Research On Pulse Rate Variability Based On Pulse Signals In Patients With Cardiovascular Diseases

The formation and changes of pulse wave are influenced by the functional status of the heart,blood and arterial vessels,and contain physiological and pathological information of the cardiovascular system.Pulse examination has the advantages of being non-invasive,simple to operate,and low-cost,making it one of the important methods for evaluating cardiovascular diseases.Compared with commonly used electrocardiographic monitoring and blood tests for cardiovascular diseases,pulse examination can avoid the limitations of larger equipment volume,complex operation,and requiring professional medical staff assistance.The type and severity of cardiovascular diseases can be evaluated by analyzing indicators such as the rhythm,intensity,frequency,and pulse rate variability.Therefore,the extraction and analysis of pulse signals from the human wrist have potential application value for early warning and real-time monitoring of cardiovascular diseases.As pulse signal is one of the important physiological parameters of the human body,this article presents the design of a pulse signal acquisition sensor and establishes a method for analyzing pulse rate variability.The accuracy and applicability of the proposed method are verified through the validation of pulse data.The specific research content is as follows:For the shortcoming of low accuracy,poor consistency,and low reliability in pulse sensor,this article proposes a finger-like pulse sensor based on a Microelectro Mechanical Systems(MEMS)pressure chip,which measures the pulse signal.The sensor consists of a MEMS resistive pressure chip as the core unit,as well as key components of a rigid matrix,flexible film,and a silicon-based circuit.Under external forces,the sensor through the flexible film deforms and transmits the force to the Wheatstone bridge,enabling measurement of the force-electricity conversion.The output performance test experiment results show that the sensitivity of the sensor can reach 0.04V/k Pa,with a linear determination coefficient R~2>0.99,the hysteresis is less than 1%,and has good repeatability and stability.It is proved that this sensor is feasible to measure pulse signals.As the time domain,frequency domain and nonlinear analysis methods of PRV signal cannot accurately describe the local feature information,combined with the pitch detection method and fuzzy entropy theory,a PRV signal analysis method based on Circular Average Magnitude Difference Function(CAMDF)fuzzy entropy is proposed.The pulse signal is processed for noise removal and baseline drift using Ensemble Empirical Mode Decomposition(EEMD)and Cubic Spline Interpolation(CSI),and the pulse rate variability signal is extracted by identifying the maximum peak point in the pulse signal.The PRV signal characteristic parameters of healthy people and cardiovascular disease patients are calculated from the time domain,frequency domain,and the proposed method,and the parameters are evaluated using t-test and Fisher discriminant analysis.The experimental results show that the proposed method has good accuracy in differential analysis of PRV signals for healthy people and cardiovascular disease patients.To verify the accuracy of CAMDF fuzzy entropy analysis method in clinical pulse data,a self-developed pulse acquisition device was used in this study for analysis of the collected clinical pulse signals,and CAMDF fuzzy entropy analysis method was used for parameter calculation of PRV signals.The results show that the proposed method can effectively distinguish the PRV signals of healthy individuals and arrhythmia patients,and three typical PRV signals are consistent with the characteristics of normal pulse,knotted pulse and intermittent pulse in traditional Chinese medicine pulse diagnosis.Therefore,the CAMDF fuzzy entropy analysis method has potential application value in cardiovascular system health monitoring and the identification and classification of traditional Chinese medicine pulse diagnosis.