Pulse diagnosis method, system and device

Abstract

The present invention discloses a pulse diagnosis method, system and device, wherein the pulse diagnosis method is a method for judging pulse condition by processing pulse wave data obtained by an optical sensor and used for calculating practical applications to obtain a pulse wave waveform containing three physical characteristics of time, space and intensity. The present invention obtains pulse condition information that is easy for ordinary people to understand by reprocessing the pulse wave data, thereby facilitating the popularization and use of electronic pulse diagnosis instruments.

Description

Technical Field

[0001] The present invention relates to the field of pulse diagnosis technology, and more particularly to a pulse diagnosis method, system and device. Background Art

[0002] "Look, smell, ask, and palpate" are the basic and important means of diagnosis in traditional Chinese medicine. Traditional Chinese medicine practitioners "palpate" - feel the pulse, apply different intensities of pressure on the fingertips to understand the pulse information transmitted by the radial artery (divided into: floating, sinking, slow, rapid, slippery, astringent, weak, strong, long, short, strong, weak, tight, slow, twisted, stringy, leathery, firm, moist, weak, scattered, thin, moving, rapid, knotted, alternating, and fast pulses), and "ask" - in addition to listening to the patient's main complaint, the following items can be asked: general situation (name, gender, age, date of consultation), the occurrence and development of the disease, current symptoms, and personal medical history. Among them, symptoms are the main content of the questioning and an important basis for syndrome differentiation. The questioning of symptoms mainly includes asking about cold and heat, chest and flank, stomach, waist and abdomen, diet, sleep, and defecation. The pulse of traditional Chinese medicine can be regarded as a combination of the pulse pressure applied by the doctor to the patient, the patient's own radial artery fluctuation information, and the inquiry of the patient and his / her informants about the occurrence of the disease.

[0003] At present, pulse diagnosis instruments used in traditional Chinese medicine are all developed using a one-to-one method using traditional physics and force sensors to collect vibration data and calculate the pulse waveform structure. Not only are the hardware instruments large and complex to operate, but the detection results are also specialized, requiring professional Chinese medicine practitioners to judge the pulse condition based on the pulse strength, and are not suitable for ordinary people to directly understand their personal physical condition. Summary of the invention

[0004] To this end, the technical problem to be solved by the present invention is to provide a pulse diagnosis method, system and device, wherein the pulse diagnosis method is a method for judging the pulse condition by processing the pulse wave waveform containing three physical characteristics of time, space and intensity obtained by processing the pulse wave data obtained by an optical sensor and used to calculate practical applications. By reprocessing the pulse wave data, pulse condition information that is easy for ordinary people to understand is obtained, thereby facilitating the popularization and use of electronic pulse diagnosis instruments.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A pulse diagnosis method comprises the following steps:

[0007] S1) using an optical sensor to obtain pulse wave data for calculating practical applications;

[0008] S2) processing the pulse wave data obtained in step S1) to obtain a pulse wave waveform including three characteristics of time, space and intensity;

[0009] S3) comparing the pulse waveform obtained in step S2) with the pulse waveform of the normal pulse to obtain the pulse waveform corresponding to the pulse waveform diagram obtained in step S2).

[0010] In the above-mentioned pulse diagnosis method, in step S2), when processing the pulse wave data obtained in step S1), a pulse wave waveform including at least one front valley point, one peak point and one back valley point is intercepted, wherein the vertical axis value of the front valley point is the same as the vertical axis value of the back valley point.

[0011] In the above-mentioned pulse diagnosis method, in step S1), when the pulse wave data is collected by using an optical sensor, the data is collected once every 1 millisecond; in step S2), the pulse wave data collected in step S1) is filtered into a pulse wave waveform diagram consisting of a value every 20 milliseconds; in step S2), the pulse wave data collected in step S1) is filtered by a DC filter, a mean filter, a median filter and a Butterworth filter in sequence.

[0012] In the above pulse diagnosis method, in step S2), when processing the pulse wave waveform, the data obtained by filtering by the DC filter, the mean filter, the median filter and the Butterworth filter in sequence are processed as follows:

[0013] S2-1) performing a difference calculation on two adjacent pulse data of the data obtained through filtering to obtain a pulse data difference, and obtaining a pulse wave waveform from the obtained pulse data difference;

[0014] S2-2) obtaining the value of each numerical point in the pulse wave waveform from the pulse data difference obtained in step S2-1), the number of numerical points in the ascending branch of the pulse wave waveform, the number of numerical points in the descending branch of the pulse wave waveform, the number of data points contained in the point-to-point relationship from the front valley point to the middle valley point, the number of numerical points from the middle valley point to the first peak point, the number of numerical points from the first peak point to the middle valley point, the number of numerical points from the middle valley point to the second peak point, the number of numerical points from the second peak point to the back valley point, the average difference of the distance points between the front upper wave, the average difference of the distance points between the front lower wave, the average difference of the distance points between the back lower wave, and the average difference of the distance points between the two peaks and the front upper wave;

[0015] In step S3), the pulse condition of the collected pulse wave waveform is judged based on the data obtained in step S2-2).

[0016] A pulse diagnosis system comprises a data acquisition unit, a storage unit and a microprocessor. The storage unit pre-stores a pulse diagnosis program for realizing pulse diagnosis and can be run on the microprocessor. The microprocessor is respectively connected to the data acquisition unit and the storage unit for communication. When the microprocessor executes the pulse diagnosis program, the steps of the pulse diagnosis method are realized.

[0017] A pulse diagnosis device comprises a computer mainboard, an optical sensor, a data acquisition card, an acceleration sensor, a vibration motor, a Bluetooth chip, a display screen, a battery, a packaging shell and a wrist strap, wherein a storage chip and a microprocessor are arranged on the computer mainboard, the microprocessor is respectively connected to the storage chip, the data acquisition card, the acceleration sensor, the vibration motor, the Bluetooth chip and the display screen in communication, and the data acquisition card is connected to the optical sensor in communication; the microprocessor, the storage chip, the optical sensor, the data acquisition card, the acceleration sensor, the vibration motor, the Bluetooth chip and the display screen are respectively electrically connected to the battery; a pulse diagnosis program for realizing pulse diagnosis and running on the microprocessor is pre-stored in the storage chip, and the steps of the pulse diagnosis method are realized when the microprocessor executes the pulse diagnosis program; the computer mainboard, the optical sensor, the data acquisition card, the acceleration sensor, the vibration motor, the Bluetooth chip and the battery are respectively installed in the packaging shell, the display screen is installed on the outer wall of the packaging shell and the wrist strap is installed on the packaging shell.

[0018] In the pulse diagnosis device, the P0.11 pin of the microprocessor is connected to the LED_EN pin of the LED driver, the LEDK pin of the LED driver is connected to the LEDK pin of the display screen, the SDA pin of the display screen is connected to the P0.18 pin of the microprocessor, the SCL pin of the display screen is connected to the P0.19 pin of the microprocessor, the RS pin of the display screen is connected to the P0.17 pin of the microprocessor, the RES pin of the display screen is connected to the P0.16 pin of the microprocessor, the CS pin of the display screen is connected to the P0.15 pin of the microprocessor, the GND pin and the GND2 pin of the display screen are grounded respectively, the IM1 pin of the display screen is electrically connected to the battery via the resistor R1 and is grounded via the resistor R1 and the capacitor C9, the VCC pin and the LEDA pin of the display screen are electrically connected to the battery respectively and are grounded via the capacitor C9; the GND pin of the LED driver is grounded.

[0019] In the pulse diagnosis device, the P0.24 pin of the microprocessor is connected to the gate of the MOS field effect tube, the source of the MOS field effect tube is electrically connected to the battery, the drain of the MOS field effect tube is connected to the VDD pin of the acceleration sensor, the CSB pin of the acceleration sensor is connected to the P0.30 / AIN6 pin of the microprocessor, the SCX pin of the acceleration sensor is connected to the P0.29 / AIN5 pin of the microprocessor, the SDO pin of the acceleration sensor is connected to the P0.28 / AIN4 pin of the microprocessor, the SDI pin of the acceleration sensor is connected to the P0.27 pin of the microprocessor, the VDDIO pin of the acceleration sensor is connected to the VDD2 pin of the microprocessor, the PS pin, the NC pin, the GND pin and the GND pin of the acceleration sensor are connected to the VDD2 pin of the microprocessor, and the VDDIO pin of the acceleration sensor is connected to the VDD2 pin of the microprocessor. The IO pins are grounded respectively; the VDD pin of the acceleration sensor is grounded via capacitor C38, and the VDDIO pin of the acceleration sensor is grounded via capacitor C39; the source and drain of the MOS field effect tube are connected through resistor R69, and the gate and source of the MOS field effect tube are connected through resistor R19.

[0020] In the pulse diagnosis device, the VI N pin of the voltage stabilizing chip is electrically connected to the battery and is grounded via capacitors C26 and C28, respectively; the EN pin of the voltage stabilizing chip is connected to the P0.13 pin of the microprocessor and the EN pin of the voltage stabilizing chip is grounded via resistor R6; the OUT pin of the voltage stabilizing chip is connected to the 4th pin of the heart rate cable and the OUT pin of the voltage stabilizing chip is grounded via capacitor C30; the NC pin of the voltage stabilizing chip is grounded; the positive electrode of the vibration motor is electrically connected to the battery via resistor R60, the negative electrode of the vibration motor is connected to the P0.31 / AI N7 pin of the microprocessor via a junction field effect transistor, and the source of the junction field effect transistor is grounded; the OUT pin of the touch detection chip is connected to the P0.08 pin of the microprocessor, the SO pin of the touch detection chip is connected to the touch panel via resistor R24, the STG pin of the touch detection chip is grounded, and the VDD pin and SLH pin of the touch detection chip are grounded via capacitors C8 and C21, respectively.

[0021] In the pulse diagnosis device, the battery is a rechargeable battery, and the rechargeable battery is electrically connected to the battery charging management chip.

[0022] The technical solution of the present invention achieves the following beneficial technical effects:

[0023] 1. The radial artery pulse wave (one of the 27 pulses in pulse medicine) has three characteristics in physics, namely time, space and intensity. The present invention first determines the conversion principle of the optical sensor, stipulates the integrated photodiode of the optical sensor, the photodiode and the analog front end (AFE) - these components capture the light refracted by the wearer at a specific distance, and convert these analog signals into digital signals for calculating the pulse wave data (abbreviated as: PPG) that can be applied in practice. In addition to calculating space and intensity, the key algorithm of the test instrument also calculates the pulse routine element data and the pulse autonomous feature data. In the composition functions of the Traditional Chinese Medicine Pulse Diagnosis Instrument and APP, since their test results are relatively primitive, in order to make it easy for users to understand, 27 types of pulse conventional element data are also used. The results of each test are divided into heat, cold, dampness, deficiency, and blood deficiency according to the conventional element types contained in the pulse. The pulse combinations containing multiple conventional element types are two-in-one, three-in-one, and four-in-one. In order to monitor the changes in good and bad pulses, each type of conventional element is divided into four levels. In the integration process of the entire instrument system combination, there are good and clear integration concepts in terms of applicability, stability, practicality, and continuous monitoring, and the corresponding use effect will be affected.

[0024] 2. The present invention extracts pathological types related to human pulse from a database of revised conditions of the system according to conventional single or combined types of pulses in combination with autonomous characteristics of pulses, and displays them on the user side for selection. After submission of the selected pathological type, the present invention extracts pathological selections aligned with the pulse from the revised database of the system to display the symptoms of viscera. According to the symptoms, the influence of food on pathology in the traditional Chinese medicine, medical and dietary therapy and health preservation treasure book is used to plan out the food advisable / taboo schemes and display them on the advisable / taboo page, laying a foundation for TCM pulse diagnosis in the field of artificial intelligence in terms of applicability and practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of the structure of the pulse diagnosis device in the present invention;

[0026] Figure 2 It is a schematic diagram of the connection of the microprocessor circuit in the present invention;

[0027] Figure 3 This is a schematic diagram of the LED driver circuit in the present invention;

[0028] Figure 4 This is a schematic diagram of the display screen circuit connection in the present invention;

[0029] Figure 5 This is a schematic diagram of the connection of the MOS field effect tube circuit in the present invention;

[0030] Figure 6 This is a schematic diagram of the connection of the acceleration sensor circuit in the present invention;

[0031] Figure 7 This is a schematic diagram of the connection of the voltage stabilizing chip circuit in the present invention;

[0032] Figure 8 This is a schematic diagram of the connection of the vibration motor circuit in the present invention;

[0033] Fig. 9 This is a schematic diagram of the circuit connection of the touch detection chip in the present invention;

[0034] Fig.10 This is a schematic diagram of the raw data collected by the optical sensor;

[0035] Fig.11 The pulse wave waveform is obtained after filtering;

[0036] Fig.12 Refer to the pulse waveform data standard of normal pulse;

[0037] Fig.13 It is a positioning diagram for the pulse conditions of urgency, knotting and alternation;

[0038] Fig.14 It is a matching diagram between the respiratory cycle and the pulse cycle;

[0039] Fig.15 Diagnose the page diagram for APP software;

[0040] Fig.16 This is a diagram of how to wear a pulse diagnosis bracelet;

[0041] Fig.17 This is a schematic diagram of the connection between the pulse diagnosis bracelet and the APP software;

[0042] Fig.18 The pulse diagnosis results displayed by the APP for a 36-year-old volunteer - hot / worse, weak / worse;

[0043] Fig.19 This is the pulse waveform (pulse count) obtained from the pulse diagnosis of a 36-year-old volunteer;

[0044] Fig. 20 The pulse diagnosis result displayed by the APP for a 13-year-old volunteer - fever / severe;

[0045] Fig.21 This is the pulse waveform diagram obtained by pulse diagnosis of a 13-year-old volunteer; (Maihong)

[0046] Fig. 22 The pulse diagnosis results displayed by the APP for a 14-year-old volunteer - weak / severe, cold / poor;

[0047] Fig.23 This is a pulse waveform diagram (short pulse) obtained from the pulse diagnosis of a 14-year-old volunteer;

[0048] Fig.24 The pulse diagnosis results displayed by the APP for a 25-year-old volunteer: weak / slightly worse, hot / relatively worse, wet / slightly worse;

[0049] Fig.25 This is the pulse wave waveform (stringy and soft pulse) obtained by pulse diagnosis of a 25-year-old volunteer.

[0050] The reference numerals in the figure are as follows: 1- wrist strap; 2- packaging shell; 3- computer motherboard; 4- battery; 5- data acquisition card; 6- optical sensor. DETAILED DESCRIPTION

[0051] In the present invention, the pulse diagnosis device is a pulse diagnosis wristband, which includes a computer motherboard 3, an optical sensor 6, a data acquisition card 5, an acceleration sensor, a vibration motor, a Bluetooth chip, a display screen, a battery 4, a packaging shell 2 and a wristband 1. Figure 1 As shown, a memory chip and a microprocessor are provided on the computer mainboard 3, and the microprocessor is respectively communicated with the memory chip, the data acquisition card 5, the acceleration sensor, the vibration motor, the Bluetooth chip and the display screen, and the data acquisition card 5 is communicated with the optical sensor 6; the microprocessor, the memory chip, the optical sensor 6, the data acquisition card 5, the acceleration sensor, the vibration motor, the Bluetooth chip and the display screen are respectively electrically connected with the battery 4; a pulse diagnosis program for realizing pulse diagnosis and running on the microprocessor is pre-stored in the memory chip, and the steps of the pulse diagnosis method are realized when the microprocessor executes the pulse diagnosis program; the computer mainboard 3, the optical sensor 6, the data acquisition card 5, the acceleration sensor, the vibration motor, the Bluetooth chip and the battery 4 are respectively installed in the packaging shell 2, the display screen is installed on the outer wall of the packaging shell 2 and the wrist strap 1 is installed on the packaging shell 2.

[0052] Among them, Figures 2 to 9As shown, the P0.11 pin of the microprocessor is connected to the LED_EN pin of the LED driver, the LEDK pin of the LED driver is connected to the LEDK pin of the display screen, the SDA pin of the display screen is connected to the P0.18 pin of the microprocessor, the SCL pin of the display screen is connected to the P0.19 pin of the microprocessor, the RS pin of the display screen is connected to the P0.17 pin of the microprocessor, the RES pin of the display screen is connected to the P0.16 pin of the microprocessor, the CS pin of the display screen is connected to the P0.15 pin of the microprocessor, the GND pin and the GND2 pin of the display screen are grounded respectively, and the I The M1 pin is electrically connected to the battery 4 via the resistor R1 and is grounded via the resistor R1 and the capacitor C9. The VCC pin and the LEDA pin of the display screen are electrically connected to the battery 4 and are grounded via the capacitor C9 respectively. The GND pin of the LED driver is grounded. The P0.24 pin of the microprocessor is connected to the gate of the MOS field effect tube, the source of the MOS field effect tube is electrically connected to the battery 4, the drain of the MOS field effect tube is connected to the VDD pin of the acceleration sensor, the CSB pin of the acceleration sensor is connected to the P0.30 / AIN6 pin of the microprocessor, the SCX pin of the acceleration sensor is connected to the P0.29 / AIN5 pin of the microprocessor, the SDO pin of the acceleration sensor is connected to the P0.28 / AIN4 pin of the microprocessor, the SDI pin of the acceleration sensor is connected to the P0.27 pin of the microprocessor, the VDDIO pin of the acceleration sensor is connected to the VDD2 pin of the microprocessor, the PS pin, the NC pin, the GND pin and the GND pin of the acceleration sensor are connected to the VDD2 pin of the microprocessor, and the VDDIO pin of the acceleration sensor is connected to the VDD2 pin of the microprocessor. The IO pins are grounded respectively; the VDD pin of the acceleration sensor is grounded via capacitor C38, and the VDDIO pin of the acceleration sensor is grounded via capacitor C39; the source and drain of the MOS field effect tube are connected via resistor R69, and the gate and source of the MOS field effect tube are connected via resistor R19; the VI of the voltage regulator chip The N pin is electrically connected to the battery 4 and is grounded via capacitors C26 and C28 respectively; the EN pin of the voltage regulator chip is connected to the P0.13 pin of the microprocessor and the EN pin of the voltage regulator chip is grounded via resistor R6; the OUT pin of the voltage regulator chip is connected to the 4th pin of the heart rate cable and the OUT pin of the voltage regulator chip is grounded via capacitor C30; the NC pin of the voltage regulator chip is grounded; the positive electrode of the vibration motor is electrically connected to the battery 4 via resistor R60; the negative electrode of the vibration motor is connected to the P0.31 / AIN7 pin of the microprocessor via a junction field effect transistor, and the source of the junction field effect transistor is grounded; the OUT pin of the touch detection chip is connected to the P0.08 pin is connected, the SO pin of the touch detection chip is connected to the touch panel via resistor R24, the STG pin of the touch detection chip is grounded, and the VDD pin and SLH pin of the touch detection chip are grounded via capacitor C8 and capacitor C21 respectively; the battery 4 is a rechargeable battery, and the rechargeable battery is electrically connected to the battery charging management chip.

[0053] In this embodiment, the microprocessor model is NFR52832-QFN-49, the storage chip model is PN25F08DF ITG DNF-8-2_3, the LED driver model is AW9364DNR, the display model is OLED_0.96-TFT, the acceleration sensor model is BMA-253, the voltage regulator chip model is LC1463CB5ATR33, the touch detection chip model is TTP23D-HA6, and the power charging management chip model is CX9058A.

[0054] When the pulse diagnosis wristband is working, the optical sensor (6) will collect a value within the range of 0G to 166000G every 1 millisecond and send the collected value to the microprocessor for calculation and filtering. The value collected by the optical sensor (6) will be filtered into a value every 20 milliseconds. These values ​​form a pulse wave waveform containing three physical properties of time, space and intensity. The structure of the pulse wave waveform is composed of data collection points collected every 20 milliseconds from the front valley point to the first peak point, the first peak point to the middle valley point, the middle valley point to the second peak point and the second peak point to the back valley point. The vertical axis value of the front valley point is the same as the vertical axis value of the back valley point. The range of 0G to 166000G is calculated based on the irradiation distance of the light emitted by the light emitter of the optical sensor (6) being 6mm; the three physical characteristics are expressed as follows: the average difference of the pulse data differences in different partitions on the pulse wave waveform, in units of S; the spatial characteristics of the pulse wave are expressed by the number of numerical points in different partitions on the pulse wave waveform, in units of M; and the pulse intensity is expressed by the vertical axis coordinates of the numerical points of the pulse wave waveform, in units of G.

[0055] When using the pulse diagnosis bracelet to diagnose the wearer's pulse, the pulse diagnosis bracelet implements pulse diagnosis through the following steps:

[0056] S1) using the optical sensor 6 to obtain pulse wave data for calculation and practical application, collecting data every 1 millisecond; collecting data and obtaining a pulse wave waveform diagram based on the collected data, such as Fig.10 As shown;

[0057] S2) processing the pulse wave data obtained in step S1) to obtain a pulse wave waveform including three characteristics of time, space and intensity, wherein the pulse wave waveform includes at least one front valley point, one peak point and one back valley point, and the vertical axis value of the front valley point is the same as the vertical axis value of the back valley point; when processing the data obtained in step S1), filtering the pulse wave data collected in step S1) into a pulse wave waveform diagram consisting of one value every 20 milliseconds, and filtering by a DC filter, a mean filter, a median filter and a Butterworth filter in sequence, the pulse wave waveform diagram after filtering is as shown in Fig.11 As shown, the data obtained by filtering by DC filter, mean filter, median filter and Butterworth filter in sequence is processed as follows:

[0058] S2-1) performing a difference calculation on two adjacent pulse data of the data obtained through filtering to obtain a pulse data difference, and obtaining a pulse wave waveform from the obtained pulse data difference;

[0059] S2-2) obtaining the value of each numerical point in the pulse wave waveform from the pulse data difference obtained in step S2-1), the number of numerical points in the ascending branch of the pulse wave waveform, the number of numerical points in the descending branch of the pulse wave waveform, the number of data points contained in the point-to-point relationship from the front valley point to the middle valley point, the number of numerical points from the middle valley point to the first peak point, the number of numerical points from the first peak point to the middle valley point, the number of numerical points from the middle valley point to the second peak point, the number of numerical points from the second peak point to the back valley point, the average difference of the distance points between the front upper wave, the average difference of the distance points between the front lower wave, the average difference of the distance points between the back lower wave, and the average difference of the distance points between the two peaks and the front upper wave;

[0060] S3) comparing the data obtained in step S2-2) with the pulse waveform of the normal pulse and obtaining the pulse waveform corresponding to the pulse waveform diagram obtained in step S2). Fig.12 shown.

[0061] After the pulse wave waveform is obtained, the normal pulse wave waveform is used as a standard reference to analyze and judge the obtained pulse wave waveform, and the pulse condition corresponding to the obtained pulse wave waveform is judged according to the following method:

[0062] Table 1 Relationship between pulse symptom degree and heart rate when pulse is hot

[0063] grade Heart rate range normal <![CDATA[HR 测 =HR 标 ]]> Slightly worse <![CDATA[HR 测 =HR 标 +5]]> Poor <![CDATA[HR 测 =HR 标 +10]]> serious <![CDATA[HR 测 =HR 标 +20]]>

[0064] Table 2 Relationship between pulse symptom severity and heart rate when the pulse is cold

[0065] grade Heart rate range normal <![CDATA[HR 测 =HR 标 ]]> Slightly worse <![CDATA[HR 测 =HR 标 -5]]> Poor <![CDATA[HR 测 =HR 标 -10]]> serious <![CDATA[HR 测 =HR 标 -15]]>

[0066] Table 3 Relationship between the degree of pulse symptoms and the difference in the number of ascending and descending branch value points when the pulse is damp

[0067]

[0068] Table 4 Relationship between the degree of pulse symptoms and the difference between the peak and valley values ​​of the pulse waveform when the pulse is weak

[0069] grade Ascending and descending branches normal <![CDATA[F 测1 =F 1 -(F 4 +F 5 ) / 2≥650G <!-- 6 -->]]> Slightly worse <![CDATA[450G≤F 测1 =F 1 -(F 4 +F 5 ) / 2≤649G]]> Poor <![CDATA[250G≤F 测1 =F 1 -(F 4 +F 5 ) / 2≤449G]]> serious <![CDATA[F 测1 =F 1 -(F 4 +F 5 ) / 2≤249G]]>

[0070] Table 5 The relationship between the pulse symptom degree and the difference between the two numerical points before and after the peak point of the main wave when the pulse is blood deficiency

[0071] grade The difference between the peak value of the main wave and the values ​​of the two points before and after the peak normal <![CDATA[F 测2 =F 1 -(F 2 +F 3 ) / 2≤10G]]> Slightly worse <![CDATA[11G≤F 测2 =F 1 -(F 2 +F 3 ) / 2≤15G]]> Poor <![CDATA[16G≤F 测2 =F 1 -(F 2 +F 3 ) / 2≤20G]]> serious <![CDATA[F 测2 =F 1 -(F 2 +F 3 ) / 2>21G]]>

[0072] The algorithm analysis of 27 pulse routine element data and pulse autonomous feature data in TCM diagnosis is as follows:

[0073] Pulse rate re>HR 标 (Characteristics of hot pulse: rapid pulse rate, 90-139 beats / minute, more than five beats per breath), the main disease is heat syndrome.

[0074] Pulse "slow" han<HR 标 (Characteristics of cold pulse: three beats per breath), mainly indicating cold syndrome.

[0075] Depend on Figure 5 Respiratory gate and HR 标 The heart rate range matching the age is combined with calculation, and the comprehensive heart rate value of each completed test is used as the standard to display according to the above heat / cold level. The two items belong to a single regular element type, so the heat / cold categories are displayed separately on the pulse diagnosis page of the APP.

[0076] Pulse condition: "weak" xu = F 1 -(F 4 +F 5 ) / 2<650G, pulse characteristics. Weak pulse is deficiency. Main disease: deficiency syndrome. Pulse “excessive”sh i=F 1 -(F 4 +F 5 ) / 2≥650G, strong pulse indicates excess, mainly indicating excess syndrome of the disease.

[0077] The pulse condition "virtual" and "real" belong to a single regular element category. For easy understanding, only one of them is displayed on the pulse diagnosis page of the APP, so the virtual value is the real value when it is normal, and the other combinations add the concept of real.

[0078] Pulse is "slippery" Pulse characteristics: smooth and fluent, like a bead rolling on a plate, smooth response to the fingers. Main disease: excess heat syndrome.

[0079] Autonomous feature algorithm:

[0080] hua1=(K 1 +K 3 )>(K 2 +K 5 )*2

[0081] Conventional element-wise algorithms:

[0082] hua2=F 1 -(F 4 +F 5 ) / 2≥650G,

[0083] hua3>HR 标 , containing solidity and heat.

[0084] Pulse characteristics: opposite to slippery pulse, like a light knife scraping bamboo. Main diseases: blood stasis, blood stasis.

[0085] Autonomous feature algorithm:

[0086] se1=F 1 -(F 2 +F 3 ) / 2≥20G

[0087] se2=(F 1 -F 6 )<F 1 / 3

[0088] Conventional element-wise algorithms:

[0089] se3=(Q 升 -Q 降 )≥50M

[0090] se4>HR 标 , containing moisture and heat.

[0091] Characteristics of a “long” pulse: The pulse is long and straight, exceeding its normal position. It indicates a normal pulse or excess evil qi.

[0092] Autonomous feature algorithm:

[0093] 1S<chang1=(K 1 +K 3 )-(K 2 +T 4 )<10Schang2=(Q 3 +Q 4 )>Q 升 >Q 5

[0094] Conventional element-wise algorithms:

[0095] chang3=F 1-(F 4 +F 5 ) / 2≥650G, including solid.

[0096] "Short" pulse characteristics: short at the beginning and end, unable to fill the whole part. Main disease: Qi deficiency.

[0097] Autonomous feature algorithm:

[0098] duan1=(Q 降 +Q 升 ) / (Q 3 +Q 4 )>3

[0099] duan2=(K 1 +K 3 )>(K 2 +K 4 )

[0100] duan3=(F 1 -F 6 )<F 1 / 3

[0101] Conventional element-wise algorithms:

[0102] duan4=F 1 -(F 4 +F 5 ) / 2≥249G, including deficiency.

[0103] Pulse characteristics of "Hong" pulse: like a flood, strong when it comes and weak when it goes. Main diseases: hyperactivity of Yang heat and loss of residual Yang.

[0104] Autonomous feature algorithm:

[0105] hong1=(K 2 +K 4 )-(K 1 +K 3 )>10S

[0106] hong2=(Q 3 +Q 4 )>Q 升 >Q 5

[0107] Conventional element-wise algorithms:

[0108] hong3=F 2 -(F 4 +F 5 ) / 2≥450G

[0109] hong4>HR 标 Contains deficiency and heat.

[0110] “Weak” pulse characteristics: thin and small pulse, weak pulse, and almost stop when pressed. Main disease: severe deficiency of Qi and blood.

[0111] Autonomous feature algorithm:

[0112] wei 1=(K 2 +K 4 )-(K 1 +K 3 )>10S

[0113] wei2=(Q 3 +Q 4 )>Q 升 >Q 5

[0114] Conventional element-wise algorithms:

[0115] wei3=F 1 -(F 4 +F 5 ) / 2≤249G

[0116] wei4=F 1 -(F 2 +F 3 ) / 2>10G

[0117] wei5<HR 标 , deficiency of blood, and cold.

[0118] Pulse is thin. Pulse characteristics: thin pulse, like a silk thread, obvious response. Main disease: deficiency of both qi and blood, and dampness syndrome.

[0119] Autonomous feature algorithm:

[0120] xi 1=(K 1 +K 3 )>(K 2 +K 4 )

[0121] Conventional element-wise algorithms:

[0122] x i2=F 1 -(F 4 +F 5 ) / 2≤249G

[0123] x i3=F 1 -(F 2 +F 3 ) / 2>20G

[0124] x i4=(Q 升 -Q 降 ), 25M<xi4<40M

[0125] x i5>HR 标

[0126] Contains deficiency, blood deficiency, dampness and heat.

[0127] Pulse "wet" pulse characteristics: floating, thin and soft, not noticeable when pressed hard. Main diseases: deficiency syndrome, dampness syndrome, autonomous feature algorithm:

[0128] 120000G<ru1<166000G,

[0129] ru2=(K 2 +K 4 )-(K 1 +K 3 )>10S

[0130] Conventional element-wise algorithms:

[0131] ru3=F 1 -(F 4 +F 5 ) / 2≤249G

[0132] ru4=(Q 升 -Q 降 ), 25M<ru4<40M, including deficiency and dampness.

[0133] The pulse condition of "weak" is characterized by: extremely thin, soft and weak. Main disease: deficiency of Qi and blood. Autonomous characteristic algorithm:

[0134] 0G<ruo1<46000G

[0135] ruo2=(Q 3 +Q 4 )>Q 升 >Q 5

[0136] Conventional element-wise algorithms:

[0137] ruo3=F 1 -(F 4 +F 5 ) / 2≤249G

[0138] ruo4=F 1 -(F 2 +F 3 ) / 2>20G, deficiency of body fluid and blood.

[0139] The characteristics of the "tight" pulse are: the pulse is tight and like a twisting rope. Main diseases: cold syndrome and pain syndrome.

[0140] Autonomous feature algorithm:

[0141] ji n1=(K 1 +K 3 )>(K 2 +K 4 )

[0142] ji n2=(F 1 -F 6 )<F 1 / 3

[0143] Conventional element-wise algorithms:

[0144] ji n3=F 1 -(F 4 +F 5 ) / 2≥450G

[0145] ji n4<HR 标 , containing deficiency and cold.

[0146] The pulse is described as "slow". The pulse is characterized by: slow coming and going or the pulse is loose and lacks sufficient tension. Main disease: dampness syndrome.

[0147] Autonomous feature algorithm:

[0148] huan1=(K 1 +K 3 )>(K 2 +K 4 )

[0149] Conventional element-wise algorithms:

[0150] huan2=F 1 -(F 4 +F 5 ) / 2≤250G

[0151] huan3=(Q 升 -Q 降 )≥50M, including deficiency and dampness.

[0152] Pulse characteristics: straight and long, like pressing a string. Main disease: liver and gallbladder diseases.

[0153] Autonomous feature class algorithm: x ian1 = (K 1 +K 3 )>(K 2 +K 4 ),

[0154] Conventional element-based algorithm: x ian2 = F 1 -(F 4 +F 5 ) / 2≥250G, including virtual.

[0155] Pulse "moving" pulse characteristics: pulse shape is like a bean, slippery, rapid and short. Main diseases: pain, panic.

[0156] Autonomous feature algorithm:

[0157] dong1=(K 1 +K 3 )>(K 2 +K 4 )

[0158] dong2=(F 1 -F 6 )<F 1 / 3

[0159] Conventional element-wise algorithms:

[0160] dong3=F 1 -(F 4 +F 5 ) / 2≥450G

[0161] dong4>HR 标 , containing deficiency and heat.

[0162] Pulse characteristics of "Le": floating and strong, hollow inside and hard outside, like pressing on the skin of a drum. Main diseases: severe deficiency of essence and blood, floating of Yang Qi.

[0163] Autonomous feature algorithm:

[0164] ge1=(F 1 -F 6 )>(F 6 -F 7 )≥(F 1 -F 6 ) / 3

[0165] Conventional element-wise algorithms:

[0166] ge2=F 1 -(F 2 +F 3 ) / 2>20G

[0167] ge3=F 1 -(F 4 +F 5 ) / 2≥650G, including excess and blood deficiency.

[0168] The pulse is characterized by five features: deep, stringy, solid, surging and long. Main diseases: internal coldness, hernia and abdominal mass.

[0169] Autonomous feature algorithm: l ao1≤46000G

[0170] Conventional element class algorithm: lao2 = xi an (string) + xu (real) + hong (flood) + chang (long) contains heat.

[0171] Pulse condition "scattered" Pulse characteristics: Floating and scattered without root, disappearing slightly when pressed, and uneven rhythm. Main diseases: Depletion of vital energy, exhaustion of visceral qi.

[0172] Autonomous feature class algorithm:

[0173] san1 = (F 1 -F 6 ) > (F 6 -F 7 ) ≥ (F 1 -F 6 ) / 3

[0174] Conventional element class algorithm:

[0175] san2 = F 1 -(F 2 +F 3 ) / 2 > 20G

[0176] san3 = F 1 -(F 4 +F 5 ) / 2 ≤ 249G, contains deficiency, blood deficiency.

[0177] Pulse condition "hollow" Pulse characteristics: Floating, large, and hollow in the middle, like pressing on a scallion tube. Main diseases: Blood loss, injury to yin.

[0178] Autonomous feature class algorithm:

[0179] kou1 = (F 1 -F 6 ) > (F 6 -F 7 ) ≥ (F 1 -F 6 ) / 3

[0180] Conventional element class algorithm:

[0181] kou2 = F 1 -(F 2 +F 3 ) / 2 > 20G

[0182] kou3 = F 1 -(F 4 +F 5 ) / 2 ≥ 449G

[0183] kou4 = (Q 升 -Q 降 ) ≥ 50M, contains deficiency, blood deficiency, dampness.

[0184] Pulse characteristics: rapid and irregular pulse, intermittent pauses. Main diseases: hyperactivity of Yang heat, blood stasis, blood stasis.

[0185] Autonomous feature algorithm:

[0186] cu1=(T 2 -T 1 )<(T 3 -T 2 ) / 2+100 ms

[0187] Conventional element-based algorithm: cu2>HR 标

[0188] cu3=F 1 -(F 2 +F 3 ) / 2>20G

[0189] cu4=(Q 升 -Q 降 )>10M, including heat, dampness and blood deficiency.

[0190] Pulse "knot" pulse characteristics: pulse is slow and sometimes stops, and the number of stops is uncertain. Main diseases: Yin excess and qi stagnation, cold phlegm and blood stasis.

[0191] Autonomous feature algorithm:

[0192] j ie1=(T 2 -T 1 )<(T 3 -T 2 ) / 2+100 ms

[0193] Conventional element-wise algorithms:

[0194] j ie2<HR 标

[0195] j ie3=F 1 -(F 2 +F 3 ) / 2>20G

[0196] j ie4=(Q 升 -Q 降 )>10M, including cold, dampness and blood deficiency.

[0197] The pulse characteristics of "intermittent pulse": pulse comes and stops, stops for a certain number of times, two beats and one stop, four beats and one stop. Main diseases: internal organ qi deficiency, pain, panic, fall and injury. Among them, the positioning diagram of pulse urgency, knot, and intermittence is as follows Fig.13 shown.

[0198] Autonomous feature algorithm:

[0199] dai 1=(T2 -T 1 )<(T 3 -T 2 ) / 2+100 ms

[0200] dai2=(T 3 -T 1 )-(T 5 -T 3 )<(T 2 -T 1 )

[0201] Conventional element-wise algorithms:

[0202] dai3=F 1 -(F 2 +F 3 ) / 2>20G

[0203] dai4=(Q 升 -Q 降 )>10M, containing dampness and blood deficiency.

[0204] Pulse "fast" Pulse characteristics: rapid pulse, seven or eight beats per breath, heart rate over 140. Main disease: hyperactivity of Yang and exhaustion of Yin, loss of vital energy,

[0205] Autonomous feature algorithm: Ji≥HR 标 *2

[0206] The pulse combinations containing multiple conventional element types are as follows:

[0207] Single: hot – (solid, long, stringy, smooth, moving, fast), cold – (solid, tight, stringy, firm), empty – (empty, short).

[0208] Two-in-one: Deficiency / heat--(deficiency, floating, surging, stringy, moving, fast, short), Deficiency / cold--(sinking, short, stringy, tight), Deficiency / dampness--(moist, slow), Deficiency / blood deficiency--(scattered, weak, , wiry), Dampness / heat--(surging, solid, astringent), Dampness / cold--(sinking, tight, stringy), Dampness / blood deficiency--(leather, wiry, substitute), Heat / blood deficiency--(leather, wiry, fast), Cold / blood deficiency--(leather).

[0209] Three-in-one: Deficiency / heat / dampness--(moist, slow, stringy, fast), Deficiency / cold / dampness--(tight, slow, stringy), Deficiency / cold / blood deficiency (slight, weak), Deficiency / heat / blood deficiency (thin, weak, fast), Deficiency / dampness / blood deficiency (weak, wiry, intermittent), Heat / dampness / blood deficiency (wiry, astringent, hurried, intermittent, fast), Cold / dampness / blood deficiency (stringy, wiry, knotty).

[0210] Four-in-one: Deficiency / heat / dampness / blood deficiency -- (thin, astringent, weak, wiry, hurried, intermittent, fast), Deficiency / cold / dampness / blood deficiency -- (slight, weak, knotty, intermittent).

[0211] HR stands for heart rate. The heart rate of a 1-year-old infant is 118-122 beats / minute, that of a 3-year-old child is 115-119 beats / minute, that of a 10-year-old child is 83-87 beats / minute, that of a 35-year-old adult is 68-72 beats / minute, that of a 60-year-old is 58-62 beats / minute, and that of an 80-year-old is 53-57 beats / minute. 测 Indicates heart rate measurement value, HR 标 Indicates the standard heart rate range; Q 测 Indicates the difference in the number of numerical points between the ascending and descending branches of the pulse wave during measurement, Q 升 is the number of numerical points in the ascending branch of the pulse wave, Q 降 is the number of numerical points in the descending branch of the pulse waveform, Q 1 Q is the number of data points from the front valley point to the middle valley point. 2 Q is the number of points from the valley point to the peak point. 3 Q is the number of numerical points from a peak point to a mid-valley point. 4 Q is the number of numerical points from the mid-valley point to the second peak point. 5 F is the number of numerical points from the second peak point to the back valley point; 测1 F is the difference between the peak value of the pulse wave and half of the sum of the preceding valley value and the following valley value. 测2 F is the difference between the value of a peak point in the pulse wave waveform during measurement, and half of the sum of the value of the point before the peak and the value of the point after the peak. 1 is a peak value, F 2 is the value of the point before a peak, F 3 is the point value after a peak, F 4 is the previous valley point value, F 5 is the point value of the back valley, F 6 is the value of the second peak point, F 7 K is the mid-valley point value; 1 is the average difference between the previous and next waves, K 2 is the average difference between the previous and next waves, K 3 is the average difference between the last wave and the next wave, K 4 is the average difference between the next wave and the next wave, K 5 is the average difference between the two peaks; T is the time point of the pulse wave main peak value detection, T 1 , T 2 , T 3 , T 4 , T 5 and T 6It is the time point for the numerical detection of the main peak points of six consecutive pulse wave waveforms; the corresponding point of the mid-valley point is the numerical point where the value of the mid-valley point on the main wave is equal to the value of the mid-valley point.

[0212] Under normal circumstances, there is a certain relationship between the respiratory cycle and the pulse cycle, and the cycle matching diagram of the two is as follows: Fig.14 shown.

[0213] The pages displayed on the mobile phone APP interface include the pulse diagnosis page, the medical consultation page, the symptom page, and the food recommendation / avoidance page. Among them, the pulse diagnosis page is the page that mainly displays the pulse condition. Fig.15 As shown in the figure, the pulse diagnosis bracelet collects the human pulse wave waveform and transmits the pulse wave waveform to the APP on the pulse page, and then the APP performs routine pulse analysis to obtain the level of heat, cold, dampness, deficiency, and blood deficiency in the human body. Fig.16 The pulse diagnosis bracelet is worn in the form shown in the figure, and the pulse diagnosis bracelet is connected to the mobile phone APP as shown in the figure Fig.17 shown.

[0214] Specific application case: The pulse diagnosis wristband is used to diagnose the pulse of 36-year-old volunteer A. The pulse diagnosis page of the APP monitors the general elements and displays the conditions as hot / poor, weak / poor, such as Fig.18 As shown, the conventional element class is a two-in-one combination, including (virtual, floating, flood, string, dynamic, fast, short), and the autonomous feature class algorithm string x ian1 = (K 1 +K 3 )>(K 2 +K 4 ), K is marked on the pulse waveform reference 1 =28S,K 3 =16S,K 2 =20, K 4 =18, which meets the condition of the autonomous characteristic class xi an1 of the string, and the normal heart rate range of 36 years old is 69-73, HR 标 =83, number of autonomous feature algorithms>HR 标 , at thermal level HR 测 =HR 标 +10, for the combined pulse pattern of stringy and rapid pulse. [Combined pulse song] Stringy and rapid pulse indicates heat, slow and slow pulse indicates cold. Large string indicates deficiency, thin and tight pulse indicates stiffness. Yang string indicates headache, Yin string indicates abdominal pain. Single string indicates drinking habit, double string indicates cold. [Main disease song] String represents liver wind, which is responsible for pain and malaria, phlegm and drinking. If the string is on the left inch, there will be pain in the heart; if the string is on the right inch, there will be chest and headache. If the left guan is stringy, there will be phlegm, malaria, dysentery and abdominal mass; if the right guan is stringy, there will be stomach cold and diaphragmatic pain. If the left chi is stringy, and the foot chi is stringy, there will be foot cramps and hernia pain. The volunteer's physical signs include severe swelling after eating, which indicates deficiency-heat in the spleen and stomach, and dry eyes, which indicates excessive liver fire. A36-year-old volunteer's pulse waveform is attached. Fig.19 .

[0215] The pulse diagnosis wristband was used to diagnose the pulse of 13-year-old volunteer B. The pulse diagnosis page of the APP monitored the general elements and showed that the condition was single fever / severe, such as Fig. 20 and Fig.21 As shown, the conventional element category is: deficiency and cold, including (slippery, long, loud, stringy, dynamic), and the autonomous feature class algorithm Hong1 = (K 2 +K 4 )-(K 1 +K 3 )>10S, the pulse wave of the 13-year-old volunteer was measured and marked with K on the reference object 2 =37S, K 4 =21S,K 1 =31S, K 3 =15S, which meets the string's autonomous feature class hong1 condition. Autonomous feature class algorithm hong2 = Q 3 +Q 4 >Q 升 >Q 5 , Q is marked on the pulse waveform reference 3 =22M,Q 升 =20M,Q 4 =4M,Q 5 =12M, which meets the condition of the autonomous characteristic class hong2 of the string. The normal heart rate range for a 13-year-old is 81-85, HR 标 =105, number of autonomous feature algorithms>HR 标 In heat rating HR 测 =HR 标 +20 is the combined pulse. [Body image song] The pulse is very strong, like a flood; it comes strong and goes weak, and it fills the fingers. [Main disease song] Hong means fullness, qi is blocked and fire is hyperactive. The left cun is swollen and large, the heart is upset and the tongue is broken. The right cun is swollen and large, the chest is swollen and the qi is reversed. The left guan is swollen, the liver wood is too much. The right guan is swollen and the spleen is hot. The left chi is swollen, the water is dry and the bowel movement is difficult. The right chi is swollen and dry, the dragon fire is burning. The volunteer's physical signs of sore throat and thirst are due to lung heat, and the right cun is swollen and large, the chest is swollen and the qi is reversed, which belongs to the symptom: lung fire is real fire.

[0216] The pulse diagnosis wristband is used to diagnose the pulse of 14-year-old volunteer C. The general element category of the pulse diagnosis page of the APP is displayed as two-in-one deficiency / severe, cold / poor, such as Fig. 22 and Fig.23 As shown, due to delay < HR 标 The value is at a poor level, so the conventional element category is: deficiency and cold, including (sinking, short, string, tight), the autonomous feature algorithm short duan1 = (Q 降 +Q 升 ) / (Q 3 +Q 4 )>3、duan2=(K 1 +K 3 )>(K 2+K 4 )、duan3=(F 1 -F 6 )>F 1 / 3, the pulse wave waveform is measured with the Q mark on the reference object 降 =51M,Q 升 =32M,Q 3 =22M,Q 4 =5M, meets the conditions of duan1, K 1 =16S,K 3 =7S, K 2 =7S, K 4 =4S, meets the conditions of duan2, F 1 =243G, F 6 =112G, which meets the condition of duan3, and is a combined pulse of coldness and shortness. [Body image song] Short pulse is astringent and small, with both ends bent down; the middle is protruding and cannot fill the whole body. [Main disease song] Shortness is the main pulse of deficiency, which is a syndrome of qi deficiency. Shortness in the main cun, restlessness; shortness in the right cun, headache due to lung deficiency. Shortness in the left guan, liver qi is injured; shortness in the right guan, diaphragm is in trouble. When the left cun is short, the lower abdomen must be painful; the true fire is not strong. The volunteer's physical signs are cold hands and feet, sore waist and soft mouth, insufficient liver qi, liver qi injury, belonging to the symptom: liver qi deficiency.

[0217] The pulse diagnosis wristband was used to diagnose the pulse of a 25-year-old volunteer D. The pulse diagnosis page of the APP (see attached Fig.24 ,25) Conventional element classes are displayed as three-in-one virtual / slightly worse, hot / relatively worse, and wet / slightly worse, such as Fig.24 and Fig.24 As shown, it contains many common elements of dampness, and the common Chinese medicine colloquial dampness and virtual fire, so the pulse page shows: virtual heat and dampness, including (wet, slow, stringy, fast), and the autonomous feature class algorithm stringy 120000G<ru1<166000G, ru2=(K 2 +K 4 )-(K 1 +K 3 )>10S,x ian1=(K 1 +K 3 )>(K 2 +K 4 ), the pulse waveform of a 25-year-old volunteer measured is marked as 136970G on the reference object, which meets the conditions of ru1, K 2 =21S,K 4 =10S, K 1 =32S, K 3=15S, meets the conditions of ru2 and x ian1, and is a combined pulse with stringy and moist pulse. [Body image song] The moist pulse is thin and soft, seen in the floating part; it is visible when lifted, and empty when pressed. [Main disease song] Moisture is the main yin deficiency, marrow and essence damage. Moisture on the left inch indicates forgetfulness and palpitations; moistness on the right inch indicates spontaneous sweating due to skin deficiency. If it is on the left guan, blood cannot nourish the tendons; if it is on the right guan, spleen deficiency and dampness. If it is on the left foot, essence and blood are withered; if it is on the right foot, fire is defeated and life is bad. [Main disease song] String is liver wind. Volunteer D has physical signs of dry mouth and dry face, severe swelling after eating, and moist pulse is the main disease of deficiency syndrome and dampness syndrome. Symptoms: liver qi deficiency, spleen qi deficiency.

[0218] The pulse condition determined by the pulse diagnosis method of the present invention is consistent with the pulse condition obtained by taking the pulse in traditional Chinese medicine. Therefore, the pulse diagnosis wristband capable of pulse diagnosis of the present invention can be used to monitor the pulse condition of the wearer, which is beneficial for the wearer to adjust his diet in time according to his pulse condition.

[0219] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the claims of this patent application.

Claims

1. A pulse diagnosis method, characterized in that: The steps include: S1) using an optical sensor to obtain pulse wave data for calculation and practical application, collecting data once every 1 millisecond; the values ​​collected by the optical sensor will be filtered into a value every 20 milliseconds, and these values ​​will form a pulse wave waveform containing three physical characteristics of time, space and intensity, and the three physical characteristics are expressed as: the average difference of pulse data differences in different partitions on the pulse wave waveform, the unit is S; The spatial characteristics of the pulse wave are described by the number of numerical points in different partitions on the pulse wave waveform, with the unit being M; The pulse intensity is expressed by the vertical coordinate of the pulse wave value point, in G; S2) Processing the pulse wave data obtained in step S1) to obtain a pulse wave waveform including three characteristics of time, space and intensity, wherein the pulse wave waveform includes at least one front valley point, one peak point and one back valley point, and the longitudinal axis value of the front valley point is the same as the longitudinal axis value of the back valley point; when processing the data obtained in step S1), filtering the pulse wave data collected in step S1) into a pulse wave waveform consisting of one value every 20 milliseconds, and filtering by a DC filter, a mean filter, a median filter and a Butterworth filter in sequence, and then performing the following processing on the data obtained by filtering by the DC filter, the mean filter, the median filter and the Butterworth filter in sequence: S2-1) performing a difference calculation on two adjacent pulse data of the data obtained through filtering to obtain a pulse data difference, and obtaining a pulse wave waveform from the obtained pulse data difference; S2-2) obtaining the value of each numerical point in the pulse wave waveform from the pulse data difference obtained in step S2-1), the number of numerical points in the ascending branch of the pulse wave waveform, the number of numerical points in the descending branch of the pulse wave waveform, the number of data points contained in the point-to-point relationship from the front valley point to the middle valley point, the number of numerical points from the middle valley point to the first peak point, the number of numerical points from the first peak point to the middle valley point, the number of numerical points from the middle valley point to the second peak point, the number of numerical points from the second peak point to the back valley point, the average difference of the distance points between the front upper wave, the average difference of the distance points between the front lower wave, the average difference of the distance points between the back lower wave, and the average difference of the distance points between the two peaks and the front upper wave; S3) comparing the data obtained in step S2-2) with the pulse waveform of the normal pulse and obtaining the pulse waveform corresponding to the pulse waveform diagram obtained in step S2).

2. A pulse diagnosis system having the pulse diagnosis method according to claim 1, characterized in that: It includes a data acquisition unit, a storage unit and a microprocessor. The storage unit pre-stores a pulse diagnosis program that realizes pulse diagnosis and can be run on the microprocessor. The microprocessor is communicatively connected to the data acquisition unit and the storage unit respectively. When the microprocessor executes the pulse diagnosis program, the steps of the pulse diagnosis method as claimed in claim 1 are implemented.

3. A pulse diagnosis device, characterized in that: The invention comprises a computer mainboard (3), an optical sensor (6), a data acquisition card (5), an acceleration sensor, a vibration motor, a Bluetooth chip, a display screen, a battery (4), a packaging shell (2) and a wrist strap (1), wherein a storage chip and a microprocessor are arranged on the computer mainboard (3), the microprocessor is respectively connected to the storage chip, the data acquisition card (5), the acceleration sensor, the vibration motor, the Bluetooth chip and the display screen in communication, and the data acquisition card (5) is connected to the optical sensor (6); the microprocessor, the storage chip, the optical sensor (6), the data acquisition card (5), the acceleration sensor, the vibration motor, the Bluetooth chip and the display screen in communication. The sensor, the vibration motor, the Bluetooth chip and the display screen are electrically connected to the battery (4) respectively; the memory chip has a pulse diagnosis program that realizes pulse diagnosis and can be run on the microprocessor pre-stored therein, and the microprocessor implements the steps of the pulse diagnosis method as claimed in claim 1 when executing the pulse diagnosis program; the computer motherboard (3), the optical sensor (6), the data acquisition card (5), the acceleration sensor, the vibration motor, the Bluetooth chip and the battery (4) are respectively installed in the packaging shell (2), the display screen is installed on the outer wall of the packaging shell (2), and the wrist band (1) is installed on the packaging shell (2).

4. The pulse diagnosis device according to claim 3, characterized in that: The P0.11 pin of the microprocessor is connected to the LED_EN pin of the LED driver, the LEDK pin of the LED driver is connected to the LEDK pin of the display screen, the SDA pin of the display screen is connected to the P0.18 pin of the microprocessor, the SCL pin of the display screen is connected to the P0.19 pin of the microprocessor, the RS pin of the display screen is connected to the P0.17 pin of the microprocessor, the RES pin of the display screen is connected to the P0.16 pin of the microprocessor, the CS pin of the display screen is connected to the P0.15 pin of the microprocessor, the GND pin and the GND2 pin of the display screen are grounded respectively, the IM1 pin of the display screen is electrically connected to the battery (4) via the resistor R1 and is grounded via the resistor R1 and the capacitor C9, the VCC pin and the LEDA pin of the display screen are electrically connected to the battery (4) respectively and are grounded via the capacitor C9; the GND pin of the LED driver is grounded.

5. The pulse diagnosis device according to claim 4, characterized in that: The P0.24 pin of the microprocessor is connected to the gate of the MOS field effect tube, the source of the MOS field effect tube is electrically connected to the battery (4), the drain of the MOS field effect tube is connected to the VDD pin of the acceleration sensor, the CSB pin of the acceleration sensor is connected to the P0.30 / AIN6 pin of the microprocessor, the SCX pin of the acceleration sensor is connected to the P0.29 / AIN5 pin of the microprocessor, the SDO pin of the acceleration sensor is connected to the P0.28 / AIN4 pin of the microprocessor, and the acceleration sensor is connected to the VDD pin of the acceleration sensor. The SDI pin of the acceleration sensor is connected to the P0.27 pin of the microprocessor, the VDDIO pin of the acceleration sensor is connected to the VDD2 pin of the microprocessor, and the PS pin, NC pin, GND pin and GNDIO pin of the acceleration sensor are grounded respectively; the VDD pin of the acceleration sensor is grounded via a capacitor C38, and the VDDIO pin of the acceleration sensor is grounded via a capacitor C39; the source and drain of the MOS field effect tube are connected via a resistor R69, and the gate and source of the MOS field effect tube are connected via a resistor R19.

6. The pulse diagnosis device according to claim 5, characterized in that: The VIN pin of the voltage stabilizing chip is electrically connected to the battery (4) and is grounded via capacitors C26 and C28 respectively; the EN pin of the voltage stabilizing chip is connected to the P0.13 pin of the microprocessor and is grounded via resistor R6; the OUT pin of the voltage stabilizing chip is connected to the 4th pin of the heart rate cable and is grounded via capacitor C30; and the NC pin of the voltage stabilizing chip is grounded; the positive electrode of the vibration motor is electrically connected to the battery (4) via resistor R60; the negative electrode of the vibration motor is connected to the P0.31 / AIN7 pin of the microprocessor via a junction field effect transistor; and the source of the junction field effect transistor is grounded; the OUT pin of the touch detection chip is connected to the P0.08 pin of the microprocessor; the SO pin of the touch detection chip is connected to the touch panel via resistor R24; the STG pin of the touch detection chip is grounded; and the VDD pin and SLH pin of the touch detection chip are grounded via capacitors C8 and C21 respectively.

7. The pulse diagnosis device according to claim 6, characterized in that: The battery (4) is a rechargeable battery, and the rechargeable battery is electrically connected to a charging management chip of the battery (4).

Images