An arterial sclerosis degree detection system and method based on a photoelectric sensor

Abstract

The present invention discloses a detection system and method for the degree of arteriosclerosis based on a photoelectric sensor, including collecting the I or II lead ECG analog waveform to obtain an electrocardiogram analog signal, and synchronously collecting a photoelectric pulse wave analog signal through the photoelectric sensor; synchronously collecting and conditioning to obtain an electrocardiogram and photoelectric pulse interconnected waveform signal, and then obtaining the best electrocardiogram and photoelectric pulse interconnected waveform signal; according to the best electrocardiogram and photoelectric pulse interconnected waveform signal, using the slope method to identify and calculate the peak feature points of the electrocardiogram R waveform, using the slope method to identify and calculate the peak feature points of the photoelectric pulse wave, and then calculating the conduction time RPT of the photoelectric pulse wave in the arterial blood vessel of the best electrocardiogram and photoelectric pulse interconnected waveform signal; at the same time, calculating the main wave width tu of the photoelectric pulse wave; if the conduction time RPT is less than the set threshold, the degree of arteriosclerosis of the arterial blood vessel is abnormal, and if the main wave width tu of the photoelectric pulse wave is greater than the set threshold, the degree of arteriosclerosis of the arterial blood vessel is abnormal.

Description

Technical Field

[0001] The present invention relates to a method for detecting the degree of arterial vascular sclerosis, and in particular to a system and method for detecting the degree of arterial vascular sclerosis based on a photoelectric sensor. Background Art

[0002] 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 occurring in the upper and lower limbs will cause ischemia and necrosis of the upper and lower limbs. Atherosclerosis in different parts of the body has different symptoms.

[0003] 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.

[0004] Therefore, it is urgent to solve the above problems. Summary of the invention

[0005] Purpose of the invention: The first purpose of the present invention is to provide a method for detecting the degree of arterial vascular sclerosis based on a photoelectric sensor by accurately measuring the conduction time of the photoelectric pulse wave in the arterial blood vessel and the width tu value in the photoelectric pulse waveform.

[0006] The second object of the present invention is to provide an arterial vascular sclerosis degree detection system based on a photoelectric sensor that can accurately calculate the pulse wave conduction time in the arterial blood vessels and the width tu value in the photoelectric pulse waveform.

[0007] Technical solution: To achieve the above purpose, the present invention discloses a method for detecting the degree of arterial vascular sclerosis based on a photoelectric sensor, comprising the following steps:

[0008] (1) Collect the ECG analog waveform of lead I or II to obtain the ECG analog signal.

[0009] (2) synchronously collecting photoelectric pulse wave analog signals through photoelectric sensors;

[0010] (3) Conditioning the synchronously collected ECG analog signal and photoelectric pulse wave analog signal to obtain ECG and photoelectric pulse interconnection waveform signals, and then obtaining the ECG and photoelectric pulse interconnection optimal waveform signals;

[0011] (4) Based on the best waveform signal of the ECG and photoelectric pulse interconnection, the slope method is used to identify and calculate the ECG R waveform peak characteristic points (Rt(j), Rp(j)), and the slope method is used to identify and calculate the photoelectric pulse wave peak characteristic points (Pt(j), Pp(j)), and then the photoelectric pulse wave conduction time RPT=Pt(j)-Rt(j) of the best waveform signal of the ECG and photoelectric pulse interconnection in the arterial blood vessel is calculated; at the same time, based on the best waveform signal of the ECG and photoelectric pulse interconnection, the main wave width tu of the photoelectric pulse wave is calculated, where the main wave width tu of the photoelectric pulse wave is the width when the main wave height of the photoelectric pulse waveform is half;

[0012] (5) If the photoelectric pulse wave conduction time RPT in the arterial blood vessel is less than the set threshold and / or the photoelectric pulse wave main wave width tu is greater than the set threshold, the degree of arterial sclerosis is abnormal.

[0013] Among them, the specific steps of obtaining the best waveform signal of the ECG and photoelectric pulse interconnection in step (3) are:

[0014] (3.1) Calculate the peak value Pp(i) and valley value Py(i) of the i-th photoelectric pulse wave;

[0015] (3.2) The photoelectric pulse wave peak value increment is calculated as the difference between the photoelectric pulse wave peak values ​​before and after: dPp(i) = Pp(i) - Pp(i-1); The photoelectric pulse wave valley value increment is calculated as the difference between the photoelectric pulse wave valley values ​​before and after: dPy(i) = Py(i) - Py(i-1);

[0016] (3.3) Find the starting point of the diamond MPstart_t;

[0017] (3.4) Find the end point of the diamond MPend_t;

[0018] (3.5) Calculate the maximum peak value Pp_max and the minimum valley value Py_min of the photoelectric pulse wave; when the screening judgment conditions are met, it is considered that the best waveform of the ECG and photoelectric pulse interconnection is obtained, otherwise it is considered that there is no obvious characteristic of the best waveform of the ECG and photoelectric pulse interconnection;

[0019] (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.

[0020] Preferably, the specific steps of finding the rhombus starting point MPstart_t in step (3.3) are:

[0021] (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.

[0022] (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.

[0023] (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 photoelectric pulse wave is not a diamond wave.

[0024] Furthermore, the specific steps for finding the diamond end point MPend_t in step (3.4) are:

[0025] (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.

[0026] (3.4.2) MPy_t_end found in step (3.3.2) is the starting point of the rising valley value of the diamond wave. From this point, 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 falling peak value of the diamond wave;

[0027] (3.4.3) When |MPp_t_over-MPy_t_over|<2 heart rate cycles, the end point of the potential diamond wave is determined: MPend_t=min(MPp_t_over, MPy_t_over); when |MPp_t_over-MPy_t_over|>2 heart rate cycles, it is determined that the current photoelectric pulse wave is not a diamond wave.

[0028] Preferably, the screening judgment condition in step (3.5) is:

[0029] a) The amplitude of the end point of the diamond peak climb MPp_v_end>k1×Pp_max;

[0030] b) The amplitude MPy_v_end at the end of the rhombus valley value drop < k2 × Py_min;

[0031] c) k1 and k2 are set thresholds, and 0.5 < k1 < 1 and 0.5 < k2 < 1.

[0032] Furthermore, the specific steps for calculating the peak feature points of the electrocardiogram waveform in step (4) are as follows:

[0033] (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);

[0034] (B) Initialization stage: In the first two seconds of Rwav, calculate: the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)) and 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Rwav(0, 2s)) and 0.375 < n2 < 1;

[0035] (C) Measurement stage: Find the starting point Ts and the ending point Te of the potential peak waveform segment;

[0036] (C1) Determine the value of Ts: When both 1) Rwav(i) > Ath and 2) k(i) > kmax are satisfied, it means the starting point Ts of the potential peak is found;

[0037] (C2) When the starting point of the potential peak waveform segment is found and Rwav(i) < Ath, it means the ending point Te of the potential peak waveform segment is found;

[0038] (C3) The peak can be found from the Ts - Te waveform segment, that is, max(Rwav(Ts, Te)), the amplitude is denoted as Rp(j), and the time is denoted as Rt(j);

[0039] (C4) The j-th feature obtained consists of the feature points (Rt(j), Rp(j)).

[0040] Preferably, the specific steps for calculating the peak feature points of the photoelectric pulse wave in step (4) are as follows:

[0041] (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);

[0042] (b) Initialization stage: In the first two seconds of Pwav, it is calculated that: 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;

[0043] (c) Measurement stage: Find the starting point Ts and the ending point Te of the potential peak waveform segment;

[0044] (c1) Determine the value of Ts: When both of the following conditions are met: 1) Pwav(i) > Ath; 2) k(i) > kmax, it indicates that the starting point Ts of the potential wave peak is found;

[0045] (c2) When the starting point of the potential peak waveform segment is found and Pwav(i) < Ath, it indicates that the ending point Te of the potential peak waveform segment is found;

[0046] (c3) The wave peak can be found from the Ts - Te waveform segment, that is, max(Pwav(Ts, Te)), the amplitude is denoted as Pp(j), and the time is denoted as Pt(j);

[0047] (c4) The j - th feature obtained is composed of (Pt(j), Pp(j)).

[0048] Furthermore, it also includes the steps of: finding eight photoelectric pulse waves before and after the peak part of the diamond waveform segment in the electrocardiogram - photoelectric pulse interconnection waveform, and analyzing and calculating the RPT of these eight photoelectric pulse waves, and taking the average value Correspondingly, the average pulse rate PR and the average heart rate HR of these eight cardiac cycles are obtained, Judge the degree of arterial vascular sclerosis according to the average value of the RPT of the eight photoelectric pulse waves, the average pulse rate PR, and the average heart rate HR.

[0049] An arterial vascular sclerosis degree detection system based on a photoelectric sensor according to the present invention includes an electrocardiogram amplifier, a photoelectric amplifier, an A / D sampling module, an optimal waveform acquisition module, a pulse wave conduction calculation module, and a pulse wave width calculation module.

[0050] The electrocardiogram amplifier is used to connect the limb lead electrode patches to collect the I or II lead ECG analog waveform and obtain the electrocardiogram analog signal;

[0051] The photoelectric amplifier is equipped with a photoelectric sensor. The photoelectric amplifier is connected to an inflatable cuff that is closely attached to the corresponding arterial blood vessel position on the skin surface to inflate and pressurize, deflate and decompress the photoelectric sensor, and adaptively select an appropriate pressure magnitude to obtain a photoelectric pulse wave analog signal that is synchronously collected with the electrocardiogram analog signal;

[0052] A / D sampling module, used for synchronously receiving ECG analog signal and photoelectric pulse wave analog signal and conditioning and outputting ECG and photoelectric pulse interconnected waveform digital signal;

[0053] The best waveform acquisition module is used to obtain the best waveform signals of ECG and photoelectric pulse interconnection from the ECG and photoelectric pulse interconnection waveform signals;

[0054] The pulse wave conduction calculation module is used to calculate the pulse wave conduction time RPT of the best waveform signal of the ECG and photoelectric pulse interconnection in the arterial blood vessel according to the best waveform signal of the ECG and photoelectric pulse interconnection;

[0055] The pulse wave width calculation module is used to calculate the main wave width tu of the photoelectric pulse wave according to the best waveform signal of the electrocardiogram and photoelectric pulse interconnection, wherein the main wave width tu of the photoelectric pulse wave is the width at half the height of the main wave of the photoelectric pulse waveform.

[0056] Among them, when the pulse wave conduction time RPT in the arterial blood vessel is less than the set threshold, the degree of arterial vascular sclerosis is abnormal, and when the main wave width tu of the photoelectric pulse wave is greater than the set threshold, the degree of arterial vascular sclerosis is abnormal.

[0057] 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 photoelectric pulse wave in the arterial blood vessel and the main wave width tu of the photoelectric pulse wave, which is convenient for subsequent auxiliary clinicians to diagnose atherosclerosis; (2) The present invention appropriately pressurizes the photoelectric sensor that obtains the photoelectric 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 the photoelectric pulse wave of the eight heart beat intervals before and after the maximum peak wave of the accurately obtained optimal ECG and photoelectric pulse interconnected waveforms, 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

[0058] Figure 1 It is a schematic diagram of the process of the present invention;

[0059] Figure 2 It is a schematic diagram of the central electrocardiogram interconnection waveform signal of the present invention;

[0060] Figure 3 It is a schematic diagram of the process of collecting pulse wave simulation signals in the present invention;

[0061] Figure 4 A schematic diagram of the optimal waveform signal of the central electrical pulse interconnection of the present invention;

[0062] Figure 5 is a schematic diagram of the RPT in the present invention;

[0063] Figure 6 It is a schematic diagram of the process of the system of the present invention;

[0064] Figure 7 It is a detection schematic diagram of the system of the present invention;

[0065] Figure 8 The present invention is a synchronous interconnected waveform diagram of the electrocardiogram and photoelectric pulse wave of the right toes of the elderly and the young;

[0066] Fig. 9 It is a synchronously interconnected waveform diagram of the electrocardiogram and photoelectric pulse wave detected on the fingers of the elderly in the present invention;

[0067] Fig.10 It is a synchronously interconnected waveform diagram of the electrocardiogram and photoelectric pulse wave detected on the fingers of young people in the present invention;

[0068] Fig.11 This is a schematic diagram of the present invention detecting the width tu value in the arterial waveform at the finger tip of the elderly;

[0069] Fig.12 This is a schematic diagram of the present invention detecting the width tu value in the arterial waveform at the finger tip of a young person. DETAILED DESCRIPTION

[0070] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0071] In order to detect atherosclerosis in a simple, non-invasive and inexpensive manner, the present invention proposes to synchronously detect and record the photoelectric pulse wave signal, and automatically detect and calculate the time RPT from the ECG R wave to the photoelectric pulse wave peak (or trough). Figure 5As shown in the figure, RPT (Rwave-pulse wave transit time) refers to the time interval between the apex of the ECG R wave and the peak value of the pulse wave in the same cardiac interval, and is the time it takes for the pulse wave to be transmitted in the arteries. The heart's ventricles eject blood to the aorta to impact the arterial wall, causing the arterial blood pressure and arterial volume to change periodically in each cardiac cycle; when the heart contracts, the blood vessel volume increases; when the heart relaxes, the blood vessel volume decreases; thus, the light that passes through the skin tissue and is incident on the blood vessel wall is reflected back to the skin, which is sensitive to the change in blood volume in the blood vessel, causing a periodic change (pulsation) in light intensity, which is converted into an electrical signal pulsation wave by the photoelectric sensor, called a photoelectric arterial blood pressure wave, commonly known as a pulse wave (formed by the heartbeat). Obviously, as arteries become less elastic due to atherosclerosis, the pulse fluctuations are transmitted faster in the arteries. When the ventricle starts to eject blood, the corresponding ECG R wave 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 the artery in a certain part. The starting point of this time is always stipulated at the ejection outlet of the ventricle, that is, the root of the aorta, which is also the starting point of the pulse wave transmission according to the electrophysiological principle. The degree of atherosclerosis in different parts of the human body is different, and the corresponding pulse wave transmission time is also different. The more severe the artery atherosclerosis, the worse the elasticity, and the faster the pulse wave transmission time; the arterial atherosclerosis area will reduce the elasticity of the artery on the one hand, and on the other hand, it will also make the blood vessels thinner, resulting in increased vascular resistance, which may be more serious for the elderly and those with vascular diseases caused by hypertension and diabetes. When the heart contracts, the peripheral blood volume is the largest, the light absorption is the largest, and the intensity of the reflected light detected is the smallest. When the heart relaxes, it is just the opposite, and the intensity of the reflected light detected is the largest. From this principle, we can know that if the vascular resistance increases, the process of blood flow into the blood vessels when the heart contracts and blood flow back to the heart from the blood vessels when the heart relaxes will slow down, causing the pulse electrical waveform converted by the photoelectric sensor to be wider, while the opposite is true for intact or healthy blood vessels. The width of the main wave of the photoelectric pulse waveform at half the height (middle width) is now defined as the width of the main wave of the photoelectric pulse wave (milliseconds, ms), represented by tu (such as Figure 8 As shown). The present invention studied the wrist (finger tip), RPT < 300ms suspected abnormal, RPT ≥ 300ms normal; ear, RPT < 230ms suspected abnormal, RPT ≥ 230ms normal; right toe, RPT < 415ms suspected abnormal, RPT ≥ 415ms normal; and the middle-width tu value can evaluate the degree of atherosclerosis of the arterial blood vessels in the human body at the time of measurement. We studied the finger tip, tu < 120ms normal, tu ≥ 120ms suspected abnormal, such as Fig.11 and Fig.12The above thresholds are for reference only and can be adjusted at any time to make them more accurate as the amount of test data increases. Therefore, the duration of RPT and the size of TU value can evaluate the degree of arteriosclerosis in various parts of the human body.

[0072] Example 1

[0073] like Figure 1 and Figure 2 As shown, the present invention provides a method for detecting the degree of arterial vascular sclerosis based on a photoelectric sensor, comprising the following steps:

[0074] (1) Collect the ECG analog waveform of lead I or II to obtain the ECG analog signal.

[0075] (2) synchronously collecting photoelectric pulse wave analog signals through photoelectric sensors;

[0076] (3) Conditioning the synchronously collected ECG analog signal and photoelectric pulse wave analog signal to obtain ECG and photoelectric pulse interconnection waveform signals, and then obtaining the ECG and photoelectric pulse interconnection optimal waveform signals;

[0077] like Figure 4 As shown, the specific steps for obtaining the best waveform signal for ECG and photoelectric pulse interconnection are:

[0078] (3.1) Calculate the peak value Pp(i) and valley value Py(i) of the i-th photoelectric pulse wave;

[0079] (3.2) The photoelectric pulse wave peak value increment is calculated as the difference between the photoelectric pulse wave peak values ​​before and after: dPp(i) = Pp(i) - Pp(i-1); The photoelectric pulse wave valley value increment is calculated as the difference between the photoelectric pulse wave valley values ​​before and after: dPy(i) = Py(i) - Py(i-1);

[0080] (3.3) Find the starting point of the diamond MPstart_t;

[0081] The specific steps for finding the rhombus starting point MPstart_t in step (3.3) are:

[0082] (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.

[0083] (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.

[0084] (3.3.3) When |MPy_t_start - MPp_t_star| < two 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| > two heart rate cycles, it is determined that the current photoelectric pulse wave is not a diamond wave;

[0085] (3.4) Find the end point MPend_t of the diamond wave;

[0086] The specific steps to find the end point MPend_t of the diamond wave in step (3.4) are as follows:

[0087] (3.4.1) MPp_t_end found in step (3.3.1) is the starting point of the peak value drop of the diamond wave. Starting from this point, find that dPp(i) is continuously negative until dPp(i) is positive or zero, which is the end point MPp_t_over of the peak value drop of the diamond wave;

[0088] (3.4.2) MPy_t_end found in step (3.3.2) is the starting point of the valley value rise of the diamond wave. Starting from this point, find that dPy(i) is continuously positive until dPy(i) is negative or zero, which is the end point MPy_t_over of the peak value drop of the diamond wave;

[0089] (3.4.3) When |MPp_t_over - MPy_t_over| < two 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| > two heart rate cycles, it is determined that the current photoelectric pulse wave is not a diamond wave;

[0090] (3.5) Calculate the maximum peak value Pp_max and the minimum valley value Py_min of the photoelectric pulse wave; when the screening and judgment conditions are met, it is considered that the best waveform of the electrocardiogram and photoelectric pulse interconnection is obtained, otherwise it is considered that there is no best waveform of the electrocardiogram and photoelectric pulse interconnection with obvious features;

[0091] The screening and judgment conditions in step (3.5) are as follows:

[0092] a) The amplitude MPp_v_end of the end point of the diamond peak climb > k1 × Pp_max;

[0093] b) The amplitude MPy_v_end of the end point of the diamond valley value drop < k2 × Py_min;

[0094] c) k1 and k2 are set thresholds, and 0.5 < k1 < 1 and 0.5 < k2 < 1.

[0095] (3.6) After screening through step (3.5), the following situations occur: If there is no potential diamond wave, it indicates that the optimal interconnected waveform has not been found; when only one potential diamond pulse wave is found, this potential diamond pulse wave is the optimal interconnected waveform; when multiple potential diamond pulse waves are obtained, the one that simultaneously meets the following conditions is the optimal interconnected waveform: the maximum potential diamond time span: MPend_t - MPstart_t, and the maximum potential diamond peak-to-peak span: Pp_max - Py_min.

[0096] (3.6) After screening through step (3.5), the following situations occur: If there is no potential diamond wave, it indicates that the optimal interconnected waveform has not been found; when only one potential diamond pulse wave is found, this potential diamond pulse wave is the optimal interconnected waveform; when multiple potential diamond pulse waves are obtained, the one that simultaneously meets the following conditions is the optimal interconnected waveform: the maximum potential diamond time span: MPend_t - MPstart_t, and the maximum potential diamond peak-to-peak span: Pp_max - Py_min;

[0097] (4) According to the optimal waveform signal of electrocardiogram and optoelectronic pulse interconnection, the peak feature points (Rt(j), Rp(j)) of the electrocardiogram R waveform are identified and calculated using the slope method, and the peak feature points (Pt(j), Pp(j)) of the optoelectronic pulse wave are identified and calculated using the slope method. Then, the conduction time RPT of the optoelectronic pulse wave in the arterial blood vessel of the optimal waveform signal of electrocardiogram and optoelectronic pulse interconnection is calculated as RPT = Pt(j) - Rt(j); simultaneously, according to the optimal waveform signal of electrocardiogram and optoelectronic pulse interconnection, the main wave width tu of the optoelectronic pulse wave is calculated, where the main wave width tu of the optoelectronic pulse wave is the width when the main wave height of the optoelectronic pulse waveform is half.

[0098] The specific steps for calculating the peak feature points of the electrocardiogram waveform in step (4) are as follows:

[0099] (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);

[0100] (B) Initialization stage: In the first two seconds of Rwav, calculate: the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)) and 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Rwav(0, 2s)) and 0.375 < n2 < 1;

[0101] (C) Measurement stage: Find the starting point Ts and the ending point Te of the potential peak waveform segment;

[0102] (C1) Determine the value of Ts: When both of the following conditions are met: 1) Rwav(i) > Ath; 2) k(i) > kmax, it indicates that the starting point Ts of the potential wave peak is found;

[0103] (C2) When the starting point of the potential wave peak waveform segment is found and Rwav(i) < Ath, it indicates that the ending point Te of the potential peak waveform segment is found;

[0104] (C3) The wave peak can be found from the Ts - Te waveform segment, which is max(Rwav(Ts, Te)), the amplitude is denoted as Rp(j), and the time is denoted as Rt(j);

[0105] (C4) The j-th feature obtained is composed of the feature points (Rt(j), Rp(j));

[0106] The specific steps for calculating the photoelectric pulse wave peak feature points in step (4) are as follows:

[0107] (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);

[0108] (b) Initialization stage: In the first two seconds of Pwav, calculate: the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)) and 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Pwav(0, 2s)) and 0.375 < n2 < 1;

[0109] (c) Measurement stage: Find the starting point Ts and ending point Te of the potential peak waveform segment;

[0110] (c1) Determine the value of Ts: When both of the following conditions are met: 1) Pwav(i) > Ath; 2) k(i) > kmax, it indicates that the starting point Ts of the potential wave peak is found;

[0111] (c2) When the starting point of the potential wave peak waveform segment is found and Pwav(i) < Ath, it indicates that the ending point Te of the potential peak waveform segment is found;

[0112] (c3) The wave peak can be found from the Ts - Te waveform segment, which is max(Pwav(Ts, Te)), the amplitude is denoted as Pp(j), and the time is denoted as Pt(j);

[0113] (c4) The j-th feature obtained is composed of (Pt(j), Pp(j)).

[0114] (5) If the conduction time RPT of the photoelectric pulse wave in the arterial blood vessel is less than the set threshold and / or the main wave width tu of the photoelectric pulse wave is greater than the set threshold, then the degree of arteriosclerosis is abnormal.

[0115] Example 2

[0116] Example 2 is the same as Example 1, except that: a method for detecting the degree of arterial vascular sclerosis based on a photoelectric sensor further includes the steps of: finding eight photoelectric pulse waves before and after the peak of the diamond waveform segment in the electrocardiogram and photoelectric pulse interconnection waveform, and analyzing and calculating the RPT of the eight photoelectric 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 degree of arterial sclerosis is determined based on the RPT average value, average pulse rate PR and average heart rate HR of eight photoelectric pulse waves.

[0117] Example 3

[0118] like Figure 1 and Figure 6 As shown, the present invention is an arterial vascular sclerosis degree detection system based on a photoelectric sensor, comprising an electrocardiogram amplifier, a photoelectric amplifier, an A / D sampling module, an optimal waveform acquisition module, a pulse wave conduction calculation module and a pulse wave width calculation module.

[0119] like Figure 7 As shown, the ECG amplifier is used to collect the ECG simulation waveform of lead I or II to obtain the ECG simulation signal; wherein the ECG amplifier is used to connect the limb lead electrode to collect the ECG simulation waveform of lead I or II to obtain the ECG simulation signal.

[0120] like Figure 3 As shown, the photoelectric amplifier is provided with a photoelectric sensor, and the photoelectric amplifier is connected to an inflatable cuff which is closely attached to the corresponding arterial blood vessel position on the skin surface to inflate and pressurize the photoelectric sensor, and deflate and decompress it to adaptively select a suitable pressure to obtain a photoelectric pulse wave simulation signal which is synchronously collected with the ECG simulation signal; the photoelectric pulse wave simulation signal contains an optimal pulse blood pressure waveform group in a diamond shape; the optimal 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.

[0121] The A / D sampling module is used to synchronously receive the ECG analog signal and the photoelectric pulse wave analog signal and condition and output the ECG and photoelectric pulse interconnected waveform digital signal; that is, to synchronously convert the sampling signal into a data signal. Figure 2 As shown in the figure, 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 when 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.

[0122] The best waveform acquisition module is used to obtain the best waveform signals of ECG and photoelectric pulse interconnection from the ECG and photoelectric pulse interconnection waveform signals; the specific steps of obtaining the best waveform signals of ECG and photoelectric pulse interconnection are as follows:

[0123] Calculate the peak value Pp(i) of the i-th pulse wave and the valley value Py(i) of the pulse wave;

[0124] 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);

[0125] 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);

[0126] 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;

[0127] 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 valley 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 decrease of the peak 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;

[0128] Calculate the maximum peak Pp_max and the minimum trough Py_min of the pulse wave; when the screening and judgment conditions are met, it is considered that the best waveform of electrocardiogram-pulse interconnection is obtained, otherwise it is considered that there is no best waveform of electrocardiogram-pulse interconnection with obvious features; the screening and judgment conditions are: a) The amplitude MPp_v_end at the end of the diamond peak climb > k1 × Pp_max; b) The amplitude MPy_v_end at the end of the diamond trough descent < k2 × Py_min; c) k1 and k2 are set thresholds, and 0.5 < k1 < 1 and 0.5 < k2 < 1;

[0129] Through the above screening, the following situations occur: If there is no potential diamond wave, it indicates that no best interconnection waveform is found; when only one potential diamond pulse wave is found, this potential diamond pulse wave is the best interconnection waveform; when multiple potential diamond pulse waves are obtained, the ones that simultaneously meet the following conditions are the best interconnection waveforms: The maximum potential diamond time span: MPend_t - MPstart_t, the maximum potential diamond peak-to-peak span: Pp_max - Py_min.

[0130] The pulse wave conduction calculation module is used to calculate the conduction time RPT of the pulse wave of the best electrocardiogram-photoelectric pulse interconnection waveform signal in the arterial blood vessel according to the best electrocardiogram-photoelectric pulse interconnection waveform signal; the pulse wave conduction calculation module first uses the slope method to identify and calculate the peak feature points (Rt(j), Rp(j)) of the electrocardiogram waveform, uses the slope method to identify and calculate the peak feature points (Pt(j), Pp(j)) of the pulse wave, and then calculates the conduction time RPT of the pulse wave of the best electrocardiogram-pulse interconnection waveform signal in the arterial blood vessel. The calculation formula of RPT is: RPT = Pt(j) - Rt(j).

[0131] Specifically calculating the peak feature points of the electrocardiogram waveform is as follows:

[0132] Let the waveform to be analyzed be Rwav, and the i-th data be Rwav(i); calculate the slope k(i) = Rwav(i) - Rwav(i - 1);

[0133] Initialization stage: In the first two seconds of Rwav, calculate: The slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)) and 0.375 < n1 < 1; The amplitude threshold Ath = n2 × Amax, where Amax = max(Rwav(0, 2s)) and 0.375 < n2 < 1;

[0134] Measurement stage: Find the starting point Ts and the ending point Te of the potential peak waveform segment;

[0135] Determine the value of Ts: When both of the following are satisfied: 1) Rwav(i) > Ath; 2) k(i) > kmax, it indicates that the starting point Ts of the potential wave peak is found;

[0136] 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;

[0137] The peak can be found from the waveform segment Ts - Te, that is, max(Rwav(Ts, Te)), the amplitude is denoted as Rp(j), and the time is denoted as Rt(j);

[0138] The j-th feature obtained consists of the feature points (Rt(j), Rp(j)).

[0139] Specifically, the calculation of the pulse peak and valley feature points is as follows:

[0140] 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);

[0141] Initialization stage: In the first two seconds of Pwav, it is calculated that: the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)) and 0.375 < n1 < 1; the amplitude threshold Ath = n2 × Amax, where Amax = max(Pwav(0, 2s)) and 0.375 < n2 < 1;

[0142] Measurement stage: Find the starting point Ts and the ending point Te of the potential peak waveform segment;

[0143] Determine the value of Ts: When both of the following conditions are met: 1) Pwav(i) > Ath; 2) k(i) > kmax, it indicates that the starting point Ts of the potential peak is found;

[0144] 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;

[0145] The peak can be found from the waveform segment Ts - Te, that is, max(Pwav(Ts, Te)), the amplitude is denoted as Pp(j), and the time is denoted as Pt(j);

[0146] The j-th feature obtained consists of (Pt(j), Pp(j)).

[0147] It also includes an average parameter calculation module. This average parameter calculation module searches for the eight pulse waves before and after the peak part of the diamond waveform segment in the electrocardiogram and optoelectronic pulse interconnection waveform, and analyzes and calculates the RPT of these eight pulse waves, and takes their average value Correspondingly, the average pulse rate PR and the average heart rate HR of these eight cardiac cycles are obtained,

[0148] The pulse wave width calculation module is used to calculate the photoelectric pulse wave main wave width tu according to the best waveform signal of the electrocardiogram and the photoelectric pulse interconnection, wherein the photoelectric pulse wave main wave width tu is the width when the photoelectric pulse waveform main wave height is half. When the pulse wave conduction time RPT in the arterial blood vessel of the present invention is less than the set threshold, the degree of arterial vascular sclerosis is abnormal, and when the photoelectric pulse wave main wave width tu is greater than the set threshold, the degree of arterial vascular sclerosis is abnormal.

[0149] The present invention uses the ECG and photoelectric pulse interconnected ECG pulse signal analysis system to test a number of people of different ages. Among them, an 80-year-old man (male, 1.65m, 70kg) has an "ECG and photoelectric pulse synchronous interconnected waveform" (RPT 348ms) on his right toe, while a young man also measured an RPT of 447ms on his right toe. Figure 8 As shown in the figure, the “ECG and photoelectric pulse synchronous interconnection waveform” (RPT 312ms) on the finger of an 80-year-old man (male, 1.65m, 70kg) is as follows: Fig. 9 As shown in the figure, a young man (male, 27 years old, 1.70m, 76kg) has a “synchronous interconnected waveform of ECG and photoelectric pulse wave” (RPT 321ms) on his finger. Fig.10 The width tu value of the arterial waveform at the finger tip of an elderly person is as follows: Fig.11 As shown in the figure, the width tu value of the arterial waveform at the finger tip of a young man is as follows: Fig.12 shown.

Claims

1. A method for detecting the degree of arterial vascular sclerosis based on a photoelectric sensor. It is characterized in that The steps include: (1) Collect the I or II lead ECG analog waveform to obtain the ECG analog signal. (2) Synchronously collect photoelectric pulse wave analog signals through photoelectric sensors; (3) Conditioning the synchronously collected ECG analog signal and photoelectric pulse wave analog signal to obtain ECG and photoelectric pulse interconnection waveform signals, and then obtaining the ECG and photoelectric pulse interconnection optimal waveform signals; In step (3), the specific steps of obtaining the best waveform signal of the ECG and photoelectric pulse interconnection are: (3.1) Calculate the peak value Pp(i) and valley value Py(i) of the i-th photoelectric pulse wave; (3.2) The photoelectric pulse wave peak value increment is calculated as the difference between the previous and next photoelectric pulse wave peak values: dPp(i)=Pp(i)-Pp(i-1); the photoelectric pulse wave trough value increment is calculated as the difference between the previous and next photoelectric pulse wave trough values: dPy(i)=Py(i)-Py(i-1); (3.3) Find the starting point MPstart_t of the potential diamond wave; (3.4) Find the end point MPend_t of the potential diamond wave; (3.5) Calculate the maximum peak value Pp_max and the minimum valley value Py_min of the photoelectric pulse wave; when the screening judgment conditions are met, it is considered that the best waveform of the ECG and photoelectric pulse interconnection is obtained, otherwise it is considered that there is no best waveform of the ECG and photoelectric 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, the potential diamond peak-to-peak span is the largest: Pp_max-Py_min; (4) Based on the best waveform signal of ECG and photoelectric pulse interconnection, the slope method is used to identify and calculate the peak characteristic points of the ECG R waveform (Rt(j), Rp(j)), and the slope method is used to identify and calculate the peak characteristic points of the photoelectric pulse wave (Pt(j), Pp(j)), and then the photoelectric pulse wave conduction time RPT = Pt(j) - Rt(j) of the best waveform signal of ECG and photoelectric pulse interconnection in the arterial blood vessel is calculated; at the same time, based on the best waveform signal of ECG and photoelectric pulse interconnection, the main wave width tu of the photoelectric pulse wave is calculated, where the main wave width tu of the photoelectric pulse wave is the width when the main wave height of the photoelectric pulse waveform is half; (5) If the photoelectric pulse wave conduction time RPT in the arterial blood vessel is less than the set threshold and / or the photoelectric pulse wave main wave width tu is greater than the set threshold, the degree of arterial sclerosis is abnormal.

2. A method for detecting the degree of arterial vascular sclerosis based on a photoelectric sensor according to claim 1, Features: The specific steps of finding the starting point MPstart_t of the potential diamond wave in step (3.3) are: (3.3.1)Find the starting point where dPp(i) is continuously positive when it is rising continuously, which is the starting point MPp_t_start of the diamond peak climb. When dPp(i) changes from positive to negative, it is the ending point MPp_t_end of the diamond peak climb; (3.3.2)Find the starting point where dPy(i) is continuously negative when it is falling continuously, which is the starting point MPy_t_start of the diamond valley decline. When dPy(i) changes from negative to positive, it is the ending point MPy_t_end of the diamond valley decline; (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, it is determined that the current photoelectric pulse wave is not a diamond wave.

3. A method for detecting the degree of arteriosclerosis based on a photoelectric sensor according to claim 2, characterized in that: The specific steps for finding the ending point MPend_t of the potential diamond wave in the step (3.4) are as follows: (3.4.1)MPp_t_end found in step (3.3.1) is the starting point of the diamond wave peak decline. Starting from this, find where dPp(i) is continuously negative until dPp(i) is positive or zero, which is the ending point MPp_t_over of the diamond wave peak decline; (3.4.2)MPy_t_end found in step (3.3.2) is the starting point of the diamond wave valley rise. Starting from this, find where dPy(i) is continuously positive until dPy(i) is negative or zero, which is the ending point MPy_t_over of the diamond wave peak decline; (3.4.3)When |MPp_t_over - MPy_t_over| < 2 heart rate cycles, determine that the ending 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, it is determined that the current photoelectric pulse wave is not a diamond wave.

4. A method for detecting the degree of arteriosclerosis based on a photoelectric sensor according to claim 3, characterized in that: The screening and judgment conditions in the step (3.5) are as follows: a) The amplitude MPp_v_end of the diamond peak climb ending point > k1 × Pp_max; b) The amplitude MPy_v_end of the diamond valley decline ending point < k2 × Py_min; c) k1 and k2 are set thresholds, and 0.5 < k1 < 1 and 0.5 < k2 < 1.

5. A method for detecting the degree of arteriosclerosis based on a photoelectric sensor according to claim 4, characterized in that: The specific steps for calculating the peak feature points of the electrocardiogram waveform in the step (4) are as follows: (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: In the first two seconds of Rwav, it is calculated that: the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)) and 0.375 < n1 < 1; The amplitude threshold Ath = n2 × Amax, where Amax = max(Rwav(0, 2s)) and 0.375 < n2 < 1; (C) Measurement stage: Find the starting point Ts and the ending point Te of the potential peak waveform segment; (C1) Determine the value of Ts: When both of the following conditions are met: 1) Rwav(i) > Ath; 2) k(i) > kmax, it indicates that the starting point Ts of the potential wave peak is found; (C2) When the starting point of the potential peak waveform segment is found and Rwav(i) < Ath, it indicates that the ending point Te of the potential peak waveform segment is found; (C3) The wave peak can be found from the Ts - Te waveform segment, which is max(Rwav(Ts, Te)), the amplitude is denoted as Rp(j), and the time is denoted as Rt(j); (C4) The j-th feature obtained consists of the feature points (Rt(j), Rp(j)).

6. A method for detecting the degree of arteriosclerosis based on a photoelectric sensor according to claim 4, characterized in that: The specific steps for calculating the photoelectric pulse wave peak feature points in the step (4) are as follows: (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: In the first two seconds of Pwav, it is calculated that: the slope threshold Kth = n1 × kmax, where kmax = max(k(0, 2s)) and 0.375 < n1 < 1; The amplitude threshold Ath = n2 × Amax, where Amax = max(Pwav(0, 2s)) and 0.375 < n2 < 1; (c) Measurement stage: Find the starting point Ts and the ending point Te of the potential peak waveform segment; (c1) Determine the value of Ts: When both of the following conditions are met: 1) Pwav(i) > Ath; 2) k(i) > kmax, it indicates that the starting point Ts of the potential wave peak is found; (c2) When the starting point of the potential peak waveform segment is found and Pwav(i) < Ath, it indicates that the ending point Te of the potential peak waveform segment is found; (c3) The wave peak can be found from the Ts - Te waveform segment, which is max(Pwav(Ts, Te)), the amplitude is denoted as Pp(j), and the time is denoted as Pt(j); (c4) The j-th feature obtained consists of two points (Pt(j), Pp(j)).

7. A method for detecting the degree of arteriosclerosis based on a photoelectric sensor according to claim 1, characterized in that: The method also includes the steps of: finding eight photoelectric pulse waves before and after the peak of the diamond waveform segment in the electrocardiogram and photoelectric pulse interconnection waveform, analyzing and calculating the RPT of the eight photoelectric pulse waves, and taking the average value thereof; ; The corresponding average pulse rate PR and average heart rate HR of eight cardiac cycles are obtained. , The degree of arteriosclerosis is determined based on the RPT average value, average pulse rate PR and average heart rate HR of eight photoelectric pulse waves.

8. A system for detecting the degree of arteriosclerosis based on a photoelectric sensor, characterized in that: It includes an electrocardiogram amplifier, a photoelectric amplifier, an A / D sampling module, an optimal waveform acquisition module, a pulse wave conduction calculation module, and a pulse wave width calculation module, The electrocardiogram amplifier is used to connect the limb lead electrode patches to collect the I or II lead ECG analog waveform and obtain the electrocardiogram analog signal; The photoelectric amplifier is equipped with a photoelectric sensor, and the photoelectric amplifier is connected to an inflatable cuff that is closely attached to the corresponding arterial blood vessel position on the skin surface to inflate and pressurize the photoelectric sensor, and deflate and decompress it to adaptively select the appropriate pressure to obtain a photoelectric pulse wave simulation signal that is synchronously collected with the ECG simulation signal; A / D sampling module, used for synchronously receiving ECG analog signal and photoelectric pulse wave analog signal and conditioning and outputting ECG and photoelectric pulse interconnected waveform digital signal; The best waveform acquisition module is used to obtain the best waveform signals of ECG and photoelectric pulse interconnection from the ECG and photoelectric pulse interconnection waveform signals; the specific steps of obtaining the best waveform signals of ECG and photoelectric pulse interconnection are as follows: Calculate the peak value Pp(i) of the i-th photoelectric pulse wave and the valley value Py(i) of the photoelectric pulse wave; The photoelectric pulse wave peak increment is calculated as the difference between the previous and next photoelectric pulse wave peaks: dPp(i)=Pp(i)-Pp(i-1); The increment of the photoelectric pulse wave valley value is calculated as the difference between the previous and next photoelectric pulse wave valley values: dPy(i)=Py(i)-Py(i-1); Find the starting point MPstart_t of the potential diamond wave; Find the end point MPend_t of the potential diamond wave; Calculate the maximum peak value Pp_max and the minimum valley value Py_min of the photoelectric pulse wave; when the screening judgment conditions are met, it is considered that the best waveform of the ECG and photoelectric pulse interconnection is obtained, otherwise it is considered that there is no best waveform of the ECG and photoelectric pulse interconnection with obvious characteristics; Through 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 best interconnected waveform is the one that meets the following conditions at the same time: 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; The pulse wave conduction calculation module is used to calculate the pulse wave conduction time RPT of the best waveform signal of the ECG and photoelectric pulse interconnection in the arterial blood vessel according to the best waveform signal of the ECG and photoelectric pulse interconnection; The pulse wave width calculation module is used to calculate the main wave width tu of the photoelectric pulse wave according to the best waveform signal of the electrocardiogram and photoelectric pulse interconnection, wherein the main wave width tu of the photoelectric pulse wave is the width at half the height of the main wave of the photoelectric pulse waveform.

9. The arterial vascular sclerosis degree detection system based on photoelectric sensor according to claim 8, Features: When the pulse wave conduction time RPT in the arterial blood vessel is less than a set threshold, the degree of arterial vascular sclerosis is abnormal; when the main wave width tu of the photoelectric pulse wave is greater than a set threshold, the degree of arterial vascular sclerosis is abnormal.

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