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CN-121987171-A - Multi-parameter analysis method integrating arteriosclerosis evaluation and health monitoring system

CN121987171ACN 121987171 ACN121987171 ACN 121987171ACN-121987171-A

Abstract

The application relates to a multiparameter analysis method and a health monitoring system for integrated arteriosclerosis evaluation, which are characterized in that cuff pressure signals, electrocardiosignals and photoelectric volume pulse wave signals of two finger ends are synchronously collected, pressure oscillation wave signals are determined based on the cuff pressure signals, a blood pressure analysis process of the pressure oscillation wave signals is calibrated based on a contraction pressure calibration standard determined by the photoelectric volume pulse wave signals, a blood pressure value is determined, calculation of heartbeat time sequence standard, cuff pressure signals and photoelectric volume pulse wave signals determined based on the electrocardiosignals comprises an arteriosclerosis degree blood vessel function evaluation result, multiparameter correlation analysis is carried out on blood oxygen signals and electrocardiosignals extracted from the photoelectric volume pulse wave signals, the multiparameter analysis result is obtained, the blood pressure value, the blood vessel function evaluation result and the multiparameter analysis result are integrated, and a comprehensive health evaluation report is generated.

Inventors

  • ZHOU YONGJUN
  • TAN WENLONG

Assignees

  • 深圳市捷美瑞科技有限公司

Dates

Publication Date
20260508
Application Date
20260120

Claims (10)

  1. 1. A multi-parameter analysis method for integrated arteriosclerosis assessment, suitable for use in a health monitoring system comprising a cuff and at least two finger-clip probes integrated with an electrocardiographic electrode and an oximetry module, the multi-parameter analysis method comprising: In response to the operation of wearing the cuff by a user and inserting the double-sided finger tips into the finger grip probe, continuously and synchronously acquiring cuff pressure signals based on the cuff and continuously and synchronously acquiring electrocardiograph signals and photoplethysmography pulse wave signals from the double-sided finger tips based on the electrocardiograph electrode and the blood oxygen module in the pressurizing process and the deflating process of the cuff; Determining a systolic pressure calibration standard based on the photoplethysmography signal, determining a pressure oscillation wave signal based on the cuff pressure signal, calibrating a blood pressure analysis process of the pressure oscillation wave signal based on the systolic pressure calibration standard, and determining a calibrated blood pressure value; Determining a heartbeat time sequence reference based on an electrocardiosignal, and calculating a blood vessel function evaluation result based on the heartbeat time sequence reference, the cuff pressure signal and the photoelectric volume pulse wave signal, wherein the blood vessel function evaluation result at least comprises arteriosclerosis degree; Extracting a blood oxygen signal from the photoplethysmogram pulse wave signal, and performing multi-parameter correlation analysis on the electrocardiosignal and the blood oxygen signal to obtain a multi-parameter analysis result of a cardiovascular cooperative state; And integrating the blood pressure value, the blood vessel function evaluation result and the multi-parameter analysis result to generate and output a comprehensive health evaluation report.
  2. 2. The method according to claim 1, wherein determining a systolic blood pressure calibration reference based on the photoplethysmography signal comprises: Monitoring a first photoelectric volume pulse wave signal of the finger end at the same side of the cuff in the cuff pressurization process, and determining a first systolic pressure reference value based on the monitored disappearance event of the first photoelectric volume pulse wave signal; monitoring a first photoelectric volume pulse wave signal of the finger end at the same side of the cuff in the cuff deflation process, and determining a second systolic pressure reference value based on the monitored reproduction event of the first photoelectric volume pulse wave signal; And performing checksum fusion processing on the first systolic pressure reference value and the second systolic pressure reference value to obtain a systolic pressure calibration standard.
  3. 3. The method according to claim 2, wherein the verifying and fusing the first systolic pressure reference value and the second systolic pressure reference value to obtain a systolic pressure calibration standard specifically comprises: judging whether the absolute value of the difference between the first contraction pressure reference value and the second contraction pressure reference value is smaller than a preset threshold value or not; If yes, calculating an arithmetic average value or a weighted average value between the first systolic pressure reference value and the second systolic pressure reference value as the systolic pressure calibration standard.
  4. 4. The method according to claim 1, wherein calculating the blood vessel function evaluation result based on the heartbeat time sequence reference, the cuff pressure signal and the photoplethysmography signal specifically comprises: Extracting a cuff pressure wave starting point moment from a cuff pressure signal in the cuff deflation process, and extracting a ipsilateral pulse wave characteristic point moment from a photoelectric volume pulse wave signal acquired by the finger end on the same side as the cuff; Calculating an arm-finger pulse wave conduction velocity based on a pre-stored arm-finger anatomical path length, the ipsilateral pulse wave feature point moment and the cuff pressure wave starting point moment; Based on the arm-finger pulse wave velocity, the degree of arteriosclerosis was evaluated.
  5. 5. The method of claim 1, wherein the vascular function assessment further comprises vascular symmetry; the determining a heartbeat time sequence reference based on the electrocardiosignal, and calculating a blood vessel function evaluation result based on the heartbeat time sequence reference, the cuff pressure signal and the photoelectric volume pulse wave signal specifically comprises the following steps: Extracting an R wave crest value moment of each cardiac cycle from the synchronously acquired electrocardiosignals, and taking the R wave crest value moment as the heartbeat time sequence reference; Extracting a first pulse wave characteristic point moment corresponding to the same cardiac cycle from a first photoelectric volume pulse wave signal of the first finger end acquired synchronously, and extracting a second pulse wave characteristic point moment corresponding to the same cardiac cycle from a second photoelectric volume pulse wave signal of the second finger end acquired synchronously; calculating a first time difference between the first pulse wave characteristic point moment and the heartbeat time sequence reference, and calculating a second time difference between the second pulse wave characteristic point moment and the heartbeat time sequence reference; taking the absolute difference between the first time difference and the second time difference as a bilateral pulse wave conduction time difference; the vessel symmetry is assessed based on the bilateral pulse transit time differences.
  6. 6. The method according to claim 1, wherein the determining a pressure oscillation wave signal based on the cuff pressure signal, calibrating a blood pressure analysis process of the pressure oscillation wave signal based on the systolic pressure calibration standard, and determining a calibrated blood pressure value specifically includes: Extracting a pressure oscillation wave component based on a cuff pressure signal in the cuff deflation process, and generating an amplitude envelope corresponding to the pressure oscillation wave component; taking the contraction pressure calibration standard as a central reference value, and restraining the determined range of the contraction pressure in an upper allowable deviation interval and a lower allowable deviation interval of the central reference value; In the upper and lower allowable deviation intervals, determining a systolic pressure value based on the characteristic points of the amplitude envelope, and determining a diastolic pressure value based on the systolic pressure value and the morphology of the amplitude envelope; And taking the systolic pressure value and the diastolic pressure value as calibrated blood pressure values.
  7. 7. The method of claim 1, wherein the multiparameter analysis results comprise arrhythmia and blood pressure transient response analysis results; The multi-parameter correlation analysis is carried out on the electrocardiosignal and the blood oxygen signal to obtain a multi-parameter analysis result of cardiovascular collaborative state, which comprises the following steps: In the cuff deflation process, analyzing the synchronously acquired electrocardiosignals in real time to identify and classify arrhythmia events and corresponding arrhythmia event occurrence moments; taking each arrhythmia event occurrence moment as a center, intercepting a cuff pressure signal segment and an blood oxygen pulse wave signal segment in a front preset time window and a rear preset time window; analyzing the cuff pressure signal segment, extracting the instantaneous fluctuation change of blood pressure, analyzing the blood oxygen pulse wave signal segment, and evaluating the instantaneous change of peripheral blood oxygen perfusion; And correlating the arrhythmia event with the blood pressure transient fluctuation change and the peripheral blood oxygen perfusion transient change to generate arrhythmia and blood pressure transient response analysis results.
  8. 8. The method of claim 1, wherein the multiparameter analysis result comprises a blood pressure-heart rate variability analysis result; The multi-parameter correlation analysis is carried out on the electrocardiosignal and the blood oxygen signal to obtain a multi-parameter analysis result of cardiovascular collaborative state, which comprises the following steps: calculating heart rate variability parameters based on the electrocardiograph signals synchronously acquired during the cuff deflation process; Acquiring the calibrated blood pressure value determined during the cuff deflation process; analyzing the association relation between the heart rate variability parameter and the blood pressure value; and generating a blood pressure-heart rate variability analysis result based on the association relation.
  9. 9. The method of claim 1, wherein the multiparameter analysis results comprise vascular elasticity assessment results; The multi-parameter correlation analysis is carried out on the electrocardiosignal and the blood oxygen signal to obtain a multi-parameter analysis result of cardiovascular collaborative state, which comprises the following steps: Extracting an R wave crest value moment from the synchronously acquired electrocardiosignals as a first timing reference for heart beat initiation; Extracting pulse wave characteristic moments of the same heart cycle corresponding to the first time sequence reference from the synchronously acquired blood oxygen signals as second time sequence reference for the pulse wave to reach the finger end; calculating the time difference between the second time sequence reference and the first time sequence reference to obtain heart-finger pulse wave conduction time; Based on the heart-finger pulse wave conduction time and the blood pressure value, calculating through a preset blood vessel function evaluation model to obtain a quantized blood vessel elasticity evaluation result.
  10. 10. A health monitoring system, which is characterized by comprising a cuff, at least two finger-clip probes integrated with an electrocardio electrode and an blood oxygen module and a control module; Wherein the control module is configured to perform the multiparameter analysis method of any of the preceding claims 1-9.

Description

Multi-parameter analysis method integrating arteriosclerosis evaluation and health monitoring system Technical Field The application relates to the technical field of health monitoring, in particular to a multiparameter analysis method for integrated arteriosclerosis evaluation and a health monitoring system. Background Along with the continuous promotion of resident health management consciousness, market has put forward higher demands to integration, measurement accuracy and analysis degree of depth of domestic health monitoring equipment. The user needs an integrated solution capable of synchronously acquiring multidimensional physiological parameters such as blood pressure, electrocardio, vascular functions and the like and realizing comprehensive evaluation of a cardiovascular system, so as to replace the traditional monitoring equipment with single function and scattered operation and meet the core requirements of daily health screening and chronic disease management. The existing health monitoring technology has a plurality of key pain points, the requirements of clinical level monitoring and comprehensive assessment are difficult to meet, firstly, the multi-parameter integration and synchronism are insufficient, the existing scheme is mainly simple functional stacking of a sphygmomanometer, an electrocardiograph and an oximeter, the operation is complicated, the time sequence is asynchronous due to independent operation of each device, the true synchronous acquisition of cuff pressure signals, bilateral electrocardiosignals and photoelectric volume pulse wave signals cannot be realized, further, the vascular function assessment requiring high-precision time alignment and multi-parameter association analysis cannot be supported, secondly, the blood pressure measurement precision is limited, the traditional household electronic sphygmomanometer relies on an oscillography, the blood pressure is estimated by analyzing the amplitude envelope of pressure oscillation waves, the interference of factors such as vascular elasticity and heart rate is easy to occur, the reliable calibration standard is lacked, the core logic of the clinical Jin Biaozhun Korotkoff sound method is difficult to reproduce, the error is obvious in special crowds such as vascular sclerosis, thirdly, the signal acquisition stability and the analysis depth are insufficient, the traditional electrocardio acquisition mode is easy to interfere due to hand shake, and the existing device only outputs parameters, the vascular function assessment and the vascular function with high precision is difficult, the clinical reference value such as the depth of the isolation is limited. Therefore, the comprehensive requirements of multi-parameter true synchronous acquisition, high-precision blood pressure measurement, quantitative evaluation of blood vessel functions and deep analysis of cardiovascular collaborative states cannot be simultaneously met in the prior art, a technical scheme is needed, synchronous acquisition, accurate calculation and deep association of multi-dimensional parameters are realized through hardware integrated optimization and algorithm innovation, comprehensive and reliable health evaluation results are provided for users, and the blank of the prior art is filled. Disclosure of Invention The application provides a multiparameter analysis method and a health monitoring system for integrated arteriosclerosis evaluation, which can realize integration of multiparameter acquisition, accurate calculation and deep analysis and provide comprehensive and reliable health evaluation support. In a first aspect, the present application provides a multiparameter analysis method suitable for a health monitoring system comprising a cuff and at least two finger grip probes integrated with an electrocardiograph electrode and an oximetry module, the multiparameter analysis method comprising, in response to a user wearing the cuff and inserting a double-sided finger tip into the finger grip probes, continuously and synchronously acquiring cuff pressure signals based on the cuff and continuously and synchronously acquiring electrocardiograph signals and photoplethysmography pulse wave signals from the double-sided finger tips based on the electrocardiograph electrode and the oximetry module during pressurization and deflation of the cuff; determining a systolic pressure calibration standard based on the photoelectric volume pulse wave signal, determining a pressure oscillation wave signal based on the cuff pressure signal, calibrating a blood pressure analysis process of the pressure oscillation wave signal based on the systolic pressure calibration standard, determining a calibrated blood pressure value, determining a heartbeat time sequence standard based on an electrocardio signal, and calculating a blood vessel function evaluation result based on the heartbeat time sequence standard, the cuff pressure signal and the photoelectric volume pu