based on pulse detection and application researches of diagnostic system software are performed.In terms of system design,firstly,in the hardware system architecture,the AM2520 sensor is used to collect the pulse signal,and the construction of the amplifier circuit and the primary filter circuit in the hardware is discussed.The low-pass performance of the filter circuit is simulated and tested.It shows the data transfer process in hardware,demonstrates the rationality of using USB as the serial port connection,and introduces the interaction between hardware and software.Secondly,in terms of software,the system uses LabVIEW programming software to design various functions and establish a human-computer interaction interface.Use the pulse classification standard stored in the database to judge the health status of the human body,collect information to establish a personal file in the database,and facilitate management and query of the data.In the aspect of pulse signal waveform processing,the characteristics of interference noise may be analyzed.The advantages of continuous wavelet discretization and wavelet transform principle are briefly described.The appropriate wavelet denoising method is selected and the pulse wave signal is processed by threshold shrinkage denoising method.In this paper,six different types of wavelet bases are selected to calculate the signal-to-noise ratio and root mean square error of the pulse wave signal.The comparison results show the wavelet base with the best denoising effect and comprehensively consider the signal needs.The number of layers broken down.Try the threshold shrinkage denoising to select the most appropriate combination of different parameters,and compare it with the translation invariant denoising method.After removing most of the interfering signals,the fitting curve formed by the four different interpolation functions is used to remove the baseline drift effect,and the final pulse processing signal waveform is obtained.After dividing and extracting the waveform Period,combining with the pulse diagnosis theory of traditional Chinese medicine,three methods in time domain analysis are used: characteristic point method,K-value method and pulse signal band energy analysis method to analyze the wavelet characteristics and the physiological and pathological information reflected by the wavelet.