A portable dynamic electrocardio blood pressure intelligent recording instrument

Abstract

This invention relates to the field of electrocardiogram (ECG) and blood pressure monitoring technology, specifically to a wearable intelligent ECG and blood pressure recorder. It includes a signal processing unit, a display unit, and several monitoring probes. This invention overcomes the limitations of existing technologies that can only assess signal quality holistically but cannot pinpoint specific probe deviations by constructing an anomaly detection mechanism based on three independent dimensions: an ECG spatial transfer matrix, a pulse wave conduction time trigonometric additivity constraint test, and a blood pressure deviation feature vector. When a probe experiences a minute displacement, it is reflected in the corresponding component of the ECG deviation feature vector, the pulse wave constraint violation vector, and the blood pressure deviation feature vector. After weighted fusion of these three components, automatic identification and alerts for probe deviation are achieved, avoiding the user's need to blindly check all probes one by one. This significantly shortens the anomaly response time, reduces blood pressure measurement errors and ECG waveform artifacts caused by probe misalignment, and ensures the continuous effectiveness of dynamic monitoring data.

Description

Technical Field

[0001] This invention relates to the field of electrocardiogram and blood pressure monitoring technology, and more specifically, to a portable dynamic electrocardiogram and blood pressure intelligent recorder. Background Technology

[0002] Wearable dynamic electrocardiogram and blood pressure recorders typically employ multiple independently attachable monitoring probes, placed at predetermined anatomical locations on the chest and left upper arm, respectively. Each probe integrates both electrocardiogram (ECG) sensing electrodes and a photoplethysmography (PPG) sensor unit. Its core working principle lies in: using the ECG signals from different probes to form a multi-lead ECG recording for the diagnosis of events such as arrhythmias; and simultaneously calculating arterial blood pressure values ​​beat-by-beat by measuring the time difference (pulse wave transit time) between characteristic points of the pulse wave at any two PPG sensor units, combined with individualized calibration parameters calibrated via a cuff blood pressure monitor. To ensure the accuracy and stability of these functions, the probes must fit tightly against the skin, and the actual lead axis direction of the ECG electrodes and the actual spacing of the PPG sensors along the arterial direction must strictly conform to the calibration settings.

[0003] In practical use, the probe is easily displaced by the user's walking, arm swinging, sleeping, and repeated friction from clothing. This displacement, often ranging from millimeters to centimeters, while not causing complete signal loss, is sufficient to fundamentally alter the characteristics of the recorded signal. In the case of ECG signals, probe movement means a change in the lead vectors of the multiple ECG leads formed by that probe, essentially altering the projection coefficients of the ECG signal acquired by the probe in different lead spaces. Simultaneously, skin contact impedance changes due to variations in skin stretching and sweat distribution under the probe, causing local signal amplitude attenuation and phase distortion. These effects collectively cause a significant drift in the second-order statistical properties—the spatial covariance structure—of the original multi-channel ECG signals relative to the baseline state. However, this drift is not caused by pathological changes in cardiac electrical activity itself, but solely by deterioration of physical contact conditions, thus constituting interference with ECG analysis.

[0004] Current methods for detecting signal anomalies primarily focus on overall signal quality assessment, such as calculating the signal-to-noise ratio (SNR), detecting flat segments or saturation clipping, and performing correlation analysis with pre-stored templates. While these methods can identify severely degraded signals in a particular channel, they struggle to pinpoint the exact source of the fault in multi-probe systems. When multiple probes are simultaneously in a critical offset state or exhibit only slight offsets, the SNR may still be within acceptable limits, but ECG waveform distortion and blood pressure deviations can significantly impact clinical interpretation. If the system only provides a general "signal anomaly" message, the user is left unsure which probe needs to be reattached, forcing them to press and reattach all probes sequentially. This process prevents effective measurements, wastes valuable monitoring time, and may even cause missed paroxysmal cardiovascular events, severely diminishing the device's practicality in dynamic monitoring. Therefore, there is an urgent need for a technical solution that can fully exploit the internal physical laws of multi-probe, multi-modal physiological signals, and accurately locate the monitoring probe experiencing positional deviations based on the disruptive patterns of abnormal data in spatial structure, geometric constraints, and blood pressure consistency.

[0005] Therefore, there is an urgent need for a portable, dynamic ECG and blood pressure smart recorder capable of responding to abnormal deviations. Summary of the Invention

[0006] The purpose of this invention is to provide a portable, dynamic electrocardiogram and blood pressure smart recorder to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, a portable dynamic electrocardiogram and blood pressure smart recorder is provided, including multiple monitoring probes. The monitoring probes are used to attach to multiple predetermined positions on the user's body surface. Each monitoring probe integrates an electrocardiogram sensing electrode and a photoplethysmography (PPG) wave sensing unit. The electrocardiogram sensing electrodes are used to acquire local electrocardiogram signals; The photoplethysmography pulse wave sensing unit is used to acquire local pulse wave signals. The display terminal is electrically connected to the plurality of monitoring probes, and the display terminal includes a signal processing unit and a display unit; The signal processing unit is used to acquire multi-channel electrocardiogram signals and multi-channel pulse wave signals synchronously collected by the multiple monitoring probes, and to perform abnormal deviation processing. The specific processing steps are as follows: S301. Based on the multi-channel ECG signal, construct a real-time ECG spatial transfer matrix, calculate the deviation of the real-time ECG spatial transfer matrix relative to the pre-stored reference ECG spatial transfer matrix, and obtain an ECG offset feature vector, wherein each element of the ECG offset feature vector corresponds to the ECG signal distortion contribution of a monitoring probe. S302. Extract pulse wave feature points from the multi-channel pulse wave signal, calculate the pulse wave conduction time between every two monitoring probes, and construct a pulse wave conduction time matrix. S303. Based on the pulse wave conduction time matrix and the pre-stored individualized calibration parameters, calculate the real-time blood pressure value step by step to form a real-time blood pressure sequence. S304. Check whether the pulse wave propagation time matrix satisfies the preset triangular additivity constraint, and generate a pulse wave constraint violation vector. S305. Calculate the degree of deviation of the real-time blood pressure sequence from the reference blood pressure sequence to obtain the blood pressure deviation feature vector; S306. The ECG deviation feature vector, the pulse wave constraint violation vector, and the blood pressure deviation feature vector are weighted and fused to obtain the positional anomaly score of each monitoring probe. S307. Based on the location anomaly score, determine the monitoring probe with location deviation, generate a prompt message containing the identifier of the monitoring probe, and output it through the display unit.

[0008] Compared with the prior art, the beneficial effects of the present invention are as follows: This portable dynamic ECG and blood pressure smart recorder overcomes the limitations of existing technologies that can only assess signal quality holistically but cannot pinpoint specific probe deviations by constructing an anomaly detection mechanism with three independent dimensions: an ECG spatial transfer matrix, a pulse wave conduction time triangular additivity constraint test, and blood pressure deviation characteristics. When a probe experiences a minute displacement, it is reflected in the corresponding component of the ECG deviation feature vector, the pulse wave constraint violation vector, and the blood pressure deviation feature vector. After weighted fusion of these three metrics, the system automatically identifies and alerts users to probe deviations, avoiding the need for users to blindly check all probes one by one. This significantly shortens the anomaly response time, reduces blood pressure measurement errors and ECG waveform artifacts caused by probe misalignment, and ensures the continuous effectiveness of dynamic monitoring data. Attached Figure Description

[0009] Figure 1 This is a schematic diagram of the overall recorder structure of the present invention; Figure 2 This is a block diagram of the overall monitoring system structure of the present invention; The meanings of the labels in the diagram are as follows: 10. Display terminal; 20. Bundle end; 30. Monitoring probe. Detailed Implementation

[0010] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0011] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0012] Please see Figure 1-2 As shown, a wearable dynamic electrocardiogram and blood pressure smart recorder is provided, including: Multiple monitoring probes 30 are used to attach to multiple predetermined locations on the user's body surface. Each monitoring probe integrates an electrocardiogram sensing electrode and a photoplethysmography (PPG) sensing unit. Among them, the electrocardiogram sensing electrodes are used to collect local electrocardiogram signals; The photoplethysmography (PPG) sensor unit is used to acquire local pulse wave signals. Display terminal 10 is electrically connected to multiple monitoring probes 30, and display terminal 10 includes a signal processing unit and a display unit; The signal processing unit is used to acquire multi-channel electrocardiogram signals and multi-channel pulse wave signals simultaneously collected by multiple monitoring probes 30, and to perform abnormal deviation processing. The specific processing steps are as follows: S301. Based on multi-channel ECG signals, construct a real-time ECG spatial transfer matrix, calculate the deviation of the real-time ECG spatial transfer matrix relative to the pre-stored reference ECG spatial transfer matrix, and obtain the ECG offset feature vector. Each element of the ECG offset feature vector corresponds to the ECG signal distortion contribution of a monitoring probe. S302. Extract pulse wave feature points from the multi-channel pulse wave signal, calculate the pulse wave conduction time between every two monitoring probes, and construct the pulse wave conduction time matrix. S303. Based on the pulse wave conduction time matrix and the pre-stored individualized calibration parameters, calculate the real-time blood pressure value step by step to form a real-time blood pressure sequence. S304. Check whether the pulse wave propagation time matrix satisfies the preset triangular additivity constraint, and generate a pulse wave constraint violation vector, wherein each element of the pulse wave constraint violation vector represents the degree of violation of the triangular additivity constraint by the corresponding monitoring probe. S305. Calculate the degree of deviation of the real-time blood pressure sequence from the baseline blood pressure sequence to obtain the blood pressure deviation feature vector; S306. Weighted fusion of ECG deviation feature vector, pulse wave constraint violation vector and blood pressure deviation feature vector is performed to obtain the positional abnormality score of each monitoring probe. S307. Based on the position anomaly score, determine the monitoring probe with position deviation, generate a prompt message containing the identifier of the monitoring probe, and output it through the display unit.

[0013] During the monitoring process, since the monitoring probe 30 is attached to the surface of the user's body, it collects ECG data through the ECG sensing electrodes and photoplethysmography (PPG) sensing unit integrated inside. However, the monitoring probe 30 has a limited size and the range of the designated monitoring area is limited. Positional deviation can easily occur during the attachment monitoring process, resulting in the acquired ECG data not being able to effectively represent the current ECG state of the user.

[0014] Based on the above problems, this solution aims to address how to identify abnormal monitoring probes 30 and provide adaptive alerts. The specific solution is as follows: The corresponding monitoring probe 30 integrates an electrocardiogram (ECG) sensing electrode and a photoplethysmography (PPG) sensing unit. Each monitoring probe forms an independent attachable component, with its bottom serving as a working surface that contacts the user's skin. On this working surface, at least one ECG sensing electrode and an optical window for the PPG sensing unit are simultaneously provided.

[0015] The ECG sensing electrodes are made of conductive materials, such as silver-plated metal sheets, silver chloride electrodes, or stainless steel conductive fabric. Their undersides are in direct contact with the skin to pick up local ECG potentials on the skin surface where the probe is attached. Each monitoring probe's ECG sensing electrode records the potential difference between its position and a common reference electrode, thus obtaining a unipolar lead signal that reflects the projection of local myocardial electrical activity. This configuration allows multiple probes to simultaneously acquire multi-channel ECG signals, forming a spatially distributed array of body surface potentials.

[0016] The photoplethysmography (PPG) sensing unit is integrated within a single probe. Its core comprises one or more light-emitting sources and one or more photodetectors. The light source typically uses a green or infrared LED, emitting light that enters the skin through an optical window, illuminating the subcutaneous arterioles and capillary beds. Some of the light is absorbed by hemoglobin in the blood, while the remainder is scattered by the tissue and returns to the skin surface, where it is received by the photodetector and converted into an electrical signal. Because arterial blood volume changes periodically with heartbeats, the amount of light absorbed also exhibits a corresponding pulsating component. This pulsating component constitutes the PPG signal, used to characterize the pulsating pattern of the local vascular bed at the probe's attachment location.

[0017] Simultaneously, the ECG sensing electrodes and the photoplethysmography (PPG) pulse wave sensing unit are physically arranged closely on the same flexible substrate, with the distance between their center points controlled within the range of a few millimeters to one centimeter, which can be considered approximately the same point. Therefore, each monitoring probe can synchronously acquire local ECG signals and local pulse wave signals at the same anatomical location. This co-point acquisition design ensures strict temporal synchronization and spatial correspondence between the ECG signal and pulse wave signal output by the same probe, providing a reliable data foundation for subsequent pulse wave conduction time calculation and ECG-pulse coupling feature extraction based on joint ECG and pulse wave analysis.

[0018] Furthermore, since there are multiple monitoring probes 30, in order to ensure the orderly progress of the monitoring process and prevent tangled wiring, this solution sets up a cluster end 20 between the display end 10 and each monitoring probe 30. The cluster end 20 has a number of limiting channels that are the same as the number of monitoring probes 30. Each monitoring probe 30 extends outward through the limiting channel at the corresponding position, forming positional isolation between it and the adjacent monitoring probe 30, thereby reducing wiring disorder.

[0019] Furthermore, in the human arterial tree, pulse waves propagate from the heart along the aorta and its branches. When multiple monitoring probes 30 are attached along the arterial path in a known order, the pulse wave conduction time (PTT) between any two probes is equal to the pulse wave propagation time in the arterial segment between them, a value determined by the physical length of the arterial segment and the local pulse wave propagation velocity. If three probes... If all probes are in the correct anatomical position, and probe j is located on the arterial path from probe i to probe k, then the conduction time should strictly meet the following conditions. In more common probe arrangements, even without a strict linear relationship, the tree-like structure of arterial branches allows for easy identification of the arterial network from the probe. To the probe The propagation path must pass through the lowest common branch point of the two on the arterial tree, therefore the conduction time... It equals the weighted sum of the arc lengths along the tree path, and and The summation path passes through the node This path maintains a certain degree of quasi-additivity with the direct path under certain constraints. For any three probes at different positions, when all probes have no positional shift, this physiological constraint manifests as follows: It is controlled within an extremely small value. This value mainly stems from minor anatomical differences caused by incomplete path overlap, slight non-uniformity of pulse wave velocity along the artery, and random errors in signal feature point detection. Therefore, it can be controlled by a preset error threshold. Covered by.

[0020] Corresponding error threshold The specific values ​​are determined during system initialization using the baseline acquisition mode: ensuring all probes are correctly attached, multiple sets of pulse wave conduction time data are continuously recorded, and calculations are performed for all possible ternary combinations. The error threshold is calculated by adding three times the standard deviation to the sample mean. This ensures that the violation amount under normal conditions is less than the error threshold with a very high probability. .

[0021] When a monitoring probe shifts position, the anatomical point to which it is attached changes, causing all pulse wave propagation time values ​​centered on that probe to be superimposed with a deviation related to the displacement. For a ternary array including the shifted probe, the original quasi-additivity relationship is broken, resulting in a violation. The system will systematically exceed the threshold error threshold. Conversely, if the ternary array does not include an offset probe and consists only of normal probes, the violation amount remains within the error threshold. Within this range. Therefore, by traversing all ternary combinations and quantifying the cumulative degree of violation, the offset effect can be concentrated on the evaluation index of a specific probe.

[0022] Based on this, in this scheme, the number of monitoring probes (30) must be at least 3 to construct at least one ternary combination and initiate the constraint check. Furthermore, for... There are [number] probes, and the total number of different ternary combinations is [number]. Pulse wave constraints violate vector... The first in element That is, corresponding to the probe Its value includes the probe. The sum of the violations of all ternary combinations, optionally divided by the number of probes. Number of ternary combinations To perform normalization, the specific algorithm formula is as follows: ; in This indicates that the pulse wave constraint violates the vector. The Each component characterizes the probe. The overall degree of violation of the triangular additivity constraint. Indicates the entire set of probes Remove probe The subset obtained after that, i.e., excluding All external probes, Indicates from the probe To the probe The pulse wave conduction time, the value of which is equal to the probe's... Subtract the probe at the characteristic point of the pulse wave At the characteristic point time, Indicates from the probe To the probe pulse wave conduction time, Indicates from the probe To the probe pulse wave conduction time, This represents absolute value operations.

[0023] When the probe When no positional shift occurs, the probe of Within the baseline range; If the probe If a significant shift occurs, then all... The violation rates of the ternary combinations at one end all increased significantly, and the probe... of When it exceeds the baseline level range.

[0024] By analyzing vectors By analyzing the numerical distribution of each element, the signal processing unit can identify... The probe showed a significantly abnormally high elevation, which was identified as the source of the positional shift.

[0025] Furthermore, to perform further position offset analysis, a specific analysis is conducted using the signal processing unit set in the display terminal 10. The specific implementation method is as follows: First, the multi-channel electrocardiogram signals and multi-channel pulse wave signals collected simultaneously by multiple monitoring probes are uploaded to the signal processing unit; For multi-channel ECG signals, a real-time ECG spatial transfer matrix is ​​constructed. The deviation of the real-time ECG spatial transfer matrix from the pre-stored reference ECG spatial transfer matrix is ​​calculated to obtain the ECG offset feature vector. Each element of the ECG offset feature vector corresponds to the ECG signal distortion contribution of a monitoring probe, i.e.: Multichannel electrocardiogram signals are distributed at different locations on the body surface. Data was collected simultaneously by several monitoring probes. Within the preset analysis time window, [data was collected]. The ECG signals from each probe are represented as follows: 3D column vector ,in Indicates the first Each probe at time The electrocardiogram potential value; according to 3D column vector Constructing a real-time ECG spatial transfer matrix This is used to capture the second-order statistical correlation structure between signals acquired by each probe, i.e., the energy distribution and cross-correlation characteristics of ECG signals from each channel in the spatial dimension. Furthermore, it includes a real-time ECG spatial transfer matrix. Through calculation The covariance matrix within the time window is obtained, and the specific expression is as follows: ; Where L is the number of sampling points within the time window. express The mean vector within the time window.

[0026] Simultaneous real-time ECG spatial transfer matrix It is A real symmetric matrix; Its diagonal elements Indicates the first The variance of the ECG signal at each probe reflects the signal energy acquired by that probe. off-diagonal elements Indicates the first The probe and the first The covariance between the ECG signals from the two probes reflects the spatial correlation strength of ECG activity at the two probes.

[0027] When all probes are correctly attached The structure is determined by the inherent spatial propagation mode of cardiac electrical activity and the fixed geometric relationship between the probes; When a probe shifts position, the direction of the corresponding ECG lead axis and the skin contact impedance both change, leading to... Systematic amplitude and structural changes occur in all elements related to the probe (i.e., the i-th row and the i-th column).

[0028] Meanwhile, this scheme has a pre-set reference ECG spatial transfer matrix. The baseline electrocardiogram spatial transfer matrix During system initialization, after confirming that all probes are in the correct anatomical position and in stable contact, a reference matrix and a baseline ECG spatial transfer matrix are calculated and stored using the same method described above. The spatial transmission characteristics of electrocardiogram signals under normal attachment conditions were recorded.

[0029] Therefore, the real-time matrix Relative to the reference matrix The deviation is calculated by measuring the difference matrix between the two. This is used for quantification. The difference matrix contains distortion information for each channel introduced by probe offset. To decompose the global bias to each probe, a selection vector is defined. For the first One element is 1, and the rest are 0. A column vector. Acting on the difference matrix Extractable Middle and the first The component related to the probe. This component... norm That is No. The vector length of the column, which combines the first... The variation in covariance between this probe and all other probes. To eliminate the influence of differences in the fundamental signal strength of different probes, the norm of the corresponding column of the reference matrix is ​​used. Normalization is performed. Based on this, the ECG deviation feature vector is defined. The element The specific algorithm formula is as follows: ; in This represents the degree of relative distortion of the ECG spatial transmission structure associated with the i-th probe relative to the baseline state. When the probe... When the adhesion is good, the covariance relationship between the signal of the corresponding channel and other channels remains unchanged. Maintain a baseline level close to zero; When the probe When positional displacement occurs, the rotation of the ECG lead axis and the change in contact resistance cause... Significant changes were observed in the rows and columns related to the probe, after normalization. It will increase significantly.

[0030] All probes Together they constitute the ECG deviation feature vector Each element of this vector corresponds to the contribution of ECG signal distortion from a monitoring probe.

[0031] Furthermore, for multi-channel pulse wave signals, it is necessary to extract pulse wave feature points, calculate the pulse wave propagation time between every two monitoring probes, and construct a pulse wave propagation time matrix, i.e.: Each monitoring probe 30's internal photoplethysmography (PPG) sensing unit outputs a continuous PPG signal. After the signal is filtered by a bandpass filter to remove high-frequency noise and low-frequency baseline drift, the feature point is selected as the pulse wave initiation point, i.e., the initial moment of rapid pulse wave rise in the cardiac cycle, corresponding to the instant of left ventricular ejection and rapid expansion of arterial volume. The detection employs a first-order differential thresholding method: calculating the discrete first-order derivative of the signal, identifying the zero-crossing point where the derivative changes from negative to positive and exceeds a preset slope, and using the moment when the signal amplitude rises to a certain proportion above the minimum value of the previous cycle as the feature point. One probe records the feature point timestamp of the nth beat in a continuous cardiac cycle. This constitutes the pulse wave characteristic point sequence of the probe.

[0032] In the calculation of pulse wave propagation time, for any two different probes... and Within the same cardiac cycle n, the pulse wave conduction time is defined. , representing a probe Feature point time and probe The time difference at the feature point is expressed as follows: ; Pulse wave conduction time Characterizing pulse wave from the probe The signal propagates from the location of the artery to the probe. The time required to reach the current location, when and When the order is reversed, the antisymmetric relation is satisfied. .

[0033] Subsequently, based on the pulse wave conduction time Define the pulse wave conduction time matrix For each cardiac cycle Organize the conduction time between all probe pairs into a single... matrix Its elements are defined as the pulse wave propagation time matrix. The specific expression is as follows: ; Where the matrix It is a real antisymmetric matrix, which fully encodes the spatiotemporal relationship of pulse wave propagation among N probes in the current beat.

[0034] After completing the construction of the pulse wave conduction time matrix, the real-time blood pressure value is calculated step by step based on the pulse wave conduction time matrix and the pre-stored individualized calibration parameters to form a real-time blood pressure sequence.

[0035] Individualized calibration parameters were obtained in the baseline acquisition mode during the initial system wear and after confirming correct probe placement. The user remained at rest, and reference blood pressure was measured using a standard cuff blood pressure monitor, while simultaneously recording the pulse wave transit time across multiple probes. For each probe pair... Establish a linear mapping model between conduction time and blood pressure: ; ; in, Indicates that the probe is used for Estimated systolic pressure Indicates that the probe is used for Estimated diastolic blood pressure , , as well as These are the individualized coefficients obtained through least squares fitting. The set of calibration parameters is stored in the non-volatile memory of display terminal 10 for use during real-time blood pressure calculation.

[0036] During the real-time monitoring phase, for each cardiac cycle Using the calibrated parameters and the currently measured conduction time Calculate the estimated blood pressure values ​​for each probe. Taking systolic blood pressure (diastolic blood pressure is calculated using the same method) as an example: ; Thus, in each beat, These blood pressure estimates together constitute the real-time blood pressure set of the current image.

[0037] The blood pressure estimates from all consecutive cardiac cycles are arranged chronologically to form a real-time blood pressure sequence. Specifically, for each probe pair... Record its individual blood pressure sequence .

[0038] In the context of probe offset determination, a baseline blood pressure sequence is also required. This is the estimated average blood pressure value for each probe pair under the baseline acquisition mode, assuming correct probe attachment. Real-time blood pressure value. Compared with the benchmark value The deviation between them directly reflects the blood pressure estimation error introduced by the change in probe position. This information is used to construct the blood pressure deviation feature vector to achieve collaborative positioning of the offset probe.

[0039] Furthermore, regarding the calculation of the pulse wave constraint violation vector, the pulse wave constraint violation vector is generated by checking whether the pulse wave propagation time matrix satisfies the preset triangular additivity constraint. Each element of the pulse wave constraint violation vector represents the degree of violation of the triangular additivity constraint by the corresponding monitoring probe. As can be seen from the above, if three probes If all probes are in the correct anatomical position, and probe j is located on the arterial path from probe i to probe k, then the conduction time should strictly meet the following conditions. In more common probe arrangements, even without a strict linear relationship, the tree-like structure of arterial branches allows for easy identification of the arterial network from the probe. To the probe The propagation path must pass through the lowest common branch point of the two on the arterial tree, therefore the conduction time... It equals the weighted sum of the arc lengths along the tree path, and and The summation path passes through the node This path maintains a certain degree of quasi-additivity with the direct path under certain constraints. For any three probes at different positions, when all probes have no positional shift, this physiological constraint manifests as follows: It is controlled within an extremely small value. This value mainly stems from minor anatomical differences caused by incomplete path overlap, slight non-uniformity of pulse wave velocity along the artery, and random errors in signal feature point detection. Therefore, it can be controlled by a preset error threshold. Covered by.

[0040] The following conditions must be met: ; All One probe Arranged according to probe number, this constitutes the pulse wave constraint violation vector at the nth beat. ; When performing pulse wave constraints, the vector is violated. During the judgment process: When the probe When the attachment is correctly positioned and there is no misalignment, all conduction times with that endpoint accurately reflect the true arterial path length. At this point, it includes... Each of the ternary combinations satisfies the approximate tree metric relation. This holds true for the vast majority of combinations, and after averaging... (n) remains near a very low baseline value, which is determined by measurement noise and the inherent slight non-uniformity of the arterial tree; When probe i shifts position, its attachment point moves along the skin surface. This displacement changed the probe With other arbitrary probes The actual arterial path length between, in the measured and All of these include a deviation term related to displacement projection. Therefore, for any object containing a probe... Triple combination Two involving conduction time and Simultaneous distortion, and Since it does not involve a probe Its value remains unchanged. The deviation is in the amount of violation. The calculations cannot cancel each other out; instead, they amplify and accumulate, leading to... Systematically break through the threshold After averaging, (n) is significantly higher than the corresponding values ​​of other normal probes.

[0041] Based on this The magnitude of each element directly reflects the probability of the corresponding probe shifting position. The larger (n) is, the larger the probe... The more likely it is to be the source of positional deviation, the clearer and quantifiable discrimination basis becomes for subsequent weighted fusion with ECG deviation feature vector and blood pressure deviation feature vector.

[0042] Regarding the calculation of the blood pressure deviation feature vector, based on the linear mapping model described above, the result is obtained for any two different probes. and Blood pressure estimates (Taking systolic blood pressure as an example) and blood pressure sequence And extract the baseline blood pressure value. ,in ,and This represents the total number of valid cardiac cycles within the baseline data collection period.

[0043] For the Take a picture, use the camera to... Real-time blood pressure value Relative to its benchmark value The deviation is defined as the absolute value of the difference between the two: ; This deviation measure measures the error in blood pressure estimation caused by factors such as changes in probe position, fluctuations in physiological state, or measurement noise. When all probes are correctly attached around Slight fluctuations This only reflects normal blood pressure variability and measurement error; When a probe shifts position, the conduction time of all probe pairs with that probe as the endpoint introduces a system deviation, resulting in corresponding... Large deviation , Significantly increased.

[0044] Based on offset Constructing a blood pressure deviation feature vector will define the probe. In the Blood pressure readings deviate from the target range For all probes The average deviation of the probe pair, i.e.: ; in For the complete set of probes Summation and traversal All probes except ,common item; If the probe If a positional shift occurs, then... For all probe pairs at one end conduction time All were distorted and propagated through the calibration formula. Consistent deviations from their respective benchmark values ,lead to Significantly increased; Conversely, if the probe No offset; even if other probes in the system are offset, since it does not involve the probe itself. Those probes exist The weights allocated to each are limited and their directions are inconsistent. The increase is much smaller than the component corresponding to the actual offset probe.

[0045] Finally, all N probes Arranged by serial number, we get the number. Blood pressure deviation from the feature vector in the image Blood pressure deviation from the feature vector Each element The abnormal contribution of blood pressure estimation corresponding to a monitoring probe.

[0046] Specifically, in order to perform actual anomaly scoring, specific anomaly calculations are performed on each monitoring probe 30. This scheme uses weighted fusion of the ECG deviation feature vector, pulse wave constraint violation vector, and blood pressure deviation feature vector to obtain the positional anomaly score of each monitoring probe. The specific method is as follows: First, to unify these heterogeneous features with different dimensions into a comparable probe offset risk measure, weighting coefficients are defined. These correspond to the relative importance of ECG deviation features, pulse wave constraint violation features, and blood pressure deviation features, respectively. The weighting coefficients are all non-negative real numbers, satisfying... .

[0047] For the The monitoring probe was placed in the [number]th monitoring probe. The three feature components captured are linearly weighted and summed to obtain the anomaly score of the probe at the current capture location. The specific expression is as follows: ; in The ECG deviation feature vector at the th The first shot One portion, The pulse wave constraint violation vector is represented at the th... The first shot One portion, This indicates that the blood pressure deviation eigenvector is at the th... The first shot Each component.

[0048] All The scores of each probe are arranged according to its serial number, thus forming a location anomaly scoring vector. ,Right now: ; The first of the scoring vectors Each element is the probe. Comprehensive location anomaly score; If a certain explorer If a positional shift occurs, then , as well as Synchronous increase, weighted fusion Significantly exceeding the normal fluctuation range; If the probe Normally, even if a single feature rises slightly due to accidental noise, the fusion score will remain near the baseline because the other two features remain low. This multimodal complementarity mechanism significantly enhances the identification and robustness of the offset probe, effectively reducing the risk of false alarms or missed alarms for single features. Anomaly scores are determined by an anomaly score threshold, and the overall location anomaly score is then analyzed. Probes that exceed the abnormal scoring threshold are marked as abnormal probes, while those that do not are marked as normal probes.

[0049] Finally, the judgment result generates a prompt message containing the identification of the monitoring probe, which is output through the display unit and presented to the user in a visual manner. The output formats include text prompts (using large fonts to clearly display the identification of abnormal probes and brief adjustment instructions, ensuring that users can quickly identify them from a distance or while in motion), a graphical probe status panel (a human body diagram or probe distribution diagram is pre-installed in the display unit, with each probe marked with an independent icon on the diagram. Normal probe icons are represented by green or gray, and abnormal probe icons switch to red, flashing, or highlighted styles. Scoring values ​​or deviation level indicators can be added next to the icons to make the status of multiple probes clear at a glance), and color-coded indicators (color-coded indicators use the border of the display unit or status indicator bar to reflect the overall probe status of the system through color changes. All probes are green when they are normal, and yellow or red when any probe is deviating, with the color deepening as the degree of deviation increases).

[0050] The prompt message is updated continuously or periodically. When the user adjusts the specified probe, the signal processing unit recalculates the position anomaly score in subsequent analysis cycles. If the score falls back to the normal range, the prompt message is automatically cleared, and the corresponding probe icon returns to its normal state.

[0051] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A portable dynamic electrocardiogram and blood pressure intelligent recorder, characterized in that: include: Multiple monitoring probes (30) are used to be attached to multiple predetermined positions on the user's body surface, and each monitoring probe integrates an electrocardiogram sensing electrode and a photoplethysmography (PPG) sensing unit. The electrocardiogram sensing electrodes are used to acquire local electrocardiogram signals; The photoplethysmography pulse wave sensing unit is used to acquire local pulse wave signals. The display terminal (10) is electrically connected to the plurality of monitoring probes (30), and the display terminal (10) includes a signal processing unit and a display unit; The signal processing unit is used to acquire multi-channel electrocardiogram signals and multi-channel pulse wave signals synchronously collected by the multiple monitoring probes (30), and to perform abnormal deviation processing. The specific processing steps are as follows: S301. Based on the multi-channel ECG signal, construct a real-time ECG spatial transfer matrix, calculate the deviation of the real-time ECG spatial transfer matrix relative to the pre-stored reference ECG spatial transfer matrix, and obtain an ECG offset feature vector, wherein each element of the ECG offset feature vector corresponds to the ECG signal distortion contribution of a monitoring probe. S302. Extract pulse wave feature points from the multi-channel pulse wave signal, calculate the pulse wave conduction time between every two monitoring probes, and construct a pulse wave conduction time matrix. S303. Based on the pulse wave conduction time matrix and the pre-stored individualized calibration parameters, calculate the real-time blood pressure value step by step to form a real-time blood pressure sequence. S304. Check whether the pulse wave propagation time matrix satisfies the preset triangular additivity constraint, and generate a pulse wave constraint violation vector. S305. Calculate the degree of deviation of the real-time blood pressure sequence from the reference blood pressure sequence to obtain the blood pressure deviation feature vector; S306. The ECG deviation feature vector, the pulse wave constraint violation vector, and the blood pressure deviation feature vector are weighted and fused to obtain the positional anomaly score of each monitoring probe. S307. Based on the location anomaly score, determine the monitoring probe with location deviation, generate a prompt message containing the identifier of the monitoring probe, and output it through the display unit.

2. The portable dynamic electrocardiogram and blood pressure intelligent recorder according to claim 1, characterized in that: The number of monitoring probes (30) configured is at least 3, for constructing a ternary combination.

3. The portable dynamic electrocardiogram and blood pressure intelligent recorder according to claim 1, characterized in that: The method for obtaining the ECG offset feature vector in S301 includes the following steps: S3011. Within the preset analysis time window, The electrocardiogram signals of each monitoring probe (30) are represented as follows: 3D column vector ,in Indicates the first Each probe at time The electrocardiogram potential value; S3012, according to 3D column vector Constructing a real-time ECG spatial transfer matrix , used to capture the second-order statistical correlation structure between the signals collected by each monitoring probe (30); S3013, Preset baseline ECG spatial transfer matrix ; S3014, Norm of the corresponding column of the reference matrix Normalization is performed to define the relative distortion of the ECG spatial transmission structure associated with the i-th monitoring probe (30) relative to the baseline state. ; S3015, relative distortion of all probes Together they constitute the ECG deviation feature vector .

4. The portable dynamic electrocardiogram and blood pressure intelligent recorder according to claim 1, characterized in that: The method for constructing the pulse wave propagation time matrix in S302 includes the following steps: S3021. The photoplethysmography (PPG) sensor unit inside each monitoring probe (30) outputs a continuous PPG signal. The PPG signal is filtered by a bandpass filter to remove high-frequency noise and low-frequency baseline drift, and the starting point of the PPG is selected as the feature point. S3022. Taking the moment when the signal amplitude rises to a certain proportion above the minimum value of the previous period as the feature point, for the first... One probe records the feature point timestamp of the nth beat in a continuous cardiac cycle. , which constitute the pulse wave characteristic point sequence of the monitoring probe (30); S3023, For any two different probes and Within the same cardiac cycle n, the pulse wave conduction time is defined. ; S3024, Based on pulse wave conduction time Define the pulse wave conduction time matrix .

5. The portable dynamic electrocardiogram and blood pressure intelligent recorder according to claim 1, characterized in that: The method for generating a real-time blood pressure sequence in S303 includes the following steps: S3031. Measure reference blood pressure using a standard cuff blood pressure monitor and record the pulse wave conduction time for each probe pair. Establish a linear mapping model between conduction time and blood pressure; S3032, For each cardiac cycle Using the calibrated parameters and the currently measured conduction time Calculate the blood pressure estimate for each probe pair. ; S3033. Arrange the blood pressure estimates of all continuous cardiac cycles in chronological order to form a real-time blood pressure sequence. .

6. The portable dynamic electrocardiogram and blood pressure intelligent recorder according to claim 1, characterized in that: The method for generating the pulse wave constraint violation vector in S304 includes the following steps: S3041, Define three probes The conduction time when all components are in the correct anatomical position satisfies the characteristic, as shown in the following expression: ； S3042. Define the physiological constraints for any three probes at different positions, when all probes are without positional displacement. Define the violation quantity for all ternary combinations, characterized as And make a judgment: when > Then, the ternary combination is marked as a ternary combination that violates the pulse wave constraint, and is marked as... Combining them into pulse wave constraints violates vector ; when ≤ If so, then the ternary combination is marked as a regular ternary combination; S3043, Regarding There are [number] probes, and the total number of different ternary combinations is [number]. Extract all ternary combinations that violate the pulse wave constraint; S3044, Violating the pulse wave constraint vector. elements in The normalization process is performed, and the specific algorithm formula is as follows: ； in Indicates the entire set of probes Remove probe The subset obtained later Indicates from the probe To the probe The pulse wave conduction time, the value of which is equal to the probe's... Subtract the probe at the characteristic point of the pulse wave At the characteristic point time, Indicates from the probe To the probe pulse wave conduction time, Indicates from the probe To the probe pulse wave conduction time, This represents the absolute value operation; S3045. Define and determine the baseline level range that violates pulse wave constraints: When the probe of When within the baseline level range, the probe No positional shift occurred; When the probe of When the probe is outside the baseline level range, A positional shift has occurred. S3046, All One probe Arranged by probe number, forming the pulse wave constraint violation vector. .

7. The portable dynamic electrocardiogram and blood pressure intelligent recorder according to claim 6, characterized in that: Each element of the pulse wave constraint violation vector represents the degree of violation of the triangular additivity constraint by the corresponding monitoring probe (30).

8. The portable dynamic electrocardiogram and blood pressure intelligent recorder according to claim 5, characterized in that: The method for obtaining the blood pressure deviation feature vector in S305 includes the following steps: S3051. Based on the linear mapping model in S3031, obtain the result for any two different probes. and Blood pressure estimates and blood pressure sequence ; S3051, Extracting baseline blood pressure values , The total number of valid cardiac cycles within the baseline data collection period; S3052, Based on blood pressure estimates and baseline blood pressure value Calculate offset ; S3053, Based on offset Constructing a blood pressure deviation feature vector will define the probe. In the Blood pressure readings deviate from the target range For all probes The mean deviation of the probe pair is expressed as follows: ； in For the complete set of probes Summation and traversal All probes except ,common item; S3054, All N probes Arranged by serial number, we get the number... Blood pressure deviation from the feature vector in the image .

9. The portable dynamic electrocardiogram and blood pressure intelligent recorder according to claim 1, characterized in that: The method for obtaining the position anomaly score of each monitoring probe in S306 includes the following steps: S3061, Define weighting coefficients These correspond to the relative importance of ECG deviation features, pulse wave constraint violation features, and blood pressure deviation features, respectively. S3062. Calculate the anomaly score of the probe's position in the current image. The specific expression is as follows: ； in The ECG deviation feature vector at the th The first shot One portion, The pulse wave constraint violation vector is represented at the th... The first shot One portion, This indicates that the blood pressure deviation eigenvector is at the th... The first shot One component; S3063, All The scores of each probe are arranged according to its serial number, forming a location anomaly score vector. .

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