Intelligent visual midwifery system for obstetrics and gynecology department based on ultrasonic technology

Abstract

The invention discloses a gynaecology and obstetrics intelligent visual midwifery system based on an ultrasonic technology, and relates to the technical field of ultrasonic midwifery, the system constructs a two-dimensional coordinate system and extracts ultrasonic echo total time and respiratory phase data, and fetal membrane structure data and fetal physiological data are generated through dimensionless processing and data analysis. And constructing an amniotic sac thickness gradient index dyn according to the thickness gradient change to evaluate the structural stability of the amniotic sac. And if the fetal respiratory phase drift index psh is evaluated to be unstable, calculating the fetal respiratory phase drift index psh, and jointly constructing a comprehensive parturition risk index Rco with the amniotic sac thickness gradient index dyn to reflect the potential parturition risk of coupling of the fetal stress level and the membrane structure variation. And the system generates different types of intervention instructions according to the evaluation result of the comprehensive parturition risk index Rco. Multi-dimensional data mapping and layer display are achieved, linkage display of a risk thermodynamic diagram and a breathing phase curve is supported, and a visual and traceable dynamic midwifery decision basis is provided for medical staff.

Description

Technical Field

[0001] This invention relates to the field of ultrasound-assisted delivery technology, specifically to a smart visual obstetric delivery system based on ultrasound technology. Background Technology

[0002] With the widespread application of ultrasound imaging technology in the medical field, data acquisition and structural analysis based on real-time intelligent ultrasound sensor arrays have become an important method for maternal and fetal assessment in obstetrics and gynecology. While traditional ultrasound examinations can assist medical staff in observing the basic morphology of the fetus and the state of the amniotic membranes, the limited information presentation format, relying primarily on image interpretation and lacking a structured data-driven dynamic assessment mechanism, makes it difficult to promptly identify subtle structural changes and fetal stress responses during labor. In recent years, intelligent visual midwifery systems have begun to integrate high-resolution imaging, dynamic curve tracking, and data fitting algorithms, driving the shift from static observation to dynamic intervention. How to transform ultrasound signals into quantifiable and analyzable indicators to reflect the structural safety of the amniotic sac and the health of fetal respiratory rhythms, while ensuring non-invasive detection, has become an important development direction in intelligent midwifery research in obstetrics and gynecology.

[0003] The health of the fetus in utero, especially near delivery, is influenced by multiple factors, including maternal condition, amniotic membrane integrity, and fetal respiratory rhythm. Most existing assessment methods primarily focus on fetal heart rate monitoring and fetal movement perception, lacking precise quantitative means for assessing changes in amniotic sac thickness and fetal respiratory phase shifts. Furthermore, they often rely on discontinuous testing, making it difficult to generate continuous assessment results, leading to delays in identifying abnormal signs and affecting the timeliness of intervention. In addition, existing systems are mostly image- or semantic-label-based, lacking the ability to fuse and analyze multidimensional physiological signals and provide real-time feedback, failing to fully capture the coupling relationship between amniotic sac microstructural degradation and fetal physiological stress during labor. Therefore, during labor, especially before sudden amniotic sac structural instability or fetal respiratory abnormalities occur, traditional methods struggle to provide continuous, quantitative, and predictive evidence for intervention. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a smart visual midwifery system for obstetrics and gynecology based on ultrasound technology, which solves the problems mentioned in the background.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a smart visual midwifery system for obstetrics and gynecology based on ultrasound technology, comprising a signal acquisition module, a structural analysis module, a functional analysis module, an instruction execution module, and a visualization module;

[0006] The signal acquisition module is used to perform a panoramic scan of the amniotic sac area of ​​the pregnant woman through an intelligent ultrasonic sensor array, determine the boundary of the amniotic sac and establish a two-dimensional rectangular coordinate system, and then obtain the total round-trip time of ultrasound at the coordinate point sj and the motion curve of the fetal chest based on the intelligent ultrasonic sensor array. After data analysis, the module performs dimensionless processing to obtain fetal membrane structure data and fetal physiological data.

[0007] The structural analysis module is used to calculate the amniotic sac thickness gradient index dyn based on the fetal membrane structure data to evaluate the structural stability of the amniotic sac, and to trigger the functional analysis module when the structure is evaluated as unstable.

[0008] The functional analysis module is used to calculate the respiratory phase drift index psh based on fetal physiological data, and fit it with the amniotic sac thickness gradient index dyn to construct a comprehensive labor risk index Rco for assessing respiratory phase shift.

[0009] The instruction execution module is used to generate corresponding intervention information based on the respiratory phase shift assessment results;

[0010] The visualization module is used to generate two-dimensional heat maps, one-dimensional curves, and comprehensive labor risk curves, and displays the layers in a layered manner on the display interface.

[0011] Preferably, the signal acquisition module includes a coordinate construction unit and an ultrasonic signal acquisition unit;

[0012] The coordinate construction unit includes a boundary calibration unit and a coordinate system generation unit;

[0013] The boundary calibration unit is used to perform a panoramic scan of the pregnant woman's lower abdomen and the entire amniotic sac using an intelligent ultrasonic sensor array, capture echo signals from different angles, and transmit the echo signals to the intelligent visual midwifery system through a dedicated API interface. The echo signals are converted into initial image data of the amniotic sac and surrounding anatomical structures through image processing algorithms and recorded. Then, the spatial boundary of the amniotic sac is determined using an echo intensity edge detection algorithm, and the identified spatial boundary is converted into a point set to form a boundary frame.

[0014] The coordinate system generation unit is used to establish a two-dimensional rectangular coordinate system within the calibrated boundary frame. The origin is fixed at the geometric center of the amniotic sac, the horizontal parallel direction of the mother body is set as the x-axis, the vertical parallel direction of the mother body is set as the y-axis, and grid points are generated at a fixed interval of 1mm. Each intersection point is set as a numberable coordinate point.

[0015] Preferably, the ultrasonic signal acquisition unit includes a data acquisition unit and a data processing unit;

[0016] The data acquisition unit is used to scan the amniotic sac of the pregnant woman based on the intelligent ultrasonic sensor array and record the total round-trip time sj of the echo at each coordinate point in the coordinate system in real time, and record the chest movement curve of the fetal chest displacement over time.

[0017] The data processing unit is used to perform dimensionless processing on the total round-trip time sj of the echo, and then perform data analysis to obtain fetal membrane structure data and fetal physiological data.

[0018] The dimensionless processing removes the dimensional influence of the state data using the Max-Min method.

[0019] The data analysis includes amniotic sac thickness analysis and respiratory phase analysis;

[0020] The amniotic sac thickness analysis is used to calculate the amniotic sac thickness hd(i,j) at sampling point (i,j) based on the sound velocity constant c of ultrasound propagation in the medium where the amniotic sac is located. Specifically: In the formula, sj(i,j) represents the total round-trip time of the echo at sampling point (i,j);

[0021] The respiratory phase analysis is used to identify the zero-crossing point from negative to positive as the inspiratory start point xk, and the zero-crossing point from positive to negative as the expiratory start point, based on the thoracic motion curve after removing non-respiratory frequency components using a bandpass filter. The respiratory cycle length Tc is obtained by subtracting the inspiratory start point of the previous cycle from the current inspiratory start point. The respiratory phase value br is then calculated. Specifically: In the formula, π represents the constant value of pi, which is taken to two decimal places.

[0022] The fetal membrane structure data includes the amniotic sac thickness hd(i,j);

[0023] The fetal physiological data includes respiratory phase values ​​(br).

[0024] Preferably, the structural analysis module includes a structural analysis unit and a structural evaluation unit;

[0025] The structural analysis unit is used to fit the fetal membrane structure data, analyze the rate of change of the amniotic sac thickness gradient over time, and construct the amniotic sac thickness gradient index dyn based on the fetal membrane structure data to reflect the dynamics of amniotic sac thinning. The specific formula is as follows: In the formula, dyn(i,j) represents the rate of change of the amniotic sac thickness gradient at sampling point (i,j), and ∆t represents the continuous sampling time interval. and These represent the spatial variation rates of the amniotic sac thickness in the horizontal x-direction and the vertical y-direction, respectively.

[0026] Preferably, the structural evaluation unit is used to sort the amniotic sac thickness gradient index dyn in the past six months from smallest to largest, preset the 50th percentile as the amniotic sac structural safety threshold Gd by the quantile method, and evaluate the amniotic sac structural stability with the real-time acquired amniotic sac thickness gradient index dyn. The specific evaluation scheme is as follows.

[0027] When the amniotic sac thickness gradient exponent dyn < the amniotic sac structural safety threshold Gd, it indicates that the amniotic sac structure is stable and the amniotic sac thickness is within the normal range. At this time, normal monitoring should be maintained.

[0028] When the amniotic sac thickness gradient exponent dyn is greater than or equal to the amniotic sac structural safety threshold Gd, it indicates that the amniotic sac structure is unstable and there is a local thinning trend in the amniotic sac thickness. At this time, the respiratory phase drift analysis command is executed.

[0029] Preferably, the functional analysis module is used to execute respiratory phase drift analysis instructions when the amniotic sac structure stability assessment indicates that the amniotic sac structure is unstable, specifically including a respiratory phase analysis unit and a risk analysis unit;

[0030] The respiratory phase analysis unit is used to fit fetal physiological data, analyze the phase shift between the fetal chest respiratory movement rhythm and a healthy baseline, and construct a respiratory phase drift index (PSH) based on the fetal physiological data to reflect the fetal physiological stress response. The specific formula is as follows: In the formula, N represents the number of thoracic markers, br(k,t) represents the respiratory phase value of the k-th thoracic marker at time t, and br0(k) represents the reference healthy respiratory phase value under standard conditions.

[0031] Preferably, the risk analysis unit includes a labor process risk analysis unit and a risk assessment unit;

[0032] The labor risk analysis unit is used to comprehensively calculate the amniotic sac thickness gradient index dyn and the respiratory phase drift index psh to construct a comprehensive labor risk index Rco. This index is used for comprehensive decision analysis by integrating the dynamic thinning rate of the fused membrane structure with the degree of fetal respiratory phase abnormalities. The specific formula is as follows: In the formula, ln represents the logarithmic function, T represents the end time of the monitoring period, t0 represents the start time of the monitoring period, and dyn(t) and psh(t) represent the amniotic sac thickness gradient index and respiratory phase drift index at time t, respectively.

[0033] Preferably, the risk assessment unit is used to sort the comprehensive labor risk index Rco within the past six months from smallest to largest, and preset the 15th percentile as the critical threshold for insufficient respiratory phase Gc and the 85th percentile as the critical threshold for hyperspiratory respiratory phase Go using the quantile method, and to evaluate the respiratory phase shift with the real-time acquired comprehensive labor risk index Rco. The specific evaluation scheme is as follows.

[0034] When the comprehensive labor risk index Rco is less than the critical threshold Gc for insufficient respiratory phase, it indicates that there is a shift in the fetal respiratory phase and insufficient fetal respiratory movement. At this time, an intervention instruction for insufficient breathing is generated.

[0035] When the respiratory phase insufficiency threshold Gc ≤ comprehensive labor risk index Rco ≤ respiratory phase hyperactivity threshold Go, it indicates that the fetal respiratory phase is stable and there is no intrauterine stress response. At this time, a stable intervention instruction is generated.

[0036] When the comprehensive labor risk index Rco is greater than the respiratory phase hyperactivity threshold Go, it indicates that the fetal respiratory phase is abnormal and the fetal respiratory movement is hyperactive. At this time, an intervention instruction for hyperactivity is generated.

[0037] Preferably, the instruction execution module is used to receive instruction information on respiratory phase shift assessment in real time, generate corresponding intervention information through the intelligent visualization midwifery system, and notify relevant medical personnel, as follows;

[0038] Insufficient breathing intervention instructions: administer oxygen to the pregnant woman to increase maternal blood oxygen partial pressure, administer intravenous drugs to inhibit uterine contractions to reduce uterine tension, and then perform iterative analysis through the structural analysis module. If the fetal respiratory phase is not stabilized after three iterations, proceed with the cesarean section plan.

[0039] Stable intervention instructions: Perform ultrasound scan and respiratory phase measurement every three hours;

[0040] Hyperactivity Intervention Instructions: Simultaneously initiate continuous fetal heart rate monitoring, provide psychological counseling to pregnant women to alleviate their anxiety, administer appropriate anti-uterine contraction drugs to pregnant women based on the medical basis of acute uterine depression, and then conduct iterative analysis through the structural analysis module. If the fetal respiratory phase is not stabilized after three iterations, proceed with the cesarean section plan.

[0041] Preferably, the visualization module includes a multi-dimensional data mapping unit and a visualization display unit;

[0042] The multidimensional data mapping unit is used to map the amniotic sac thickness gradient index dyn, respiratory phase drift index psh, and comprehensive labor risk index Rco to the same time axis and coordinate system using dynamic time warping algorithm and coordinate index. It also uses bilinear interpolation technology to expand sparse coordinate points into a continuous two-dimensional heat map, maps the respiratory phase drift data of the fetal chest into a one-dimensional curve, and uses data overlay mapping technology to overlay the data into bottom, middle and top layers.

[0043] Bottom layer: Thermal distribution map of amniotic sac thickness gradient;

[0044] Middle layer: Respiratory phase drift curve;

[0045] Upper layer: Comprehensive labor risk curve;

[0046] The visualization unit is used to mark layers on the display interface based on the assessment results of amniotic sac structural stability assessment and respiratory phase shift assessment. The comprehensive labor risk curve segment with insufficient fetal respiratory movement is marked in orange, the comprehensive labor risk curve segment with stable fetal respiratory phase is marked in yellow, and the comprehensive labor risk curve segment with hyperactive fetal respiratory movement is marked in red. Clicking on the comprehensive labor risk curve enters the corresponding middle layer, which displays the respiratory phase drift curve and intuitively shows the corresponding rhythm fluctuations. Clicking on the respiratory phase drift curve again enters the bottom layer, where the stable areas of the amniotic sac structure are marked in green and the unstable areas of the amniotic sac structure are marked in blue.

[0047] This invention provides a smart visual midwifery system for obstetrics and gynecology based on ultrasound technology. It has the following beneficial effects:

[0048] (1) The system's signal acquisition module achieves comprehensive information acquisition of the pregnant woman's lower abdomen and amniotic sac area. First, the coordinate construction unit accurately calibrates the amniotic sac boundary and establishes a two-dimensional rectangular coordinate system through an intelligent ultrasonic sensor array, thereby forming a numberable grid point system in space. Subsequently, the ultrasonic signal acquisition unit records the echo round-trip time of each coordinate point in real time, and simultaneously acquires the displacement curve of the fetal chest. The total echo round-trip time sj is dimensionlessly processed using the minimization method, and then the data is analyzed to obtain fetal membrane structure data and fetal physiological data, laying a stable data foundation for subsequent structural dynamic modeling and physiological function judgment.

[0049] (2) The system structure analysis module performs spatiotemporal fitting analysis on the trend of amniotic sac thickness change, constructs the amniotic sac thickness gradient index dyn, which reflects the thinning speed and direction of the amniotic sac, and is used to analyze the stability and integrity of the overall structure of the amniotic sac. It also performs amniotic sac structure stability assessment with the preset amniotic sac structure safety threshold Gd. When the unstable characteristics of the amniotic sac structure are identified, the system automatically calls the functional analysis module to further analyze the fetal chest wall respiratory movement pattern, constructs the respiratory phase drift index psh, judges whether its rhythm has shifted or become disordered, and fits it with the amniotic sac thickness gradient index dyn to construct the comprehensive labor risk index Rco, which is used to reflect the cumulative effect of the intrauterine environment on the fetus. It assesses the respiratory phase shift by comparing it with the respiratory phase insufficiency threshold Gc and the respiratory phase hyperactivity threshold Go, assesses whether there is potential labor risk, and performs quantitative grading based on the statistical results of historical data.

[0050] (3) The system's instruction execution module generates corresponding intervention instructions based on different risk types. For example, it automatically suggests oxygen supplementation and uterine suppression when breathing is insufficient, and simultaneously initiates fetal heart rate monitoring and emotional intervention when breathing is hyperactive. At the same time, it evaluates the intervention effect through an iterative analysis mechanism and initiates a cesarean section plan when necessary. Meanwhile, the visualization module maps the three core assessment results into multi-layered graphical forms, displaying the amniotic sac structure heatmap, fetal respiratory rhythm curve, and risk evolution trend curve in layers on the display interface. Different risk level areas are marked with different colors to achieve a visual and intuitive display of labor risks, providing clinical personnel with accurate, real-time, and graded intervention decision-making basis. The construction of the overall system effectively solves the problems of single information, delayed identification, and ambiguous intervention in traditional monitoring methods, and realizes dynamic assessment and intelligent intervention of intrauterine health status based on multi-parameter fusion. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the process of an intelligent visual midwifery system for obstetrics and gynecology based on ultrasound technology according to the present invention;

[0052] Figure 2 This is a schematic diagram illustrating the operating principle of an intelligent visual midwifery system for obstetrics and gynecology based on ultrasound technology, as described in this invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Example 1

[0055] Please see Figure 1 This invention provides a smart visual obstetrics and gynecology midwifery system based on ultrasound technology. To achieve the above objectives, this invention is implemented through the following technical solutions: including a signal acquisition module, a structural analysis module, a functional analysis module, an instruction execution module, and a visualization module;

[0056] The signal acquisition module is used to perform a panoramic scan of the amniotic sac area of ​​the pregnant woman through an intelligent ultrasonic sensor array, determine the boundary of the amniotic sac and establish a two-dimensional rectangular coordinate system, and then obtain the total round-trip time of ultrasound at the coordinate point sj and the motion curve of the fetal chest based on the intelligent ultrasonic sensor array. After data analysis, the module performs dimensionless processing to obtain fetal membrane structure data and fetal physiological data.

[0057] The structural analysis module is used to calculate the amniotic sac thickness gradient index dyn based on the fetal membrane structure data to evaluate the structural stability of the amniotic sac, and to trigger the functional analysis module when the structure is evaluated as unstable.

[0058] The functional analysis module is used to calculate the respiratory phase drift index psh based on fetal physiological data, and fit it with the amniotic sac thickness gradient index dyn to construct a comprehensive labor risk index Rco for assessing respiratory phase shift.

[0059] The instruction execution module is used to generate corresponding intervention information based on the respiratory phase shift assessment results;

[0060] The visualization module is used to generate two-dimensional heat maps, one-dimensional curves, and comprehensive labor risk curves, and displays the layers in a layered manner on the display interface.

[0061] In this embodiment, the signal acquisition module not only enables panoramic ultrasound scanning of the amniotic sac region of the pregnant woman, but also, through coordinate system construction and echo time measurement, and by eliminating the dimensionality effects caused by individual differences through dimensionless processing, acquires amniotic sac thickness variation data and fetal chest respiratory curves, which were previously difficult to quantify continuously in clinical practice. This forms a unified source of fetal membrane structure data and fetal physiological data input. Unlike existing technologies that rely on single-frame ultrasound images or empirical judgment, this invention completes the task transformation from discrete images to time-series data, and from static judgment to dynamic continuous monitoring, achieving the goal of improving the continuity and reliability of data acquisition. The structural analysis module constructs an amniotic sac thickness gradient index dyn based on the rate of change of the amniotic sac thickness hd(i,j) gradient over time, and assesses the structural stability of the amniotic sac by comparing it with the amniotic sac structural safety threshold Gd, thus achieving dynamic assessment of the local thinning trend of the amniotic sac. When amniotic sac structural instability is detected, the functional analysis module further performs bandpass filtering and phase analysis on the fetal respiratory motion curve, calculates the respiratory phase drift index psh, and then fits it with the thickness gradient index dyn to form a comprehensive labor risk index Rco, which is then compared with the respiratory phase insufficiency threshold Gc and the respiratory phase hyperactivity threshold Go to assess respiratory phase shift. Through this dual-index fusion and time accumulation method, the system can simultaneously reflect the coupling relationship between the mechanical state of the fetal membrane structure and the physiological state of fetal respiratory function, achieving a scientific quantitative assessment of potential risks in labor. Compared with traditional technologies that rely solely on ultrasound image thickness or fetal heart rate monitoring signals for one-sided judgment, the improvement of this invention lies in establishing a dynamic coupling index system across structural and physiological dimensions, avoiding the shortcomings of strong subjectivity and large delays, and achieving the goal of identifying risks in the early stages of abnormalities. The instruction execution module receives real-time instructions based on respiratory phase shift assessments and automatically generates corresponding intervention information. For example, it recommends oxygen therapy and uterine contraction suppression in cases of hypoventilation, and simultaneously initiates fetal heart rate monitoring and psychological intervention in cases of hyperventilation. It then iteratively verifies the data to determine whether to proceed with a cesarean section plan. Simultaneously, the visualization module utilizes multidimensional data mapping and layered display to integrate amniotic sac thickness gradient heatmaps, fetal respiratory phase curves, and comprehensive risk curves into a single coordinate system, color-coding risk levels to help medical staff quickly and intuitively grasp the overall condition of the pregnant woman and fetus. Compared to current ultrasound interpretation methods that rely solely on two-dimensional images and text reports, this invention improves upon traditional methods by achieving a data-driven intervention loop and intuitive risk presentation. Ultimately, it significantly enhances monitoring real-time performance, intervention accuracy, and clinical decision-making efficiency, further reducing the incidence of sudden pregnancy risks.

[0062] Example 2

[0063] Please refer to Figure 1 and Figure 2Specifically: the signal acquisition module includes a coordinate construction unit and an ultrasonic signal acquisition unit;

[0064] The coordinate construction unit includes a boundary calibration unit and a coordinate system generation unit;

[0065] The boundary calibration unit is used to perform a panoramic scan of the pregnant woman's lower abdomen and the entire amniotic sac using an intelligent ultrasonic sensor array, capture echo signals from different angles, and transmit the echo signals to the intelligent visual midwifery system through a dedicated API interface. The echo signals are converted into initial image data of the amniotic sac and surrounding anatomical structures through image processing algorithms and recorded. Then, the spatial boundary of the amniotic sac is determined using an echo intensity edge detection algorithm, and the identified spatial boundary is converted into a point set to form a boundary frame.

[0066] The coordinate system generation unit is used to establish a two-dimensional rectangular coordinate system within the calibrated boundary frame. The origin is fixed at the geometric center of the amniotic sac, the horizontal parallel direction of the mother body is set as the x-axis, the vertical parallel direction of the mother body is set as the y-axis, and grid points are generated at a fixed interval of 1mm. Each intersection point is set as a numberable coordinate point.

[0067] The ultrasonic signal acquisition unit includes a data acquisition unit and a data processing unit;

[0068] The data acquisition unit is used to scan the amniotic sac of the pregnant woman based on the intelligent ultrasonic sensor array and record the total round-trip time sj of the echo at each coordinate point in the coordinate system in real time, and record the chest movement curve of the fetal chest displacement over time.

[0069] The data processing unit is used to perform dimensionless processing on the total round-trip time sj of the echo, and then perform data analysis to obtain fetal membrane structure data and fetal physiological data.

[0070] The dimensionless processing removes the dimensional influence of the state data using the Max-Min method.

[0071] The data analysis includes amniotic sac thickness analysis and respiratory phase analysis;

[0072] The amniotic sac thickness analysis is used to calculate the amniotic sac thickness hd(i,j) at sampling point (i,j) based on the sound velocity constant c of ultrasound propagation in the medium where the amniotic sac is located. Specifically: In the formula, sj(i,j) represents the total round-trip time of the echo at sampling point (i,j);

[0073] The respiratory phase analysis is used to identify the zero-crossing point from negative to positive as the inspiratory start point xk, and the zero-crossing point from positive to negative as the expiratory start point, based on the thoracic motion curve after removing non-respiratory frequency components using a bandpass filter. The respiratory cycle length Tc is obtained by subtracting the inspiratory start point of the previous cycle from the current inspiratory start point. The respiratory phase value br is then calculated. Specifically: In the formula, π represents the constant value of pi, which is taken to two decimal places.

[0074] The fetal membrane structure data includes the amniotic sac thickness hd(i,j);

[0075] The fetal physiological data includes respiratory phase values ​​(br).

[0076] In this embodiment, the signal acquisition module performs a panoramic ultrasound scan of the entire lower abdomen and amniotic sac of the pregnant woman through the boundary calibration unit, capturing echo signals from different angles. The echo signals are then transmitted to the intelligent visualization obstetric system via a dedicated API interface. The image processing algorithm converts the echo signals into initial image data of the amniotic sac and surrounding anatomical structures and records them. The echo intensity edge detection algorithm is then used to determine the spatial boundary of the amniotic sac. The identified spatial boundary is converted into a point set to form a boundary frame. Based on this, the coordinate system generation unit establishes a two-dimensional rectangular coordinate system with the geometric center of the amniotic sac as the origin, forming a grid of numbered coordinate points with a 1mm spacing. The data acquisition unit records the total echo round-trip time sj and the fetal chest movement curve of each coordinate point in real time. The data processing unit performs dimensionless processing on the total echo round-trip time sj, followed by thickness calculation and respiratory phase analysis, ultimately obtaining dimensionless fetal membrane structure data and fetal physiological data. This implementation method not only achieves dynamic quantification of amniotic sac thickness and accurate identification of fetal respiratory phase, ensuring data consistency and comparability, but also overcomes the shortcomings of traditional ultrasound examinations that rely solely on static images and experience-based judgment. This improves the accuracy of structural measurements and the stability of respiratory rhythm analysis, ultimately providing high-quality input for subsequent structural assessment and risk analysis, and effectively enhancing the real-time nature, objectivity, and scientific rigor of clinical decision-making in labor monitoring.

[0077] Example 3

[0078] Please refer to Figure 1 and Figure 2 Specifically: the structural analysis module includes a structural analysis unit and a structural evaluation unit;

[0079] The structural analysis unit is used to fit the fetal membrane structure data, analyze the rate of change of the amniotic sac thickness gradient over time, and construct the amniotic sac thickness gradient index dyn based on the fetal membrane structure data to reflect the dynamics of amniotic sac thinning. The specific formula is as follows: In the formula, dyn(i,j) represents the rate of change of the amniotic sac thickness gradient at sampling point (i,j), and ∆t represents the continuous sampling time interval. and These represent the spatial variation rates of the amniotic sac thickness in the horizontal x-direction and the vertical y-direction, respectively.

[0080] The structural evaluation unit is used to sort the amniotic sac thickness gradient index dyn from smallest to largest within the past six months, preset the 50th percentile as the amniotic sac structural safety threshold Gd using the quantile method, and evaluate the amniotic sac structural stability with the real-time acquired amniotic sac thickness gradient index dyn. The specific evaluation scheme is as follows.

[0081] When the amniotic sac thickness gradient exponent dyn < the amniotic sac structural safety threshold Gd, it indicates that the amniotic sac structure is stable and the amniotic sac thickness is within the normal range. At this time, normal monitoring should be maintained.

[0082] When the amniotic sac thickness gradient exponent dyn is greater than or equal to the amniotic sac structural safety threshold Gd, it indicates that the amniotic sac structure is unstable and there is a local thinning trend in the amniotic sac thickness. At this time, the respiratory phase drift analysis command is executed.

[0083] In this embodiment, the structural analysis module consists of a structural analysis unit and a structural evaluation unit. First, the structural analysis unit fits the amniotic membrane structure data and calculates the amniotic sac thickness gradient change rate dyn at each sampling point within a continuous time interval, quantitatively reflecting the dynamic process of amniotic sac thinning.

[0084] The core significance of the formula, including its logic, derivation basis, and meaning, is to measure the rate of change of the amniotic sac thickness gradient at the sampling point (i,j) over time, and to describe the dynamic quantitative index of the local thinning trend of the amniotic sac. and The formulas represent the spatial rates of change of amniotic sac thickness in the horizontal and vertical directions, respectively, i.e., the gradient distribution of thickness in a two-dimensional coordinate system. The squares of these values ​​are used to obtain the overall thickness gradient, avoiding unidirectional bias. Dividing by the continuous sampling time interval Δt converts the spatial gradient into a temporal rate of change, reflecting the dynamic evolution of the amniotic sac thickness gradient over time. The formula embodies the local rate of change of amniotic sac thickness in two-dimensional space and reflects the dynamic thinning trend of the amniotic sac within the continuous sampling time through time normalization. The amniotic sac thickness gradient exponent dyn is derived from the strain rate theory in continuum mechanics. It replaces the material's displacement or velocity field with the amniotic sac thickness field hd(i,j), analogizing the spatial gradient of thickness to the spatial distribution of strain. It corresponds the "displacement changing with time" in the continuum to the "amniotic sac thickness gradient changing with time." Based on this, the amniotic sac thickness gradient exponent dyn is defined, emphasizing the thickness gradient rather than the absolute thickness, because clinical risk depends primarily on the thinning trend rather than the thickness value at a particular moment.

[0085] The structural assessment unit ranks the amniotic sac thickness gradient index (dyn) over the past six months by quantile, taking the 50th quantile as the amniotic sac structural safety threshold (Gd). This threshold is then compared with the real-time amniotic sac thickness gradient index (dyn) to assess amniotic sac structural stability. If the amniotic sac thickness gradient index (dyn) is below the amniotic sac structural safety threshold (Gd), the structure is considered stable, requiring only routine monitoring. If the amniotic sac thickness gradient index (dyn) is above or equal to the amniotic sac structural safety threshold (Gd), a local thinning risk is identified, triggering subsequent respiratory phase drift analysis. This implementation achieves a closed-loop assessment from dynamic thickness gradient quantification to structural stability risk grading, achieving the objective and real-time identification of potential amniotic sac thinning abnormalities. Compared to existing methods relying on subjective image interpretation, this invention introduces a dual mechanism of quantile threshold and time-series fitting, effectively reducing human judgment bias, improving the sensitivity and accuracy of abnormality identification, thereby enhancing early warning capabilities for pregnancy risks and significantly improving labor safety and clinical decision-making efficiency.

[0086] Example 4

[0087] Please refer to Figure 1 and Figure 2 Specifically: the functional analysis module is used to execute respiratory phase drift analysis instructions when the amniotic sac structure stability assessment indicates that the amniotic sac structure is unstable, and specifically includes a respiratory phase analysis unit and a risk analysis unit;

[0088] The respiratory phase analysis unit is used to fit fetal physiological data, analyze the phase shift between the fetal chest respiratory movement rhythm and a healthy baseline, and construct a respiratory phase drift index (PSH) based on the fetal physiological data to reflect the fetal physiological stress response. The specific formula is as follows: In the formula, N represents the number of thoracic markers, br(k,t) represents the respiratory phase value of the k-th thoracic marker at time t, and br0(k) represents the reference healthy respiratory phase value under standard conditions.

[0089] The risk analysis unit includes a labor process risk analysis unit and a risk assessment unit;

[0090] The labor risk analysis unit is used to comprehensively calculate the amniotic sac thickness gradient index dyn and the respiratory phase drift index psh to construct a comprehensive labor risk index Rco. This index is used for comprehensive decision analysis by integrating the dynamic thinning rate of the fused membrane structure with the degree of fetal respiratory phase abnormalities. The specific formula is as follows: In the formula, ln represents the logarithmic function, T represents the end time of the monitoring period, t0 represents the start time of the monitoring period, and dyn(t) and psh(t) represent the amniotic sac thickness gradient exponent and respiratory phase drift exponent at time t, respectively. It is used to accumulate the degree of abnormality over time, emphasizing the danger of persistent abnormalities. The logarithmic function ln is used to logarithmically compress the results to prevent extreme values ​​from causing abnormal amplification of the risk index, and to maintain the stability and interpretability of the comprehensive labor risk index.

[0091] The risk assessment unit is used to sort the comprehensive labor risk index Rco from the past six months in ascending order, and to preset the 15th percentile as the critical threshold for insufficient respiratory phase Gc and the 85th percentile as the critical threshold for hyperspiratory respiratory phase Go using the quantile method. The unit is then compared with the real-time acquired comprehensive labor risk index Rco to assess respiratory phase shift. The specific assessment scheme is as follows.

[0092] When the comprehensive labor risk index Rco is less than the critical threshold Gc for insufficient respiratory phase, it indicates that there is a shift in the fetal respiratory phase and insufficient fetal respiratory movement. At this time, an intervention instruction for insufficient breathing is generated.

[0093] When the respiratory phase insufficiency threshold Gc ≤ comprehensive labor risk index Rco ≤ respiratory phase hyperactivity threshold Go, it indicates that the fetal respiratory phase is stable and there is no intrauterine stress response. At this time, a stable intervention instruction is generated.

[0094] When the comprehensive labor risk index Rco is greater than the respiratory phase hyperactivity threshold Go, it indicates that the fetal respiratory phase is abnormal and the fetal respiratory movement is hyperactive. At this time, an intervention instruction for hyperactivity is generated.

[0095] In this embodiment, when the amniotic sac structure stability assessment indicates that the amniotic sac structure is unstable, the functional analysis module automatically initiates the respiratory phase drift analysis command. First, the respiratory phase analysis unit performs data fitting on the fetal chest wall respiratory movement curve based on fetal physiological data to construct the respiratory phase drift index psh, which is used to reflect the phase shift of the fetus relative to a healthy baseline and potential physiological stress response.

[0096] The formula's logic, derivation basis, and significance aim to measure the degree of difference between the fetal thoracic respiratory movement rhythm and a healthy baseline state. br(k,t) represents the respiratory phase value of the k-th thoracic point at time t, reflecting the thoracic movement rhythm of the k-th thoracic point over time. br0(k) represents the standard respiratory phase value of the same thoracic point under healthy baseline conditions. The absolute value of the difference between the two represents the degree of deviation between actual breathing and baseline breathing. By averaging all thoracic points, local deviations are integrated into an overall indicator, reflecting whether there are any deviations or irregularities in the overall fetal respiratory movement. The formula is derived from an error function. In statistics and signal processing, the difference between two signal sequences is usually measured using mean absolute error and root mean square error. The physical meaning is based on the classic concept of periodic motion phase difference. The phase difference between different systems represents the deviation of the motion rhythm and is a commonly used measurement method for vibration and wave systems.

[0097] Subsequently, the risk analysis unit merges the amniotic sac thickness gradient index dyn with the respiratory phase drift index psh to construct a comprehensive labor risk index Rco. By using time accumulation and logarithmic function compression, the risk of persistent abnormalities is highlighted while maintaining the stability and interpretability of the results.

[0098] The formula, its logic, derivation basis, and significance are used to temporally couple the rate of amniotic membrane thinning with the degree of fetal respiratory abnormalities, forming a comprehensive risk quantification index. The amniotic sac thickness gradient index (dyn) represents the rate of change in the amniotic sac thickness gradient, reflecting whether structural stability is deteriorating; essentially, it reflects the local thinning trend of the amniotic sac over time. The respiratory phase drift index (psh) measures the phase shift between the fetal chest wall respiratory rhythm and a healthy baseline, serving as a quantitative expression of fetal physiological stress and reflecting the fetus's active response to changes in the amniotic sac environment. Multiplying these two indices represents the risk superposition effect when "structural thinning" and "respiratory abnormalities" occur simultaneously. Integrating this multiplication over time and averaging the results indicates the cumulative and persistent risk over the monitoring period, rather than just an anomaly at a single instant. Finally, a logarithmic function is used to compress extreme values, ensuring the risk index remains interpretable and stable even with severe abnormalities, avoiding conclusions based on isolated extreme values. The formula is derived from the classical form of time averaging. In physics and signal processing, the assessment of energy and power is often obtained by integrating the square or product of the signal. The product dyn(t)*psh(t) is essentially the "risk power" of structural and respiratory abnormalities. The integral of the product dyn(t)*psh(t) realizes the composite risk model of "structural dynamics multiplied by respiratory abnormalities", similar to the coupling meaning of cross power spectrum in physics. After integration, it is divided by the length of the monitoring period (T−t0) to avoid the influence of the monitoring duration on the results, making the results of short-term and long-term monitoring comparable. A logarithmic function is introduced into the results, drawing on the logarithmic compression mechanism in acoustic signal processing, to prevent the risk value from being infinitely amplified in extreme cases, and to maintain the interpretability and clinical applicability of the results.

[0099] The risk assessment unit uses historical data quantile thresholds to set critical thresholds for insufficient breathing (Gc) and hyperventilation (Go), and assesses the respiratory phase shift based on the real-time acquired comprehensive labor risk index (Rco), automatically generating corresponding intervention instructions for insufficient, stable, or hyperventilated breathing. Through the above implementation, this invention achieves synergistic analysis of amniotic sac thinning trends and fetal respiratory abnormalities, enabling early quantification of potential labor risks, improving the accuracy and timeliness of risk identification, and avoiding delays and misjudgments caused by traditional reliance on single imaging findings. This allows for refined management of pregnant women and fetuses and effective intervention for sudden risks during labor.

[0100] Example 5

[0101] Please refer to Figure 1 and Figure 2 Specifically: the instruction execution module is used to receive instruction information on respiratory phase shift assessment in real time, generate corresponding intervention information through the intelligent visualization midwifery system, and notify relevant medical personnel, as follows;

[0102] Insufficient breathing intervention instructions: administer oxygen to the pregnant woman to increase maternal blood oxygen partial pressure, administer intravenous drugs to inhibit uterine contractions to reduce uterine tension, and then perform iterative analysis through the structural analysis module. If the fetal respiratory phase is not stabilized after three iterations, proceed with the cesarean section plan.

[0103] Stable intervention instructions: Perform ultrasound scan and respiratory phase measurement every three hours;

[0104] Hyperactivity Intervention Instructions: Simultaneously initiate continuous fetal heart rate monitoring, provide psychological counseling to pregnant women to alleviate their anxiety, administer appropriate anti-uterine contraction drugs to pregnant women based on the medical basis of acute uterine depression, and then conduct iterative analysis through the structural analysis module. If the fetal respiratory phase is not stabilized after three iterations, proceed with the cesarean section plan.

[0105] In this embodiment, the instruction execution module, through real-time linkage with the respiratory phase shift assessment results, can promptly trigger oxygen administration and uterine contraction suppression interventions when fetal breathing is insufficient, simultaneously conduct fetal heart rate monitoring and psychological intervention when breathing is hyperactive, and quickly enter the cesarean section contingency plan when multiple iterative assessments are ineffective; when fetal breathing is stable, periodic ultrasound re-measures are maintained to ensure continuous dynamic tracking. This implementation achieves closed-loop control from risk identification to clinical intervention, avoiding the delays and uncertainties caused by relying solely on manual judgment in the past, and achieving the goal of automatically generating intervention plans and improving the safety of pregnant women and fetuses. Compared with the prior art, this invention not only improves the timeliness and scientific nature of risk management, but also significantly improves the accuracy and operability of clinical decision-making through a layered and progressive intervention strategy, thereby effectively reducing the risk of intrauterine stress and sudden delivery risks.

[0106] Example 6

[0107] Please refer to Figure 1 Specifically: the visualization module includes a multi-dimensional data mapping unit and a visualization display unit;

[0108] The multidimensional data mapping unit is used to map the amniotic sac thickness gradient index dyn, respiratory phase drift index psh, and comprehensive labor risk index Rco to the same time axis and coordinate system using dynamic time warping algorithm and coordinate index. It also uses bilinear interpolation technology to expand sparse coordinate points into a continuous two-dimensional heat map, maps the respiratory phase drift data of the fetal chest into a one-dimensional curve, and uses data overlay mapping technology to overlay the data into bottom, middle and top layers.

[0109] Bottom layer: Thermal distribution map of amniotic sac thickness gradient;

[0110] Middle layer: Respiratory phase drift curve;

[0111] Upper layer: Comprehensive labor risk curve;

[0112] The visualization unit is used to mark layers on the display interface based on the assessment results of amniotic sac structural stability assessment and respiratory phase shift assessment. The comprehensive labor risk curve segment with insufficient fetal respiratory movement is marked in orange, the comprehensive labor risk curve segment with stable fetal respiratory phase is marked in yellow, and the comprehensive labor risk curve segment with hyperactive fetal respiratory movement is marked in red. Clicking on the comprehensive labor risk curve enters the corresponding middle layer, which displays the respiratory phase drift curve and intuitively shows the corresponding rhythm fluctuations. Clicking on the respiratory phase drift curve again enters the bottom layer, where the stable areas of the amniotic sac structure are marked in green and the unstable areas of the amniotic sac structure are marked in blue.

[0113] In this embodiment, the visualization module, through the cooperation of the multidimensional data mapping unit and the visualization display unit, achieves unified mapping and layered display of the amniotic sac thickness gradient index (dyn), respiratory phase drift index (psh), and comprehensive labor risk index (Rco). The multidimensional data mapping unit employs a dynamic time warping algorithm and bilinear interpolation technology to expand sparse ultrasound sampling points into a continuous heatmap, and overlays and maps fetal respiratory phase data with the labor risk index into multi-layered curves, forming a multi-layered system of bottom, middle, and top layers. The visualization display unit uses color coding to classify different risk levels based on real-time assessment results and supports top-down, layer-by-layer click-through, from the risk curve to the respiratory curve and then to the bottom heatmap distribution, achieving dynamic linkage between structural and functional data. Through the above implementation, this invention not only enables medical personnel to intuitively observe the correspondence between fetal membrane structure stability and fetal respiratory rhythm but also achieves rapid identification and traceable analysis of risk levels. Compared with existing technologies that rely on experience to interpret single ultrasound images, this invention improves clinical interpretability and real-time performance, enhances the intuitiveness of risk warnings and the accuracy of intervention decisions, thereby significantly improving the safety level of the pregnancy and childbirth process.

[0114] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart visual midwifery system for obstetrics and gynecology based on ultrasound technology, characterized in that: It includes a signal acquisition module, a structural analysis module, a functional analysis module, an instruction execution module, and a visualization module; The signal acquisition module is used to perform a panoramic scan of the amniotic sac area of ​​the pregnant woman through an intelligent ultrasonic sensor array, determine the boundary of the amniotic sac and establish a two-dimensional rectangular coordinate system, and then obtain the total round-trip time of ultrasound at the coordinate point sj and the motion curve of the fetal chest based on the intelligent ultrasonic sensor array. After data analysis, the module performs dimensionless processing to obtain fetal membrane structure data and fetal physiological data. The structural analysis module is used to calculate the amniotic sac thickness gradient index dyn based on the fetal membrane structure data to evaluate the structural stability of the amniotic sac, and to trigger the functional analysis module when the structure is evaluated as unstable. The functional analysis module is used to calculate the respiratory phase drift index psh based on fetal physiological data, and fit it with the amniotic sac thickness gradient index dyn to construct a comprehensive labor risk index Rco for assessing respiratory phase shift. The instruction execution module is used to generate corresponding intervention information based on the respiratory phase shift assessment results; The visualization module is used to generate two-dimensional heat maps, one-dimensional curves, and comprehensive labor risk curves, and displays the layers in a layered manner on the display interface.

2. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 1, characterized in that: The signal acquisition module includes a coordinate construction unit and an ultrasonic signal acquisition unit; The coordinate construction unit includes a boundary calibration unit and a coordinate system generation unit; The boundary calibration unit is used to perform a panoramic scan of the pregnant woman's lower abdomen and the entire amniotic sac using an intelligent ultrasonic sensor array, capture echo signals from different angles, and transmit the echo signals to the intelligent visual midwifery system through a dedicated API interface. The echo signals are converted into initial image data of the amniotic sac and surrounding anatomical structures through image processing algorithms and recorded. Then, the spatial boundary of the amniotic sac is determined by the echo intensity edge detection algorithm, and the identified spatial boundary is converted into a point set to form a boundary frame. The coordinate system generation unit is used to establish a two-dimensional rectangular coordinate system within the calibrated boundary frame. The origin is fixed at the geometric center of the amniotic sac, the horizontal parallel direction of the mother body is set as the x-axis, the vertical parallel direction of the mother body is set as the y-axis, and grid points are generated at a fixed interval of 1mm. Each intersection point is set as a numberable coordinate point.

3. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 2, characterized in that: The ultrasonic signal acquisition unit includes a data acquisition unit and a data processing unit; The data acquisition unit is used to scan the amniotic sac of the pregnant woman based on the intelligent ultrasonic sensor array and record the total round-trip time sj of the echo at each coordinate point in the coordinate system in real time, and record the chest movement curve of the fetal chest displacement over time. The data processing unit is used to perform dimensionless processing on the total round-trip time sj of the echo, and then perform data analysis to obtain fetal membrane structure data and fetal physiological data. The dimensionless processing removes the dimensional influence of the state data using the Max-Min method. The data analysis includes amniotic sac thickness analysis and respiratory phase analysis; The amniotic sac thickness analysis is used to calculate the amniotic sac thickness hd(i,j) at sampling point (i,j) based on the sound velocity constant c of ultrasound propagation in the medium where the amniotic sac is located. Specifically: In the formula, sj(i,j) represents the total round-trip time of the echo at sampling point (i,j); The respiratory phase analysis is used to identify the zero-crossing point from negative to positive as the inspiratory start point xk, and the zero-crossing point from positive to negative as the expiratory start point, based on the thoracic motion curve after removing non-respiratory frequency components using a bandpass filter. The respiratory cycle length Tc is obtained by subtracting the inspiratory start point of the previous cycle from the current inspiratory start point. The respiratory phase value br is then calculated. Specifically: In the formula, π represents the constant value of pi, which is taken to two decimal places. The fetal membrane structure data includes the amniotic sac thickness hd(i,j); The fetal physiological data includes respiratory phase values ​​(br).

4. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 3, characterized in that: The structural analysis module includes a structural analysis unit and a structural evaluation unit; The structural analysis unit is used to fit the fetal membrane structure data, analyze the rate of change of the amniotic sac thickness gradient over time, and construct the amniotic sac thickness gradient index dyn based on the fetal membrane structure data to reflect the dynamics of amniotic sac thinning. The specific formula is as follows: In the formula, dyn(i,j) represents the rate of change of the amniotic sac thickness gradient at sampling point (i,j), and ∆t represents the continuous sampling time interval. and These represent the spatial variation rates of the amniotic sac thickness in the horizontal x-direction and the vertical y-direction, respectively.

5. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 4, characterized in that: The structural evaluation unit is used to sort the amniotic sac thickness gradient index dyn from smallest to largest within the past six months, preset the 50th percentile as the amniotic sac structural safety threshold Gd using the quantile method, and evaluate the amniotic sac structural stability with the real-time acquired amniotic sac thickness gradient index dyn. The specific evaluation scheme is as follows. When the amniotic sac thickness gradient exponent dyn < the amniotic sac structural safety threshold Gd, it indicates that the amniotic sac structure is stable and the amniotic sac thickness is within the normal range. At this time, normal monitoring should be maintained. When the amniotic sac thickness gradient exponent dyn is greater than or equal to the amniotic sac structural safety threshold Gd, it indicates that the amniotic sac structure is unstable and there is a local thinning trend in the amniotic sac thickness. At this time, the respiratory phase drift analysis command is executed.

6. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 5, characterized in that: The functional analysis module is used to execute respiratory phase drift analysis commands when the amniotic sac structure stability assessment indicates that the amniotic sac structure is unstable. Specifically, it includes a respiratory phase analysis unit and a risk analysis unit. The respiratory phase analysis unit is used to fit fetal physiological data, analyze the phase shift between the fetal chest respiratory movement rhythm and a healthy baseline, and construct a respiratory phase drift index (PSH) based on the fetal physiological data to reflect the fetal physiological stress response. The specific formula is as follows: In the formula, N represents the number of thoracic markers, br(k,t) represents the respiratory phase value of the k-th thoracic marker at time t, and br0(k) represents the reference healthy respiratory phase value under standard conditions.

7. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 6, characterized in that: The risk analysis unit includes a labor process risk analysis unit and a risk assessment unit; The labor risk analysis unit is used to comprehensively calculate the amniotic sac thickness gradient index dyn and the respiratory phase drift index psh to construct a comprehensive labor risk index Rco. This index is used for comprehensive decision analysis by integrating the dynamic thinning rate of the fused membrane structure with the degree of fetal respiratory phase abnormalities. The specific formula is as follows: In the formula, ln represents the logarithmic function, T represents the end time of the monitoring period, t0 represents the start time of the monitoring period, and dyn(t) and psh(t) represent the amniotic sac thickness gradient index and respiratory phase drift index at time t, respectively.

8. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 7, characterized in that: The risk assessment unit is used to sort the comprehensive labor risk index Rco from the past six months in ascending order, and to preset the 15th percentile as the critical threshold for insufficient respiratory phase Gc and the 85th percentile as the critical threshold for hyperspiratory respiratory phase Go using the quantile method. The unit is then compared with the real-time acquired comprehensive labor risk index Rco to assess respiratory phase shift. The specific assessment scheme is as follows. When the comprehensive labor risk index Rco is less than the critical threshold Gc for insufficient respiratory phase, it indicates that there is a shift in the fetal respiratory phase and insufficient fetal respiratory movement. At this time, an intervention instruction for insufficient breathing is generated. When the respiratory phase insufficiency threshold Gc ≤ comprehensive labor risk index Rco ≤ respiratory phase hyperactivity threshold Go, it indicates that the fetal respiratory phase is stable and there is no intrauterine stress response. At this time, a stable intervention instruction is generated. When the comprehensive labor risk index Rco is greater than the respiratory phase hyperactivity threshold Go, it indicates that the fetal respiratory phase is abnormal and the fetal respiratory movement is hyperactive. At this time, an intervention instruction for hyperactivity is generated.

9. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 8, characterized in that: The instruction execution module is used to receive instruction information on respiratory phase shift assessment in real time, generate corresponding intervention information through the intelligent visualization midwifery system, and notify relevant medical personnel, as follows; Insufficient breathing intervention instructions: administer oxygen to the pregnant woman to increase maternal blood oxygen partial pressure, administer intravenous drugs to inhibit uterine contractions to reduce uterine tension, and then perform iterative analysis through the structural analysis module. If the fetal respiratory phase is not stabilized after three iterations, proceed with the cesarean section plan. Stable intervention instructions: Perform ultrasound scan and respiratory phase measurement every three hours; Hyperactivity Intervention Instructions: Simultaneously initiate continuous fetal heart rate monitoring, provide psychological counseling to pregnant women to alleviate their anxiety, administer appropriate anti-uterine contraction drugs to pregnant women based on the medical basis of acute uterine depression, and then conduct iterative analysis through the structural analysis module. If the fetal respiratory phase is not stabilized after three iterations, proceed with the cesarean section plan.

10. The intelligent visual obstetric and gynecological midwifery system based on ultrasound technology according to claim 1, characterized in that: The visualization module includes a multidimensional data mapping unit and a visualization display unit; The multidimensional data mapping unit is used to map the amniotic sac thickness gradient index dyn, respiratory phase drift index psh, and comprehensive labor risk index Rco to the same time axis and coordinate system using dynamic time warping algorithm and coordinate index. It also uses bilinear interpolation technology to expand sparse coordinate points into a continuous two-dimensional heat map, maps the respiratory phase drift data of the fetal chest into a one-dimensional curve, and uses data overlay mapping technology to overlay the data into bottom, middle and top layers. Bottom layer: Thermal distribution map of amniotic sac thickness gradient; Middle layer: Respiratory phase drift curve; Upper layer: Comprehensive labor risk curve; The visualization unit is used to mark layers on the display interface based on the assessment results of amniotic sac structural stability assessment and respiratory phase shift assessment. The comprehensive labor risk curve segment with insufficient fetal respiratory movement is marked in orange, the comprehensive labor risk curve segment with stable fetal respiratory phase is marked in yellow, and the comprehensive labor risk curve segment with hyperactive fetal respiratory movement is marked in red. Clicking on the comprehensive labor risk curve enters the corresponding middle layer, which displays the respiratory phase drift curve and intuitively shows the corresponding rhythm fluctuations. Clicking on the respiratory phase drift curve again enters the bottom layer, where the stable areas of the amniotic sac structure are marked in green and the unstable areas of the amniotic sac structure are marked in blue.

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