Research Of Pulse Recognition Technology Based On Pulse Wave

Pulse wave signal as a marker of early human metabolic disorders,to a large extent,can reflect the body’s heart and lungs and other organs of the functional status,through the radial artery pulse wave monitoring,can detect and prevent the body’s disease.The study of pulse wave in traditional Chinese medicine has been a thousand years of history.This article uses the pulse diagnosis of traditional Chinese medicine as an entry point to design a terminal pulse acquisition system based on pulse theory of traditional Chinese medicine.Integrate pulse diagnosis and computer science in Chinese traditional medicine,and use computer to automatically collect,process and extract features of pulse signals from human body,and identify and classify pulse signals,thus providing a basis for further sub-health testing.This article contains two parts: terminal pulse acquisition system design and pulse condition classification.The terminal pulse collecting device adopts a piezoresistive pressure sensor to perform voltage signal conversion on the pulse wave,and the signal processing device abandons the traditional hardware filter amplifying circuit.Direct use of high-resolution 24-bit A/D conversion chip,and a Bluetooth chip with a microprocessor(MCU),and loaded with an integrated display,can display real-time pulse waveform and pulse results to achieve human-computer interaction.Compared with the traditional pulse signal acquisition device,which is too complex,bulky,and difficult to carry,the pulse signal meter designed in this paper has the advantages of small size,display,and portability,which is conducive to the popularity of wearable,intelligent,and remote diagnosis.Pulse type classification,pulse data collected through Bluetooth wireless transmission,pulse signal analysis on the PC side,including wavelet transform selected the appropriate wavelet base to remove the baseline and filter to eliminate noise,and then use wavelet reconstruction to construct a smooth waveform,get Waveforms that facilitate the extraction of feature points.According to the theory of traditional Chinese medicine,the method of classification of pulse images is proposed,and the feature extraction of the data collected by the pulse acquisition system is performed,and feature vectors are constructed for the classification of pulse patterns.Finally,the paper applies pulse diagnosis to sub-health testing and uses the KNN classification algorithm to verify the feasibility of pulse detection for sub-health detection.The experimental results show that the wearable pulse acquisition system studied in this paper is compatible with the pulse diagnosis of traditional Chinese medicine.Using the wireless transmission method,it achieved the synchronous acquisition,curve drawing,transmission,storage,and processing of the three pulse signals at the optimal pulse pressure.In the study of pulse pattern classification and recognition,the algorithm used can well identify different types of pulse patterns.The KNN biometric algorithm has a good recognition of sub-health.The accuracy rate is stable at 91.67%,which is consistent with the diagnosis of sub-health by the pulse of Chinese medicine,which is conducive to the objectiveness of pulse diagnosis and the inheritance of traditional Chinese medicine theory.