CN115363543A

CN115363543A - Uric acid monitoring method based on wearable equipment

Info

Publication number: CN115363543A
Application number: CN202211050223.XA
Authority: CN
Inventors: 白伟民
Original assignee: Beijing Xueyang Technology Co ltd
Current assignee: Beijing Xueyang Technology Co ltd
Priority date: 2022-08-31
Filing date: 2022-08-31
Publication date: 2022-11-22

Abstract

The invention provides a uric acid monitoring method based on wearable equipment, which comprises the following steps: step 1: acquiring original pulse data of a wearer based on wearable equipment, and step 2: analyzing the original pulse data to obtain PPG data of the wearer, and 3: and inputting the PPG data into a big data AI model to evaluate the current uric acid level of the wearer, transmitting the current uric acid level to a designated terminal to be displayed so as to acquire original pulse data in real time all day under an insensitive state, and objectively and accurately evaluating the uric acid level by using the big data model.

Description

Uric acid monitoring method based on wearable equipment

Technical Field

The invention relates to the technical field of wearable devices, in particular to a uric acid monitoring method based on wearable equipment.

Background

Uric acid is the final product of purine metabolism in the human body, and has no physiological function in the human body, and the main sources of purine in the human body are diet and nucleoprotein decomposition. Under normal conditions, the urine is mainly excreted by the kidney, and the rest is excreted out of the body through intestinal tracts, skin, hair and the like, and gout, hyperlipoidemia, malignant blood diseases, kidney diseases, chronic leukemia and the like all reflect the rise of the content of uric acid clinically, so the uric acid component can be used as an important index for diagnosing the etiology by testing.

The mode of the current popular detection uric acid is, go formal hospital and draw blood and detect, need low purine diet 3 days after moreover before drawing blood, empty stomach 8 hours before drawing blood moreover, the inefficiency of detecting like this, latency is long, is not convenient for carry out the high frequency and measures, and to diet before drawing blood, the work and rest has the requirement, influences patient's normal life.

In view of this, the present invention provides a uric acid monitoring method based on wearable devices.

Disclosure of Invention

According to the uric acid monitoring method based on the wearable equipment, the intelligent wearable equipment can acquire data in real time all day in a non-inductive state, and the uric acid level can be objectively and accurately evaluated by using the big data model.

The invention provides a uric acid monitoring method based on wearable equipment, which comprises the following steps:

step 1: acquiring raw pulse data of a wearer based on a wearable device;

and 2, step: analyzing the original pulse data to obtain PPG data of the wearer;

and step 3: and inputting the PPG data into a big data AI model to evaluate the current uric acid level of the wearer, and transmitting the current uric acid level to a specified terminal for displaying.

In one manner that may be implemented,

contacting the skin of the wearer by a preset sensor comprised by a wearable device, acquiring raw pulse data of the wearer.

In one manner that may be implemented,

the preset sensor is used for acquiring the skin color of the wearer and the ambient light intensity of the wearing environment;

establishing an adaptive environment based on the skin color of the wearer and the ambient light intensity of the wearing environment;

acquiring raw pulse data of the wearer in the adaptive environment.

In one manner that may be implemented,

analyzing the PPG data of the wearer to obtain a heart rate parameter, a blood pressure parameter and a blood oxygen parameter of the wearer;

and respectively analyzing the heart rate parameter, the blood pressure parameter and the blood oxygen parameter, and obtaining the body health state of the wearer according to the analysis result.

In one manner that may be implemented,

and acquiring the current uric acid level of the wearer in a preset time period, establishing a uric acid level fluctuation list, and transmitting the uric acid level fluctuation list to the appointed terminal for displaying.

In one manner that may be implemented,

a process of parsing the raw pulse data to obtain PPG data of the wearer, comprising:

dividing the original pulse data into a plurality of original subdata segments at intervals of 1min as a unit, and respectively obtaining the heartbeat frequency of each original subdata segment; acquiring a frequency difference between adjacent original subdata segments;

if the frequency differences are within a first preset range, analyzing the original pulse data to obtain a first heartbeat threshold value of the wearer; correcting a preset filter function based on the first heartbeat threshold value to obtain a target filter function; filtering the original pulse data by using the target filtering function to obtain target pulse data;

dividing the target pulse data into a plurality of target subdata segments at intervals of 1min, and performing fast Fourier transform on each target subdata segment to obtain a frequency spectrum corresponding to each target subdata segment;

clustering the target subdata segments with the same frequency spectrum to obtain a plurality of clustering sequences; acquiring a second heartbeat threshold corresponding to each clustering sequence from a preset spectrum-heartbeat threshold list based on the spectrum corresponding to each clustering sequence;

acquiring a data peak corresponding to each target subdata segment in the same clustering sequence; acquiring a third heartbeat threshold corresponding to each target subdata segment by combining a preset data peak-heartbeat threshold list; obtaining a threshold difference between a third heartbeat threshold corresponding to each target subdata segment and a second heartbeat threshold corresponding to the cluster sequence;

obtaining a plurality of pieces of heartbeat information of the wearer based on each target subdata segment; analyzing the heartbeat information to obtain vasoconstriction-dilation information of a heartbeat period corresponding to each target sub-data segment;

and when the threshold difference is larger than 0, adjusting the vasoconstriction information in the corresponding vasoconstriction-dilation information, otherwise, adjusting the dilation information in the corresponding vasoconstriction-dilation information to obtain the PPG data of the wearer.

In one manner that may be implemented,

establishing an adaptive environment based on the skin color of the wearer and the ambient light intensity of the wearing environment; a process of acquiring raw pulse data of the wearer in the adaptive environment, comprising:

obtaining the skin color of the wearer, inquiring a color system corresponding to the skin color in a preset skin color database, and recording the color system as a target color system; matching the wearer with a first emission ray based on the target color system;

acquiring the ambient light intensity of the wearing environment and the first light intensity of the first emission light; superposing the ambient light intensity and the first light intensity, and analyzing the attenuation degree of the ambient light intensity to the first light intensity;

if the weakening degree is larger than a preset weakening degree threshold value, a first irradiation model is established based on the ambient light intensity and the first light intensity to irradiate the target color system, and a first absorption component of the target color system to the first light intensity is obtained;

adjusting the first light intensity in the first irradiation model until the attenuation degree is smaller than a preset attenuation threshold value, acquiring emission light corresponding to the adjusted first light intensity, recording the emission light as second emission light, and acquiring a second absorption component of the target color system to the second emission light intensity;

if the second absorption component is smaller than a preset absorption threshold value, recording the adjusted first irradiation model as a second irradiation model; superposing different light colors for the second emission light in the second illumination model to obtain a third absorption component of the target color system under different light colors; extracting a second irradiation model corresponding to the maximum third absorption component, and recording the second irradiation model as a third irradiation model; extracting second emission light rays after the light colors are superposed in the third irradiation model, and recording the second emission light rays as third emission light rays;

analyzing the third irradiation model to obtain a plurality of model parameters; respectively establishing corresponding inverse parameters for each model parameter to obtain a self-adaptive environment;

and based on the self-adaptive environment, emitting a third emission light to the skin of the wearer, and collecting the reflection light of the skin of the wearer to obtain the original pulse data of the wearer.

In one manner that may be implemented,

if the weakening degree is smaller than a preset weakening degree threshold value, an initial self-adaptive environment is established, and first emission light is emitted to the skin of the wearer.

In one manner that may be implemented,

acquiring the uric acid level fluctuation list, and judging whether the uric acid level of the wearer is in a preset uric acid level range or not;

if not, generating health reminding information, and transmitting the health reminding information to a specified terminal for displaying.

In one manner that may be implemented,

a process of inputting the PPG data into a big data AI model to assess the current uric acid level of the wearer, comprising:

analyzing the PPG data to obtain heart rate parameters, blood pressure parameters and blood oxygen parameters of the wearer, inputting the heart rate parameters, the blood pressure parameters and the blood oxygen parameters into a big data AI model for blood evaluation to obtain blood evaluation information of the wearer;

and extracting uric acid information from the blood evaluation information to obtain the current uric acid level of the wearer.

Compared with the prior art, the invention has the following beneficial effects:

the original pulse data of the wearer is collected, the PPG data of the wearer can be obtained by analyzing the original pulse data, then the PPG data is input into a big data AI model, the uric acid level of the wearer is evaluated, uric acid monitoring can be carried out by utilizing intelligent wearable equipment in a non-inductive state, data are collected in real time all day, the uric acid level can be objectively and accurately evaluated by utilizing the big data model, the detection efficiency is improved, the wearer can eat normally, and the normal life of the wearer is not influenced.

The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

fig. 1 is a schematic view of a workflow of a uric acid monitoring method based on a wearable device in an embodiment of the present invention;

fig. 2 is a schematic workflow diagram of step 2 of a uric acid monitoring method based on a wearable device in an embodiment of the present invention;

fig. 3 is a schematic flow chart illustrating a wearable device-based uric acid monitoring method in an embodiment of the present invention, based on the wearable device collecting the original pulse data of the wearer.

Detailed Description

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.

Example 1

A uric acid monitoring method based on wearable device, as shown in fig. 1, includes:

step 1: acquiring raw pulse data of a wearer based on a wearable device;

step 2: analyzing the original pulse data to obtain PPG data of the wearer;

In this example, the PPG data represents data of the blood volume changes in the microvascular tissue under the skin of the wearer;

in this example, the raw pulse data represents data collected by the wearable device while the wearer is in pulse;

in the example, the big data AI model represents a function model in a big data environment, wherein the function model comprises a plurality of functions, the function updated in the big data is obtained, the use field corresponding to the function is obtained, and the function is input into the AI model if the use field is consistent with the human health field;

in this example, there is some attenuation of the illumination as it passes through the skin tissue and then reflects back to the light sensitive sensor. The absorption of light by other connective tissue like muscles, bones, veins, etc. is substantially constant. (provided that there is no substantial movement of the measurement site), but the blood is different and the absorption of light naturally varies due to the flow of blood in the artery. When we convert light into an electrical signal, it is because the absorption of light by arteries changes, but the absorption of light by other tissues is basically unchanged, and the resulting signal can be divided into a Direct Current (DC) signal and an Alternating Current (AC) signal. The AC signal is extracted to reflect the characteristic of blood flow, i.e. the blood flow condition is pulse wave which can be matched with the pulse condition waveform of traditional Chinese medicine. A technique to determine blood flow characteristics, we use as photoplethysmography PPG. The pulse wave waveform is acquired based on PPG, the traditional Chinese medicine pulse condition waveform is matched, and the relation between the original pulse data and the PPG data is communicated.

The working principle and the beneficial effects of the technical scheme are as follows: gather wearer's original pulse data, it can obtain wearer's PPG data to carry out the analysis to it, then in inputing the big data AI model with PPG data, assess wearer's uric acid level, because the heart beats and can drive vasodilatation and shrink, can gather the blood volume change in the blood vessel from this, it can be under the non-sensible state to utilize intelligent wearing equipment to carry out uric acid monitoring, data are gathered in real time all day, the aassessment uric acid level that utilizes big data model can be objective accurate improves detection efficiency, the wearer can eat and eat normally, do not influence its normal life.

Example 2

On the basis of embodiment 1, the uric acid monitoring method based on the wearable device comprises the following steps:

The working principle and the beneficial effects of the technical scheme are as follows: the sensor is in contact with the skin of a wearer to acquire original pulse data, so that real-time pulse data can be obtained, and uric acid can be conveniently monitored.

Example 3

On the basis of embodiment 2, the uric acid monitoring method based on the wearable device comprises the following steps:

establishing an adaptive environment based on the skin color of the wearer and the ambient light intensity of the wearing environment; acquiring raw pulse data of the wearer in the adaptive environment.

The working principle and the beneficial effects of the technical scheme are as follows: in order to ensure that the acquisition effect avoids external interference, a self-adaptive environment is established according to the skin color of the wearer and the light intensity of the external environment, and then the data is acquired to ensure the accuracy of the data.

Example 4

On the basis of embodiment 1, the uric acid monitoring method based on a wearable device further includes:

The working principle and the beneficial effects of the technical scheme are as follows: by analyzing the PPG data, the heart rate parameter, the blood pressure parameter and the blood oxygen parameter of the wearer can be obtained, the health state of the wearer is further analyzed, and multiple functions of one device are realized.

Example 5

In this example, the predetermined time period is one day;

in this example, the uric acid level fluctuation list represents the uric acid fluctuations of the wearer over a day.

The working principle and the beneficial effects of the technical scheme are as follows: the uric acid fluctuation of the wearer at different time intervals in one day is obtained, a uric acid fluctuation level list is established, and the wearer can observe the uric acid fluctuation condition of the wearer.

Example 6

On the basis of embodiment 1, the process of parsing the raw pulse data to obtain PPG data of the wearer according to the uric acid monitoring method based on a wearable device, as shown in fig. 2, includes:

step 201: dividing the original pulse data into a plurality of original subdata segments at intervals of 1min as a unit, and respectively obtaining the heartbeat frequency of each original subdata segment; acquiring a frequency difference between adjacent original subdata segments;

step 202: if the frequency differences are within a first preset range, analyzing the original pulse data to obtain a first heartbeat threshold value of the wearer; correcting a preset filter function based on the first heartbeat threshold value to obtain a target filter function; filtering the original pulse data by using the target filtering function to obtain target pulse data;

step 203: dividing the target pulse data into a plurality of target subdata segments at intervals of 1min, and respectively carrying out fast Fourier transform on each target subdata segment to obtain a frequency spectrum corresponding to each target subdata segment;

step 204: clustering the target subdata segments with the same frequency spectrum to obtain a plurality of clustering sequences; acquiring a second heartbeat threshold corresponding to each clustering sequence from a preset spectrum-heartbeat threshold list based on the spectrum corresponding to each clustering sequence;

step 205: acquiring a data peak corresponding to each target subdata segment in the same clustering sequence; acquiring a third heartbeat threshold corresponding to each target subdata segment by combining a preset data peak-heartbeat threshold list; acquiring a threshold difference between a third heartbeat threshold corresponding to each target sub-data segment and a second heartbeat threshold corresponding to the cluster sequence;

step 206: obtaining a plurality of pieces of heartbeat information of the wearer based on each target subdata segment; analyzing the heartbeat information to obtain vasoconstriction-dilation information of a heartbeat period corresponding to each target sub-data segment;

step 207: and when the threshold difference is larger than 0, adjusting the vasoconstriction information in the corresponding vasoconstriction-dilation information, otherwise, adjusting the dilation information in the corresponding vasoconstriction-dilation information to obtain the PPG data of the wearer.

In this example, the raw sub-data segment represents the pulse beat of the wearer within one minute;

in this example, the frequency difference represents a heartbeat frequency between two adjacent original sub-data segments;

in this example, the first heartbeat threshold represents a maximum heartbeat of the wearer;

in this example, the preset filter function may be a rectangular window function;

in this example, the target filter function represents a function obtained by correcting a preset filter function by a first heartbeat threshold value and used for filtering the original pulse data;

in this example, the cluster sequence represents a result of classifying the target sub-data segments with the same frequency spectrum into one class;

in this example, the preset data peak-heartbeat threshold value list represents a corresponding relationship list of the data peak and the heartbeat threshold value;

in this example, the vasoconstriction-dilation information represents the state of the blood vessel under heartbeat;

example verification this example: dividing original pulse data into 5 original sub-data segments, namely an original sub-data segment 1, an original sub-data segment 2, an original sub-data segment 3, an original sub-data segment 4 and an original sub-data segment 5, respectively, obtaining direct frequency differences of adjacent original sub-data segments, respectively recording the frequency differences as a, b, c and d, wherein the frequency differences are within a preset first range, analyzing the original pulse data to obtain a first heartbeat threshold value t, then correcting a preset filter function f (x) by using the first heartbeat threshold value t to obtain target filter data tf (x), filtering the original pulse function to obtain a target pulse function MT, then dividing the target pulse function MT into a plurality of target data segments, namely a target sub-data segment 1, a target sub-data segment 2, a target sub-data segment 3, a target sub-data segment 4 and a target sub-data segment 5, performing fast Fourier transform on the 5 original data segments to obtain corresponding frequency spectrums, clustering target sub-data segments with the same frequency spectrums to obtain 3 clustering sequences [ target sub-data segment 1, target sub-data segment 3], [ target sub-data segment 2], [ target sub-data segment 4 and target sub-data segment 5], wherein second heartbeat thresholds of the 3 clustering sequences are x, y and z respectively, data peaks of each clustering sequence are f1, f2 and f3 respectively, corresponding third heartbeat thresholds are g1, g2 and g3, then threshold differences c1, c2 and c3 are obtained, a plurality of pieces of heartbeat information are established to obtain blood vessel contraction-expansion information of a heartbeat period corresponding to each target sub-data segment, and finally corresponding blood vessel contraction-expansion information is adjusted according to the threshold differences to obtain PPG data.

The working principle and the beneficial effects of the technical scheme are as follows: the heartbeat information of a wearer is obtained by analyzing the original pulse data, and the blood vessel is obviously changed due to the fact that the blood vessel is driven to contract and expand during the heartbeat, so that the blood vessel information of the wearer can be indirectly obtained, and the PPG data is obtained by analyzing and is used as a basis for subsequently monitoring the uric acid level.

Example 7

On the basis of embodiment 3, in the uric acid monitoring method based on the wearable device, an adaptive environment is established based on the skin color of the wearer and the ambient light intensity of the wearing environment; the process of acquiring raw pulse data of the wearer in the adaptive environment, as shown in fig. 3, comprises:

step A: obtaining the skin color of the wearer, inquiring a color system corresponding to the skin color in a preset skin color database, and recording the color system as a target color system; matching the wearer with a first emission ray based on the target color system;

and B: acquiring the ambient light intensity of the wearing environment and the first light intensity of the first emission light; superposing the ambient light intensity and the first light intensity, and analyzing the attenuation degree of the ambient light intensity to the first light intensity;

and C: if the weakening degree is larger than a preset weakening degree threshold value, a first irradiation model is established based on the ambient light intensity and the first light intensity to irradiate the target color system, and a first absorption component of the target color system to the first light intensity is obtained;

step D: adjusting the first light intensity in the first illumination model until the attenuation degree is smaller than a preset attenuation threshold value, acquiring emission light corresponding to the adjusted first light intensity, recording the emission light as second emission light, and acquiring a second absorption component of the target color system to the second emission light intensity;

step E: if the second absorption component is smaller than a preset absorption threshold value, recording the adjusted first irradiation model as a second irradiation model; superposing different light colors for the second emission light in the second illumination model to obtain a third absorption component of the target color system under different light colors; extracting a second irradiation model corresponding to the maximum third absorption component, and recording the second irradiation model as a third irradiation model; extracting second emission light rays after the light colors are superposed in the third irradiation model, and recording the second emission light rays as third emission light rays;

step F: analyzing the third irradiation model to obtain a plurality of model parameters; respectively establishing corresponding inverse parameters for each model parameter to obtain a self-adaptive environment;

In this example, the color system represents the system of colors corresponding to skin tones;

in this example, the first emission light represents a monitoring light matched according to a target color system;

in this example, the attenuation degree indicates the degree to which the first light intensity is weakened under the disturbance of the ambient light intensity;

in this example, the first illumination model represents a model established by the ambient light intensity and the first light intensity;

in this example, the first absorption component represents an amount of the first light absorbed by the skin;

in this example, the second illumination model represents a model established by the ambient light intensity and the second light intensity;

in this example, the second emission light ray represents the first emission light ray after intensity adjustment;

example verification this example: the method comprises the steps of obtaining skin color of a wearer, obtaining a color system S of the skin color of the wearer, matching a first emitting light ray x1 with the skin color, obtaining a weakening degree r of the environment light intensity to the first light ray intensity according to the environment light ray intensity H1 and the first light ray intensity D1, establishing a first irradiation model M1 when the weakening degree r is larger than a preset weakening degree, irradiating a target color system to obtain a first absorption component f1, adjusting the first emitting light ray x1 in the first irradiation model M1 to obtain a second emitting light ray x2 and a second absorption component f2, obtaining a second irradiation model M2 if the f2 is smaller than a preset threshold value, adjusting the light color of the second emitting light ray in the second irradiation model M2 to obtain a third absorption component f3, extracting the third emitting light ray x3 with the highest absorption component and the third irradiation model M3, reversely obtaining a self-adaptive environment, and finally collecting original pulse data.

The working principle and the beneficial effects of the technical scheme are as follows: in order to guarantee the acquisition effect and the accuracy of the equipment, the acquisition object and the acquisition environment are analyzed before the original pulse data is acquired, different methods are adopted for different acquisition objects and acquisition environments to acquire, the self-adaptive environment is established in advance, the acquisition effect is guaranteed to be expected, the external interference is reduced to the minimum, and the accuracy of the data is guaranteed.

Example 8

On the basis of embodiment 7, the uric acid monitoring method based on the wearable device comprises the following steps:

The working principle and the beneficial effects of the technical scheme are as follows: and if the weakening degree is smaller than a preset threshold value, directly collecting, and improving the collection efficiency.

Example 9

On the basis of embodiment 5, the method for uric acid monitoring based on a wearable device, = further includes:

if not, generating health reminding information, and transmitting the health reminding information to the designated terminal for display.

The working principle and the beneficial effects of the technical scheme are as follows: and analyzing the health condition of the wearer by analyzing the uric acid level fluctuation list, and then carrying out corresponding reminding.

Example 10

On the basis of embodiment 1, the process of inputting the PPG data into a big data AI model to evaluate the current uric acid level of the wearer includes:

The working principle and the beneficial effects of the technical scheme are as follows: the uric acid of the wearer is evaluated by analyzing the heart rate parameter, the blood pressure parameter and the blood oxygen parameter of the wearer and combining a big data AI model, so that the evaluation result is closer to the real value.

Example 11

inputting the original pulse data into a preset two-dimensional coordinate system for signal processing to obtain a heartbeat signal of the wearer;

analyzing the heartbeat signals, and respectively acquiring an X heartbeat waveform and a Y heartbeat waveform of the wearer in the X direction and the Y direction;

calculating the heartbeat characteristics of the wearer according to formulas (I) and (II);

wherein γ represents the heartbeat characteristic parameter of the wearer, α represents the maximum beating intensity in the X heartbeat waveform and the Y heartbeat waveform, and the value is (0,3), k _x Representing smoothness, k, of the X-beat waveform _y Representing smoothness of the Y heartbeat waveform, representing a waveform peak value by mu, generally taking a waveform peak value corresponding to a maximum peak value in the Y heartbeat waveform, if the peak value of the Y heartbeat waveform is 0, taking a waveform peak value of the X heartbeat waveform, and representing heartbeat characteristics of the wearer by F;

and acquiring a calculation result, judging whether the heartbeat feature of the wearer is matched with a preset feature in a database, and if not, generating first-aid information and transmitting the first-aid information to a designated terminal for displaying.

The working principle and the beneficial effects of the technical scheme are as follows: the database includes 3 preset features, which correspond to 3 situations of the heartbeat feature of the wearer, respectively. In order to further analyze the physical characteristics of the wearer, heartbeat signals are established by utilizing the original pulse data, then the heartbeat characteristics of the wearer are analyzed, if the heartbeat characteristics of the wearer are abnormal, the heart of the wearer is abnormal, emergency information is generated at the moment, and surrounding personnel are warned to rescue in time.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims

1. A uric acid monitoring method based on wearable equipment is characterized by comprising the following steps:

step 1: acquiring raw pulse data of a wearer based on a wearable device;

step 2: analyzing the original pulse data to obtain PPG data of the wearer;

2. The uric acid monitoring method based on wearable equipment as claimed in claim 1, wherein:

a preset sensor comprised by a wearable device contacts the wearer's skin, collecting the wearer's raw pulse data.

3. The uric acid monitoring method based on wearable equipment as claimed in claim 2, wherein:

4. The wearable device-based uric acid monitoring method according to claim 1, further comprising:

5. The wearable device-based uric acid monitoring method according to claim 1, further comprising:

and acquiring the current uric acid level of the wearer in a preset time period, establishing a uric acid level fluctuation list, and transmitting the uric acid level fluctuation list to the specified terminal for displaying.

6. The wearable device-based uric acid monitoring method according to claim 1, wherein the process of analyzing the raw pulse data to obtain the PPG data of the wearer comprises:

clustering the target subdata segments with the same frequency spectrum to obtain a plurality of clustering sequences; acquiring a second heartbeat threshold corresponding to each clustering sequence from a preset frequency spectrum-heartbeat threshold list based on the frequency spectrum corresponding to each clustering sequence;

acquiring a data peak corresponding to each target subdata segment in the same clustering sequence; acquiring a third heartbeat threshold corresponding to each target subdata segment by combining a preset data peak-heartbeat threshold list; acquiring a threshold difference between a third heartbeat threshold corresponding to each target sub-data segment and a second heartbeat threshold corresponding to the cluster sequence;

obtaining a plurality of pieces of heartbeat information of the wearer based on each target subdata segment; analyzing the heartbeat information to obtain vasoconstriction-dilatation information of a heartbeat period corresponding to each target subdata segment;

adjusting vasoconstriction information in the corresponding vasoconstriction-dilation information when the threshold difference is greater than 0; and otherwise, adjusting the expansion information in the corresponding vasoconstriction-expansion information to obtain the PPG data of the wearer.

7. The wearable device-based uric acid monitoring method according to claim 3, wherein an adaptive environment is established based on the skin color of the wearer and the ambient light intensity of the wearing environment; a process of acquiring raw pulse data of the wearer in the adaptive environment, comprising:

8. The wearable device-based uric acid monitoring method according to claim 7, wherein:

9. The wearable device-based uric acid monitoring method according to claim 5, further comprising:

10. The wearable device-based uric acid monitoring method according to claim 1, wherein the process of inputting the PPG data into a big data AI model to evaluate the current uric acid level of the wearer comprises: