CN114916923B - Electro-mechanical interconnection electrocardio pulse signal analysis method and system - Google Patents

Abstract

The invention discloses an electro-mechanical interconnection electrocardio pulse signal analysis method, which comprises the steps of collecting I or II lead ECG analog waveforms to obtain electrocardio analog signals, and synchronously collecting pulse wave analog signals through a piezoelectric sensor; the electrocardio-pulse interconnection waveform signals are obtained by conditioning the synchronously acquired electrocardio-analog signals and pulse wave analog signals, and then the electrocardio-pulse interconnection optimal waveform signals are obtained; according to the optimal waveform signal of the electrocardio-pulse interconnection, adopting a slope method to identify and calculate characteristic points (Rt (j) and Rp (j)) of the wave crest of the electrocardio-pulse R waveform, adopting the slope method to identify and calculate characteristic points (Pt (j), pp (j)) and (Vt (j), vp (j)) of the wave crest and the valley of the electrocardio-pulse interconnection, and then calculating to obtain the conduction time RPT of the pulse wave of the optimal waveform signal of the electrocardio-pulse interconnection in the arterial vessel. The invention can accurately calculate the conduction time of the pulse wave in the artery vessel.

Description

Electromechanically interconnected electrocardiogram pulse signal analysis method and system

Technical Field

The present invention relates to an electrocardiogram pulse signal analysis method, and in particular to an electromechanically interconnected electrocardiogram pulse signal analysis method and system.

Background Art

Arteriosclerosis can occur in the arteries of the human body. Atherosclerosis refers to the gradual deposition of lipid components in the blood in the blood vessels in the blood vessels to form plaques. As the blood vessel wall increases with age, its elasticity decreases, and together they form atherosclerosis. This process exists in all arteries of the human body. However, the harmfulness of atherosclerosis in important organs and tissues is extremely great. For example, coronary atherosclerosis will have symptoms such as angina pectoris, myocardial necrosis, myocardial fibrosis, and sudden coronary death; cerebral atherosclerosis will have symptoms such as brain tissue ischemia, acute lesion symptoms, and cerebral infarction; renal artery atherosclerosis will have symptoms such as hypertension and proteinuria; atherosclerosis occurs in the upper and lower limbs, causing ischemia and necrosis of the upper and lower limbs. Atherosclerosis in different parts of the body has different symptoms.

Atherosclerosis is a common disease among the middle-aged and elderly. Using color Doppler ultrasound to detect atherosclerosis is currently the most direct and common method for diagnosing atherosclerosis, but it requires expensive equipment and is subject to certain technical conditions.

Therefore, it is urgent to solve the above problems.

Summary of the invention

Purpose of the invention: The first purpose of the present invention is to provide an electromechanically interconnected ECG pulse signal analysis method that can accurately calculate the conduction time of the pulse wave in the arterial blood vessels.

The second object of the present invention is to provide an electromechanically interconnected ECG pulse signal analysis system that can accurately calculate the conduction time of the pulse wave in the arterial blood vessels.

Technical solution: To achieve the above purpose, the present invention discloses an electromechanically interconnected ECG pulse signal analysis method, comprising the following steps:

(1) Collect the ECG analog waveform of lead I or II to obtain the ECG analog signal.

(2) synchronously collecting pulse wave analog signals through piezoelectric sensors;

(3) Conditioning the synchronously collected ECG analog signal and pulse wave analog signal to obtain an ECG pulse interconnection waveform signal, and then obtaining an ECG pulse interconnection optimal waveform signal;

(4) Based on the best waveform signal of ECG pulse interconnection, the slope method is used to identify and calculate the ECG R waveform peak feature points (Rt(j), Rp(j)), and the slope method is used to identify and calculate the pulse wave peak and trough feature points (Pt(j), Pp(j)) and (Vt(j), Vp(j)), and then the pulse wave conduction time RPT in the arterial blood vessel of the best waveform signal of ECG pulse interconnection is calculated.

The specific steps of obtaining the best waveform signal of the ECG pulse interconnection in step (3) are as follows:

(3.1) Calculate the peak value Pp(i) and the valley value Py(i) of the i-th pulse wave;

(3.2) Calculate the pulse wave peak increment as the difference between the previous and next pulse wave peaks: dPp(i) = Pp(i) - Pp(i-1); Calculate the pulse wave trough increment as the difference between the previous and next pulse wave troughs: dPy(i) = Py(i) - Py(i-1);

(3.3) Find the starting point of the diamond MPstart_t;

(3.4) Find the end point of the diamond MPend_t;

(3.5) Calculate the maximum peak value Pp_max and the minimum valley value Py_min of the pulse wave; when the screening judgment conditions are met, it is considered that the best waveform of the ECG pulse interconnection is obtained, otherwise it is considered that there is no best waveform of the ECG pulse interconnection with obvious characteristics;

(3.6) After screening in step (3.5), the following situations occur: if there is no potential diamond wave, it means that the best interconnected waveform has not been found; when only one potential diamond pulse wave is found, the potential diamond pulse wave is the best interconnected waveform; when multiple potential diamond pulse waves are obtained, the one that meets the following conditions at the same time is the best interconnected waveform: the potential diamond time span is the largest: MPend_t-MPstart_t, and the potential diamond peak-to-peak span is the largest: Pp_max-Py_min.

Preferably, the specific steps of finding the rhombus starting point MPstart_t in step (3.3) are:

(3.3.1) Find the starting point where dPp(i) is continuously positive when it continues to rise, which is the starting point of the diamond peak climb MPp_t_start. When dPp(i) turns from positive to negative, it is the end point of the diamond peak climb MPp_t_end.

(3.3.2) Find the starting point where dPy(i) is continuously negative when it continues to decrease, which is the starting point of the diamond valley value MPy_t_start. When dPy(i) turns from negative to positive, it is the end point of the diamond valley value MPy_t_end.

(3.3.3) When |MPy_t_start-MPp_t_star|<2 heart rate cycles, determine that the starting point of the potential diamond wave is found: MPstart_t=min(MPy_t_start, MPp_t_star); when |MPy_t_start-MPp_t_star|>2 heart rate cycles, determine that the current pulse wave is not a diamond wave.

Furthermore, the specific steps for finding the diamond end point MPend_t in step (3.4) are:

(3.4.1) The MPp_t_end found in step (3.3.1) is the starting point of the rhombus wave peak value drop. From here, we start looking for dPp(i) to be continuously negative until dPp(i) becomes positive or zero, which is the end point MPp_t_over of the rhombus wave peak value drop.

(3.4.2) MPy_t_end found in step (3.3.2) is the starting point of the rising diamond trough value. From here, we start looking for dPy(i) to be continuously positive until dPy(i) becomes negative or zero, which is the end point MPy_t_over of the rising diamond trough value.

(3.4.3) When |MPp_t_over-MPy_t_over|<2 heart rate cycles, determine that the end point of the potential diamond wave is found: MPend_t=min(MPp_t_over, MPy_t_over); when |MPp_t_over-MPy_t_over|>2 heart rate cycles, determine that the current pulse wave is not a diamond wave.

Furthermore, the screening judgment condition in step (3.5) is:

a) The amplitude of the end point of the diamond peak climb MPp_v_end>k1×Pp_max;

b) The amplitude of the end point of the diamond valley drop MPy_v_end<k2×Py_min;

c) k1, k2 are set thresholds, and 0.5<k1<1 and 0.5<k2<1.

Furthermore, the specific steps of calculating the peak feature points of the ECG waveform in step (4) are:

(A) Let the waveform to be analyzed be Rwav, and the i-th data be Rwav(i); calculate the slope of the waveform k(i) = Rwav(i) - Rwav(i-1);

(B) Initialization stage: Two seconds before Rwav, the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)), 0.375<n1<1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Rwav(0, 2s)), 0.375<n2<1;

(C) Measurement phase: finding the starting point Ts and end point Te of the potential peak waveform segment;

(C1) Determine Ts value: When the following conditions are met at the same time: 1) Rwav(i)>Ath; 2) k(i)>kmax, it means that the starting point Ts of the potential peak is found;

(C2) When the starting point of the potential peak waveform segment is found and Rwav(i)<Ath, it indicates that the end point Te of the potential peak waveform segment is found;

(C3) The peak value can be found from the Ts-Te waveform segment, which is max(Rwav(Ts, Te)), the amplitude is recorded as Rp(j), and the time is recorded as Rt(j);

(C4) The j-th feature obtained consists of feature points (Rt(j), Rp(j)).

Preferably, the specific steps of calculating the pulse wave peak and valley characteristic points in step (4) are:

(a) Let the waveform to be analyzed be Pwav, and the i-th data be Pwav(i); calculate the slope of the waveform k(i) = Pwav(i) - Pwav(i-1);

(b) Initialization stage: Two seconds before Pwav, the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)), 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Pwav(0, 2s)), 0.375 < n2 < 1;

(c) Measurement phase: finding the starting point Ts and end point Te of the potential peak waveform segment;

(c1) Determine Ts value: When the following conditions are met at the same time: 1) Pwav(i)>Ath; 2) k(i)>kmax, it means that the starting point Ts of the potential peak is found;

(c2) When the starting point of the potential peak waveform segment is found and Pwav(i)<Ath, it indicates that the end point Te of the potential peak waveform segment is found;

(c3) The peak value can be found from the Ts-Te waveform segment, which is max(Pwav(Ts, Te)), the amplitude is recorded as Pp(j), and the time is recorded as Pt(j);

(c4) Find the minimum value between the two peaks to get the valley value, that is, min(Pwav(Pt(j), Pt(j-1))), the amplitude is recorded as Vp(j), and the time is recorded as Vt(j);

(c5) The j-th feature obtained consists of two points (Pt(j), Pp(j)) and (Vt(j), Vp(j)).

Furthermore, in step (4), the calculation formula of RPT of the optimal waveform signal of the central electrical pulse interconnection is: RPT=Pt(j)-Rt(j).

相应得到该八个心动周期的平均脉率PR和平均心率HR，

Furthermore, the method further includes the following steps: (5) finding eight pulse waves before and after the peak of the diamond-shaped waveform segment in the ECG pulse interconnection waveform, analyzing and calculating the RPT of the eight pulse waves, and taking the average value thereof.

The average pulse rate PR and average heart rate HR of the eight cardiac cycles are obtained accordingly.

The present invention discloses an electromechanically interconnected electrocardiovascular pulse signal analysis system, comprising an electrocardiovascular conditioning module, a pulse conditioning module, an A/D sampling module, an optimal waveform acquisition module and a pulse wave conduction calculation module.

The ECG conditioning module is used to collect the I or II lead ECG analog waveform to obtain the ECG analog signal;

The pulse conditioning module is used to collect pulse wave simulation signals synchronously with the ECG simulation signals through the piezoelectric sensor;

A/D sampling module, used for receiving ECG analog signal and pulse wave analog signal and conditioning and outputting ECG pulse interconnection waveform digital signal;

The best waveform acquisition module is used to obtain the best ECG pulse interconnection waveform signal from the ECG pulse interconnection waveform signal;

The pulse wave conduction calculation module is used to calculate the pulse wave conduction time RPT of the ECG pulse interconnection optimal waveform signal in the arterial blood vessel based on the ECG pulse interconnection optimal waveform signal.

Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: (1) The present invention can accurately calculate the conduction time of the pulse wave in the arterial blood vessels, which is convenient for subsequent auxiliary clinicians to diagnose atherosclerosis; (2) The present invention appropriately pressurizes the piezoelectric sensor for obtaining the pulse wave, and selects a suitable and stable optimal pulse diamond wave as the reference waveform and the R wave during the same heart beat to further ensure the accuracy of the RPT calculation value; (3) The present invention averages the RPT calculated from the ECG R wave and pulse wave of the eight heart beat intervals before and after the maximum peak wave of the accurately obtained optimal ECG pulse interconnection waveform, so as to reduce the measurement error caused by the natural objective variation of the intervals before and after the heart beat, so as to make the parameter calculation value more accurate, and provide more accurate auxiliary parameters for subsequent clinicians to perform clinical diagnosis.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a schematic diagram of the process of the present invention;

FIG2 is a schematic diagram of a central electrical pulse interconnection waveform signal of the present invention;

FIG3 is a schematic diagram of a process for collecting pulse wave simulation signals in the present invention;

FIG4 is a schematic diagram of an optimal waveform signal of a central electrical pulse interconnection according to the present invention;

FIG5 is a schematic diagram of the RPT in the present invention;

FIG6 is a schematic diagram of a flow chart of the system of the present invention;

FIG7 is a detection schematic diagram of the system of the present invention;

FIG8 is a schematic diagram of the present invention for detecting the wrist artery RPT of an elderly person;

FIG. 9 is a schematic diagram of detecting the wrist artery RPT of a young person in the present invention.

DETAILED DESCRIPTION

The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

In order to detect atherosclerosis in a simple, non-invasive and inexpensive manner, the present invention proposes to synchronously detect and record the ECG pulse (electromechanical interconnection) wave signal, and automatically detect and calculate the time RPT from the ECG R wave to the pulse wave peak (or trough). RPT (R wave-pulse wave transit time) refers to the time interval between the apex of the ECG R wave and the pulse wave peak of the same cardiac interval, and is the time it takes for the pulse wave to be conducted in the arteries. The ventricles of the heart eject blood into the aorta to impact the arterial wall, causing the arterial blood pressure and arterial volume to change periodically in each cardiac cycle, causing the arterial wall to pulsate (fluctuate) periodically, which is called the arterial blood pressure wave, commonly known as the pulse wave. The pulse wave is a mechanical wave. Obviously, as the arteries become less elastic due to atherosclerosis, the pulse fluctuations are conducted faster in the arteries. When the ventricle begins to eject blood, the corresponding R wave ECG signal is transmitted to all parts of the human body in an instant under the action of the cardiac electromagnetic field. Therefore, RPT refers to the time it takes for the pulse wave to travel to a certain artery. The starting point of this time is always set at the ejection outlet of the ventricle, that is, the root of the aorta, which is also the starting point of the pulse wave conduction according to the electrophysiological principle. The degree of atherosclerosis in various parts of the human body is different, and the corresponding pulse wave conduction time is also different. The more severe the arterial sclerosis, the worse the elasticity, and the faster the pulse wave conduction time. Therefore, the length of RPT can evaluate the degree of atherosclerosis in various parts of the human body.

Example 1

As shown in FIG. 1 and FIG. 2 , the present invention provides an electromechanically interconnected ECG pulse signal analysis method, comprising the following steps:

(1) Collect the ECG analog waveform of lead I or II to obtain the ECG analog signal.

(2) acquiring pulse wave simulation signals synchronously with ECG simulation signals through piezoelectric sensors;

(3) Conditioning the synchronously collected ECG analog signal and pulse wave analog signal to obtain an ECG pulse interconnection waveform digital signal, and then obtaining an ECG pulse interconnection optimal waveform signal;

As shown in FIG4 , the specific steps for obtaining the best waveform signal of the ECG pulse interconnection are:

(3.1) Calculate the peak value Pp(i) and valley value Py(i) of the i-th pulse wave;

(3.2) Calculate the pulse wave peak increment as the difference between the previous and next pulse wave peaks: dPp(i) = Pp(i) - Pp(i-1); Calculate the pulse wave trough increment as the difference between the previous and next pulse wave troughs: dPy(i) = Py(i) - Py(i-1);

(3.3) The specific steps to find the rhombus starting point MPstart_t are:

(3.3.1) Find the starting point where dPp(i) is continuously positive when it continues to rise, which is the starting point of the diamond peak climb MPp_t_start. When dPp(i) turns from positive to negative, it is the end point of the diamond peak climb MPp_t_end.

(3.3.2) Find the starting point where dPy(i) is continuously negative when it continues to decrease, which is the starting point of the diamond valley value MPy_t_start. When dPy(i) turns from negative to positive, it is the end point of the diamond valley value MPy_t_end.

(3.3.3) When |MPy_t_start-MPp_t_star|<2 heart rate cycles, determine that the starting point of the potential rhombus wave is found: MPstart_t=min(MPy_t_start, MPp_t_star); When |MPy_t_start-MPp_t_star|>2 heart rate cycles, determine that the current pulse wave is not a rhombus wave;

(3.4) Find the end point of the diamond MPend_t. The specific steps are:

(3.4.1) The MPp_t_end found in step (3.3.1) is the starting point of the rhombus wave peak value drop. From here, we start looking for dPp(i) to be continuously negative until dPp(i) becomes positive or zero, which is the end point MPp_t_over of the rhombus wave peak value drop.

(3.4.2) MPy_t_end found in step (3.3.2) is the starting point of the rising diamond trough value. From here, we start looking for dPy(i) to be continuously positive until dPy(i) becomes negative or zero, which is the end point MPy_t_over of the rising diamond trough value.

(3.4.3) When |MPp_t_over-MPy_t_over|<2 heart rate cycles, determine that the end point of the potential rhombus wave is found: MPend_t=min(MPp_t_over, MPy_t_over); when |MPp_t_over-MPy_t_over|>2 heart rate cycles, determine that the current pulse wave is not a rhombus wave;

(3.5) Calculate the maximum peak value Pp_max and the minimum valley value Py_min of the pulse wave; when the following conditions are met, it is considered that the best waveform of the ECG pulse interconnection is obtained, otherwise it is considered that there is no best waveform of the ECG pulse interconnection with obvious characteristics:

a) The amplitude of the end point of the diamond peak climb MPp_v_end>k1×Pp_max;

b) The amplitude of the end point of the diamond valley drop MPy_v_end<k2×Py_min;

c) k1, k2 are set thresholds, and 0.5<k1<1 and 0.5<k2<1;

(3.6) After screening in step (3.5), the following situations occur: if there is no potential diamond wave, it means that the best interconnected waveform has not been found; when only one potential diamond pulse wave is found, the potential diamond pulse wave is the best interconnected waveform; when multiple potential diamond pulse waves are obtained, the one that meets the following conditions at the same time is the best interconnected waveform: the potential diamond time span is the largest: MPend_t-MPstart_t, the potential diamond peak-to-peak span is the largest: Pp_max-Py_min;

(4) Based on the best waveform signal of the ECG pulse interconnection, the slope method is used to identify and calculate the ECG R waveform peak feature points (Rt(j), Rp(j)), and the slope method is used to identify and calculate the pulse wave peak and trough feature points, that is, the feature points (Pt(j), Pp(j)) and (Vt(j), Vp(j)), and then the pulse wave conduction time RPT of the ECG pulse interconnection best waveform signal in the arterial blood vessel is calculated. The RPT is calculated by the formula RPT=Pt(j)-Rt(j), as shown in FIG5 ;

The specific steps for calculating the peak feature points of the ECG waveform are:

(A) Let the waveform to be analyzed be Rwav, and the i-th data be Rwav(i); calculate the slope of the waveform k(i) = Rwav(i) - Rwav(i-1);

(B) Initialization stage: Two seconds before Rwav, the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)), 0.375<n1<1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Rwav(0, 2s)), 0.375<n2<1;

(C) Measurement phase: finding the starting point Ts and end point Te of the potential peak waveform segment;

(C1) Determine Ts value: When the following conditions are met at the same time: 1) Rwav(i)>Ath; 2) k(i)>kmax, it means that the starting point Ts of the potential peak is found;

(C2) When the starting point of the potential peak waveform segment is found and Rwav(i)<Ath, it indicates that the end point Te of the potential peak waveform segment is found;

(C3) From the Ts-Te waveform segment, the peak can be found, which is max(Rwav(Ts, Te)), the amplitude is recorded as Rp(j), and the time is recorded as Rt(j);

(C4) The j-th feature obtained consists of feature points (Rt(j), Rp(j));

The specific steps for calculating the pulse wave peak and valley characteristic points are:

(a) Let the waveform to be analyzed be Pwav, and the i-th data be Pwav(i); calculate the slope of the waveform k(i) = Pwav(i) - Pwav(i-1);

(b) Initialization stage: Two seconds before Pwav, the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)), 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Pwav(0, 2s)), 0.375 < n2 < 1;

(c) Measurement phase: finding the starting point Ts and end point Te of the potential peak waveform segment;

(c1) Determine Ts value: When the following conditions are met at the same time: 1) Pwav(i)>Ath; 2) k(i)>kmax, it means that the starting point Ts of the potential peak is found;

(c2) When the starting point of the potential peak waveform segment is found and Pwav(i)<Ath, it indicates that the end point Te of the potential peak waveform segment is found;

(c3) The peak value can be found from the Ts-Te waveform segment, which is max(Pwav(Ts, Te)), the amplitude is recorded as Pp(j), and the time is recorded as Pt(j);

(c4) Find the minimum value between the two peaks to get the valley value, that is, min(Pwav(Pt(j), Pt(j-1))), the amplitude is recorded as Vp(j), and the time is recorded as Vt(j);

(c5) The j-th feature obtained consists of two points (Pt(j), Pp(j)) and (Vt(j), Vp(j)).

Example 2

As shown in FIG1 , the present invention provides an electromechanically interconnected ECG pulse signal analysis method, comprising the following steps:

(1) Collect the ECG analog waveform of lead I or II to obtain the ECG analog signal.

(2) acquiring pulse wave simulation signals synchronously with ECG simulation signals through piezoelectric sensors;

(3) Conditioning the synchronously collected ECG analog signal and pulse wave analog signal to obtain an ECG pulse interconnection waveform digital signal, and then obtaining an ECG pulse interconnection optimal waveform signal;

The specific steps for obtaining the best waveform signal of ECG pulse interconnection are:

(3.1) Calculate the peak value Pp(i) and the valley value Py(i) of the i-th pulse wave;

(3.2) Calculate the pulse wave peak increment as the difference between the previous and next pulse wave peaks: dPp(i) = Pp(i) - Pp(i-1); Calculate the pulse wave trough increment as the difference between the previous and next pulse wave troughs: dPy(i) = Py(i) - Py(i-1);

(3.3) The specific steps to find the rhombus starting point MPstart_t are:

(3.3.1) Find the starting point where dPp(i) is continuously positive when it continues to rise, which is the starting point of the diamond peak climb MPp_t_start. When dPp(i) turns from positive to negative, it is the end point of the diamond peak climb MPp_t_end.

(3.3.2) Find the starting point where dPy(i) is continuously negative when it continues to decrease, which is the starting point of the diamond valley value MPy_t_start. When dPy(i) turns from negative to positive, it is the end point of the diamond valley value MPy_t_end.

(3.3.3) When |MPy_t_start-MPp_t_star|<2 heart rate cycles, determine that the starting point of the potential rhombus wave is found: MPstart_t=min(MPy_t_start, MPp_t_star); When |MPy_t_start-MPp_t_star|>2 heart rate cycles, determine that the current pulse wave is not a rhombus wave;

(3.4) Find the end point of the diamond MPend_t. The specific steps are:

(3.4.1) The MPp_t_end found in step (3.3.1) is the starting point of the rhombus wave peak value drop. From here, we start looking for dPp(i) to be continuously negative until dPp(i) becomes positive or zero, which is the end point MPp_t_over of the rhombus wave peak value drop.

(3.4.2) MPy_t_end found in step (3.3.2) is the starting point of the rising diamond trough value. From here, we start looking for dPy(i) to be continuously positive until dPy(i) becomes negative or zero, which is the end point MPy_t_over of the rising diamond trough value.

(3.4.3) When |MPp_t_over-MPy_t_over|<2 heart rate cycles, determine that the end point of the potential rhombus wave is found: MPend_t=min(MPp_t_over, MPy_t_over); when |MPp_t_over-MPy_t_over|>2 heart rate cycles, determine that the current pulse wave is not a rhombus wave;

(3.5) Calculate the maximum peak value Pp_max and the minimum valley value Py_min of the pulse wave; when the following conditions are met, it is considered that the best waveform of the ECG pulse interconnection is obtained, otherwise it is considered that there is no best waveform of the ECG pulse interconnection with obvious characteristics:

a) The amplitude of the end point of the diamond peak climb MPp_v_end>k1×Pp_max;

b) The amplitude of the end point of the diamond valley drop MPy_v_end<k2×Py_min;

c) k1, k2 are set thresholds, and 0.5<k1<1 and 0.5<k2<1;

(3.6) After screening in step (3.5), the following situations occur: if there is no potential diamond wave, it means that the best interconnected waveform has not been found; when only one potential diamond pulse wave is found, the potential diamond pulse wave is the best interconnected waveform; when multiple potential diamond pulse waves are obtained, the one that meets the following conditions at the same time is the best interconnected waveform: the potential diamond time span is the largest: MPend_t-MPstart_t, the potential diamond peak-to-peak span is the largest: Pp_max-Py_min;

(4) Based on the best waveform signal of the ECG pulse interconnection, the slope method is used to identify and calculate the ECG R waveform peak feature points (Rt(j), Rp(j)), and the slope method is used to identify and calculate the pulse wave peak and trough feature points, that is, the feature points (Pt(j), Pp(j)) and (Vt(j), Vp(j)), and then the pulse wave conduction time RPT of the ECG pulse interconnection best waveform signal in the artery is calculated, and RPT is calculated by the formula RPT=Pt(j)-Rt(j);

The specific steps for calculating the peak feature points of the ECG waveform are:

(A) Let the waveform to be analyzed be Rwav, and the i-th data be Rwav(i); calculate the slope of the waveform k(i) = Rwav(i) - Rwav(i-1);

(B) Initialization stage: Two seconds before Rwav, the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)), 0.375<n1<1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Rwav(0, 2s)), 0.375<n2<1;

(C) Measurement phase: finding the starting point Ts and end point Te of the potential peak waveform segment;

(C1) Determine Ts value: When the following conditions are met at the same time: 1) Rwav(i)>Ath; 2) k(i)>kmax, it means that the starting point Ts of the potential peak is found;

(C2) When the starting point of the potential peak waveform segment is found and Rwav(i)<Ath, it indicates that the end point Te of the potential peak waveform segment is found;

(C3) The peak value can be found from the Ts-Te waveform segment, which is max(Rwav(Ts, Te)), the amplitude is recorded as Rp(j), and the time is recorded as Rt(j);

(C4) The j-th feature obtained consists of feature points (Rt(j), Rp(j));

The specific steps for calculating the pulse wave peak and valley characteristic points are:

(a) Let the waveform to be analyzed be Pwav, and the i-th data be Pwav(i); calculate the slope of the waveform k(i) = Pwav(i) - Pwav(i-1);

(b) Initialization stage: Two seconds before Pwav, the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)), 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Pwav(0, 2s)), 0.375 < n2 < 1;

(c) Measurement phase: finding the starting point Ts and end point Te of the potential peak waveform segment;

(c1) Determine Ts value: When the following conditions are met at the same time: 1) Pwav(i)>Ath; 2) k(i)>kmax, it means that the starting point Ts of the potential peak is found;

(c2) When the starting point of the potential peak waveform segment is found and Pwav(i)<Ath, it indicates that the end point Te of the potential peak waveform segment is found;

(c3) The peak value can be found from the Ts-Te waveform segment, which is max(Pwav(Ts, Te)), the amplitude is recorded as Pp(j), and the time is recorded as Pt(j);

(c4) Find the minimum value between the two peaks to get the valley value, that is, min(Pwav(Pt(j), Pt(j-1))), the amplitude is recorded as Vp(j), and the time is recorded as Vt(j);

(c5) The j-th feature obtained consists of two points (Pt(j), Pp(j)) and (Vt(j), Vp(j));

相应得到该八个心动周期的平均脉率PR和平均心率HR，

(5) Find the eight pulse waves before and after the peak of the diamond waveform segment in the ECG pulse interconnection waveform, analyze and calculate the eight RPTs, and take their average value

The average pulse rate PR and average heart rate HR of the eight cardiac cycles are obtained accordingly.

Example 3

As shown in FIG. 1 and FIG. 6 , the electromechanically interconnected ECG pulse signal analysis system of the present invention includes an ECG conditioning module, a pulse conditioning module, an A/D sampling module, an optimal waveform acquisition module and a pulse wave conduction calculation module.

As shown in FIG7 , the ECG conditioning module is used to collect the I or II lead ECG simulation waveform to obtain the ECG simulation signal; wherein the limb lead electrode of the ECG conditioning module obtains the I or II lead ECG simulation waveform.

As shown in Figure 3, the pulse conditioning module is used to synchronously collect pulse wave simulation signals through piezoelectric sensors and ECG simulation signals. The pulse conditioning module inflates and pressurizes the piezoelectric sensor cuff placed on the artery, and deflates and decompresses it to adaptively select the appropriate pressure to obtain the pulse wave simulation signal through the piezoelectric sensor. The pulse wave simulation signal contains the best pulse blood pressure waveform group in a diamond shape; the best pulse blood pressure waveform should meet the following conditions: whether a diamond-shaped pulse wave group appears; whether the amplitude of the diamond-shaped pulse wave group is the largest. The A/D sampling module is used to receive ECG simulation signals and pulse wave simulation signals and condition and output ECG pulse interconnection waveform signals, that is, to convert the synchronous sampling signal into a data signal. As shown in Figure 2, the synchronously collected ECG and pulse data waveforms are placed in the same coordinate system to form an ECG-pulse interconnected waveform signal. In order to make the analyzed and calculated RPT have better regularity and consistency, that is, good repeatability, it is found that the diamond-shaped wave group appearing in the ECG-pulse interconnected waveform is the best waveform. As the reference waveform for detecting RPT, the 8 blood pressure waveforms before and after the peak of the diamond-shaped wave group can be taken to calculate its RPT.

The best waveform acquisition module is used to obtain the best waveform signal of ECG pulse interconnection from the ECG pulse interconnection waveform signal; the specific steps of obtaining the best waveform signal of ECG pulse interconnection are:

Calculate the peak value Pp(i) and the valley value Py(i) of the i-th pulse wave;

The pulse wave peak increment is calculated as the difference between the previous and next pulse wave peaks: dPp(i)=Pp(i)-Pp(i-1);

The pulse wave trough value increment is calculated as the difference between the previous and next pulse wave trough values: dPy(i)=Py(i)-Py(i-1);

Find the diamond starting point MPstart_t, find the starting point that is continuously positive when dPp(i) continues to rise, that is, the diamond peak climbing starting point MPp_t_start, when dPp(i) changes from positive to negative, it is the diamond peak climbing end point MPp_t_end; find the starting point that is continuously negative when dPy(i) continues to decrease, that is, the diamond valley value decreasing starting point MPy_t_start, when dPy(i) changes from negative to positive, it is the diamond valley value decreasing end point MPy_t_end; when |MPy_t_start-MPp_t_star|<2 heart rate cycles, determine that the starting point of the potential diamond wave is found: MPstart_t=min(MPy_t_start, MPp_t_star); when |MPy_t_start-MPp_t_star|>2 heart rate cycles, determine that the current pulse wave is not a diamond wave;

Find the end point MPend_t of the diamond wave. The MPp_t_end found is the starting point of the decrease of the peak value of the diamond wave. From this, start to look for dPp(i) to be continuously negative, until dPp(i) is positive or zero, which is the end point MPp_t_over of the decrease of the peak value of the diamond wave; the MPy_t_end found is the starting point of the increase of the trough value of the diamond wave. From this, start to look for dPy(i) to be continuously positive, until dPy(i) is negative or zero, which is the end point MPy_t_over of the increase of the trough value of the diamond wave; when |MPp_t_over-MPy_t_over|<2 heart rate cycles, determine that the end point of the potential diamond wave is found: MPend_t=min(MPp_t_over, MPy_t_over); when |MPp_t_over-MPy_t_over|>2 heart rate cycles, determine that the current pulse wave is not a diamond wave;

Calculate the maximum peak value Pp_max and the minimum valley value Py_min of the pulse wave; when the screening judgment conditions are met, it is considered that the best waveform of ECG pulse interconnection is obtained, otherwise it is considered that there is no best waveform of ECG pulse interconnection with obvious characteristics; the screening judgment conditions are: a) the amplitude of the end point of the diamond peak climbing MPp_v_end>k1×Pp_max; b) the amplitude of the end point of the diamond valley falling MPy_v_end<k2×Py_min; c) k1, k2 are the set thresholds, and 0.5<k1<1 and 0.5<k2<1;

Through the above screening, the following situations occur: if there is no potential diamond wave, it means that the best interconnected waveform has not been found; when only one potential diamond pulse wave is found, the potential diamond pulse wave is the best interconnected waveform; when multiple potential diamond pulse waves are obtained, the one that meets the following conditions at the same time is the best interconnected waveform: the potential diamond time span is the largest: MPend_t-MPstart_t, and the potential diamond peak-to-peak span is the largest: Pp_max-Py_min.

The pulse wave conduction calculation module is used to calculate the conduction time RPT of the pulse wave of the best waveform signal of the ECG pulse interconnection in the arterial blood vessels based on the best waveform signal of the ECG pulse interconnection; the pulse wave conduction calculation module first uses the slope method to identify and calculate the ECG waveform peak characteristic points (Rt(j), Rp(j)), and uses the slope method to identify and calculate the pulse wave peak and valley characteristic points (Pt(j), Pp(j)) and (Vt(j), Vp(j)), and then calculates the conduction time RPT of the pulse wave of the best waveform signal of the ECG pulse interconnection in the arterial blood vessels, and the calculation formula of RPT is: RPT=Pt(j)-Rt(j).

The calculation of the ECG waveform peak feature point is as follows:

Assume that the waveform to be analyzed is Rwav, and the i-th data is Rwav(i); calculate the slope of the waveform k(i) = Rwav(i) - Rwav(i-1);

Initialization stage: Two seconds before Rwav, the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)), 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Rwav(0, 2s)), 0.375 < n2 < 1;

Measurement phase: Find the starting point Ts and end point Te of the potential peak waveform segment;

Determine the Ts value: When the following conditions are met at the same time: 1) Rwav(i)>Ath; 2) k(i)>kmax, it means that the starting point Ts of the potential peak is found;

When the starting point of the potential peak waveform segment is found and Rwav(i)<Ath, it means that the end point Te of the potential peak waveform segment is found;

The peak can be found from the Ts-Te waveform segment, which is max(Rwav(Ts, Te)), the amplitude is recorded as Rp(j), and the time is recorded as Rt(j);

The j-th feature obtained consists of feature points (Rt(j), Rp(j)).

The calculation of the pulse wave peak and valley characteristic points is as follows:

Assume that the waveform to be analyzed is Pwav, and the i-th data is Pwav(i); calculate the slope of the waveform k(i) = Pwav(i) - Pwav(i-1);

Initialization stage: Two seconds before Pwav, the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)), 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Pwav(0, 2s)), 0.375 < n2 < 1;

Measurement phase: Find the starting point Ts and end point Te of the potential peak waveform segment;

Determine the Ts value: When the following conditions are met at the same time: 1) Pwav(i)>Ath; 2) k(i)>kmax, it means that the starting point Ts of the potential peak is found;

When the starting point of the potential peak waveform segment is found and Pwav(i)<Ath, it means that the end point Te of the potential peak waveform segment is found;

The peak can be found from the Ts-Te waveform segment, which is max(Pwav(Ts, Te)), the amplitude is recorded as Pp(j), and the time is recorded as Pt(j);

Finding the minimum value between two peaks gives the trough value, i.e., min(Pwav(Pt(j), Pt(j-1))), with the amplitude recorded as Vp(j) and the time as Vt(j);

The j-th feature obtained consists of two points (Pt(j), Pp(j)) and (Vt(j), Vp(j)).

相应得到该八个心动周期的平均脉率PR和平均心率HR，

It also includes an average parameter calculation module, which finds eight pulse waves before and after the peak part of the diamond waveform segment in the ECG pulse interconnection waveform, analyzes and calculates the RPT of the eight pulse waves, and takes the average value

The average pulse rate PR and average heart rate HR of the eight cardiac cycles are obtained accordingly.

The present invention uses an electromechanically interconnected ECG pulse signal analysis system to test a number of people of different ages. The RPT of an old man (81 years old) and a young man (28 years old) on their wrist arteries are shown in Figures 8 and 9. According to actual measurements, the RPT (310ms) of the relatively healthy old man is smaller than the RPT (320ms) of the young man. Obviously, the degree of arterial vascular sclerosis of the old man is greater than that of the young man. If the old man has other underlying diseases (such as high-risk factors such as hyperlipidemia and diabetes that damage the structure and function of the blood vessel wall) and cause severe arterial vascular sclerosis, the measured RPT will be smaller than this time.

Claims (6)

1. An electro-mechanical interconnection electrocardio pulse signal analysis method is characterized by comprising the following steps:

(1) Collecting I or II lead ECG analog waveform to obtain ECG analog signal,

(2) Synchronously acquiring pulse wave analog signals through a piezoelectric sensor;

(3) The electrocardio-pulse interconnection waveform signals are obtained by conditioning the synchronously acquired electrocardio-analog signals and pulse wave analog signals, and then the electrocardio-pulse interconnection optimal waveform signals are obtained;

the method comprises the following specific steps of obtaining an optimal waveform signal of the electrocardio-pulse interconnection:

(3.1) calculating a peak value Pp (i) of the ith pulse wave and a valley value Py (i) of the pulse wave;

(3.2) calculating the increment of the pulse wave peak value as the difference of the pulse wave peak values before and after: dPp (i) = Pp (i) -Pp (i-1); calculating the incremental change of the pulse wave trough value as the difference of the front and the rear pulse wave trough values: dPy (i) = Py (i) -Py (i-1);

(3.3) searching a diamond starting point MPstart _ t, which comprises the following specific steps:

(3.3.1) searching for a starting point which is continuously positive when the dPp (i) continuously rises, namely a diamond-shaped peak value climbing starting point MPp _ t _ start, and when the dPp (i) continuously rises from positive to negative, namely a diamond-shaped peak value climbing end point MPp _ t _ end;

(3.3.2) searching for a starting point which is continuously negative when the dPy (i) continuously descends, namely a diamond valley descending starting point MPy _ t _ start, and when the dPy (i) is changed from negative to positive, namely a diamond valley descending end point MPy _ t _ end;

(3.3.3) when | MPy _ t _ start-MPp _ t _ start | <2 heart rate cycles, it is determined that the start of the potential diamond wave is found: mptstart _ t = min (MPy _ t _ start, MPp _ t _ start); determining that the current pulse wave is not a diamond wave when the absolute value MPy _ t _ start-MPp _ t _ star >2 heart rate periods;

(3.4) searching a diamond end point MPend _ t, which comprises the following specific steps:

(3.4.1) finding MPp _ t _ end in the step (3.3.1) as a starting point of the diamond wave peak value reduction, and starting to find that the dPp (i) is continuously negative until the dPp (i) is positive or zero, namely as an end point MPp _ t _ over of the diamond wave peak value reduction;

(3.4.2) finding MPy _ t _ end in the step (3.3.2) as the starting point of the diamond wave trough value rising, and starting to search for dPy (i) continuously positive until the dPy (i) is negative or zero, namely as the end point of the diamond wave trough value rising MPy _ t _ over;

(3.4.3) determining to find an endpoint for the potential diamond wave when | MPp _ t _ over-MPy _ t _ over | <2 heart rate cycles: MPend _ t = min (MPp _ t _ over, MPy _ t _ over); determining that the current pulse wave is not a diamond wave when the absolute value MPp _ t _ over-MPy _ t _ over >2 heart rate periods;

(3.5) calculating the maximum peak value Pp _ max and the minimum valley value Py _ min of the pulse wave; when the screening judgment condition is met, considering that the optimal waveform of the electrocardio-pulse interconnection is obtained, or considering that the optimal waveform of the electrocardio-pulse interconnection with obvious characteristics does not exist;

wherein the screening judgment conditions are as follows:

a) The amplitude MPp _ v _ end of the diamond peak value climbing terminal point is larger than k1 multiplied by Pp _ max;

b) The amplitude MPy _ v _ end of the diamond valley descent end point is less than k2 multiplied by Py _ min;

c) k1 and k2 are set threshold values, and 0.5-k1-k2-k1;

(3.6) by the screening of step (3.5), the following occurs: if no potential diamond wave exists, the fact that the best interconnection waveform is not found is indicated; when only one potential rhombic pulse wave is found, the potential rhombic pulse wave is an interconnection optimal waveform; when a plurality of potential rhombus pulse waves are obtained, the following conditions are simultaneously met, namely the optimal waveform is interconnected: the potential diamond time span is largest: MPend _ t-MPstart _ t, with the largest span of potential diamond peaks: pp _ max-Py _ min;

(4) According to the optimal waveform signal of the electrocardio-pulse interconnection, adopting a slope method to identify and calculate characteristic points (Rt (j) and Rp (j)) of the wave crest of the electrocardio-pulse R waveform, adopting the slope method to identify and calculate characteristic points (Pt (j), pp (j)) and (Vt (j), vp (j)) of the wave crest and the wave trough, and then calculating to obtain the conduction time RPT of the pulse wave of the optimal waveform signal of the electrocardio-pulse interconnection in the arterial vessel.

2. The method for analyzing electro-mechanically interconnected heart pulse signals according to claim 1, wherein: the specific steps of calculating the characteristic points of the wave crests of the electrocardiographic waveform in the step (4) are as follows:

(A) Setting the waveform to be analyzed as Rwav, and the ith data as Rwav (i); calculating the slope k (i) = Rwav (i) -Rwav (i-1) of the waveform;

(B) An initialization stage: two seconds before Rwav, calculated as: slope threshold Kth = n1 × kmax, where kmax = max (k (0, 2s)), 0.375-n 1-n; an amplitude threshold Ath = n2 × Amax, where Amax = max (Rwav (0, 2s)), 0.375 nls 2 and 1;

(C) And (3) a measuring stage: searching a starting point Ts and an end point Te of the potential peak waveform segment;

(C1) Determining a Ts value: when simultaneously satisfying: 1) Rwav (i) > Ath; 2) k (i) > kmax, representing that the starting point Ts of the potential peak is found;

(C2) When the starting point of the potential peak waveform segment is found and Rwav (i) < Ath, the end point Te of the potential peak waveform segment is found;

(C3) Finding a peak from the Ts-Te waveform segment, namely max (Rwav (Ts, te)), the amplitude is recorded as Rp (j), and the time is recorded as Rt (j);

(C4) The j-th feature obtained is composed of feature points (Rt (j), rp (j)).

3. The method for analyzing electro-mechanically interconnected heart pulse signals according to claim 1, wherein: the specific steps of calculating the pulse peak and valley feature points in the step (4) are as follows:

(a) Setting a waveform to be analyzed as Pwav, and setting the ith data as Pwav (i); calculating the slope k (i) = Pwav (i) -Pwav (i-1) of the waveform;

(b) An initialization stage: two seconds before Pwav, calculated as: slope threshold Kth = n1 × kmax, where kmax = max (k (0, 2s)), 0.375-n 1-n; an amplitude threshold Ath = n2 × Amax, where Amax = max (Pwav (0, 2s)), 0.375-n 2-n 1;

(c) And (3) a measuring stage: searching a starting point Ts and an end point Te of the potential peak waveform segment;

(c1) Determining the Ts value: when simultaneously satisfying: 1) Pwav (i) > Ath; 2) k (i) > kmax, representing that the starting point Ts of the potential peak is found;

(c2) When the starting point of the potential peak waveform segment is found and Pwav (i) < Ath, the end point Te of the potential peak waveform segment is found;

(c3) Finding a peak from the Ts-Te waveform segment, namely max (Pwav (Ts, te)), marking the amplitude as Pp (j) and the time as Pt (j);

(c4) Finding a minimum value between two wave crests to obtain a valley value, namely min (Pwav (Pt (j), pt (j-1))), recording the amplitude as Vp (j), and recording the time as Vt (j);

(c5) The obtained jth feature is composed of two points (Pt (j), pp (j)) and (Vt (j), vp (j)).

4. The method for analyzing electro-mechanically interconnected heart pulse signals according to claim 1, wherein: the calculation formula of the RPT of the optimal waveform signal of the center electrical pulse interconnection in the step (4) is as follows: RPT = Pt (j) -Rt (j).

5. The electro-mechanically interconnected heart pulse signal analysis method according to claim 4, characterized in that: further comprising the steps of: (5) Searching eight pulse waves before and after the peak value part of diamond-shaped waveform segment in the electrocardio-pulse interconnection waveform, analyzing and calculating to obtain the RPT of the eight pulse waves, and taking the average value

Correspondingly, an average pulse rate PR and an average heart rate HR, <' > in the eight cardiac cycles are obtained>

6. The utility model provides an electro-mechanical interconnection's heart pulse signal analysis system which characterized in that: comprises an electrocardio conditioning module, a pulse conditioning module, an A/D sampling module, an optimal waveform acquisition module and a pulse wave conduction calculation module,

the electrocardio conditioning module is used for acquiring I or II lead ECG analog waveforms to obtain electrocardio analog signals;

the pulse conditioning module is used for synchronously acquiring pulse wave analog signals through the piezoelectric sensor and the electrocardio analog signals;

the A/D sampling module is used for receiving the electrocardio analog signals and the pulse wave analog signals and conditioning and outputting electrocardio-pulse interconnection waveform digital signals;

the optimal waveform acquisition module is used for acquiring the optimal waveform signal of the electrocardio-pulse interconnection from the electrocardio-pulse interconnection waveform signal, and the acquisition of the optimal waveform signal of the electrocardio-pulse interconnection is as follows:

calculating the peak value Pp (i) of the ith pulse wave and the valley value Py (i) of the pulse wave;

calculating the increment of the pulse wave peak value as the difference of the pulse wave peak values before and after: dPp (i) = Pp (i) -Pp (i-1); calculating the incremental change of the pulse wave trough value as the difference of the front and the rear pulse wave trough values: dPy (i) = Py (i) -Py (i-1);

looking for the diamond start point mptart _ t,

finding a continuous positive starting point when the dPp (i) continuously rises, namely a diamond peak value climbing starting point MPp _ t _ start, and when the dPp (i) continuously rises from positive to negative, namely a diamond peak value climbing end point MPp _ t _ end;

searching for a starting point which is continuously negative when the dPy (i) continuously decreases, namely a diamond valley value decreasing starting point MPy _ t _ start, and when the dPy (i) is changed from negative to positive, namely a diamond valley value decreasing end point MPy _ t _ end;

when | MPy _ t _ start-MPp _ t _ start | <2 heart rate cycles, it is determined that the start of a potential diamond wave is found: mptstart _ t = min (MPy _ t _ start, MPp _ t _ start); determining that the current pulse wave is not a diamond wave when the absolute value of MPy _ t _ start-MPp _ t _ star is greater than 2 heart rate periods;

searching a diamond-shaped end point MPend _ t,

the found MPp _ t _ end is the starting point of the diamond wave peak value reduction, and then dPp (i) is continuously found to be negative until the dPp (i) is positive or zero, namely the end point MPp _ t _ over of the diamond wave peak value reduction;

the found MPy _ t _ end is the starting point of the rising of the rhombus wave trough value, and then the searching of dPy (i) is continuously positive until the dPy (i) is negative or zero, namely the end point MPy _ t _ over of the rising of the rhombus wave trough value is started;

when | MPp _ t _ over-MPy _ t _ over | <2 heart rate cycles, it is determined to find the end point of the potential diamond wave: MPend _ t = min (MPp _ t _ over, MPy _ t _ over); determining that the current pulse wave is not a diamond wave when the absolute value MPp _ t _ over-MPy _ t _ over >2 heart rate periods;

calculating the maximum peak value Pp _ max and the minimum valley value Py _ min of the pulse wave; when the screening judgment condition is met, considering that the optimal waveform of the electrocardio-pulse interconnection is obtained, or considering that the optimal waveform of the electrocardio-pulse interconnection with obvious characteristics does not exist;

wherein the screening judgment conditions are as follows:

a) The amplitude MPp _ v _ end of the diamond peak value climbing terminal point is larger than k1 multiplied by Pp _ max;

b) The amplitude MPy _ v _ end of the diamond valley descent end point is less than k2 multiplied by Py _ min;

c) k1 and k2 are set threshold values, and 0.5-k1-1 and 0.5-k2-1;

by screening, the following situations arise: if no potential diamond wave exists, it is indicated that the optimal waveform of interconnection is not found; when only one potential diamond-shaped pulse wave is found, the potential diamond-shaped pulse wave is an optimal waveform of interconnection; when a plurality of potential rhombus pulse waves are obtained, the following conditions are simultaneously met, namely the optimal waveform is interconnected: the potential diamond time span is largest:

MPend _ t-MPstart _ t, with the largest span of potential diamond peaks: pp _ max-Py _ min;

and the pulse wave conduction calculation module is used for calculating the conduction time RPT of the pulse wave of the electrocardio-pulse interconnection optimal waveform signal in the arterial vessel according to the electrocardio-pulse interconnection optimal waveform signal.

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