User identification methods, devices and electronic equipment

Abstract

This invention provides a user identification method, device, and electronic device, including acquiring and recording the current characteristic data and current arm circumference of the current user; wherein the current characteristic data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum; comparing the current user's current characteristic data and current arm circumference with pre-stored target characteristic data and target arm circumference of a target user to obtain comparison results; and determining whether the current user is a target user based on the comparison results of the current user's current characteristic data and current arm circumference with pre-stored target characteristic data and target arm circumference of a target user. This method can identify non-target users, thereby improving the reliability of long-term blood pressure monitoring and management for individual target users.

Description

Technical Field

[0001] This invention relates to the field of user identification technology, and in particular to a user identification method, apparatus and electronic device. Background Technology

[0002] Currently, electronic blood pressure monitors using the oscillometric method have been on the market for many years. This type of blood pressure monitor works by wrapping an air bag around a part of the body and adjusting the air pressure inside the bag, collecting data on the changes in internal pressure, and calculating the subject's systolic / diastolic blood pressure accordingly.

[0003] This method is only effective for a single measurement. If the same blood pressure monitor is used for multiple measurements by the same user or by different users, it will not make a distinction. Therefore, when conducting long-term blood pressure monitoring / chronic disease management for a single target user, it may be affected by measurement data from non-target users, thereby reducing the reliability of long-term blood pressure monitoring and management for a single target user. Summary of the Invention

[0004] The purpose of this invention is to provide a user identification method, device, and electronic device to improve the reliability of long-term blood pressure monitoring and management for individual target users.

[0005] This invention provides a user identification method applied to a blood pressure monitor, the method comprising:

[0006] Acquire and record the current user's current characteristic data and current arm circumference; wherein, the current characteristic data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum;

[0007] The current user's current feature data and current arm circumference are compared with the pre-stored target user's target feature data and target arm circumference to obtain the comparison results;

[0008] Based on the comparison results, determine whether the current user is the target user.

[0009] Furthermore, the blood pressure monitor includes an air pump and an air bag. The steps for acquiring and recording the current user's current characteristic data include:

[0010] Obtain the sequence of air pressure values ​​for the air bag;

[0011] The air pressure value sequence of the air bag is filtered to obtain the air pressure pulsation sequence;

[0012] An envelope is generated based on a pressure pulsation sequence.

[0013] Based on the envelope and air bag pressure value sequence, obtain the current user's current feature data;

[0014] Record the current feature data.

[0015] Furthermore, the steps for obtaining the current user's current characteristic data based on the envelope and air bag pressure value sequence include:

[0016] Based on the envelope, obtain the current user's systolic blood pressure, diastolic blood pressure, heart rate, current mean blood pressure, and maximum pulse amplitude;

[0017] The difference between each two adjacent air pressure values ​​in the air bag pressure value sequence is processed to obtain multiple difference results; among the multiple difference results, the largest difference result is the first-order difference maximum value and the smallest difference result is the first-order difference minimum value.

[0018] Furthermore, the steps to obtain and record the current user's current arm circumference include:

[0019] Collect the current air pump drive command sequence;

[0020] Based on the current air pump drive command sequence, obtain the current air pump output sequence and the current air bag volume sequence.

[0021] Determine the current arm circumference of the current user based on the current air pump output sequence, the current air bag volume sequence, and the current user's maximum pulse amplitude.

[0022] Record your current arm circumference.

[0023] Furthermore, the steps of obtaining the current air pump output sequence and the current air bag volume sequence based on the current air pump drive command sequence include:

[0024] The current air output sequence of the air pump is obtained according to the formula Og=U*(a1*Pr+b1) / (Pr+c1) or the formula Og=U*(a2-b2*Pr); where U is the effective voltage of the air pump; Pr is the air pressure value sequence of the air bag; and a1, b1, c1, a2, and b2 are all coefficients.

[0025] The current airbag volume sequence is obtained using the formula V = Vatm * Patm / Pr; where Patm is a standard atmospheric pressure value; Vatm is the volume of the gas inside the airbag converted to one atmosphere.

[0026] Furthermore, the steps for determining the current arm circumference of the current user based on the current air pump output sequence, the current air bag volume sequence, and the current user's maximum pulse amplitude include:

[0027] The current arm circumference of the current user is determined according to the formula Cir = a3 * Ogmean * ts + b3 * Ogend * ts + c2 * Vmean + d * Vend; where a3, b3, c2, and d are coefficients; ts is the sampling period; Ogmean is the air volume output of the air pump corresponding to the maximum pulse amplitude of the current user; Ogend is the air volume output of the air pump at the end of the blood pressure measurement; Vmean is the air bag volume corresponding to the maximum pulse amplitude of the current user; and Vend is the air bag volume at the end of the blood pressure measurement.

[0028] Furthermore, the steps of comparing the current user's current feature data and current arm circumference with the pre-stored target user's target feature data and target arm circumference to obtain the comparison results include:

[0029] Calculate the absolute value of the difference between the current user's current arm circumference and the pre-stored target arm circumference of the target user to obtain the first difference result;

[0030] If the first difference result meets the first preset threshold, calculate the absolute value of the difference between the current feature data of the current user and the target feature data of the pre-stored target user to obtain multiple second difference results.

[0031] Furthermore, based on the comparison results, the steps to determine whether the current user is the target user include:

[0032] If at least a first preset number of second difference results among multiple second difference results satisfy their respective second preset thresholds, then the current user is determined to be the target user.

[0033] If at least a second preset number of second difference results among multiple second difference results do not meet their respective second preset thresholds, it is determined that the current user is not the target user.

[0034] The present invention provides a user identification device, which is installed in a blood pressure monitor. The device includes:

[0035] The acquisition module is used to acquire and record the current user's current feature data and current arm circumference; wherein, the current feature data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum.

[0036] The comparison module is used to compare the current user's current feature data and current arm circumference with the pre-stored target user's target feature data and target arm circumference, and obtain the comparison results.

[0037] The judgment module is used to determine whether the current user is the target user based on the comparison result.

[0038] The present invention provides an electronic device, including a memory and a processor. The memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the steps of any of the above-mentioned methods.

[0039] The present invention provides a user identification method, device, and electronic device, comprising acquiring and recording the current characteristic data and current arm circumference of the current user; wherein the current characteristic data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum; comparing the current user's current characteristic data and current arm circumference with pre-stored target characteristic data and target arm circumference of a target user, respectively, to obtain comparison results; and determining whether the current user is a target user based on the comparison results of the current user's current characteristic data and current arm circumference with pre-stored target characteristic data and target arm circumference of a target user. This method can identify non-target users, thereby improving the reliability of long-term blood pressure monitoring and management for individual target users. Attached Figure Description

[0040] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1 A flowchart of a user identification method provided in an embodiment of the present invention;

[0042] Figure 2 A flowchart of another user identification method provided in an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of an air bag pressure value sequence provided in an embodiment of the present invention;

[0044] Figure 4 This is a schematic diagram of a series of air pressure pulsations provided in an embodiment of the present invention;

[0045] Figure 5 A schematic diagram of the original envelope and the smoothed envelope provided in an embodiment of the present invention;

[0046] Figure 6 This is a schematic diagram of current feature data provided in an embodiment of the present invention;

[0047] Figure 7A schematic diagram illustrating the relationship between the air output of an air pump per unit time, the effective voltage obtained by the air pump, and the air pressure in the air bag, provided for an embodiment of the present invention.

[0048] Figure 8 This is a schematic diagram illustrating the relationship between the volume of gas inside an air bag when converted to one atmosphere and the current air bag volume sequence, provided by an embodiment of the present invention.

[0049] Figure 9 A schematic diagram illustrating the quantity and distribution of clinical data used in formula coefficient calibration, provided for an embodiment of the present invention;

[0050] Figure 10 A schematic diagram of a user identification process provided in an embodiment of the present invention;

[0051] Figure 11 This is a schematic diagram of the structure of a user identification device provided in an embodiment of the present invention;

[0052] Figure 12 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0053] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Currently, commonly used oscillometric electronic blood pressure monitors calculate a person's blood pressure (systolic / diastolic) by adjusting the air pressure inside the air bag and collecting data on changes in internal pressure. However, if the same blood pressure monitor is used multiple times by different users, it does not differentiate between the data from each user. Therefore, when conducting long-term blood pressure monitoring / chronic disease management for a single target user, it may be affected by measurement data from non-target users, thus reducing the reliability of long-term blood pressure monitoring and management for a single target user.

[0055] To facilitate understanding of this embodiment, a user identification method disclosed in this invention will first be described in detail. This method is applied to a blood pressure monitor, such as... Figure 1 As shown, the method includes the following steps:

[0056] Step S102: Obtain and record the current user's current feature data and current arm circumference; wherein, the current feature data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum.

[0057] The maximum pulse amplitude mentioned above can be understood as the maximum amplitude of air pressure pulsation; the first-order difference maximum and minimum can be understood as the maximum and minimum values ​​obtained by pairwise difference of the air pressure value sequence of the air bag collected by the sensor during the blood pressure measurement process.

[0058] In practice, by controlling components such as the air pump and valve of the sphygmomanometer, the air bag can be inflated / deflated, causing changes in the amount of air inside the bag, which in turn leads to changes in the air pressure (the pressure change caused by inflation / deflation is called the basal pressure change). When the blood vessels in the coiled part of the body are compressed by the air bag, the pulsation of the blood vessels also causes changes in the air pressure inside the bag (the pressure change caused by vascular pulsation is called pressure pulsation). Furthermore, when the basal pressure changes, the degree of compression of the blood vessels by the air bag also changes, and the amplitude of the pressure pulsation also changes. After collecting the pressure pulsation sequence, the systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maxima, and first-order difference minima of the subject (current user) are calculated based on its envelope characteristics. Based on the relationship between the air pump output, changes in air bag pressure, and changes in air bag volume, the subject's arm circumference can be estimated.

[0059] The part of the human body that is wrapped can be the upper arm or the wrist; correspondingly, the air bag can also be a cuff or a wristband, and the arm circumference can also be the arm circumference or the wrist circumference.

[0060] Step S104: Compare the current feature data and current arm circumference of the current user with the target feature data and target arm circumference of the target user stored in advance to obtain the comparison results.

[0061] The target users mentioned above can be understood as individual users who need long-term blood pressure monitoring and management.

[0062] In the specific implementation process, when it is necessary to conduct long-term blood pressure monitoring and chronic disease management for a single target user, the target characteristic data and target arm circumference of the target user can usually be obtained and recorded through a blood pressure monitor. For example, when the blood pressure monitor measures the target user for the first time, the characteristic data and arm circumference obtained from the first measurement can be determined as the target characteristic data and target arm circumference, and then the target characteristic data and target arm circumference can be stored in the blood pressure monitor. Then, the current characteristic data and current arm circumference of the current user obtained through step S102 can be compared with the target characteristic data and target arm circumference to obtain the comparison results.

[0063] Step S106: Based on the comparison results, determine whether the current user is the target user.

[0064] In the specific implementation process, after storing the target feature data and target arm circumference in the blood pressure monitor, when the blood pressure monitor is used for measurement, the measurement object may be the target user or a non-target user (i.e., other users besides the target user). Therefore, in order to determine whether it is multiple measurements to the same user (target user) or multiple measurements to different users (target user and non-target user), the current arm circumference and current feature data obtained and recorded after each measurement of the same blood pressure monitor can be compared with the target feature data and target arm circumference previously stored in the blood pressure monitor.

[0065] If the difference between the current user's arm circumference and the target arm circumference is within a preset range, and after subtracting the systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum from the corresponding target feature data to obtain multiple difference values, and a certain number of these differences are within the preset range, then the current user is considered a target user; otherwise, they are considered a non-target user.

[0066] Furthermore, if it is determined that the current user is not the target user, the current arm circumference and current characteristic data of the current user that have been acquired and recorded can be treated as invalid user data and discarded (not stored in the blood pressure monitor); if it is determined that the current user is the target user, the current arm circumference and current characteristic data of the current user that have been acquired and recorded can be treated as valid data and stored in the blood pressure monitor.

[0067] In practice, the current user's arm circumference is estimated based on the patterns of air pump output, air bag pressure changes, and air bag volume changes. In addition, the current characteristic data during the current user's measurement process is used to determine whether multiple measurements from the same blood pressure monitor belong to the same user, and invalid user (non-target user) data is excluded, so as to conduct long-term blood pressure monitoring and management for a single valid user (target user).

[0068] The aforementioned user identification method includes acquiring and recording the current user's current characteristic data and current arm circumference; wherein the current characteristic data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maxima, and first-order difference minima; comparing the current user's current characteristic data and current arm circumference with pre-stored target user's target characteristic data and target arm circumference to obtain comparison results; and determining whether the current user is a target user based on the comparison results between the current user's current characteristic data and current arm circumference and pre-stored target user's target characteristic data and target arm circumference. This method can identify non-target users, thereby improving the reliability of long-term blood pressure monitoring and management for individual target users.

[0069] This invention also provides another user identification method, which is implemented based on the method in the above embodiments; the blood pressure monitor includes an air pump and an air bag, such as... Figure 2 As shown, the method includes the following steps:

[0070] Step S202: Obtain the air pressure value sequence of the air bag.

[0071] The above air bag pressure value sequence includes a baseline pressure sequence (containing all baseline pressures during the measurement process) and a pressure pulsation sequence (containing all pressure pulsations during the measurement process).

[0072] In the specific implementation process, the air bag can be inflated / deflated by controlling components such as the air pump and air valve. There are two methods for inflating / deflating the air bag: one is rapid inflation followed by gradual deflation, with the pressure pulsation series collected during the gradual deflation process; the other is gradual inflation followed by rapid deflation, with the pressure pulsation sequence collected during the gradual inflation process. Regardless of whether inflation or deflation is used, the abscissa of the envelope is the baseline pressure, and the envelopes generated by the two measurement methods are consistent.

[0073] In practical implementation, taking inflation-based measurement as an example, the air pressure value inside the air bag is first continuously collected during the inflation process to obtain an air bag pressure value sequence, such as... Figure 3 As shown, Figure 3 The horizontal axis represents the sampling points, with 64 points corresponding to 1 second, and the vertical axis represents the air pressure, in mmHg.

[0074] Step S204: Filter the air bag pressure value sequence to obtain the pressure pulsation sequence.

[0075] After executing step S202, all air bag pressure values ​​(air bag pressure value sequence) collected during the inflation process can be high-pass filtered to obtain a pressure pulsation series (the pressure pulsation series includes pressure pulsations in all air bag pressure values), such as... Figure 4 As shown, Figure 4 The horizontal axis represents the sampling points, with 64 points corresponding to 1 second, and the vertical axis represents the air pressure, in mmHg.

[0076] Step S206: Generate an envelope based on the pressure pulsation sequence.

[0077] The envelope mentioned above can be the original envelope or a smoothed envelope with dashed lines.

[0078] In the specific implementation process, after executing step S204, the amplitudes corresponding to all pressure pulsations in the pressure pulsation sequence can be used as the ordinate, and the base pressures corresponding to all pressure pulsations in the pressure pulsation sequence can be used as the abscissa. Then, the original envelope can be generated. Afterward, the original envelope can be smoothed to obtain a smoothed envelope, such as... Figure 5 The diagram shows a raw envelope and a smoothed envelope. Figure 5 The horizontal axis represents the base pressure corresponding to the pressure pulsation, in mmHg, and the vertical axis represents the amplitude of the pressure pulsation, in mmHg. The solid line is the original envelope, and the dashed line is the smoothed envelope.

[0079] Step S208: Based on the envelope and air bag pressure value sequence, obtain the current feature data of the current user.

[0080] In the specific implementation process, step S208 can be achieved through the following steps one to two:

[0081] Step 1: Based on the envelope, obtain the current user's systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, and maximum pulse amplitude.

[0082] In practice, the maximum value of the envelope (maximum value on the ordinate) can be identified as the maximum amplitude of the pressure pulsation. Multiplying this maximum value by the diastolic pressure coefficient yields the amplitude of the pressure pulsation corresponding to the diastolic pressure. The point to the left of the envelope that equals this amplitude is the diastolic pressure, and its corresponding abscissa (baseline pressure). Similarly, multiplying the maximum value of the envelope by the systolic pressure coefficient yields the amplitude of the pressure pulsation corresponding to the systolic pressure. The point to the right of the envelope that equals this amplitude is the systolic pressure, and its corresponding baseline pressure is the systolic pressure.

[0083] The x-axis corresponding to the maximum value of the envelope (maximum value on the ordinate) is the mean pressure. Within the envelope, the amplitude of each pressure pulsation corresponds to one pressure pulsation, which in turn corresponds to one pulse beat of the subject. The duration of these pressure pulsations can be determined by... Figure 4 The x-axis is transformed to obtain the number of pulse beats per unit time (60s), thus determining the heart rate. For example, the amplitude of 40 barometric pulsations in the envelope (equivalent to...) Figure 4 If there are 40 pressure pulses (within 30 seconds), then in 60 seconds that is, there are 80 pulse beats, or a heart rate of 80 beats per minute.

[0084] like Figure 6 The diagram shown is a schematic representation of current feature data. Figure 6The horizontal axis represents the base pressure corresponding to the pressure pulsation, in mmHg, and the vertical axis represents the amplitude of the pressure pulsation, in mmHg. The black curve is a smoothed envelope.

[0085] Step 2: Subtract each two adjacent air pressure values ​​in the air bag pressure value sequence to obtain multiple difference results; among the multiple difference results, the largest difference result is the first-order difference maximum value and the smallest difference result is the first-order difference minimum value.

[0086] In the specific implementation process, each sampling point corresponds to an air bag pressure value. Therefore, the air bag pressure value sequence contains the air bag pressure values ​​corresponding to all sampling points during the measurement process. Following the order of the sampling points, the air bag pressure values ​​corresponding to every two consecutive sampling points are compared to obtain multiple difference results. For example, in the air bag pressure value sequence, there are air bag pressure values ​​from four sampling points: the first sampling point has an air bag pressure of 1.0 mmHg, the second has 1.3 mmHg, the third has 1.8 mmHg, and the fourth has 2.5 mmHg. Therefore, the air bag pressure value corresponding to the first sampling point... The pressure value is calculated by comparing it with the air bag pressure value at the second sampling point. The first difference is 0.3 mmHg. The difference between the air bag pressure values ​​at the second and third sampling points is calculated, resulting in a second difference of 0.5 mmHg. The difference between the air bag pressure values ​​at the third and fourth sampling points is calculated, resulting in a third difference of 0.7 mmHg. The largest difference among these three results is taken as the first-order finite maximum, and the smallest difference is taken as the first-order finite minimum. That is, the first-order finite maximum is 0.7 mmHg, and the first-order finite minimum is 0.3 mmHg.

[0087] Step S210: Record the current feature data.

[0088] Step S212: Based on the current air pump drive command sequence, obtain the current air pump output sequence and the current air bag volume sequence.

[0089] In the specific implementation process, the air output of the air pump per unit time is positively correlated with the driving voltage of the air pump and negatively correlated with the pressure inside the air bag. The calculation method of the current air output sequence of the air pump can be one of the following two methods, one of which is formula (1):

[0090] Og=U*(a1*Pr + b1) / (Pr + c1) (1)

[0091] In formula (1): Og is the air output volume of the air pump per unit time (equivalent to the current air output volume sequence of the air pump mentioned above), in ml / s; U is the effective voltage obtained by the air pump, in V; Pr is the air pressure of the container at the output end of the air pump (equivalent to the air pressure value sequence of the air bag mentioned above), in mmHg; a1, b1, and c1 are all coefficients; it should be noted that Og, U, and Pr are all column vectors with N rows, where N is the number of sampling points from the start of measurement to the end of measurement of the electronic blood pressure monitor.

[0092] The above values ​​are: a1 is the voltage / output volume coefficient, in ml / (s*V), with a range of [-1.4, 1.0]; b1 is the air pressure / output volume coefficient, in (ml*mmHg) / (s*V), with a range of [-1000, 1800]; c1 is the air pressure / output volume coefficient, in mmHg, with a range of [-200, 300].

[0093] The above U can be calculated based on the PWM command applied to the air pump by the firmware during the measurement process and the power supply voltage. The specific formula is formula (2):

[0094] U = Us*PWM / PWMmax (2)

[0095] In formula (2): U is the effective voltage obtained by the air pump, Us is the power supply voltage, and the unit is V; PWM is the PWM applied by the firmware (equivalent to the current air pump drive command sequence mentioned above), which is a column vector with N rows, dimensionless, and N is the number of sampling points from the start of measurement to the end of measurement of the electronic blood pressure monitor; PWMmax is the maximum value of the PWM applied by the firmware (equivalent to the maximum PWM in the current air pump drive command sequence mentioned above), dimensionless.

[0096] The firmware applies a PWM command to the air pump, typically a positive integer ranging from [0, 255]. Different PWM values ​​result in different effective drive voltages U. For example, if the power supply voltage is 6V, and the applied PWM value is 255, the effective drive voltage received by the air pump is 6V. If the applied PWM value is 100, the effective drive voltage received by the air pump is 100 / 255*6V. The higher the effective drive voltage received by the air pump, the higher the rotational speed and the greater the air output.

[0097] Another method for calculating the current air pump output sequence is formula (3):

[0098] Og = U*(a² - b²*Pr) (3)

[0099] In formula (3): Og is the air output volume of the air pump per unit time (equivalent to the current air output volume sequence of the air pump mentioned above), in ml / s; U is the effective voltage obtained by the air pump, in V; Pr is the air pressure of the container at the output end of the air pump (equivalent to the air pressure value sequence of the air bag mentioned above), in mmHg; a2 and b2 are both coefficients; it should be noted that Og, U and Pr are all column vectors with N rows, where N is the number of sampling points from the start of measurement to the end of measurement of the electronic blood pressure monitor.

[0100] In actual implementation, a2 is the voltage / output volume coefficient, with units of ml / (s*V) and a value range of [-4, 12]; b2 is the air pressure / output volume coefficient, with units of ml / (s*mmHg) and a value range of [-0.1, 0.3]. U in the above formula (3) can still be calculated according to formula (2).

[0101] The coefficients in formulas (1) and (2) need to be calibrated through air pump performance testing. Specifically, the performance testing scheme used can be:

[0102] Apply a fixed power supply voltage (U) to the air pump, connect the air pump outlet to a fixed 100ml cylinder, and collect the air pressure data sequence (Pr) during the process of air pressure in the cylinder from 0 to 300mmHg; the air pump power supply voltage (U) can be selected from 4.2V, 4.8V, 5.4V, and 6.0V.

[0103] The aforementioned air pressure sampling data sequences are all subjected to noise reduction processing, which can be achieved through low-pass filtering, weighted averaging of adjacent points, sliding window averaging, etc.; then, the pairs are subtracted to obtain the air pressure increment sequence (ΔV); and then, the air pump output sequence is obtained according to the following formula:

[0104] Og=△V*100*64*6 / 760 / U

[0105] Formula (1) can be calibrated as follows: Using the cftool fitting toolbox of MATLAB software, set the air pump output sequence Og to y, the air pressure data sequence Pr to x, and select Rational for the fitting model. The Numerator degree parameter and the Denominator degree parameter are both set to 1. This will give you the parameters of the air pump output formula (1). Preferably, the average value of the parameters fitted under each air pump power supply voltage can be used to obtain a more accurate result.

[0106] Formula (2) can be calibrated as follows:

[0107] a) Create a column vector of the same length as the air pressure sequence, with all elements being 1, denoted as x1;

[0108] b) Arrange the aforementioned column vector x1 and the air pressure data sequence Pr from left to right to form a matrix, namely [x1,Pr], denoted as X;

[0109] c) Let Y = Og / U, and fit P in the equation Y = X * Para. You can use the regress function in MATLAB software. Para is a column vector of length 2, and its elements correspond to the coefficients a2 and b2 in the second air pump output formula (3).

[0110] The fitting method described above is just one of them. Other methods can also be used, such as the polyfit function and cftool toolbox in MATLAB, as well as trend prediction / regression analysis functions in other software such as Excel.

[0111] It should be noted that if different models of air pumps are used, the formula for calculating the air output per unit time may change. That is, different models of air pumps can correspond to different formulas for calculating the air output per unit time. Therefore, this application does not limit the formula for calculating the air output per unit time of the air pump.

[0112] In the specific implementation process, the relationship between the air output of the aforementioned air pump per unit time, the effective voltage obtained by the air pump, and the air pressure in the container at the air pump output end (equivalent to the air pressure in the air bag) is as follows: Figure 7 As shown, Figure 7 The horizontal axis represents the air pressure inside the air bag, in mmHg, and the vertical axis represents the air output of the air pump per unit time, in ml / s.

[0113] In the specific implementation process, the gas volume inside the air bag included in the current air bag volume sequence is constantly changing. Before calculating the current air bag volume sequence, the volume Vatm of the gas inside the air bag converted to one atmosphere can be calculated first. The specific calculation formula for Vatm is formula (4):

[0114] Vatm = Mtril(N)*Og*ts (4)

[0115] In formula (4): Vatm is a column vector with N rows and one column, in ml; N is the number of sampling points; Mtril(N) is a lower triangular matrix; Og is the air output of the air pump per unit time, which is a column vector with N rows and one column, and can be calculated according to formula (2) or formula (3); ts is the sampling period, in s.

[0116] The specific calculation formula for Mtril(N) above is formula (5):

[0117]

[0118] After calculating Vatm, the current airbag volume sequence can be calculated according to formula (6). The specific formula (6) is as follows:

[0119] V = Vatm * Patm / Pr (6)

[0120] Where V is the constantly changing volume of the air bag (equivalent to the current air bag volume sequence mentioned above), which is a column vector with N rows and the unit is ml; Vatm is the volume of the gas in the air bag when converted to one atmosphere; Patm is a standard atmospheric pressure value, which is 760 mmHg; Pr is the air pressure value in the air bag, which is a column vector with N rows and the unit is mmHg.

[0121] In the specific implementation process, the relationship between Vatm (the volume of gas in the air bag converted to one atmosphere) and V (the current air bag volume sequence) is as follows: Figure 8 As shown, Figure 8 The horizontal axis represents the sampling points, with 64 points equaling 1 second. The vertical axis represents the air bag volume in ml. The solid line represents V, and the dashed line represents Vatm.

[0122] Step S214: Determine the current arm circumference of the current user based on the current air pump output sequence, the current air bag volume sequence, and the current user's maximum pulse amplitude;

[0123] In the specific implementation process, the user's arm circumference basically satisfies the following formula (7):

[0124] Cir = a3*Ogmean*ts + b3*Ogend*ts + c2*Vmean+ d*Vend (7)

[0125] In formula (7), Cir is the user's arm circumference in cm; a3, b3, c2, and d are coefficients in cm / ml; a3 ranges from -0.2 to 0.2; b3 ranges from -0.3 to 0.3; c2 ranges from -0.1 to 0.1; d ranges from -0.1 to 0.1; ts is the sampling period in seconds; Ogmean is the air output per unit time of the air pump corresponding to the maximum amplitude of the pulse wave (the maximum amplitude of the air pressure pulsation) (the air output per unit time of the air pump is the current air output of the air pump). The sequence contains: Ogend (air pump output volume in a sequence), in ml / s; Vmean (air bag volume), in ml / s; Vmean (air bag volume), in ml, ...

[0126] In actual implementation, the coefficients in the user arm circumference estimation formula (7) are all derived from the analysis and statistics of effective clinical test data. The more effective clinical data, the better. There are also requirements for the distribution of the test population. The wider the distribution of subject types / blood pressure levels, the better.

[0127] Preferably, the number of cases, distribution range, and testing methods of the clinical data conform to the requirements of ISO 81060:2013. The quantity and distribution of clinical data used in the calibration coefficients in this method are as follows: Figure 9 As shown:

[0128] When calibrating the coefficients in formula (7), you can first process... Figure 9 The following information from 255 clinical data points:

[0129] Calculate the pump output volume Ogmean when the pulse amplitude is at its maximum, and arrange all clinical data Ogmean*ts into a column vector, which is recorded as x1;

[0130] Calculate the air pump output volume Ogend at the end of the measurement, arrange all clinical data Ogend*ts into a column vector, and record it as x2;

[0131] Calculate the air bag volume Vmean when the pulse amplitude is at its maximum, arrange the Vmean of all clinical data into a column vector, and record it as x3.

[0132] Calculate the air bag volume Vend at the end of the measurement, arrange the Vend of all clinical data into a column vector, and record it as x4;

[0133] Arrange the aforementioned column vectors x1 to x4 from left to right to form a 255-row, 4-column matrix, namely [x1, x2, x3, x4], denoted as X;

[0134] Obtain arm circumference during the measurement process, arrange all clinical data arm circumferences into a column vector, and record it as Z;

[0135] Combined with the user's arm circumference sequence Z, Para in the equation Z = X * Para is fitted. Preferably, the regress function in the software MATLAB is used. P is a column vector of length 4, whose elements correspond to the coefficients a3, b3, c2, and d in the formula (7) for estimating the user's arm circumference.

[0136] The fitting method described above is just one of them. Other methods can also be used, such as the polyfit function and cftool toolbox in MATLAB, as well as trend prediction / regression analysis functions in other software such as Excel.

[0137] Step S216: Record the current arm circumference.

[0138] Step S218: Calculate the absolute value of the difference between the current arm circumference of the current user and the target arm circumference of the pre-stored target user to obtain the first difference result.

[0139] In the specific implementation process, after obtaining the current user's arm circumference (Cir) through step S214, the difference between the current user's current arm circumference and the target user's target arm circumference can be calculated, and then the absolute value of the difference is taken (equivalent to the first difference result mentioned above).

[0140] Step S220: If the first difference result satisfies the first preset threshold, calculate the absolute value of the difference between the current feature data of the current user and the target feature data of the pre-stored target user to obtain multiple second difference results.

[0141] In the specific implementation process, the range of the first preset threshold can be set in advance according to actual needs, with the unit being cm, such as [0,3], [3,5], etc. Assuming that the range of the first preset threshold is [1,3], if the first difference result is within this range, such as 0, 1, 2, 3, then the first preset threshold is satisfied; if the first difference result is 4, 5, etc., then the first preset threshold is not satisfied.

[0142] If the first difference result does not meet the first preset threshold, the current user is directly considered to be a non-target user. If the first difference result meets the first preset threshold, the current user may be a target user or a non-target user. To make a further judgment, the absolute value of the difference between the current feature data of the current user and the target feature data of the pre-stored target user can be calculated to obtain multiple second difference results.

[0143] In the specific implementation process, the following data can be subtracted from the systolic blood pressure included in the current feature data and the systolic blood pressure included in the target feature data, the systolic and diastolic blood pressure included in the current feature data and the diastolic blood pressure included in the target feature data, the heart rate included in the current feature data and the heart rate included in the target feature data, the mean blood pressure included in the current feature data and the mean blood pressure included in the target feature data, the maximum pulse amplitude included in the current feature data and the maximum pulse amplitude included in the target feature data, the first-order difference maxima included in the current feature data and the first-order difference maxima included in the target feature data, and the first-order difference minima included in the current feature data and the first-order difference minima included in the target feature data, respectively, to obtain 7 difference values. Then, the absolute value of each difference value is taken to obtain 7 second difference results.

[0144] Step S222: If at least a first preset number of second difference results among multiple second difference results satisfy their respective second preset thresholds, determine that the current user is the target user.

[0145] In the specific implementation process, the second preset threshold unit corresponding to the first difference result (absolute value of diastolic blood pressure difference) is mmHg, with a value range of [5, 30]; the second preset threshold unit corresponding to the second difference result (absolute value of systolic blood pressure difference) is mmHg, with a value range of [5, 30]; the second preset threshold unit corresponding to the third difference result (absolute value of heart rate difference) is bpm, with a value range of [5, 20]; and the second preset threshold unit corresponding to the fourth difference result (absolute value of mean blood pressure difference) is mmHg, with a value range of [5, 30]. The range is [5, 30]; the second preset threshold unit corresponding to the fifth difference result (the absolute value of the difference in maximum pulse amplitude) is mmHg, and the value range is [0.5, 3]; the second preset threshold unit corresponding to the sixth difference result (the absolute value of the difference in the maximum value of the first difference) is mmHg, and the value range is [0.1, 2.5]; the second preset threshold unit corresponding to the seventh difference result (the absolute value of the difference in the minimum value of the first difference) is mmHg, and the value range is [0.1, 2.5].

[0146] If at least a first preset number (which can be set to 3) of these seven second difference results satisfy their respective second preset thresholds (within the range of the second preset threshold), then the current user is determined to be the target user.

[0147] Step S224: If at least a second preset number of second difference results among multiple second difference results do not meet their respective second preset thresholds, determine that the current user is not the target user.

[0148] If at least a second preset number (which can be set to 5) of the seven second difference results do not meet their respective second preset thresholds (exceeding the range of values ​​of the second preset threshold), then the current user is determined to be a non-target user.

[0149] Specifically, seven conditions can be set: a) The absolute value of the difference in systolic blood pressure does not exceed a certain threshold, which is in mmHg and ranges from [5,30]; b) The absolute value of the difference in diastolic blood pressure does not exceed a certain threshold, which is in mmHg and ranges from [5,30]; c) The absolute value of the difference in heart rate does not exceed a certain threshold, which is in bpm and ranges from [5,20]; d) The absolute value of the difference in mean blood pressure does not exceed a certain threshold, which is in mmHg and ranges from [5,30]; e) The absolute value of the difference in maximum pulse amplitude does not exceed a certain threshold, which is in mmHg and ranges from [0.5,3]; f) The absolute value of the difference in the first-order difference maxima does not exceed a certain threshold, which is in mmHg and ranges from [0.1,2.5]; g) The absolute value of the difference in the first-order difference minima does not exceed a certain threshold, which is in mmHg and ranges from [0.1,2.5].

[0150] If at least five of the seven conditions mentioned above are not met, it is determined that different users used the same blood pressure monitor for measurement.

[0151] The user identification method described above identifies non-target users and target users by roughly estimating the current user's current arm circumference and combining it with other current characteristics of the current user. This improves the reliability of long-term blood pressure monitoring and management for individual target users.

[0152] To better understand the above embodiments, this application provides a schematic diagram of a user identification process, such as... Figure 10 As shown, taking inflatable measurement as an example, Figure 10 The process includes the following steps:

[0153] Step ST1 involves continuously collecting the air pressure value sequence inside the air bag during the inflation process.

[0154] In the collected air pressure value sequence, there are superimposed air pressure pulsations with constantly changing amplitudes on top of the continuously stable base air pressure.

[0155] Step ST2: Extract the air pressure pulsation sequence from the air pressure value sequence collected in step ST1.

[0156] Specific methods could include filtering the air pressure value sequence, such as high-pass filtering, band-pass filtering, and moving average filtering.

[0157] Step ST3: Generate the envelope based on the pressure pulsation sequence obtained in step ST2.

[0158] A specific method could be to identify the amplitude of each pressure pulsation in the pressure pulsation sequence, and generate an envelope with the amplitude of all pressure pulsations as the vertical axis and their corresponding baseline pressure as the horizontal axis. Then (preferably), the envelope is smoothed. The smoothing method could be multi-point weighted averaging, Fourier transform, and inverse transform.

[0159] Step ST4: Calculate the feature data during the user measurement process.

[0160] The characteristic data may include systolic blood pressure, diastolic blood pressure, heart rate, mean pressure, maximum pulse amplitude, first-order difference maximum and first-order difference minimum. The first five items can be obtained from the envelope generated in step ST3, while the latter two items can be obtained by finding the extreme values ​​of the pairwise differences of the air pressure value sequence.

[0161] Step ST5: Collect the air pump drive command sequence.

[0162] Specifically, during the inflation process, the firmware applies a sequence of drive commands (PWM) to the air pump. This step is performed simultaneously with step ST1.

[0163] Step ST6: Calculate the air pump output sequence.

[0164] Specifically, the air pump drive command sequence PWM obtained in step ST5 can be substituted into formula (1) or formula (3) to calculate the air pump output sequence.

[0165] Step ST7: After obtaining the air pump output sequence according to step ST6, calculate the air bag volume sequence according to the corresponding formulas (4) to (6).

[0166] Step ST8: Based on the air pump output sequence obtained in Step ST6, the air bag volume sequence obtained in Step ST7, and the maximum value of the envelope obtained in Step ST4, calculate the following information:

[0167] The air output of the air pump corresponding to the maximum amplitude (maximum value of the envelope) of the pulse wave;

[0168] The air output of the air pump at the end of the measurement;

[0169] The volume of the air bag corresponding to the maximum amplitude of the pulse wave;

[0170] The volume of the air bag at the end of the measurement.

[0171] Then, by substituting the above information into formula (7), the user's arm circumference can be estimated.

[0172] Step ST9, User Identification.

[0173] Specifically, the user's arm circumference obtained in step ST8 can be combined with the characteristic data during the user's measurement process to determine whether multiple measurements taken by the same blood pressure monitor belong to the same user (target user).

[0174] This invention also provides a user identification device, which is installed on a blood pressure monitor, such as... Figure 11 As shown, the device includes: an acquisition module 100, used to acquire and record the current characteristic data and current arm circumference of the current user; wherein the current characteristic data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum; a comparison module 101, used to compare the current characteristic data and current arm circumference of the current user with the target characteristic data and target arm circumference of the target user stored in advance, respectively, and obtain a comparison result; and a judgment module 102, used to determine whether the current user is the target user based on the comparison result.

[0175] The aforementioned user identification device includes acquiring and recording the current user's current characteristic data and current arm circumference; wherein the current characteristic data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum; comparing the current user's current characteristic data and current arm circumference with pre-stored target user's target characteristic data and target arm circumference to obtain comparison results; and determining whether the current user is a target user based on the comparison results between the current user's current characteristic data and current arm circumference and pre-stored target user's target characteristic data and target arm circumference, this device can identify non-target users, thereby improving the reliability of long-term blood pressure monitoring and management for individual target users.

[0176] Furthermore, the blood pressure monitor includes an air pump and an air bag, and the acquisition module is also used for:

[0177] Obtain the sequence of air pressure values ​​for the air bag;

[0178] The air pressure value sequence of the air bag is filtered to obtain the air pressure pulsation sequence;

[0179] An envelope is generated based on a pressure pulsation sequence.

[0180] Based on the envelope and air bag pressure value sequence, obtain the current user's current feature data;

[0181] Record the current feature data.

[0182] Furthermore, the acquisition module is also used for:

[0183] Based on the envelope, obtain the current user's systolic blood pressure, diastolic blood pressure, heart rate, current mean blood pressure, and maximum pulse amplitude;

[0184] The difference between each two adjacent air pressure values ​​in the air bag pressure value sequence is processed to obtain multiple difference results; among the multiple difference results, the largest difference result is the first-order difference maximum value and the smallest difference result is the first-order difference minimum value.

[0185] Furthermore, the acquisition module is also used for:

[0186] Collect the current air pump drive command sequence;

[0187] Based on the current air pump drive command sequence, obtain the current air pump output sequence and the current air bag volume sequence.

[0188] Determine the current arm circumference of the current user based on the current air pump output sequence, the current air bag volume sequence, and the current user's maximum pulse amplitude.

[0189] Record your current arm circumference.

[0190] Furthermore, the acquisition module is also used for:

[0191] The current air output sequence of the air pump is obtained according to the formula Og=U*(a*Pr+b) / (Pr+c) or the formula Og=U*(ab*Pr); where U is the effective voltage of the air pump; Pr is the air pressure value sequence of the air bag; and a, b, and c are coefficients.

[0192] The current airbag volume sequence is obtained using the formula V = Vatm * Patm / Pr; where Patm is a standard atmospheric pressure value; Vatm is the volume of the gas inside the airbag converted to one atmosphere.

[0193] Furthermore, the acquisition module is also used for:

[0194] The current arm circumference of the current user is determined according to the formula Cir = a*Ogmean*ts + b*Ogend*ts + c*Vmean + d*Vend; where a, b, c, and d are coefficients; ts is the sampling period; Ogmean is the air volume output of the air pump corresponding to the current user's maximum pulse amplitude; Ogend is the air volume output of the air pump at the end of the blood pressure measurement; Vmean is the air bag volume corresponding to the current user's maximum pulse amplitude; and Vend is the air bag volume at the end of the blood pressure measurement.

[0195] Furthermore, the comparison results module:

[0196] Calculate the absolute value of the difference between the current user's current arm circumference and the pre-stored target arm circumference of the target user to obtain the first difference result;

[0197] If the first difference result meets the first preset threshold, calculate the absolute value of the difference between the current feature data of the current user and the target feature data of the pre-stored target user to obtain multiple second difference results.

[0198] Furthermore, the judgment module is also used for:

[0199] If at least a first preset number of second difference results among multiple second difference results satisfy their respective second preset thresholds, then the current user is determined to be the target user.

[0200] If at least a second preset number of second difference results among multiple second difference results do not meet their respective second preset thresholds, it is determined that the current user is not the target user.

[0201] The user identification device provided in this embodiment of the invention has the same implementation principle and technical effect as the aforementioned user identification method embodiment. For the user identification device embodiment, please refer to the corresponding content in the aforementioned user identification method embodiment.

[0202] This invention also provides an electronic device, see [link to relevant documentation]. Figure 12 As shown, the electronic device includes a processor 130 and a memory 131. The memory 131 stores machine-executable instructions that can be executed by the processor 130. The processor 130 executes the machine-executable instructions to implement the user identification method described above.

[0203] Furthermore, Figure 12 The electronic device shown also includes a bus 132 and a communication interface 133, with the processor 130, the communication interface 133 and the memory 131 connected via the bus 132.

[0204] The memory 131 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 133 (which can be wired or wireless), such as the Internet, wide area network, local area network, or metropolitan area network. The bus 132 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 12The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0205] Processor 130 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 130 or by instructions in software form. Processor 130 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 131, and processor 130 reads the information in memory 131 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0206] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A user identification method, characterized in that, Applied to a blood pressure monitor, the method includes: Acquire and record the current characteristic data and current arm circumference of the current user; wherein, the current characteristic data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum; The current user's current feature data and current arm circumference are compared with the pre-stored target user's target feature data and target arm circumference to obtain the comparison results; Based on the comparison results, it is determined whether the current user is the target user; The blood pressure monitor includes an air pump and an air bag. The steps for acquiring and recording the current user's current characteristic data include: Obtain the air pressure value sequence of the air bag; The air pressure value sequence of the air bag is filtered to obtain the air pressure pulsation sequence; An envelope is generated based on the aforementioned pressure pulsation sequence; Based on the envelope and the air bag pressure value sequence, obtain the current user's current feature data; Record the current feature data; The steps for obtaining the current user's current feature data based on the envelope and the air bag pressure value sequence include: Based on the envelope, obtain the current user's systolic blood pressure, diastolic blood pressure, heart rate, current mean blood pressure, and maximum pulse amplitude; The air pressure values ​​in the air bag pressure value sequence are subtracted to obtain multiple difference results; among the multiple difference results, the largest difference result is the first-order difference maximum and the smallest difference result is the first-order difference minimum.

2. The method according to claim 1, characterized in that, The steps to obtain and record the current user's current arm circumference include: Collect the current air pump drive command sequence of the air pump; Based on the current air pump drive command sequence, obtain the current air pump output sequence of the air pump and the current air bag volume sequence of the air bag; Based on the current air pump output sequence, the current air bag volume sequence, and the current user's maximum pulse amplitude, determine the current user's current arm circumference; Record the current arm circumference.

3. The method according to claim 2, characterized in that, The steps of obtaining the current air pump output sequence and the current air bag volume sequence based on the current air pump drive command sequence include: The current air output sequence of the air pump is obtained according to the formula Og = U*(a1*Pr + b1) / (Pr + c1) or the formula Og=U*(a2-b2*Pr); where U is the effective voltage of the air pump; Pr is the air pressure value sequence of the air bag; a1, b1, c 1、 a2 and b2 are both coefficients; The current air bag volume sequence is obtained according to the formula V=Vatm*Patm / Pr; where Patm is a standard atmospheric pressure value; Vatm is the volume of the gas in the air bag when converted to one atmosphere.

4. The method according to claim 2, characterized in that, The steps for determining the current arm circumference of the current user based on the current air pump output sequence, the current air bag volume sequence, and the current user's maximum pulse amplitude include: The current arm circumference of the current user is determined according to the formula Cir = a3*Ogmean*ts + b3*Ogend*ts + c2*Vmean + d*Vend; where a3, b3, c2, and d are coefficients; ts is the sampling period; Ogmean is the air volume output of the air pump corresponding to the maximum pulse amplitude of the current user; Ogend is the air volume output of the air pump at the end of the blood pressure measurement; Vmean is the air bag volume corresponding to the maximum pulse amplitude of the current user; and Vend is the air bag volume at the end of the blood pressure measurement.

5. The method according to claim 1, characterized in that, The steps of comparing the current user's current feature data and current arm circumference with the pre-stored target user's target feature data and target arm circumference to obtain the comparison results include: Calculate the absolute value of the difference between the current arm circumference of the current user and the target arm circumference of the pre-stored target user to obtain the first difference result; If the first difference result satisfies the first preset threshold, the absolute value of the difference between the current feature data of the current user and the target feature data of the pre-stored target user is calculated to obtain multiple second difference results.

6. The method according to claim 5, characterized in that, Based on the comparison result, the step of determining whether the current user is the target user includes: If at least a first preset number of the multiple second difference results satisfy their respective second preset thresholds, then the current user is determined to be the target user; If at least a second preset number of the second difference results among the multiple second difference results do not meet their respective second preset thresholds, it is determined that the current user is not the target user.

7. A user identification device, characterized in that, The device, which is installed in a blood pressure monitor, includes: The acquisition module is used to acquire and record the current characteristic data and current arm circumference of the current user; wherein, the current characteristic data includes at least: systolic blood pressure, diastolic blood pressure, heart rate, mean blood pressure, maximum pulse amplitude, first-order difference maximum, and first-order difference minimum. The comparison module is used to compare the current feature data and current arm circumference of the current user with the target feature data and target arm circumference of the target user stored in advance, and obtain the comparison result; The judgment module is used to determine whether the current user is the target user based on the comparison result; The blood pressure monitor includes an air pump and an air bag. The acquisition module is further configured to acquire the air bag pressure value sequence; filter the air bag pressure value sequence to obtain a pressure pulsation sequence; generate an envelope based on the pressure pulsation sequence; acquire the current user's current feature data based on the envelope and the air bag pressure value sequence; and record the current feature data. The acquisition module is further configured to acquire the current user's systolic blood pressure, diastolic blood pressure, heart rate, current mean blood pressure, and maximum pulse amplitude based on the envelope; and to perform difference processing on every two adjacent air pressure values ​​in the air bag pressure value sequence to obtain multiple difference results; wherein, among the multiple difference results, the largest difference result is the first-order difference maximum and the smallest difference result is the first-order difference minimum.

8. An electronic device, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program that can run on the processor, characterized in that the processor executes the computer program to implement the steps of the method described in any one of claims 1-6.

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