Intelligent real-time blood pressure monitoring and intervention system for hypertensive patients

Abstract

The invention relates to the technical field of human body bio-electricity signal measurement, and provides an intelligent real-time blood pressure monitoring and intervention system for hypertensive patients, which comprises a server, a wearing module, a monitoring module, an evaluation module, an intervention interaction module and an early warning module, the monitoring module collects state data of a monitoring position, the evaluation module evaluates the blood pressure of a patient according to the state data to form an evaluation result, the intervention interaction module triggers intervention operation and interaction prompt according to the evaluation result, and the early warning module generates corresponding early warning prompt according to the intervention operation and the interaction prompt and gives an early warning to a monitor. Through mutual cooperation of the monitoring module and the evaluation module, the blood pressure state of a patient can be accurately measured, and it is guaranteed that the whole system has the advantages of being good in real-time monitoring performance, high in intelligence degree and reliable in personalized monitoring capacity.

Description

Technical Field

[0001] The present invention relates to the technical field of measuring human bioelectrical signals, and in particular to an intelligent real-time blood pressure monitoring and intervention system for hypertensive patients. Background Art

[0002] Hypertension is one of the most common chronic diseases, and its management and treatment usually rely on patients to measure their blood pressure and take medication on their own. However, traditional blood pressure monitoring methods cannot provide continuous and accurate blood pressure data, and patients cannot receive timely and effective intervention guidance.

[0003] For example, the Chinese patent CN111067508B discloses a non-interventional monitoring and evaluation method for hypertension in a non-clinical environment. Although it provides a method for monitoring and evaluating the blood pressure signal of the human body through an electrocardiogram, it cannot fully consider the individual differences of patients (such as age, weight, gender, etc.), so the accuracy of the measured data may be affected. At the same time, traditional blood pressure monitoring equipment usually only has a blood pressure measurement function and lacks intelligent intervention methods. When blood pressure is abnormal, the device only provides data prompts and cannot effectively help patients take scientific countermeasures, especially non-drug intervention methods are relatively few. This passive health management model increases patients' dependence on drugs and may cause blood pressure fluctuations to be unable to be controlled in a timely and effective manner.

[0004] In addition, there are the following problems in the prior art:

[0005] 1. Existing blood pressure monitoring systems often only provide one-way data monitoring. Patients cannot effectively provide feedback on the effectiveness of intervention measures. The system also lacks a learning mechanism and is unable to adjust intervention strategies based on patient feedback, resulting in insufficient accuracy and sustainability of intervention.

[0006] 2. Traditional blood pressure monitoring mainly relies on cuff-type blood pressure monitors, which usually require patients to measure at a specific time and place, and cannot achieve continuous monitoring. This method not only brings inconvenience to patients, but also fails to capture the dynamic changes in blood pressure, especially blood pressure fluctuations at night or during daily activities. In addition, scheduled measurements cannot reflect abnormal fluctuations in blood pressure in a timely manner, which may lead to failure to intervene in time and increase the risk of complications.

[0007] 3. Existing blood pressure monitoring devices usually use universal algorithms that cannot fully consider individual differences of patients (such as age, weight, gender, etc.), so the accuracy of the measured data may be affected. Hypertension management needs to be individualized, and universal algorithms may have errors in some patients, leading to misjudgment or inefficient intervention.

[0008] The present invention is made to solve the common problems in the field, such as lack of personalized monitoring, poor intervention means, low intelligence, inability to achieve continuous monitoring, insufficient personalized monitoring capabilities, etc. Summary of the invention

[0009] The purpose of the present invention is to address the current deficiencies and propose an intelligent real-time blood pressure monitoring and intervention system for hypertensive patients.

[0010] In order to overcome the shortcomings of the prior art, the present invention adopts the following technical solutions:

[0011] An intelligent real-time blood pressure monitoring and intervention system for patients with hypertension, the intelligent real-time blood pressure monitoring and intervention system comprising a server, the intelligent real-time blood pressure monitoring and intervention system further comprising a wearing module, a monitoring module, an evaluation module, an intervention interaction module, and an early warning module, the data of the wearing module, the monitoring module, the evaluation module, the intervention interaction module, and the early warning module are all transmitted to the server for storage;

[0012] The wearing module binds the monitoring module to the monitoring position of the patient, the monitoring module collects status data of the monitoring position, the evaluation module evaluates the patient's blood pressure according to the status data to form an evaluation result, the intervention interaction module triggers intervention operations and interaction prompts according to the evaluation result, and the early warning module generates corresponding early warning prompts according to the intervention operations and interaction prompts, and issues an early warning to the monitor;

[0013] The wearing module includes a wearing unit and a limiting unit, wherein the wearing unit is used for placing the monitoring module and is fixed at the monitoring position of the patient, and the limiting unit limits the wearing unit so that the wearing unit is fixed and limited at the monitoring position;

[0014] Wherein, the monitoring module is arranged on the contact end surface between the wearing unit and the patient monitoring position.

[0015] Optionally, the wearing unit includes a wearing belt and a fixing seat, and two ends of the wearing belt are detachably connected to two side walls of the fixing seat to form an annular wearing portion, and the wearing portion is nested and bound at the monitoring position of the patient;

[0016] Wherein, the fixing seat is made of silicone rubber.

[0017] Optionally, the limiting unit includes a limiting component and an anti-slip component, both of which are arranged on the contact end surface between the wearing unit and the patient monitoring position, the limiting component limits the wearing belt portion and the monitoring position, and the anti-slip component is used to limit the contact end surface between the wearing portion and the monitoring position, so that the wearing portion is limited at the monitoring position;

[0018] The limiting components and the anti-slip components are distributed at equal intervals along the contact end surface of the monitoring position.

[0019] Optionally, the monitoring module includes a monitoring unit and a data storage device, the monitoring unit collects the status data of the patient, and the data storage device stores the status data collected by the monitoring unit;

[0020] The monitoring unit includes a PPG sensor, an ECG sensor and a GSR sensor, wherein the PPG sensor collects blood volume change data, the ECG sensor collects electrical signal data generated each time the heart beats, and the GSR sensor collects skin conductivity data. The PPG sensor, the ECG sensor and the GSR sensor are all arranged on the contact end surface of the wearing belt and the patient monitoring position;

[0021] The status data includes blood volume change data, electrical signal data, and skin conductivity data.

[0022] Optionally, the evaluation module obtains the status data and performs filtering processing on the status data to calculate the comprehensive index BP_index of the patient according to the following formula:

[0023]

[0024] Where PWTT is the pulse wave transmission time, HR is the heart rate, which is acquired by the ECG sensor, K is the proportional constant, which is used to adjust the amplification factor and its value is set by the system, λ is the individual calibration coefficient, △GSR(t) is the rate of change of skin conductance, Temp is the patient's current body temperature, and Temp is norm is the reference value of normal body temperature, usually 37°C, and Activity is the patient's activity level;

[0025] If the patient's comprehensive index BP_index does not fall within the state monitoring threshold range [range1, range2] set by the system, it means that the patient's blood pressure may be abnormal, and the intervention interaction module is triggered to perform intervention operations and interactive prompts.

[0026] Optionally, the intervention interaction module includes an intervention unit and a prompt unit, wherein the intervention unit triggers an intervention operation to the patient according to the evaluation result, and the prompt unit prompts the patient of the intervention operation;

[0027] The intervention interaction module triggers the intervention operation according to the following steps:

[0028] S1, the intervention unit obtains BP_index and a preset threshold range [range1, range2], and compares the current BP_index value to determine whether it exceeds the threshold range;

[0029] S2. If the intervention unit determines that BP_index exceeds the set threshold range, the intervention unit first initiates a non-drug intervention operation;

[0030] Among them, non-drug intervention operations include: performing relaxation training, body position adjustment, and dietary advice;

[0031] S3. After the non-drug intervention operation is performed, the intervention unit will re-acquire the patient's comprehensive index BP_index and evaluate the effect of the non-drug intervention. By continuously monitoring BP_index, the system determines whether the intervention is effective;

[0032] S4. If the non-drug intervention effect is not obvious and BP_index still exceeds the threshold range, drug intervention measures and intervention reminders will be triggered through the prompt unit;

[0033] The drug intervention measures include: a prompting unit prompting the patient to take antihypertensive or hypertensive drugs according to the doctor's advice, suggesting that the patient contact the doctor immediately, and automatically notifying medical staff according to settings;

[0034] S5. After the drug intervention is completed, the system continues to monitor the patient's BP_index;

[0035] If the drug intervention is effective and BP_index returns to the normal range, the intervention process will end;

[0036] If drug intervention is ineffective and abnormal blood pressure persists, the warning module will be triggered to issue an emergency warning prompt.

[0037] Optionally, the prompt unit includes a prompt screen and a vibration prompt component, wherein the prompt screen is used to display current prompt information, and the vibration prompt component is used to prompt the patient that there is currently interactive prompt information, so that the patient can view it;

[0038] The vibration prompt component includes a vibration motor, a drive controller, and a vibration sensor. The vibration motor is used to generate mechanical vibration to prompt the patient to check the prompt information. The drive controller controls the vibration motor to vibrate. The vibration sensor collects the vibration amount of the vibration motor during the vibration process and feeds it back to the drive controller to trigger the drive controller to control the vibration motor.

[0039] Optionally, the early warning module includes a communicator, an alarm, and a power supply, the alarm obtains the intervention operation and interaction prompts, and generates corresponding early warning prompts, the communicator warns the manager of the early warning prompts issued by the alarm, and the power supply supplies power to the communicator and the alarm.

[0040] Optionally, a placement cavity is provided on the fixing seat body, and the prompt unit is arranged in the placement cavity.

[0041] Optionally, the wearing belt is made of elastic material and is nested and bound at the monitoring position.

[0042] The beneficial effects achieved by the present invention are:

[0043] 1. Through the cooperation between the monitoring module and the evaluation module, the patient's blood pressure status can be accurately measured, ensuring that the entire system has the advantages of good real-time monitoring, high intelligence and reliable personalized monitoring capabilities;

[0044] 2. Through the cooperation between the wearing module and the monitoring module, patients can obtain monitoring comfort and bind according to actual needs, ensuring that the entire system has the advantages of strong continuous and convenient blood pressure monitoring capabilities, good comfort and high intelligence;

[0045] 3. Through the cooperation between the evaluation module and the intervention interaction module, the patient can obtain intervention interaction prompts, ensuring that the entire system has the advantages of good intervention interaction comfort, precise intervention means, high intelligence, and real-time monitoring.

[0046] 4. Through the cooperation of the intervention interaction module and the early warning module, patients can intervene in their blood pressure according to the early warning prompts, ensuring that the entire system has the advantages of reliable intervention capability, high intelligence, good interactive comfort and strong personalized monitoring capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate the same parts.

[0048] Figure 1 It is an overall block diagram of the present invention.

[0049] Figure 2 It is a schematic diagram of the evaluation process of the evaluation module of the present invention.

[0050] Figure 3 Schematic diagram of application scenarios of the wearing module and the monitoring module of the present invention.

[0051] Figure 4 It is a schematic structural diagram of the fixing base and the prompt screen of the present invention.

[0052] Figure 5 It is a schematic structural diagram of the wearing belt, the limiting component and the anti-slip component of the present invention.

[0053] Figure 6 for Figure 5 Schematic cross-sectional view at AA in the middle.

[0054] Figure 7 It is a cross-sectional schematic diagram of the fixing seat of the present invention.

[0055] Explanation of the accompanying reference numerals: 1. Wearing strap; 2. Limit block; 3. Limit rope; 4. Anti-slip airbag; 5. Anti-slip protrusion; 6. Limit seat; 7. Card connection cavity; 8. Rotating gear; 9. Limit drive mechanism; 10. Fixed seat; 11. Limit control button; 12. Prompt screen; 13. Monitoring unit. DETAILED DESCRIPTION

[0056] The following is an explanation of the embodiments of the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are only simple schematic illustrations and are not depicted according to actual sizes. It is stated in advance. The following embodiments will further explain the relevant technical contents of the present invention in detail, but the disclosed contents are not intended to limit the scope of protection of the present invention.

[0057] Embodiment 1: According to Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 ,as well as Figure 7As shown, this embodiment provides an intelligent real-time blood pressure monitoring and intervention system for hypertensive patients, the intelligent real-time blood pressure monitoring and intervention system includes a server, the intelligent real-time blood pressure monitoring and intervention system also includes a wearing module, a monitoring module, an evaluation module, an intervention interaction module, and an early warning module, and the data of the wearing module, the monitoring module, the evaluation module, the intervention interaction module, and the early warning module are all transmitted to the server for storage;

[0058] In this embodiment, the server is respectively connected to the data of the wearing module, the monitoring module, the evaluation module, the intervention interaction module, and the early warning module, and stores the intermediate data and process data of the wearing module, the monitoring module, the evaluation module, the intervention interaction module, and the early warning module in the database of the server for query and call;

[0059] The intelligent real-time blood pressure monitoring and intervention system also includes a central processor, which is respectively connected to the wearing module, the monitoring module, the evaluation module, the intervention interaction module, and the early warning module, and centrally controls the wearing module, the monitoring module, the evaluation module, the intervention interaction module, and the early warning module based on the central processor, and stores the control data in the database of the server to improve the monitoring reliability and intervention accuracy of the entire system;

[0060] The wearing module binds the monitoring module to the monitoring position of the patient, the monitoring module collects status data of the monitoring position, the evaluation module evaluates the patient's blood pressure according to the status data to form an evaluation result, the intervention interaction module triggers intervention operations and interaction prompts according to the evaluation result, and the early warning module generates corresponding early warning prompts according to the intervention operations and interaction prompts, and issues an early warning to the monitor;

[0061] The wearing module includes a wearing unit and a limiting unit, wherein the wearing unit is used for placing the monitoring module and is fixed at the monitoring position of the patient, and the limiting unit limits the wearing unit so that the wearing unit is fixed and limited at the monitoring position;

[0062] Wherein, the monitoring module is arranged on the contact end surface between the wearing unit and the patient monitoring position;

[0063] Optionally, the wearing unit includes a wearing belt 1 and a fixing seat 10, and the two ends of the wearing belt 1 are detachably connected to the two side walls of the fixing seat 10 to form an annular wearing portion, and the wearing portion is nested and bound at the monitoring position of the patient;

[0064] Wherein, the fixing seat 10 is made of silicone rubber;

[0065] In addition, the storage cavity is provided in the main body of the fixing seat 10, and the storage cavity is used to place the limiting member;

[0066] Optionally, the wearing belt 1 is made of elastic material and is nested and bound at the monitoring position;

[0067] Optionally, the limiting unit includes a limiting component and an anti-slip component, both of which are arranged on the contact end surface between the wearing unit and the patient monitoring position, the limiting component limits the wearing belt 1 and the monitoring position, and the anti-slip component is used to limit the contact end surface between the wearing portion and the monitoring position, so that the wearing portion is limited at the monitoring position;

[0068] The limiting member and the anti-slip member are distributed at equal intervals along the contact end surface of the monitoring position;

[0069] At the same time, the position-limiting member and the anti-slip member are both hidden and arranged on the contact end surface with the monitoring position, and are in direct contact with the patient's skin;

[0070] like Figure 7 As shown, the limiting component includes a limiting cavity, a limiting rope 3, a limiting driving mechanism 9, a limiting seat 6, a limiting control button 11, and limiting blocks 2 arranged at both ends of the limiting rope 3, the limiting cavity is hidden on the wearing belt 1, the ends of both ends of the limiting rope 3 are connected to the limiting blocks 2, the middle section of the limiting rope 3 runs through the limiting cavity, and is detachably connected to the clamping cavity 7 arranged on the limiting seat 6, the two ends of the limiting seat 6 are hinged to the two side walls of the storage cavity of the fixing seat 10 to form a hinged portion, and a rotating gear 8 is provided in the middle of the limiting seat 6, the limiting driving mechanism 9 is meshed with the rotating gear 8, and drives the limiting seat 6 to rotate along the axis of the hinged portion, and the other side end face of the fixing seat 10 is provided with a storage slot, and the limiting seat is hidden in the storage slot;

[0071] At the same time, the engaging cavity 7 provided on the limiting seat 6 is adapted to the limiting block 2, so that the limiting block 2 can be detachably engaged in the engaging cavity 7;

[0072] The limit control button 11 is electrically connected to the limit drive mechanism 9 and controls the limit drive mechanism 9 so that the limit drive mechanism 9 drives the limit seat 6, thereby winding the limit rope 3 around the limit seat 6, thereby binding the wearing belt 1 to the monitoring position;

[0073] The limiting member is used to assist in limiting the binding belt, so that the binding belt will not cause the wearing belt 1 to shift or deviate due to the change of the monitoring position, thereby causing the monitoring effect to decrease;

[0074] The anti-skid component includes an anti-skid protrusion 5, an anti-skid airbag 4, an air pump, an electronic deflation valve and a control panel. The anti-skid protrusion 5 is arranged on the anti-skid airbag 4 and is arranged toward the contact end surface with the monitoring position. The air pump inflates the anti-skid airbag 4 so that the anti-skid airbag 4 is inflated and bulged, and the anti-skid protrusion 5 is directly in contact with the contact end surface of the monitoring position. The electronic deflation valve is arranged on the anti-skid airbag 4 and discharges the gas in the anti-skid airbag 4. The control panel is electrically connected to the electronic deflation valve and the air pump, and when a patient or a user operates the control panel, the air pump inflates the anti-skid airbag 4 and discharges the gas in the anti-skid airbag 4.

[0075] Wherein, the control panel is arranged on the fixing base 10 and can be easily controlled by the patient or user;

[0076] Optionally, the monitoring module includes a monitoring unit 13 and a data storage device, wherein the monitoring unit 13 collects the status data of the patient, and the data storage device stores the status data collected by the monitoring unit 13;

[0077] The monitoring unit 13 includes a PPG sensor, an ECG sensor and a GSR sensor, wherein the PPG sensor collects blood volume change data, the ECG sensor collects electrical signal data generated each time the heart beats, and the GSR sensor collects skin conductivity data. The PPG sensor, the ECG sensor and the GSR sensor are all arranged on the contact end surface of the wearing belt 1 and the patient monitoring position;

[0078] Wherein, the state data includes blood volume change data, electrical signal data, and skin conductivity data;

[0079] The PPG sensor emits light (usually red light or near-infrared light) to the skin through a light-emitting diode (LED), and receives the reflected light signal through a photodiode. Blood is the main medium for absorbing light. Every time the heart beats, the amount of blood in the blood vessels changes, causing the intensity of light absorption and reflection to fluctuate. The PPG sensor can infer changes in heart rate and pulse waves through the fluctuations of these optical signals.

[0080] ECG sensors contact the skin through electrode patches or conductive materials to capture the weak electrical signals (ECG signals) generated by the heart during each beat. When the heart beats, a complex electrical activity process is generated, mainly manifested as P waves, QRS complexes and T waves. These electrical signals are the result of depolarization and repolarization of the heart muscle. By measuring the time intervals and amplitudes of these waveforms, ECG sensors can record the electrical activity of the heart and provide important information about heart health.

[0081] The GSR sensor measures the conductivity of the skin through electrodes. The conductivity of the skin is directly related to the sweat level of the skin. The electrolytes in sweat can increase the conductivity of the skin. Therefore, when the human body is under stress, anxiety or emotional fluctuations, the sympathetic nervous system is activated, resulting in increased secretion of sweat glands, which causes an increase in skin conductivity. The GSR sensor applies a small voltage through two electrodes to measure the change in skin conductivity, thereby inferring a person's emotional state, anxiety or stress level.

[0082] Through the cooperation between the wearing module and the monitoring module, the patient can obtain monitoring comfort and bind according to actual needs, ensuring that the entire system has the advantages of strong continuous and convenient blood pressure monitoring capability, good comfort and high intelligence;

[0083] Optionally, the evaluation module obtains the status data and performs filtering processing on the status data to calculate the comprehensive index BP_index of the patient according to the following formula:

[0084]

[0085] Where PWTT is the pulse wave transmission time, HR is the heart rate, and its value is collected by the ECG sensor. K is the proportional constant used to adjust the amplification factor. Its value range is [100, 1000] and its value is set by the system. λ is the individual calibration coefficient, and its value range is [0.5, 2]. △GSR(t) is the rate of change of skin conductance. Temp is the patient's current body temperature. Temp norm is the reference value of normal body temperature, usually 37°C, Activity is the patient's activity level, usually 0 (stationary), 0.5 (mild activity), 1 (moderate activity), 1.5 (vigorous activity), specifically, the accelerometer can detect the intensity of body movement in different directions, usually in g (gravitational acceleration, about 9.81 m / s 2 ) as a unit. The following is how the different activity levels are distinguished:

[0086] Light activity (0.5): The acceleration value is around 0.2g-0.5g. Usually corresponds to light activities, such as walking, standing, and slight turning.

[0087] Moderate activity (1): The acceleration value is around 0.5g-1g. It corresponds to activities of moderate intensity, such as jogging, climbing stairs, etc.

[0088] Vigorous activity (1.5): The acceleration value is greater than 1g. Corresponding to more intense exercise, such as fast running, jumping or other high-intensity exercise.

[0089] Specifically, for the value of the proportional constant K, this embodiment provides several common value examples:

[0090] 1) Stable blood pressure scenario (patients with small blood pressure fluctuations):

[0091] Among them, for patients with relatively stable blood pressure and small fluctuations. The blood pressure of such patients does not fluctuate violently, and the system needs to maintain a certain stability to avoid unnecessary warnings due to minor changes. The K value range is: 100-300;

[0092] Among them, a smaller K value is selected to reduce the fluctuation range of BP_index, ensuring that the system only responds to significant changes and reducing invalid reminders.

[0093] 2) Hypertension fluctuation scenario (hypertensive patients with large blood pressure fluctuations):

[0094] It is suitable for patients with large blood pressure fluctuations and prone to hypertension. The system needs to be more sensitive to changes in BP_index so as to monitor significant increases in blood pressure in a timely manner. The K value range is: 400-700;

[0095] Among them, a larger K value is set to make BP_index more sensitive to changes in PWTT and HR, so as to capture the trend of blood pressure fluctuations and help hypertensive patients get early warnings in time;

[0096] 3) Motion status scenario (need to avoid false alarms caused by motion):

[0097] That is, it is suitable for patients with large fluctuations in heart rate and PWTT during exercise. The system needs to reduce sensitivity to changes in the exercise state to reduce false alarms caused by exercise, so the K value range is: 100-250

[0098] Among them, a lower K value is set during exercise to reduce the variation range of BP_index and prevent irrelevant warnings caused by fluctuations caused by increased heart rate during exercise.

[0099] 4) Hypotensive patient scenario (need to improve sensitivity to hypotension):

[0100] Scenario description: Applicable to patients with low blood pressure and small fluctuation range. The system needs to be more sensitive to the changes of patients with low blood pressure, so as to promptly indicate the risk of low blood pressure. The K value range is: 300-600;

[0101] Among them, a moderate K value is set so that BP_index can change significantly when blood pressure decreases, thereby triggering a low blood pressure warning in time.

[0102] In short, the value of K needs to be set according to the actual situation and input from the human-computer interaction interface to achieve real-time monitoring of hypertensive patients;

[0103] λ is an individual calibration coefficient, and its value range is [0.5, 2]. Specifically, in this embodiment, different individual calibration coefficient values ​​are used for different patient conditions, as shown in Table 1:

[0104] Table 1:

[0105]

[0106] The value of λ is adjustable in each scenario to adapt to the individual needs and specific circumstances of the patient. It is set according to the actual situation of the patient and input from the human-computer interaction interface. This is a technical means well known to those skilled in the art, so it will not be described in detail in this embodiment;

[0107] In addition, the skin conductivity GSR(t) is calculated according to the following formula:

[0108] ΔGSR(t)=GSR(t)-GSR baseline ;

[0109] Where GSR(t) is the static skin conductivity value at time t, GSR baseline The baseline value of skin conductivity is usually the average value when the patient is calm or resting. The value is obtained by measuring the GSR data over a period of time when the patient is calm or relaxed, and calculating the average value as GSR. baseline This baseline value can be used as a reference for dynamic comparison in subsequent mood swing monitoring.

[0110] The pulse wave transit time (PWTT) is calculated according to the following formula:

[0111] PWTT=(t PPG_peak -t ECG_R )·(1+α·GSR(t));

[0112] In the formula, t PPG_peak is the time when the pulse wave reaches its highest point, t ECG_R is the time point of the R wave peak in the QRS complex in the ECG (electrocardiogram) signal, GSR(t) is the static skin conductivity value at time t, and α is the adjustment coefficient, whose value is obtained after correction based on experimental data;

[0113] In this embodiment, the adjustment coefficient α is determined according to the following steps:

[0114] S11. First, collect the physiological data of the subjects in different situations through experiments:

[0115] GSR data: records skin conductivity values ​​in different situations (such as resting, stress test, relaxation, etc.);

[0116] Blood pressure data: blood pressure values ​​(such as systolic pressure and diastolic pressure) measured in different situations using a standard sphygmomanometer;

[0117] S12. Calculate GSR and blood pressure changes

[0118] Based on the experimental data, calculate the changes in skin conductivity (GSR) and blood pressure; for example:

[0119] At some point in the experiment, the GSR signal increased from the baseline value: ΔGSR = GSR 实验 -GSR 基线 ;

[0120] At the same time, the blood pressure change of the subject measured by the sphygmomanometer is: ΔBP = BP 实验 -BP 基线 ;

[0121] S13. Calculate the α value using the formula:

[0122]

[0123] For example, in an experiment, there is the following data:

[0124] The blood pressure at baseline was 120 / 80 mmHg (baseline blood pressure);

[0125] The blood pressure changes measured in the experiment were an increase in systolic blood pressure from 120 to 130 (i.e., ΔBP = 10 mmHg);

[0126] At the same time, the GSR signal increased by 5 μS (microSiemens, the unit of GSR) from the baseline, i.e., ΔGSR = 5 μS;

[0127] So:

[0128]

[0129] At this time, α = 2 mmHg / μS, indicating that every increase of 1 μS in skin conductivity will cause a 2 mmHg change in blood pressure;

[0130] If the patient's comprehensive index BP_index does not fall within the state monitoring threshold range [range1, range2] set by the system, it means that the patient's blood pressure may be abnormal, and the intervention interaction module is triggered to perform intervention operations and interactive prompts. Specifically: if the patient's comprehensive index BP_index is greater than range2, it means that the patient is at risk of high blood pressure; if the patient's comprehensive index BP_index is less than range1, it means that the patient is at risk of low blood pressure;

[0131] If the patient's comprehensive index BP_index falls within the state monitoring threshold range [range1, range2] set by the system, it means that the patient's blood pressure is within the normal range and no intervention is required;

[0132] In addition, in this embodiment, the state monitoring threshold range [range1, range2] set by the system is set by the system or the administrator according to actual needs and input from the human-computer interaction interface. This is a technical means well known to those skilled in the art. Those skilled in the art can refer to relevant technical manuals to learn about the technology, so it will not be described in detail in this embodiment.

[0133] Through the cooperation between the monitoring module and the evaluation module, the patient's blood pressure status can be accurately measured, ensuring that the entire system has the advantages of good real-time monitoring, high intelligence and reliable personalized monitoring capabilities;

[0134] Optionally, the intervention interaction module includes an intervention unit and a prompt unit, wherein the intervention unit triggers an intervention operation to the patient according to the evaluation result, and the prompt unit prompts the patient of the intervention operation;

[0135] The intervention interaction module triggers the intervention operation according to the following steps:

[0136] S1, the intervention unit obtains BP_index and a preset threshold range [range1, range2], and compares the current BP_index value to determine whether it exceeds the threshold range;

[0137] S2. If the intervention unit determines that BP_index exceeds the set threshold range, the intervention unit first initiates a non-drug intervention operation;

[0138] Among them, non-drug intervention operations include: performing relaxation training, body position adjustment, and dietary advice;

[0139] Relaxation training: Reduce tension and blood pressure by guiding patients to take deep breaths, meditate, relax muscles, etc.

[0140] Body position adjustment: When blood pressure is too low, prompt the patient to lie down or sit down to avoid risks such as dizziness and fainting;

[0141] Dietary advice: In case of low blood pressure, patients should be advised to drink enough water or eat salty food to help restore blood pressure quickly.

[0142] At the same time, in this embodiment, reminders are sent through the prompting unit to guide the patient to perform relaxation exercises, deep breathing and other operations, or to play corresponding audio and video tutorials;

[0143] Provides an intuitive interactive interface that displays specific guidance information, such as breathing rhythm diagrams, body position adjustment diagrams, etc.

[0144] S3. After the non-drug intervention operation is performed, the intervention unit will re-acquire the patient's comprehensive index BP_index and evaluate the effect of the non-drug intervention. By continuously monitoring BP_index, the system determines whether the intervention is effective;

[0145] S4. If the non-drug intervention effect is not obvious and BP_index still exceeds the threshold range, drug intervention measures and intervention reminders will be triggered through the prompt unit;

[0146] The drug intervention measures include: a prompting unit prompting the patient to take antihypertensive or hypertensive drugs according to the doctor's advice, suggesting that the patient contact the doctor immediately, and automatically notifying medical staff according to settings;

[0147] Specifically, smart devices can display reminders for taking medication, for example: "Please take antihypertensive medications as recommended by your doctor";

[0148] If the patient needs emergency medical attention, the doctor’s contact information will be displayed, or a preset emergency number will be called;

[0149] Can be linked to the patient's health record to ensure that medication intervention recommendations are based on individualized medical history and physician recommendations;

[0150] S5. After the drug intervention is completed, the system continues to monitor the patient's BP_index;

[0151] If the drug intervention is effective and BP_index returns to the normal range, the intervention process will end;

[0152] If drug intervention is ineffective and abnormal blood pressure persists, the warning module will be triggered to issue an emergency warning prompt;

[0153] Optionally, the prompt unit includes a prompt screen 12 and a vibration prompt component, wherein the prompt screen 12 is used to display current prompt information, and the vibration prompt component is used to prompt the patient that there is currently interactive prompt information, so that the patient can view it;

[0154] The vibration prompting component includes a vibration motor, a drive controller, and a vibration sensor. The vibration motor is used to generate mechanical vibration to prompt the patient to check the prompt information. The drive controller controls the vibration motor to vibrate. The vibration sensor collects the vibration amount of the vibration motor during the vibration process and feeds it back to the drive controller to trigger the drive controller to control the vibration motor.

[0155] Information is displayed and conveyed through the prompt screen 12; for example, when blood pressure is too high, the screen will display "blood pressure is high, please do deep breathing exercises" and play relevant audio or video instructions;

[0156] In an emergency, the vibration prompting component prompts the patient through strong vibration to ensure that the information is received in time;

[0157] In this embodiment, through the cooperation between the evaluation module and the intervention interaction module, the patient obtains the intervention interaction prompt, ensuring that the entire system has the advantages of good intervention interaction comfort, accurate intervention means, high intelligence, and real-time monitoring.

[0158] Optionally, the early warning module includes a communicator, an alarm, and a power supply, the alarm acquires the intervention operation and the interaction prompt, and generates a corresponding early warning prompt, the communicator warns the manager of the early warning prompt issued by the alarm, and the power supply supplies power to the communicator and the alarm;

[0159] When it is detected that the patient needs to be reminded to check the prompt information (such as blood pressure exceeding the normal range, intervention operation failure, etc.), the central processor sends a vibration instruction through the drive controller to start the vibration prompt; the drive controller sends a start signal to the vibration motor according to the preset vibration mode or intensity; the drive controller is responsible for receiving instructions from the main control unit (such as the microcontroller MCU), and sends a current signal to the vibration motor according to these instructions to control the start of the vibration motor; the drive controller controls the speed or vibration frequency of the vibration motor by adjusting the current or voltage, thereby generating mechanical vibrations of different intensities and modes (such as continuous vibration, intermittent vibration, etc.); the drive controller can control the working parameters of the vibration motor, such as the duration, frequency and intensity of vibration;

[0160] When the vibration motor starts to operate, the internal eccentric mass block (in the ERM motor) or linear actuator (in the LRA motor) starts to rotate or move, thereby generating mechanical vibrations. The vibration motor transmits this mechanical vibration to the device housing, and then transmits the vibration to the patient through the housing, reminding the patient that there is important information to be checked.

[0161] The vibration sensor is used to monitor the vibration intensity and frequency generated by the vibration motor during operation in real time; the vibration sensor can be an accelerometer or a dedicated vibration detection sensor, which is used to collect the physical quantity of vibration; through the vibration sensor, the system can accurately obtain the current vibration state, ensure that the vibration motor works in the expected mode, and avoid excessive vibration or insufficient vibration; the vibration quantity measured by the vibration sensor usually includes acceleration, frequency, displacement and other parameters;

[0162] The vibration sensor will feed back the collected vibration data to the drive controller in real time so that the drive controller can adjust and optimize the working state of the vibration motor; if the vibration amount is insufficient or the vibration frequency does not meet expectations, the drive controller will adjust the output current or voltage and change the operating parameters of the vibration motor to achieve the required vibration intensity and frequency; the drive controller will further finely control the operation of the vibration motor based on the information fed back by the vibration sensor; if it is detected that the vibration amount is too small, the drive controller will increase the current or voltage to enhance the vibration; if the vibration amount is too large, the current or voltage will be reduced to weaken the vibration to ensure that the intensity of the vibration prompt is moderate; the drive controller can also stop the vibration motor and end the vibration prompt after detecting that the vibration prompt has reached the preset time or intensity according to the system settings;

[0163] When the prompt time ends or the user has responded to the prompt, the drive controller receives a stop signal and sends a stop command to the vibration motor; the vibration motor stops running, the prompt ends, and waits for the next trigger;

[0164] Optionally, a placement cavity is provided on the main body of the fixing seat 10, and the prompt unit is arranged in the placement cavity; wherein, placing the prompt unit in the placement cavity can make the prompt unit easily observed by the patient, effectively improving the whole interaction effect, ensuring that the patient can perform self-non-drug intervention and drug intervention guidance according to the real-time prompt information, and improving the convenience and comfort of the whole blood pressure monitoring and intervention;

[0165] In this embodiment, through the cooperation of the intervention interaction module and the early warning module, the patient can perform blood pressure intervention according to the early warning prompts, ensuring that the entire system has the advantages of reliable intervention capability, high intelligence, good interactive comfort and strong personalized monitoring capability.

[0166] Embodiment 2: This embodiment should be understood to include all the features of any of the above embodiments, and further improve upon them. Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 ,as well as Figure 7As shown, the intelligent real-time blood pressure monitoring and intervention system also includes a control module, and the control module can learn the normal health status of the patient according to the historical data (such as the fluctuation trend of heart rate and blood pressure) of the patient-set time period (including one day, one week, half a month, and one month), so as to adjust the personalized threshold range [range1, range2];

[0167] The control module includes a data processing unit and a control analysis unit. The data processing unit obtains the patient's historical data, wherein the historical data includes heart rate (HR), blood pressure comprehensive index (BP_index), and other auxiliary physiological data (such as activity status, sleep time, etc.). The control analysis unit automatically adjusts the personalized threshold range [range1, range2] according to the historical data processed by the data processing unit to adapt to individual differences and provide more accurate blood pressure monitoring and intervention;

[0168] The data processing unit performs basic processing on the collected historical data, including de-noising and smoothing;

[0169] Among them, denoising removes noise from the data by using filtering algorithms (such as Kalman filtering), and smoothing reduces the impact of random fluctuations on the analysis by smoothing the data using a moving average method;

[0170] Meanwhile, the moving average method is calculated according to the following formula:

[0171]

[0172] In the formula, is the smoothed data or estimated value at a certain time point t, which is a smoother and noise-free approximation of the original data x(t) after processing. x(ti) is the original data at the ti-th moment (such as heart rate, blood pressure comprehensive index, etc.), and n is the window size of the moving average, that is, the data of the past n moments are used to calculate the smoothed value at the t-th moment;

[0173] In this embodiment, the heart rate (HR), blood pressure comprehensive index (BP_index), and other auxiliary physiological data (such as activity status, sleep time, etc.) are substituted into the above formula to calculate the corresponding smoothed data or estimated values;

[0174] For example, to smooth the comprehensive blood pressure index in the past 10 minutes, the window size n can be set to 10, and data can be collected once a minute. The smoothed comprehensive blood pressure index at time t is:

[0175]

[0176] In the formula, is the smoothed blood pressure comprehensive index estimate at time point t, BP_index(ti) is the original blood pressure comprehensive index at time ti;

[0177] The control analysis unit analyzes data from the past period of time (such as changes in heart rate and blood pressure over the past week or month) to identify the patient's health trend. In this embodiment, linear regression is used to calculate the fluctuation trend of the blood pressure index (BP_index); linear regression can be used to fit the blood pressure change trend over the past period of time to determine whether the blood pressure is gradually increasing or decreasing;

[0178] The linear regression formula is:

[0179] BP_index(t)=β0+β1·t;

[0180] Where, BP_index(t): blood pressure index at time t, β0 is the intercept, indicating the initial blood pressure index, and β1 is the slope, indicating the trend of blood pressure change over time (if β1>0, it means that blood pressure is rising, if β1<0, it means that blood pressure is falling);

[0181] The control and analysis unit calculates the normal fluctuation range of heart rate and blood pressure based on historical data; and determines the patient's personalized normal range by calculating the mean and standard deviation of the historical data;

[0182]

[0183] Where, μ is the mean of the comprehensive blood pressure index at all time points, N is the number of data points, indicating the total number of samples in the time period, BP_index(i): the comprehensive blood pressure index data at the i-th time point;

[0184]

[0185] Wherein, σ represents the standard deviation of blood pressure fluctuation, which reflects the amplitude of blood pressure fluctuation of patients. The larger the standard deviation, the greater the blood pressure fluctuation. μ is the mean of the comprehensive blood pressure index at all time points. N is the number of data points, which represents the total number of samples in the time period. BP_index(i): the comprehensive blood pressure index data at the i-th time point.

[0186] The control analysis unit dynamically adjusts the personalized threshold range [range1, range2] according to the trend analysis results and the historical fluctuation range, so that the monitoring threshold is more in line with the patient's personal health status;

[0187] The control and analysis unit sets a personalized monitoring threshold range for blood pressure according to the patient's mean μ and fluctuation range σ:

[0188]

[0189] Where μ is the mean of the comprehensive blood pressure index at all time points, σ ​​is the standard deviation of the patient's blood pressure fluctuation, indicating the normal fluctuation range, and k1 and k2 are adjustment coefficients that determine the width of the monitoring range; they can usually be determined through historical data analysis, specifically:

[0190] According to the patient's blood pressure fluctuation range, k1 and k2 are adjusted to ensure that the system can accurately reflect the patient's individual health conditions; the adjustment formula is as follows:

[0191]

[0192] In the formula, k1 初始 and k2 初始 is the monitoring range adjustment coefficient initially set by the system (usually set to 2), σ is the standard deviation of the patient’s blood pressure fluctuation over a certain period of time, and σ 基准 is a standard deviation of a benchmark, used to represent the normal range of healthy blood pressure fluctuations. In this embodiment, σ 基准 It can be determined based on clinical experience or statistical data of a large number of patients. For example, the standard deviation of blood pressure fluctuation range in clinically healthy people may be 10 mmHg.

[0193] When the patient's fluctuation σ is greater than the baseline fluctuation σ 基准 When the value of k1 and k2 increases, the monitoring range becomes wider; this can avoid frequent warnings, because large fluctuations are normal;

[0194] On the contrary, when the patient's fluctuation σ is less than σ 基准 When k1 and k2 decrease, the monitoring range becomes narrower, thereby increasing the system's sensitivity to abnormalities.

[0195] In this embodiment, the process of dynamically adjusting the threshold value includes the following steps:

[0196] S21, initial setting: When the system starts running, a fixed standard threshold range [range1, range2] is used until enough historical data is collected;

[0197] S22, Trend learning and analysis: The system regularly (e.g., weekly or monthly) analyzes the patient's historical health data and calculates the fluctuation range and change trend;

[0198] S23, personalized threshold adjustment: based on historical data, the system dynamically adjusts the threshold range [range1, range2] to better match the individual health status of the patient;

[0199] Through the mutual cooperation of the control module and the evaluation module, the personalized monitoring capability of the patient is made more reliable, ensuring that the entire system has the advantages of good monitoring reliability, strong intelligent monitoring capability, and high efficiency of personalized monitoring capability.

[0200] The contents disclosed above are only preferred feasible embodiments of the present invention, and do not limit the protection scope of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention specification and drawings are included in the protection scope of the present invention. In addition, the elements therein can be updated as technology develops.

Claims

1. An intelligent real-time blood pressure monitoring and intervention system for hypertensive patients, the intelligent real-time blood pressure monitoring and intervention system comprising a server, characterized in that: The intelligent real-time blood pressure monitoring and intervention system also includes a wearing module, a monitoring module, an evaluation module, an intervention interaction module, and an early warning module. The data of the wearing module, the monitoring module, the evaluation module, the intervention interaction module, and the early warning module are all transmitted to the server for storage; The wearing module binds the monitoring module to the patient's monitoring position, the monitoring module collects status data of the monitoring position, the evaluation module evaluates the patient's blood pressure according to the status data to form an evaluation result, the intervention interaction module triggers intervention operations and interaction prompts according to the evaluation results, the early warning module generates corresponding early warning prompts according to the intervention operations and interaction prompts, and issues an early warning to the monitor; the status data includes pulse wave transmission time, heart rate, skin conductance change rate, patient's current body temperature, and patient's activity level; The wearing module includes a wearing unit and a limiting unit, wherein the wearing unit is used for placing the monitoring module and is fixed at the monitoring position of the patient, and the limiting unit limits the wearing unit so that the wearing unit is fixed and limited at the monitoring position; Wherein, the monitoring module is arranged on the contact end surface between the wearing unit and the monitoring position of the patient.

2. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 1, characterized in that: The wearing unit comprises a wearing belt and a fixing seat, the two ends of the wearing belt are detachably connected to the two side walls of the fixing seat to form an annular wearing part, and the wearing part is nested and bound at the monitoring position of the patient; Wherein, the fixing seat is made of silicone rubber.

3. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 2, characterized in that: The limiting unit includes a limiting component and an anti-slip component, both of which are arranged on the contact end surface between the wearing unit and the patient monitoring position, the limiting component limits the wearing belt portion and the monitoring position, and the anti-slip component is used to limit the contact end surface between the wearing portion and the monitoring position, so that the wearing portion is limited at the monitoring position; The limiting components and the anti-slip components are distributed at equal intervals along the contact end surface of the monitoring position.

4. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 3, characterized in that: The monitoring module includes a monitoring unit and a data storage device, wherein the monitoring unit collects the status data of the patient, and the data storage device stores the status data collected by the monitoring unit; The monitoring unit includes a PPG sensor, an ECG sensor and a GSR sensor, wherein the PPG sensor collects blood volume change data, the ECG sensor collects electrical signal data generated each time the heart beats, and the GSR sensor collects skin conductivity data. The PPG sensor, the ECG sensor and the GSR sensor are all arranged on the contact end surface of the wearing belt and the patient monitoring position; The status data includes blood volume change data, electrical signal data, and skin conductivity data.

5. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 4, characterized in that: The evaluation module obtains the status data and performs filtering on the status data to calculate the comprehensive index BP_index of the patient according to the following formula: Where PWTT is the pulse wave transmission time, HR is the heart rate, which is acquired by the ECG sensor, K is the proportional constant, which is used to adjust the amplification factor and its value is set by the system, λ is the individual calibration coefficient, △GSR(t) is the rate of change of skin conductance, Temp is the patient's current body temperature, and Temp is norm is the reference value of normal body temperature. Activity is the patient's activity level; If the patient's comprehensive index BP_index does not fall within the state monitoring threshold range [range1, range2] set by the system, it means that the patient's blood pressure may be abnormal, and the intervention interaction module is triggered to perform intervention operations and interactive prompts.

6. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 5, characterized in that: The intervention interaction module includes an intervention unit and a prompt unit, wherein the intervention unit triggers an intervention operation to the patient according to the evaluation result, and the prompt unit prompts the patient of the intervention operation; The intervention interaction module triggers the intervention operation according to the following steps: S1, the intervention unit obtains BP_index and a preset threshold range [range1, range2], and compares the current BP_index value to determine whether it exceeds the threshold range; S2. If the intervention unit determines that BP_index exceeds the set threshold range, the intervention unit first initiates a non-drug intervention operation; Among them, non-drug intervention operations include: performing relaxation training, body position adjustment, and dietary advice; S3. After the non-drug intervention operation is performed, the intervention unit will re-acquire the patient's comprehensive index BP_index and evaluate the effect of the non-drug intervention. By continuously monitoring BP_index, the system determines whether the intervention is effective; S4. If the non-drug intervention effect is not obvious and BP_index still exceeds the threshold range, drug intervention measures and intervention reminders will be triggered through the prompt unit; The drug intervention measures include: a prompting unit prompting the patient to take antihypertensive or hypertensive drugs according to the doctor's advice, suggesting that the patient contact the doctor immediately, and automatically notifying medical staff according to settings; S5. After the drug intervention is completed, the system continues to monitor the patient's BP_index; If the drug intervention is effective and BP_index returns to the normal range, the intervention process will end; If drug intervention is ineffective and abnormal blood pressure persists, the warning module will be triggered to issue an emergency warning prompt.

7. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 6, characterized in that: The prompt unit includes a prompt screen and a vibration prompt component, wherein the prompt screen is used to display the current prompt information, and the vibration prompt component is used to prompt the patient that there is currently interactive prompt information, so that the patient can view it; The vibration prompt component includes a vibration motor, a drive controller, and a vibration sensor. The vibration motor is used to generate mechanical vibration to prompt the patient to check the prompt information. The drive controller controls the vibration motor to vibrate. The vibration sensor collects the vibration amount of the vibration motor during the vibration process and feeds it back to the drive controller to trigger the drive controller to control the vibration motor.

8. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 7, characterized in that: The early warning module includes a communicator, an alarm, and a power supply. The alarm obtains the intervention operation and interaction prompts and generates corresponding early warning prompts. The communicator warns the administrator of the early warning prompts issued by the alarm, and the power supply supplies power to the communicator and the alarm.

9. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 8, characterized in that: The fixing seat body is provided with a placement cavity, and the prompt unit is arranged in the placement cavity.

10. The intelligent real-time blood pressure monitoring and intervention system for hypertensive patients according to claim 9, characterized in that: The wearing belt is made of elastic material and is nested and bound at the monitoring position.

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