TWM542444U - Wearable pulse contour analysis device with multiple diagnositic functions - Google Patents

Abstract

A multiple function wearable device can analyze arterial pulse contour and can perform diagnosis. The essential component is an "arterial scan module" which contains LED as light source, photo diode as detector, and a MCU. With the innovated data procession algorithm and hardware design, more than 27 invaluable physiologic indexes can be extracted from enhanced high resolution PPG signals collected by this device. Based on these results, further diagnosis about arterial stiffness, constriction power of ventricles, remaining blood volume, overall cardiovascular health, arteriosclerosis progress, SpO2, mental stress, autonomic nervous system activity measurements, and many more medical grade heart rate variability indexes. Blood pressure, respiration rate, and pulse frequency analysis can also be measured simultaneously. Even better, the same innovated device can measure the heart rates for both of pregnant woman and her fetus. The arterial scan module can be implemented into various products such as watch, bracelet, senior care devices, and smart clothing. This invention enables users to obtain all of these health related indexes whenever they need and to receive notifications from any detected abnormal sign automatically.

Description

Wearable multifunctional pulse wave diagnosis and analysis device

This author is about a multi-functional intelligent pulse wave diagnostic device, especially a multi-functional intelligent pulse wave diagnostic device that is convenient to use.

Although there are many wearable devices that can measure heartbeats on the market, portable devices that can measure and analyze health information contained in deeper or more pulse waves are rare. All only provide heartbeat, blood pressure, sleep detection, GPS path navigation, steps, calories and other functions. The blood pressure value of the non-inflatable pulse pressure belt is often very different. These technical functions are not enough for personal cardiovascular health management or physical and mental stress analysis.

At present, personal or home cardiovascular related testing instruments are limited to sphygmomanometers, oximeters and simple heartbeats; however, these instruments cannot achieve the detection of vascular aging, obstruction and cardiac function. Modern people are under great pressure to work, often in sudden deaths in young and middle-aged. At present, the device for measuring personal and physical stress can be used to measure HRV by using the electrocardiogram (ECG) principle; the chest strap must be tied, or the finger can be placed on the ECG sensor for measurement, and automatic long-term monitoring cannot be performed. As a result, the user forgets to take measurements when he is busy, so that it is impossible to monitor and alert the user at any time. Some use the light volume method (PPG), which can be used with a watch or a finger sensor or a camera directly with a mobile phone. To make HRV measurements, in addition to the watch can be measured at any time, the other methods are still like the shortcomings of ECG. In addition, HRV is currently used to display physical and mental stress, and often only simple HRV measurement results are obtained without providing complete and correct HRV measurement results and interpretation, and it is impossible to provide over-the-counter warning function. In addition, the current arteriosclerosis examinations almost all have to go to the hospital for X-ray angiography, ultrasound, or arteriosclerosis detectors to detect. There is no home-based or personal portable type of vascular sclerosis detection device.

In view of this, how to eliminate the above-mentioned deficiencies is the technical difficulty point that the creators of this case want to solve; this creation aims at cardiovascular health care and is committed to developing innovative arterial scanning technology with medical-grade specifications. (Free chest straps, finger-free touch) to measure arteriosclerosis index, heart rate, blood flow rate and pulse wave rebound speed, respiratory rate, post-exercise heart rate recovery, heart rate variability (living psychological stress and physical exertion index). In order to prevent overwork and death, prevent cardiovascular disease, prevent dementia, depression, ridicule; master breathing and heart rate, stress and physical strength, help everyone stay away from the fear of overwork, get early warning of danger, seek medical treatment as soon as possible; fight for gold rescue Time, to avoid excessive use of physical health and not knowing. We hope that this smart health watch needs to have a dangerous warning function in addition to cardiovascular health monitoring.

In addition to other important functions unique to this creation, including pulse wave spectrum analysis (which can be used to analyze heart rate, heart valve opening and closing, and vibrational noise caused by blood flow in coronary arteries); pulse wave waveform analysis and diagnosis ( The pulse wave type can be output for the pulse diagnosis of the doctor, or the pulse wave type for several important diseases can be automatically identified and interpreted by the automatic pattern recognition method; the fetal heartbeat of the pregnant woman can be monitored at the same time; also the heart rate variability ( HRV) measurement, respiratory rate detection; can also be used to monitor the heartbeat of infants and toddlers Breathing; more importantly, there is also a blood pressure measurement function that allows continuous blood pressure measurement to be obtained without the need for a pressurized inflation belt.

In view of the above disadvantages, the present invention provides a multifunctional wearable pulse wave analysis device, comprising: a casing and a main circuit board for receiving and analyzing data, having a display unit and an input unit, or the same The unit has both display and input functions to provide an interface for operation and reading with the user, such as a TFT LCD touch screen. An optical sensing device for sensing a cardiovascular related diagnostic value, connecting the main circuit board by wire or wirelessly; and uploading the collected data of the wearable device to a mobile phone or a tablet computer by wire or wirelessly Or directly to the network cloud storage analysis device.

The other is that the housing does not have the above-mentioned user operation interface, and the wireless transmission mode is adopted, and the data collected by the wearable device is directly transmitted to the mobile phone; the mobile phone is used as the user control interface. The results measured by the authoring device can be uploaded to a computer or various cloud devices by means of a mobile phone.

Preferably, the optical sensing device comprises a light-emitting component and a light-receiving component for reading the pulse wave signal in a reflective manner (or in a penetrating manner). It is harmless to the human body, and it is not necessary to tie the chest strap, and it is not necessary to hold or clamp the finger to measure. Just input the height, age and weight of the individual and easily wear it on the wrist to do the above various measurements. The light-emitting component is an LED, and its wavelength can be green light (525 nm), red light (640 nm), near-infrared light (840 nm, 940 nm), and the light-receiving component is a photo diode of a corresponding spectral range. This creation uses this optical sensing device to detect 27 types simultaneously or in different combinations. The physiological signal on the upper: and the entire measurement time can be completed in about 1 to 3 minutes (the length of time depends on the number of detection items).

Because the optical sensing device takes signals in a reflective manner, the shape of the housing can be a ring type, a watch type as shown in FIG. 2, a wristband, and other possible handheld devices. The outer casing may even be in the form of a module that is attached to any hand-held device by means of an adhesive or screwing, such as a steering wheel, a cane, etc. as shown in FIG. Other features and embodiments of the present invention can be further understood from the following detailed description in conjunction with the accompanying drawings.

1‧‧‧Touch display

2‧‧‧ watch button

4‧‧‧Optical window

21‧‧‧ pulse wave main wave

22‧‧‧ pulse wave rebound wave

23‧‧‧Time difference between main wave 21 and rebound wave 22

25‧‧‧ pulse wave crest

26‧‧‧ pulse wave crest

28 ‧ ‧ time difference between peaks

30‧‧‧Arterial Scanning Module

31‧‧‧Microprocessor

32‧‧‧Grounded metal protection box

33‧‧‧Light sensor

34‧‧‧LED

36‧‧‧LED light rays that illuminate blood vessels

37‧‧‧Light reflected from the skin and blood vessels

38‧‧‧ shading materials

39‧‧‧Touch Screen Module

40‧‧‧Wireless Transmission Module

41‧‧‧Connecting line

The first picture is the structure diagram of the pulse wave automatic monitoring analysis and diagnosis device.

The second picture is the appearance of the artificial artery scanning wisdom watch (Aegis Heart Table).

The third picture is the array optical sensor module of the creation

Figure 4 is the pulse wave pattern read by the authoring device.

Figure 5 is a flow chart of the pulse wave signal processing program.

Fig. 6(a) shows the pulse wave pattern read by the authoring device; (b) is the first-order pulse wave type derivative map; and (c) is the second-order pulse wave type derivative map.

Figure 7 is a pulse waveform analysis diagram of the creation.

Figure 8 (a) is the actual measured value of the retraction pressure of the authoring device compared with the measured value of the reference blood pressure machine; Figure (b) is the comparison between the actual measured value of the diastolic pressure of the authoring device and the measured value of the reference blood pressure machine; The actual measured value of the heartbeat of the authoring device is compared with the measured value of the reference blood pressure machine.

Figure 9 is a flow chart of the signal processing procedure for simultaneous monitoring of fetal heartbeat in pregnant women.

Figure 10 is the application of the original Figure 2 (a) arterial scanning module or its working principle, can be assembled Different product types.

The following is further described in the specific embodiment:

As shown in Fig. 2, the schematic diagram of the multi-function pulse wave analysis device is a watch type, as shown in Fig. 2(a), after the user inputs the height, age and weight by using the touch screen 1 or the mobile phone, The signal is taken near the back of the hand through the optical window 4 by the arterial scanning module 30 (behind the back cover). As shown in FIG. 1, the arterial scanning module 30 includes a photo sensor 33 (which may be a photodiode); an LED 34 having a wavelength of visible light or infrared light, and a cover metal grounding protection box 32. There are other electronic components on the back of the module, such as the microprocessor 31 to complete the entire function. Thus, the LED light can penetrate into the subcutaneous blood vessels, especially the near-infrared light can penetrate more than 5, 6 mm; as shown in Fig. 1, the green LED illuminates the blood vessel 36, and the photo sensor 33 receives the light 37 reflected from the skin and blood vessels. The center of the reflective photo sensor 33 and the LED 34 of the present invention is about 6.5 mm apart. In order to reduce the scattering interference of light, the surrounding area is blocked by a light-shielding material 38, such as a black light absorbing material. A ground conductor, such as a ferrous metal protection box 32, is placed over the sensor to further reduce other interference to increase the signal to noise (S/N) ratio. The grounded metal protection box 32 can be placed close to the photo sensor 33 or placed at a few meters above the photo sensor 33.

In addition to the addition of the light-shielding material and the grounding conductor piece as described above, the present invention has an array type optical sensor, for example, FIG. 3 has four photo sensors 33, and an LED 34 is in the middle. The basic principle of operation is to increase S/N by multiple synchronization signals. One party adds signals, and on the other hand, it eliminates the common noise.

The amount of light 37 read back from the blood vessel is subject to changes in blood flow pulsations. That is, the amount of blood per unit area of the blood vessel changes with the pulsation of the heart, and the light sensing element converts the intensity of the reflected light that changes with the amount of blood into an induced voltage that changes with the synchronous change, that is, the light volume change signal (Photo plethysmography, PPG). The period in which the most light is absorbed is just the period of contraction of the heart, thus producing the pulse wave pattern as shown in FIG. As shown in the pulse wave mode of Fig. 4, the main wave 21 is a pulse wave sent from the heart (left ventricle), and the formation of the bounce wave 22 has two main causes, one is the rebound of the blood vessel wall, and the other is the aortic The big turns are caused by small branches.

After the user obtains the pulse wave raw data 70 of the user by the optical module, as shown in FIG. 5, after the filtering 71 processing, if the fast Fourier (FFT) 72 operation is performed, the pulse wave spectrum analysis 73 can be obtained. The heart rate 74 can be obtained from the filtered waveform, and the first vascular sclerosis index 1 (NSI) 78 and the second vascular sclerosis index 2: pulse wave conduction velocity can be obtained from the first-order differential 77 wave pattern of the heart rate. (PWV) 79. By further subdividing the differential result 77, the second-order differential waveform 80 of the pulse wave can be obtained. Thus, the "accelerated volumetric pulse wave (APG)" 81 can be obtained, and the following several cardiovascular-related physiological parameters can be obtained from APG. 83: Third vascular sclerosis index 3: vascular elasticity AE, vascular aging degree DPI, ventricle After the systolic function EC and the systolic blood supply, the residual blood volume RBV in the blood vessel and the seven types of blood vessels may be blocked.

The blood pressure value of 76 can be obtained from the filtered waveform, and the fourth vascular sclerosis index 4 (82) can be obtained from the difference of the blood pressure values.

After collecting the heart rate change data for more than 1 minute, 75, the heart rate variability (HRV) of the time domain and the frequency domain can be analyzed 84. At least 9 physiological parameters 85 can be obtained from HRV, including respiratory number, AVNN, SDNN, RMSSD, PNN50, total power, VLF power, HF power, LF/HF, etc.

This creation can also be packaged into an infant foot ring or bracelet cardiovascular health monitor to monitor cardiovascular health and respiratory counts in infants and young children. It can be used to prevent sudden death in children.

The above items are detailed as follows:

The center hop count is calculated from the time between the two peaks as shown in Fig. 4, 25, 26. The arteriosclerosis index SI (meters per second) is defined in the prior art as SI = height / T23 (1)

T23 is defined as shown in Fig. 423 and the time difference between the main wave 21 and the bounce wave 22. The author compares the clinical measured values of the medical device with the medical grade SA3000P, as shown in the following table: Comparison of the clinical measured values of the two instruments: It can be confirmed that the arteriosclerosis and vascular elasticity values of the present device are highly correlated with the vascular elasticity value of SA3000P. But this creation found that this definition needs to be corrected as follows:

First, T23 is distorted by the speed of the heartbeat, that is, when the heartbeat is accelerated, the degree of hardening of the blood vessel is overestimated, so this creation adds a heartbeat compensation function, which can be from the same person in the same PWV or ABI. The measurement of arteriosclerosis, but different heartbeats; the other thing that needs to be corrected is the simple height as the rebound wave conduction distance. The calculation of the deviation is likely to cause deviations in the measurement results, such as the elasticity of the microvessels of two people (the meaning of the SI measurement), but if the calculation is based on the formula (1), the SI value will be higher when the height is higher. A correction function can be obtained from the SI values of people with the same ABI value (also measured for microvascular hardening) but different heights. A compensation function C(q) obtained by the deviation caused by the heartbeat and the height. The hardening index of this creation is corrected to SIN=h/T23 x C(q) (2)

From the labeled points (a to e) in the second-order derivative of the waveform of Fig. 6(c), a number of important cardiovascular parameters can be obtained as follows: (1). The fourth vascular sclerosis index can be obtained from the value c/a. (AE). The smaller the value, the higher the degree of hardening of the blood vessel. (2). The ventricular contraction function (EC) index can be obtained from the value b/a. The larger the value, the worse the ventricular systolic function. (3). From the value d / a can be obtained after the systolic blood transfusion, intravascular residual blood (RBV) indicators, the smaller the measurement, the worse the representative. (4). The fifth type of arteriosclerosis index is obtained from the value e/a. The smaller the value, the higher the degree of hardening of the blood vessel. (5). The blood vessel aging degree (DPI) index can be obtained from the value (b-c-d-e)/a. The larger the measured value, the worse. (6). The "vessel age" value is obtained from the value 45.5*(b-c-d-e)/a +65.9. If the blood vessel age is greater than the current actual age value, then of course it is not good. (7). The value line formed by the two points of bd is as shown in Fig. 6(c), and the slope of the bd line can be used as a reference index for the vascular occlusion situation. When the angle θ is about 45 degrees, it means that the blockage is small and the blood circulation is good; when θ is close to 0 degree, it means that it is not good; and when θ<0 degree, the smaller the θ is, the worse the cycle is.

More preferably, this creation calibrates the algorithm for each "turning point" in Figure 6. This algorithm compares the relative relationships between feature points, such as relative size, position, angle, time sequence, physiological meaning between feature points, and the subject itself. Various physiological conditions, etc., we make different classification conditions to filter the measured values, so that we can accurately find various feature points in the waveform. One of the features of this authoring algorithm is that the program is simple, especially suitable for use on microprocessors, and can be applied to different wearable products.

By performing the FFT spectrum analysis on the signal after the noise is removed from the creation, the pulse signal of the pulse wave in FIG. 4 can be converted into a signal on the frequency. Figure 7 shows the spectrum analysis in Figure 4. The right axis is the intensity after FFT conversion and the horizontal axis is frequency. There are several major waves in Figure 7 (for example, 51, 52, 53: This is the measured result of the creation of the watch product). If there are some large amplitude or irregular noise waves beside these main amplitudes, it is very likely to reflect Some problems exist in the user's cardiovascular system. It can be used to analyze the heartbeat frequency, the opening and closing of the heart valve and the vibration noise of the coronary artery due to blood flow. It is also possible to determine whether there is a disease in the coronary artery.

What's more, this creation can avoid the pressure and discomfort caused by the general air bag type spectrum sphygmomanometer; it can also avoid the cumbersome and inconvenient portability of the sphygmomanometer. With the creation of the analysis device, the user can easily measure the pulse wave spectrum analysis at any time within a limited range of hand movements.

Even better, this creation uses the relationship between blood pressure and the amount of blood vessel deformation to measure blood pressure. The blood vessel is an elastic tube body that is deformed by the impact of blood injected by the heart. It is straightforward to think that the higher the blood pressure, the greater the relative deformation of the blood vessels, as shown in Figure 6(a). Of course, the amount of deformation of the blood vessel after compression is also closely related to the age and vascular characteristics of the subject. This creation uses a medical-grade sphygmomanometer as a reference standard machine, and uses this creative wisdom table to measure the waveform data of Figure 6(a) for different subjects, and then refer to it immediately. The standard blood pressure value (Pref) measured by the blood pressure machine. From the relative pulse wave, the deformation amount A and the blood vessel characteristic value B of the subject are analyzed, and then from the following formula (3), the coefficients C0, C1 and the blood vessel deformation function f (A, composed of A, B) are obtained. B). The vascular deformation function f(A, B) is first assumed to be substituted into the equation (3) by the linear function of A and B. This application uses multiple regression algorithms to change the form of the function, and adjusts the coefficients C0 and C1 to find the most suitable. The function type and coefficient combination. In this way, the blood pressure value can be obtained by applying the formula (3) without having to use a barometric pressure sphygmomanometer.

Pref=C0+C1*f(A,B) (3) The comparison between the blood pressure value actually measured by the original product and the standard blood pressure value measured by the reference blood pressure machine, as shown in Fig. 8(a), the reduction pressure, Fig. 8 ( b) Comparison of diastolic blood pressure. Among them, Figure 8 (c) compares the heartbeat value, the correlation coefficient is as high as 0.985, which means that the accuracy of the heartbeat in this creation can replace the reference machine.

Since this creation can continuously measure pulse waves, the same device can also measure heart rate variability (HRV). HRV is a slight difference between each heartbeat cycle, a natural phenomenon of the body, not arrhythmia. This creation can measure within 15 minutes or longer, such as 24 hours of HRV. At least 8 effective physiological data can be obtained by HRV of 2 to 3 minutes, as shown in Fig. 4: for example, from the original pulse wave data 70 to the collection of each heart rate for 3 consecutive minutes. Then the average heartbeat interval period (AVNN) of these heart rates is obtained, and the standard deviation of each heart rate period relative to the average is calculated to obtain the SDNN; the square of the difference between each adjacent two heartbeat periods is calculated, and then the difference is obtained. The mean square root (rMSSD); it can also be obtained by dividing the sum of the number of occurrences of the adjacent heartbeat cycle time difference greater than 50msec by the total number of heartbeats, which is a percentage, which is (PNN50), and above is the time domain of HRV Analysis Department Share. If the heartbeat period and its corresponding time are subjected to a Fourier transform (FFT), and then the power spectral density (PSD) is obtained from the FFT result, various frequency domain analysis results of the HRV can be obtained. For example, TOTPWR can be obtained from the power spectral density (PSD) to the total power within 0.04 Hz; the total power in the ultra-low frequency range (0.003 to 0.04 Hz) is calculated from the power spectral density (PSD) as VLF; The total power in the low frequency range (0.04 to 0.15 Hz) is calculated as LF in the distribution (PSD); the total power in the high frequency range (0.15 to 0.4 Hz) is calculated from the spectral power distribution (PSD) as HF; Another useful indicator is also available for the ratio of HF; various related physiological health conditions can be seen from the indicators obtained from these HRVs. For example, if the SDNN<50msec is compared with the average healthy person (SDNN is around 130msec), the chance of death due to heart disease will increase by 5.3 times; for example, the average LF/HF of patients with coronary heart disease is 3.0 (than the average healthy person) It is much higher than 2.5). These values also reflect the balance between the individual's sympathetic and parasympathetic nerves. This can show life stress and physical exertion index, psychological state measurement (emotional fluctuations, stress, excitement, sadness, depression, anxiety, etc.). The frequency of breathing can also be obtained from the frequency domain analysis of the HRV.

Another important parameter in the diagnosis of arteriosclerosis is the pulse wave velocity (PWV). The pulse wave caused by the contraction of the heart is transmitted to the various parts of the body through the artery, and the time difference of the pulse wave conduction can be synchronously measured by the non-invasive optical sensor. The pulse wave conduction rate is the ratio of the conduction distance to the time difference. PWV is directly related to the degree of arteriosclerosis in the measurement area. Generally, the harder the arterial blood vessels, the worse the elasticity, and the faster the PWV. By substituting PTT in the first derivative of Fig. 6b as the pulse wave conduction velocity into equation (4), PWV is obtained, where B is body correction factor=0.5 (for adults), PWV=B* height/PTT (4)

Another invention of the present invention is the simultaneous monitoring of fetal heartbeat in pregnant women. The basic principle is shown in Fig. 9. For example, the pulse wave 101 of the mother and the fetus is first obtained by the creation of the smart watch, and the noise 110 is removed by filtering, and then passed through the FFT 120. The large difference in the number of heartbeats between the pregnant woman and the fetus is then applied, and the spectrum analysis of the two heartbeats can be separately derived from the heartbeat spectrum analysis. By the regular characteristics and amplitude of the fetal and mother harmonics (for example, the fetal pulse amplitude is small, and the number of heartbeats is high, etc.). From these characteristics, we find out the mother's heartbeat 121 from the common pulse wave between the fetus and the mother. The principle of application is to use the mother's heartbeat amplitude to separate the mother's heartbeat from the larger amplitude in the spectrum analysis. Then take the mother's heartbeat out of the pulse wave of the parent and child 122. From the principle of linear superposition of pulse wave signals, the pulse wave at this time only has the signal 123 of the fetus, as shown in Fig. 9. Then, the fetal heartbeat can be calculated from the time difference 28 of 21, 26 in Fig. 4.

In addition to the original green light, the blood oxygen concentration can be measured by adding two IR LEDs (wavelengths of about 660 nm and 940 nm) and then calculating the area ratio of the two different wavelength pulse waves.

More preferably, the user can immediately display the individual BMI and body fat number after the user inputs the weight. It also allows the user to set the weight loss target, and after each exercise, estimate the weight loss based on the calories burned by the user and display it instantly.

However, the above descriptions are only preferred embodiments of the present invention. When it is not possible to limit the scope of the creation of the creation, the changes and modifications that can be made by those who are familiar with the industry should be regarded as not deviating. The substance of this creation.

30‧‧‧Arterial Scanning Module

31‧‧‧Microprocessor

32‧‧‧Grounded metal protection box

33‧‧‧Light sensor

34‧‧‧LED

36‧‧‧LED light rays that illuminate blood vessels

37‧‧‧Light reflected from the skin and blood vessels

38‧‧‧ shading materials

39‧‧‧Touch Screen Module

40‧‧‧Wireless Transmission Module

41‧‧‧Connecting line

Claims (14)

A pulse wave automatic monitoring analysis and diagnosis device comprises the following modules: an arterial scanning module for emitting light and receiving light reflected from skin and blood vessels, and analyzing the obtained pulse wave signal; and a wireless transmission mode a group, the bidirectional connection of the arterial scanning module, outputting the operation result to a mobile phone, a flat computer or a computer, and transmitting instructions of the mobile phone, the flat computer or the computer to the arterial scanning module; and a touch screen module, The arterial scanning module and the wireless transmission module are respectively connected to display various messages and allow the user to control the arterial scanning module, the wireless transmission module and the user to input different messages. The pulse wave automatic monitoring analysis and diagnosis device according to claim 1, wherein the arterial scanning module comprises a photo sensor, one to several light emitting diodes (LEDs), and an electronic signal processing unit; The arterial scanning module can be made or assembled in various watches, bracelets, necklaces, earrings, earphones, upper arm ring, foot ring, mobile phone, sphygmomanometer, blood glucose meter, glasses, oximeter, steering wheel, clothes, crutches Different types of products such as accessories, seats and beds. The pulse wave automatic monitoring analysis and diagnosis device according to claim 2, wherein the light sensor comprises a light-emitting component (such as an LED) and a light-receiving component (such as a photo diode); wherein the light-receiving component and the light-receiving component The center of the light-emitting component is about 3 to 10 mm apart, and the stray light is blocked by the light-shielding material around the periphery, and the grounding conductor is used above the sensor or the light-receiving component to further reduce other interference to increase signal noise (S/N )ratio. The pulse wave automatic monitoring analysis and diagnosis device according to claim 1, wherein the artery scanning module can simultaneously or separately analyze the following physiological police monitoring values, including heartbeat, blood pressure, and blood pressure, from the acquired pulse wave signals. Difference, pulse intensity, pulse wave rebound intensity, vascular sclerosis index, pulse wave conduction velocity, vascular aging degree, vascular elasticity, ventricular systolic function, residual blood volume in the blood vessels after systole, possible occlusion of 7 kinds of blood vessels, respiratory number After exercise Heart rate recovery, heart rate recovery after exercise, fetal heart rate, pulse wave spectrum analysis, blood oxygen concentration; and 9 values of heart rate variability, including mean heartbeat interval period, standard deviation of normal heartbeat interval, adjacent The ratio of the number of normal heartbeats over 50 milliseconds, the root mean square of the sum of squared differences between adjacent normal heartbeats, the total power, the power of the very low frequency range, the power of the low frequency range, the power of the high frequency range, and the low and high frequency power ratio. The pulse wave automatic monitoring analysis and diagnosis device according to claim 3, wherein the photo sensor can be expanded into an array type photo sensor, which comprises four light collecting components, and an LED in the middle; This can increase the signal on the one hand, and eliminate the noise that is common to each other. The pulse wave automatic monitoring analysis and diagnosis device according to claim 4, wherein the artery scanning module can analyze a blood vessel hardening index from the obtained pulse wave signal, and includes a heartbeat and a height compensation function C(q). , q is a variable related to the heartbeat or height to correct the error caused by the heartbeat or height; and the corrected blood vessel hardening measurement can be expressed as the right type, SIN=height/T23 x C(q), where SIN The corrected value of the arteriosclerosis is measured, and T23 is the time difference between the main wave of the pulse wave and the rebound wave. The pulse wave automatic monitoring analysis and diagnosis device according to claim 4, wherein the artery scanning module can analyze the blood pressure value from the obtained pulse wave signal, wherein the blood pressure value can be expressed as the right formula Pref=C0 +C1*f(A,B); where Pref is the analyzed blood pressure value, C0, C1 are the coefficients obtained by the regression algorithm, and f(A, B) is the blood vessel characteristic value B and the blood vessel deformation amount A. Vascular deformation function. The pulse wave automatic monitoring analysis and diagnosis device according to claim 4, wherein the artery scanning module can obtain a pulse wave spectrum analysis from the obtained pulse wave signal, thereby eliminating the general air bag type spectrum blood pressure. The pressure and discomfort caused by the meter can also allow the user to measure anytime and anywhere within a limited range of hand movements, and thereby determine whether there is a coronary artery disease. The pulse wave automatic monitoring analysis and diagnosis device according to claim 4, wherein the artery scanning module can perform heart rate variability analysis in the time domain and the frequency domain from the obtained pulse wave signal, and obtain 8 kinds of The heart rate variability measurement allows the user to measure anytime and anywhere within a limited range of hand movements, achieving the measurement results of the previously large and complex, expensive fixed-point diagnostic devices. The pulse wave automatic monitoring analysis and diagnosis device according to claim 4, wherein the artery scanning module can perform second-order differentiation from the acquired pulse wave signal, and use artificial intelligence to identify the second-order differential wave of the pulse wave. The type of blood vessel aging, vascular elasticity, ventricular systolic function, residual blood volume in the blood vessels after contraction of the heart, and the measurement of the possible occlusion of the seven kinds of blood vessels can further allow the user to move within a limited range of hand movements. Measure anytime, anywhere, to achieve the measurement results of the previous large and complex, expensive fixed-point diagnostic device. The pulse wave automatic monitoring analysis and diagnosis device according to claim 4, wherein the artery scanning module can analyze a pulse wave velocity from the obtained pulse wave signal, wherein the pulse wave velocity value can be expressed as Right type PWV = 0.5 * height / PTT; where PWV is the pulse wave conduction velocity, and PTT is the time required for the systolic pressure to reach the apex. The pulse wave automatic monitoring analysis and diagnosis device according to claim 4, wherein the artery scanning module can apply the mother's heartbeat amplitude from the obtained pulse signal of the pregnant woman, which is larger from the spectrum analysis. The mother's heartbeat is separated from the amplitude, and the mother's fetal heart rate is calculated by taking the mother's heartbeat signal from the pulse wave of the parent and child. The pulse wave automatic monitoring analysis and diagnosis device according to claim 2, wherein the artery scanning module can be formed or assembled in various bracelets, upper arm rings, or foot rings, and then a thermometer can be added. As an immediate remote monitoring of infant heartbeat, body temperature and respiratory rate, it is used to prevent sudden death in children. The pulse wave automatic monitoring analysis and diagnosis device according to the fourth aspect of the invention, wherein the artery scanning module obtains a pulse wave signal, and then undergoes filtering processing, and if the fast Fourier operation is entered, the pulse wave spectrum analysis is obtained; From the filtered waveform, the heart rate can be obtained, and then the first-order differential waveform of the pulse wave can be obtained by comparing the relative relationship between the respective peaks and troughs, such as relative size, position, angle, and time sequence. And the physiological significance between the various feature points, the vascular sclerosis index and the pulse wave conduction velocity can be obtained; if the differential result is further differentiated, the second-order differential wave pattern of the pulse wave can be obtained; Thus, the vascular elasticity, the degree of vascular aging, the ventricular systolic function, the residual blood volume in the blood vessels after systolic blood delivery, and the possible clogging of the seven kinds of blood vessels can be obtained; and the waveforms after filtering and differentiation can be obtained. The difference between the blood pressure value and the blood pressure value; after collecting the heart rate change data for more than 1 minute, the heart rate variability in the time domain and the frequency domain can be analyzed, and the heart rate is obtained. Of at least nine different physiological parameters can be obtained.