Intelligent monitoring system for gynecological operation

Abstract

The invention relates to the technical field of medical monitoring, in particular to an intelligent monitoring system for gynecological surgery, which comprises a data acquisition module, an abnormal fusion decision module, an infection risk grading module, a pneumoperitoneum dynamic regulation and control module, a volume pressure collaboration module and an intelligent response execution module. Wherein the data acquisition module is used for acquiring multi-source data; the exception fusion decision module is used for carrying out multi-source data fusion and outputting a comprehensive exception evaluation result; the infection risk grading module is used for generating a real-time infection risk grade signal; the pneumoperitoneum dynamic regulation and control module is used for dynamically regulating the pressure change rate of the carbon dioxide pneumoperitoneum machine; and the volume pressure cooperation module is used for generating an optimized pneumoperitoneum pressure instruction. According to the invention, through multi-source data fusion and intelligent regulation and control, key physiological parameters in a gynecological operation are monitored and evaluated in real time, potential risks are accurately identified, and an operation strategy is automatically adjusted, so that the safety and the effect of the operation are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical monitoring, and in particular to an intelligent monitoring system for gynecological surgery. Background Art

[0002] With the increasing complexity of gynecological surgery and the continuous development of minimally invasive techniques, monitoring of patients' physiological parameters during surgery has become increasingly important. Traditional surgical monitoring systems mostly focus on monitoring a single indicator, mainly including basic physiological parameters such as blood pressure, heart rate, and oxygen saturation. However, during gynecological surgery, especially in laparoscopic surgery or robot-assisted surgery, organ displacement in the surgical area, changes in fluid permeability of surgical field tissues, and abnormal electromyographic signals may have a significant impact on the safety and effectiveness of the surgery.

[0003] Existing technologies mainly rely on traditional monitoring methods, which make it difficult to comprehensively and real-time monitor and evaluate multi-dimensional abnormal changes, especially in complex situations with dynamic changes during surgery, and it is difficult to accurately reflect the actual physiological state and potential risks during surgery. Therefore, how to accurately monitor and evaluate multi-source data during surgery and adjust surgical strategies in real time has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] Based on the above objectives, the present invention provides an intelligent monitoring system for gynecological surgery.

[0005] An intelligent monitoring system for gynecological surgery includes a data acquisition module, an abnormal fusion decision module, an infection risk classification module, a pneumoperitoneum dynamic control module, a volume pressure coordination module and an intelligent response execution module; wherein:

[0006] Data acquisition module: equipped with flexible array pressure sensors, miniature spectral analysis probes, and multi-band impedance detection electrodes, used to obtain pelvic organ displacement, surgical field tissue fluid permeability, and uterine myoelectric signals in real time;

[0007] Abnormal fusion decision module: receives pelvic organ displacement, surgical field tissue fluid permeability and uterine electromyographic signals, performs multi-source data fusion through improved DS evidence theory, and outputs comprehensive abnormal evaluation results including organ displacement abnormality, permeability mutation trend and electromyographic rhythm disorder index;

[0008] Infection risk grading module: inputs the comprehensive abnormality assessment results into the gynecology-specific infection dynamics model to generate a real-time infection risk level signal;

[0009] Pneumoperitoneum dynamic control module: used to dynamically adjust the pressure change rate of the carbon dioxide pneumoperitoneum machine according to the real-time infection risk level signal;

[0010] Volume-pressure coordination module: used to receive the pressure change rate parameters adjusted by the pneumoperitoneum dynamic control module, combine the real-time abdominal volume fluctuation data, and generate optimized pneumoperitoneum pressure instructions through the organ displacement-volume coupling algorithm, including the pressure baseline value, fluctuation tolerance range and emergency pressure relief trigger conditions;

[0011] Intelligent response execution module: used to synchronously execute multi-level response operations according to the real-time infection risk level signal when the permeability mutation trend in the comprehensive abnormal evaluation results exceeds the threshold of the current surgical stage.

[0012] Optionally, the data acquisition module includes a flexible array pressure sensor unit, a miniature spectral analysis probe unit and a multi-band impedance detection electrode unit; wherein:

[0013] Flexible array pressure sensing unit: It is composed of multiple flexible array pressure sensors, which are used to detect the pressure changes in the pelvic area in real time. Each sensor uses its pressure sensing chip to collect the tiny displacement of the pelvic organs during the operation, and then calculate the displacement of the pelvic organs;

[0014] Micro-spectral analysis probe unit: Using micro-spectral analysis technology, the probe can obtain the change data of the permeability of the surgical field tissue fluid in real time. The probe can identify the water content of the tissue fluid by monitoring the spectral characteristics reflected by the surface of the surgical field tissue, thereby calculating the permeability of the surgical field tissue fluid;

[0015] Multi-band impedance detection electrode unit: It is composed of multi-band impedance detection electrodes and is used to monitor uterine electromyographic signals in real time. By applying electrical signals and detecting reflected resistance, the electrodes can capture the electrical activity of the uterine muscles and obtain the timing data of the uterine electromyographic signals.

[0016] Optionally, the abnormal fusion decision module includes a data receiving unit, a multi-source data fusion unit and an abnormality evaluation unit; wherein:

[0017] Data receiving unit: used to receive real-time data of pelvic organ displacement, surgical field tissue fluid permeability and uterine myoelectric signal from the data acquisition module;

[0018] Multi-source data fusion unit: fuses the received multi-source data through the improved DS evidence theory to output the fused data;

[0019] Abnormality assessment unit: used to calculate the comprehensive abnormality assessment results including organ displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index based on the fused data.

[0020] Optionally, the abnormality evaluation unit specifically includes:

[0021] Calculating the abnormality of organ displacement: by comparing the difference between the current displacement of the pelvic organs and the preset normal displacement range, the abnormality Δd of the organ displacement is calculated;

[0022] Calculate the mutation trend of permeability: Analyze the change trend based on the time series data of the tissue fluid permeability in the surgical field and determine whether a mutation has occurred; determine whether a mutation has occurred by calculating the relative change rate between the current permeability and the permeability at the previous time point, and give the mutation degree ΔT;

[0023] Calculation of electromyographic rhythm disorder index: by analyzing the time series data of uterine electromyographic signals, the degree of electromyographic rhythm disorder ΔEMG was calculated;

[0024] Calculate the comprehensive abnormality assessment result: combine the above displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index to generate a comprehensive abnormality assessment result, which is specifically weighted calculated using the following formula: E=w1·Δd+w2·ΔT+w3·ΔEMG, where E is the comprehensive abnormality assessment result, and w1, w2, and w3 are the weight values ​​corresponding to the displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index, respectively.

[0025] Optionally, the infection risk grading module includes a comprehensive abnormality assessment result input unit and an infection risk assessment unit; wherein:

[0026] Comprehensive anomaly assessment result input unit: used to receive the comprehensive anomaly assessment result from the anomaly fusion decision module and transmit it to the infection risk assessment unit for processing;

[0027] Infection risk assessment unit: used to input the comprehensive abnormality assessment results into the gynecological-specific infection dynamics model, combined with the characteristics of pathogen diffusion in viscoelastic media, to calculate the real-time infection risk level signal.

[0028] Optionally, the infection risk assessment unit includes:

[0029] Analysis of pathogen diffusion characteristics in viscoelastic media: The viscoelastic characteristics of the surgical field tissue in the surgical area are modeled to analyze the spread trend of pathogens in the surgical field tissue; the expression of the pathogen diffusion coefficient is: Where D is the diffusion coefficient of the pathogen, k is the diffusion constant of the pathogen, η is the viscosity of the tissue, and τ is the strain time constant of the tissue;

[0030] Infection risk level generation: Based on the diffusion characteristics and combined with the comprehensive abnormality assessment results, the infection dynamics model is used to calculate the real-time infection risk index. The formula is: Among them, R infis the real-time infection risk index, between 0 and 1, Δd is the degree of organ displacement abnormality, ΔT is the mutation trend of surgical field tissue permeability, ΔEMG is the uterine myoelectric rhythm disorder index, D is the diffusion coefficient of the pathogen, and a, b, c, d are weight coefficients adjusted according to clinical experience;

[0031] The real-time risk index R inf Mapped into three levels of infection risk signals:

[0032] When R inf When <0.3, it is low risk;

[0033] When 0.3≤R inf <0.7, medium risk;

[0034] When R inf When ≥0.7, it is high risk.

[0035] Optionally, the pneumoperitoneum dynamic control module includes a real-time infection risk signal input unit and a pressure change rate adjustment unit; wherein:

[0036] Real-time infection risk signal input unit: used to receive real-time infection risk level signals from the infection risk grading module, including three-level signals of low risk, medium risk and high risk, and transmit the signals to the pneumoperitoneum control unit for processing;

[0037] Pressure change rate adjustment unit: used to adjust the pressure change rate of the carbon dioxide insufflator according to the real-time infection risk level signal;

[0038] When the real-time infection risk level signal shows medium risk, the pneumoperitoneum dynamic control module will start the step-by-step pressure compensation mechanism to gradually increase the pneumoperitoneum pressure;

[0039] When the real-time infection risk level signal shows a high risk, the pneumoperitoneum dynamic control module will trigger the pressure drop mechanism to reduce the pneumoperitoneum pressure.

[0040] Optionally, the volume pressure coordination module includes a real-time pneumoperitoneum volume data receiving unit, an organ displacement-volume coupling unit and an optimized pneumoperitoneum pressure instruction generating unit; wherein:

[0041] Real-time pneumoperitoneum volume data receiving unit: used to collect abdominal volume fluctuation data in real time and transmit it to the organ displacement-volume coupling algorithm unit for processing;

[0042] Organ displacement-volume coupling unit: Through the organ displacement-volume coupling algorithm, combined with the pelvic organ displacement data from the data acquisition module, the relationship between abdominal volume fluctuation and pelvic organ displacement is analyzed, and then the organ displacement-volume coupling model is established, and its expression is: Among them, V is the change in abdominal volume, Δd is the displacement of pelvic organs, and Δt is the change in time;

[0043] Optimized pneumoperitoneum pressure instruction generation unit: Based on the relationship between volume fluctuation and organ displacement, it generates optimized pneumoperitoneum pressure instructions, including pressure reference value, fluctuation tolerance range and emergency pressure relief trigger conditions.

[0044] Optionally, the optimizing pneumoperitoneum pressure instruction generating unit comprises:

[0045] Pressure reference value: According to the real-time volume change and pelvic organ displacement, the optimal pressure reference value is calculated. The formula is: P ref =P0+γ1·V+γ2·Δd, where, P ref is the optimized pressure reference value, P0 is the initial pneumoperitoneum pressure value, γ1 and γ2 are constants adjusted according to the tissue response during the actual operation, V is the change in abdominal volume, and Δd is the displacement of pelvic organs;

[0046] Fluctuation tolerance range: Calculate the fluctuation tolerance range based on the real-time volume change and pressure reference value. The formula is: ΔP tol =α·Δd+β·V, where ΔP tol is the fluctuation tolerance range, α and β are the preset adjustment coefficients, Δd is the displacement of pelvic organs, and V is the abdominal volume;

[0047] Emergency pressure relief trigger conditions: according to the current volume and pressure data, set the emergency pressure relief trigger conditions to trigger the emergency pressure relief mechanism when the pneumoperitoneum pressure exceeds the preset range;

[0048] Pressure trigger condition 1: P emergency =P current ≥P max ;

[0049] Pressure trigger condition 2: P current ≤P min , where P current is the current pneumoperitoneum pressure, P max is the maximum allowable pressure, P min is the minimum allowable pressure.

[0050] Optionally, the intelligent response execution module includes a threshold judgment unit and a multi-level response operation unit; wherein:

[0051] Threshold judgment unit: used to judge whether the permeability mutation trend in the comprehensive abnormality assessment result exceeds the threshold of the current surgical stage; if the permeability mutation trend exceeds the threshold of the current surgical stage, a trigger signal is sent to the multi-level response operation unit to instruct the execution of the corresponding response operation;

[0052] Multi-level response operation unit: used to perform the following multi-level response operations according to the real-time infection risk level signal and the degree of permeability mutation trend:

[0053] When the real-time infection risk level signal is low risk and the permeability mutation trend exceeds the threshold, the system will perform low-risk response operations, including activating the surgical field spectral marker to identify abnormal areas and generating organ displacement compensation suggestions;

[0054] When the real-time infection risk level signal is medium risk and the permeability mutation trend exceeds the threshold, the system will perform medium risk response operations, including starting the local pulse hemostasis device and adjusting the pressure fluctuation tolerance range;

[0055] When the real-time infection risk level signal is high risk and the permeability mutation trend exceeds the threshold, the system will perform high-risk response operations, including complete pressure relief operations and output a lesion isolation path planning map.

[0056] Beneficial effects of the present invention:

[0057] The present invention, through the coordinated work of multiple modules such as the data acquisition module, the abnormal fusion decision module, and the infection risk grading module, the system can obtain pelvic organ displacement, surgical field tissue fluid permeability and uterine myoelectric signals in real time, and accurately reflect the slight changes of organs and tissues during the operation; especially during the operation, the system can automatically evaluate and output comprehensive abnormality evaluation results, provide real-time warning for abnormal changes during the operation, and can perform precise dynamic adjustments according to the real-time infection risk level, thereby avoiding the occurrence of potential risks.

[0058] The present invention, through the intelligent response execution module, synchronously executes multi-level response operations for different risk levels, thereby effectively controlling pressure fluctuations during surgery, adjusting pneumoperitoneum pressure, and responding step by step to different risk levels; this intelligent control mechanism based on real-time monitoring and evaluation can significantly improve the safety and effectiveness of surgery, especially in complex surgical environments, reduce risk factors during surgery, and ensure the safety and smooth progress of patients' operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0060] Figure 1 A schematic diagram of an intelligent monitoring system for gynecological surgery according to an embodiment of the present invention;

[0061] Figure 2 Schematic diagram of an abnormal fusion decision module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0063] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0064] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0065] like Figure 1-Figure 2 As shown, an intelligent monitoring system for gynecological surgery includes a data acquisition module, an abnormal fusion decision module, an infection risk classification module, a pneumoperitoneum dynamic control module, a volume pressure coordination module and an intelligent response execution module; wherein:

[0066] Data acquisition module: equipped with flexible array pressure sensors, miniature spectral analysis probes, and multi-band impedance detection electrodes, used to obtain pelvic organ displacement, surgical field tissue fluid permeability, and uterine myoelectric signals in real time;

[0067] Abnormal fusion decision module: receives pelvic organ displacement, surgical field tissue fluid permeability and uterine electromyographic signals, performs multi-source data fusion through improved DS evidence theory, and outputs comprehensive abnormal evaluation results including organ displacement abnormality, permeability mutation trend and electromyographic rhythm disorder index;

[0068] Infection risk grading module: inputs the comprehensive abnormality assessment results into the gynecology-specific infection dynamics model to generate a real-time infection risk level signal;

[0069] Pneumoperitoneum dynamic control module: used to dynamically adjust the pressure change rate of the carbon dioxide pneumoperitoneum machine according to the real-time infection risk level signal;

[0070] Volume-pressure coordination module: used to receive the pressure change rate parameters adjusted by the pneumoperitoneum dynamic control module, combine the real-time abdominal volume fluctuation data, and generate optimized pneumoperitoneum pressure instructions through the organ displacement-volume coupling algorithm, including the pressure baseline value, fluctuation tolerance range and emergency pressure relief trigger conditions;

[0071] Intelligent response execution module: used to synchronously execute multi-level response operations according to the real-time infection risk level signal when the permeability mutation trend in the comprehensive abnormal evaluation results exceeds the threshold of the current surgical stage.

[0072] The data acquisition module includes a flexible array pressure sensor unit, a miniature spectral analysis probe unit, and a multi-band impedance detection electrode unit; wherein:

[0073] Flexible array pressure sensing unit: It is composed of multiple flexible array pressure sensors and is used to detect the pressure changes in the pelvic area in real time. Each sensor uses its pressure sensing chip to collect the tiny displacement of the pelvic organs during the operation and then calculate the displacement of the pelvic organs. The formula is: Among them, Δd is the displacement of pelvic organs, P i is the pressure value collected by the i-th sensor, S i is the sensitivity of the i-th sensor, n is the total number of sensors, and the displacement of the pelvic organs can be obtained by calculating the sum of the product of the pressure value and the sensitivity;

[0074] Micro-spectral analysis probe unit: Using micro-spectral analysis technology, the probe obtains the change data of the permeability of the surgical field tissue fluid in real time. The probe monitors the spectral characteristics reflected by the surface of the surgical field tissue, and can identify the water content of the tissue fluid, thereby calculating the permeability of the surgical field tissue fluid; the formula is: Wherein, T is the permeability of the surgical field tissue fluid, I0 is the initial reflected light intensity of the surgical field tissue surface, and I is the real-time light intensity reflected from the surgical field tissue surface. By comparing the changes in the reflected light intensity, the permeability of the surgical field tissue fluid can be calculated.

[0075] Multi-band impedance detection electrode unit: It is composed of multi-band impedance detection electrodes and is used to monitor uterine electromyographic signals in real time. By applying electrical signals and detecting reflected resistance, the electrodes can capture the electrical activity of the uterine muscles and obtain the timing data of uterine electromyographic signals. Through the coordinated work of the above units, the displacement of pelvic organs, the permeability of surgical field tissue fluid and uterine electromyographic signals can be comprehensively and accurately obtained, providing reliable data support for subsequent risk assessment and dynamic regulation.

[0076] The abnormal fusion decision module includes a data receiving unit, a multi-source data fusion unit and an abnormality evaluation unit; wherein:

[0077] Data receiving unit: used to receive real-time data of pelvic organ displacement, surgical field tissue fluid permeability and uterine myoelectric signal from the data acquisition module;

[0078] Multi-source data fusion unit: The received multi-source data are fused through the improved DS evidence theory. Specifically, the weighted average method is used to weight each input data source, and the results are corrected according to the credibility of each data source to output the fused data as the basic data for abnormal evaluation. Specifically, assuming that the input displacement data is D displacement , the permeability data is D permeability , the electromyographic signal data is D electromyography, The fused data is D fused , the formula is: Among them, w i is the weight value of the i-th data source, D i is the data of the ith data source (corresponding to displacement, permeability and electromyographic signal respectively);

[0079] Abnormality assessment unit: used to calculate the comprehensive abnormality assessment results including organ displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index based on the fused data; the above unit effectively integrates physiological data from different sources through the improved DS evidence theory, ensuring the accuracy and reliability of the data.

[0080] The abnormality assessment unit specifically includes:

[0081] Calculate the abnormal degree of organ displacement: By comparing the difference between the current displacement of the pelvic organs and the preset normal displacement range, calculate the abnormal degree of organ displacement Δd; the specific calculation formula is: Δd = |D current -D normal |, where Δd is the degree of organ displacement abnormality, D current is the displacement of the pelvic organs currently collected, D normal is the average value of the preset normal range;

[0082] Calculate the mutation trend of permeability: Analyze the change trend based on the time series data of the tissue fluid permeability in the surgical field and determine whether a mutation occurs. The calculation formula for the mutation trend of permeability is: Among them, ΔT is the permeability mutation trend, T current is the current tissue fluid permeability in the surgical field, T previs the permeability of the surgical field tissue fluid at the previous time point; by calculating the relative change rate between the current permeability and the permeability at the previous time point, it is determined whether a mutation occurs and the degree of mutation ΔT is given;

[0083] Calculation of electromyographic rhythm disorder index: By analyzing the time series data of uterine electromyographic signals, the degree of electromyographic rhythm disorder ΔEMG is calculated; the calculation formula is as follows: Among them, ΔEMG is the electromyographic rhythm disorder index, is the uterine myoelectric signal strength at the i-th sampling point, is the average value of all sampling point signals, and N is the total number of sampling points. By calculating the degree of deviation of the electromyographic signal, the degree of disorder of the electromyographic rhythm can be obtained.

[0084] Calculate the comprehensive abnormality assessment result: combine the above displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index to generate a comprehensive abnormality assessment result, which is specifically weighted calculated using the following formula: E=w1·Δd+w2·ΔT+w3·ΔEMG, where E is the comprehensive abnormality assessment result, and w1, w2, and w3 are the weight values ​​corresponding to the displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index, respectively; through a weighted method, the impact of different abnormalities is comprehensively evaluated to obtain a comprehensive abnormality assessment result for subsequent surgical adjustments and risk warnings.

[0085] The infection risk classification module includes a comprehensive abnormality assessment result input unit and an infection risk assessment unit; wherein:

[0086] Comprehensive abnormality assessment result input unit: used to receive the comprehensive abnormality assessment results from the abnormality fusion decision module, including organ displacement abnormality, permeability mutation trend and myoelectric rhythm disorder index, and transmit them to the infection risk assessment unit for processing;

[0087] Infection risk assessment unit: used to input the comprehensive abnormality assessment results into the gynecological-specific infection dynamics model, combined with the characteristics of pathogen diffusion in viscoelastic media, to calculate the real-time infection risk level signal.

[0088] The infection risk assessment unit includes:

[0089] Analysis of pathogen diffusion characteristics in viscoelastic media: The viscoelastic characteristics of the surgical field tissue in the surgical area are modeled to analyze the spread trend of pathogens in the surgical field tissue; the expression of the pathogen diffusion coefficient is: Where D is the diffusion coefficient of the pathogen, k is the diffusion constant of the pathogen, η is the viscosity of the tissue, and τ is the strain time constant of the tissue;

[0090] Infection risk level generation: Based on the diffusion characteristics and combined with the comprehensive abnormality assessment results, the infection dynamics model is used to calculate the real-time infection risk index. The formula is: Among them, R inf is the real-time infection risk index, between 0 and 1, Δd is the degree of organ displacement abnormality, ΔT is the mutation trend of surgical field tissue permeability, ΔEMG is the uterine myoelectric rhythm disorder index, D is the diffusion coefficient of the pathogen, and a, b, c, d are weight coefficients adjusted according to clinical experience;

[0091] The real-time risk index R inf Mapped into three levels of infection risk signals:

[0092] When R inf When <0.3, it is low risk;

[0093] When 0.3≤R inf <0.7, medium risk;

[0094] When R inf When ≥0.7, it is a high risk. The above-mentioned infection risk grading module adopts an infection dynamics model based on the diffusion characteristics of pathogens in viscoelastic media and multiple comprehensive abnormal evaluation results. It can generate high-precision infection risk level signals according to the actual situation of the surgical field tissue and abnormal conditions occurring during the operation, thereby achieving early warning of intraoperative infection risks.

[0095] The pneumoperitoneum dynamic control module includes a real-time infection risk signal input unit and a pressure change rate adjustment unit; wherein:

[0096] Real-time infection risk signal input unit: used to receive real-time infection risk level signals from the infection risk grading module, including three-level signals of low risk, medium risk and high risk, and transmit the signals to the pneumoperitoneum control unit for processing;

[0097] Pressure change rate adjustment unit: used to adjust the pressure change rate of the carbon dioxide insufflator according to the real-time infection risk level signal;

[0098] When the real-time infection risk level signal shows medium risk, the pneumoperitoneum dynamic control module will start the step-by-step pressure compensation mechanism to gradually increase the pneumoperitoneum pressure;

[0099] The operation when the stepped pressure compensation mechanism is activated is as follows:

[0100] First, a starting pressure value P0 is set according to the current pneumoperitoneum pressure, and the required pressure change rate ΔP is calculated. rate ;

[0101] Then, according to the preset rules of stroke risk level, a step-by-step pressure change method is selected, with each pressure increase being ΔPstep ,This increase value is gradually adjusted according to the tissue response during the actual surgery;

[0102] In this process, the specific value of each pressure increase is calculated by the following formula: Among them, P target is the target pneumoperitoneum pressure value, and n1 is the predetermined number of compensation steps, which ensures that the pneumoperitoneum pressure increases gradually to avoid sharp fluctuations.

[0103] When the real-time infection risk level signal shows a high risk, the pneumoperitoneum dynamic control module will trigger the pressure drop mechanism to reduce the pneumoperitoneum pressure;

[0104] The operation of triggering the pressure drop mechanism is as follows:

[0105] First, according to the high-risk warning output by the real-time infection risk level signal, the current pneumoperitoneum pressure and the target return pressure value P are calculated. target The difference ΔP;

[0106] According to the preset rules for high-risk levels, quickly reduce the pneumoperitoneum pressure to the target pressure value P target And reduce the pressure of the system through rapid pressure relief to avoid further aggravating the risk of surgical field infection;

[0107] The pressure drop rate ΔP calculated by the formula down for: Among them, P current is the current pneumoperitoneum pressure, P target T is the target pneumoperitoneum pressure value set for high risk. down is the time constant required for the return to normalcy; through the combination of the above units, a feedback mechanism for real-time infection risk level signals can be formed, and the rate of change of pneumoperitoneum pressure can be intelligently adjusted; for medium-risk situations, the pneumoperitoneum pressure is gradually adjusted through step-by-step pressure compensation to ensure the stability of the surgical field; in high-risk situations, the pneumoperitoneum pressure is quickly reduced through the pressure return mechanism to reduce the risk of infection; this mechanism can not only respond to real-time changes in infection risk, but also effectively optimize the regulation of pneumoperitoneum during surgery, ensure patient safety, and improve surgical efficiency and success rate.

[0108] The volume pressure coordination module includes a real-time pneumoperitoneum volume data receiving unit, an organ displacement-volume coupling unit, and an optimized pneumoperitoneum pressure instruction generating unit; wherein:

[0109] Real-time pneumoperitoneum volume data receiving unit: used to collect abdominal volume fluctuation data in real time and transmit it to the organ displacement-volume coupling algorithm unit for processing;

[0110] Organ displacement-volume coupling unit: Through the organ displacement-volume coupling algorithm, combined with the pelvic organ displacement data from the data acquisition module, the relationship between abdominal volume fluctuation and pelvic organ displacement is analyzed, and then the organ displacement-volume coupling model is established, and its expression is: Among them, V is the change in abdominal volume, Δd is the displacement of pelvic organs, and Δt is the time change. Through this model, the system can update the coupling relationship between abdominal volume and organ displacement in real time, and predict the future pneumoperitoneum pressure demand based on this relationship.

[0111] Optimized pneumoperitoneum pressure instruction generation unit: Based on the relationship between volume fluctuation and organ displacement, it generates optimized pneumoperitoneum pressure instructions, including pressure reference value, fluctuation tolerance range and emergency pressure relief trigger conditions.

[0112] The optimized pneumoperitoneum pressure instruction generating unit includes:

[0113] Pressure reference value: According to the real-time volume change and pelvic organ displacement, the optimal pressure reference value is calculated. The formula is: P ref =P0+γ1·V+γ2·Δd, where, P ref is the optimized pressure reference value, P0 is the initial pneumoperitoneum pressure value, γ1 and γ2 are constants adjusted according to the tissue response during the actual operation, V is the change in abdominal cavity volume, and Δd is the displacement of pelvic organs; this formula calculates the optimal pneumoperitoneum pressure reference value based on the actual changes in volume and displacement to ensure that the pneumoperitoneum pressure is maintained at a reasonable level;

[0114] Fluctuation tolerance range: Based on the real-time volume change and pressure reference value, the fluctuation tolerance range is calculated. This range is used to control the maximum allowable fluctuation of pneumoperitoneum pressure. The formula is: ΔP tol =α·Δd+β·V, where ΔP tol is the fluctuation tolerance range, α and β are the preset adjustment coefficients, Δd is the displacement of pelvic organs, and V is the abdominal cavity volume; through this formula, the system can determine the maximum and minimum tolerance values ​​of pneumoperitoneum pressure;

[0115] Emergency pressure relief trigger conditions: according to the current volume and pressure data, set the emergency pressure relief trigger conditions to trigger the emergency pressure relief mechanism when the pneumoperitoneum pressure exceeds the preset range;

[0116] Pressure trigger condition 1: P emergency =P current ≥P max ;

[0117] Pressure trigger condition 2: P current ≤P min , where P current is the current pneumoperitoneum pressure, P max is the maximum allowable pressure, Pmin is the minimum allowable pressure; when the current pneumoperitoneum pressure exceeds the maximum allowable pressure P max Or below the minimum allowable pressure P min When the pressure is too high, the system immediately triggers the pressure relief operation to prevent unsafe conditions during surgery. By generating the pressure reference value, fluctuation tolerance range and emergency pressure relief trigger conditions, the system can ensure the stability of the pneumoperitoneum pressure and avoid excessive fluctuations, thereby effectively reducing the risks that may occur during surgery.

[0118] The intelligent response execution module includes a threshold judgment unit and a multi-level response operation unit; wherein:

[0119] Threshold judgment unit: used to judge whether the permeability mutation trend in the comprehensive abnormality assessment result exceeds the threshold of the current surgical stage; if the permeability mutation trend exceeds the threshold of the current surgical stage, a trigger signal is sent to the multi-level response operation unit to instruct the execution of the corresponding response operation;

[0120] Multi-level response operation unit: used to perform the following multi-level response operations according to the real-time infection risk level signal and the degree of permeability mutation trend:

[0121] When the real-time infection risk level signal is low risk and the permeability mutation trend exceeds the threshold, the system will perform low-risk response operations, including activating the surgical field spectral marker to identify abnormal areas and generating organ displacement compensation suggestions;

[0122] When the real-time infection risk level signal is medium risk and the permeability mutation trend exceeds the threshold, the system will perform medium risk response operations, including starting the local pulse hemostasis device and adjusting the pressure fluctuation tolerance range;

[0123] When the real-time infection risk level signal is high risk and the permeability mutation trend exceeds the threshold, the system will execute high-risk response operations, including complete pressure relief operations and output lesion isolation path planning maps; through the above-mentioned unit intelligent response execution module, it can flexibly execute multi-level response operations according to the permeability mutation trend and real-time infection risk level signal in the comprehensive abnormal evaluation results; by automatically executing different levels of operations, such as activating spectral markers, starting hemostasis devices, adjusting pressure tolerance ranges, performing pressure relief operations, etc., it can effectively respond to abnormal situations that occur during surgery and ensure the safety and effectiveness of the surgery.

[0124] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0125] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An intelligent monitoring system for gynecological surgery, characterized in that: It includes data acquisition module, abnormal fusion decision module, infection risk classification module, pneumoperitoneum dynamic control module, volume pressure coordination module and intelligent response execution module; among which: Data acquisition module: equipped with flexible array pressure sensors, miniature spectral analysis probes, and multi-band impedance detection electrodes, used to obtain pelvic organ displacement, surgical field tissue fluid permeability, and uterine myoelectric signals in real time; Abnormal fusion decision module: receives pelvic organ displacement, surgical field tissue fluid permeability and uterine electromyographic signals, performs multi-source data fusion through improved DS evidence theory, and outputs comprehensive abnormal evaluation results including organ displacement abnormality, permeability mutation trend and electromyographic rhythm disorder index; Infection risk grading module: inputs the comprehensive abnormality assessment results into the gynecology-specific infection dynamics model to generate a real-time infection risk level signal; Pneumoperitoneum dynamic control module: used to dynamically adjust the pressure change rate of the carbon dioxide pneumoperitoneum machine according to the real-time infection risk level signal; Volume-pressure coordination module: used to receive the pressure change rate parameters adjusted by the pneumoperitoneum dynamic control module, combine the real-time abdominal volume fluctuation data, and generate optimized pneumoperitoneum pressure instructions through the organ displacement-volume coupling algorithm, including the pressure baseline value, fluctuation tolerance range and emergency pressure relief trigger conditions; Intelligent response execution module: used to synchronously execute multi-level response operations according to the real-time infection risk level signal when the permeability mutation trend in the comprehensive abnormal evaluation results exceeds the threshold of the current surgical stage.

2. The intelligent monitoring system for gynecological surgery according to claim 1, characterized in that: The data acquisition module includes a flexible array pressure sensor unit, a micro-spectral analysis probe unit and a multi-band impedance detection electrode unit; wherein: Flexible array pressure sensing unit: It is composed of multiple flexible array pressure sensors, which are used to detect the pressure changes in the pelvic area in real time. Each sensor uses its pressure sensing chip to collect the tiny displacement of the pelvic organs during the operation, and then calculate the displacement of the pelvic organs; Micro-spectral analysis probe unit: Using micro-spectral analysis technology, the probe can obtain the change data of the permeability of the surgical field tissue fluid in real time. The probe can identify the water content of the tissue fluid by monitoring the spectral characteristics reflected by the surface of the surgical field tissue, thereby calculating the permeability of the surgical field tissue fluid; Multi-band impedance detection electrode unit: It is composed of multi-band impedance detection electrodes and is used to monitor uterine electromyographic signals in real time. By applying electrical signals and detecting reflected resistance, the electrodes can capture the electrical activity of the uterine muscles and obtain the timing data of the uterine electromyographic signals.

3. The intelligent monitoring system for gynecological surgery according to claim 1, characterized in that: The abnormal fusion decision module includes a data receiving unit, a multi-source data fusion unit and an abnormality evaluation unit; wherein: Data receiving unit: used to receive real-time data of pelvic organ displacement, surgical field tissue fluid permeability and uterine myoelectric signal from the data acquisition module; Multi-source data fusion unit: fuses the received multi-source data through the improved DS evidence theory to output the fused data; Abnormality assessment unit: used to calculate the comprehensive abnormality assessment results including organ displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index based on the fused data.

4. The intelligent monitoring system for gynecological surgery according to claim 3, characterized in that: The abnormality evaluation unit specifically includes: Calculating the abnormality of organ displacement: by comparing the difference between the current displacement of the pelvic organs and the preset normal displacement range, the abnormality Δd of the organ displacement is calculated; Calculate the mutation trend of permeability: Analyze the change trend based on the time series data of the tissue fluid permeability in the surgical field and determine whether a mutation has occurred; determine whether a mutation has occurred by calculating the relative change rate between the current permeability and the permeability at the previous time point, and give the mutation degree ΔT; Calculation of electromyographic rhythm disorder index: by analyzing the time series data of uterine electromyographic signals, the degree of electromyographic rhythm disorder ΔEMG was calculated; Calculate the comprehensive abnormality assessment result: combine the above displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index to generate a comprehensive abnormality assessment result, which is specifically weighted calculated using the following formula: E=w1·Δd+w2·ΔT+w3·ΔEMG, where E is the comprehensive abnormality assessment result, and w1, w2, and w3 are the weight values ​​corresponding to the displacement abnormality, permeability mutation trend, and electromyographic rhythm disorder index, respectively.

5. The intelligent monitoring system for gynecological surgery according to claim 1, characterized in that: The infection risk grading module includes a comprehensive abnormality assessment result input unit and an infection risk assessment unit; wherein: Comprehensive anomaly assessment result input unit: used to receive the comprehensive anomaly assessment result from the anomaly fusion decision module and transmit it to the infection risk assessment unit for processing; Infection risk assessment unit: used to input the comprehensive abnormality assessment results into the gynecological-specific infection dynamics model, combined with the characteristics of pathogen diffusion in viscoelastic media, to calculate the real-time infection risk level signal.

6. The intelligent monitoring system for gynecological surgery according to claim 5, characterized in that: The infection risk assessment unit comprises: Analysis of pathogen diffusion characteristics in viscoelastic media: The viscoelastic characteristics of the surgical field tissue in the surgical area are modeled to analyze the spread trend of pathogens in the surgical field tissue; the expression of the pathogen diffusion coefficient is: Where D is the diffusion coefficient of the pathogen, k is the diffusion constant of the pathogen, η is the viscosity of the tissue, and τ is the strain time constant of the tissue; Infection risk level generation: Based on the diffusion characteristics and combined with the comprehensive abnormality assessment results, the infection dynamics model is used to calculate the real-time infection risk index. The formula is: Among them, R inf is the real-time infection risk index, between 0 and 1, Δd is the degree of organ displacement abnormality, ΔT is the mutation trend of surgical field tissue permeability, ΔEMG is the uterine myoelectric rhythm disorder index, D is the diffusion coefficient of the pathogen, and a, b, c, d are weight coefficients adjusted according to clinical experience; The real-time risk index R inf Mapped into three levels of infection risk signals: When R inf When <0.3, it is low risk; When 0.3≤R inf <0.7, medium risk; When R inf When ≥0.7, it is high risk.

7. The intelligent monitoring system for gynecological surgery according to claim 1, characterized in that: The pneumoperitoneum dynamic control module includes a real-time infection risk signal input unit and a pressure change rate adjustment unit; wherein: Real-time infection risk signal input unit: used to receive real-time infection risk level signals from the infection risk grading module, including three-level signals of low risk, medium risk and high risk, and transmit the signals to the pneumoperitoneum control unit for processing; Pressure change rate adjustment unit: used to adjust the pressure change rate of the carbon dioxide insufflator according to the real-time infection risk level signal; When the real-time infection risk level signal shows medium risk, the pneumoperitoneum dynamic control module will start the step-by-step pressure compensation mechanism to gradually increase the pneumoperitoneum pressure; When the real-time infection risk level signal shows a high risk, the pneumoperitoneum dynamic control module will trigger the pressure drop mechanism to reduce the pneumoperitoneum pressure.

8. The intelligent monitoring system for gynecological surgery according to claim 1, characterized in that: The volume pressure coordination module includes a real-time pneumoperitoneum volume data receiving unit, an organ displacement-volume coupling unit and an optimized pneumoperitoneum pressure instruction generating unit; wherein: Real-time pneumoperitoneum volume data receiving unit: used to collect abdominal volume fluctuation data in real time and transmit it to the organ displacement-volume coupling algorithm unit for processing; Organ displacement-volume coupling unit: Through the organ displacement-volume coupling algorithm, combined with the pelvic organ displacement data from the data acquisition module, the relationship between abdominal volume fluctuation and pelvic organ displacement is analyzed, and then the organ displacement-volume coupling model is established, and its expression is: Among them, V is the change in abdominal volume, Δd is the displacement of pelvic organs, and Δt is the change in time; Optimized pneumoperitoneum pressure instruction generation unit: Based on the relationship between volume fluctuation and organ displacement, it generates optimized pneumoperitoneum pressure instructions, including pressure reference value, fluctuation tolerance range and emergency pressure relief trigger conditions.

9. The intelligent monitoring system for gynecological surgery according to claim 8, characterized in that: The optimized pneumoperitoneum pressure instruction generating unit comprises: Pressure reference value: According to the real-time volume change and pelvic organ displacement, the optimal pressure reference value is calculated. The formula is: P ref =P0+γ1·V+γ2·Δd, where, P ref is the optimized pressure reference value, P0 is the initial pneumoperitoneum pressure value, γ1 and γ2 are constants adjusted according to the tissue response during the actual operation, V is the change in abdominal volume, and Δd is the displacement of pelvic organs; Fluctuation tolerance range: Calculate the fluctuation tolerance range based on the real-time volume change and pressure reference value. The formula is: ΔP tol =α·Δd+β·V, where ΔP tol is the fluctuation tolerance range, α and β are the preset adjustment coefficients, Δd is the displacement of pelvic organs, and V is the abdominal volume; Emergency pressure relief trigger conditions: according to the current volume and pressure data, set the emergency pressure relief trigger conditions to trigger the emergency pressure relief mechanism when the pneumoperitoneum pressure exceeds the preset range; Pressure trigger condition 1: P emergency =P current ≥P max ; Pressure trigger condition 2: P current ≤P min , where P current is the current pneumoperitoneum pressure, P max is the maximum allowable pressure, P min is the minimum allowable pressure.

10. The intelligent monitoring system for gynecological surgery according to claim 1, characterized in that: The intelligent response execution module includes a threshold judgment unit and a multi-level response operation unit; wherein: Threshold judgment unit: used to judge whether the permeability mutation trend in the comprehensive abnormality assessment result exceeds the threshold of the current surgical stage; if the permeability mutation trend exceeds the threshold of the current surgical stage, a trigger signal is sent to the multi-level response operation unit to instruct the execution of the corresponding response operation; Multi-level response operation unit: used to perform the following multi-level response operations according to the real-time infection risk level signal and the degree of permeability mutation trend: When the real-time infection risk level signal is low risk and the permeability mutation trend exceeds the threshold, the system will perform low-risk response operations, including activating the surgical field spectral marker to identify abnormal areas and generating organ displacement compensation suggestions; When the real-time infection risk level signal is medium risk and the permeability mutation trend exceeds the threshold, the system will execute medium risk level response operations, including starting the local pulse hemostasis device and adjusting the pressure fluctuation tolerance range; When the real-time infection risk level signal is high risk and the permeability mutation trend exceeds the threshold, the system will perform high-risk response operations, including complete pressure relief operations and output a lesion isolation path planning map.

Images