Early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases

Abstract

The invention relates to the technical field of microwave signal frequency measurement, and discloses a cardiovascular and cerebrovascular acute critical disease early warning and monitoring system, which comprises a patient risk layering module, a multi-dimensional physiological signal acquisition module, a physiological signal abnormity analysis module and an early warning trigger and response module, and all the modules realize two-way communication through a data bus. According to the cardiovascular and cerebrovascular acute critical disease early warning and monitoring system, risk values are calculated and graded through the patient risk layering module according to the age, the basic disease number and the historical attack number, differential acquisition parameters are configured for patients with different risks, the problem that the monitoring precision of high-risk patients is insufficient is avoided, and resource waste of low-risk patients is reduced.

Description

Technical Field

[0001] This invention relates to the field of cardiovascular and cerebrovascular disease monitoring technology, specifically to an early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases. Background Technology

[0002] Existing cardiovascular and cerebrovascular monitoring systems often have the following shortcomings:

[0003] Single monitoring dimension: Most systems only focus on a single physiological indicator (such as heart rate and blood pressure) and do not integrate key indicators such as hemodynamics and vascular elasticity, making it difficult to comprehensively reflect the patient's cardiovascular and cerebrovascular functional status and easily leading to missed early risks.

[0004] Lack of risk stratification: No differentiated monitoring strategies were developed for individual patient differences (such as age, underlying diseases, and history of acute and critical illness). High-risk patients and low-risk patients were treated with the same collection interval and warning threshold, resulting in insufficient monitoring accuracy for high-risk patients and waste of resources for low-risk patients.

[0005] The abnormality assessment and response are disconnected: It can only identify abnormal physiological indicators, but lacks a linkage mechanism of "abnormality index - risk level - response measures". After the warning, it is impossible to quickly match the targeted intervention process, which delays the treatment opportunity.

[0006] The calculation of abnormality index is crude: no standardized abnormality quantification model has been established, and it relies heavily on simple threshold comparison (such as "blood pressure > 140 / 90 mmHg is considered abnormal"), ignoring the fluctuation trend of the index and the differences in individual baselines, resulting in a high false alarm rate and false negative rate.

[0007] To address the aforementioned problems, this invention proposes an early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases. This system overcomes the technical deficiencies of existing systems through patient risk stratification, multi-dimensional signal acquisition, refined anomaly analysis, and intelligent early warning response. Summary of the Invention

[0008] This invention provides an early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases, which helps to solve the problems mentioned in the background art.

[0009] This invention provides the following technical solution: a cardiovascular and cerebrovascular emergency and critical illness early warning monitoring system, including a patient risk stratification module, a multi-dimensional physiological signal acquisition module, a physiological signal abnormality analysis module, and an early warning triggering and response module, wherein each module realizes bidirectional communication through a data bus;

[0010] The patient risk stratification module is used to calculate risk values ​​based on basic patient information and clinical information, classify risk levels, and configure differentiated physiological signal acquisition parameters for different risk levels.

[0011] The multi-dimensional physiological signal acquisition module is used to acquire at least three types of physiological signals from the patient's heart rate, blood pressure, blood oxygen saturation, blood flow velocity, and vascular elasticity coefficient in real time according to the acquisition parameters, and transmit them to the physiological signal abnormality analysis module after preprocessing.

[0012] The physiological signal abnormality analysis module is used to analyze the preprocessed physiological signals and calculate three types of abnormal indices: heart rate abnormality index, blood pressure abnormality index, and hemodynamic abnormality index.

[0013] The early warning triggering and response module is used to calculate the comprehensive anomaly index, determine the early warning level based on the early warning threshold, and execute the corresponding response measures.

[0014] Optionally, the patient risk stratification module includes a data input unit, a risk value calculation unit, a risk level classification unit, and a data acquisition parameter configuration unit; the data input unit acquires the patient's age, number of underlying diseases, and number of historical attacks of acute and critical cardiovascular and cerebrovascular diseases;

[0015] The risk value calculation unit uses the formula Calculate the risk value, where For age normalized value, Normalized value of the number of underlying diseases λ1, λ2, λ3 are normalized values ​​of historical seizure counts, and λ1, λ2, λ3 are adjustable weights that satisfy λ1 + λ2 + λ3 = 1;

[0016] The risk level classification unit sets thresholds R1 = 0.3 and R2 = 0.7 to classify patients into low risk (R < 0.3), medium risk (0.3 ≤ R < 0.7), and high risk (R ≥ 0.7).

[0017] The data acquisition parameter configuration unit configures a 5-minute data acquisition interval for low-risk patients, a 2-minute data acquisition interval for medium-risk patients, and a 1-minute data acquisition interval for high-risk patients.

[0018] Optionally, the multi-dimensional physiological signal acquisition module includes an acquisition device interface unit, a signal acquisition control unit, a signal preprocessing unit, and a data buffer and transmission unit; the acquisition device interface unit is compatible with electrocardiogram monitors, non-invasive blood pressure monitors, ultrasonic Doppler flowmeters, and vascular elasticity detectors, and supports wired or wireless data transmission; the signal preprocessing unit uses a wavelet transform denoising algorithm to remove signal interference and normalizes the signal values ​​to the [0,1] interval; the data buffer and transmission unit supports offline storage for ≥72 hours and data transmission latency ≤100ms.

[0019] Optionally, the physiological signal abnormality analysis module includes a heart rate abnormality analysis submodule, a blood pressure abnormality analysis submodule, and a hemodynamic abnormality analysis submodule;

[0020] The heart rate abnormality analysis submodule uses the formula Ω1=w1·D HR +w2·(N HR / 9) Calculate the heart rate abnormality index, D HR N represents the resting deviation of heart rate. HR The number of dynamic fluctuations in heart rate is w1 = 0.6, w2 = 0.4;

[0021] The blood pressure abnormality analysis submodule calculates the blood pressure abnormality index using the formula Ω2=w3·ΔSBP+w4·ΔDBP, where ΔSBP is the systolic blood pressure fluctuation amplitude, ΔDBP is the diastolic blood pressure fluctuation amplitude, w3=0.5, w4=0.5;

[0022] The hemodynamic abnormality analysis submodule uses the formula Ω3=w5·ΔFV * +w6·ΔE * Calculate the hemodynamic abnormality index, ΔFV * ΔE is the normalized rate of change of blood flow velocity. * The normalized rate of change of vascular elasticity coefficient is w5 = 0.6, w6 = 0.4.

[0023] Optionally, the early warning triggering and response module includes a comprehensive anomaly index calculation unit, an early warning threshold determination unit, a multi-channel response unit, and an early warning recording and backtracking unit;

[0024] The comprehensive anomaly index calculation unit calculates the comprehensive anomaly index using the formula Ω=(Ω1+Ω2+Ω3) / 3;

[0025] The warning threshold determination unit sets three threshold levels: Level 1 warning 0.3≤Ω<0.5, Level 2 warning 0.5≤Ω<0.8, and Level 3 warning Ω≥0.8; the multi-channel response unit initiates an emergency response process for Level 3 warnings, including triggering emergency channel notifications, pushing data to the emergency team, and calling family members.

[0026] The warning recording and backtracking unit automatically records warning logs and supports exporting to PDF / Excel format.

[0027] Optionally, the age normalized value Normalization of the number of underlying diseases Normalized value of historical seizure frequency

[0028] Optionally, the heart rate static deviation The mean of the most recent 10 standardized heart rates is 0.5, which is the normal heart rate standardization baseline. The systolic blood pressure fluctuation amplitude ΔSBP = (max(SBP1,...,SBP5)-min(SBP1,...,SBP5)) / SBP0, where SBP0 is the patient's baseline systolic blood pressure value in the past 72 hours.

[0029] The present invention has the following beneficial effects:

[0030] This cardiovascular and cerebrovascular emergency and critical illness early warning and monitoring system employs a patient risk stratification module. Based on age, number of underlying diseases, and historical frequency of attacks, it calculates risk values ​​and classifies patients into different risk levels, configuring differentiated acquisition parameters for patients with varying risk profiles. This avoids insufficient monitoring accuracy for high-risk patients while reducing resource waste for low-risk patients. The multi-dimensional physiological signal acquisition module is compatible with various monitoring devices and can acquire at least three types of physiological signals. Wavelet transform denoising and normalization preprocessing ensure signal quality, guaranteeing data continuity and timeliness. The physiological signal anomaly analysis module calculates three abnormal indices—heart rate, blood pressure, and hemodynamics—using standardized formulas, overcoming the limitations of simple threshold comparisons and reducing false alarm and false negative rates. The early warning triggering and response module implements three levels of early warning based on comprehensive abnormal indices, executing multi-channel responses for different levels while automatically recording early warning logs for retrospective analysis. This effectively improves the accuracy and response efficiency of early warning for cardiovascular and cerebrovascular emergencies, reducing treatment delays. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the system modules of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] A cardiovascular and cerebrovascular emergency and critical illness early warning and monitoring system is provided to achieve accurate early warning and efficient response to cardiovascular and cerebrovascular emergencies. Its core technical solution is as follows:

[0035] System Overall Architecture

[0036] The system includes a patient risk stratification module, a multi-dimensional physiological signal acquisition module, a physiological signal abnormality analysis module, and an early warning triggering and response module. Each module communicates bidirectionally via a data bus, with the specific connection relationships as follows:

[0037] The risk level output terminal of the patient risk stratification module is connected to the acquisition parameter control terminal of the multi-dimensional physiological signal acquisition module;

[0038] The signal output terminal of the multi-dimensional physiological signal acquisition module is connected to the signal input terminal of the physiological signal abnormality analysis module;

[0039] The abnormal index output of the physiological signal abnormality analysis module is connected to the judgment input of the early warning trigger and response module;

[0040] The feedback signal terminal of the early warning triggering and response module is connected to the risk update terminal of the patient risk stratification module (used to dynamically adjust the patient risk level based on the early warning result).

[0041] Detailed functions of each module

[0042] 1. Patient risk stratification module

[0043] This tool is used to calculate risk values ​​based on individual patient information, classify risk levels, and match differentiated physiological signal acquisition parameters (acquisition interval, monitoring indicator priority) for different risk levels. Specific functions include:

[0044] Data input unit: Acquires patient basic information (age, gender), clinical information (number of underlying diseases such as hypertension / diabetes / coronary heart disease, number of historical attacks of acute and critical cardiovascular and cerebrovascular diseases), and real-time basic indicators (resting heart rate, baseline blood pressure);

[0045] Risk value calculation unit: The patient's risk value R is calculated through normalization and weighted summation, as shown in the following formula: in:

[0046] This is the normalized value for age, ranging from 0 to 1.

[0047] This is the normalized value of the number of basic diseases, ranging from 0 to 1;

[0048] This is a normalized value for the number of historical seizures, ranging from 0 to 1.

[0049] λ1, λ2, and λ3 are adjustable weights that satisfy λ1 + λ2 + λ3 = 1. The default values ​​are λ1 = 0.2, λ2 = 0.5, and λ3 = 0.3, which are used to adjust the degree of influence of each factor on the risk value.

[0050] Risk level classification unit: Set risk thresholds R1 = 0.3 and R2 = 0.7. If R < 0.3, it is classified as "low risk", 0.3 ≤ R < 0.7 is classified as "medium risk", and R ≥ 0.7 is classified as "high risk".

[0051] The parameter acquisition configuration unit is configured as follows: for low-risk patients, it is configured with "5-minute acquisition interval, heart rate + blood pressure priority monitoring", for medium-risk patients, it is configured with "2-minute acquisition interval, heart rate + blood pressure + blood oxygen priority monitoring", and for high-risk patients, it is configured with "1-minute acquisition interval, heart rate + blood pressure + blood oxygen + blood flow velocity + vascular elasticity full index monitoring".

[0052] 2. Multi-dimensional physiological signal acquisition module

[0053] This module is used to collect cardiovascular and cerebrovascular related physiological signals in real time based on the acquisition parameters output by the patient risk stratification module, and then transmits the standardized signal data to the physiological signal abnormality analysis module. Specific functions include:

[0054] Data acquisition device interface unit: compatible with electrocardiogram monitor (acquiring heart rate HR, blood oxygen saturation SpO2), non-invasive blood pressure monitor (acquiring systolic blood pressure SBP, diastolic blood pressure DBP), ultrasonic Doppler flowmeter (acquiring cerebral / coronary blood flow velocity FV), vascular elasticity detector (acquiring vascular elasticity coefficient E), and supports wired (RS485) or wireless (Bluetooth 5.0, LoRa) data transmission;

[0055] Signal acquisition and control unit: Based on the acquisition interval corresponding to the risk level, trigger synchronous / asynchronous acquisition of each device (high-risk patients trigger synchronous acquisition of all devices, and medium- and low-risk patients trigger asynchronous acquisition of priority indicators);

[0056] Signal preprocessing unit: performs filtering (removing power frequency interference and motion artifacts), denoising (using wavelet transform denoising algorithm), and standardization (mapping signal values ​​to the [0,1] interval, such as the heart rate standardization formula HR) on the acquired raw signal. * = (HR-40) / (120-40), where 40 is the minimum normal heart rate and 120 is the maximum normal heart rate;

[0057] Data caching and transmission unit: The preprocessed signal data is cached locally (supports offline storage of ≥72 hours) and transmitted to the physiological signal abnormality analysis module through the hospital intranet / IoT, with a transmission delay of ≤100ms.

[0058] 3. Physiological Signal Anomaly Analysis Module

[0059] This module is used to analyze standardized signals transmitted by the multi-dimensional physiological signal acquisition module, calculate three types of abnormal indices: abnormal heart rate index, abnormal blood pressure index, and abnormal hemodynamics index, and quantify the degree of abnormality in the patient's physiological state. Specifically, it includes the following sub-modules:

[0060] 3.1 Heart Rate Anomaly Analysis Submodule

[0061] Function: Calculates the heart rate abnormality index Ω1 based on the static deviation and dynamic fluctuation characteristics of heart rate;

[0062] Calculation steps:

[0063] Obtain standardized heart rate values ​​from the patient's last 10 heart rate measurements. Calculate the mean

[0064] Calculate static deviation (0.5 is the standardized baseline value for normal heart rate);

[0065] Statistical dynamic fluctuation number N HR If the difference between two consecutive heart rates (0.1 is the heart rate fluctuation threshold), then it is recorded as 1 fluctuation;

[0066] Calculate the heart rate abnormality index Ω1 = w1·D HR +w2·(N HR / 9), where w1=0.6, w2=0.4 are weights (satisfying w1+w2=1), and 9 is the upper limit of adjacent collection times;

[0067] Note: The value of Ω1 ranges from [0,1]. The larger the value, the higher the degree of heart rate abnormality.

[0068] 3.2 Blood Pressure Abnormality Analysis Submodule

[0069] Function: Calculates the blood pressure abnormality index Ω2 based on the fluctuation range and deviation from baseline of systolic and diastolic blood pressure;

[0070] Calculation steps:

[0071] Obtain the patient's systolic blood pressure SBP1,...,SBP5 and diastolic blood pressure DBP1,...,DBP5 from the last 5 collections, and calculate the patient's baseline blood pressure values ​​SBP0 (mean systolic blood pressure under normal conditions in the last 72 hours) and DBP0 (mean diastolic blood pressure under normal conditions in the last 72 hours).

[0072] Calculate the systolic blood pressure fluctuation amplitude ΔSBP=(max(SBP1,...,SBP5)-min(SBP1,...,SBP5)) / SBP0;

[0073] Calculate the diastolic blood pressure fluctuation amplitude ΔDBP = (max(DBP1,...,DBP5) - min(DBP1,...,DBP5)) / DBP0;

[0074] Calculate the blood pressure abnormality index Ω2 = w3·ΔSBP + w4·ΔDBP, where w3 = 0.5 and w4 = 0.5 are weights;

[0075] Note: The value of Ω2 ranges from [0,1]. The larger the value, the higher the degree of blood pressure abnormality.

[0076] 3.3 Hemodynamic Abnormality Analysis Submodule

[0077] Function: Calculates the hemodynamic abnormality index Ω3 based on the rate of change of blood flow velocity and vascular elasticity coefficient;

[0078] Calculation steps:

[0079] Obtain the blood flow velocities FV1, FV2, FV3 and vascular elasticity coefficients E1, E2, E3 from the patient's three most recent blood collections.

[0080] Calculate the rate of change of blood flow velocity ΔFV=|FV3-FV1| / (FV2·Δt), where Δt is the time interval between the three data collections (unit: min);

[0081] Calculate the rate of change of the vascular elasticity coefficient ΔE = |E3 - E1| / (E2·Δt);

[0082] Normalize ΔFV and ΔE. * =ΔFV / 0.2, ΔE * =ΔE / 0.1, where 0.2 and 0.1 are the maximum normal rates of change of blood flow velocity and vascular elasticity coefficient, respectively;

[0083] Calculate the hemodynamic abnormality index Ω3 = w5·ΔFV * +w6·ΔE * Where w5 = 0.6 and w6 = 0.4 are the weights;

[0084] Note: The value of Ω3 ranges from [0,1]. The larger the value, the higher the degree of hemodynamic abnormality.

[0085] 4. Early Warning Triggering and Response Module

[0086] This system is used to calculate a comprehensive abnormality index based on the three types of abnormality indices output by the physiological signal abnormality analysis module, determine whether an early warning is triggered, and execute corresponding response measures. Specific functions include:

[0087] Comprehensive Abnormality Index Calculation Unit: Calculates the comprehensive abnormality index Ω = (Ω1 + Ω2 + Ω3) / 3, where Ω1, Ω2, and Ω3 are the abnormality indices of heart rate, blood pressure, and hemodynamics, respectively.

[0088] Warning threshold determination unit: Set three-level warning thresholds:

[0089] Level 1 Warning (Low Risk): 0.3 ≤ Ω < 0.5;

[0090] Level II Warning (Medium Risk): 0.5 ≤ Ω < 0.8;

[0091] Level 3 warning (high risk, risk of acute and critical illness): Ω ≥ 0.8; if Ω < 0.3, it is judged as "normal" and no warning is triggered;

[0092] Multi-channel response unit:

[0093] Level 1 alert: When the patient's bedside monitor displays a "low-risk alert," a notification is simultaneously sent to the responsible nurse's mobile app.

[0094] Level 2 warning: Patient information (name, bed number, abnormal indicators) is highlighted on the monitoring screen at the nurse station, triggering an audible and visual alarm at the nurse station and sending a text message to the attending physician;

[0095] Level 3 warning: Initiate the emergency response process, trigger hospital emergency channel notification (emergency department, ICU), push the patient's historical medical records and real-time abnormal data to the emergency team terminal, and automatically dial the patient's family members (if it is a home scenario);

[0096] Early warning recording and retrospective unit: Automatically records the time, abnormal index, response measures and subsequent processing results of each early warning, forming an early warning log (supports export to PDF / Excel format), which is used for clinical review and system parameter optimization.

[0097] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0098] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A cardiovascular and cerebrovascular emergency and critical illness early warning and monitoring system, characterized in that, It includes a patient risk stratification module, a multi-dimensional physiological signal acquisition module, a physiological signal abnormality analysis module, and an early warning triggering and response module. Each module achieves bidirectional communication through a data bus. The patient risk stratification module is used to calculate risk values ​​based on basic patient information and clinical information, classify risk levels, and configure differentiated physiological signal acquisition parameters for different risk levels. The multi-dimensional physiological signal acquisition module is used to acquire at least three types of physiological signals from the patient's heart rate, blood pressure, blood oxygen saturation, blood flow velocity, and vascular elasticity coefficient in real time according to the acquisition parameters, and transmit them to the physiological signal abnormality analysis module after preprocessing. The physiological signal abnormality analysis module is used to analyze the preprocessed physiological signals and calculate three types of abnormal indices: heart rate abnormality index, blood pressure abnormality index, and hemodynamic abnormality index. The early warning triggering and response module is used to calculate the comprehensive anomaly index, determine the early warning level based on the early warning threshold, and execute the corresponding response measures.

2. The early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases according to claim 1, characterized in that, The patient risk stratification module includes a data input unit, a risk value calculation unit, a risk level classification unit, and a data acquisition parameter configuration unit; the data input unit acquires the patient's age, number of underlying diseases, and number of historical attacks of acute and critical cardiovascular and cerebrovascular diseases. The risk value calculation unit uses the formula Calculate the risk value, where For age normalized value, Normalized value of the number of underlying diseases λ1, λ2, λ3 are normalized values ​​of historical seizure counts, and λ1, λ2, λ3 are adjustable weights that satisfy λ1 + λ2 + λ3 = 1; The risk level classification unit sets thresholds R1 = 0.3 and R2 = 0.7 to classify patients into low risk (R < 0.3), medium risk (0.3 ≤ R < 0.7), and high risk (R ≥ 0.7). The data acquisition parameter configuration unit configures a 5-minute data acquisition interval for low-risk patients, a 2-minute data acquisition interval for medium-risk patients, and a 1-minute data acquisition interval for high-risk patients.

3. The early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases according to claim 1, characterized in that, The multi-dimensional physiological signal acquisition module includes an acquisition device interface unit, a signal acquisition control unit, a signal preprocessing unit, and a data buffer and transmission unit. The acquisition device interface unit is compatible with electrocardiogram monitors, non-invasive blood pressure monitors, ultrasonic Doppler flowmeters, and vascular elasticity detectors, and supports wired or wireless data transmission. The signal preprocessing unit uses a wavelet transform denoising algorithm to remove signal interference and normalizes the signal values ​​to the [0,1] interval. The data buffer and transmission unit supports offline storage for ≥72 hours and data transmission latency ≤100ms.

4. The early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases according to claim 1, characterized in that, The physiological signal abnormality analysis module includes a heart rate abnormality analysis submodule, a blood pressure abnormality analysis submodule, and a hemodynamic abnormality analysis submodule. The heart rate abnormality analysis submodule uses the formula Ω1=w1·D HR +w2·(N HR / 9) Calculate the heart rate abnormality index, D HR N represents the resting deviation of heart rate. HR The number of dynamic fluctuations in heart rate is w1 = 0.6, w2 = 0.4; The blood pressure abnormality analysis submodule calculates the blood pressure abnormality index using the formula Ω2=w3·ΔSBP+w4·ΔDBP, where ΔSBP is the systolic blood pressure fluctuation amplitude, ΔDBP is the diastolic blood pressure fluctuation amplitude, w3=0.5, w4=0.5; The hemodynamic abnormality analysis submodule uses the formula Ω3=w5·ΔFV * +w6·ΔE * Calculate the hemodynamic abnormality index, ΔFV * ΔE is the normalized rate of change of blood flow velocity. * The normalized rate of change of vascular elasticity coefficient is w5 = 0.6, w6 = 0.

4.

5. The early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases according to claim 1, characterized in that, The early warning triggering and response module includes a comprehensive anomaly index calculation unit, an early warning threshold determination unit, a multi-channel response unit, and an early warning recording and backtracking unit; The comprehensive anomaly index calculation unit calculates the comprehensive anomaly index using the formula Ω=(Ω1+Ω2+Ω3) / 3; The warning threshold determination unit sets three threshold levels: Level 1 warning 0.3≤Ω<0.5, Level 2 warning 0.5≤Ω<0.8, and Level 3 warning Ω≥0.8; the multi-channel response unit initiates an emergency response process for Level 3 warnings, including triggering emergency channel notifications, pushing data to the emergency team, and calling family members. The warning recording and backtracking unit automatically records warning logs and supports exporting to PDF / Excel format.

6. The early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases according to claim 2, characterized in that, The age normalized value Normalization of the number of underlying diseases Normalized value of historical seizure frequency 7. The early warning and monitoring system for acute and critical cardiovascular and cerebrovascular diseases according to claim 4, characterized in that, Heart rate static deviation The mean of the most recent 10 standardized heart rates is 0.5, which is the normal heart rate standardization baseline. The systolic blood pressure fluctuation amplitude ΔSBP = (max(SBP1,...,SBP5)-min(SBP1,...,SBP5)) / SBP0, where SBP0 is the patient's baseline systolic blood pressure value in the past 72 hours.

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