Intelligent blood pressure monitoring device and method for elderly atrial fibrillation patients

Abstract

This invention relates to an intelligent blood pressure monitoring device and method for elderly patients with atrial fibrillation. The device includes a blood pressure measurement module, an electrocardiogram (ECG) measurement module, and a processing module. The blood pressure measurement module measures the arterial blood pressure data of the target subject; the ECG measurement module collects the ECG data of the target subject and generates ECG data; the processing module aligns the ECG data with the arterial blood pressure data in time, and dynamically adjusts the measurement frequency and duration of the blood pressure measurement module based on changes in the ECG data, selecting arterial blood pressure data that meets the time interval requirements and is less affected by atrial fibrillation as the measurement data. By combining ECG data, this invention can identify the stable period of the heart rhythm, ensuring the reliability and practicality of the measurement results. By dynamically adjusting the measurement frequency and duration and selecting data less affected by atrial fibrillation, this invention effectively reduces unnecessary measurements and improves the accuracy of blood pressure data.

Description

Technical Field

[0001] This invention relates to the field of blood pressure monitoring technology, and in particular to an intelligent blood pressure monitoring device and method for elderly patients with atrial fibrillation. Background Technology

[0002] Patients with atrial fibrillation (AF), especially elderly patients, may exhibit some unique characteristics in terms of blood pressure compared to other patients. Understanding these unique characteristics helps in better monitoring and managing patients' blood pressure, preventing complications, and improving treatment outcomes. Typical characteristics of blood pressure in patients with atrial fibrillation include: (1) Large fluctuations in blood pressure; Atrial fibrillation causes irregular heartbeats and large variations in cardiac output, which easily leads to fluctuations in blood pressure. Due to irregular heart contractions, there may be temporary increases in blood pressure. (2) False hypotension; Due to irregular heartbeats, traditional blood pressure measurement methods may be inaccurate, resulting in measured values ​​lower than the actual values. This condition is called false hypotension. Although some measurements show low blood pressure, the actual effective blood pressure may be normal or high. (3) Comorbid hypertension; Hypertension combined with atrial fibrillation: Hypertension is one of the important risk factors for atrial fibrillation. Elderly patients often suffer from both hypertension and atrial fibrillation, further increasing the difficulty of management. (4) Increased pulse pressure; Atrial fibrillation causes inconsistent cardiac output with each contraction, which may lead to an increased pulse pressure difference between systolic and diastolic blood pressure. This situation requires special attention because an increased pulse pressure may increase the risk of cardiovascular events. (5) Nocturnal blood pressure changes; some patients with atrial fibrillation may experience hypertension at night. (6) No blood pressure drop: some patients do not experience a natural drop in blood pressure at night like normal people, increasing the risk of cardiovascular events.

[0003] Due to significant blood pressure fluctuations, patients with atrial fibrillation require more frequent blood pressure monitoring, typically using smart blood pressure monitoring devices for continuous monitoring. To obtain more accurate blood pressure data, multiple measurements are taken and averaged, especially under conditions of irregular heartbeats. However, the accuracy and reliability of smart blood pressure monitoring devices may be affected by irregular heartbeats. The irregular heart rate in patients with atrial fibrillation can increase the measurement error of traditional blood pressure monitors. Therefore, even averaging multiple measurements may not completely eliminate measurement errors caused by irregular heartbeats. This necessitates more advanced data processing algorithms and analysis tools to correctly interpret the measurement results and avoid misinterpretations and misdiagnoses.

[0004] Patent document CN117017246A discloses a blood pressure measurement system, method, and apparatus for determining the blood pressure of patients with atrial fibrillation based on arterial blood pressure and beat-by-beat blood pressure information, thereby improving the accuracy of blood pressure measurement in these patients. The blood pressure measurement system provided in this application includes a blood pressure monitor. The system further includes: an atrial fibrillation detection module, used to acquire arterial blood pressure information of the target over a preset detection period using the blood pressure monitor, determine whether the target has atrial fibrillation within the preset detection period based on the arterial blood pressure information, and notify the blood pressure measurement control module of the determination result; and a blood pressure measurement control module, used to control the blood pressure monitor to continue detecting the target for a preset duration when the determination result output by the atrial fibrillation detection module indicates that the target has atrial fibrillation within the preset detection period, acquire beat-by-beat blood pressure information of the target within the preset duration, and determine the target's systolic and / or diastolic blood pressure based on the beat-by-beat blood pressure information. For patients with atrial fibrillation, this blood pressure measurement system relies on the arterial blood pressure information acquired by the blood pressure monitor to determine whether atrial fibrillation has occurred. Because atrial fibrillation can cause irregular blood pressure waveforms, this waveform-based atrial fibrillation detection method may result in false positives or false negatives. During atrial fibrillation, irregular heart rhythms can lead to significant fluctuations in beat-by-beat blood pressure data, potentially affecting the reliability of this information. Furthermore, if atrial fibrillation causes a significant decrease in cardiac output, beat-by-beat blood pressure data may not accurately reflect the patient's true blood pressure level. The duration and severity of atrial fibrillation can vary considerably among patients, and the preset detection duration may not cover all possible blood pressure fluctuations. Therefore, the blood pressure data measured by this system still contains errors, and patients with atrial fibrillation cannot determine whether their blood pressure readings are accurate.

[0005] The patent document with publication number CN105662382A discloses a display method and system for an oscillometric electronic blood pressure monitor; the display method includes: sampling the cuff pressure data during the oscillometric blood pressure measurement process to obtain the cuff pressure sampling data; extracting the oscillation pressure data of the artery at the measured site from the sampling data; drawing the test oscillation waveform according to the correspondence between the oscillation pressure data and the measurement time, and displaying it. The display method of this invention, by sampling the cuff pressure data and the oscillation pressure data of the artery at the measured site, graphically displays the oscillation waveform of the artery under the cuff pressure. The measurer can intuitively perceive the oscillation of the artery at the measured site under different pressure conditions during the entire measurement process, thereby timely detecting interference or abnormalities in the measurement process, which helps to make a correct diagnosis. However, if the system is used to measure the blood pressure of patients with atrial fibrillation, the following problems may occur: (1) The heartbeat of patients with atrial fibrillation is usually irregular, which will lead to irregular changes in the oscillation waveform and make it difficult to form a stable waveform. Irregular waveforms may make it difficult for blood pressure monitors to accurately identify the correspondence between cuff pressure and arterial oscillation pressure, thus affecting the accuracy of measurement results. (2) Due to the irregular heart rhythm caused by atrial fibrillation, the pulse interval time becomes uneven, and the pulse wave amplitude varies greatly. The oscillometric method relies on a uniform pulse interval time to extract stable oscillation pressure data. Uneven pulse intervals will interfere with data extraction and analysis, leading to measurement errors. (3) Atrial fibrillation causes large fluctuations in arterial oscillation pressure data, and even significant changes in a short period of time. This volatility makes it difficult for blood pressure monitors to determine accurate systolic and diastolic pressure values, because traditional algorithms assume that the changes in oscillation pressure data are relatively stable.

[0006] To address the aforementioned deficiencies, this invention provides an intelligent blood pressure monitoring device and method for elderly patients with atrial fibrillation, in order to avoid obtaining erroneous blood pressure data caused by false hypotension.

[0007] Furthermore, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making this invention, but due to space limitations, not all details and contents were listed in detail. However, this does not mean that the present invention does not possess the features of these prior art. On the contrary, the present invention already possesses all the features of the prior art, and the applicant reserves the right to add relevant prior art to the background art. Summary of the Invention

[0008] Due to significant blood pressure fluctuations, patients with atrial fibrillation require more frequent blood pressure monitoring, typically achieved through continuous monitoring using smart blood pressure monitoring devices. To obtain more accurate blood pressure data, especially in cases of arrhythmia, multiple measurements and averages are necessary. The accuracy and reliability of smart blood pressure monitoring devices may be affected by irregular heartbeats. Because of the irregular heart rate in patients with atrial fibrillation, the measurement error of traditional blood pressure monitors may increase. Therefore, even averaging multiple measurements may not completely eliminate measurement errors caused by irregular heartbeats. This necessitates the use of more advanced data processing algorithms and analysis tools to accurately interpret measurement results and prevent misinterpretation and misdiagnosis.

[0009] To address the shortcomings of existing technologies, this invention provides, from a first aspect, an intelligent blood pressure monitoring device for elderly patients with atrial fibrillation, comprising a blood pressure measurement module, an electrocardiogram (ECG) measurement module, and a processing module. The blood pressure measurement module measures the arterial blood pressure data of the target subject; the ECG measurement module collects the target subject's electrocardiogram (ECG) data and generates ECG data; the processing module aligns the ECG data with the arterial blood pressure data in time, and dynamically adjusts the measurement frequency and duration of the blood pressure measurement module based on changes in the ECG data, selecting arterial blood pressure data that meets the time interval requirements and is less affected by atrial fibrillation as the measurement data.

[0010] Because patients with atrial fibrillation have irregular heart rhythms, traditional fixed-frequency measurements often fail to capture accurate blood pressure values. By combining electrocardiogram (ECG) data, this device can identify and measure periods of stable heart rhythm, ensuring the reliability and practicality of the measurement results. This invention effectively reduces unnecessary measurements and improves the accuracy of blood pressure data by dynamically adjusting the measurement frequency and duration and selecting data less affected by atrial fibrillation.

[0011] According to a preferred embodiment, the processing module determines the stability of the RR interval in the electrocardiogram data, and determines the arterial blood pressure value in real time when the RR interval is stable; and / or the processing module determines at least one arterial blood pressure value and its average value during the period when the RR interval is stable.

[0012] The stability of the RR interval directly reflects the stability of the heart rate. When the heart rate is stable, blood pressure is also relatively stable, so measurements taken during this period yield more accurate data. Furthermore, calculating the average value further enhances the stability and representativeness of the data, reducing potential errors from single measurements. By performing immediate measurements when the RR interval is stable, this invention avoids the influence of arrhythmias on blood pressure data, improving the accuracy of the measurement data.

[0013] According to a preferred embodiment, the processing module selects the arterial blood pressure value when the P wave in the electrocardiogram data is clear and continuous.

[0014] The stability of the RR interval directly reflects the stability of the heart rate. When the heart rate is stable, blood pressure is also relatively stable, so measurements taken during this period can obtain more accurate data. Furthermore, calculating the average value further enhances the stability and representativeness of the data, reducing potential errors from a single measurement.

[0015] According to a preferred embodiment, the processing module identifies atrial fibrillation based on electrocardiogram data and determines arterial blood pressure data during the stable period after the atrial fibrillation cycle ends.

[0016] After an atrial fibrillation cycle ends, cardiac activity tends to stabilize, and blood pressure measurements taken at this time better reflect the patient's actual blood pressure status. By identifying the atrial fibrillation cycle and selecting a stable period for measurement, a more accurate blood pressure value can be captured. Therefore, measuring blood pressure during the stable period after the atrial fibrillation cycle ends can reduce the interference of arrhythmia on blood pressure measurement, thereby improving the reliability of the measurement results.

[0017] According to a preferred embodiment, the processing module filters the instantaneously determined arterial blood pressure data based on a heart rate threshold and a heart rate variability threshold, thereby deleting inaccurate arterial blood pressure data.

[0018] By filtering inaccurate blood pressure data, the processing module effectively eliminates abnormal data, ensuring the accuracy and consistency of the final measurement results. This is because heart rate thresholds and heart rate variability thresholds help identify unreliable data caused by large heart rate fluctuations or high heart rate variability. By setting these thresholds, the processing module can identify and exclude this data, thereby improving the overall data quality.

[0019] According to a preferred embodiment, when the RR interval change rate of the electrocardiogram data increases, the processing module increases the measurement frequency of the blood pressure measurement module to obtain more information on arterial blood pressure changes.

[0020] An increase in the RR interval variability rate usually indicates greater heart rate variability. Increasing the measurement frequency can more accurately reflect real-time changes in blood pressure. This method is particularly suitable for patients with atrial fibrillation, as their RR interval variability rate is typically high; increasing the measurement frequency can improve the accuracy of diagnosis and treatment. Therefore, increasing the measurement frequency when the RR interval variability rate increases captures more details of blood pressure changes, providing more comprehensive information for subsequent data analysis.

[0021] According to a preferred embodiment, when the P wave amplitude of the electrocardiogram data fluctuates significantly, the processing module extends the measurement time of the blood pressure measurement module to ensure that more stable arterial blood pressure data is obtained.

[0022] The fluctuation of P wave amplitude directly reflects the stability of atrial activity. When P wave amplitude fluctuates significantly, atrial activity may be unstable, and blood pressure measurements may be inaccurate. By extending the measurement time, stable blood pressure values ​​can be better captured in patients with atrial fibrillation. Therefore, by extending the measurement time when P wave amplitude fluctuations are significant, stable blood pressure data can still be obtained under conditions of large fluctuations, thus improving the reliability of the measurement.

[0023] According to a preferred embodiment, the processing module dynamically adjusts the measurement frequency and duration of the blood pressure measurement module based on the heart rate variability in the electrocardiogram data. When the heart rate variability shows a decreasing trend, the processing module reduces the measurement frequency of the blood pressure measurement module and extends the duration of a single measurement to improve the measurement comfort of the target subject.

[0024] Heart rate variability (HRV) is an indicator of heart rate fluctuations. When HRV decreases, heart rate stabilizes, and blood pressure tends to stabilize as well. Therefore, reducing the frequency of measurements can minimize patient discomfort and increase comfort. Conversely, extending the duration of each measurement helps obtain more accurate and stable blood pressure data when the heart rate is stable. This is particularly important for patients with atrial fibrillation, as their heart rate fluctuates significantly, and traditional frequent measurements may lead to inaccurate data and discomfort. This dynamic adjustment method allows for more effective monitoring of blood pressure, improving the scientific validity of measurements and patient compliance. Therefore, when HRV decreases, heart rate tends to stabilize, and blood pressure is relatively stable. In this case, reducing the measurement frequency will not affect the accuracy of blood pressure data, while extending the duration of each measurement ensures more stable data. This adjustment not only reduces the discomfort caused by frequent measurements but also improves the reliability of blood pressure monitoring.

[0025] This invention provides, from a second aspect, an intelligent blood pressure monitoring method for elderly patients with atrial fibrillation. The method includes: measuring arterial blood pressure data of the target subject; acquiring electrocardiogram (ECG) data of the target subject and generating ECG data; aligning the ECG data with the arterial blood pressure data in time, and dynamically adjusting the measurement frequency and duration of the blood pressure measurement module based on changes in the ECG data, selecting arterial blood pressure data that meets the time interval requirements and is less affected by atrial fibrillation as the measurement data. By aligning the ECG data with the arterial blood pressure data in time, it ensures that the acquired ECG changes accurately correspond to the corresponding blood pressure measurement data. This alignment method guarantees data consistency, making the dynamic adjustment of measurement frequency and duration more scientifically based. The blood pressure measurement frequency and duration are dynamically adjusted according to real-time changes in the ECG data. This method ensures that the measurement frequency is increased when the ECG data indicates a relatively stable heart rate, and decreased when atrial fibrillation is severe, while the duration of each measurement is prolonged, thus ensuring the stability and accuracy of the measurement data. This invention utilizes an intelligent blood pressure monitoring method, specifically designed for elderly patients with atrial fibrillation. It dynamically adjusts the measurement frequency and duration of the blood pressure measurement module based on changes in electrocardiogram (ECG) data, ensuring blood pressure measurements are taken within time intervals where the impact of atrial fibrillation is minimal. Specifically, when ECG data shows stable RR intervals, minimal P wave changes, or relatively stable atrial fibrillation, the system automatically selects these time periods for arterial blood pressure measurement. This dynamic adjustment mechanism significantly improves measurement frequency because it leverages real-time changes in the patient's ECG data, avoiding ineffective or inaccurate measurements during periods of severe atrial fibrillation.

[0026] According to a preferred embodiment, the method further includes selecting arterial blood pressure data or calculating the average value of arterial blood pressure data based on RR interval stability, P wave changes, and / or atrial fibrillation status in the electrocardiogram (ECG) data. When the ECG data indicates a stable heart rate and minimal atrial fibrillation influence, the selected blood pressure data better reflects the patient's true blood pressure level. By analyzing RR interval stability and P wave changes, the system can identify and filter out data points significantly affected by atrial fibrillation, thereby improving the accuracy of blood pressure measurement. Furthermore, dynamically adjusting the measurement duration ensures sufficient effective data is acquired within key time periods, further enhancing the reliability of the measurement. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the hardware connection relationship of the intelligent blood pressure monitoring device for elderly patients with atrial fibrillation provided by the present invention in the hospitalization state;

[0028] Figure 2 This is a schematic diagram of the hardware connection relationship of the intelligent blood pressure monitoring device for elderly patients with atrial fibrillation provided by the present invention in a home setting;

[0029] Figure 3This is a schematic diagram of the display interface of the terminal of the intelligent blood pressure monitoring device for elderly patients with atrial fibrillation provided by the present invention;

[0030] Figure 4 This is a schematic diagram of the composition structure of the intelligent blood pressure monitoring device for elderly patients with atrial fibrillation provided by the present invention;

[0031] Figure 5 This is a logical diagram illustrating the operating principle of the intelligent blood pressure monitoring device for elderly patients with atrial fibrillation provided by the present invention.

[0032] Figure 6 These are aortic pressure curves for patients with atrial fibrillation and patients with sinus rhythm.

[0033] List of reference numerals

[0034] 100: Electrocardiogram (ECG) measurement module; 200: Blood pressure measurement module; 300: Processing module; 310: Reading module; 320: Adjustment module; 400: Terminal; 410: ECG display interface; 420: Arterial blood pressure value display interface. Detailed Implementation

[0035] The following is a detailed explanation with reference to the accompanying drawings.

[0036] Atrial fibrillation (AF) is a common cardiac arrhythmia involving rapid and irregular beatings of the upper chambers of the heart (atria). In AF, the atrial firing rate abnormally increases to 350 to 600 beats per minute, causing the atria to lose their ability to contract in a coordinated manner, and the ventricular beats become irregular.

[0037] Symptoms of atrial fibrillation may include palpitations, chest discomfort, shortness of breath, fatigue, dizziness, and pre-syncope symptoms. Due to the rapid, irregular fibrillation of the atria, blood clots can easily form within the atria, increasing the risk of complications such as embolic stroke.

[0038] Treatment for atrial fibrillation typically involves using medication to control the ventricular rate, preventing thromboembolism, and sometimes converting the atrial fibrillation to a normal sinus rhythm through medication or cardiopulmonary bypass. Furthermore, the diagnosis of atrial fibrillation primarily relies on an electrocardiogram (ECG), whose characteristic features include the disappearance of P waves and the appearance of fine, irregular f waves (fibrillation waves) between QRS complexes, with absolutely irregular RR intervals.

[0039] It is worth noting that the incidence of atrial fibrillation increases with age, reaching a high proportion in people over 80 years of age. Atrial fibrillation is classified into paroxysmal, persistent, long-term persistent, and permanent types, and different types of atrial fibrillation require different treatment and management strategies.

[0040] Persistent atrial fibrillation is an independent risk factor for orthostatic hypotension, especially in patients aged ≥60 years and those with uncontrolled hypertension. Poor blood pressure control can worsen symptoms and increase the frequency of attacks in patients with atrial fibrillation, and reduce the success rate of cardioversion. Accurate blood pressure measurement is a prerequisite for effective blood pressure management in patients with atrial fibrillation.

[0041] Hemodynamic characteristics of patients with atrial fibrillation include: irregular ventricular rate leading to significant fluctuations in intra-arterial pressure. Strokes following longer RR intervals have higher intra-arterial pressure, while strokes following shorter RR intervals have lower intra-arterial pressure, sometimes even to the point of being unmeasurable. Figure 6 The aortic pressure curves of patients with atrial fibrillation and patients with sinus rhythm are shown, and it can be seen that there are significant differences in the intra-arterial pressure curves between the two.

[0042] However, current electrocardiograms (ECGs) are only used to evaluate the accuracy of blood pressure measurement devices. For example, clinicians can evaluate the accuracy of oscillometric systolic blood pressure measurements by referring to the ventricular rate (auscultation for 30–60 seconds) and pulse rate variability across three blood pressure measurements in patients with atrial fibrillation. Oscillometric systolic blood pressure readings are highly reliable when the ventricular rate is <90 or 100 beats / min and the pulse rate variability across three measurements is <10 beats / min. However, the large size and high cost of professional ECG equipment limit their use in home settings.

[0043] For patients with atrial fibrillation, this may prevent them from obtaining electrocardiogram (ECG) data in a home environment, making it impossible to correlate blood pressure measurements with cardiac status. This can increase the error in blood pressure measurements and affect the accuracy of blood pressure monitoring. Patients with atrial fibrillation can only obtain accurate arterial blood pressure data by relying on professional medical personnel to measure their blood pressure.

[0044] While some portable electrocardiogram (ECG) measurement devices exist, patients with atrial fibrillation cannot directly link ECG data with blood pressure monitors. Furthermore, newly emerging integrated ECG and blood pressure devices simply display both ECG and arterial blood pressure values ​​on the device itself or on a mobile device (such as a smartphone). The displayed arterial blood pressure values ​​are those for general patients; they are not specially selected, and the measurement frequency and duration are not personalized. Therefore, integrated ECG and blood pressure devices measure arterial blood pressure in the same way as ordinary blood pressure monitors, and cannot provide accurate arterial blood pressure values ​​for patients with atrial fibrillation.

[0045] Therefore, the present invention aims to solve the problem of how to provide a device and system suitable for patients with atrial fibrillation that can reduce the number of measurements while obtaining accurate arterial blood pressure data.

[0046] This invention provides a portable blood pressure measuring device suitable for patients with atrial fibrillation, ideal for their home environment. This device enables patients with atrial fibrillation to achieve accurate blood pressure measurement at home, reducing reliance on professional medical personnel.

[0047] This invention also provides a blood pressure measurement system and method capable of interacting with hospital systems. When the analysis results of blood pressure measurement data or electrocardiogram data from a patient with atrial fibrillation indicate a high health risk, the system can promptly send relevant information, including warnings and medical advice, to the patient via terminal 400, helping the patient take timely measures to avoid potential dangers. This device and method not only improve the accuracy of blood pressure monitoring but also enhance the patient's self-management ability, contributing to improved quality of life for patients with atrial fibrillation.

[0048] This embodiment provides an intelligent blood pressure monitoring device for elderly patients with atrial fibrillation, such as... Figures 1 to 4 As shown, the system includes a blood pressure measurement module 200, an electrocardiogram (ECG) measurement module 100, and a processing module 300. The blood pressure measurement module 200 and the ECG measurement module 100 establish communication connections with the processing module 300 via wired or wireless means. Preferably, the wireless connection includes WiFi communication, Bluetooth communication, etc. Preferably, the blood pressure measurement module 200 and the ECG measurement module 100 also include an NFC communication module. When the blood pressure measurement module 200 and the ECG measurement module 100 are close to the terminal 400, and driven by the NFC communication module within the terminal 400, the blood pressure measurement module 200 and the ECG measurement module 100 respectively transmit the measured data to the terminal 400 via NFC communication.

[0049] Preferably, such as Figure 1 and Figure 5As shown, the blood pressure measurement module 200 is used to measure arterial blood pressure data of a target subject. The blood pressure measurement module 200 includes a pressure sensor, an inflation pump, a deflation valve, a cuff, a microcontroller unit (MCU), a wireless transmission module, a power supply, and a wired communication port. The inflation pump and deflation valve are respectively located at the air inlet and outlet of the cuff. The pressure sensor is connected to the MCU to send the measured arterial blood pressure data to the MCU and adjusts the measurement frequency and adjustment duration based on the control commands from the MCU. The MCU is connected to the wireless transmission module and the wired communication port to enable information interaction with the outside world. The inflation pump and deflation valve are connected to the MCU to inflate and deflate the pressure at a specified speed based on the control commands sent by the MCU. The power supply is connected to the pressure sensor, inflation pump, deflation valve, MCU, wireless transmission module, and wired communication port to provide power to each component.

[0050] A pressure sensor, typically a strain gauge or piezoelectric sensor, is used to detect and record changes in arterial blood pressure. An inflation pump and deflation valve automatically control the inflation and slow deflation of the cuff to measure arterial fluctuations at different pressures. The cuff is an inflatable band that wraps around the upper arm to transmit and receive pressure signals from the artery. A microcontroller unit (MCU) receives and processes signals from the pressure sensor and controls the operation of the inflation pump and deflation valve. A wireless transmission module, such as Bluetooth or Wi-Fi, transmits the measured arterial blood pressure data to the processing module 300. Power supplies, including a battery and power management circuitry, ensure continuous power to all components within the blood pressure measurement module 200.

[0051] like Figure 1 and Figure 5 As shown, the electrocardiogram (ECG) measurement module 100 is used to collect ECG data from the target object and generate ECG data. Unlike traditional ECG measurement modules 100, such as... Figure 2 As shown, the electrocardiogram measurement module 100 in this invention can be a portable electrocardiogram measurement module 100 for home use by patients with atrial fibrillation.

[0052] The electrocardiogram (ECG) measurement module 100 may include several electrodes, a signal amplification circuit module, and a microprocessor. Preferably, the number of electrodes is at least one. Generally, the number of electrodes is two. The electrodes can be attached to the body or worn by a wearable device. Preferably, the ECG measurement module 100 also includes a memory for storing ECG data. The signal amplification circuit module and the microprocessor are installed in a housing and are used to capture ECG signals and form ECG data in a time-related manner. The ECG measurement module 100 has a power supply to provide power to the electrodes, signal amplification circuit module, microprocessor, memory, and other devices. Preferably, the ECG measurement module 100 can also be installed in an auxiliary wearable device so that patients with atrial fibrillation can wear the ECG measurement module 100 near their heart. The ECG measurement module 100 also includes a wireless transmission module and a wired transmission port. The wireless transmission module is used to send ECG data to the processing module 300 in real time. The wired transmission port is used to send ECG data to the processing module 300 in real time via an information transmission line. Preferably, as Figure 2 As shown, the processing module 300 can be a hospital server, receiving electrocardiogram (ECG) data and arterial blood pressure data via a terminal 400. The terminal 400 can be a portable device such as a computer, mobile phone, tablet, smartwatch, or smartphone, which can remotely transmit the received ECG and arterial blood pressure data to the hospital server for arterial blood pressure data determination by running the corresponding application module.

[0053] like Figure 1 , Figure 2 and Figure 5 As shown, the processing module 300 executes the intelligent blood pressure monitoring method for elderly patients with atrial fibrillation according to the present invention. Figure 5 As shown, the processing module 300 is used to analyze and determine accurate arterial blood pressure data. Specifically, the processing module 300 can be a server, a dedicated integrated chip, or a processor capable of analyzing electrocardiogram (ECG) data and arterial blood pressure data. The processing module 300 may also be connected to a memory to store arterial blood pressure data and ECG data measured each time by atrial fibrillation patients, and may even store atrial fibrillation cycle data and arterial pressure curves of atrial fibrillation patients.

[0054] In this invention, such as Figure 5 As shown, after receiving the data, the processing module 300 aligns the electrocardiogram data with the arterial blood pressure data in time to ensure that the collected electrocardiogram changes can accurately correspond to the corresponding blood pressure measurement data.

[0055] For example, when the processing module 300 receives electrocardiogram (ECG) data and arterial blood pressure data, it checks the timestamp of each data point. By comparing the timestamps, it ensures that the ECG data and arterial blood pressure data at the same time correspond. If there is a timestamp inconsistency, the processing module 300 performs time correction to make the timestamps of the two data points consistent.

[0056] In some cases, the sampling frequencies of electrocardiogram (ECG) data and arterial blood pressure data may differ. To achieve time alignment, the processing module 300 interpolates the data with the lower sampling frequency to give it the same time resolution as the data with the higher sampling frequency. This way, data alignment can be achieved even if there are differences in sampling intervals in the original data.

[0057] Because there is a certain delay in the physiological propagation of electrocardiogram (ECG) and arterial blood pressure signals, the processing module 300 performs delay compensation on one of the signals according to a pre-set delay parameter. This ensures the true temporal correspondence between the two signals and improves the accuracy of data analysis.

[0058] Preferably, if the electrocardiogram data and arterial blood pressure data are acquired through different devices, the processing module 300 may use a synchronization trigger signal to ensure that data acquisition from both devices begins at the same time. This synchronization trigger signal can be an external event (such as pressing a button) or an internal clock signal, used to coordinate the data acquisition process of the different devices.

[0059] After time alignment is completed, the processing module 300 may smooth the data to reduce the impact of noise and outliers. This can be achieved through filters, moving averages, or other statistical methods, thereby improving data quality and ensuring an accurate correspondence between ECG changes and blood pressure measurements.

[0060] As described above, the processing module 300 ensures the temporal consistency between electrocardiogram (ECG) data and arterial blood pressure data through methods such as timestamp alignment, interpolation alignment, delay compensation, synchronization triggering, and data smoothing, thereby enabling the collected ECG changes to accurately correspond to the corresponding blood pressure measurement data.

[0061] This alignment method ensures data consistency, making the dynamic adjustment of measurement frequency and duration more scientifically based.

[0062] The processing module 300 dynamically adjusts the measurement frequency and duration of the blood pressure measurement module 200 based on changes in electrocardiogram data, and selects arterial blood pressure data that meets the time interval requirements and is less affected by atrial fibrillation as the measurement data.

[0063] Specifically, the processing module 300 includes a reading module 310 and an adjustment module 320. The reading module 310 reads data such as RR interval, P wave, atrial fibrillation status, heart rate, and heart rate variability from the electrocardiogram (ECG) data. Preferably, the processing module 300 may further include a data preprocessing module for filtering the received ECG data to remove noise and interference. The preprocessed ECG data is then read by the reading module 310.

[0064] The RR interval is the time interval between two consecutive R waves on an electrocardiogram (ECG). Normally, the faster the heart rate, the shorter the RR interval; the slower the heart rate, the longer the RR interval.

[0065] On an electrocardiogram (ECG), the P wave represents atrial depolarization, the electrical activity of atrial contraction. A normal P wave should be a positive wave, typically upright in leads I, II, and aVF, and inverted in lead aVR. The duration of a normal P wave is usually no more than 0.12 seconds (or 120 milliseconds). In standard leads, the amplitude of the P wave is usually no more than 2.5 mm (or 0.25 mV).

[0066] When atrial fibrillation occurs, the ventricular rate (i.e., the rate at which the ventricles respond to rapid atrial excitation) is usually rapid and irregular, generally between 100 and 180 beats per minute, but can be slower or faster. P waves disappear, RR intervals are irregular, and the QRS complex may widen. The reading module 310 can read and determine the duration of atrial fibrillation based on the electrocardiogram data.

[0067] Under normal circumstances, the relationship between the RR interval and heart rate is as follows:

[0068]

[0069] RR i HR indicates the time interval between two consecutive R waves. i This indicates the number of heartbeats per minute.

[0070] The duration of a normal P wave is:

[0071]

[0072] t Pi The waveform P represents atrial depolarization. i The duration.

[0073] In standard leads, the P-wave amplitude P ABPi satisfy:

[0074]

[0075] P ampiThis indicates the maximum amplitude of the P wave in an electrocardiogram (ECG). ABPi This refers to the specific measured value or parameter representing the amplitude of the P-wave.

[0076] The ventricular rate range during atrial fibrillation is: 100 ≤ HR AF ≤180bpm(4).

[0077] HR AF This indicates the ventricular rate.

[0078] The processing module 300 also includes an adjustment module 320. The adjustment module 320 and the reading module 310 can transmit data to each other. The adjustment module 320 is used to determine the timing of arterial blood pressure data selection in real time based on electrocardiogram data and to generate control commands for the blood pressure measurement module 200. When an early warning is required, the adjustment module 320 generates an early warning command, controlling the terminal 400 to perform alarm operations such as atrial fibrillation warning and danger level warning.

[0079] Specifically, the timing of arterial blood pressure data selection by the adjustment module 320 is t. ABPi The calculation formula is:

[0080]

[0081] HRV i AF represents heart rate fluctuation data. dur This indicates the duration of atrial fibrillation. k1 to k4 represent the first regulation coefficient.

[0082] Adjustment module 320 calculates the measurement frequency f measure The formula is:

[0083]

[0084] Adjustment module 320 calculates measurement time t measure The formula is:

[0085] t measure =β1·RR i +β2·HR i +β3·HRV i +β4·AF dur (7).

[0086] β1 to β4 represent the second adjustment coefficients.

[0087] For example, the present invention provides two sets of exemplary data, as shown in the table below.

[0088]

[0089] Data group 1 had no atrial fibrillation, AF dur =0.

[0090] Data set 2 showed atrial fibrillation lasting 2 seconds.

[0091] Preferably, such as Figure 3 As shown, the user interface of terminal 400 includes an electrocardiogram (ECG) display interface 410 and an arterial blood pressure value display interface 420. The ECG display interface 410 is used to display real-time or historical ECG values. The arterial blood pressure value display interface 420 is used to display real-time or historical arterial blood pressure values.

[0092] The adjustment module 320 is trained using electrocardiogram sample data and time-aligned arterial blood pressure sample data from several atrial fibrillation patients. Preferably, the adjustment module 320 is a time series prediction model. The time series prediction model is preferably a time series model such as LSTM (Long Short-Term Memory) or GRU (Gated Recurrent Unit). The algorithm of the time series prediction model includes mean squared error (MSE) or mean absolute error (MAE) to minimize the time series prediction error.

[0093] The sample data, labeled with RR interval, P wave, atrial fibrillation events and corresponding arterial blood pressure data, is input into the adjustment module 320 to ensure the consistency of time points between the electrocardiogram data and the arterial blood pressure data. The training adjustment module 320 outputs the selection timing of the arterial blood pressure data.

[0094] According to a preferred embodiment, the adjustment module 320 in the processing module 300 determines the stability of the RR interval in the electrocardiogram data, and determines the arterial blood pressure value in real time when the RR interval is stable.

[0095] A preset time window is used, with each window containing a certain number of RR intervals. A time window refers to a period of time preceding a given moment. RR intervals are extracted from the ECG data within each time window. RR interval stability is calculated by determining the standard deviation of the RR intervals within each time window; a smaller standard deviation indicates higher stability. A standard deviation threshold is set. If the standard deviation of the RR intervals within a given time window is less than the set threshold, the RR intervals within that time window are considered stable.

[0096] As the electrocardiogram (ECG) data dynamically changes, the stability of the RR interval within the preset time window also changes dynamically. Preferably, when the RR interval is determined to be stable, the adjustment module 320 in the processing module 300 immediately determines at least one arterial blood pressure value. Preferably, multiple arterial blood pressure values ​​are dynamically acquired, and the acquisition time interval between adjacent arterial blood pressure values ​​is at least 1 minute, allowing the processing module 300 to calculate the average arterial blood pressure. It should be noted that the average arterial blood pressure calculated here is used to verify the real-time arterial blood pressure value and is not a mandatory step. In this invention, the processing module 300 acquires multiple real-time arterial blood pressure values, which also facilitates the selection of the more accurate one based on additional conditions.

[0097] For example, let's define a time window as W, where each window contains N RR intervals. A time window refers to a period of time preceding this point in time. The RR intervals (RR1, RR2, ... RR) are extracted from the ECG data within each time window. N ).

[0098] Calculate the standard deviation σ of the RR interval within each time window. RR .

[0099]

[0100] The average RR interval within the time window is:

[0101]

[0102] If the standard deviation σ of the RR interval within a certain time window RR If the interval is less than the set standard deviation threshold, the RR interval within that time window is considered stable.

[0103]

[0104] σ th This represents the standard deviation threshold.

[0105] When the RR interval is determined to be stable, the adjustment module 320 in the processing module 300 immediately determines at least one arterial blood pressure value (BP).

[0106] When the RR interval is stable, multiple arterial blood pressure values ​​BP1, BP2, ... BP are dynamically acquired. M Set the time interval for collecting adjacent arterial blood pressure values ​​to at least 1 minute.

[0107] Calculate the average arterial blood pressure The formula is:

[0108]

[0109] M represents the number of arterial blood pressure values, and j represents the index of the arterial blood pressure value. BP j This represents the j-th arterial blood pressure value.

[0110] The stability of the RR interval directly reflects the stability of the heart rate. When the heart rate is stable, blood pressure is also relatively stable, so measurements taken during this period yield more accurate data. Furthermore, calculating the average value further enhances the stability and representativeness of the data, reducing potential errors from single measurements. By performing immediate measurements when the RR interval is stable, this invention avoids the influence of arrhythmias on blood pressure data, improving the accuracy of the measurement data.

[0111] According to a preferred embodiment, the adjustment module 320 in the processing module 300 selects the arterial blood pressure value in real time when the P wave in the electrocardiogram data is clear and continuous.

[0112] The adjustment module 320 dynamically determines the clarity of the P wave based on electrocardiogram data. Specifically, the adjustment module 320 calculates the amplitude of the P wave. An amplitude threshold is set; P waves with an amplitude greater than this threshold are considered clear. The adjustment module 320 analyzes the morphological characteristics of the P wave, such as the rising slope and falling slope, to ensure that the P wave morphology conforms to normal standards.

[0113] The adjustment module 320 calculates the time interval between adjacent P waves in real time. A time interval threshold is set to ensure that the time interval between P waves is within the normal range. During real-time monitoring, if the P waves remain clear and the time interval is stable, the P waves are considered continuous.

[0114] At the point in time when the P wave is clear and continuous, the adjustment module 320 immediately generates a control command, instructing the blood pressure measurement module 200 to measure the arterial blood pressure value. The corresponding arterial blood pressure value is recorded in real time. The P wave characteristics, time points, and arterial blood pressure values ​​are stored in a correlated manner.

[0115] For example, the adjustment module 320 calculates the amplitude A of the P wave. P A th This represents the amplitude threshold.

[0116] A P =max(P(t))-min(P(t)) (11).

[0117] A P >A th P(t) is the P-wave portion of the electrocardiogram signal at time t.

[0118] Set an amplitude threshold A th P waves with amplitudes greater than this threshold are considered clear.

[0119] Adjustment module 320 analyzes the rising slope S of the P wave. up and the descending slope S down Set a threshold S for the rising slope that meets normal standards. up-th and the descent slope threshold S down-th .

[0120] Ascent slope S up The calculation formula is:

[0121]

[0122] t1 is the starting point of the upward phase, and t2 is the ending point of the upward phase. Between these two points, the amplitude of the P wave increases.

[0123] Descent slope S down The calculation formula is:

[0124]

[0125] S up ≥S up-th And S down ≤S down-th .

[0126] t3 is the starting point of the downward phase, and t4 is the ending point of the downward phase. Between these two points, the amplitude of the P wave decreases.

[0127] The adjustment module 320 calculates the time interval T between adjacent P waves in real time. PP , defined as the time difference between two adjacent P-wave peaks: T PP =t i+1 -t i (14).

[0128] T min-th ≤T PP ≤T max-th .

[0129] t i T represents the time of the peak of the i-th P-wave. min-th T represents the minimum time interval threshold. max-th This represents the maximum time interval threshold.

[0130] During real-time monitoring, if the P wave remains clear and the time interval is stable, the P wave is considered continuous: that is, (A P >A th )∧(T min-th ≤T PP ≤T max-th At this time, the P wave is continuous.

[0131] According to a preferred embodiment, the processing module 300 identifies atrial fibrillation based on electrocardiogram data. During the stable period after the atrial fibrillation cycle ends, the processing module 300 determines arterial blood pressure data.

[0132] After an atrial fibrillation cycle ends, cardiac activity tends to stabilize, and blood pressure measurements taken at this time better reflect the patient's actual blood pressure status. By identifying the atrial fibrillation cycle and selecting a stable period for measurement, a more accurate blood pressure value can be captured. Therefore, measuring blood pressure during the stable period after the atrial fibrillation cycle ends can reduce the interference of arrhythmia on blood pressure measurement, thereby improving the reliability of the measurement results.

[0133] According to a preferred embodiment, the processing module 300 filters the instantaneously determined arterial blood pressure data based on a heart rate threshold and a heart rate variability threshold, thereby deleting inaccurate arterial blood pressure data.

[0134] For example, the regulation module 320 calculates the real-time heart rate (HR). i Heart rate can be measured by measuring the time interval T between adjacent R waves (i.e., the peak of the heartbeat on an electrocardiogram). RR To calculate:

[0135]

[0136] T RRi This represents the time interval (in seconds) of the i-th heartbeat.

[0137] Calculate heart rate variability (HRV). HRV can be calculated using the following formula:

[0138]

[0139] It is the average of all heartbeat intervals, and N is the number of heartbeats.

[0140] Set heart rate threshold HR th Heart rate variability threshold (HRV) th .

[0141] HR min-th ≤HR i ≤HR max-th HRV i ≤HRV th .

[0142] Real-time arterial blood pressure data (BP) were filtered based on the above threshold. i Arterial blood pressure data are considered accurate only when heart rate and heart rate variability are within the threshold range.

[0143] If (HR) min-th ≤HR i≤HR max-th )∧(HRV i ≤HRV th ), then BP i It is accurate. Otherwise, delete the real-time arterial blood pressure data (BP). i .

[0144] By filtering inaccurate blood pressure data, the processing module 300 can effectively remove abnormal data, ensuring the accuracy and consistency of the final measurement results. This is because heart rate thresholds and heart rate variability thresholds help identify unreliable data caused by large heart rate fluctuations or high heart rate variability. By setting these thresholds, the processing module 300 can identify and exclude this data, thereby improving the overall data quality.

[0145] According to a preferred embodiment, when the RR interval change rate of the electrocardiogram data increases, the processing module 300 increases the measurement frequency of the blood pressure measurement module 200 to obtain more information on arterial blood pressure changes.

[0146] An increase in the RR interval variability rate usually indicates greater heart rate variability. Increasing the measurement frequency can more accurately reflect real-time changes in blood pressure. This method is particularly suitable for patients with atrial fibrillation, as their RR interval variability rate is typically high; increasing the measurement frequency can improve the accuracy of diagnosis and treatment. Therefore, increasing the measurement frequency when the RR interval variability rate increases captures more details of blood pressure changes, providing more comprehensive information for subsequent data analysis.

[0147] The processing module 300 adjusts the inflation rate of the blood pressure measurement module 200 based on the RR interval variability in the initial electrocardiogram data. When the RR interval variability is high, the inflation rate is reduced to decrease additional stress on the patient's cardiovascular system.

[0148] For example, the following R-wave peak time points (in seconds) were extracted from electrocardiogram data:

[0149] {t1,t2,t3,t4,t5}={0.0,1.0,2.2,3.3,4.4}.

[0150] The time interval between adjacent R waves is:

[0151] T RR1 =1.0 - 0.0 = 1.0 seconds; T RR2 =2.2 - 1.0 = 1.2 seconds; T RR3 =3.3 - 2.2 = 1.1 seconds;

[0152] T RR4 =4.4 - 3.3 = 1.1 seconds.

[0153] The mean RR interval is:

[0154]

[0155] The RR interval variability is:

[0156]

[0157] Set the variability threshold RRV th It takes 0.05 seconds.

[0158] Because RRV = 0.71 seconds is greater than 0.05 seconds, the inflation frequency needs to be reduced.

[0159] Set the normal inflation frequency to F normal =1.0H Z The frequency reduction was 0.2H. Z Therefore, the adjusted inflation frequency is: F = F normal -ΔF=1.0H Z -0.2H Z =0.8H Z .

[0160] Because the RR interval variability was high (exceeding the threshold), it indicated cardiac rhythm instability. To reduce additional stress on the patient's cardiovascular system, the inflation rate was reduced to 0.8 Hz to slow down the measurement process.

[0161] According to a preferred embodiment, when the P-wave amplitude of the electrocardiogram data fluctuates significantly, the processing module 300 extends the measurement time of the blood pressure measurement module 200 to ensure that more stable arterial blood pressure data is obtained.

[0162] For example, the following P-wave amplitude (unit: mV) was extracted from electrocardiogram data:

[0163] {A P1 A P2 A P3} = {0.2, 0.35, 0.5}.

[0164] Rate of change of adjacent P-wave amplitude:

[0165]

[0166] Set amplitude fluctuation threshold So and All values ​​are greater than the amplitude fluctuation threshold, therefore the measurement time needs to be extended.

[0167] Set the normal measurement duration to T normal =10 seconds, the increased duration ΔT = 5 seconds.

[0168] Therefore, the increased measurement time is:

[0169] T measure =T normal +ΔT=10 seconds + 5 seconds=15 seconds (21).

[0170] Because the P wave amplitude fluctuates significantly (exceeding the threshold), it indicates that the electrocardiogram signal is unstable. To ensure more stable arterial blood pressure data, the measurement time is extended to 15 seconds to obtain more data samples for averaging, thereby improving the reliability of the measurement.

[0171] The fluctuation of P wave amplitude directly reflects the stability of atrial activity. When P wave amplitude fluctuates significantly, atrial activity may be unstable, and blood pressure measurements may be inaccurate. By extending the measurement time, stable blood pressure values ​​can be better captured in patients with atrial fibrillation. Therefore, by extending the measurement time when P wave amplitude fluctuations are significant, stable blood pressure data can still be obtained under conditions of large fluctuations, thus improving the reliability of the measurement.

[0172] According to a preferred embodiment, the processing module 300 dynamically adjusts the measurement frequency and duration of the blood pressure measurement module 200 based on the heart rate variability in the electrocardiogram data. When the heart rate variability shows a decreasing trend, the processing module 300 reduces the measurement frequency of the blood pressure measurement module 200 and extends the duration of a single measurement to improve the measurement comfort of the target subject.

[0173] When a decrease in heart rate variability is detected, HRV k <HRV k-1 (twenty two).

[0174] HRV k Indicates current heart rate variability; HRV k-1 This indicates the variability of heart rate over a previous period.

[0175] The formula is now adjusted to:

[0176] f new =f old ·α (23).

[0177] t new =t old ·β (24).

[0178] f old This indicates the current measurement frequency, measured in times per minute. new This indicates the new measurement frequency. t old This indicates the duration of a single measurement, in minutes. t newThis indicates the new duration of a single measurement. α is an adjustment factor for the measurement frequency (0 < α < 1, indicating a decrease in measurement frequency). β is an adjustment factor for the duration of a single measurement (β > 1, indicating an increase in measurement duration).

[0179] Assume the current measurement frequency is f old = 1 time / minute, current single measurement duration is t old =2 minutes, with adjustment factors of α=0.5 and β=1.5, and HRV was detected. k <HRV k-1 ,but:

[0180] The new measurement frequency is: f new =f old α = 1 · 0.5 = 0.5 times / minute.

[0181] The new duration of a single measurement is: t new =t old ·β=2·1.5=3 minutes.

[0182] Heart rate variability (HRV) is an indicator of heart rate fluctuations. When HRV decreases, heart rate stabilizes, and blood pressure tends to stabilize as well. Therefore, reducing the frequency of measurements can minimize patient discomfort and increase comfort. Conversely, extending the duration of each measurement helps obtain more accurate and stable blood pressure data when the heart rate is stable. This is particularly important for patients with atrial fibrillation, as their heart rate fluctuates significantly, and traditional frequent measurements may lead to inaccurate data and discomfort. This dynamic adjustment method allows for more effective monitoring of blood pressure, improving the scientific validity of measurements and patient compliance. Therefore, when HRV decreases, heart rate tends to stabilize, and blood pressure is relatively stable. In this case, reducing the measurement frequency will not affect the accuracy of blood pressure data, while extending the duration of each measurement ensures more stable data. This adjustment not only reduces the discomfort caused by frequent measurements but also improves the reliability of blood pressure monitoring.

[0183] Preferably, the processing module 300 adjusts the deflation frequency of the blood pressure measurement module 200 according to the pulse pressure difference in the initial arterial blood pressure data. When the pulse pressure difference is large, the deflation frequency is increased to quickly adapt to rapid changes in blood pressure and improve measurement accuracy.

[0184] Pulse pressure (PP) is the difference between systolic blood pressure (SBP) and diastolic blood pressure (DBP), and can be expressed by the formula:

[0185] PP = SBP - DBP (25).

[0186] Let the current venting frequency be D. old (Unit: mmHg / s), the new venting frequency is D. newThe formula for adjusting the venting frequency based on the pulse pressure difference can be expressed as: D new =D old ·γ(26).

[0187] When the pulse pressure difference is large, the deflation frequency increases. γ > 1 indicates an increase in the deflation frequency.

[0188] Based on the initial pulse pressure difference, the processing module 300 or the adjustment module 320 within the processing module 300 will dynamically adjust the venting frequency using the following comprehensive formula:

[0189]

[0190] Among them, PP threshold It is a preset pulse pressure difference threshold used to determine whether the venting frequency needs to be increased.

[0191] Assume the current venting frequency is D old =3 mmHg / s, adjustment factor γ = 1.2, preset pulse pressure threshold is PP threshold =40 mmHg. If the initial pulse pressure difference is PP = 45 mmHg.

[0192] Since PP ≥ PP threshold The new venting frequency is:

[0193] D new =D old· γ = 3·1.2 = 3.6 mmHg / s.

[0194] Clearly, by adjusting the deflation frequency of the blood pressure measurement module 200, this invention can improve the accuracy of blood pressure measurement. Firstly, patients with atrial fibrillation have irregular heart rates and significant blood pressure fluctuations. Traditional fixed deflation frequencies are prone to large measurement errors when dealing with such irregular heartbeats, while dynamically adjusting the deflation frequency can significantly reduce these errors, improving measurement accuracy and reliability. By dynamically adjusting the deflation frequency, the blood pressure measurement module 200 can adapt to these rapid changes in a timely manner, avoiding measurement lag and thus providing more real-time and accurate measurement data.

[0195] Secondly, dynamically adjusting the deflation frequency can effectively avoid false hypotension. False hypotension is an erroneous low value caused by the measurement process failing to respond promptly to rapid changes in blood pressure. By adjusting the deflation frequency in real time, the device can more accurately capture true blood pressure fluctuations, avoid the influence of false hypotension, and thus provide more reliable blood pressure measurement results.

[0196] Furthermore, the dynamic adjustment mechanism provides a more accurate raw data foundation for advanced data processing algorithms, enabling them to better interpret measurement results and reduce misjudgments and misdiagnoses. This high-precision data foundation enhances the flexibility of the algorithm, allowing the blood pressure measurement module 200 to maintain efficient and accurate operation even in complex atrial fibrillation situations.

[0197] Furthermore, heart rate and blood pressure variations in patients with atrial fibrillation exhibit significant individual differences. The mechanism of dynamically adjusting the deflation frequency allows the blood pressure measurement module 200 to better adapt to the specific circumstances of different patients, providing more personalized and accurate measurement results. This personalized measurement not only improves measurement accuracy but also enhances the clinical applicability of the device.

[0198] Finally, through the intelligent analysis and adjustment of the processing module 300, the blood pressure measurement module 200 possesses a more intelligent response capability, enabling it to optimize the measurement process based on the patient's real-time condition. This intelligence not only provides more accurate blood pressure readings but also accumulates more valuable health data over long-term monitoring, offering important references for medical decision-making.

[0199] Therefore, the technique of dynamically adjusting the deflation frequency can significantly improve the accuracy and reliability of blood pressure measurement in patients with atrial fibrillation, avoid false hypotension, reduce measurement errors, provide personalized measurement, and enhance the intelligence and applicability of the equipment.

[0200] The processing module 300 adjusts the inflation and deflation frequency of the blood pressure measurement module 200 based on the heart rate in the initial physiological parameters. When the heart rate is fast, the inflation and deflation frequency is reduced to reduce the burden on the heart.

[0201] Specifically, record the initial heart rate (HR). initial Determine if the heart rate exceeds a preset threshold HR. threshold If HR initial >HR threshold The adjustment factor α for the measurement frequency is recalculated.

[0202]

[0203] HR max This indicates the upper limit of heart rate.

[0204] For example, the HR records initial =110 bpm; HR threshold =100 bpm; HR max =150 bpm.

[0205]

[0206] f new =fold 0.8.

[0207] The processing module 300 adjusts the inflation time of the blood pressure measurement module 200 based on the QT interval in the initial electrocardiogram data. When the QT interval is long, the inflation time is extended to ensure the accuracy of blood pressure measurement and avoid measurement errors caused by arrhythmia.

[0208] Recording QT intervals QT initial Determine if the QT interval exceeds a preset threshold QT interval. threshold If QT initial >QT threshold The inflation time needs to be extended, so the adjustment factor λ for the inflation time needs to be calculated. 充气new =T 充气old ·λ.

[0209] T 充气new This indicates the adjusted inflation time, in seconds (s); T 充气old This indicates the inflation time before the adjustment.

[0210] There are two formulas for calculating the adjustment factor λ.

[0211] The formula A for calculating the adjustment factor λ is:

[0212]

[0213] The formula B for calculating the adjustment factor λ is:

[0214]

[0215] QT max This indicates the upper limit of the QT interval.

[0216] For example, the current inflation time is T. 充气old = 30 seconds; QT initial = 480 milliseconds; QT threshold = 450 milliseconds; QT max = 500 milliseconds.

[0217] The formula A for calculating the adjustment factor λ is:

[0218]

[0219] T 充气new =T 充气old ·λ=30 seconds × 1.067≈32.01 seconds.

[0220] The formula B for calculating the adjustment factor λ is:

[0221]

[0222] T 充气new =T 充气old ·λ=30 seconds × 1.6≈48 seconds.

[0223] The advantage of formula A for calculating the adjustment factor λ is that it provides a smoother adjustment, preventing drastic changes in inflation time, which is particularly important for stable measurements in patients with atrial fibrillation. Since patients with atrial fibrillation may have arrhythmias, this formula can avoid over-adjustment due to heart rate fluctuations. However, in cases of large fluctuations in the QT interval, the adjustment range may be insufficient and unable to quickly adapt to large changes.

[0224] The advantages of formula B for calculating the adjustment factor λ are: it is suitable for situations requiring significant adjustment, and it can quickly adjust the inflation time when the QT interval deviates significantly from the preset threshold. When the QT interval approaches its upper limit, the adjustment factor increases more significantly, making it more sensitive to changes in the QT interval. However, in patients with atrial fibrillation, rhythm fluctuations may lead to over-adjustment, affecting the stability and accuracy of the measurement.

[0225] Therefore, for blood pressure measurement in patients with atrial fibrillation, the following combined strategy can be referenced and implemented based on their specific needs and the variability of the QT interval.

[0226] If the patient's QT interval has minimal fluctuations, it is more appropriate to use formula A, which calculates the adjustment factor λ, to determine the inflation duration. This method provides a smoother and more robust adjustment, avoiding over-adjustment caused by heart rhythm fluctuations.

[0227] If a patient's QT interval fluctuates significantly, it is more appropriate to use formula B, which calculates the adjustment factor λ, to determine the inflation duration. This is especially true when the QT interval is close to its upper limit, requiring rapid and significant adjustments to accommodate the changes.

[0228] Furthermore, the inflation duration is smoothly adjusted using formula A, which calculates the adjustment factor λ, ensuring stability in most cases. When the QT interval significantly deviates from the preset threshold and approaches the upper limit, the inflation duration is adjusted using formula B, which calculates the adjustment factor λ, to quickly adapt to larger fluctuations. This combined strategy provides more accurate and stable blood pressure measurements under different conditions, ensuring that the measurement needs of patients with atrial fibrillation are met.

[0229] The processing module 300 adjusts the deflation time of the blood pressure measurement module 200 based on the skin conductance response in the initial physiological parameters. When the skin conductance response is high, the deflation time is shortened to reduce stimulation and discomfort to the patient.

[0230] Specifically, recording the skin electrical conductivity response G initial Determine whether the skin conductivity response exceeds the preset threshold G. thresholdIf G initial >G threshold Calculate the adjustment factor δ for the venting frequency.

[0231]

[0232] The adjusted venting time is: T 放气new =T 放气old ·δ.

[0233] G max This indicates the upper limit of skin electrical conductivity response. T 放气new This indicates the adjusted venting time, in seconds (s); T 放气old This indicates the venting time before adjustment.

[0234] For example, setting the skin conductance response G initial =5ms; G threshold =3ms; G max = 6ms.

[0235] Since 5ms > 3ms, the skin conductance response is considered to be high.

[0236]

[0237] T 放气new =T 放气old 0.33.

[0238] In blood pressure measurement of patients with atrial fibrillation, the processing module 300 can adjust the deflation time of the blood pressure measurement module 200 according to the skin conductance response in the initial physiological parameters, which can bring significant advantages.

[0239] (1) A high skin conductivity response usually indicates that the patient is in a state of tension or anxiety. By shortening the deflation time, the pressure and discomfort on the patient during the measurement process can be reduced, thereby improving the patient's comfort and cooperation.

[0240] (2) By adjusting the deflation time in real time, the blood pressure of patients with atrial fibrillation can be measured more accurately. This reduces the impact of dynamic blood pressure changes caused by excessive deflation time on the measurement results, thereby improving the accuracy of the measurement.

[0241] (3) Dynamically adjusting the deflation time makes the blood pressure measurement process more personalized and humane, improving the overall experience of patients.

[0242] (4) Skin conductance is one of the indicators of the body's response to stress. By adjusting the deflation time based on skin conductance, the stress response of patients during blood pressure measurement can be reduced to a certain extent, thereby avoiding the rise in blood pressure caused by stress.

[0243] (5) Shortening the deflation time can speed up the overall blood pressure measurement process, reduce waiting time, and improve measurement efficiency.

[0244] It should be noted that the specific embodiments described above are exemplary. Those skilled in the art can devise various solutions inspired by the disclosure of this invention, and these solutions all fall within the scope of this invention and its protection. Those skilled in the art should understand that this specification and its accompanying drawings are illustrative and not intended to limit the scope of the claims. The scope of protection of this invention is defined by the claims and their equivalents. This specification contains multiple inventive concepts; phrases such as "preferredly" or "according to a preferred embodiment" indicate that the corresponding paragraph discloses an independent concept. The applicant reserves the right to file divisional applications based on each inventive concept.

Claims

1. An intelligent blood pressure monitoring device for elderly patients with atrial fibrillation, characterized in that, A suitable home environment for patients with atrial fibrillation includes: A portable electrocardiogram (ECG) measurement module for home use by atrial fibrillation patients, which collects ECG data from the target subject and generates ECG data; a blood pressure measurement module for measuring arterial blood pressure data from the target subject. A terminal that receives electrocardiogram (ECG) data and arterial blood pressure data; The ECG data and arterial blood pressure data are time-aligned, and the measurement frequency and duration of the blood pressure measurement module are dynamically adjusted based on changes in the ECG data. Arterial blood pressure data that meets the time interval requirements and is less affected by atrial fibrillation is selected as the measurement data and set in the hospital's processing module. The processing module filters real-time arterial blood pressure data based on heart rate thresholds and heart rate variability thresholds, thereby removing inaccurate arterial blood pressure data. Heart rate variability (HRV) is calculated using the following formula: ， It is the average of all heartbeat intervals, where N is the number of heartbeats and T is the average of all heartbeat intervals. RRi This represents the time interval of the i-th heartbeat; The processing module dynamically adjusts the measurement frequency and duration of the blood pressure measurement module based on the heart rate variability in the electrocardiogram data. When the heart rate variability shows a decreasing trend, the processing module reduces the measurement frequency of the blood pressure measurement module and extends the duration of a single measurement to improve the measurement comfort of the target subject. The processing module includes an adjustment module, which determines the timing of arterial blood pressure data selection (t). ABPi The calculation formula is: ； RR i HR represents the time interval between two consecutive R waves. i HRV represents the number of heartbeats per minute. i AF represents heart rate fluctuation data. dur The duration of atrial fibrillation is indicated by k1 to k4, which represent the first regulation coefficient. The adjustment module calculates the measurement frequency f. measure The formula is: α is the adjustment factor for the measurement frequency; The adjustment module calculates the measurement duration t. measure The formula is: ； β1~β4 represent the second adjustment coefficients; When the processing module receives ECG and arterial blood pressure data, it checks the timestamp of each data point. By comparing the timestamps, it ensures that ECG and arterial blood pressure data at the same time correspond. If the sampling frequencies of ECG and arterial blood pressure data are different, the processing module interpolates the data with the lower sampling frequency to make it have the same time resolution as the data with the higher sampling frequency. There is a delay in the physiological propagation of ECG and arterial blood pressure signals. The processing module compensates for the delay of one of the signals according to a pre-set delay parameter. If ECG and arterial blood pressure data are collected by different devices, the processing module uses a synchronization trigger signal to ensure that the data acquisition of the two devices starts at the same time. After completing the time alignment, the processing module performs data smoothing.

2. The intelligent blood pressure monitoring device for elderly patients with atrial fibrillation according to claim 1, characterized in that, The processing module (300) determines the stability of the RR interval in the electrocardiogram data, and immediately determines the arterial blood pressure value when the RR interval is stable; and / or The processing module (300) determines at least one arterial blood pressure value and its average value during the stable RR interval period.

3. The intelligent blood pressure monitoring device for elderly patients with atrial fibrillation according to claim 1, characterized in that, The processing module (300) selects the arterial blood pressure value when the P wave in the electrocardiogram data is clear and continuous.

4. The intelligent blood pressure monitoring device for elderly patients with atrial fibrillation according to claim 1, characterized in that, The processing module (300) identifies atrial fibrillation based on the electrocardiogram data and determines arterial blood pressure data during the stable period after the atrial fibrillation cycle ends.

5. The intelligent blood pressure monitoring device for elderly patients with atrial fibrillation according to claim 1, characterized in that, When the rate of change of the RR interval in the electrocardiogram data increases, the processing module (300) increases the measurement frequency of the blood pressure measurement module (200) to obtain information on changes in arterial blood pressure.

6. The intelligent blood pressure monitoring device for elderly patients with atrial fibrillation according to claim 1, characterized in that, When the P-wave amplitude of the electrocardiogram data fluctuates significantly, the processing module (300) extends the measurement time of the blood pressure measurement module (200) to ensure that stable arterial blood pressure data is obtained.

7. A method for intelligent blood pressure monitoring in elderly patients with atrial fibrillation, characterized in that, include: Measure the arterial blood pressure data of the target subject; Collect electrocardiogram (ECG) data from the target subject and generate ECG data; The ECG data and arterial blood pressure data are time-aligned, and the measurement frequency and duration of the blood pressure measurement module are dynamically adjusted based on changes in the ECG data. Arterial blood pressure data that meets the time interval requirements and is less affected by atrial fibrillation are selected as the measurement data. Real-time arterial blood pressure data is filtered based on heart rate thresholds and heart rate variability thresholds to remove inaccurate data. Heart rate variability (HRV) is calculated using the following formula: ， It is the average of all heartbeat intervals, where N is the number of heartbeats and T is the average of all heartbeat intervals. RRi This represents the time interval of the i-th heartbeat; The measurement frequency and duration of the blood pressure measurement module are dynamically adjusted based on the heart rate variability in electrocardiogram data. When the heart rate variability shows a decreasing trend, the measurement frequency of the blood pressure measurement module is reduced and the duration of a single measurement is extended to improve the measurement comfort of the target subject. Timing of arterial blood pressure data selection t ABPi The calculation formula is: ； RR i HR represents the time interval between two consecutive R waves. i HRV represents the number of heartbeats per minute. i AF represents heart rate fluctuation data. dur The duration of atrial fibrillation is indicated by k1 to k4, which represent the first regulation coefficient. Calculate the measurement frequency f measure The formula is: α is the adjustment factor for the measurement frequency; Calculate the measurement duration t measure The formula is: ； β1~β4 represent the second adjustment coefficients; Upon receiving ECG and arterial blood pressure data, the timestamp of each data point is checked. By comparing the timestamps, it is ensured that ECG and arterial blood pressure data at the same time correspond. If the sampling frequencies of ECG and arterial blood pressure data are different, interpolation is performed on the data with the lower sampling frequency to make it have the same time resolution as the data with the higher sampling frequency. There is a delay in the physiological propagation of ECG and arterial blood pressure signals. According to the preset delay parameter, delay compensation is performed on one of the signals. If ECG and arterial blood pressure data are collected by different devices, a synchronization trigger signal is used to ensure that the data acquisition of the two devices starts at the same time. After time alignment is completed, the data is smoothed.

8. The intelligent blood pressure monitoring method for elderly patients with atrial fibrillation according to claim 7, characterized in that, The method further includes: Arterial blood pressure data or the average value of arterial blood pressure data can be selected based on the stability of the RR interval, changes in the P wave, and / or atrial fibrillation in the electrocardiogram data.

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