A method, device and equipment for acquiring lower limb hemodynamic parameters

Abstract

This application provides a method, apparatus, and device for acquiring lower limb hemodynamic parameters, relating to the field of non-invasive detection technology. The method includes: acquiring a first foot pulse wave sequence under a first pressurization mode, a second foot pulse wave sequence under a second pressurization mode, a third foot pulse wave sequence under a third pressurization mode, and a corresponding air pressure sequence for the user's lower limb blood vessels; analyzing the trend of the first foot pulse wave sequence to obtain the first hemodynamic parameter of the lower limb; analyzing the second foot pulse wave sequence to obtain the second hemodynamic parameter; analyzing the third foot pulse wave sequence to obtain a correction parameter; correcting the second hemodynamic parameter using the correction parameter; and obtaining the lower limb hemodynamic parameters based on the first hemodynamic parameter and the corrected second hemodynamic parameter. This application achieves non-invasive measurement of lower limb hemodynamic parameters and distinguishes between arterial and venous hemodynamic parameters.

Description

Technical Field

[0001] This application relates to the field of non-invasive detection technology, and more specifically, to a method, apparatus, and device for obtaining lower limb hemodynamic parameters. Background Technology

[0002] Existing methods for detecting vascular structure, function, and corresponding parameters mainly target arterial vessels, specifically the arterial vessels of the upper limbs. The results obtained can only reflect the condition of the upper limb arterial vessels. Currently, there is no technology for detecting the structure, function, and corresponding hemodynamic parameters of lower limb vessels.

[0003] Existing vascular detection methods are divided into invasive and non-invasive methods. Invasive methods are highly accurate, but they require invasive procedures, which can cause some damage to the body and leave wounds. Improper operation can lead to complications such as infection, thrombosis, and bleeding. Non-invasive methods have a low complication rate and are convenient to use, but they currently lack complete theoretical guidance, have low accuracy, and cannot effectively distinguish the vascular signal characteristics of arteries and veins. Summary of the Invention

[0004] The purpose of this application is to provide a method, apparatus, and device for acquiring lower limb hemodynamic parameters, which solves the problems of existing technologies that cannot detect lower limb hemodynamic parameters and cannot distinguish between arterial and venous hemodynamic parameters. It can use a PPG sensor to achieve non-invasive measurement of lower limb hemodynamic parameters and can distinguish between arterial and venous hemodynamic parameters.

[0005] Firstly, a method for obtaining lower limb hemodynamic parameters is provided, which may include:

[0006] For the user's lower limb blood vessels, a first foot pulse wave sequence under a first pressurization mode, a second foot pulse wave sequence under a second pressurization mode, a third foot pulse wave sequence under a third pressurization mode, and a corresponding air pressure sequence are acquired; wherein, the foot pulse wave sequence is formed by arranging the acquired foot pulse waves in chronological order; and the air pressure sequence is formed by arranging the acquired air pressures in chronological order.

[0007] A trend analysis of the first foot pulse wave sequence was performed to obtain the trend change analysis results of the first foot pulse wave sequence;

[0008] Extract the time corresponding to the trend change analysis results to obtain the first time parameter; extract the air pressure corresponding to the first time parameter from the air pressure sequence to obtain the first air pressure;

[0009] Based on the trend change analysis results of the first foot pulse wave sequence and the first air pressure, the first hemodynamic parameters of the lower limb are obtained;

[0010] Peak-to-peak value extraction is performed on the second foot pulse wave sequence; polynomial fitting analysis is performed on the extracted peak-to-peak value to obtain the polynomial fitting analysis results; the second foot pulse wave with the largest pulse wave value is extracted from the second foot pulse wave sequence.

[0011] Based on the second foot pulse wave with the largest pulse wave value and the polynomial fitting analysis results, the second hemodynamic parameters of the lower limb are obtained; wherein, the second hemodynamic parameters include the second venous hemodynamic parameters and the second arterial hemodynamic parameters;

[0012] The third foot pulse wave sequence was analyzed to obtain the first correction parameter and the second correction parameter;

[0013] The second arterial hemodynamic parameters are corrected using the first correction parameter and the second correction parameter to obtain the corrected second arterial hemodynamic parameters;

[0014] The lower limb hemodynamic parameters are obtained by combining the first hemodynamic parameter of the lower limb, the second venous hemodynamic parameter, and the modified second arterial hemodynamic parameter.

[0015] In an optional implementation, the first pressurization mode includes at least a first high-pressure duration phase;

[0016] A trend analysis was performed on the first foot pulse wave sequence to obtain the trend change analysis results of the first foot pulse wave sequence, including:

[0017] For any first foot pulse wave sequence during the first high-pressure sustained phase, a low-pass filter is applied to the first foot pulse wave sequence during the first high-pressure sustained phase to obtain a filtered first foot pulse wave sequence.

[0018] The changing trend of the filtered first foot pulse wave sequence is analyzed to obtain the initial trend change analysis results of the first foot pulse wave sequence during the first high pressure sustained phase.

[0019] The initial trend change analysis results of the first foot pulse wave sequences obtained in multiple first high pressure sustained phases were screened to obtain the trend change results of the first foot pulse wave sequences.

[0020] In an optional implementation, the foot pulse wave sequence is composed of multiple foot pulse wave sequence segments; each foot pulse wave sequence segment corresponds to a cardiac cycle; each foot pulse wave sequence segment includes a foot pulse wave sequence ascending segment and a foot pulse wave sequence descending segment.

[0021] Before acquiring the first foot pulse wave sequence under the first compression mode, the method further includes:

[0022] Acquire a resting foot pulse wave sequence; wherein the resting foot pulse wave sequence is formed by arranging foot pulse waves collected without applying pressure to the user's lower limbs in chronological order of acquisition time;

[0023] The resting foot pulse wave sequence is divided according to the cardiac cycle to obtain multiple resting foot pulse wave sequence segments;

[0024] For any segment of the resting foot pulse wave sequence, extract the maximum and minimum points of the rising segment of the resting foot pulse wave sequence; subtract the minimum point from the maximum point of the rising segment to obtain the peak-to-peak value of the rising segment.

[0025] Extract the maximum and minimum points of the descending segment of the resting foot pulse wave sequence; subtract the minimum point from the maximum point of the descending segment to obtain the peak-to-peak value of the descending segment;

[0026] Based on the peak-to-peak value of the rising segment and the peak-to-peak value of the falling segment, abnormal resting foot pulse wave sequence segments are removed to obtain multiple non-abnormal resting foot pulse wave sequence segments; wherein, the abnormal resting foot pulse wave sequence segments are resting foot pulse wave sequence segments whose peak-to-peak value of the rising segment excluding the peak-to-peak value of the falling segment does not meet the first threshold.

[0027] For any non-abnormal resting foot pulse wave sequence segment, calculate the average of the peak-to-peak value of the rising segment and the peak-to-peak value of the falling segment to obtain the peak-to-peak value of the non-abnormal resting foot pulse wave sequence segment.

[0028] Based on the peak-to-peak values ​​of the multiple non-abnormal resting foot pulse wave sequence segments, the average peak-to-peak value of all non-abnormal resting foot pulse wave sequence segments is calculated to obtain the user's average amplitude.

[0029] Determine the total duration and total number of all non-abnormal resting foot pulse wave sequence segments; based on the total duration and total number, obtain the user's heart rate.

[0030] In an optional implementation, the second pressurization mode includes a second depressurization phase;

[0031] Peak-to-peak value extraction is performed on the second foot pulse wave sequence; polynomial fitting analysis is then performed on the extracted peak-to-peak values ​​to obtain the polynomial fitting analysis results, including:

[0032] Extract the second foot pulse wave sequence during the second blood pressure reduction phase to obtain the second foot pulse wave sequence to be analyzed;

[0033] Differentiate the second foot pulse wave sequence to be analyzed to obtain the extreme points of the second foot pulse wave sequence to be analyzed;

[0034] Based on the user's heart rate, the user's average amplitude, and the extreme points of the second foot pulse wave sequence to be analyzed, the dicrotic notch in the second foot pulse wave sequence to be analyzed is removed to obtain the second foot pulse wave sequence to be fitted.

[0035] The second foot pulse wave sequence to be fitted is divided according to the cardiac cycle to obtain multiple second foot pulse wave sequence segments;

[0036] Calculate the peak-to-peak value of each segment of the second foot pulse wave sequence; fit the peak-to-peak value of all segments of the second foot pulse wave sequence to obtain the peak-to-peak value fitting curve of the second foot pulse wave sequence;

[0037] The zero point, maximum point, and stable point of the peak-to-peak fitting curve of the second foot pulse wave sequence are extracted as the polynomial fitting result.

[0038] In an optional implementation, based on the second foot pulse wave sequence with the largest pulse wave sequence value and the polynomial fitting analysis results, the second hemodynamic parameters of the lower limb are obtained, including:

[0039] The time corresponding to the zero point of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results is extracted to obtain the second time parameter;

[0040] The time corresponding to the maximum value of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results is extracted to obtain the third time parameter.

[0041] The fourth time parameter is obtained by extracting the time corresponding to the stable point of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results.

[0042] Extract the time corresponding to the second foot pulse wave sequence with the largest pulse wave sequence value to obtain the fifth time parameter;

[0043] The second arterial hemodynamic parameter is obtained by extracting the air pressure corresponding to the second time parameter and the air pressure corresponding to the third time parameter from the air pressure sequence.

[0044] The second venous hemodynamic parameter is obtained by extracting the air pressure corresponding to the fourth time parameter and the air pressure corresponding to the fifth time parameter from the air pressure sequence;

[0045] Based on the second arterial hemodynamic parameters and the second venous hemodynamic parameters, the second hemodynamic parameters of the user's lower limb are obtained.

[0046] In an optional implementation, the third pressurization mode includes at least two third high-pressure duration phases;

[0047] The third foot pulse wave sequence was analyzed to obtain the first correction parameter and the second correction parameter, including:

[0048] Extract the third foot pulse wave sequence for all third high-pressure sustained phases;

[0049] For any third foot pulse wave sequence during the third high pressure sustained phase, the derivative of the third foot pulse wave sequence during the third high pressure sustained phase is obtained to obtain the extreme points of the third foot pulse wave sequence to be analyzed.

[0050] Based on the user's heart rate, the user's average amplitude, and the extreme points of the third foot pulse wave sequence to be analyzed, remove the dicrotic notch from the third foot pulse wave sequence to be analyzed.

[0051] The third foot pulse wave sequence to be analyzed after removing the dicrotic notch is divided according to the cardiac cycle to obtain multiple third foot pulse wave sequence segments.

[0052] Calculate the peak-to-peak value of each third foot pulse wave sequence segment; based on the peak-to-peak value of each third foot pulse wave sequence segment, calculate the average peak-to-peak value of all third foot pulse wave sequence segments;

[0053] Arrange the average peak-to-peak values ​​of all the third foot pulse wave sequence segments in chronological order;

[0054] The sixth time parameter is obtained by selecting the time corresponding to the maximum value of the average of the peak-to-peak values ​​of all the segments of the third foot pulse wave sequence after arrangement.

[0055] The seventh time parameter is obtained by selecting the time corresponding to the first value that is 0 from the average value of the peak-to-peak values ​​of the third foot pulse wave sequence segment after the arrangement;

[0056] The pressure corresponding to the sixth time parameter is extracted from the pressure sequence to obtain the first correction parameter;

[0057] The pressure corresponding to the seventh time parameter is extracted from the pressure sequence to obtain the second correction parameter.

[0058] In an optional implementation, the second arterial hemodynamic parameter includes a second arterial pressure parameter and a second arterial characteristic parameter; wherein, the second arterial pressure parameter is the air pressure corresponding to the second time parameter; and the second arterial characteristic parameter is the air pressure corresponding to the third time parameter.

[0059] The second arterial hemodynamic parameters are corrected using the first correction parameter and the second correction parameter to obtain the corrected second arterial hemodynamic parameters, including:

[0060] The second arterial pressure parameter is corrected using the first correction parameter to obtain the corrected second arterial pressure parameter;

[0061] The second artery characteristic parameters are corrected using the second correction parameter to obtain the corrected second artery characteristic parameters;

[0062] Based on the corrected second arterial pressure parameters and the corrected second arterial characteristic parameters, the corrected second arterial hemodynamic parameters are obtained.

[0063] Secondly, a device for acquiring lower limb hemodynamic parameters is provided, the device may include:

[0064] The signal acquisition unit is used to acquire, for the user's lower limb blood vessels, a first foot pulse wave sequence under a first pressurization mode, a second foot pulse wave sequence under a second pressurization mode, a third foot pulse wave sequence under a third pressurization mode, and a corresponding air pressure sequence for the foot pulse wave sequences; wherein, the foot pulse wave sequence is formed by arranging the acquired foot pulse waves in chronological order of acquisition time; and the air pressure sequence is formed by arranging the acquired air pressures in chronological order of acquisition time.

[0065] The trend analysis unit is used to perform trend analysis on the first foot pulse wave sequence to obtain the trend change analysis result of the first foot pulse wave sequence; extract the time corresponding to the trend change analysis result to obtain the first time parameter; extract the air pressure corresponding to the first time parameter from the air pressure sequence to obtain the first air pressure; and obtain the first hemodynamic parameter of the lower limb based on the trend change analysis result of the first foot pulse wave sequence and the first air pressure.

[0066] The fitting analysis unit is used to extract peak-to-peak values ​​from the second foot pulse wave sequence; perform polynomial fitting analysis on the extracted peak-to-peak values ​​to obtain polynomial fitting analysis results; extract the second foot pulse wave with the largest pulse wave value from the second foot pulse wave sequence; and obtain the second hemodynamic parameters of the lower limb based on the second foot pulse wave with the largest pulse wave value and the polynomial fitting analysis results; wherein, the second hemodynamic parameters include second venous hemodynamic parameters and second arterial hemodynamic parameters;

[0067] The correction unit is used to analyze the third foot pulse wave sequence to obtain a first correction parameter and a second correction parameter; and to correct the second arterial hemodynamic parameters using the first correction parameter and the second correction parameter to obtain the corrected second arterial hemodynamic parameters.

[0068] The output unit is used to combine the first hemodynamic parameters of the lower limb, the second venous hemodynamic parameters, and the modified second arterial hemodynamic parameters to obtain the lower limb hemodynamic parameters.

[0069] Thirdly, an electronic device is provided, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0070] Memory, used to store computer programs;

[0071] When a processor executes a program stored in memory, it implements any of the steps described in the first aspect above.

[0072] Fourthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of any of the methods described in the first aspect above.

[0073] This application, based on the differences in vascular structure and blood volume between arteries and veins, as well as their varying stiffness and compliance, provides a method for acquiring lower limb hemodynamic parameters. This method achieves non-invasive acquisition of hemodynamic parameters of both lower limb arteries and veins, exhibiting excellent generalization ability and accuracy. By designing different pressure modes, this application effectively distinguishes the degree of collapse between arteries and veins, solving the problem of differentiating arteriovenous hemodynamic parameters. Furthermore, this application allows for correction of the obtained parameters through different pressure methods, improving the accuracy of the measured parameters. Attached Figure Description

[0074] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0075] Figure 1 A system architecture diagram for acquiring lower limb hemodynamic parameters provided in this application embodiment;

[0076] Figure 2 A flowchart illustrating a method for obtaining lower limb hemodynamic parameters provided in this application embodiment;

[0077] Figure 3 This application provides a foot pulse wave sequence processing method for an initial resting state, as described in an embodiment of the present application.

[0078] Figure 4 A flowchart illustrating a method for processing foot pulse waves acquired under a first pressurization mode, provided in an embodiment of this application;

[0079] Figure 5 A flowchart illustrating a method for processing foot pulse waves under a second pressurization mode, as provided in an embodiment of this application;

[0080] Figure 6 A flowchart illustrating a method for processing foot pulse waves under a third pressurization mode, provided in an embodiment of this application;

[0081] Figure 7 A schematic diagram of a device for acquiring lower limb hemodynamic parameters provided in an embodiment of this application;

[0082] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0083] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0084] The cardiac cycle refers to the process of the cardiovascular system from the start of one heartbeat to the start of the next; the cardiac cycle is determined by the heart rate.

[0085] A PPG sensor is a device that uses photoplethysmography (PPG) technology to detect human heart rate during exercise.

[0086] The dicrotic notch, a dicrotic wave on the descending limb of the pulse pressure waveform, originates in the early diastolic phase of the heart. When the aortic valve closes, blood in the artery attempts to return to the left ventricle, but is blocked by the aortic valve, creating the notch. The notch between the dicrotic wave and the descending limb of the pulse pressure waveform is called the descending isthmus (dicrotic notch), a marker of aortic valve closure. On the waveform, the diastolic phase occurs when the waveform declines and then rises again. The dicrotic notch is not always detectable, nor does it represent the end of the systolic phase in the entire cardiac cycle. The beginning of the descending limb signifies the end of the systolic phase. The dicrotic notch is not used to distinguish between the systolic and diastolic phases of the pulse pressure curve. It is only when the cardiac cycle is segmented using extreme values ​​that the presence of the dicrotic wave divides the diastolic phase into two segments. Removing the extreme values ​​of the dicrotic wave with smaller fluctuations allows identification of the start and end points of a complete cardiac cycle.

[0087] The method for obtaining lower limb hemodynamic parameters provided in this application embodiment can be applied to... Figure 1 In the system architecture shown, such as Figure 1 As shown, the system for acquiring lower limb hemodynamic parameters may include a host computer, a pressurization device, a cuff, and a PPG sensor; the host computer and the pressurization device are connected via a serial port; the PPG sensor and the pressurization device communicate via Bluetooth or other wireless communication methods; the pressurization device is also equipped with a pressure sensor, which is connected to the cuff through an air tube, and the pressure sensor is used to detect the pressure of the gas inside the cuff.

[0088] The host computer is used to control the pressurization mode and parameters and save relevant data. The host computer can include: a server in the enterprise's backend and terminals for enterprise employees. The server can be a physical server, a server cluster composed of multiple physical servers, or a distributed system. It can also be a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. Terminals can be user equipment (UE) such as mobile phones, smartphones, laptops, digital radio receivers, personal digital assistants (PDAs), and tablets (PADs), handheld devices, in-vehicle devices, wearable devices, computing devices, or other processing devices connected to a wireless modem, mobile stations (MS), and mobile terminals. Terminals and servers can be directly or indirectly connected via wired or wireless communication methods, which is not limited herein.

[0089] The pressurization device consists of an air valve, an air pump, a control chip, and a display; it is used to control the inflation and deflation process of the cuff.

[0090] A PPG sensor includes at least a light source and a photodetector. The light source is used to illuminate the ventral side of the big toe. The photodetector is used to acquire the pulse wave signal of the big toe. The pulse wave signals of the big toe acquired by the PPG sensor are arranged in chronological order to obtain a foot pulse wave sequence. The light source can be a light-emitting diode.

[0091] Specifically, such as Figure 1 As shown, the workflow of the lower limb hemodynamic parameter acquisition system is as follows: A cuff is wrapped around the user's calf, with the PPG sensor's light source facing the ventral side of the big toe; pressure parameters for different pressurization modes are set via a host computer; the pressurization device controls the pressurization mode to sequentially change from no pressurization to the first pressurization mode, the second pressurization mode, the third pressurization mode, and no pressurization. Simultaneously, during the pressurization mode changes, a pressure sensor within the pressurization device continuously monitors the gas pressure inside the cuff, and the photodetector of the PPG sensor continuously monitors the user's foot pulse wave signal; the pressure data detected by the pressure sensor is transmitted to the pressurization device via a wired connection, and the foot pulse wave signal detected by the PPG sensor is also transmitted to the pressurization device; the pressurization device transmits the pressurization mode (which includes pressurization parameters, and different pressurization modes can be represented by symbols), pressure data, foot pulse wave signal, and corresponding time signal to the host computer via serial communication. The host computer then analyzes and processes the signals and data to obtain the user's lower limb hemodynamic parameters.

[0092] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application. Furthermore, the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0093] Figure 2 This is a flowchart illustrating a method for obtaining lower limb hemodynamic parameters provided in an embodiment of this application. Figure 2 As shown, the method may include:

[0094] Step S210: For the user's lower limb blood vessels, obtain the resting foot pulse wave sequence when no pressure is applied, the first foot pulse wave sequence under the first pressure mode, the second foot pulse wave sequence under the second pressure mode, the third foot pulse wave sequence under the third pressure mode, and the air pressure sequence corresponding to the foot pulse wave sequence.

[0095] In this embodiment, due to the differences in vascular structure and blood volume between arteries and veins during calf compression, they exhibit varying degrees of stiffness and compliance. Consequently, the arteries and veins at the compression site will collapse to varying degrees. The pulse wave signal of the foot, being the distal end (i.e., the foot pulse wave signal), will show distinct characteristics compared to the resting state. These characteristics are significantly correlated with the hemodynamic parameters of the arteries and veins. Therefore, this application determines the hemodynamic parameters of the lower limbs by collecting foot pulse wave signals.

[0096] In this embodiment of the application, during a complete pressurization process, continuous sampling is performed at a sampling rate of 24Hz to obtain numerous foot pulse waves. All the collected foot pulse waves are arranged in the order of sampling time to obtain a complete foot pulse wave sequence during the pressurization process.

[0097] In this embodiment of the application, the foot pulse wave sequence is acquired during multiple consecutive cardiac cycles. Therefore, the foot pulse wave sequence can be divided into multiple segments according to the cardiac cycle. Since a cardiac cycle includes the process of the heart from contraction to relaxation, a cardiac cycle must include an ascending segment and a descending segment. The corresponding foot pulse wave sequence segments include an ascending segment and a descending segment.

[0098] In this embodiment of the application, a complete pressurization process is divided into 5 stages, which are in the following order: initial resting state, first pressurization mode, second pressurization mode, third pressurization mode, and final resting state; wherein, the initial resting state is the state in which no pressure is initially applied to the cuff wrapped around the user's calf; the final resting state is the state in which no pressure is applied to the cuff wrapped around the user's calf after the third pressurization mode.

[0099] Specifically, the pressure parameters for each pressurization mode in a complete pressurization process are as follows:

[0100] In the initial resting state, no pressure is applied to the cuff, and the pressure sensor detects that the gas pressure inside the cuff is 0 kPa; the entire initial resting state lasts for 1 minute.

[0101] The first pressurization mode lasts for a total of 1 minute and includes two pressurization cycles. Each pressurization cycle consists of four phases: a first low-pressure holding phase, a first pressurization phase, a first high-pressure sustaining phase, and a first depressurization phase. The low pressure of the first pressurization mode is 0 kPa, and the high pressure is 8-13 kPa (specific values ​​are determined based on individual user conditions). The pressure parameter of the first low-pressure holding phase is the same as the low pressure of the first pressurization mode, and the duration is 16 seconds. The first pressurization phase lasts for 0.5 seconds, during which the pressure increases from the low pressure of the first pressurization mode to the high pressure of the first pressurization mode. The pressure parameter of the first high-pressure sustaining phase is the same as the high pressure of the first pressurization mode, and the duration is 4 seconds, during which the pressure remains constant. The first depressurization phase lasts for 0.5 seconds, during which the pressure decreases from the high pressure of the first pressurization mode to the low pressure of the first pressurization mode.

[0102] Except for the first low-pressure holding phase of the second pressurization cycle in the first pressurization mode, which lasts for 16-32 seconds and differs from the first low-pressure holding phase of the first pressurization cycle, all other pressure parameters and durations of the two pressurization cycles in the first pressurization mode are consistent.

[0103] The second pressurization mode lasts approximately 100 seconds and includes four phases in sequence: the second pressurization phase, the second high-pressure phase, the second depressurization phase, and the second low-pressure holding phase. The second pressurization phase lasts 0.5 seconds, with the low pressure at 0 kPa and the high pressure at 26-32 kPa (specific values ​​depend on the individual user). The second pressurization phase increases the pressure from low to high. The pressure parameter of the second high-pressure phase is the same as the high pressure of the second pressurization mode. Once the high pressure of the second pressurization mode is reached, it is not maintained at the high pressure but immediately enters the second depressurization phase. The second depressurization phase lasts approximately 80 seconds, with the depressurization rate gradually decreasing from the high pressure of the second pressurization mode to the low pressure of the second pressurization mode. The pressure parameter of the second low-pressure holding phase is the same as the low pressure of the second pressurization mode, and the duration is 10-20 seconds (specific values ​​depend on the individual user).

[0104] The third pressurization mode is a stepped pressurization mode. The low pressure of the third pressurization mode is 0 kPa, and the high pressure is 26-32 kPa (the specific value is determined according to the individual user). The third pressurization mode consists of multiple third pressurization stages, multiple third high-pressure continuous stages, a third depressurization stage, and a third low-pressure holding stage. The pressurization time of each third pressurization stage is 0.1-1 s. Each third pressurization stage is followed by a third high-pressure continuous stage, and each third high-pressure continuous stage lasts for 4 s. The third pressurization stage and the third high-pressure continuous stage are repeated until the high pressure of the third pressurization mode is reached. When the high pressure of the third pressurization mode is reached, the third depressurization stage begins. The pressure of the third depressurization stage decreases from the high pressure of the third pressurization mode to the low pressure of the third pressurization mode, and the depressurization time is 0.5 s. When the pressure drops to the low pressure of the third pressurization mode, the third low-pressure continuous stage begins. The pressure parameters of the third low-pressure continuous stage are the same as the low pressure parameters of the third pressurization mode, and the duration is 60 s.

[0105] For example, if the user's third high-pressure is 30 kPa, the pressure increase time is 0.1 s, and the pressure increase rate is constant, assuming the pressure increase rate is 50 kPa / s, then the first third pressure increase stage increases the pressure to 5 kPa, and the first third high-pressure continuous stage lasts at 5 kPa for 4 s; the second third pressure increase stage increases the pressure to 10 kPa; the second third high-pressure continuous stage lasts at 10 kPa for 4 s before entering the next third pressure increase stage, until it reaches 30 kPa.

[0106] In each pressurization mode, the high pressure is determined based on each user's height, weight, and other physiological parameters.

[0107] In this embodiment, when changing the pressurization mode, a mode change flag signal is sent to the pressurization device; simultaneously, when changing a pressurization mode, a stage change flag signal is also sent to the pressurization device. The sequence between any two flag signals is determined based on the received flag signals to identify the specific pressurization mode and stage of the foot pulse wave sequence. For example, assuming the initial resting state flag signal is 0, the first pressurization mode flag signal is 1, and the flag signals for the first low-pressure holding stage, the first pressurization stage, the first high-pressure sustaining stage, and the first depressurization stage are 11, 12, 13, and 14 respectively; then, when the initial resting state begins and ends, flag signal 0 is sent to the pressurization device; when entering the first pressurization mode, flag signal 1 and the first low-pressure holding stage signal 11 are sent to the pressurization device; when the first low-pressure holding stage ends, flag signal 11 and the first pressurization stage flag signal 12 are sent to the pressurization device, and so on. When processing signals from a specific stage within a specific mode is required, only the foot pulse waves between the corresponding flag signals need to be extracted.

[0108] In this embodiment, the foot pulse wave sequence at the initial resting state, the first high-pressure sustained phase of the first pressurization mode, the second depressurization phase of the second pressurization mode, and the foot pulse wave sequences of multiple third high-pressure sustained phases in the third pressurization mode are extracted for subsequent analysis and processing to determine the time parameters at specific points. Based on the time parameters at specific points, the corresponding pressure data are extracted from the pressure sequence collected by the barometer to obtain the corresponding hemodynamic parameters.

[0109] In the embodiments of this application, before analyzing the extracted foot pulse wave sequences, it is necessary to remove the dicrotic notch segment and the rapid fluctuation segment of each foot pulse wave sequence.

[0110] Specifically, removing the dicrotic notch segment includes the following steps: generating a waveform based on the foot pulse wave sequence; analyzing the obtained multiple maxima and minima in conjunction with the waveform; if the horizontal axis between any maxima and minima is less than one-sixth of the number of samples in the resting cardiac cycle, and the vertical axis between the maxima and minima is less than one-quarter of the user's average amplitude, then the maxima and minima are determined to be the maxima and minima of the dicrotic notch segment; deleting the second foot pulse wave signal from the minima to the maxima of the dicrotic notch segment from the foot pulse wave sequence, thus obtaining a process of cardiac activity from nothing to something. The number of samples for the resting cardiac cycle is calculated from the user's heart rate. For example, if the user's heart rate is 90 beats per second, then the user's heart beats 1.5 (90 / 60) times per second, and the duration of one cardiac cycle is 0.75 seconds. With a sampling rate of 24Hz (i.e., 24 signals are collected per second), 18 foot pulse wave data points will be collected in 0.75 seconds, meaning that 18 foot pulse wave data points will be collected within one cardiac cycle.

[0111] Specifically, removing rapid fluctuation segments involves the following steps: If the number of sampling points within any cardiac cycle is less than one-third of the number of sampling points in a resting cardiac cycle, then that period is considered a rapid fluctuation segment. For example, if a user's heart rate is 90 beats per minute, then the user's heart beats 1.5 (90 / 60) times per second, and one cardiac cycle lasts 0.75 seconds. With a sampling rate of 24Hz (i.e., 24 signals are collected per second), 18 foot pulse wave data points will be collected in 0.75 seconds. If only one foot pulse wave data point is collected within any 0.75-second period in the foot pulse wave sequence, then that 0.75-second period is considered a rapid fluctuation segment and needs to be removed.

[0112] Step S220: Perform trend analysis on the first foot pulse wave sequence to obtain the trend change analysis results of the first foot pulse wave sequence; extract the time corresponding to the trend change analysis results to obtain the first time parameter; extract the air pressure corresponding to the first time parameter from the air pressure sequence to obtain the first air pressure; based on the trend change analysis results of the first foot pulse wave sequence and the first air pressure, obtain the first hemodynamic parameters of the lower limb.

[0113] In this embodiment of the application, before performing trend analysis on the first foot pulse wave sequence, it is necessary to analyze the foot pulse wave sequence in the initial resting state to determine the user's average amplitude and heart rate.

[0114] In this embodiment of the application, analyzing the foot pulse wave sequence at the initial resting state to determine the user's average amplitude and heart rate may include the following steps:

[0115] Obtain the resting foot pulse wave sequence; divide the resting foot pulse wave sequence according to the cardiac cycle to obtain multiple resting foot pulse wave sequence segments; for any resting foot pulse wave sequence segment, extract the maximum and minimum points of the rising segment of the resting foot pulse wave sequence; subtract the minimum point from the maximum point of the rising segment to obtain the peak-to-peak value of the rising segment;

[0116] Extract the maximum and minimum points of the descending segment of the resting foot pulse wave sequence; subtract the minimum point from the maximum point of the descending segment to obtain the peak-to-peak value of the descending segment; based on the peak-to-peak value of the ascending segment and the peak-to-peak value of the descending segment, remove abnormal resting foot pulse wave sequence segments to obtain multiple non-abnormal resting foot pulse wave sequence segments.

[0117] For any non-abnormal resting foot pulse wave sequence segment, calculate the average of the peak-to-peak value of the rising segment and the peak-to-peak value of the falling segment to obtain the peak-to-peak value of the non-abnormal resting foot pulse wave sequence segment; based on the peak-to-peak values ​​of multiple non-abnormal resting foot pulse wave sequence segments, calculate the average peak-to-peak value of all non-abnormal resting foot pulse wave sequence segments to obtain the user's average amplitude; determine the total duration and total number of all non-abnormal resting foot pulse wave sequence segments; based on the total duration and total number, obtain the user's heart rate.

[0118] In this embodiment, an abnormal resting foot pulse wave sequence segment is a resting foot pulse wave sequence segment in which the ratio of the peak-to-peak value of the ascending segment to the peak-to-peak value of the descending segment does not meet a first threshold; specifically, the first threshold can be in the range of 1 / 4 to 4. That is, cardiac cycles in which the ratio of the peak-to-peak value of the ascending segment to the peak-to-peak value of the descending segment is not in the range of 1 / 4 to 4 are determined to be abnormal cardiac cycles, and the foot pulse wave sequence segment corresponding to the abnormal cardiac cycle is an abnormal segment.

[0119] In one embodiment of this application, such as Figure 3 As shown, the processing of the foot pulse wave sequence in the initial resting state may include the following steps: extracting the maximum and minimum points of the PPG (foot pulse wave sequence); extracting all cardiac cycles of the foot pulse wave sequence based on the maximum and minimum points; obtaining the peak-to-peak value of the rising segment of the cardiac cycle by subtracting the minimum point of the rising segment of the foot pulse wave sequence from the maximum point of the rising segment of the cardiac cycle; obtaining the peak-to-peak value of the falling segment of the cardiac cycle by subtracting the minimum point of the falling segment of the foot pulse wave sequence from the maximum point of the falling segment of the cardiac cycle; and obtaining the peak-to-peak value of a cardiac cycle by averaging the peak-to-peak values ​​of the rising and falling segments.

[0120] If the ratio of the peak-to-peak value of the rising segment to the peak-to-peak value of the falling segment in any cardiac cycle is not within the range of 1 / 4 to 4, then the cardiac cycle is determined to be an abnormal cycle. Foot pulse wave sequences from abnormal cycles are removed, resulting in multiple foot pulse wave sequences for normal cardiac cycles. Based on the peak-to-peak values ​​of the foot pulse wave sequences from multiple normal cardiac cycles, the average peak-to-peak value of all normal cardiac cycle foot pulse wave sequences is calculated to obtain the user's average amplitude. The time axis of all normal cardiac cycles is extracted to determine the total duration and number of all normal cardiac cycles. The user's heart rate is obtained by dividing the total duration of normal cardiac cycles by the total number of normal cardiac cycles.

[0121] In this embodiment of the application, a trend analysis of the first foot pulse wave sequence is performed to obtain the trend change analysis results of the first foot pulse wave sequence, including:

[0122] For any first foot pulse wave sequence during the first high pressure duration phase, a low-pass filter is applied to the first foot pulse wave sequence during the first high pressure duration phase to obtain the filtered first foot pulse wave sequence.

[0123] The changing trend of the filtered first foot pulse wave sequence was analyzed to obtain the initial trend change analysis results of the first foot pulse wave sequence during the first high pressure sustained stage; the initial trend change analysis results of the first foot pulse wave sequence during the first high pressure sustained stage were screened to obtain the trend change results of the first foot pulse wave sequence.

[0124] In this embodiment, the first air pressure is obtained by collecting the air pressure in the cuff using an air pressure sensor in the pressurization device. That is, the first hemodynamic parameters of the lower limb include the trend change results of the first foot pulse wave sequence and the pressure data collected by the air pressure sensor under the corresponding trend change first time parameter; it is not the low pressure or high pressure value in the preset first pressurization mode directly obtained.

[0125] In one embodiment of this application, such as Figure 4 As shown, the processing of the foot pulse wave acquired in the first pressurization mode may include the following steps: performing low-pass filtering on the foot pulse wave signal, i.e., the PPG signal; generating a waveform based on the PPG signal sequence after low-pass filtering; analyzing the waveform to determine the changing trend of the PPG signal during the high-pressure continuous phase in the first pressurization mode; and recording the pressure of the gas inside the cuff detected by the pressure sensor during the high-pressure continuous phase; and outputting the determined changing trend and the recorded pressure as physiological feature 1.

[0126] In this embodiment, the foot pulse wave sequence of the first high-pressure duration phase of the first pressurization mode is extracted from all acquired foot pulse wave sequences based on the flag signal. Since the first pressurization mode has two pressurization cycles, and each pressurization cycle has one first high-pressure duration phase, this application actually extracts two foot pulse wave sequences of the first high-pressure duration phase from the first pressurization mode. Trend analysis is performed on the foot pulse wave sequence of each high-pressure duration phase to obtain two trend analysis results. However, since the various phases of the two pressurization cycles and the pressurization parameters of each phase are almost completely identical, the analysis results of the two extracted trends are almost completely identical. The analysis results of the two trends, along with the corresponding collected air pressure in the cuff, are transmitted to the pressurization device.

[0127] Step S230: Extract peak-to-peak values ​​from the second foot pulse wave sequence; perform polynomial fitting analysis on the extracted peak-to-peak values ​​to obtain the polynomial fitting analysis results; extract the second foot pulse wave with the largest pulse wave value from the second foot pulse wave sequence; based on the second foot pulse wave with the largest pulse wave value and the polynomial fitting analysis results, obtain the second hemodynamic parameters of the lower limb.

[0128] In this embodiment of the application, peak-to-peak value extraction is performed on the second foot pulse wave sequence; polynomial fitting analysis is performed on the extracted peak-to-peak value to obtain the polynomial fitting analysis results, including:

[0129] Extract the second foot pulse wave sequence during the second blood pressure reduction phase to obtain the second foot pulse wave sequence to be analyzed; differentiate the second foot pulse wave sequence to be analyzed to obtain the extreme points of the second foot pulse wave sequence to be analyzed; based on the user's heart rate, the user's average amplitude and the extreme points of the second foot pulse wave sequence to be analyzed, remove the dicrotic notch from the second foot pulse wave sequence to be analyzed to obtain the second foot pulse wave sequence to be fitted;

[0130] The second foot pulse wave sequence to be fitted is divided according to the cardiac cycle to obtain multiple second foot pulse wave sequence segments; the peak-to-peak value of each second foot pulse wave sequence segment is calculated; the peak-to-peak value of all second foot pulse wave sequence segments is fitted to obtain the peak-to-peak value fitting curve of the second foot pulse wave sequence; the zero point, maximum point and stationary point of the peak-to-peak value fitting curve of the second foot pulse wave sequence are extracted as the polynomial fitting result.

[0131] In this embodiment of the application, based on the second foot pulse wave sequence with the largest pulse wave sequence value and the results of polynomial fitting analysis, the second hemodynamic parameters of the lower limb are obtained, including:

[0132] The time corresponding to the zero point of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results is extracted to obtain the second time parameter; the time corresponding to the maximum point of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results is extracted to obtain the third time parameter.

[0133] The fourth time parameter is obtained by extracting the time corresponding to the stable point of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results; the fifth time parameter is obtained by extracting the time corresponding to the second foot pulse wave sequence with the largest pulse wave sequence value.

[0134] The second arterial hemodynamic parameters are obtained by extracting the air pressure corresponding to the second time parameter and the air pressure corresponding to the third time parameter from the air pressure sequence; the second venous hemodynamic parameters are obtained by extracting the air pressure corresponding to the fourth time parameter and the air pressure corresponding to the fifth time parameter from the air pressure sequence; and the second hemodynamic parameters of the user's lower limbs are obtained based on the second arterial hemodynamic parameters and the second venous hemodynamic parameters.

[0135] In this embodiment, the second hemodynamic parameter includes a second venous hemodynamic parameter and a second arterial hemodynamic parameter; the second arterial hemodynamic parameter includes a second arterial pressure parameter and a second arterial characteristic parameter; wherein, the second arterial pressure parameter is the air pressure corresponding to the second time parameter; and the second arterial characteristic parameter is the air pressure corresponding to the third time parameter.

[0136] In one embodiment of this application, such as Figure 5As shown, processing the foot pulse wave in the second pressurization mode may include the following steps: differentiating the PPG signal (foot pulse wave) and extracting extreme points; analyzing the PPG signal and removing the PPG signal corresponding to the rapid fluctuation segment and the notch segment; segmenting the PPG signal after removing the rapid fluctuation segment and the notch segment (i.e., the dicrotic notch segment) according to the cardiac cycle; calculating the peak-to-peak mean value of the PPG signal for each cardiac cycle; fitting the peak-to-peak value variation trend based on the peak-to-peak mean value for each cardiac cycle to obtain a fitting curve; extracting the zero point, maximum point, and stable point of the fitting curve, as well as the corresponding times of the zero point, maximum point, and stable point. The pressure of the gas inside the cuff detected by the barometric pressure sensor is used to obtain arterial physiological parameter 1 (i.e., the second arterial pressure parameter in the second arterial hemodynamic parameters), arterial physiological parameter 2 (i.e., the second arterial pressure parameter in the second arterial hemodynamic parameters), and venous physiological parameter 1 (i.e., one of the parameters in the second venous hemodynamic parameters). The maximum value and the pressure of the gas inside the cuff detected by the barometric pressure sensor at the corresponding moment of the maximum value are extracted from all PPG signals to obtain venous physiological parameter 2 (i.e., the other parameter in the second venous hemodynamic parameters). The stable point of the fitted curve is the point where the slope approaches 0.

[0137] Specifically, the PPG signal, after removing the rapid fluctuation segment and the notch segment (i.e., the dicrotic notch segment), is segmented according to the cardiac cycle, including:

[0138] The number of PPG signals in one cardiac cycle is determined based on the user's heart rate. If any two minimum values ​​contain a maximum value, and the number of PPG signals between these two minimum values ​​is the same as or close to the number of PPG signals in one cardiac cycle, then the period between these two minimum values ​​constitutes one cardiac cycle. The PPG signal, after removing the rapid fluctuation segment and the notch segment (i.e., the dicrotic notch segment), is segmented according to the cardiac cycle. For example, if the user's heart rate is 90 beats per minute, 18 foot pulse wave data points will be collected within one cardiac cycle. That is, there should be 18 foot pulse wave data points between the initial minimum point and the final minimum point of one cardiac cycle. If there is a maximum value between two minimum points, and the two minimum points contain 18 foot pulse wave data points, then the period between these two minimum points constitutes one cardiac cycle.

[0139] Step S240: Analyze the third foot pulse wave sequence to obtain the first correction parameter and the second correction parameter; use the first correction parameter and the second correction parameter to correct the second artery hemodynamic parameters to obtain the corrected second artery hemodynamic parameters.

[0140] In this embodiment of the application, the third foot pulse wave sequence is analyzed to obtain a first correction parameter and a second correction parameter, including:

[0141] Extract the third foot pulse wave sequence for all third high pressure sustained phases; for any third foot pulse wave sequence for the third high pressure sustained phase, differentiate the third foot pulse wave sequence for the third high pressure sustained phase to obtain the extreme points of the third foot pulse wave sequence to be analyzed.

[0142] Based on the user's heart rate, average amplitude, and extreme points of the third foot pulse wave sequence to be analyzed, the dicrotic notch in the third foot pulse wave sequence to be analyzed is removed. The third foot pulse wave sequence to be analyzed after removing the dicrotic notch is divided according to the cardiac cycle to obtain multiple third foot pulse wave sequence segments. The peak-to-peak value of each third foot pulse wave sequence segment is calculated. Based on the peak-to-peak value of each third foot pulse wave sequence segment, the average peak-to-peak value of all third foot pulse wave sequence segments is calculated. The average peak-to-peak value of all third foot pulse wave sequence segments is arranged in chronological order.

[0143] The sixth time parameter is obtained by selecting the time corresponding to the maximum value from the average of the peak-to-peak values ​​of all the segments of the third foot pulse wave sequence after arrangement; the seventh time parameter is obtained by selecting the time corresponding to the first value that is 0 from the average of the peak-to-peak values ​​of the segments of the third foot pulse wave sequence after arrangement; the first correction parameter is obtained by extracting the air pressure corresponding to the sixth time parameter from the air pressure sequence; and the second correction parameter is obtained by extracting the air pressure corresponding to the seventh time parameter from the air pressure sequence.

[0144] Specifically, such as Figure 6 As shown, the processing of foot pulse waves in the third inflation mode may include the following steps: segmenting and extracting the PPG signal for each high-pressure sustained phase in the third inflation mode; sequentially differentiating the PPG signal, extracting extreme points (including maximum and minimum points), removing rapid fluctuation segments and dicrotic notches, and then segmenting it according to the cardiac cycle to obtain PPG sequences corresponding to multiple cardiac cycles; calculating the peak-to-peak value of the PPG sequence for each cardiac cycle; calculating the average of the peak-to-peak values ​​of the PPG sequences corresponding to all cardiac cycles in each high-pressure sustained phase to obtain the average of multiple peak-to-peak values ​​corresponding to multiple high-pressure sustained phases; selecting the maximum value from the average of the peak-to-peak values ​​of all high-pressure sustained phases as the first correction parameter; selecting the first 0 value (i.e., ...) from the average of the peak-to-peak values ​​of the high-pressure sustained phases. Figure 6 The zero point in the equation is used as the second correction parameter.

[0145] For example, if the third pressurization mode has four high-pressure duration phases, a, b, c, and d respectively, and each high-pressure duration phase contains two cardiac cycles after removing the fast wave band and dicrotic notch, calculate the peak-to-peak value of each cardiac cycle and the average of the peak-to-peak values ​​of the two cardiac cycles to obtain the four peak-to-peak average values ​​as a1, b1, c1, and d1; where a1 is the peak-to-peak average of all cardiac cycles in phase a, b1 is the peak-to-peak average of all cardiac cycles in phase b, c1 is the peak-to-peak average of all cardiac cycles in phase c, and d1 is the peak-to-peak average of all cardiac cycles in phase d; assuming a1 is 10, b1 is 5, c1 is 0, and d1 is 0; then select the largest value, a1, from a1, b1, c1, and d1 as the first correction parameter; and select c1, which has a value of 0, from a1, b1, c1, and d1 as the second correction parameter.

[0146] When pressure is applied to the calf to a certain value, a corresponding foot pulse wave signal can be detected at the big toe. However, this detected foot pulse wave signal does not contain regular heartbeat fluctuations, so the value of the foot pulse wave signal without regular heartbeat fluctuations is assigned to 0. In the last or last two high-pressure duration phases of the third pressurization mode, no foot pulse wave signal can be detected throughout the entire high-pressure duration phase, meaning the foot pulse wave in the last or last two high-pressure duration phases is 0. At this time, the peak-to-peak value and the average peak-to-peak value of this high-pressure duration phase are also 0, and the average peak-to-peak value of 0 is zero. Simultaneously, since the peak-to-peak value is 0 in the last or last two high-pressure duration phases of the third pressurization mode, there will be multiple cardiac cycles with peak-to-peak values ​​of 0. This application selects the time parameter corresponding to the first cardiac cycle with a value of 0 as the seventh time parameter and extracts the corresponding second correction parameter.

[0147] In this embodiment of the application, the second artery hemodynamic parameters are corrected using a first correction parameter and a second correction parameter to obtain the corrected second artery hemodynamic parameters. This includes: correcting the second artery pressure parameter using the first correction parameter to obtain the corrected second artery pressure parameter; correcting the second artery characteristic parameter using the second correction parameter to obtain the corrected second artery characteristic parameter; and obtaining the corrected second artery hemodynamic parameters based on the corrected second artery pressure parameter and the corrected second artery characteristic parameter.

[0148] Specifically, correcting the second arterial pressure parameter using the first correction parameter can be achieved by taking the average of the first correction parameter and the second arterial pressure parameter to obtain the corrected second arterial pressure parameter; similarly, correcting the second arterial characteristic parameter using the second correction parameter can be achieved by taking the average of the second correction parameter and the second arterial characteristic parameter to obtain the corrected second arterial characteristic parameter.

[0149] Step S250: Combine the first hemodynamic parameters of the lower limb, the second venous hemodynamic parameters, and the corrected second arterial hemodynamic parameters to obtain the lower limb hemodynamic parameters.

[0150] In this embodiment of the application, the lower limb hemodynamic parameters include: the trend change results of the first foot pulse wave sequence and the air pressure values ​​corresponding to the time parameters of multiple specific points.

[0151] In the embodiments of this application, the obtained lower limb hemodynamic parameters physiologically represent the pressure of the lower limb arteries and veins corresponding to the onset and remission of a cardiac cycle.

[0152] Corresponding to the above method, this application also provides a device for acquiring lower limb hemodynamic parameters, such as... Figure 7 As shown, the device for acquiring lower limb hemodynamic parameters includes:

[0153] The signal acquisition unit 710 is used to acquire, for the user's lower limb blood vessels, a first foot pulse wave sequence under a first pressurization mode, a second foot pulse wave sequence under a second pressurization mode, a third foot pulse wave sequence under a third pressurization mode, and a corresponding air pressure sequence for the foot pulse wave sequences; wherein, the foot pulse wave sequence is formed by arranging the acquired foot pulse waves in the order of acquisition time; and the air pressure sequence is formed by arranging the acquired air pressures in the order of acquisition time.

[0154] The trend analysis unit 720 is used to perform trend analysis on the first foot pulse wave sequence to obtain the trend change analysis results of the first foot pulse wave sequence; extract the time corresponding to the trend change analysis results to obtain the first time parameter; extract the air pressure corresponding to the first time parameter from the air pressure sequence to obtain the first air pressure; and obtain the first hemodynamic parameters of the lower limb based on the trend change analysis results of the first foot pulse wave sequence and the first air pressure.

[0155] The fitting analysis unit 730 is used to extract peak-to-peak values ​​from the second foot pulse wave sequence; perform polynomial fitting analysis on the extracted peak-to-peak values ​​to obtain polynomial fitting analysis results; extract the second foot pulse wave with the largest pulse wave value from the second foot pulse wave sequence; and obtain the second hemodynamic parameters of the lower limb based on the second foot pulse wave with the largest pulse wave value and the polynomial fitting analysis results; wherein, the second hemodynamic parameters include the second venous hemodynamic parameters and the second arterial hemodynamic parameters.

[0156] The correction unit 740 is used to analyze the third foot pulse wave sequence to obtain the first correction parameter and the second correction parameter; and to correct the second artery hemodynamic parameters using the first correction parameter and the second correction parameter to obtain the corrected second artery hemodynamic parameters.

[0157] The output unit 750 is used to combine the first hemodynamic parameters of the lower limb, the second venous hemodynamic parameters, and the corrected second arterial hemodynamic parameters to obtain the lower limb hemodynamic parameters.

[0158] The functions of each functional unit in the lower limb hemodynamic parameter acquisition device provided in the above embodiments of this application can be implemented through the above method steps. Therefore, the specific working process and beneficial effects of each unit in the lower limb hemodynamic parameter acquisition device provided in the embodiments of this application will not be repeated here.

[0159] This application also provides an electronic device, such as... Figure 8 As shown, it includes a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840.

[0160] Memory 830 is used to store computer programs;

[0161] When the processor 810 executes the program stored in the memory 830, it performs the following steps:

[0162] For the user's lower limb blood vessels, the following sequences were acquired: the first foot pulse wave sequence under the first pressurization mode, the second foot pulse wave sequence under the second pressurization mode, the third foot pulse wave sequence under the third pressurization mode, and the corresponding air pressure sequence for the foot pulse wave sequence. The foot pulse wave sequence was formed by arranging the acquired foot pulse waves in chronological order of acquisition time; the air pressure sequence was formed by arranging the acquired air pressures in chronological order of acquisition time.

[0163] Trend analysis was performed on the first foot pulse wave sequence to obtain the trend change analysis results; the time corresponding to the trend change analysis results was extracted to obtain the first time parameter; the air pressure corresponding to the first time parameter was extracted from the air pressure sequence to obtain the first air pressure; based on the trend change analysis results of the first foot pulse wave sequence and the first air pressure, the first hemodynamic parameters of the lower limb were obtained.

[0164] Peak-to-peak value extraction was performed on the second foot pulse wave sequence; polynomial fitting analysis was conducted on the extracted peak-to-peak values ​​to obtain the polynomial fitting analysis results; the second foot pulse wave with the largest pulse wave value was extracted from the second foot pulse wave sequence; based on the second foot pulse wave with the largest pulse wave value and the polynomial fitting analysis results, the second hemodynamic parameters of the lower limb were obtained; among which, the second hemodynamic parameters include the second venous hemodynamic parameters and the second arterial hemodynamic parameters;

[0165] The pulse wave sequence of the third foot was analyzed to obtain the first correction parameter and the second correction parameter; the hemodynamic parameters of the second artery were corrected using the first correction parameter and the second correction parameter to obtain the corrected hemodynamic parameters of the second artery.

[0166] The lower limb hemodynamic parameters are obtained by combining the first hemodynamic parameter, the second venous hemodynamic parameter, and the corrected second arterial hemodynamic parameter.

[0167] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0168] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0169] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0170] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0171] The implementation methods and beneficial effects of the various components of the electronic device in the above embodiments for solving the problem can be found in [reference needed]. Figure 2 The steps in the illustrated embodiments are used to implement the electronic device. Therefore, the specific working process and beneficial effects of the electronic device provided in this application will not be repeated here.

[0172] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores instructions that, when executed on a computer, cause the computer to perform any of the methods for obtaining lower limb hemodynamic parameters in the above embodiments.

[0173] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the methods for obtaining lower limb hemodynamic parameters in the above embodiments.

[0174] Those skilled in the art will understand that the embodiments in this application can be provided as methods, systems, or computer program products. Therefore, the embodiments in this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments in this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0175] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0176] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0177] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0178] Although preferred embodiments have been described in this application, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of this application.

[0179] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims in this application and their equivalents, then this application also intends to include these modifications and variations.

Claims

1. A method for obtaining lower limb hemodynamic parameters, characterized in that, The method includes: For the user's lower limb blood vessels, a first foot pulse wave sequence under a first pressurization mode, a second foot pulse wave sequence under a second pressurization mode, a third foot pulse wave sequence under a third pressurization mode, and a corresponding air pressure sequence are acquired; wherein, the foot pulse wave sequence is formed by arranging the acquired foot pulse waves in chronological order; and the air pressure sequence is formed by arranging the acquired air pressures in chronological order. A trend analysis of the first foot pulse wave sequence was performed to obtain the trend change analysis results of the first foot pulse wave sequence; Extract the time corresponding to the trend change analysis results to obtain the first time parameter; extract the air pressure corresponding to the first time parameter from the air pressure sequence to obtain the first air pressure; Based on the trend change analysis results of the first foot pulse wave sequence and the first air pressure, the first hemodynamic parameters of the lower limb are obtained; Peak-to-peak value extraction is performed on the second foot pulse wave sequence; polynomial fitting analysis is performed on the extracted peak-to-peak value to obtain the polynomial fitting analysis results; the second foot pulse wave with the largest pulse wave value is extracted from the second foot pulse wave sequence. Based on the second foot pulse wave with the largest pulse wave value and the polynomial fitting analysis results, the second hemodynamic parameters of the lower limb are obtained; wherein, the second hemodynamic parameters include the second venous hemodynamic parameters and the second arterial hemodynamic parameters; The third foot pulse wave sequence was analyzed to obtain the first correction parameter and the second correction parameter; The second arterial hemodynamic parameters are corrected using the first correction parameter and the second correction parameter to obtain the corrected second arterial hemodynamic parameters; The lower limb hemodynamic parameters are obtained by combining the first hemodynamic parameter of the lower limb, the second venous hemodynamic parameter, and the modified second arterial hemodynamic parameter.

2. The method as described in claim 1, characterized in that, The first pressurization mode includes at least one first high-pressure continuous phase; A trend analysis was performed on the first foot pulse wave sequence to obtain the trend change analysis results of the first foot pulse wave sequence, including: For any first foot pulse wave sequence during the first high-pressure sustained phase, a low-pass filter is applied to the first foot pulse wave sequence during the first high-pressure sustained phase to obtain a filtered first foot pulse wave sequence. The changing trend of the filtered first foot pulse wave sequence is analyzed to obtain the initial trend change analysis results of the first foot pulse wave sequence during the first high pressure sustained phase. The initial trend change analysis results of the first foot pulse wave sequences obtained in multiple first high pressure sustained phases were screened to obtain the trend change results of the first foot pulse wave sequences.

3. The method as described in claim 1, characterized in that, The foot pulse wave sequence is composed of multiple foot pulse wave sequence segments; each foot pulse wave sequence segment corresponds to one cardiac cycle; each foot pulse wave sequence segment includes a foot pulse wave sequence ascending segment and a foot pulse wave sequence descending segment; Before acquiring the first foot pulse wave sequence under the first compression mode, the method further includes: Acquire a resting foot pulse wave sequence; wherein the resting foot pulse wave sequence is formed by arranging foot pulse waves collected without applying pressure to the user's lower limbs in chronological order of acquisition time; The resting foot pulse wave sequence is divided according to the cardiac cycle to obtain multiple resting foot pulse wave sequence segments; For any segment of the resting foot pulse wave sequence, extract the maximum and minimum points of the rising segment of the resting foot pulse wave sequence; subtract the minimum point from the maximum point of the rising segment to obtain the peak-to-peak value of the rising segment. Extract the maximum and minimum points of the descending segment of the resting foot pulse wave sequence; subtract the minimum point from the maximum point of the descending segment to obtain the peak-to-peak value of the descending segment; Based on the peak-to-peak value of the rising segment and the peak-to-peak value of the falling segment, abnormal resting foot pulse wave sequence segments are removed to obtain multiple non-abnormal resting foot pulse wave sequence segments; wherein, the abnormal resting foot pulse wave sequence segments are resting foot pulse wave sequence segments whose peak-to-peak value of the rising segment excluding the peak-to-peak value of the falling segment does not meet the first threshold. For any non-abnormal resting foot pulse wave sequence segment, calculate the average of the peak-to-peak value of the rising segment and the peak-to-peak value of the falling segment to obtain the peak-to-peak value of the non-abnormal resting foot pulse wave sequence segment. Based on the peak-to-peak values ​​of the multiple non-abnormal resting foot pulse wave sequence segments, the average peak-to-peak value of all non-abnormal resting foot pulse wave sequence segments is calculated to obtain the user's average amplitude. Determine the total duration and total number of all non-abnormal resting foot pulse wave sequence segments; based on the total duration and total number, obtain the user's heart rate.

4. The method as described in claim 3, characterized in that, The second pressurization mode includes a second depressurization phase; Peak-to-peak value extraction is performed on the second foot pulse wave sequence; polynomial fitting analysis is then performed on the extracted peak-to-peak values ​​to obtain the polynomial fitting analysis results, including: Extract the second foot pulse wave sequence during the second blood pressure reduction phase to obtain the second foot pulse wave sequence to be analyzed; Differentiate the second foot pulse wave sequence to be analyzed to obtain the extreme points of the second foot pulse wave sequence to be analyzed; Based on the user's heart rate, the user's average amplitude, and the extreme points of the second foot pulse wave sequence to be analyzed, the dicrotic notch in the second foot pulse wave sequence to be analyzed is removed to obtain the second foot pulse wave sequence to be fitted. The second foot pulse wave sequence to be fitted is divided according to the cardiac cycle to obtain multiple second foot pulse wave sequence segments; Calculate the peak-to-peak value of each segment of the second foot pulse wave sequence; fit the peak-to-peak value of all segments of the second foot pulse wave sequence to obtain the peak-to-peak value fitting curve of the second foot pulse wave sequence; The zero point, maximum point, and stable point of the peak-to-peak fitting curve of the second foot pulse wave sequence are extracted as the polynomial fitting result.

5. The method as described in claim 4, characterized in that, Based on the second foot pulse wave with the largest pulse wave value and the polynomial fitting analysis results, the second hemodynamic parameters of the lower limb are obtained, including: The time corresponding to the zero point of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results is extracted to obtain the second time parameter; The time corresponding to the maximum value of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results is extracted to obtain the third time parameter. The fourth time parameter is obtained by extracting the time corresponding to the stable point of the peak-to-peak fitting curve of the second foot pulse wave sequence in the polynomial fitting analysis results. Extract the time corresponding to the second foot pulse wave with the largest pulse wave value to obtain the fifth time parameter; The second arterial hemodynamic parameter is obtained by extracting the air pressure corresponding to the second time parameter and the air pressure corresponding to the third time parameter from the air pressure sequence. The second venous hemodynamic parameter is obtained by extracting the air pressure corresponding to the fourth time parameter and the air pressure corresponding to the fifth time parameter from the air pressure sequence; Based on the second arterial hemodynamic parameters and the second venous hemodynamic parameters, the second hemodynamic parameters of the user's lower limb are obtained.

6. The method as described in claim 3, characterized in that, The third pressurization mode includes at least two third high-pressure sustained phases; The third foot pulse wave sequence was analyzed to obtain the first correction parameter and the second correction parameter, including: Extract the third foot pulse wave sequence for all third high-pressure sustained phases; For any third foot pulse wave sequence during the third high pressure sustained phase, the derivative of the third foot pulse wave sequence during the third high pressure sustained phase is obtained to obtain the extreme points of the third foot pulse wave sequence to be analyzed. Based on the user's heart rate, the user's average amplitude, and the extreme points of the third foot pulse wave sequence to be analyzed, remove the dicrotic notch from the third foot pulse wave sequence to be analyzed. The third foot pulse wave sequence to be analyzed after removing the dicrotic notch is divided according to the cardiac cycle to obtain multiple third foot pulse wave sequence segments. Calculate the peak-to-peak value of each third foot pulse wave sequence segment; based on the peak-to-peak value of each third foot pulse wave sequence segment, calculate the average peak-to-peak value of all third foot pulse wave sequence segments; Arrange the average peak-to-peak values ​​of all the third foot pulse wave sequence segments in chronological order; The sixth time parameter is obtained by selecting the time corresponding to the maximum value of the average of the peak-to-peak values ​​of all the segments of the third foot pulse wave sequence after arrangement. The seventh time parameter is obtained by selecting the time corresponding to the first value that is 0 from the average value of the peak-to-peak values ​​of the third foot pulse wave sequence segment after the arrangement; The pressure corresponding to the sixth time parameter is extracted from the pressure sequence to obtain the first correction parameter; The pressure corresponding to the seventh time parameter is extracted from the pressure sequence to obtain the second correction parameter.

7. The method as described in claim 5, characterized in that, The second arterial hemodynamic parameters include a second arterial pressure parameter and a second arterial characteristic parameter; wherein, the second arterial pressure parameter is the air pressure corresponding to the second time parameter; and the second arterial characteristic parameter is the air pressure corresponding to the third time parameter. The second arterial hemodynamic parameters are corrected using the first correction parameter and the second correction parameter to obtain the corrected second arterial hemodynamic parameters, including: The second arterial pressure parameter is corrected using the first correction parameter to obtain the corrected second arterial pressure parameter; The second artery characteristic parameters are corrected using the second correction parameter to obtain the corrected second artery characteristic parameters; Based on the corrected second arterial pressure parameters and the corrected second arterial characteristic parameters, the corrected second arterial hemodynamic parameters are obtained.

8. A device for acquiring lower limb hemodynamic parameters, characterized in that, The device includes: The signal acquisition unit is used to acquire, for the user's lower limb blood vessels, a first foot pulse wave sequence under a first pressurization mode, a second foot pulse wave sequence under a second pressurization mode, a third foot pulse wave sequence under a third pressurization mode, and a corresponding air pressure sequence for the foot pulse wave sequences; wherein, the foot pulse wave sequence is formed by arranging the acquired foot pulse waves in chronological order of acquisition time; and the air pressure sequence is formed by arranging the acquired air pressures in chronological order of acquisition time. The trend analysis unit is used to perform trend analysis on the first foot pulse wave sequence to obtain the trend change analysis result of the first foot pulse wave sequence; extract the time corresponding to the trend change analysis result to obtain the first time parameter; extract the air pressure corresponding to the first time parameter from the air pressure sequence to obtain the first air pressure; and obtain the first hemodynamic parameter of the lower limb based on the trend change analysis result of the first foot pulse wave sequence and the first air pressure. The fitting analysis unit is used to extract peak-to-peak values ​​from the second foot pulse wave sequence; perform polynomial fitting analysis on the extracted peak-to-peak values ​​to obtain polynomial fitting analysis results; extract the second foot pulse wave with the largest pulse wave value from the second foot pulse wave sequence; and obtain the second hemodynamic parameters of the lower limb based on the second foot pulse wave with the largest pulse wave value and the polynomial fitting analysis results; wherein, the second hemodynamic parameters include second venous hemodynamic parameters and second arterial hemodynamic parameters; The correction unit is used to analyze the third foot pulse wave sequence to obtain a first correction parameter and a second correction parameter; and to correct the second arterial hemodynamic parameters using the first correction parameter and the second correction parameter to obtain the corrected second arterial hemodynamic parameters. The output unit is used to combine the first hemodynamic parameters of the lower limb, the second venous hemodynamic parameters, and the modified second arterial hemodynamic parameters to obtain the lower limb hemodynamic parameters.

9. An electronic device, characterized in that, The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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