A non-invasive multi-frequency heart displacement monitoring method

Abstract

The present invention provides a non-invasive multi-frequency cardiac output monitoring method, which controls the lower embedded system to switch different frequencies in real time according to the set intervals by setting the excitation frequency set and the frequency switching interval through the upper display and control machine, thereby realizing the real-time switching of multiple frequency points; the lower embedded system collects the electrocardiogram signal and the cardiac impedance signal of the monitored object, and transmits them to the upper display and control machine through wired or wireless WIFI / Bluetooth; the upper display and control machine performs corresponding filtering and wavelet transform analysis on the cardiac impedance signal and the electrocardiogram signal, extracts the important characteristic points of the signal, and calculates the cardiac output index. The present invention realizes the monitoring of multi-frequency excitation of the human body by controlling the lower embedded system through the upper display and control machine, avoids the interference of different frequency noises in measuring the electrocardiogram and cardiac impedance signals in different environments, can realize non-invasive continuous cardiovascular monitoring, and provide more accurate hemodynamic parameters for clinical diagnosis and treatment.

Description

Technical Field

[0001] The invention relates to the field of biomedical engineering, and in particular to a non-invasive multi-frequency heart displacement monitoring method. Background Art

[0002] According to the World Health Organization's report in 2023, cardiovascular disease (CVD), as the leading cause of death worldwide, claims about 17.9 million lives each year, accounting for 32% of the global death toll. In this context, cardiac output (CO), as an important physiological parameter, plays a vital role. Cardiac output refers to the amount of blood pumped by the heart in one minute. By monitoring cardiac output, we can gain an in-depth understanding of the heart's pumping function and systemic blood perfusion, and then calculate relevant hemodynamic indicators, which reflect the important characteristics of human heart function. With the continuous advancement of science and technology, cardiac output monitoring technology has gradually developed from traditional invasive and minimally invasive methods to non-invasive methods. This transformation has brought revolutionary changes to the medical field, making cardiac output monitoring safer, more convenient and widely applicable. However, how to achieve non-invasive and continuous monitoring of cardiac output is still an urgent problem that needs to be solved. Summary of the invention

[0003] In view of this, the present invention aims to propose a non-invasive multi-frequency cardiac output monitoring method, which aims to effectively realize continuous monitoring of cardiac output without invasive operation, thereby providing a more convenient and safe option for medical practice. By adopting multi-frequency technology, it is possible to more comprehensively capture the changes in the heart's pumping function, provide medical staff with more detailed and accurate data, and help them better assess the patient's cardiovascular condition.

[0004] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0005] A non-invasive multi-frequency heart displacement monitoring method, the method comprising the following steps:

[0006] 1) The upper display and control machine sets the excitation frequency set and the frequency switching interval, and controls the lower embedded system to switch different frequencies in real time according to the set frequency switching interval, thereby realizing real-time switching of multiple frequency points;

[0007] 2) The lower embedded system collects the ECG signal and cardiac impedance signal of the monitored object and transmits them to the upper display and control machine via wired or wireless WIFI / Bluetooth;

[0008] 3) The upper display and control machine collects cardiac impedance signals and electrocardiogram signals at different excitation frequencies, and performs filtering and wavelet transform analysis on these signals to extract key feature points. According to the feature point data at different excitation frequencies, multi-frequency data dimension reduction and signal fusion are performed. Finally, the cardiac output is calculated through the following cardiac output calculation formula, and other hemodynamic parameters are further derived;

[0009] The formula for calculating cardiac output is as follows:

[0010] CO = SV × HR;

[0011] ;

[0012] Among them, CO is cardiac output; SV is the stroke volume of the monitored object; HR is heart rate; V ITBV V is the intrathoracic blood volume, which is related to body weight W (kg). ITBV =16×W 1.02 ml; Z 0 is the basic impedance; ε is a dimensionless index of abnormal transthoracic conduction, that is, when Z 0 <20Ω, 0<ε<1; when Z 0 ≥20Ω, ε=1; trr is the RR interval of the electrocardiogram, LVET is the left ventricular ejection time, LVET / Used to correct left ventricular ejection time; K 1 is the correction coefficient, which depends on the impedance waveform change after filtering by the lower embedded system and the upper display and control machine; LVET and are left ventricular ejection time and maximum differential impedance respectively; A is vascular elasticity factor, B is chest resistance factor, C is gender difference factor, and D is body position factor.

[0013] Among them, V ITBV It is the intrathoracic blood volume, which is related to body weight W (kg). Weight adjustment helps to further standardize the measurement results based on BSA. Body weight directly affects the metabolic demand and hemodynamic parameters of the heart. Adding weight factors can make the measurement more in line with the actual situation of the individual, especially for obese or extreme weight individuals, whose heart function may be different. This method helps to provide a fairer and more scientific heart health assessment for people of different body shapes and weights.

[0014] in, The maximum impedance differential value represents the change in blood flow velocity through large blood vessels, especially the hemodynamic response during cardiac contraction. It is closely related to the heart's pumping function and the rate of change of blood flow. It can more accurately reflect the heart's stroke volume (SV) and help identify whether the heart's pumping function is normal.

[0015] Among them, Z0 Z stands for basal impedance, which refers to the initial impedance of blood flow in the absence of cardiac contraction and is usually related to the tone and compliance of the blood vessels. 0 It reflects the basic characteristics of blood vessels, such as their size and elasticity. 0 It represents the static vascular impedance. Its introduction can help correct the dynamic fluctuations caused by changes in vascular status, thereby improving the accuracy of cardiac stroke volume (SV) measurement and making the measurement results closer to the actual cardiac output.

[0016] Among them, A represents the vascular elasticity factor, which reflects the adaptability of blood vessels to blood flow. For patients with hypertension, atherosclerosis, etc., vascular compliance is reduced, which in turn affects the efficiency of the heart's pumping. By introducing the vascular elasticity factor, the actual blood output of the heart can be more accurately evaluated. B is the chest resistance factor, which represents the individual difference in chest resistance. If the chest wall is thicker or there is more fat, it may change the path of the current through the chest, thereby affecting the measurement of cardiac output. The introduction of the chest resistance factor helps to correct these effects and reduce errors. C is the gender difference factor. Generally, men have a larger heart volume, higher blood volume, and their vascular structure and heart pumping function may be different from those of women. The introduction of the gender difference factor helps to adjust these physiological differences, thereby achieving more accurate cardiac output measurement. D is the body position factor. When standing, gravity causes blood to accumulate in the lower limbs, affecting the amount of blood returning to the heart; when lying down, changes in body position may promote blood return and affect the amount of blood discharged by the heart. The introduction of the body position factor can effectively correct these changes and accurately measure cardiac output.

[0017] Among them, LVET / Used to correct the left ventricular ejection time, the introduction of this parameter can reduce the measurement error caused by inconsistent or changing ejection time to a certain extent. Especially in the case of high heart rate, low blood pressure, etc., the change of ejection time may affect the estimation of cardiac output, which helps to obtain more reliable results under different physiological conditions.

[0018] Since different tissues and fluids (such as blood, cells, and blood vessel walls) respond differently to electric current at different frequencies, low-frequency current mainly senses the impedance of extracellular fluid and cell membrane, while high-frequency current is more likely to penetrate the cell membrane and interact with intracellular fluid. Therefore, multi-frequency excitation can simultaneously consider the impedance characteristics of different tissues at different frequencies and provide more comprehensive physiological information. In addition, multi-frequency excitation also effectively overcomes the interference at a single frequency, further improving the robustness and stability of the system and enhancing the sensitivity of cardiac output measurement.

[0019] The basic principle of this method uses Ohm's law. The human body's blood, bones, fat, and muscles have different electrical conductivity. The impedance of blood and body fluids is the smallest, while the impedance of bones and air is the largest. As the heart contracts and relaxes, the blood flow in the aorta changes, and the impedance of the current passing through the chest also changes accordingly. The left ventricular contraction time and heart rate are measured and calculated.

[0020] In the process of dimensionality reduction, the principal component analysis (PCA) method is used to process multi-frequency data and extract the most representative feature information. In terms of signal fusion, the least squares method is used to synthesize the signals of multiple frequencies to generate a comprehensive signal that more accurately reflects the changes in cardiac output.

[0021] Furthermore, the excitation frequency set includes 3 low-frequency signals and 3 high-frequency signals, the frequency range of the low-frequency signals is 10-50 kHz, and the frequency range of the high-frequency signals is 50-100 kHz; the frequency switching interval is 60 milliseconds or 240 milliseconds.

[0022] Low-frequency signals are more sensitive to changes in blood impedance, especially those closely related to changes in blood flow in large blood vessels (such as the aorta) and systemic blood volume, and mainly reflect more significant hemodynamic changes. High-frequency signals are more sensitive to changes in tissue impedance, especially soft tissue (such as muscle and fat), and can reveal the dynamic characteristics of water and cellular components in small blood vessels (such as capillaries) and tissues, providing more detailed information about the tissue. This frequency selection scheme takes into account multiple factors such as cardiovascular physiological characteristics, signal stability, noise suppression, and equipment performance to ensure accurate and reliable cardiac output measurement results.

[0023] The 60 millisecond interval is suitable for situations with fast dynamic changes, such as patients with high heart rates. The 240 millisecond interval is suitable for stable cardiovascular conditions. The longer switching interval helps reduce measurement errors during frequency switching and ensures signal stability and accuracy. This setting can be flexibly adjusted according to actual needs and has good adaptability.

[0024] Furthermore, a four-electrode measurement method is used to simultaneously collect cardiac impedance signals and electrocardiogram signals. The four electrodes include an output excitation positive electrode, a receiving signal positive electrode, an output excitation negative electrode, and a receiving signal negative electrode; the output excitation positive electrode and the receiving signal positive electrode are attached to the left carotid artery, while the output excitation negative electrode and the receiving signal negative electrode are attached to the intersection of the xiphoid process horizontal line and the left mid-axillary line. The four-electrode design ensures the separation of the current and voltage measurement paths, thereby reducing noise interference caused by current and improving the stability of the measurement. This is especially important for the simultaneous collection of cardiac impedance signals and electrocardiogram signals, which can avoid mutual interference between the two signals.

[0025] This electrode integration method is a three-lead detection method for ECG signals and a four-point impedance measurement method for cardiac impedance signals. The output excitation negative electrode and the receiving signal negative electrode are attached to the left carotid artery from top to bottom, and the distance between the two electrodes is 3-5cm; the receiving signal positive electrode and the output excitation positive electrode are attached to the intersection of the xiphoid horizontal line and the left mid-axillary line from top to bottom, and the distance between the two electrodes is 5-7cm. Among them, the system has four-electrode DC and AC lead shedding detection to monitor the fit between the electrode and the skin in real time.

[0026] Furthermore, the upper display and control machine performs filtering processing on the received ECG signal and cardiac impedance signal. The specific method is as follows:

[0027] Perform notch, low-pass and high-pass filtering on the ECG signal to remove 50Hz power frequency interference, myoelectric interference and baseline drift respectively, which are used for waveform display and subsequent feature point R peak recognition to calculate heart rate HR;

[0028] For the cardiac impedance signal, first use low-pass filtering to extract its basic impedance Z 0 , then subtract the base impedance Z from the cardiac impedance signal 0 The impedance change signal ΔZ is obtained, and then the impedance change signal ΔZ is band-pass filtered to further eliminate noise interference, and finally a first-order differential calculation is performed to obtain the impedance differential dz / dt.

[0029] Furthermore, the ECG signal filtering process uses 50Hz notch, 40Hz low-pass, and 0.8Hz high-pass filtering;

[0030] The cardiac impedance signal uses a 0.2Hz low-pass and a 0.8-6Hz band-pass.

[0031] Furthermore, the impedance differential dz / dt signal is subjected to wavelet transform analysis, the entropy of the wavelet coefficients is calculated, and the part with an entropy value greater than 0.1 is screened out; the final dz / dt signal is obtained through reconstruction processing, and the important feature points are identified, and the dz / dt feature points aortic valve opening time B, maximum amplitude time C, aortic valve closing time X, which are used to calculate the left ventricular ejection time LVET and the maximum value of the impedance differential are identified. , and then perform model calculations.

[0032] Furthermore, in the ECG signal, the R point is located by the findpink peak-finding algorithm to calculate the heart rate HR value and the RR interval time Trr;

[0033] In the impedance differential signal dz / dt processing, the signal is first preprocessed by wavelet transform, and then the peak point C of the dz / dt signal is identified by the findpink peak search algorithm; then, the dz / dt signal is derived to obtain the second-order derivative signal of the impedance signal, and the position of point R of the electrocardiogram signal and point C of the cardiac impedance signal are mapped to the first-order derivative signal of the dz / dt signal. In this signal, the only extreme point between point R and point C is determined as point B. Finally, the position of point X is determined. In the dz / dt signal, 0.15Trr after point C is the time position of point X.

[0034] Furthermore, the lower embedded system includes a master control module, a cardiac impedance signal and electrocardiogram signal acquisition module, a wireless transmission module, a power management module, and a USB wired transmission module; the cardiac impedance signal and electrocardiogram signal acquisition module acquires cardiac impedance signals and electrocardiogram signals in real time according to the control of the upper display and control machine, preliminarily pre-processes the signals, and then sends them to the upper display and control machine through the USB wired transmission module or the wireless transmission module.

[0035] Furthermore, the master control module adopts the STM32L452 chip, which is responsible for effectively managing and monitoring the operating status of the lower embedded system; the cardiac impedance signal and electrocardiogram signal acquisition module adopts the ADPD6000 chip to capture physiological signal data in real time at a sampling rate of 500Hz; the wireless transmission module adopts the ESP32-PICO-D4 chip to realize convenient Bluetooth or WIFI transmission of data, ensuring the efficiency and reliability of information transmission; the power management module adopts the BQ34Z100PWR-G1 chip, which can monitor the battery status and related information in real time to ensure the continuous and stable operation of the system.

[0036] The master control module is connected to the cardiac impedance and ECG signal acquisition module through I 2 C protocol is used for communication. After receiving the instruction from the upper display and control machine, the master control module controls the cardiac impedance and ECG signal acquisition modules to generate high-frequency AC excitation of the set frequency and collect two physiological signals at a sampling frequency of up to 500Hz according to the instruction requirements. After the acquisition is completed, the master control module pre-processes the two signals, uses 50Hz notch filtering to initially filter out the power frequency noise interference, and then sends them to the upper display and control machine through wired transmission or wireless WIFI / Bluetooth.

[0037] Furthermore, other hemodynamic parameters include cardiac output index SI, cardiac index CI, ejection fraction EF, and systemic vascular resistance SVR;

[0038] The calculation formula of cardiac output index SI is as follows:

[0039] SI = SV / BSA;

[0040] Among them, BSA is the body surface area, which is related to body weight and height;

[0041] The calculation formula of cardiac index CI is as follows:

[0042] CI = CO / BSA;

[0043] Wherein, CO is cardiac output;

[0044] The calculation formula of ejection fraction EF is as follows:

[0045] EF = 84 × (64 × (PEP / LVET));

[0046] Among them, PEP is the pre-ejection time, and LVET is the left ventricular ejection time;

[0047] The calculation formula of systemic vascular resistance SVR is as follows:

[0048] SVR = 80 × (MAP × CVP) / CO;

[0049] Among them, MAP is mean arterial pressure and CVP is central venous pressure.

[0050] Compared with the prior art, the non-invasive multi-frequency heart displacement monitoring method of the present invention has the following advantages:

[0051] (1) The non-invasive multi-frequency heart displacement monitoring method described in the present invention is used to monitor hemodynamic parameters in real time. The present invention realizes multi-frequency excitation monitoring of the human body by controlling the real-time switching of the high-frequency excitation frequency of the lower embedded system through the upper display and control machine, thereby avoiding the interference of different frequency noises on the measurement signal in different environments. Moreover, the desired excitation frequency is input through the upper display and control machine. When the input excitation value exceeds or falls below the controllable excitation frequency range, it is automatically corrected to the maximum or minimum excitation frequency value. In addition, non-invasive continuous cardiovascular monitoring can also be realized to provide more accurate hemodynamic parameters for clinical diagnosis and treatment.

[0052] (2) The non-invasive multi-frequency cardiac output monitoring method described in the present invention adopts a four-electrode measurement method, which is a three-lead detection method for electrocardiogram signals and a four-point impedance measurement method for cardiac impedance signals.

[0053] (3) The non-invasive multi-frequency heart displacement monitoring method described in the present invention uses an accurate recognition algorithm to determine the characteristic points of the electrocardiogram (ECG) signal and the impedance differential signal (dz / dt). Accurate heart rate (HR), left ventricular ejection time (LVET) and impedance differential maximum value (dz / dt) are obtained through each characteristic point. max , and then through model calculation, accurate cardiac output and other related hemodynamic parameters are obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0055] Figure 1 It is a schematic block diagram of the non-invasive multi-frequency heart displacement monitoring method of the present invention;

[0056] Figure 2 A host computer interface used in the non-invasive multi-frequency heart displacement monitoring method of the present invention;

[0057] Figure 3 It is a schematic diagram of ECG and ICG signal filtering processing and waveform display;

[0058] Figure 4 is the collected ECG waveform;

[0059] Figure 5 The waveforms of the collected impedance change ΔZ and impedance differential dz / dt are shown;

[0060] Figure 6 Display diagrams for ECG and ICG feature parameter acquisition and model calculation;

[0061] Figure 7 This is a comparison chart of the non-invasive multi-frequency heart displacement monitoring method described in the present invention and the expert positioning results. DETAILED DESCRIPTION

[0062] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] A non-invasive multi-frequency cardiac displacement monitoring system includes a lower embedded system and an upper display and control machine. The lower embedded system includes a master control module, a cardiac impedance signal and electrocardiogram signal acquisition module, a wireless transmission module, a power management module, and a USB wired transmission module; the cardiac impedance signal and electrocardiogram signal acquisition module preliminarily pre-processes the real-time cardiac impedance signal (ICG) and electrocardiogram signal (ECG) according to the control of the upper display and control machine, and then sends the signals to the upper display and control machine through the USB wired transmission module or the wireless transmission module.

[0065] The master control module uses the STM32L452 chip, which is responsible for effectively managing and monitoring the operating status of the lower embedded system; the cardiac impedance signal and electrocardiogram signal acquisition module uses the ADPD6000 chip to capture physiological signal data in real time at a sampling rate of 500Hz; the wireless transmission module uses the ESP32-PICO-D4 chip to achieve convenient Bluetooth or WIFI transmission of data, ensuring the efficiency and reliability of information transmission; the power management module uses the BQ34Z100PWR-G1 chip, which can monitor the battery status and related information in real time to ensure the continuous and stable operation of the system.

[0066] The master control module is connected to the cardiac impedance and ECG signal acquisition module through I 2 C protocol is used for communication. After receiving the instruction from the upper display and control machine, the master control module controls the cardiac impedance and ECG signal acquisition modules to generate high-frequency AC excitation of the set frequency and collect two physiological signals at a sampling frequency of up to 500Hz according to the instruction requirements. After the acquisition is completed, the master control module pre-processes the two signals, uses 50Hz notch filtering to initially filter out the power frequency noise interference, and then sends them to the upper display and control machine through wired transmission or wireless WIFI / Bluetooth.

[0067] Non-invasive multi-frequency heart displacement monitoring method Figure 1 As shown, the specific steps include:

[0068] (1) Open the lower embedded system and the upper display and control machine respectively, and select the transmission mode wireless (WIFI or Bluetooth transmission) or wired transmission in the upper display and control machine. After successfully connecting to the lower embedded system, the interface pops up "Connected". In this embodiment, wireless WIFI connection is selected;

[0069] (2) A four-electrode measurement method is used to simultaneously collect cardiac impedance signals and electrocardiogram signals. The four electrodes include a positive electrode for output excitation, a positive electrode for receiving signals, a negative electrode for output excitation, and a negative electrode for receiving signals; Figure 1 As shown, the four electrodes are attached to various parts of the body according to their positions. The output excitation negative electrode E1 and the receiving signal negative electrode E2 are attached to the left carotid artery from top to bottom, and the distance between the two electrodes is 4 cm; the receiving signal positive electrode E3 and the output excitation positive electrode E4 are attached to the intersection of the xiphoid process horizontal line and the left axillary midline from top to bottom, and the distance between the two electrodes is 6 cm.

[0070] (3) After the four electrodes are attached, first manually enter your basic personal information in the information bar on the upper display control machine, including name, gender, height, weight and age. Figure 2; Then, set the excitation output set and the excitation switching interval in the excitation output column. In this embodiment, the excitation output set is set to 20kHz, 30kHz, and 40kHz for low-frequency excitation, 60kHz, 70kHz, and 80kHz for high-frequency excitation, and the switching interval is 240ms. After clicking the "Start" button, data acquisition officially begins. In this process, the lower embedded system collects ECG and ICG signals in real time and performs preprocessing according to the multi-frequency control of the upper display and control machine. The processed signal is transmitted to the upper display and control machine through the wireless transmission module. The upper display and control machine performs filtering and wavelet transform analysis on the data obtained at different frequencies, extracts important feature points of the signal, such as the R point of the ECG signal and the B point (aortic valve opening time), C point (maximum amplitude time), and X point (aortic valve closing time) of the impedance differential signal, and calculates the left ventricular ejection time (LVET) and the maximum impedance differential value ((dz / dt)max). Finally, the model is calculated based on the personal information, and multi-frequency data dimension reduction and signal fusion are performed based on the feature point data under different excitation frequencies. Finally, the cardiac output is calculated through the cardiac output calculation formula, and other hemodynamic parameters are further derived.

[0071] Specifically, the impedance differential dz / dt signal is subjected to wavelet transform analysis, the entropy of the wavelet coefficients is calculated, and the part with an entropy value greater than 0.1 is screened out; the final dz / dt signal is obtained by signal reconstruction, and the important feature points are identified, and the dz / dt feature points are identified, namely, the aortic valve opening time B, the maximum amplitude time C, the aortic valve closing time X, which are used to calculate the left ventricular ejection time LVET and the maximum impedance differential value. , and then perform model calculations.

[0072] In the process of dimensionality reduction, the principal component analysis (PCA) method is used to process multi-frequency data and extract the most representative feature information. In terms of signal fusion, the least squares method is used to synthesize the signals of multiple frequencies to generate a comprehensive signal that more accurately reflects the changes in cardiac output.

[0073] The upper display and control machine page displays the corresponding hemodynamic parameter information in real time, such as Figure 2 shown.

[0074] Click the "End" button to stop the acquisition. Click the "Generate Information" button to generate a document containing relevant hemodynamic parameters such as cardiac output, left ventricular ejection time, and pre-ejection period.

[0075] The formula for calculating cardiac output is as follows:

[0076] CO = SV × HR;

[0077] ;

[0078] Among them, CO is cardiac output; SV is the stroke volume of the monitored object; HR is heart rate; V ITBV V is the intrathoracic blood volume, which is related to body weight W (kg). ITBV =16×W 1.02 (ml); Z 0 is the basic impedance; ε is a dimensionless index of abnormal transthoracic conduction, that is, when Z 0 <20Ω, 0<ε<1; when Z 0 ≥20Ω, ε=1; trr is the RR interval of the electrocardiogram, LVET is the left ventricular ejection time, LVET / Used to correct left ventricular ejection time; K 1 is the correction coefficient, which depends on the impedance waveform change after filtering by the lower embedded system and the upper display and control machine; is the maximum value of left ventricular ejection time and impedance differential; A is the vascular elasticity factor, B is the chest resistance factor, C is the gender difference factor, and D is the body position factor.

[0079] Cardiac output value is the basic hemodynamic parameter, and its function can be further used to calculate other related hemodynamic parameters.

[0080] The calculation formula of cardiac output index SI is as follows:

[0081] SI = SV / BSA;

[0082] Among them, BSA is the body surface area, which is related to body weight and height;

[0083] The calculation formula of cardiac index CI is as follows:

[0084] CI = CO / BSA;

[0085] Wherein, CO is cardiac output;

[0086] The calculation formula of ejection fraction EF is as follows:

[0087] EF = 84 × (64 × (PEP / LVET));

[0088] Among them, PEP is the pre-ejection time, and LVET is the left ventricular ejection time;

[0089] The calculation formula of systemic vascular resistance SVR is as follows:

[0090] SVR = 80 × (MAP × CVP) / CO;

[0091] Among them, MAP is mean arterial pressure and CVP is central venous pressure.

[0092] Among them, the filtering processing method is as follows Figure 3As shown in the figure, after the upper display and control machine receives the data uploaded from the lower embedded system, it performs 50Hz notch, 40Hz low-pass and 0.8Hz high-pass filtering on the ECG signal; and performs 0.2Hz low-pass filtering on the cardiac impedance signal to obtain the basic impedance Z 0 , cardiac impedance signal and Z 0 The impedance change signal ΔZ is obtained by difference, and ΔZ is then processed by 0.8-6Hz bandpass filtering and first-order differential processing to obtain the impedance differential signal dz / dt. The upper display control machine displays the ECG waveform, ΔZ waveform and dz / dt waveform after filtering for further analysis and display.

[0093] Figure 4 The ECG waveform is a graph of the collected electrocardiogram signal. The P wave represents the depolarization of the atrium, the QRS complex represents the depolarization of the ventricle, and the T wave represents the repolarization of the ventricle. The U wave is an inconspicuous small wave that appears about 0.03s after the end of the T wave. It has little scientific research value and is generally believed to be generated by the repolarization process of the left ventricular anterior papillary muscle. The ECG waveform is ahead of the impedance change ΔZ and the impedance differential dz / dt waveform in the time domain, providing a new perspective and method for cardiac output monitoring.

[0094] In the ECG signal, the findpink peak algorithm is used to locate the R point, which is used to calculate the heart rate HR value and the RR interval time Trr.

[0095] Figure 5 The waveforms of impedance change ΔZ and impedance differential dz / dt collected are shown in Figure 1. In the ΔZ waveform, the peak S represents that the blood flowing into the artery is equal to the blood flowing out, and the aortic blood vessel filling degree is the largest at this time. The notch I is the dicrotic canyon point, at which the aortic valve is closed, and then the heart enters the diastole period, and the curve rises to form the dicrotic wave vertex D. The size of the dicrotic wave reflects the elasticity of the heart and blood vessels. At the end of the diastole period, the atrium contracts before the ventricle, forming an atrial contraction wave A. The amplitude of ΔZ reflects the intensity and size of the ejection volume of each heart beat. In the dz / dt waveform, B is the moment when the aortic valve opens, X is the moment when the aortic valve closes, C is the positive wave with the largest amplitude in the differential signal of cardiac impedance, and the left ventricular ejection time LVET starts at point B and ends at point X. (dz / dt)max is the amplitude difference between points C and B.

[0096] In the impedance differential signal dz / dt processing, the signal is first preprocessed by wavelet transform, and then the peak point C of the dz / dt signal is identified by the findpink peak search algorithm; then, the dz / dt signal is derived to obtain the second-order derivative signal of the impedance signal, and the position of point R of the electrocardiogram signal and point C of the cardiac impedance signal are mapped to the first-order derivative signal of the dz / dt signal. In this signal, the only extreme point between point R and point C is determined as point B. Finally, the position of point X is determined. In the dz / dt signal, 0.15Trr after point C is the time position of point X.

[0097] The upper display and control machine acquires ECG and ICG characteristic parameters and calculates the model as follows Figure 6 shown.

[0098] The accuracy of the algorithm was verified using the publicly available ReBeatICG database. The ReBeatICG database contains 48 ICG signals recorded in both static and working states, with impedance differential feature points for each heartbeat annotated by cardiologists for testing the feature point recognition algorithm. The database also contains synchronized ECG signals as a reference for comparison and marking of cardiac events. Figure 7 As shown, by comparing the algorithm with the expert annotation, within the maximum tolerance range of ±10 milliseconds, the accuracy of point B, point C and point X in the static state is 97.58%, 99.11% and 92.12% respectively (in the static state, the total number of points B, C and X is 787); in the working state, the accuracy of point B, point C and point X is 95.08%, 99.07% and 90.29% respectively (in the working state, the total number of points B, C and X is 752). This shows that the method of the present invention can provide medical personnel with more detailed and accurate data, helping them to better assess the cardiovascular status of patients.

[0099] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A non-invasive multi-frequency heart displacement monitoring method, characterized in that: The method comprises the following steps: 1) The upper display and control machine sets the excitation frequency set and the frequency switching interval, and controls the lower embedded system to switch different frequencies in real time according to the set frequency switching interval, thereby realizing real-time switching of multiple frequency points; the excitation frequency set includes 3 low-frequency signals and 3 high-frequency signals, the frequency range of the low-frequency signal is 10-50 kHz, and the frequency range of the high-frequency signal is 50-100kHz; the frequency switching interval is 60 milliseconds or 240 milliseconds; 2) The lower embedded system collects the ECG signal and cardiac impedance signal of the monitored object, and transmits them to the upper display and control machine via wired or wireless WIFI / Bluetooth; the cardiac impedance signal and ECG signal are collected simultaneously by a four-electrode measurement method, and the four electrodes include an output excitation positive electrode, a receiving signal positive electrode, an output excitation negative electrode, and a receiving signal negative electrode; the output excitation negative electrode and the receiving signal negative electrode are attached to the left carotid artery from top to bottom, and the distance between the two electrodes is 3-5cm; the receiving signal positive electrode and the output excitation positive electrode are attached to the intersection of the xiphoid process horizontal line and the left axillary midline from top to bottom, and the distance between the two electrodes is 5-7cm; 3) The upper display and control machine collects cardiac impedance signals and electrocardiogram signals at different excitation frequencies, and performs filtering and wavelet transform analysis on these signals to extract key feature points. According to the feature point data at different excitation frequencies, multi-frequency data dimension reduction and signal fusion are performed. Finally, the cardiac output is calculated through the following cardiac output calculation formula, and other hemodynamic parameters are further derived; The formula for calculating cardiac output is as follows: CO = SV × HR; ； Among them, CO is cardiac output; SV is the stroke volume of the monitored object; HR is heart rate; V ITBV V is the intrathoracic blood volume, which is related to body weight W (kg). ITBV =16×W 1.02 ml; Z0 is the basic impedance; ε is the dimensionless index of abnormal transthoracic conduction, that is, when Z0<20Ω, 0<ε<1; when Z0≥20Ω, ε=1; trr is the ECG RR interval, LVET is the left ventricular ejection time, LVET / Used to correct left ventricular ejection time; K1 is the correction coefficient, which depends on the impedance waveform change after filtering by the lower embedded system and the upper display and control machine; is the maximum value of left ventricular ejection time and impedance differential; A is the vascular elasticity factor, B is the chest resistance factor, C is the gender difference factor, and D is the body position factor; Among them, the impedance differential dz / dt signal is subjected to wavelet transform analysis, the entropy value of the wavelet coefficient is calculated, and the part with entropy value greater than 0.1 is screened out; the final dz / dt signal is obtained by signal reconstruction, and the important feature points are identified, and the dz / dt feature points aortic valve opening time B, maximum amplitude time C, aortic valve closing time X are identified, which are used to calculate the left ventricular ejection time LVET and the maximum value of impedance differential , and then perform model calculations.

2. The non-invasive multi-frequency heart displacement monitoring method according to claim 1, characterized in that: The upper display and control machine filters the received ECG signals and cardiac impedance signals. The specific method is as follows: Perform notch, low-pass and high-pass filtering on the ECG signal to remove 50Hz power frequency interference, myoelectric interference and baseline drift respectively, which are used for waveform display and subsequent feature point R peak recognition to calculate heart rate HR; For the cardiac impedance signal, its basic impedance Z0 is first extracted through low-pass filtering, and then the basic impedance Z0 is subtracted from the cardiac impedance signal to obtain the impedance change signal ΔZ. Then the impedance change signal ΔZ is band-pass filtered to further eliminate noise interference, and finally a first-order differential calculation is performed to obtain the impedance differential dz / dt.

3. The non-invasive multi-frequency heart displacement monitoring method according to claim 2, characterized in that: ECG signal filtering uses 50Hz notch, 40Hz low-pass and 0.8Hz high-pass filtering; The cardiac impedance signal uses a 0.2Hz low-pass and a 0.8-6Hz band-pass.

4. The non-invasive multi-frequency heart displacement monitoring method according to claim 1, characterized in that: In the ECG signal, the R point is located by the findpink peak algorithm to calculate the heart rate HR value and RR interval time Trr; In the impedance differential signal dz / dt processing, the signal is first preprocessed by wavelet transform, and then the peak point C of the dz / dt signal is identified by the findpink peak search algorithm; then, the dz / dt signal is derived to obtain the second-order derivative signal of the impedance signal, and the position of point R of the electrocardiogram signal and point C of the cardiac impedance signal are mapped to the first-order derivative signal of the dz / dt signal. In this signal, the only extreme point between point R and point C is determined as point B. Finally, the position of point X is determined. In the dz / dt signal, 0.15Trr after point C is the time position of point X.

5. The non-invasive multi-frequency heart displacement monitoring method according to claim 1, characterized in that: The lower embedded system includes a master control module, a cardiac impedance signal and electrocardiogram signal acquisition module, a wireless transmission module, a power management module, and a USB wired transmission module; the cardiac impedance signal and electrocardiogram signal acquisition module acquires cardiac impedance signals and electrocardiogram signals in real time according to the control of the upper display and control machine, preliminarily pre-processes the signals, and then sends them to the upper display and control machine through the USB wired transmission module or the wireless transmission module.

6. The non-invasive multi-frequency heart displacement monitoring method according to claim 5, characterized in that: The master control module uses the STM32L452 chip, which is responsible for effectively managing and monitoring the operating status of the lower embedded system; the cardiac impedance signal and electrocardiogram signal acquisition module uses the ADPD6000 chip to capture physiological signal data in real time at a sampling rate of 500Hz; the wireless transmission module uses the ESP32-PICO-D4 chip to achieve convenient Bluetooth or WIFI transmission of data, ensuring the efficiency and reliability of information transmission; the power management module uses the BQ34Z100PWR-G1 chip, which can monitor the battery status and related information in real time to ensure the continuous and stable operation of the system.

7. The non-invasive multi-frequency heart displacement monitoring method according to claim 1, characterized in that: Other hemodynamic parameters include cardiac output index SI, cardiac index CI, ejection fraction EF, systemic vascular resistance SVR; The calculation formula of cardiac output index SI is as follows: SI = SV / BSA; Among them, BSA is the body surface area, which is related to body weight and height; The calculation formula of cardiac index CI is as follows: CI = CO / BSA; Wherein, CO is cardiac output; The calculation formula of ejection fraction EF is as follows: EF = 84 × (64 × (PEP / LVET)); Among them, PEP is the pre-ejection time, and LVET is the left ventricular ejection time; The calculation formula of systemic vascular resistance SVR is as follows: SVR = 80 × (MAP × CVP) / CO; Among them, MAP is mean arterial pressure and CVP is central venous pressure.

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