Method for monitoring pressure of extracorporeal membrane oxygenation pipeline in real time

Abstract

The invention discloses an extracorporeal membrane oxygenation pipeline pressure real-time monitoring method, and relates to the technical field of extracorporeal membrane oxygenation pipelines, and the method comprises the following steps: extracting steady-state distribution segments with stable pressure and balanced amplitude from a flow direction response distribution cluster under the condition that the pipeline is determined to be externally compressed but not completely closed, and determining the flow direction response distribution cluster; the steady-state distribution segment is subjected to fluctuation consistency turn-back analysis, and the pressure signal abnormal stability phenomenon under the condition that the pipeline is externally pressed but not completely closed is determined; on the basis of determining the abnormal stability phenomenon of the pressure signal, a contrast relation between a structural steady-state block and a flowing vector direction path is established, and whether the pipeline is in a limited operation state or not is judged by comparing vector direction deviation with change characteristics of the steady-state block. According to the invention, the problem that the pipeline is limited and difficult to identify under the illusion that the pressure is stable is solved, and accurate monitoring and dynamic regulation and control of the operation state of the extracorporeal membrane oxygenation pipeline are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of extracorporeal membrane oxygenation pipeline, and particularly relates to a real-time monitoring method for extracorporeal membrane oxygenation pipeline pressure. BACKGROUND

[0002] Real-time monitoring of extracorporeal membrane oxygenation (ECMO) pipeline pressure refers to, during operation of an extracorporeal membrane oxygenation system, continuously collecting pressure data in the process of blood flow through pressure sensors arranged at key positions of an oxygenation pipeline (such as an arterial return pipe, a venous drainage pipe, before and after a pump, etc.), and transmitting the pressure values to a monitoring system in real time through a data acquisition module to realize dynamic sensing, abnormal early warning and safety guarantee of changes in ECMO loop pressure. At present, common real-time monitoring technologies for ECMO pressure mainly rely on integrated pressure sensors (such as MEMS, capacitive or piezoresistive) installed at pipeline connection parts, analog voltage or digital signals are obtained through special data acquisition cards or embedded systems, and then input to a central processing unit after filtering, amplification and signal conditioning, and then the pressure data are subjected to curve fitting, threshold judgment and trend analysis through built-in algorithms to realize early identification of dangerous states such as high pressure, low pressure, obstruction and blood leakage. In addition, modern systems usually include a wireless communication module for uploading data to a hospital information system or a mobile terminal for remote monitoring by doctors, and are equipped with a graphical user interface (GUI) for local real-time display of pressure curves, alarm logs and historical data analysis. The whole system usually covers six links of "sensor arrangement - signal acquisition - data processing - alarm output - remote transmission - user interaction", realizing a closed-loop monitoring system from data sensing to intelligent decision-making.

[0003] The prior art has the following disadvantages: During real-time monitoring of extracorporeal membrane oxygenation pipeline pressure, when equipment is moved in the ward, the patient's body position is adjusted or medical personnel temporarily place instruments, the venous drainage section of the extracorporeal membrane oxygenation pipeline may be unintentionally compressed by external objects. Such compression does not completely block the blood flow, but limits the cross section of the pipeline, causing the local blood flow rate to decrease and form a mild turbulent flow. Due to the decrease in fluid kinetic energy, the measured pressure signal is stable on the surface and in the normal range, thus forming a "pressure abnormal stability illusion". The existing real-time monitoring technology for extracorporeal membrane oxygenation pipeline pressure cannot judge whether the pipeline is in a limited operation state according to the abnormal stability of the pressure signal when the pipeline is compressed by external objects but not completely closed, because the technology defaults that pressure stability represents a smooth loop and only relies on the trend of pressure value changes for abnormal identification, without establishing an identification mechanism for the "numerical stability but fluid abnormality" state. This problem causes the system to be unable to effectively detect the drainage limitation caused by external compression, and medical personnel are difficult to discover potential risks in time, thus possibly causing continuous slowing of local blood flow, microembolus formation and decrease in membrane oxygenation efficiency, and finally causing pipeline obstruction or system failure.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure, specifically comprising the following steps: S1. Collect continuous pressure data at multiple pressure contact points along the venous drainage path of the extracorporeal membrane oxygenation (ECMO) tubing, construct a flow direction response distribution cluster arranged in time sequence, and determine whether the tubing is under external pressure but not completely closed based on the response amplitude shift trend between each contact point in the flow direction response distribution cluster. S2. When it is determined that the pipeline is under external pressure but not completely closed, extract a steady-state distribution segment with stable pressure and balanced amplitude from the flow response distribution cluster, and determine the abnormally stable pressure signal phenomenon when the pipeline is under external pressure but not completely closed by performing fluctuation consistency back-return analysis on the steady-state distribution segment. S3. Based on the determination of the abnormal stability of the pressure signal, establish the comparison relationship between the structural steady-state block and the flow vector path. By comparing the vector deviation and the change characteristics of the steady-state block, determine whether the pipeline is in a restricted operating state. S4. Based on the judgment that the pipeline is in a restricted operating state, the pressure energy offset value and fluid stress transmission trajectory within the structural steady-state block are integrated to construct a pipeline operation trend assessment structure to present dynamic response change characteristics. S5. Assess structural changes based on pathway operation trends, adjust the drainage direction of the blood drainage inlet, apply flow disturbance, and dynamically regulate the operation status of the extracorporeal membrane oxygenation (ECMO) pipeline based on disturbance feedback changes.

[0007] Preferably, S1 is as follows: Multiple pressure contact points are set up along the venous drainage path of the extracorporeal membrane oxygenation (ECMO) tubing. Pressure data is continuously collected at each pressure contact point within a uniform time interval. The collected pressure data is arranged in chronological order to form a continuous pressure data set containing time labels and spatial coordinates. Based on a continuous pressure dataset, the pressure data of each pressure contact point are arranged and combined in chronological order to construct a flow response distribution cluster with chronological order as the main axis and the spatial location of the pressure contact point as the auxiliary axis. This cluster is used to represent the response relationship between different pressure contact points within the venous drainage path. The pressure response amplitude of adjacent pressure contact points in the flow response distribution cluster is calculated by difference in continuous time segments to extract the amplitude offset curve between adjacent contact points. On the amplitude offset curve, an interval in which the amplitude continuously decreases and does not show a symmetrical rebound is detected, and the offset direction and duration of the interval are calculated. When the offset direction is always along the blood flow direction and the duration exceeds the stable duration of the adjacent cycle, it is determined that the pipeline is under external pressure but not completely closed.

[0008] Preferably, S2 specifically includes the following steps: S201. When it is determined that the pipeline is under external pressure but not completely closed, the pressure response sequence of each pressure contact point in the continuous time interval is extracted based on the flow response distribution cluster. The continuous segments that simultaneously meet the requirements of the response value change range being less than the preset amplitude offset threshold and the waveform fluctuation being less than the mean square error limit are defined as steady-state distribution segments with stable pressure and balanced amplitude. S202. Copy the response data of each pressure contact point in the steady-state distribution segment with stable pressure and uniform amplitude in reverse order of time to generate a backtracking sequence, and calculate the point-to-point amplitude difference with the original sequence. Calculate the variance of the difference within the continuous time window and construct a fluctuation consistency backtracking analysis diagram. S203. Based on the variation characteristics of the difference variance distribution in the fluctuation consistency return analysis diagram, identify segments in which the difference variance remains within the preset deviation range and there is no periodic reversal within the continuous time interval. Determine that the pressure signal is in an abnormally stable state and identify the abnormally stable pressure signal phenomenon when the pipeline is externally compressed but not completely closed.

[0009] Preferably, S203 is as follows: The difference variance sequence in the fluctuation consistency return analysis graph is discretized and segmented according to time order. The difference variance value in each segment is compared with the preset deviation threshold point by point to select the stable interval in which all difference variances in continuous time segments are within the preset deviation range. Within the stable interval, the direction of change of the variance of the difference between adjacent time segments is calculated. The direction determination algorithm is used to detect whether there is a periodic reversal phenomenon of the variance of the difference. When the direction of change of all consecutive segments is consistent and there is no alternation of direction, the stable interval is defined as the non-periodic reversal interval. Within the non-periodic reversal interval, the temporal distribution of the difference variance is continuously verified. When the duration of the non-periodic reversal interval exceeds the average stable duration of the adjacent normal cycle, the non-periodic reversal interval is determined to be an abnormally stable pressure signal. Based on this determination result, the abnormally stable pressure signal phenomenon under external pressure but not complete closure of the pipeline is identified.

[0010] Preferably, S3 specifically includes the following steps: S301. Based on the determination of the abnormal stability of the pressure signal, extract the pressure response data within the time interval corresponding to the abnormal stability of the pressure signal, construct a pressure response map according to the spatial arrangement of the pressure contact points, and extract equal amplitude response regions in segments with the stability interval as the boundary. Based on the consistency of the response, aggregate the equal amplitude response regions into structural steady-state blocks. S302. Based on the temporal and spatial locations of the structural steady-state blocks, establish a reference axis for comparison, fit the response extension direction of each pressure contact point in a continuous time interval, construct a flow vector path that reflects the actual blood flow trend, and cross-compare the flow vector path with the structural steady-state blocks in both time and space dimensions. S303. Compare the degree of overlap between the structural steady-state block and the flow vector path under the same response axis. When the vector deviation is detected in the flow vector path as continuously deviating from the main axis direction of the structural steady-state block, and the deviation trend does not show directional correction, it is determined that the pipeline is in a restricted operating state, and the deviation direction and degree are used as the judgment output.

[0011] Preferably, S303 is as follows: Based on the comparison between the structural steady-state block and the flow vector path, the vector coordinate values ​​at each time point under the same response axis are extracted, the deviation angle between the flow vector path and the principal axis direction of the structural steady-state block is calculated, and a vector deviation curve with time as the sequence is formed to represent the trend of deviation over time. The deviation angle changes in the continuous time interval of the vector deviation curve are statistically analyzed. When the deviation angle increases continuously in the same direction and does not decrease in the opposite direction in adjacent sampling periods, the time interval is marked as a continuous deviation interval, and the deviation growth rate is extracted as the vector offset trend parameter. Within the continuous deviation range, when the directional offset trend parameter remains in an increasing state and there is no directional repair characteristic, the pressure signal corresponding to the continuous deviation range is determined to be that the pipeline is in a restricted operating state, and the combined value of the offset direction and offset degree is output as a quantitative judgment result to characterize the intensity of restricted operation.

[0012] Preferably, S4 is as follows: Based on the judgment that the pipeline is in a restricted operating state, the pressure response data of each pressure contact point in the structural steady-state block is extracted in the continuous time interval, the pressure energy offset value of each pressure contact point relative to the center of the steady-state block is calculated, and the pressure energy offset value is time series normalized to form the pressure energy offset distribution trajectory. Based on the pressure energy offset distribution trajectory, the pressure energy gradient change rate between adjacent pressure contact points is calculated within the continuous response time window. Combined with the temporal distribution of the flow vector path, a fluid stress transmission trajectory reflecting the force direction of blood flow is generated, and the correlation path structure between pressure energy gradient and stress direction is established. The pressure energy offset value and the fluid stress transmission trajectory are jointly fitted in both time and space to generate a dynamic response matrix that includes the pressure energy vector, stress extension direction and rate of change. This dynamic response matrix is ​​then used to construct a pipeline operation trend assessment structure to present the response change trend of the current pipeline operation status.

[0013] Preferably, S5 is as follows: Based on the trend of pathway operation, structural changes are assessed. Within the continuous response time interval, the rate of change of pressure energy vector and the rate of change of stress extension direction are extracted to construct a response deviation model that reflects the trend of flow path offset. Based on the information of offset direction and offset amplitude in the response deviation model, offset control parameters for adjusting the drainage direction of blood drainage inlet are generated. The drainage direction of the blood drainage inlet is adjusted based on the offset control parameters. The flow direction disturbance is applied within a preset time period by changing the drainage direction. During the disturbance, continuous pressure response data of multiple pressure contact points in the extracorporeal membrane oxygenation (ECMO) tubing are collected to form a pressure feedback sequence before and after the disturbance, and a flow direction disturbance feedback change structure is constructed. Based on the feedback change structure of flow direction disturbance, the response change trend of pressure energy offset value and stress transmission trajectory before and after disturbance is analyzed. When the pressure energy distribution in the feedback change structure gradually returns to equilibrium and the stress transmission tends to a stable direction, the pathway operation trend evaluation structure is updated, and the operation status of the extracorporeal membrane oxygenation pipeline is continuously and dynamically adjusted accordingly.

[0014] The technical effects and advantages provided by the present invention in the above technical solution are as follows: 1. This invention overcomes the limitations of traditional methods that rely solely on pressure value changes for anomaly identification by introducing multi-dimensional quantitative models, including flow response distribution clusters, structural steady-state blocks, fluctuation consistency return analysis diagrams, directional deviation curves, and pathway operation trend assessment structures. Even when pipelines are externally compressed but not completely closed, this method can identify hidden anomalies in the pressure signal under surface stability. In particular, through refined analysis of the difference variance distribution and directional changes, it accurately determines the formation mechanism of pressure anomaly stability phenomena. Simultaneously, by modeling the correlation between the flow directional path and structural steady-state blocks, it enables the determination of whether the pipeline is in a restricted operating state, making anomaly identification more timely and spatially resolvable, significantly improving the accuracy and responsiveness of the extracorporeal circulation system's operating status assessment.

[0015] 2. This invention also constructs a pathway operation trend assessment structure based on pressure energy offset values ​​and fluid stress transmission trajectories, and implements a closed-loop perturbation control mechanism based on this structure, enabling the system to possess dynamic intervention and self-optimization capabilities. By applying flow direction perturbations and combining them with perturbation feedback changes for trend updates, this method can achieve real-time dynamic control of the pipeline operation status, ensuring the continuous and smooth operation of the drainage pathway in complex clinical environments. Compared with existing solutions, this invention not only solves the identification blind spot of "numerical stability but fluid abnormality," but also establishes a quantitative linkage mechanism between abnormal signal identification and control regulation. It has significant technical advantages such as high identification accuracy, fast control response, and adaptability to complex scenarios, and can effectively reduce the clinical risks caused by pipeline restrictions during extracorporeal membrane oxygenation (ECMO). Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0017] Figure 1 This is a schematic flowchart of the method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure according to the present invention. Detailed Implementation

[0018] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0019] This invention provides, for example Figure 1 The method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure, as shown, specifically includes the following steps: S1. Collect continuous pressure data at multiple pressure contact points along the venous drainage path of the extracorporeal membrane oxygenation (ECMO) tubing, construct a flow direction response distribution cluster arranged in time sequence, and determine whether the tubing is under external pressure but not completely closed based on the response amplitude shift trend between each contact point in the flow direction response distribution cluster. In this embodiment, S1 specifically refers to: Multiple pressure contact points are set up along the venous drainage path of the extracorporeal membrane oxygenation (ECMO) tubing. Pressure data is continuously collected at each pressure contact point within a uniform time interval. The collected pressure data is arranged in chronological order to form a continuous pressure data set containing time labels and spatial coordinates. Multiple pressure contact points are set along the venous drainage path of the extracorporeal membrane oxygenation (ECMO) tubing to obtain real-time pressure distribution information of blood at different locations. These pressure contact points can be arranged by embedding miniature pressure sensors at predetermined positions along the drainage path. Sensor types can be resistive, piezoelectric, or MEMS miniature pressure sensors, requiring high sensitivity and rapid response capabilities. Each pressure sensor reflects the pressure value at that location by acquiring an electrical signal, which is uniformly collected by a multi-channel data acquisition device. A uniform time interval, such as once per second or higher, must be set during data acquisition to ensure synchronization of data between pressure contact points. Arranging continuous data from multiple pressure contact points according to acquisition time reflects the dynamic pressure change process on a time axis. Simultaneously, by assigning spatial coordinate labels to each contact point, a pressure data set with a joint time and location index is constructed. This method can accurately describe pressure changes in blood at different spatial locations, helping to further identify abnormal patterns or trend deviations.

[0020] Pressure contact points refer to pressure signal acquisition units deployed at equidistant or key locations along the venous drainage path, with each contact point independently acquiring local pressure data. A uniform time interval means all contact points are sampled at the same time point to ensure time synchronization between data points, thereby enabling horizontal comparability of pressure data from different locations. Continuous acquisition means uninterrupted recording of pressure changes to capture potential abnormal signal fluctuations. Pressure data is arranged chronologically to construct dynamic change curves, providing a foundation for subsequent trend analysis. Time stamps are used to identify the time each data point was generated, ensuring accurate time anchors when processing time-series information. Spatial coordinates are used to mark the specific physical location of pressure contact points in the drainage path, facilitating the mapping of pressure data back to the actual pipeline structure. The resulting continuous pressure data set is essentially a time-space dual-dimensional data structure, supporting further trend deviation identification and stability analysis, providing a data foundation for identifying abnormal situations where the pipeline is externally compressed but not completely closed.

[0021] Based on a continuous pressure dataset, the pressure data of each pressure contact point are arranged and combined in chronological order to construct a flow response distribution cluster with chronological order as the main axis and the spatial location of the pressure contact point as the auxiliary axis. This cluster is used to represent the response relationship between different pressure contact points within the venous drainage path. Arranging and combining pressure data from various pressure contact points in a continuous pressure dataset according to time sequence aims to construct a multidimensional structure reflecting pressure changes along the venous drainage path. This can be achieved by establishing a two-dimensional data framework, with time sequence as the main axis, horizontally expanded, and the pressure values ​​of each contact point at each moment arranged vertically, forming a data grid that synchronously corresponds in time and space. In this process, each column represents a snapshot of the pressure at all contact points within a given time node, and each row represents the pressure trajectory of a specific contact point over time. The flow response distribution cluster constructed in this way can reflect the pressure transmission relationship of blood from distal to proximal along the venous drainage path. The purpose of constructing this structure is to integrate the spatial extension characteristics of local pressure and the global temporal evolution characteristics into a unified observation system, enabling not only the observation of abnormal trends but also their qualitative and localization. This structure is crucial for determining whether there is a persistent pressure shift or abnormal stability at a specific location.

[0022] A continuous pressure dataset refers to the total collection of raw data acquired from all pressure contact points at uniform time intervals throughout the entire monitoring period. Arranging the pressure data from each contact point in chronological order involves filling the pressure value of each contact point at each time point into a two-dimensional structure with time as the horizontal axis and the spatial location of the contact point as the vertical axis. The chronological order is the primary axis, representing the dominant dimension of data organization, used to capture the dynamic process of pressure changes. The spatial location of the pressure contact points is the secondary axis, ensuring that the relative order between different locations remains unchanged, facilitating the identification of local flow anomalies or lag phenomena. The flow response distribution cluster is a data array structure that can display the pressure response characteristics of different contact points at different times through a joint spatial-temporal mapping. This structure allows for the precise location of areas with abnormal local pressure responses within a specific time period through their shape changes, thus providing a data foundation and analytical support for subsequent trend analysis and determining whether the pipeline is under external pressure but not completely closed.

[0023] The pressure response amplitude of adjacent pressure contact points in the flow response distribution cluster is calculated by difference in continuous time segments to extract the amplitude offset curve between adjacent contact points. On the amplitude offset curve, an interval in which the amplitude continuously decreases and does not show a symmetrical rebound is detected, and the offset direction and duration of the interval are calculated. When the offset direction is always along the blood flow direction and the duration exceeds the stable duration of the adjacent cycle, it is determined that the pipeline is under external pressure but not completely closed.

[0024] The purpose of differential calculation of the pressure response amplitudes of adjacent pressure contact points within a continuous time segment in a flow response distribution cluster is to reveal the trend of pressure gradient changes at various locations along the venous drainage path. This is achieved by extracting the pressure values ​​of adjacent contact points at the same time node, calculating the amplitude difference between them, and forming a continuous difference sequence. Furthermore, the trend of pressure difference changes in this sequence is analyzed at multiple consecutive time points. If the difference continues to widen, it indicates that the pressure at the previous contact point is decreasing while the pressure at the subsequent contact point remains unchanged or increases, constituting a phenomenon of continuous amplitude decline. If this phenomenon does not show a pressure recovery in the opposite direction (i.e., a symmetrical rebound) at subsequent time points, it can be considered that a stable offset interval exists. The direction of the offset can be determined by the sign of the difference, and the duration is determined by statistically analyzing the length of the time window in which the phenomenon continues. For example, in a continuously changing segment, if the pressure gradually decreases from the distal contact point to the proximal contact point and does not rebound for ten seconds, this indicates a continuous amplitude decline without rebound. If this trend is consistent with the direction of blood flow and lasts for longer than the average pressure plateau in the adjacent normal cycle, it can be inferred that the path area is under external pressure but not completely closed.

[0025] The amplitude offset curve is a time series composed of the differences between adjacent pressure contact points at each time node, reflecting the pressure change trend of spatially adjacent points in the time dimension. A continuous decrease in amplitude means that the values ​​at multiple consecutive points on the curve show a unidirectional decrease, indicating a continuously intensifying pressure gradient. The absence of a symmetrical rebound means that no process of pressure difference compensation in the opposite direction has been observed, thus ruling out short-term fluctuations or physiological disturbances. The offset direction refers to the overall trend direction of the pressure difference change over time. If this direction is consistent with the actual blood flow direction, it indicates that the pressure reduction occurs during downstream flow and is clinically relevant. The duration is calculated by the duration of continuous offset segments and needs to be compared with the stable duration of adjacent cycles. The stable duration of adjacent cycles refers to the average duration of continuous time segments without significant pressure offset within the monitoring period, which can be used as a reference baseline for abnormal state judgment. Only when the duration of abnormal offset exceeds this baseline can natural fluctuations be ruled out and an abnormal state be confirmed. This judgment mechanism can effectively identify local blood flow restriction problems masked by stable surface pressure signals.

[0026] S2. When it is determined that the pipeline is under external pressure but not completely closed, extract a steady-state distribution segment with stable pressure and balanced amplitude from the flow response distribution cluster, and determine the abnormally stable pressure signal phenomenon when the pipeline is under external pressure but not completely closed by performing fluctuation consistency back-return analysis on the steady-state distribution segment. In this embodiment, S2 specifically includes the following steps: S201. When it is determined that the pipeline is under external pressure but not completely closed, the pressure response sequence of each pressure contact point in the continuous time interval is extracted based on the flow response distribution cluster. The continuous segments that simultaneously meet the requirements of the response value change range being less than the preset amplitude offset threshold and the waveform fluctuation being less than the mean square error limit are defined as steady-state distribution segments with stable pressure and balanced amplitude. After confirming the possibility that the venous drainage path of the extracorporeal membrane oxygenation (ECMO) tubing may be compressed externally but not completely closed, a representative continuous time interval needs to be extracted from the flow response distribution cluster. Within this time interval, pressure response sequences are extracted for multiple pressure contact points. To ensure that the extracted segments possess abnormal stability characteristics, two quantitative criteria are used for screening: first, calculating the difference between the maximum and minimum values ​​of each pressure response sequence within the time interval, i.e., the range of response value variation; second, statistically analyzing the standard deviation of pressure values ​​within the sequence to measure the degree of waveform fluctuation. When the range of response value variation at multiple pressure contact points is less than the set amplitude offset threshold within a certain time period, and the waveform fluctuation is within a defined root mean square deviation range, this time window is determined to be a steady-state distribution segment. For example, if the pressure values ​​at all five pressure contact points remain within a very small fluctuation range within a five-second continuous sampling time period, and the standard deviation does not exceed the system's set stability upper limit, then this time period can be identified as a candidate steady-state distribution segment.

[0027] A preset amplitude offset threshold is a limiting indicator used to determine whether the pressure response deviates from the normal fluctuation range. It is typically set statistically based on a large amount of historical stable operating data, with the aim of filtering out non-steady-state data caused by drastic changes or external disturbances. This threshold can be dynamically configured according to clinical application scenarios, such as loop flow type, pump speed level, or patient blood flow characteristics. A continuous segment with waveform fluctuations less than the mean square deviation limit refers to a stable state where all data points in the pressure response sequence fluctuate minimally around the mean within the target time window, lacking abrupt changes. Visually, this continuous segment resembles a nearly straight curve segment, lacking the periodic fluctuations common in normal physiological activities. Through this dual limitation, the influence of random errors and short-term interference can be accurately eliminated, retaining only the "pseudo-stationary" state generated under external pressure, providing accurate original samples for subsequent re-entry analysis and anomaly identification.

[0028] S202. Copy the response data of each pressure contact point in the steady-state distribution segment with stable pressure and uniform amplitude in reverse order of time to generate a backtracking sequence, and calculate the point-to-point amplitude difference with the original sequence. Calculate the variance of the difference within the continuous time window and construct a fluctuation consistency backtracking analysis diagram. After obtaining a steady-state distribution segment with stable pressure and balanced amplitude, a time-axis reversal operation needs to be performed on the response data of each pressure contact point. Specifically, the original pressure sequence within the continuous time window is arranged from the end to the beginning, generating a new sequence with the opposite time direction and completely corresponding points, called the foldback sequence. The amplitude difference between this foldback sequence and the original sequence is calculated one-to-one, that is, the difference between the original pressure value at each time point and the pressure value at its foldback position, forming a set of differences reflecting symmetrical fluctuation differences. Subsequently, a sliding time window is used to calculate the variance of continuous segments within the difference set, thereby assessing the concentration of fluctuation differences within that time period. These difference variance results are mapped onto a two-dimensional graph, with the horizontal axis representing the time segment number and the vertical axis representing the difference variance value, forming a complete fluctuation consistency foldback analysis diagram, used for further analysis of the fluctuation symmetry and stability characteristics of the pressure response. For example, in a pressure sequence containing fifty time points, the generated retracement sequence also contains fifty points. After calculating the difference point by point, fifty difference values ​​are obtained. Then, the variance is calculated within a sliding window consisting of ten points, and the continuous change curve of the difference variance is plotted in sequence.

[0029] The reverse replication of time to generate a foldback sequence introduces temporal mirroring logic, giving the pressure sequence a comparable axis of symmetry. This approach reveals the inconsistencies in fluctuations hidden behind numerical stability, overcoming the limitation of traditional sequence analysis which can only perform unidirectional analysis. Point-to-point amplitude difference calculation directly compares the amplitudes of the original and foldback sequences at perfectly matched points, constructing a difference array that reflects whether the original fluctuations are consistent in temporal structure. This method can amplify some minute shifts that are difficult to detect in conventional trend analysis, and is particularly suitable for identifying abnormally stable but irregularly reversing pressure response states. The variance of the difference, as a core parameter of fluctuation consistency, reflects the degree of aggregation of fluctuation differences within a specific window; the smaller the value, the stronger the symmetry, and vice versa, indicating structural asymmetry in the fluctuations. Therefore, by constructing this analysis chart, not only can potential abnormally stable states be accurately located, but it can also provide quantitative evidence for subsequent judgments on whether pressure signals possess pathological characteristics.

[0030] S203. Based on the variation characteristics of the difference variance distribution in the fluctuation consistency return analysis diagram, identify segments in which the difference variance remains within the preset deviation range and there is no periodic reversal within the continuous time interval. Determine that the pressure signal is in an abnormally stable state and identify the abnormally stable pressure signal phenomenon when the pipeline is externally compressed but not completely closed.

[0031] The fundamental purpose of this approach is to accurately identify abnormal operating states of the tubing caused by external pressure that is not fully closed. These states are easily misjudged as normal using existing real-time pressure monitoring technologies for extracorporeal membrane oxygenation (ECMO) tubing. Traditional monitoring methods rely primarily on drastic fluctuations or abrupt changes in pressure values ​​to assess risk. However, when the tubing is subjected to mild pressure, local blood flow velocity decreases, and fluid kinetic energy weakens, causing the pressure data to appear stable and normal on the surface, creating a "false good" state. By introducing a fluctuation consistency return analysis plot and further analyzing the variation characteristics of the difference variance, signals in non-physiological stable states can be identified from the perspective of pressure signal fluctuation rather than solely from numerical values. Especially when identifying segments where the difference variance remains within a preset deviation range and without periodic reversals over a continuous time interval, short-term stability errors caused by normal blood flow fluctuations can be eliminated, accurately pinpointing the stability of abnormal signals caused by human interference. This allows for the identification of abnormal stable states and further determination of whether the tubing is operating under restricted conditions. This identification logic enhances the monitoring system's sensitivity to "seemingly normal" states within an abnormality, and is key to overcoming the blind spots of misjudgment in existing technologies.

[0032] In this embodiment, S203 specifically refers to: The difference variance sequence in the fluctuation consistency return analysis graph is discretized and segmented according to time order. The difference variance value in each segment is compared with the preset deviation threshold point by point to select the stable interval in which all difference variances in continuous time segments are within the preset deviation range. After constructing the fluctuation consistency return analysis chart, the resulting difference variance sequence needs to be segmented according to the time axis to refine the identification of variance change patterns within each time period. Specifically, the entire difference variance sequence is divided into equal-length time segments, each containing difference variance values ​​corresponding to several consecutive time points. For each time segment, the difference variance corresponding to each time point within it is extracted point by point, and these values ​​are then compared one by one with a preset deviation threshold. The preset deviation threshold is a constant set during system calibration based on the statistical standard deviation of pressure fluctuation differences under normal operating conditions. Its definition is used to distinguish the boundary between normal fluctuation ranges and potential abnormal fluctuations. When all difference variances within a certain time segment fall within the preset deviation range defined by the deviation threshold, it indicates that the fluctuation changes within that segment are highly concentrated and no significant fluctuation expansion has occurred, thus being determined as a stable interval. For example, if each time segment contains ten data points, and the variance of each data point is below the set deviation threshold, it indicates that the fluctuation distribution is stable during that period, without periodic disturbances or trend reversals. Therefore, it is selected as a candidate region for pressure anomaly stability analysis. This operation can effectively eliminate the misleading influence of occasional interference signals on the overall judgment, and at the same time, the identification of stability in continuous intervals enhances the accuracy and reliability of subsequent judgments.

[0033] Within the stable interval, the direction of change of the variance of the difference between adjacent time segments is calculated. The direction determination algorithm is used to detect whether there is a periodic reversal phenomenon of the variance of the difference. When the direction of change of all consecutive segments is consistent and there is no alternation of direction, the stable interval is defined as the non-periodic reversal interval. When determining the trend characteristics of the difference variance sequence, it is necessary to analyze the direction of change of the difference variance between adjacent time segments one by one within the stable interval. This involves determining whether the mean of the difference variance between two adjacent time segments is increasing, decreasing, or remaining constant, thereby extracting the trend sequence within the entire stable interval. The identification of the direction of change can be achieved through a direction determination algorithm. This algorithm sets the determination logic based on the difference in the mean variance of adjacent time segments: if the mean variance of the later time segment is greater than that of the previous segment, it is defined as increasing; if it is less, it is defined as decreasing; and if they are equal, it is defined as stable. This algorithm marks the direction of change of all consecutive time segments as a single direction sequence, and then analyzes and determines whether there is an alternating pattern of "increasing-decreasing" or "decreasing-increasing" in this sequence. If the direction of change of all segments within the entire stable interval remains consistent or is in a stable state, and no arbitrary alternation of directions occurs, it is determined to be a non-periodic reversal interval. This is done because periodic reversals in fluid dynamics typically represent stress feedback regulation of restricted blood flow caused by local turbulence or structural elastic deformation. The absence of such regulation may indicate that the pressure restriction within the tubing has become non-dynamically regulated, meaning the pressure state has been statically locked. For example, if the variance of the pressure signal difference continues to decrease slightly over a certain period without recovering, it indicates that the abnormal pressure stability phenomenon is persistent and structural, no longer a result of physiological fluctuations. Therefore, this interval is identified as the non-periodic reversal interval and proceeds to the subsequent abnormal stability assessment process.

[0034] Within the non-periodic reversal interval, the temporal distribution of the difference variance is continuously verified. When the duration of the non-periodic reversal interval exceeds the average stable duration of the adjacent normal cycle, the non-periodic reversal interval is determined to be an abnormally stable pressure signal. Based on this determination result, the abnormally stable pressure signal phenomenon under external pressure but not complete closure of the pipeline is identified.

[0035] After identifying the non-periodic reversal interval, further continuity verification is needed to confirm whether the interval exhibits abnormally stable temporal characteristics. Specifically, this is done by statistically analyzing the continuous-time distribution of the variance of the difference within the non-periodic reversal interval, calculating the duration of the interval, and comparing this duration with the average stable duration of stable segments within multiple adjacent normal cycles. The stable duration of a normal cycle can be obtained by extracting multiple short-term stable segments during operation phases where no pressure interference is detected and averaging them, serving as a reference. If the duration of the current non-periodic reversal interval significantly exceeds this average stable duration, it indicates that the stability of the current pressure signal has exceeded the normal physiological range and possesses abnormally persistent characteristics. This judgment is made because the stable state of the pressure signal during normal operation is usually maintained for a short time, subsequently fluctuating due to heartbeats, changes in body position, or circuit regulation. Once a sustained stable state far exceeding the average stable duration appears, without periodic reversal characteristics, it is highly suspected to be a signal artifact caused by non-physiological factors such as external pressure. For example, when a venous drainage line is slightly compressed, although the reduced blood flow velocity keeps the pressure within the normal range, the pressure fluctuations are artificially suppressed, creating a prolonged stable signal. This should be identified as an abnormally stable pressure signal, further determined to be an abnormally stable pressure phenomenon caused by external compression of the line without complete closure. This method effectively avoids misjudgments based on absolute numerical values ​​and improves the accuracy of identifying non-dynamic anomalies.

[0036] S3. Based on the determination of the abnormal stability of the pressure signal, establish the comparison relationship between the structural steady-state block and the flow vector path. By comparing the vector deviation and the change characteristics of the steady-state block, determine whether the pipeline is in a restricted operating state. In this embodiment, S3 specifically includes the following steps: S301. Based on the determination of the abnormal stability of the pressure signal, extract the pressure response data within the time interval corresponding to the abnormal stability of the pressure signal, construct a pressure response map according to the spatial arrangement of the pressure contact points, and extract equal amplitude response regions in segments with the stability interval as the boundary. Based on the consistency of the response, aggregate the equal amplitude response regions into structural steady-state blocks. After confirming the abnormal stability of the pressure signal, the corresponding time interval can be selected as the data extraction window to obtain the response data sequence of all pressure contact points within that interval. These response data are then used to construct a two-dimensional pressure response map according to the actual spatial arrangement of the pressure contact points along the venous drainage path, creating a visual mapping between the time and spatial dimensions. Within this pressure response map, continuous time periods with small signal fluctuations are extracted as boundaries of the stability interval, based on signal continuity and numerical stability. Within these boundaries, a group of response regions with similar numerical amplitudes is extracted based on the clustering characteristics of the pressure value amplitudes at each contact point, defined as equal-amplitude response regions. Subsequently, based on the spatial proximity and response value consistency of these regions, multiple equal-amplitude response regions are merged to generate a structurally stable block with strong continuity and orderly distribution, used for subsequent comparative analysis of the flow vector path. This processing method can eliminate the local fluctuations caused by occasional disturbances in the abnormal state, highlighting the stable and slowly changing fluid dynamic structural characteristics, providing a clearer analytical benchmark for identifying whether the system is in a restricted operating state.

[0037] The "stability interval" refers to a continuous period in a time series where the fluctuation range of pressure response values ​​remains within a small range. Its determination criteria typically include the difference between consecutive response values ​​being less than the average offset threshold and the fluctuation frequency not exceeding the periodic stability standard. This interval serves to limit the data window for structural analysis and eliminate interference factors introduced by high-fluctuation segments. The "equal amplitude response region" is a spatial region within the stability interval obtained by horizontally clustering the response values ​​of multiple pressure contact points, where the pressure response amplitudes of each contact point within the region are at similar levels. The existence of this region reflects the relative homogeneity of blood flow status within that time and spatial range. Aggregating it into structural steady-state blocks can accurately capture the basic morphology of blood flow under constrained conditions in spatial structure, thus providing a stable geometric reference for subsequent directional offset judgment.

[0038] S302. Based on the temporal and spatial locations of the structural steady-state blocks, establish a reference axis for comparison, fit the response extension direction of each pressure contact point in a continuous time interval, construct a flow vector path that reflects the actual blood flow trend, and cross-compare the flow vector path with the structural steady-state blocks in both time and space dimensions. To assess whether there is a restricted operation in the extracorporeal membrane oxygenation (ECMO) tubing caused by external pressure, a reference axis is first constructed, using the temporal and spatial locations of the structural steady-state block as a reference. This axis reflects the ideal blood flow direction when the pressure signal is stable. Based on this, the response position change trajectory of each pressure contact point within a continuous time interval is selected. Mathematical fitting is then performed on the spatial displacement trends of these trajectory points to generate a flow vector path reflecting the actual blood flow trend. The fitting process can employ methods such as polynomial regression or Bézier curve interpolation to fully capture minute changes in flow direction. Subsequently, the fitted flow vector path is cross-referenced with the reference axis along both the time and spatial axes to identify whether the actual flow direction matches the ideal state. This cross-comparison not only determines whether blood flow has deviated but also locates the starting point and duration of the deviation, facilitating precise analysis of abnormal blood flow states.

[0039] "The temporal and spatial locations of the structural steady-state block" refer to the positioning information of each contact point in the time series and spatial arrangement under abnormal steady-state conditions, respectively. These together determine the geometric range and duration of the block. The "reference axis" is an ideal flow direction reference line constructed on the central region of the steady-state block based on the average pressure signal fluctuation and the spatial sequence of contact points. The "response extension direction" reflects the propagation trend of the pressure signal over time in space and is the core basis for constructing the flow vector path. The "flow vector path" is a fitted curve used to depict the spatial movement direction of blood flow during its temporal evolution. "Cross-comparison" refers to comparing key parameters such as the angle difference, positional offset, and overlap length between the flow vector path and the reference axis at the same time point and spatial location, thereby assessing whether the actual blood flow unfolds consistently along the main axis direction of the structural steady-state block. This two-dimensional cross-analysis method can effectively reveal small but continuous flow direction deviations under restricted conditions, providing logical support for the diagnosis of abnormal operating states.

[0040] S303. Compare the degree of overlap between the structural steady-state block and the flow vector path under the same response axis. When the vector deviation is detected in the flow vector path as continuously deviating from the main axis direction of the structural steady-state block, and the deviation trend does not show directional correction, it is determined that the pipeline is in a restricted operating state, and the deviation direction and degree are used as the judgment output.

[0041] The purpose of this approach is to address the problem of hidden flow anomalies caused by external pressure but incomplete closure during extracorporeal membrane oxygenation (ECMO) tubing operation, which cannot be accurately identified by existing pressure monitoring technologies. When the tubing is subjected to mild pressure, although the pressure values ​​appear stable on the surface, the actual blood flow direction may experience a slight and continuous deviation, forming a non-physiological flow path. By comparing and analyzing the structural steady-state blocks with the flow vector path, this seemingly stable but actually deviated from the normal blood flow axis can be identified. Further detection of whether the vector deviation is continuous and lacks directional correction can effectively rule out transient deviations caused by short-term postural changes or local disturbances, ensuring that the judgment results are highly specific and consistent. Finally, using the direction and degree of deviation as outputs, not only can the qualitative identification of restricted operating conditions be achieved, but the severity of flow deviation can also be quantified, providing precise data support for clinical intervention, thereby significantly improving the operational safety and real-time response capability of the ECMO system.

[0042] In this embodiment, S303 specifically refers to: Based on the comparison between the structural steady-state block and the flow vector path, the vector coordinate values ​​at each time point under the same response axis are extracted, the deviation angle between the flow vector path and the principal axis direction of the structural steady-state block is calculated, and a vector deviation curve with time as the sequence is formed to represent the trend of deviation over time. To assess whether blood flow in an extracorporeal membrane oxygenation (ECMO) system is under restricted operation, the coordinate information of the structural steady-state block and the flow vector path under the same response axis can be extracted based on the established structural steady-state block and the flow vector path. Then, the vector deviation between the two at different time points can be calculated. Specifically, at each time point, equally spaced sampling points are first set in the time dimension. The spatial coordinates of the flow vector path and the corresponding coordinates on the principal axis of the structural steady-state block are obtained at each time point. The angle between the line connecting the two points and the principal axis is measured to obtain the deviation angle at that time point. The deviation angles at all time points are arranged sequentially to form a vector deviation curve with time as the sequence. This curve reflects the continuous offset of the flow vector path relative to the structural steady-state block over the entire time interval, especially whether the deviation trend intensifies or eases. Statistical analysis of the deviation curve's changing trend, such as identifying key features like continuously rising segments, inflection points, and plateau segments, can further determine whether the offset is cumulative and whether there are signs of structural imbalance, thus providing a reliable dynamic basis for judging whether the pipeline is under restricted operation. Furthermore, this method can also support spatial positioning of deviations in different areas, thereby helping to accurately identify potential risk points in pipelines. The above calculation process can typically be completed through vector angle measurement, coordinate difference analysis, and time series data fitting, exhibiting good real-time performance and adaptability.

[0043] The deviation angle changes in the continuous time interval of the vector deviation curve are statistically analyzed. When the deviation angle increases continuously in the same direction and does not decrease in the opposite direction in adjacent sampling periods, the time interval is marked as a continuous deviation interval, and the deviation growth rate is extracted as the vector offset trend parameter. To assess whether the blood flow path continuously deviates from the principal axis of the structural steady-state block, trend analysis can be performed on continuous time intervals in the directional deviation curve. Specifically, a time window should first be selected in the directional deviation curve, and the changes in deviation angle at all time points within that window should be statistically analyzed. By calculating the difference in deviation angle between adjacent time points, it can be determined whether the deviation angle continuously increases in a certain direction, i.e., whether the change is consistently positive or negative, and whether there is a sampling period in which the deviation angle decreases throughout the entire time window. If this condition is met, the time interval can be marked as a continuous deviation interval. Subsequently, the first derivative of the deviation angle values ​​within this continuous deviation interval is fitted to obtain the rate of change of the deviation angle per unit time, thereby extracting the deviation growth rate within this interval as a directional offset trend parameter. The larger the deviation growth rate, the more obvious the trend of the flow path deviating from the principal axis, meaning that the asymmetry of the flow state within the pipeline is continuously increasing. This analysis can reveal whether the blood flow direction deviation caused by external pipeline pressure is in a development stage, which is of great significance for identifying early restricted operating states. The above calculations can be achieved by combining sliding window difference statistics, trend direction determination logic, and linear fitting methods. All technical features, such as "deviation angle continuously increases in the same direction", "no reverse decrease occurs", and "deviation growth rate", are used to accurately characterize the asymmetric evolution process of the flow trend.

[0044] Within the continuous deviation range, when the directional offset trend parameter remains in an increasing state and there is no directional repair characteristic, the pressure signal corresponding to the continuous deviation range is determined to be that the pipeline is in a restricted operating state, and the combined value of the offset direction and offset degree is output as a quantitative judgment result to characterize the intensity of restricted operation.

[0045] Within the sustained deviation range, to confirm whether the pipeline is in a restricted operating state, it is necessary to continuously monitor the changes in the directional offset trend parameter and combine this with the presence of directional repair features for judgment. Specifically, the directional offset trend parameter within the sustained deviation range is first dynamically tracked. If this parameter continuously increases positively or worsens negatively throughout the entire time interval, it indicates that the blood flow path is continuously moving away from the main axis direction of the structural steady-state block. At this point, it is necessary to detect whether there are directional repair features, i.e., whether there is a trend of the offset angle returning to the original main axis direction at any given time point. If no signs of a decrease in offset angle, trend reversal, or oscillation recovery are detected throughout the entire range, it can be determined that there are no directional repair features in this range. In this case, the pressure signal within the sustained deviation range can be considered as the pipeline entering a restricted operating state, and two key quantities are used as quantitative judgment criteria: the offset direction, which characterizes the systematic transfer direction of blood flow, and the offset degree, which assesses the spatial magnitude of the flow deviation. The combination of these two quantities forms a quantitative output value that reflects the intensity level of restricted operation, thus providing an accurate judgment basis for subsequent intervention. The core of non-directional repair features lies in excluding reversible fluctuations caused by physiological disturbances or short-term oscillations, triggering judgment only in cases of long-term, unidirectional, and irreversible offsets, ensuring that the identified restricted state is persistent and pathological. This analysis process can be jointly implemented through an offset trend continuous judgment algorithm, direction reversal monitoring logic, and amplitude threshold matching mechanism.

[0046] S4. Based on the judgment that the pipeline is in a restricted operating state, the pressure energy offset value and fluid stress transmission trajectory within the structural steady-state block are integrated to construct a pipeline operation trend assessment structure to present dynamic response change characteristics. In this embodiment, S4 specifically refers to: Based on the judgment that the pipeline is in a restricted operating state, the pressure response data of each pressure contact point in the structural steady-state block is extracted in the continuous time interval, the pressure energy offset value of each pressure contact point relative to the center of the steady-state block is calculated, and the pressure energy offset value is time series normalized to form the pressure energy offset distribution trajectory. Based on the assessment that the pipeline is in a restricted operating state, to further characterize the locally restricted response behavior within the pipeline, it is necessary to extract pressure response data for each pressure contact point over a continuous time interval from the structural steady-state block. This response data is first segmented according to the time axis to ensure the stability and continuity of the analysis period. Then, using the geometric center of the structural steady-state block as a reference point, the energy deviation between the response pressure value at each pressure contact point and the pressure value at the center point is calculated; this is the pressure energy offset value. This offset value reflects the degree of inherent imbalance in the pressure distribution relative to the steady-state center, helping to reveal whether there is potential fluid misalignment caused by minor forces. By organizing the pressure energy offset values ​​at different times in chronological order, a continuous pressure energy offset distribution trajectory can be generated, thereby capturing the evolution trend of pressure distribution over time. For example, if the offset value gradually expands away from the center over a certain period, it may indicate that the flow resistance in that area is increasing; such trends are crucial for subsequent flow state assessment.

[0047] The response data at pressure contact points must be continuous and spatially comparable; therefore, standardization is required through a unified time sampling interval and spatial mapping method. The center of the structural steady-state block is not a simple geometric center, but rather a weighted calculation based on the region with the most stable amplitude in the pressure distribution, ensuring the representativeness of the comparison benchmark. The pressure energy offset value is the difference between the current contact point pressure value and the central benchmark value. It not only expresses the pressure gradient at the spatial level but also implies the potential energy change tendency caused by micro-velocity fluctuations. Time series normalization means that within each time segment, the degree of deviation from the center must be recalculated and a trajectory formed sequentially to reconstruct the dynamic response evolution path in the pipeline caused by constraints. The pressure energy offset distribution trajectory ultimately provides an important basis for judging the operational trend of the pipeline and can be used to further fit and model it in conjunction with other physical quantities.

[0048] Based on the pressure energy offset distribution trajectory, the pressure energy gradient change rate between adjacent pressure contact points is calculated within the continuous response time window. Combined with the temporal distribution of the flow vector path, a fluid stress transmission trajectory reflecting the force direction of blood flow is generated, and the correlation path structure between pressure energy gradient and stress direction is established. To further analyze the fluid response mechanism within the pipeline, it is necessary to calculate the rate of change of pressure energy gradient between adjacent pressure contact points within a continuous response time window, based on the pressure energy offset distribution trajectory. This process obtains the rate of change of pressure energy per unit distance by performing temporal and spatial difference on the pressure energy offset values ​​of each pair of adjacent contact points. Subsequently, the rate of change of pressure energy gradient within each time window is matched with the flow vector path fitted within that time period to generate a fluid stress transmission trajectory, which is used to characterize the directionality and intensity trend of stress transmission between different locations in the blood. For example, if the pressure energy at the upstream contact point of a certain path continuously increases while the downstream contact point changes slowly, it indicates that there is energy accumulation in this path, and stress transmission in the flow direction may be obstructed. In this way, a logical connection between pressure energy gradient and stress direction can be established in both time and space dimensions, clarifying the stress transmission mode of each response unit within the pathway under blood flow restriction, which facilitates subsequent trend judgment and dynamic modeling.

[0049] The pressure energy offset distribution trajectory is time-series data, reflecting the pressure change trend of each pressure contact point relative to the steady-state baseline. By extracting the pressure energy offset differences between adjacent contact points within a continuous time window and calculating the gradient change rate in conjunction with spatial coordinate differences, the energy flow tendency within each small segment can be clearly identified. The flow vector path is a continuous curve fitted to the response extension direction of each pressure contact point, exhibiting clear temporal characteristics. Cross-comparison of the two allows for the extraction of the main direction of stress propagation in the pipeline and its variation law, thereby drawing a trajectory line that truly reflects the fluid force transmission path. The associated path structure is a space-time mapping model constructed based on the stress transmission trajectory and combined with the pressure energy gradient direction, used to represent the stress and energy transfer relationship between each contact point under constrained conditions. This structure provides underlying support for the subsequent construction of a pathway operation trend assessment structure, achieving an accurate expression of the dynamic changes in blood flow response.

[0050] The pressure energy offset value and the fluid stress transmission trajectory are jointly fitted in both time and space to generate a dynamic response matrix that includes the pressure energy vector, stress extension direction and rate of change. This dynamic response matrix is ​​then used to construct a pipeline operation trend assessment structure to present the response change trend of the current pipeline operation status.

[0051] To accurately represent the blood flow trend within the tubing under restricted conditions, a dynamic response matrix needs to be constructed by jointly fitting the pressure energy offset value and the fluid stress transmission trajectory in both time and space. This matrix forms a multi-dimensional data structure by matching the pressure energy vector information of each pressure contact point at different times with the stress extension direction and velocity change value of the corresponding time period, reflecting the dynamic evolution of each location point over time. Specifically, the pressure energy offset value is vectorized, its directional and intensity components are extracted, and then vector-coupled with the stress transmission path within the corresponding time period to obtain the composite response characteristics of each contact point at a certain moment. For example, within a certain time window, if the pressure energy vector and stress extension direction of a contact point tend to be consistent, and their rates of change increase synchronously, it can be determined that there is a risk of increased restriction at that location. Extending this joint characteristic to the entire pathway forms a dynamic response matrix, which can capture minute fluctuations in the internal flow trend of the tubing in real time, thus providing a basis for subsequent dynamic control.

[0052] The pressure energy vector is composed of the directionality of the pressure energy offset value in three-dimensional space, reflecting the main direction of pressure energy conduction per unit time at each contact point. The stress propagation direction is the temporal flow direction based on the fluid stress conduction trajectory, indicating the main axial trend of force propagation in the blood. The rate of change refers to the rate at which the pressure energy vector and stress propagation direction shift with time, obtained through differential calculations at continuous time points. Organizing these parameters into a unified three-dimensional tensor structure forms a dynamic response matrix, used to describe the system's operating state at each spatiotemporal point. This matrix not only serves as an intuitive representation of the operating state but also possesses the ability to predict trends. By analyzing the continuity of vector changes and gradient abrupt changes in the matrix, potential operational anomalies can be identified and modeled, forming the core structural foundation for assessing pathway operational trends.

[0053] S5. Assess structural changes based on pathway operation trends, adjust the drainage direction of the blood drainage inlet, apply flow disturbance, and dynamically regulate the operation status of the extracorporeal membrane oxygenation (ECMO) pipeline based on disturbance feedback changes.

[0054] In this embodiment, S5 specifically refers to: Based on the trend of pathway operation, structural changes are assessed. Within the continuous response time interval, the rate of change of pressure energy vector and the rate of change of stress extension direction are extracted to construct a response deviation model that reflects the trend of flow path offset. Based on the information of offset direction and offset amplitude in the response deviation model, offset control parameters for adjusting the drainage direction of blood drainage inlet are generated. Extracting the rate of change of pressure energy vector and the rate of change of stress extension direction within a continuous response time interval is typically achieved by calculating the rate of change of pressure energy distribution at each pressure contact point in the structural steady-state block over time, combined with the rate of change of stress direction vector in the fluid stress transmission trajectory over time. Specifically, this can be accomplished by setting a fixed response sampling period and performing first-order difference processing on the pressure energy value at each pressure contact point to obtain the rate of change of pressure energy vector; simultaneously, based on the change in the angle between stress direction vectors at adjacent time points, the rate of change of stress extension direction is calculated. Subsequently, these two sets of rate of change data are subjected to multidimensional fitting to construct a response deviation model. This model uses time as the basic axis and integrates the offset trend information of both pressure energy and stress directional dimensions. In this model, if the pressure energy vector continuously shifts within a certain interval and the stress direction tends to deviate from the principal axis, an offset control parameter can be extracted based on the directionality and magnitude of the shift. This parameter is used to control the drainage direction of the blood drainage inlet, thereby achieving directional adjustment of the unstable flow path. The purpose of this is to perform fine-tuning control before structural anomalies appear in the flow trend, to prevent the potential operational risks from escalating.

[0055] "Pressure energy vector change rate" is a quantitative indicator obtained by measuring the increase or decrease trend of pressure energy displacement relative to the structural steady-state center over time. Its value represents the speed and direction of pressure center offset. "Stress extension direction change rate" is based on the speed of rotation or offset of the main axis direction of the stress transmission path constructed by the contact point during blood flow, reflecting the instability trend of blood flow direction. "Response deviation model" is a two-dimensional or three-dimensional data structure, whose coordinate axes represent time, spatial position and vector change information, respectively, and can completely capture the synchronous change behavior of pressure energy and stress. "Offset control parameters" are a set of parameters extracted from the model to characterize vector anomalies, mainly including offset angle, offset speed and offset duration. They are usually input into the drainage control system in vector form to control the fine adjustment of the blood drainage inlet angle to achieve active correction and stable maintenance of the running path.

[0056] The drainage direction of the blood drainage inlet is adjusted based on the offset control parameters. The flow direction disturbance is applied within a preset time period by changing the drainage direction. During the disturbance, continuous pressure response data of multiple pressure contact points in the extracorporeal membrane oxygenation (ECMO) tubing are collected to form a pressure feedback sequence before and after the disturbance, and a flow direction disturbance feedback change structure is constructed. Adjusting the drainage direction of the blood drainage inlet based on offset control parameters mainly involves inputting parameters such as offset angle and offset rate extracted from the response deviation model into the control system. This controls the physical posture of the drainage catheter or the bending angle of the drainage path, thereby altering the blood flow direction as it enters the extracorporeal membrane oxygenation (ECMO) tubing. In practice, adjustable-angle drainage interfaces or electrically controlled flexible drainage catheters can be used to dynamically regulate the directionality of blood inflow. Within a set disturbance time period, the overall flow direction is disturbed by physically adjusting the drainage path. This disturbance can be a small-amplitude angular offset, periodic angular switching, or flow disturbance at a specific frequency. Simultaneously with the disturbance, continuous pressure response data before and after the flow direction disturbance is collected in real time using multiple pressure contact points arranged within the ECMO tubing. Subsequently, the pressure data before and after the disturbance are processed to form a pressure response sequence. By comparing the response differences between the two sequences, a flow direction disturbance feedback change structure reflecting the changes in the disturbance's impact is constructed to analyze the specific effects of the drainage direction change on the overall operating status. This method of achieving closed-loop regulation of drainage control and feedback modeling is an important technical means for dynamically controlling the operating status of pipelines.

[0057] "Offset control parameters" refers to the set of information parameters extracted from the preceding deviation model, including the directional deviation angle, velocity, and time interval, which serves as the input basis for drainage control actions. "Drainage direction" is the initial flow path of blood fluid entering the pipeline, and its angle and path directly affect the subsequent internal fluid distribution and pressure structure. "Preset time period" is a stable duration window set by the control system for each disturbance, used to limit the application time of the disturbance and the feedback acquisition window. "Flow direction disturbance" is an artificially created flow environment disturbance, aimed at verifying or adjusting whether the current pipeline response trend can be affected by controlled intervention. "Pressure feedback sequence" is a set of pressure value data collected at the pressure contact point at different time periods before and after the disturbance, reflecting the changes in the internal system before and after the disturbance. "Flow direction disturbance feedback change structure" is a structure obtained by performing difference analysis and trend modeling on the above feedback data before and after the disturbance, used to quantitatively analyze the effect of disturbance control and assist in the next dynamic adjustment decision. It can be used to determine whether it is necessary to continue optimizing the drainage direction, whether it is necessary to terminate the disturbance, or whether the flow path correction has been successfully achieved.

[0058] Based on the feedback change structure of flow direction disturbance, the response change trend of pressure energy offset value and stress transmission trajectory before and after disturbance is analyzed. When the pressure energy distribution in the feedback change structure gradually returns to equilibrium and the stress transmission tends to a stable direction, the pathway operation trend evaluation structure is updated, and the operation status of the extracorporeal membrane oxygenation pipeline is continuously and dynamically adjusted accordingly.

[0059] After applying flow disturbance and collecting feedback data, it is necessary to compare and analyze the internal response trend of the system before and after the disturbance based on the changes in the flow disturbance feedback structure. The analysis process uses the pressure energy offset value and fluid stress transmission trajectory before and after the disturbance as the core indicators. Specifically, the pressure energy offset distribution before and after the disturbance is fitted and compared on the time and space axes to calculate whether the pressure energy offset at the same response position has decreased, and to determine whether the overall distribution tends to be symmetrical or balanced. At the same time, the stress transmission path in continuous time periods after the disturbance is extracted, and it is observed whether its extension direction tends to be stable and whether the path oscillation has decreased. If the fluctuation of the pressure energy distribution curve weakens, the center value shifts back, and the stress transmission trajectory line tends to be in a single direction and nonlinear disturbances decrease, it is determined that the system response is returning to a normal state. At this time, the current state is used as the input of the new pathway operation trend evaluation structure and as the latest basis for dynamic control system to continuously adjust the pipeline operation state. Through repeated disturbances and evaluations, the drainage pipeline is gradually made to reach the optimal operation path to ensure the efficiency and safety of the extracorporeal membrane oxygenation process.

[0060] The "Flow Direction Disturbance Feedback Change Structure" is a structure based on modeling the difference in continuous pressure data before and after a disturbance, used to reveal the changes in the system's internal response caused by the disturbance; the "Pressure Energy Offset Value" is the deviation of the pressure value at each pressure contact point from the steady-state center point, reflecting the degree of local energy imbalance; the "Stress Transmission Trajectory" is a vector path constructed based on the stress extension trend between pressure contact points, characterizing the change in the direction of blood force; the "Response Change Trend" is the trend information extracted by comparing the parameter change trajectories before and after the disturbance, used to judge the intervention effect; "Equilibrium" refers to a state where the pressure energy tends to be symmetrical, concentrated, or stable in spatial distribution; "Tends to Stable Direction" refers to a state where the stress trajectory gradually fixes in a certain direction and no longer undergoes significant deviation or reversal; the "Updated Pathway Operation Trend Evaluation Structure" refers to using the new round of response state as the basis for judgment, replacing the old operation trend reference; "Continuous Dynamic Regulation" refers to continuously making real-time adjustments based on the feedback trend tending to the ideal state, ensuring that the system always operates in the optimal state. These elements constitute the core components of the closed-loop control system and are the key path to achieving high-precision dynamic regulation.

[0061] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions according to the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means (e.g., infrared, wireless, microwave, etc.). A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0062] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0063] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0064] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0065] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0066] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0067] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for real-time monitoring of pressure in extracorporeal membrane oxygenation (ECMO) tubing, characterized in that, Specifically, the following steps are included: S1. Collect continuous pressure data at multiple pressure contact points along the venous drainage path of the extracorporeal membrane oxygenation (ECMO) tubing, construct a flow direction response distribution cluster arranged in time sequence, and determine whether the tubing is under external pressure but not completely closed based on the response amplitude shift trend between each contact point in the flow direction response distribution cluster. S2. When it is determined that the pipeline is under external pressure but not completely closed, extract a steady-state distribution segment with stable pressure and balanced amplitude from the flow response distribution cluster, and determine the abnormally stable pressure signal phenomenon when the pipeline is under external pressure but not completely closed by performing fluctuation consistency back-return analysis on the steady-state distribution segment. S3. Based on the determination of the abnormal stability of the pressure signal, establish the comparison relationship between the structural steady-state block and the flow vector path. By comparing the vector deviation and the change characteristics of the steady-state block, determine whether the pipeline is in a restricted operating state. S4. Based on the judgment that the pipeline is in a restricted operating state, the pressure energy offset value and fluid stress transmission trajectory within the structural steady-state block are integrated to construct a pipeline operation trend assessment structure to present dynamic response change characteristics. S5. Assess structural changes based on pathway operation trends, adjust the drainage direction of the blood drainage inlet, apply flow disturbance, and dynamically regulate the operation status of the extracorporeal membrane oxygenation (ECMO) pipeline based on disturbance feedback changes.

2. The method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure according to claim 1, characterized in that, S1 specifically refers to: Multiple pressure contact points are set up along the venous drainage path of the extracorporeal membrane oxygenation (ECMO) tubing. Pressure data is continuously collected at each pressure contact point within a uniform time interval. The collected pressure data is arranged in chronological order to form a continuous pressure data set containing time labels and spatial coordinates. Based on a continuous pressure dataset, the pressure data of each pressure contact point are arranged and combined in chronological order to construct a flow response distribution cluster with chronological order as the main axis and the spatial location of the pressure contact point as the auxiliary axis. This cluster is used to represent the response relationship between different pressure contact points within the venous drainage path. The difference calculation is performed on the pressure response amplitude of adjacent pressure contact points in the flow response distribution cluster within a continuous time segment to extract the amplitude offset curve between adjacent contact points; on the amplitude offset curve, an interval in which the amplitude continuously decreases and does not show a symmetrical rebound is detected, and the offset direction and duration of the interval are calculated. When the offset direction is always along the blood flow direction and the duration exceeds the stable duration of the adjacent cycle, it is determined that the tubing is under external pressure but not completely closed.

3. The method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure according to claim 1, characterized in that, S2 specifically includes the following steps: S201. When it is determined that the pipeline is under external pressure but not completely closed, the pressure response sequence of each pressure contact point in the continuous time interval is extracted based on the flow response distribution cluster. The continuous segments that simultaneously meet the requirements of the response value change range being less than the preset amplitude offset threshold and the waveform fluctuation being less than the mean square error limit are defined as steady-state distribution segments with stable pressure and balanced amplitude. S202. Copy the response data of each pressure contact point in the steady-state distribution segment with stable pressure and uniform amplitude in reverse order of time to generate a backtracking sequence, and calculate the point-to-point amplitude difference with the original sequence. Calculate the variance of the difference within the continuous time window and construct a fluctuation consistency backtracking analysis diagram. S203. Based on the variation characteristics of the difference variance distribution in the fluctuation consistency return analysis diagram, identify segments in which the difference variance remains within the preset deviation range and there is no periodic reversal within the continuous time interval. Determine that the pressure signal is in an abnormally stable state and identify the abnormally stable pressure signal phenomenon when the pipeline is externally compressed but not completely closed.

4. The method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure according to claim 3, characterized in that, S203 specifically refers to: The difference variance sequence in the fluctuation consistency return analysis graph is discretized and segmented according to time order. The difference variance value in each segment is compared with the preset deviation threshold point by point to select the stable interval in which all difference variances in continuous time segments are within the preset deviation range. Within the stable interval, the direction of change of the variance of the difference between adjacent time segments is calculated. The direction determination algorithm is used to detect whether there is a periodic reversal phenomenon of the variance of the difference. When the direction of change of all consecutive segments is consistent and there is no alternation of direction, the stable interval is defined as the non-periodic reversal interval. Within the non-periodic reversal interval, the temporal distribution of the difference variance is continuously verified. When the duration of the non-periodic reversal interval exceeds the average stable duration of the adjacent normal cycle, the non-periodic reversal interval is determined to be an abnormally stable pressure signal. Based on this determination result, the abnormally stable pressure signal phenomenon under external pressure but not complete closure of the pipeline is identified.

5. The method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure according to claim 1, characterized in that, S3 specifically includes the following steps: S301. Based on the determination of the abnormal stability of the pressure signal, extract the pressure response data within the time interval corresponding to the abnormal stability of the pressure signal, construct a pressure response map according to the spatial arrangement of the pressure contact points, and extract equal amplitude response regions in segments with the stability interval as the boundary. Based on the consistency of the response, aggregate the equal amplitude response regions into structural steady-state blocks. S302. Based on the temporal and spatial locations of the structural steady-state blocks, establish a reference axis for comparison, fit the response extension direction of each pressure contact point in a continuous time interval, construct a flow vector path that reflects the actual blood flow trend, and cross-compare the flow vector path with the structural steady-state blocks in both time and space dimensions. S303. Compare the degree of overlap between the structural steady-state block and the flow vector path under the same response axis. When the vector deviation is detected in the flow vector path as continuously deviating from the main axis direction of the structural steady-state block, and the deviation trend does not show directional correction, it is determined that the pipeline is in a restricted operating state, and the deviation direction and degree are used as the judgment output.

6. The method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure according to claim 5, characterized in that, S303 specifically refers to: Based on the comparison between the structural steady-state block and the flow vector path, the vector coordinate values ​​at each time point under the same response axis are extracted, the deviation angle between the flow vector path and the principal axis direction of the structural steady-state block is calculated, and a vector deviation curve with time as the sequence is formed to represent the trend of deviation over time. The deviation angle changes in the continuous time interval of the vector deviation curve are statistically analyzed. When the deviation angle increases continuously in the same direction and does not decrease in the opposite direction in adjacent sampling periods, the time interval is marked as a continuous deviation interval, and the deviation growth rate is extracted as the vector offset trend parameter. Within the continuous deviation range, when the directional offset trend parameter remains in an increasing state and there is no directional repair characteristic, the pressure signal corresponding to the continuous deviation range is determined to be that the pipeline is in a restricted operating state, and the combined value of the offset direction and offset degree is output as a quantitative judgment result to characterize the intensity of restricted operation.

7. The method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure according to claim 1, characterized in that, S4 specifically refers to: Based on the judgment that the pipeline is in a restricted operating state, the pressure response data of each pressure contact point in the structural steady-state block is extracted in the continuous time interval, the pressure energy offset value of each pressure contact point relative to the center of the steady-state block is calculated, and the pressure energy offset value is time series normalized to form the pressure energy offset distribution trajectory. Based on the pressure energy offset distribution trajectory, the pressure energy gradient change rate between adjacent pressure contact points is calculated within the continuous response time window. Combined with the temporal distribution of the flow vector path, a fluid stress transmission trajectory reflecting the force direction of blood flow is generated, and the correlation path structure between pressure energy gradient and stress direction is established. The pressure energy offset value and the fluid stress transmission trajectory are jointly fitted in both time and space to generate a dynamic response matrix that includes the pressure energy vector, stress extension direction and rate of change. This dynamic response matrix is ​​then used to construct a pipeline operation trend assessment structure to present the response change trend of the current pipeline operation status.

8. The method for real-time monitoring of extracorporeal membrane oxygenation (ECMO) tubing pressure according to claim 1, characterized in that, S5 specifically refers to: Based on the trend of pathway operation, structural changes are assessed. Within the continuous response time interval, the rate of change of pressure energy vector and the rate of change of stress extension direction are extracted to construct a response deviation model that reflects the trend of flow path offset. Based on the information of offset direction and offset amplitude in the response deviation model, offset control parameters for adjusting the drainage direction of blood drainage inlet are generated. The drainage direction of the blood drainage inlet is adjusted based on the offset control parameters. The flow direction disturbance is applied within a preset time period by changing the drainage direction. During the disturbance, continuous pressure response data of multiple pressure contact points in the extracorporeal membrane oxygenation (ECMO) tubing are collected to form a pressure feedback sequence before and after the disturbance, and a flow direction disturbance feedback change structure is constructed. Based on the feedback change structure of flow direction disturbance, the response change trend of pressure energy offset value and stress transmission trajectory before and after disturbance is analyzed. When the pressure energy distribution in the feedback change structure gradually returns to equilibrium and the stress transmission tends to a stable direction, the pathway operation trend evaluation structure is updated, and the operation status of the extracorporeal membrane oxygenation pipeline is continuously and dynamically adjusted accordingly.

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