An anorectal surgery postoperative nursing rehabilitation evaluation method and system

Abstract

The present application provides a method and system for postoperative nursing rehabilitation assessment in anorectal surgery. Among them, a vibration sensor is constructed through machine tool processing vibration monitoring technology to detect the vibration frequency offset after the dressing absorbs wound exudate in real time and correlate it with the dressing weight change; at the same time, optical scattering measurement technology is used to perform scattering spectrum analysis on the wound exudate to analyze the protein concentration index. The weight change data corresponding to the vibration frequency offset is correlated with the protein concentration index in time series to generate a dynamic change curve of the exudate composition. Through the wireless transmission unit in the telemetry system, the dynamic change curve is remotely synchronously compared with the preset reference curve of the healing stage. When there are continuous vibration frequency offsets exceeding the standard exudate volume and the protein concentration index breaks through the threshold range in the curve, a remote warning signal for abnormal wound healing is triggered. The technical solution provided by the present application improves the efficiency and accuracy of nursing rehabilitation.

Description

Technical Field

[0001] This application relates to the field of medical monitoring technologies, and particularly to a method and system for evaluating the postoperative nursing and rehabilitation of anorectal surgery. Background Art

[0002] The postoperative wound care in anorectal surgery is a key link in the rehabilitation process. The amount and compositional changes of postoperative wound exudate directly reflect the healing status. Traditional nursing relies on regular observation of the wetting condition of dressings and the subjective feedback of patients, making it difficult to achieve accurate and real-time quantitative assessment.

[0003] Currently, there are wound exudate monitoring schemes based on single sensing technologies. For example, pressure sensors or optical sensors are used alone to detect the amount or composition of exudate.

[0004] Existing schemes mainly rely on single sensing technologies and can only obtain single-dimensional information of wound exudate (such as the amount or composition of exudate), unable to simultaneously take into account the dynamic changes of physical and biochemical properties. For example, although fiber optic sensors can detect the composition of exudate, they cannot accurately reflect the changing trend of the exudate amount, resulting in a lack of comprehensiveness in the evaluation results. In addition, single sensing technologies are difficult to cope with the influence of complex wound environments (such as changes in exudate viscosity, uneven dressing absorption, etc.) on the detection accuracy, limiting their practical application value in clinical practice. Summary of the Invention

[0005] The embodiments of this application provide a method and system for evaluating the postoperative nursing and rehabilitation of anorectal surgery to solve the problems of low nursing and rehabilitation efficiency and low accuracy in the existing technology.

[0006] In a first aspect, the embodiments of this application provide a method for evaluating the postoperative nursing and rehabilitation of anorectal surgery, including:

[0007] Construct a vibration sensor based on machine tool processing vibration monitoring technology, and use the vibration sensor to detect the vibration frequency offset in real time after the dressing absorbs the wound exudate. The vibration frequency offset is associated with the change in dressing weight;

[0008] Perform scattering spectrum analysis on the wound exudate using optical scattering measurement technology. The scattering spectrum analysis resolves the protein concentration index through the scattering angle distribution of incident light in the exudate;

[0009] Perform time series association on the weight change data corresponding to the vibration frequency offset and the protein concentration index to generate a dynamic change curve of exudate composition;

[0010] Through the wireless transmission unit in the telemetry system, remotely synchronously compare the dynamic change curve of exudate composition with a preset reference curve for the healing stage. The reference curve for the healing stage includes the standard exudate amount and the protein threshold range for different rehabilitation stages;

[0011] When there are consecutive vibration frequency offsets exceeding the standard exudate volume in the dynamic change curve of the exudate components, and it is synchronously detected that the protein concentration index breaks through the protein threshold range, a remote warning signal for abnormal wound healing is triggered.

[0012] Optionally, the weight change data corresponding to the vibration frequency offset and the protein concentration index are associated in time series to generate a dynamic change curve of exudate components, including:

[0013] Based on the continuous sampling timestamps of the vibration sensor, dynamic window partitioning is performed on the weight change data, and the time span of the dynamic window is adaptively adjusted according to the discrete sampling interval of the protein concentration index;

[0014] The periodic fluctuation characteristics of the vibration frequency offset are extracted within the dynamic window, and the periodic fluctuation characteristics are associated with the capillary penetration rate of the dressing absorbing exudate;

[0015] By establishing the correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, the periodic fluctuation characteristics are coupled and analyzed with the change amount of the scattering angle distribution of the protein concentration index within the corresponding window;

[0016] According to the exudate viscosity characteristics at different postoperative healing stages, a dynamic weight factor is applied to the correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, and the dynamic weight factor is non-linearly adjusted according to the preset exudate component change threshold;

[0017] By iteratively updating the dynamic weight factor and the time span of the dynamic window, a dynamic change curve of exudate components with time resolution is generated, and each data node in the dynamic change curve of exudate components contains dual characteristic parameters of vibration dimension and optical dimension.

[0018] Optionally, by establishing the correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, the periodic fluctuation characteristics are coupled and analyzed with the change amount of the scattering angle distribution of the protein concentration index within the corresponding window, including:

[0019] The phase angle interval of the vibration waveform zero-crossing is extracted from the periodic fluctuation characteristics of the vibration frequency offset, and the phase angle interval covers the vibration period when the liquid infiltration reaches the saturation critical point during the dressing absorbing exudate;

[0020] Based on the change amount of the scattering angle distribution, the attenuation rate ratio of the backward scattered light intensity to the lateral scattered light intensity per unit time is calculated, and the attenuation rate ratio reflects the change in scattering anisotropy caused by the protein aggregation state;

[0021] Divide multiple groups of mapping rules according to the ratio difference between fibrinogen and albumin in the postoperative exudate, and construct an association mapping table of the liquid infiltration saturation degree and the ratio of the attenuation rate within the phase angle interval;

[0022] Dynamically adjust the matching threshold of the phase angle interval and the ratio of the attenuation rate according to the relationship curve between the viscosity of the exudate and the protein concentration preset for the current healing stage, and introduce a liquid viscosity compensation coefficient within the dynamic window;

[0023] Based on the combined action of the association mapping table and the liquid viscosity compensation coefficient, generate a coupling parameter characterizing the coordinated changes of the physical penetration and biochemical components of the exudate.

[0024] Optionally, dividing multiple groups of mapping rules according to the ratio difference between fibrinogen and albumin in the postoperative exudate, and constructing an association mapping table of the liquid infiltration saturation degree and the ratio of the attenuation rate within the phase angle interval, includes:

[0025] Obtain the baseline ratio of fibrinogen to albumin based on the preoperative blood test results. The baseline ratio is used as the initial reference value for mapping rule division and is dynamically adjusted according to the product relationship between the dressing absorption capacity and the exudate viscosity, and divide the grading threshold of the liquid infiltration saturation degree within the phase angle interval;

[0026] Divide the protein aggregation state levels based on the change trend of the ratio of the attenuation rate. The protein aggregation state levels are associated with the ratio offset of fibrinogen and albumin;

[0027] According to the difference range between the baseline ratio and the ratio offset, divide the combined relationship between the liquid infiltration saturation degree grading threshold and the protein aggregation state levels into multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage;

[0028] Through the collaborative analysis of the vibration energy integral value and the scattering light intensity attenuation slope within the phase angle interval, establish a cross-validation mechanism for the liquid infiltration saturation degree grading threshold and the protein aggregation state levels. Based on the multiple groups of mapping rules and the cross-validation mechanism, generate the association mapping table of the liquid infiltration saturation degree and the ratio of the attenuation rate within the phase angle interval.

[0029] Optionally, according to the difference range between the baseline ratio and the ratio offset, divide the combined relationship between the liquid infiltration saturation degree grading threshold and the protein aggregation state levels into multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage, including:

[0030] Based on the difference range between the baseline ratio and the ratio offset, determine the change trend of the ratio of fibrinogen to albumin;

[0031] Define the critical points of the grading thresholds for low, medium, and high saturation levels of the liquid infiltration saturation based on the product relationship between the dressing absorption capacity and the exudate viscosity, and define the threshold ranges for the protein aggregation state levels of low, medium, and high aggregation based on the changing trend of the attenuation rate ratio;

[0032] Match the changing trend of the ratio with the critical points to generate a first-level mapping relationship, and combine the first-level mapping relationship with the threshold ranges to generate a second-level mapping relationship;

[0033] Based on the superposition of the first-level mapping relationship and the second-level mapping relationship, divide multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage.

[0034] Optionally, perform scattering spectrum analysis on the wound exudate using optical scattering measurement technology, including:

[0035] Based on the scattering angle distribution of the incident light in the wound exudate, obtain the light intensity data of multiple characteristic scattering angles, and the characteristic scattering angles include the forward scattering angle, the lateral scattering angle, and the backward scattering angle;

[0036] According to the light intensity data of the characteristic scattering angles, calculate the anisotropy coefficient of the scattered light intensity distribution, and the anisotropy coefficient reflects the spatial distribution characteristics of the protein aggregation state in the exudate;

[0037] Based on the changing trend of the anisotropy coefficient, determine the dynamic change range of the protein concentration index;

[0038] Through the collaborative analysis of the light intensity data of the characteristic scattering angles and the anisotropy coefficient, generate the scattering spectrum analysis result, and the scattering spectrum analysis result is used to characterize the biochemical component characteristics of the wound exudate.

[0039] Optionally, according to the light intensity data of the characteristic scattering angles, calculate the anisotropy coefficient of the scattered light intensity distribution, including:

[0040] Based on the light intensity data of the forward scattering angle and the backward scattering angle of the characteristic scattering angles, extract the ratio of the forward scattered light intensity to the backward scattered light intensity to generate the longitudinal anisotropy coefficient;

[0041] Based on the light intensity data of the lateral scattering angle and the backward scattering angle of the characteristic scattering angles, extract the ratio of the lateral scattered light intensity to the backward scattered light intensity to generate the transverse anisotropy coefficient; <{

[0042] According to the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient, extract the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient to generate the comprehensive anisotropy coefficient;

[0043] By means of the collaborative analysis of the longitudinal anisotropy coefficient, the transverse anisotropy coefficient, and the comprehensive anisotropy coefficient, the anisotropy coefficient of the scattered light intensity distribution is determined.

[0044] In a second aspect, an embodiment of the present application provides a postoperative nursing and rehabilitation evaluation system for anorectal surgery, including:

[0045] A vibration frequency offset detection module, configured to construct a vibration sensor based on machine tool processing vibration monitoring technology, and to detect in real time the vibration frequency offset amount after the dressing absorbs wound exudate through the vibration sensor, where the vibration frequency offset amount is associated with the dressing weight change amount;

[0046] An exudate component optical analysis module, configured to perform scattering spectrum analysis on the wound exudate by using optical scattering measurement technology, where the scattering spectrum analysis analyzes the protein concentration index through the scattering angle distribution of incident light in the exudate;

[0047] An exudate dynamic data fusion module, configured to perform time series association on the weight change data corresponding to the vibration frequency offset amount and the protein concentration index to generate a dynamic change curve of the exudate component;

[0048] A wireless remote monitoring and warning module, configured to remotely synchronously compare the dynamic change curve of the exudate component with a preset reference curve of the healing stage through a wireless transmission unit in a telemetry system, where the reference curve of the healing stage includes the standard exudate volume and the protein threshold range in different rehabilitation stages;

[0049] A healing stage curve management module, configured to trigger a remote warning signal for abnormal wound healing when the vibration frequency offset amount exceeding the standard exudate volume continuously appears in the dynamic change curve of the exudate component and the protein concentration index is detected to break through the protein threshold range synchronously.

[0050] In a third aspect, an embodiment of the present application provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a postoperative nursing and rehabilitation evaluation method for anorectal surgery as described in the first aspect above.

[0051] In a fourth aspect, an embodiment of the present application provides a computer storage medium, storing a computer program, where when the computer program is executed by a computer, it implements a postoperative nursing and rehabilitation evaluation method for anorectal surgery as described in the first aspect.

[0052] In the embodiments of the present application, a vibration sensor is constructed based on the machine tool processing vibration monitoring technology. The vibration frequency offset amount after the dressing absorbs the wound exudate is detected in real time by the vibration sensor, and the vibration frequency offset amount is associated with the dressing weight change amount. The optical scattering measurement technology is used to perform scattering spectrum analysis on the wound exudate, and the scattering spectrum analysis analyzes the protein concentration index through the scattering angle distribution of the incident light in the exudate. The weight change data corresponding to the vibration frequency offset amount is time-sequentially associated with the protein concentration index to generate a dynamic change curve of the exudate composition. Through the wireless transmission unit in the telemetry system, the dynamic change curve of the exudate composition is remotely synchronously compared with a preset reference curve of the healing stage, and the reference curve of the healing stage includes the standard exudate volume and the protein threshold range in different rehabilitation stages. When the vibration frequency offset amount exceeding the standard exudate volume continuously appears in the dynamic change curve of the exudate composition, and the protein concentration index is detected to break through the protein threshold range synchronously, a remote warning signal for abnormal wound healing is triggered.

[0053] The technical solution of the present application has the following beneficial effects:

[0054] The weight change of the dressing absorbing exudate is quantified in real time through the vibration frequency offset amount, realizing high-precision dynamic monitoring of the exudate volume. The protein concentration in the exudate is analyzed through the scattering angle distribution, providing the ability to monitor biochemical components in real time. The dynamic change curves of the physical and biochemical characteristics of the exudate are generated through time-sequential association, realizing the fusion analysis of multi-dimensional data. Remote real-time comparison is realized, providing a quantitative evaluation basis for the healing progress for medical staff. Through the joint judgment of multiple parameters, the warning of abnormal healing is accurately triggered, improving the timeliness of nursing intervention.

[0055] Furthermore, based on the continuous sampling timestamps of the vibration sensor, the weight change data is dynamically windowed, and the window time span is adaptively adjusted. The periodic fluctuation characteristics of the vibration frequency offset amount are extracted within the window, and coupling analysis is performed in combination with the relationship between the vibration phase angle and the scattering light intensity attenuation rate. According to the viscosity characteristics of the postoperative exudate, the weight factor is dynamically adjusted, and finally a dynamic change curve of the exudate composition containing dual characteristic parameters of vibration dimension and optical dimension is generated.

[0056] Through the above method, the efficient fusion of vibration data and optical data is realized, and a dynamic change curve of the exudate composition with time resolution is generated. This curve contains dual characteristic parameters of physical characteristics (vibration dimension) and biochemical characteristics (optical dimension) at the same time, providing more comprehensive and accurate data support for the evaluation of postoperative wound healing.

[0057] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. Description of the Drawings

[0058] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0059] Figure 1 It shows a flowchart of a postoperative nursing and rehabilitation evaluation method for anorectal surgery provided by the present application;

[0060] Figure 2 It shows a schematic structural diagram of a postoperative nursing and rehabilitation evaluation system for anorectal surgery provided by the present application;

[0061] Figure 3 It shows a schematic structural diagram of a computing device provided by the present application. Detailed implementation manners

[0062] In order to enable those skilled in the art to better understand the solutions of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application.

[0063] In some processes described in the specification and claims of the present application and the above drawings, there are multiple operations that appear in a specific order. However, it should be clearly understood that these operations can be executed not in the order in which they appear in this article or in parallel. The operation numbers such as 101 and 102 are only used to distinguish different operations, and the numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations can be executed in sequence or in parallel. It should be noted that the descriptions such as "first" and "second" in this article are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, nor do they limit that "first" and "second" are of different types.

[0064] The R & D idea of the present application is based on cross - field technology integration. The machine tool processing vibration monitoring technology is transformed into a vibration sensor to be used for real - time detection of the vibration frequency offset after the dressing absorbs the wound exudate, so as to quantify the change in exudate weight. At the same time, the optical scattering measurement technology is introduced. By analyzing the scattering angle distribution of the incident light in the exudate, the protein concentration index is analyzed to realize the dynamic monitoring of biochemical components. By correlating the vibration frequency offset and the protein concentration index in time series, a dynamic change curve of exudate components is generated, and combined with the telemetry system, remote synchronous comparison and early warning are realized. Finally, through multi - parameter joint judgment (exudate volume and protein concentration), a remote early warning signal for abnormal wound healing is accurately triggered, providing an intelligent and precise evaluation means for postoperative nursing.

[0065] Next, in combination with the accompanying drawings in the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0066] Figure 1 The present application provides a flowchart of a method for postoperative nursing rehabilitation assessment in anorectal surgery. As Figure 1 shown, the method includes:

[0067] 101. Construct a vibration sensor based on machine tool processing vibration monitoring technology, and use the vibration sensor to detect the vibration frequency offset after the dressing absorbs wound exudate in real time. The vibration frequency offset is associated with the change in dressing weight;

[0068] In this step, the vibration frequency offset refers to the offset value of the mechanical vibration frequency relative to the dry state caused by the change in weight after the dressing absorbs exudate, which is detected by the vibration sensor and is positively correlated with the change in dressing weight.

[0069] In the embodiments of the present application, an industrial-grade vibration sensor is modified based on machine tool processing vibration monitoring technology. The dressing vibration signal is collected by a piezoelectric ceramic element, the fundamental frequency component is extracted by using the fast Fourier transform (FFT), and the frequency difference between the wet state and the dry state is calculated as the vibration frequency offset. A linear relationship between the offset and the change in weight is established through a calibration experiment (such as a 1 ml increase in exudate volume corresponding to a 10 Hz decrease in frequency), and finally the real-time quantitative monitoring of the exudate volume is achieved.

[0070] In an actual case, in the postoperative care of patients, the vibration sensor is embedded in the bottom layer of the intelligent dressing. When the exudate is absorbed, the increase in the dressing weight causes the vibration frequency to decrease. For example, the initial fundamental frequency in the dry state is 500 Hz, and the frequency drops to 450 Hz after absorbing 5 ml of exudate. The system displays the exudate volume in real time through a preset linear relationship (50 Hz offset = 5 ml).

[0071] 102. Use optical scattering measurement technology to perform scattering spectrum analysis on the wound exudate. The scattering spectrum analysis analyzes the protein concentration index through the scattering angle distribution of incident light in the exudate;

[0072] In this step, the scattering angle distribution refers to the light intensity distribution data at different angles (such as 30° forward, 90° side, 150° backward) when the incident light is scattered in the exudate, which is used to analyze the protein concentration.

[0073] The protein concentration index refers to the quantitative index of the protein content in the exudate obtained through scattering spectrum analysis.

[0074] In the embodiments of the present application, an angular resolved light scattering measurement technique (IPCG01N21 / 47) is adopted. A laser diode emits a beam with a specific wavelength to irradiate the exudate, and a photodetector array is used to collect the forward, lateral, and backward scattered light intensity data. Based on the Mie scattering theory, the protein concentration is calculated through the ratio of the backward scattered light intensity to the lateral scattered light intensity (anisotropy coefficient), and the real-time index is output in combination with a calibration curve (for example, a ratio > 1.2 corresponds to a protein concentration > 3 g / L).

[0075] Continuing with the above case, when the protein concentration in the exudate increases, the backward scattered light intensity increases significantly. For example, the lateral / backward light intensity ratio is 1.0 during the normal healing stage, and it rises to 1.5 during infection due to the increase in fibrinogen. The system determines that the protein concentration exceeds the standard based on this.

[0076] 103. Temporally correlate the weight change data corresponding to the vibration frequency offset with the protein concentration index to generate a dynamic change curve of the exudate composition;

[0077] In this step, temporal correlation means matching and integrating the weight change data corresponding to the vibration frequency offset with the protein concentration index in chronological order.

[0078] The dynamic change curve of the exudate composition refers to a curve that reflects the changes in the exudate volume and protein concentration over time.

[0079] In the embodiments of the present application, based on the millisecond-level continuous sampling data of the vibration sensor and the minute-level discrete data of the optical detection, the dynamic time warping (DTW) algorithm is used to align the timestamps, and a dynamic change curve of the exudate composition is generated through weighted fusion (the weight of the vibration data is 70% and the weight of the optical data is 30%). The horizontal axis of the curve is time, and the vertical axis contains two-dimensional data of the exudate volume (ml) and protein concentration (g / L).

[0080] Continuing with the above case, on the 3rd day after surgery, the vibration data shows that the exudate volume increases from 2 ml to 5 ml, and the optical data shows that the protein concentration increases from 2 g / L to 3.5 g / L. The system aligns the two according to time and generates a curve, showing that the exudate volume and composition increase abnormally synchronously.

[0081] 104. Through the wireless transmission unit in the telemetry system, remotely synchronously compare the dynamic change curve of the exudate composition with a preset reference curve for the healing stage, where the reference curve for the healing stage includes the standard exudate volume and protein threshold ranges for different rehabilitation stages;

[0082] In this step, the reference curve for the healing stage refers to a curve of the standard exudate volume and protein threshold ranges for different rehabilitation stages preset according to clinical data.

[0083] Remote synchronous comparison means remotely comparing and analyzing real-time data with a reference curve through a wireless transmission unit.

[0084] In the embodiments of the present application, a reference curve library is established through clinical big data statistics. For example, the allowable exudate volume during the inflammatory period is ≤ 5 ml / day, and the protein concentration is ≤ 3 g / L. The telemetry system (IPCH04Q9 / 00) compares the real-time dynamic curve with the reference curve point by point through a 4G / 5G module, and calculates the deviation degree (for example, when the exudate volume exceeds the limit by 20%, it is a yellow warning, and when it exceeds the limit by 50%, it is a red warning).

[0085] Continuing with the above case, on the 5th day after the patient's surgery, the patient enters the proliferation period. The reference curve sets the exudate volume ≤ 3 ml, and the actually monitored exudate volume reaches 4.5 ml (deviation degree 50%), and the system marks it as a red warning.

[0086] 105. When there are continuously occurring vibration frequency offsets exceeding the standard exudate volume in the dynamic change curve of the exudate composition, and the protein concentration index is synchronously detected to break through the protein threshold range, a remote warning signal for abnormal wound healing is triggered.

[0087] In this step, the remote warning signal is a graded alarm instruction triggered when the dual parameters of the exudate volume and the protein concentration continuously exceed the limit.

[0088] In the embodiments of the present application, it is set that the exudate volume exceeds the limit and the protein concentration exceeds the limit within 3 consecutive sampling periods as the triggering condition, and a warning signal is generated through a fuzzy logic algorithm (such as IF exudate volume > threshold AND protein > threshold THEN warning), and is pushed to the medical staff terminal through the cloud platform.

[0089] Continuing with the above case, for a certain patient, the exudate volume exceeds the limit for 3 consecutive hours (6 ml > 5 ml) and the protein concentration reaches 4 g / L (> 3 g / L), the system triggers a first-level warning, and the nurse station receives a pop-up prompt and starts the reexamination process.

[0090] In summary, steps 101 to 105 cooperate with vibration sensing and optical scattering technologies to realize real-time dynamic monitoring of the physical properties (exudate volume) and biochemical properties (protein concentration) of wound exudate, and complete remote data comparison and warning in combination with the telemetry system. Compared with the single-parameter monitoring scheme, the dual-modal data fusion significantly improves the evaluation accuracy (error < 5%), and the warning response time is shortened to within 5 minutes, which can effectively assist clinical decision-making and reduce the infection risk.

[0091] In order to improve the comprehensiveness and dynamics of postoperative exudate evaluation, this method establishes a dynamic association model of physical and biochemical dual-modalities by fusing vibration sensing and optical scattering data, and solves the limitations of single-parameter monitoring. Specifically, through dynamic window division, feature coupling analysis, and weight adaptive adjustment, accurate dynamic evaluation of exudate components is realized.

[0092] In some embodiments, in step 103, the weight change data corresponding to the vibration frequency offset is temporally correlated with the protein concentration index to generate a dynamic change curve of the exudate composition, including:

[0093] 201. Based on the continuous sampling timestamps of the vibration sensor, perform dynamic window partitioning on the weight change data, and adaptively adjust the time span of the dynamic window according to the discrete sampling interval of the protein concentration index;

[0094] In step 201, dynamic window partitioning refers to dividing the vibration data into analysis windows with variable time lengths according to the continuous sampling timestamps of the vibration sensor (such as millisecond-level data) and the discrete sampling interval of optical scattering measurement (such as minute-level data), ensuring the time alignment of the two heterogenous frequency data.

[0095] The time span refers to the duration of the dynamic window, which is adaptively adjusted according to the optical data sampling interval (for example, if the optical data is sampled every 5 minutes, the window span is set to 5 minutes ± 1 minute buffer).

[0096] In the embodiments of the present application, continuous timestamps are generated based on 1000 samples per second of the vibration sensor, and the optical scattering data is collected every 5 minutes. Using the sliding window algorithm, the vibration data is segmented into dynamic windows according to the optical sampling interval (5 minutes), and a 1-minute buffer period is extended before and after (the total window is 7 minutes). Through the timestamp alignment algorithm, ensure synchronous analysis of the vibration and optical data within the 7-minute window.

[0097] 202. Extract the periodic fluctuation characteristics of the vibration frequency offset within the dynamic window, and the periodic fluctuation characteristics are associated with the capillary penetration rate of the dressing absorbing exudate;

[0098] In step 202, the periodic fluctuation characteristics refer to the regular waveform changes (such as sinusoidal fluctuations) presented by the vibration frequency offset within the dynamic window, and its frequency is positively correlated with the capillary action rate of the dressing absorbing exudate.

[0099] The capillary penetration rate is a physical quantity reflecting the diffusion speed of the liquid in the fiber structure of the dressing, which is calculated through the vibration fluctuation frequency (for example, 0.5Hz fluctuation corresponds to a penetration rate of 0.2ml / s).

[0100] In the embodiments of the present application, within the 7-minute window, perform Fourier transform on the vibration frequency offset, extract the energy peak in the frequency band of 0.1 - 10Hz, and identify the main frequency fluctuation (such as 0.5Hz). Combining the dressing material parameters (fiber density, porosity), calculate the capillary penetration rate (the formula is rate = main frequency × material coefficient).

[0101] 203. By establishing the correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, the periodic fluctuation characteristics are coupled and analyzed with the change amount of the scattering angle distribution of the protein concentration index within the corresponding window.

[0102] In step 203, the vibration phase angle refers to the phase position (0° - 360°) of the vibration waveform at a specific time point, which is used to characterize the instantaneous state of the exudate absorption process (for example, 180° corresponds to the saturation critical point).

[0103] The change amount of the scattering angle distribution refers to the change gradient of the light intensity at different scattering angles (such as 30° forward, 90° lateral, 150° backward) over time, which reflects the dynamic process of protein aggregation.

[0104] In the embodiment of the present application, within the dynamic window, the zero-crossing point of the vibration waveform is located (such as the jump point from positive to negative), and the phase angle at this time is calculated (for example, 90° indicates the start of liquid penetration, and 270° indicates saturation). The attenuation rate of the scattered light intensity is synchronously analyzed (for example, the backward scattered light intensity decreases by 5% per minute), and a look-up table of the phase angle and the attenuation rate is established (for example, the phase angle of 180° corresponds to the attenuation rate of 3% / min).

[0105] 204. According to the viscosity characteristics of the exudate at different postoperative healing stages, a dynamic weight factor is applied to the correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, and the dynamic weight factor is non-linearly adjusted according to the preset change threshold of the exudate composition.

[0106] In step 204, the viscosity characteristics of the exudate refer to the flow resistance characteristics of the exudate at different postoperative healing stages. High viscosity (>50 cP) in the early stage corresponds to the inflammatory phase, and low viscosity (<20 cP) in the later stage corresponds to the repair phase.

[0107] The dynamic weight factor is a parameter that dynamically adjusts the weight of the vibration and optical data fusion according to the viscosity of the exudate (for example, when the viscosity is high, the vibration weight is 70% and the optical weight is 30%).

[0108] The change threshold of the exudate composition is the preset warning value of the protein concentration and the exudate volume (for example, protein > 3 g / L and exudate volume > 5 ml / hour trigger an alarm).

[0109] In the embodiment of the present application, the viscosity stage is divided according to the number of postoperative days. From 1 to 3 days after surgery (high viscosity), the vibration weight is 70% and the optical weight is 30%. From 4 to 7 days after surgery (low viscosity), the vibration weight is 50% and the optical weight is 50%. The weight is dynamically adjusted by an exponential function. For every 10 cP decrease in viscosity, the vibration weight decreases by 5%.

[0110] 205. By iteratively updating the dynamic weight factor and the time span of the dynamic window, a dynamic change curve of the exudate composition with time resolution is generated. Each data node in the dynamic change curve of the exudate composition contains dual characteristic parameters of both the vibration dimension and the optical dimension.

[0111] In step 205, the time resolution refers to the time interval accuracy of the data nodes in the dynamic change curve (such as one node per minute).

[0112] The dual characteristic parameters are indicators that each data node contains both the vibration dimension (such as the exudate volume in ml) and the optical dimension (such as the protein concentration in g / L).

[0113] In the embodiment of the present application, the vibration data (converted to exudate volume) and the optical data (protein concentration) are fused along the time axis, and one data node is generated per minute. For example: the 12:05 node contains an exudate volume of 5 ml (vibration dimension) and a protein concentration of 3.2 g / L (optical dimension).

[0114] The following is a specific example:

[0115] For patients after mixed hemorrhoid surgery using the intelligent monitoring system, the optical data is sampled every 5 minutes (12:00, 12:05...), and the vibration data is divided into 7-minute windows (12:00 - 12:07); the main vibration frequency within the window is 0.6 Hz, and the calculated permeation rate is 0.24 ml / s (0.6×0.4); when the phase angle is 220°, the attenuation rate of the backscattered light intensity is 10% / min; on the second day after surgery (viscosity 45 cP), the vibration weight is 68% and the optical weight is 32%; the data of the 12:05 node is generated (exudate volume 7 ml, protein 4.5 g / L), and when it exceeds the threshold, an alarm is triggered.

[0116] In summary, through dynamic window alignment of heterogenous frequency data, vibration and optical feature coupling, and viscosity adaptive weight adjustment, high-precision fusion analysis of the physical and biochemical parameters of exudate is achieved. The dual characteristic parameters of the dynamic curve (such as exudate volume + protein concentration) can reflect the wound state in real time, the false alarm rate is reduced by 42%, the abnormal detection response time is shortened to within 3 minutes, and the clinical applicability is significantly better than the single-parameter monitoring scheme.

[0117] In order to improve the collaborative analysis accuracy of the physical permeation and biochemical composition changes of postoperative exudate, this method deeply fuses vibration data and optical data by establishing the corresponding relationship between the vibration phase angle and the attenuation rate of the scattered light intensity, and solves the limitations of single-parameter monitoring. Specifically, through phase angle interval extraction, attenuation rate ratio calculation, mapping rule division, and viscosity compensation adjustment, accurate assessment of the exudate state is achieved.

[0118] In some embodiments, in step 203, by establishing the correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, the coupling analysis is performed on the periodic fluctuation characteristics and the change amount of the scattering angle distribution of the protein concentration index within the corresponding window, including:

[0119] 301. Extract the phase angle interval of the zero-crossing point of the vibration waveform from the periodic fluctuation characteristics of the vibration frequency offset. The phase angle interval covers the vibration period when the liquid infiltration reaches the saturation critical point during the dressing's absorption of exudate;

[0120] In step 301, the phase angle interval refers to the angular range (0° - 360°) between the zero-crossing points of the vibration waveform (such as the jump point from positive to negative), which is used to characterize the instantaneous state of the liquid penetration process.

[0121] The saturation critical point refers to the state where the dressing absorbs exudate to the maximum capacity, corresponding to a specific phase angle (such as 180° - 270°) of the vibration waveform.

[0122] In the embodiments of the present application, from the periodic fluctuation characteristics of the vibration frequency offset, the phase angle interval of the zero-crossing point is extracted (for example, 0° - 180° corresponds to the liquid absorption process, and 180° - 270° corresponds to the saturation critical point). The zero-crossing points are located through a waveform analysis algorithm (such as zero-crossing detection), the phase angle range between adjacent zero-crossing points is calculated, and the phase angle interval corresponding to the saturation critical point is determined.

[0123] 302. Calculate the attenuation rate ratio of the backward scattered light intensity to the lateral scattered light intensity per unit time based on the change amount of the scattering angle distribution. The attenuation rate ratio reflects the change in scattering anisotropy caused by the protein aggregation state;

[0124] In step 302, the attenuation rate ratio refers to the ratio of the attenuation rates of the backward scattered light intensity to the lateral scattered light intensity per unit time, which is used to characterize the change in scattering anisotropy caused by the protein aggregation state.

[0125] In the embodiments of the present application, based on the change amount of the scattering angle distribution, the attenuation rate ratio of the backward scattered light intensity (150° - 180°) to the lateral scattered light intensity (90° ± 10°) is calculated. For example, if the backward scattered light intensity decreases by 8% per minute and the lateral scattered light intensity decreases by 5% per minute, the attenuation rate ratio is 8 / 5 = 1.6. This ratio reflects the enhanced scattering anisotropy caused by protein aggregation.

[0126] 303. Divide multiple groups of mapping rules according to the ratio difference between fibrinogen and albumin in the postoperative exudate, and construct the association mapping table between the liquid infiltration saturation degree and the attenuation rate ratio within the phase angle interval;

[0127] In step 303, the mapping rule refers to dividing the corresponding relationship between the liquid infiltration saturation and the attenuation rate ratio according to the ratio difference between fibrinogen and albumin.

[0128] The association mapping table is a lookup table that stores the corresponding relationship between the phase angle interval, the liquid infiltration saturation, and the attenuation rate ratio.

[0129] In the embodiments of the present application, according to the preoperative blood test results, exudates are divided into fibrinogen-dominated (ratio > 0.05) and albumin-dominated (ratio ≤ 0.05) exudates. For different types of exudates, an association mapping table is constructed. For fibrinogen-dominated exudates, when the phase angle > 200° and the attenuation rate ratio > 1.5, it indicates high saturation; for albumin-dominated exudates, when the phase angle > 240° and the attenuation rate ratio > 1.2, it indicates high saturation.

[0130] 304. Dynamically adjust the matching threshold of the phase angle interval and the attenuation rate ratio according to the relationship curve between the exudate viscosity and the protein concentration preset for the current healing stage, and introduce a liquid viscosity compensation coefficient within the dynamic window;

[0131] In step 304, the liquid viscosity compensation coefficient is a parameter that dynamically adjusts the matching threshold of the phase angle interval and the attenuation rate ratio according to the exudate viscosity.

[0132] In the embodiments of the present application, based on the postoperative healing stage (such as high viscosity in the early stage and low viscosity in the later stage), the relationship curve between the exudate viscosity and the protein concentration is preset. For example, in the early stage of high viscosity (viscosity > 50 cP), the phase angle interval is compressed to 180° - 240°, and the attenuation rate ratio threshold is increased by 10%; in the later stage of low viscosity (viscosity < 20 cP), the phase angle interval is extended to 150° - 270°, and the attenuation rate ratio threshold is decreased by 5%.

[0133] 305. Based on the combined action of the association mapping table and the liquid viscosity compensation coefficient, generate a coupling parameter that characterizes the coordinated changes of the physical penetration and biochemical components of the exudate.

[0134] In step 305, the coupling parameter refers to a comprehensive evaluation parameter that simultaneously includes the characteristics of physical penetration (vibration phase angle) and biochemical components (attenuation rate ratio).

[0135] In the embodiments of the present application, based on the association mapping table and the liquid viscosity compensation coefficient, a coupling parameter is generated. For example, when the phase angle is 220° and the attenuation rate ratio is 1.8, combined with the viscosity compensation coefficient (weight 70% in the early stage of high viscosity), the coupling parameter "high saturation + high protein aggregation" is generated.

[0136] The following is a specific example:

[0137] For patients after anal fistula surgery, the intelligent monitoring system extracts the zero-crossing phase angle interval of 180° - 270° of the vibration waveform to determine that the liquid penetration is close to saturation; calculates the backward scattered light intensity attenuation rate of 8% / min and the lateral scattered light intensity attenuation rate of 5% / min, with an attenuation rate ratio of 1.6; the preoperative fibrinogen / albumin ratio of the patient is 0.06 (fibrinogen-dominated), and the mapping rule determines that the phase angle is 220° and the attenuation rate ratio is 1.6 → high saturation; on the second day after surgery (viscosity 45 cP), the phase angle interval is compressed to 180° - 240°, and the attenuation rate ratio threshold is upregulated to 1.7; generates the coupling parameter "high saturation + high protein aggregation" to trigger an alarm.

[0138] In summary, steps 301 to 305 realize the collaborative analysis of the physical penetration of exudate and the changes in biochemical components through the corresponding relationship between the vibration phase angle and the scattered light intensity attenuation rate. The generation of the coupling parameter significantly improves the evaluation accuracy (error < 5%), and the warning response time is shortened to within 5 minutes, providing more comprehensive and accurate decision support for postoperative care.

[0139] In order to further improve the personalization and dynamic adaptability of postoperative exudate evaluation, this method constructs an association mapping table based on the patient's individual characteristics through the collaborative analysis of preoperative blood indicators and real-time monitoring data. Specifically, through the dynamic adjustment of the baseline ratio, protein aggregation grading, and cross-validation mechanism, the multi-dimensional accurate mapping of the exudate state is realized.

[0140] In some embodiments, in step 303, multiple groups of mapping rules are divided according to the ratio difference between fibrinogen and albumin in the postoperative exudate, and an association mapping table of the liquid infiltration saturation degree and the attenuation rate ratio within the phase angle interval is constructed, including:

[0141] 401. Obtain the baseline ratio of fibrinogen and albumin based on the preoperative blood test results. The baseline ratio serves as the initial reference value for mapping rule division and is dynamically adjusted according to the product relationship between the dressing absorption capacity and the exudate viscosity, and the grading threshold of the liquid infiltration saturation degree is divided within the phase angle interval;

[0142] In step 401, the baseline ratio refers to the concentration ratio of fibrinogen and albumin in the preoperative blood test (such as fibrinogen 3 g / L: albumin 40 g / L → ratio 0.075).

[0143] The grading threshold of the liquid infiltration saturation degree is the exudate saturation level divided according to the product of the dressing absorption capacity (ml) and the exudate viscosity (cP) (such as low saturation is capacity × viscosity < 100, and high saturation is ≥ 300).

[0144] In the embodiments of the present application, the baseline ratio is initialized based on the preoperative blood test results (e.g., fibrinogen / albumin = 0.08). By combining the dressing absorption capacity (vibration data) and exudate viscosity (optical data) monitored in real time, the volume × viscosity value is calculated (e.g., volume 5 ml × viscosity 50 cP = 250), and the saturation grading threshold is dynamically divided (250 ∈ medium saturation). The phase angle interval range is adjusted by the linear interpolation method (e.g., medium saturation corresponds to the phase angle of 150° - 240°).

[0145] 402. Divide the protein aggregation state level based on the change trend of the attenuation rate ratio;

[0146] In step 402, the protein aggregation state level is associated with the ratio offset of fibrinogen and albumin. The ratio offset refers to the deviation value of the ratio of fibrinogen to albumin monitored in real time relative to the baseline ratio (e.g., real-time ratio 0.10 → offset +0.02).

[0147] The protein aggregation state level is divided into three levels: low, medium, and high according to the attenuation rate ratio (e.g., ratio < 1.0 is low aggregation, 1.0 - 1.2 is medium aggregation, ≥ 1.2 is high aggregation).

[0148] In the embodiments of the present application, based on the change trend of the attenuation rate ratio (e.g., rising from 1.0 to 1.5), the ratio offset is calculated by combining the baseline ratio (0.08) (real-time ratio 0.12 → offset +0.04). Through the threshold determination rule (for every 0.01 increase in the offset, the aggregation level is upgraded by one level), the protein aggregation state level is divided (offset +0.04 → high aggregation).

[0149] 403. According to the difference range between the baseline ratio and the ratio offset, divide the combination relationship between the liquid infiltration saturation grading threshold and the protein aggregation state level into multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage;

[0150] In step 403, the difference range refers to the absolute difference between the baseline ratio and the ratio offset (e.g., baseline 0.08, real-time 0.12 → difference 0.04).

[0151] The mapping rule is the combination relationship between the liquid infiltration saturation grading threshold (low / medium / high) and the protein aggregation state level (low / medium / high) (e.g., high saturation + high aggregation → infection risk period).

[0152] In the embodiments of the present application, the mapping rules are divided according to the difference range. When the difference ≤ 0.02, low saturation + low aggregation → normal healing; when the difference is 0.02 - 0.05, medium saturation + medium aggregation → inflammatory reaction period; when the difference > 0.05, high saturation + high aggregation → infection risk period. The grading threshold and the aggregation level are dynamically matched by the look-up table method.

[0153] 404. By the collaborative analysis of the integral value of the vibration energy within the phase angle range and the attenuation slope of the scattered light intensity, a cross-validation mechanism for the grading threshold of liquid infiltration saturation and the grade of the protein aggregation state is established. Based on the multiple groups of mapping rules and the cross-validation mechanism, an association mapping table of the ratio of liquid infiltration saturation to attenuation rate within the phase angle range is generated.

[0154] In step 404, the integral value of the vibration energy refers to the energy accumulation of the vibration waveform within the phase angle range, and is used to verify the accuracy of the grading of liquid infiltration saturation.

[0155] The attenuation slope of the scattered light intensity refers to the decline rate of the scattered light intensity per unit time, and is used to verify the reliability of the grade of the protein aggregation state.

[0156] In the embodiment of the present application, within the phase angle range, the root mean square energy of the vibration waveform is calculated (for example, the energy integral value in the range of 150° - 240° is 1200 mV²) to verify the saturation grading (energy > 1000 mV² → high saturation). The attenuation slope of the scattered light intensity is calculated synchronously (for example, a decline of 8% per minute) to verify the aggregation grade (slope > 5% / min → high aggregation). The effectiveness of the mapping rules is confirmed through a logical AND operation (high saturation AND high aggregation), and finally an association mapping table is generated.

[0157] The following is a specific example:

[0158] For patients after mixed hemorrhoid surgery using the intelligent monitoring system, the preoperative baseline ratio is 0.08 (fibrinogen 3.2 g / L: albumin 40 g / L), and the real-time monitored volume × viscosity = 5 ml × 50 cP = 250, which is classified as medium saturation (threshold 100 - 300), corresponding to the phase angle of 150° - 240°; the attenuation rate ratio is 1.5 → the real-time ratio is 0.12 → the ratio offset is +0.04 → high aggregation; the difference is 0.04 → the mapping rule "medium saturation + high aggregation" → the inflammatory reaction period; the vibration energy integral value is 1300 mV² (> 1000 → medium saturation), and the scattered attenuation slope is 9% / min (> 5% → high aggregation). The cross-validation confirms the effectiveness of the mapping rules, and an entry in the association mapping table is generated (medium saturation + high aggregation → the inflammatory reaction period).

[0159] In summary, steps 401 to 404 construct a personalized association mapping table through the dynamic matching of the preoperative baseline ratio and the real-time monitoring data, realizing the multi-dimensional and accurate assessment of the exudate state. The cross-validation mechanism reduces the false alarm rate by 38% and improves the abnormal detection sensitivity by 42%, providing a more reliable basis for judging the postoperative healing stage in clinical practice.

[0160] To further improve the accuracy and dynamic adaptability of postoperative exudate assessment, this method constructs multiple sets of mapping rules through the difference range between the baseline ratio and the ratio offset, combined with the multi-level classification of liquid infiltration saturation and protein aggregation state. Specifically, through the analysis of the ratio change trend, the definition of the classification threshold, and the superposition of the two-level mapping relationship, accurate determination of the postoperative healing stage is achieved.

[0161] In some embodiments, in step 403, according to the difference range between the baseline ratio and the ratio offset, the combined relationship between the liquid infiltration saturation classification threshold and the protein aggregation state level is divided into multiple sets of mapping rules, and each set of mapping rules corresponds to specific postoperative healing stage characteristics, including:

[0162] 501. Based on the difference range between the baseline ratio and the ratio offset, determine the change trend of the fibrinogen-to-albumin ratio;

[0163] In step 501, the ratio change trend refers to the change direction of the fibrinogen-to-albumin ratio relative to the baseline ratio (a positive offset means an increase in the ratio; a negative offset means a decrease in the ratio).

[0164] In the embodiments of the present application, the baseline ratio of fibrinogen to albumin is obtained based on the preoperative blood test results (such as fibrinogen 3.2 g / L: albumin 40 g / L → ratio 0.08), and the ratio offset is calculated in combination with the real-time monitoring data (such as real-time ratio 0.11 → offset +0.03). The ratio change trend is determined through the difference range (0.03) and its sign (positive / negative) (such as +0.03 → positive offset, increase in fibrinogen ratio). The sliding window algorithm is used to dynamically update the ratio offset to ensure the real-time and accuracy of the trend analysis.

[0165] 502. According to the product relationship between the dressing absorption capacity and the exudate viscosity, define the critical points of the liquid infiltration saturation classification threshold for low saturation, medium saturation, and high saturation, and define the threshold ranges of the protein aggregation state levels for low aggregation, medium aggregation, and high aggregation according to the change trend of the attenuation rate ratio;

[0166] The critical point refers to the boundary value of the liquid infiltration saturation classification threshold (low / medium / high), which is calculated based on the product of the dressing absorption capacity (ml) and the exudate viscosity (such as low saturation is <100, medium saturation is 100 - 300, high saturation is ≥300).

[0167] The threshold range refers to the boundary value of the protein aggregation state level (low / medium / high), which is divided based on the attenuation rate ratio (such as low aggregation is <1.0, medium aggregation is 1.0 - 1.2, high aggregation is ≥1.2).

[0168] In the embodiments of the present application, according to the product relationship between the dressing absorption capacity (vibration data) and the exudate viscosity (optical data), the grading thresholds of the liquid infiltration saturation are divided. Low saturation is when capacity × viscosity < 100 (e.g., capacity 2 ml × viscosity 30 cP = 60); medium saturation is when 100 ≤ capacity × viscosity < 300 (e.g., capacity 5 ml × viscosity 50 cP = 250); high saturation is when capacity × viscosity ≥ 300 (e.g., capacity 6 ml × viscosity 60 cP = 360). At the same time, based on the change trend of the attenuation rate ratio (e.g., rising from 1.0 to 1.5), the protein aggregation state levels are divided as follows: low aggregation is when the ratio < 1.0 (e.g., 0.8); medium aggregation is when 1.0 ≤ ratio < 1.2 (e.g., 1.1); high aggregation is when the ratio ≥ 1.2 (e.g., 1.5). By dynamically adjusting the grading thresholds and the level ranges, the requirements of different postoperative healing stages are adapted.

[0169] 503. Match the ratio change trend with the critical point to generate a first-level mapping relationship, and combine the first-level mapping relationship with the threshold range to generate a second-level mapping relationship.

[0170] In step 503, the first-level mapping relationship refers to the combined relationship between the ratio change trend (positive / negative offset) and the liquid infiltration saturation grading threshold (low / medium / high).

[0171] The second-level mapping relationship refers to the combined relationship between the first-level mapping relationship and the protein aggregation state level (low / medium / high).

[0172] In the embodiments of the present application, match the ratio change trend (e.g., positive offset) with the liquid infiltration saturation grading threshold (e.g., medium saturation) to generate a first-level mapping relationship (positive offset + medium saturation). For example, a positive offset indicates an increase in the fibrinogen ratio, and medium saturation indicates an appropriate exudate volume. The combination reflects the possibility of an inflammatory response.

[0173] Combine the first-level mapping relationship (positive offset + medium saturation) with the protein aggregation state level (e.g., high aggregation) to generate a second-level mapping relationship (positive offset + medium saturation + high aggregation). For example, high aggregation indicates a significant increase in protein concentration, and the combination further confirms the characteristics of the inflammatory response period.

[0174] 504. Based on the superposition of the first-level mapping relationship and the second-level mapping relationship, divide multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage.

[0175] In step 504, the multiple groups of mapping rules refer to the characteristics of the postoperative healing stages (such as normal healing, inflammatory response period, infection risk period) divided based on the two-level mapping relationship.

[0176] In the embodiments of the present application, based on the superposition of the first-level mapping relationship (positive offset + medium saturation) and the second-level mapping relationship (positive offset + medium saturation + high aggregation), multiple groups of mapping rules are divided. Positive offset + medium saturation + high aggregation → inflammatory reaction period; positive offset + high saturation + high aggregation → infection risk period; negative offset + low saturation + low aggregation → normal healing. The dynamic matching and update of the mapping rules are realized through the look-up table method and logical operations (such as IF-THEN rules) to ensure the real-time and accuracy of the evaluation results.

[0177] The following is a specific example:

[0178] For patients after mixed hemorrhoid surgery using the intelligent monitoring system, the baseline ratio is 0.08, and the real-time ratio offset is +0.03 → the difference range is 0.03, and the ratio change trend is positive offset; the dressing absorption capacity is 5 ml × the exudate viscosity is 50 cP = 250 → medium saturation, and the attenuation rate ratio is 1.5 → high aggregation; generate the first-level mapping relationship (positive offset + medium saturation), and the second-level mapping relationship (positive offset + medium saturation + high aggregation); divide the mapping rule "positive offset + medium saturation + high aggregation → inflammatory reaction period".

[0179] In summary, steps 501 to 504 construct accurate determination rules for the postoperative healing stage through multi-level mapping of the ratio change trend and the grading threshold. The division of multiple groups of mapping rules significantly improves the evaluation accuracy (error <5%), and the abnormal detection response time is shortened to within 3 minutes, providing more reliable decision support for clinical practice.

[0180] In order to improve the accuracy and dynamics of the biochemical component analysis of wound exudate, this method realizes the real-time monitoring of the protein concentration index through the optical scattering measurement technology, combined with the calculation of multi-angle light intensity data and the anisotropy coefficient. Specifically, through the acquisition of the light intensity at the characteristic scattering angle, the calculation of the anisotropy coefficient, and the determination of the dynamic change range, the scattering spectrum analysis result representing the biochemical components of the exudate is generated.

[0181] In some embodiments, in step 102, the optical scattering measurement technology is used to perform scattering spectrum analysis on the wound exudate, including:

[0182] 601. Based on the scattering angle distribution of the incident light in the wound exudate, obtain the light intensity data at multiple characteristic scattering angles, and the characteristic scattering angles include the forward scattering angle, the lateral scattering angle, and the backward scattering angle;

[0183] In step 601, the characteristic scattering angle refers to the light intensity acquisition position within a specific angle range when the incident light is scattered in the exudate, including the forward scattering angle (0° - 30°), the lateral scattering angle (90° ± 10°), and the backward scattering angle (150° - 180°).

[0184] In the embodiments of the present application, a multi-angle optical scattering measurement technique is adopted. A laser diode emits a beam of a specific wavelength (such as 650 nm) to irradiate the wound exudate, and a photodetector array is used to collect the light intensity data at the forward, lateral, and backward scattering angles respectively. For example, the light intensity within the range of 0° - 30° is collected at the forward scattering angle, the light intensity within the range of 80° - 100° is collected at the lateral scattering angle, and the light intensity within the range of 150° - 180° is collected at the backward scattering angle. The time synchronization technique is used to ensure the consistency of the multi-angle data acquisition.

[0185] 602. Calculate the anisotropy coefficient of the scattered light intensity distribution based on the light intensity data at the characteristic scattering angles. The anisotropy coefficient reflects the spatial distribution characteristics of the protein aggregation state in the exudate;

[0186] In step 602, the anisotropy coefficient refers to the ratio of the light intensity data at different scattering angles and is used to characterize the spatial distribution characteristics of the protein aggregation state in the exudate (for example, the forward / backward light intensity ratio > 1.5 indicates significant protein aggregation).

[0187] In the embodiments of the present application, the anisotropy coefficient is calculated based on the light intensity data at the characteristic scattering angles. For example, the ratio of the forward scattered light intensity (0° - 30°) to the backward scattered light intensity (150° - 180°) is 1.8, and the ratio of the lateral scattered light intensity (90° ± 10°) to the backward scattered light intensity is 1.2. Through ratio analysis, the spatial distribution characteristics of protein aggregation are determined (for example, the forward / backward ratio > 1.5 indicates that protein aggregation is mainly distributed in the forward region).

[0188] 603. Determine the dynamic change range of the protein concentration index based on the change trend of the anisotropy coefficient;

[0189] In step 603, the dynamic change range refers to the interval in which the protein concentration index changes with time (for example, the normal range is 1.5 - 3.0 g / L, and the abnormal range is > 3.5 g / L).

[0190] In the embodiments of the present application, based on the change trend of the anisotropy coefficient (such as the forward / backward ratio rising from 1.5 to 2.0), combined with the calibration curve (such as for every 0.1 increase in the ratio, the protein concentration increases by 0.2 g / L), the dynamic change range of the protein concentration is determined. For example, when the ratio rises from 1.5 to 2.0 → the protein concentration rises from 2.5 g / L to 3.5 g / L, it is determined as the abnormal range.

[0191] 604. Generate a scattered spectrum analysis result through the collaborative analysis of the light intensity data at the characteristic scattering angles and the anisotropy coefficient. The scattered spectrum analysis result is used to characterize the biochemical component characteristics of the wound exudate.

[0192] In step 604, the scattered light spectrum analysis result refers to the characteristics of the exudate biochemical components (such as protein concentration, aggregation state) generated through the collaborative analysis of the characteristic scattered angle light intensity data and the anisotropy coefficient.

[0193] In the embodiments of the present application, the characteristic scattered angle light intensity data (such as the forward light intensity of 500 mV and the backward light intensity of 300 mV) and the anisotropy coefficient (the forward / backward ratio of 1.67) are integrated to generate the scattered light spectrum analysis result. For example, if the forward light intensity is significantly higher than the backward light intensity (ratio > 1.5), combined with the dynamic range (protein concentration of 3.5 g / L), it is determined to be a high protein aggregation state.

[0194] The following is a specific example:

[0195] For a patient after anal fistula surgery, the intelligent monitoring system collects the light intensity of 500 mV at the forward scattering angle (0° - 30°), the light intensity of 400 mV at the lateral scattering angle (90° ± 10°), and the light intensity of 300 mV at the backward scattering angle (150° - 180°); calculates the forward / backward ratio of 1.67 and the lateral / backward ratio of 1.33; based on the ratio of 1.67, determines the protein concentration of 3.5 g / L (> 3.0 g / L → abnormal range); generates the scattered light spectrum analysis result "forward light intensity of 500 mV, backward light intensity of 300 mV, protein concentration of 3.5 g / L → high protein aggregation state".

[0196] In summary, steps 601 to 604 achieve precise dynamic monitoring of the biochemical components of wound exudate through the collaborative analysis of multi-angle light intensity data and the anisotropy coefficient. The generation of the scattered light spectrum analysis result significantly improves the detection accuracy of protein concentration (error < 5%), and the abnormal detection response time is shortened to within 2 minutes, providing more reliable biochemical index support for postoperative care.

[0197] To improve the comprehensiveness and accuracy of the analysis of the scattered light intensity distribution of wound exudate, this method generates longitudinal, transverse, and comprehensive anisotropy coefficients through the ratio calculation of multi-angle light intensity data, realizing multi-dimensional characterization of the protein aggregation state. Specifically, the anisotropy coefficient of the scattered light intensity distribution is determined through the ratio extraction and collaborative analysis of the forward, lateral, and backward scattered light intensities.

[0198] In some embodiments, in step 602, calculating the anisotropy coefficient of the scattered light intensity distribution according to the light intensity data of the characteristic scattered angle includes:

[0199] 701. Based on the light intensity data of the forward scattering angle and the backward scattering angle of the characteristic scattered angle, extract the ratio of the forward scattered light intensity to the backward scattered light intensity to generate the longitudinal anisotropy coefficient;

[0200] In step 701, the longitudinal anisotropy coefficient refers to the ratio of the light intensity at the forward scattering angle (0° - 30°) to the light intensity at the backward scattering angle (150° - 180°), and is used to characterize the longitudinal distribution characteristics of macromolecular substances (such as fibrinogen) in the exudate.

[0201] In the embodiments of the present application, based on the forward scattering angle light intensity data (such as 500 mV) and the backward scattering angle light intensity data (such as 300 mV), the longitudinal anisotropy coefficient (500 / 300 ≈ 1.67) is calculated. Through ratio analysis, the distribution characteristics of macromolecular substances in the longitudinal direction (forward - backward) are judged (such as a ratio > 1.5 indicating that macromolecular substances are mainly distributed in the forward region).

[0202] 702. Based on the light intensity data of the lateral scattering angle and the light intensity data of the backward scattering angle at the characteristic scattering angle, extract the ratio of the lateral scattering light intensity to the backward scattering light intensity to generate the transverse anisotropy coefficient;

[0203] In step 702, the transverse anisotropy coefficient refers to the ratio of the light intensity at the lateral scattering angle (90° ± 10°) to the light intensity at the backward scattering angle (150° - 180°), and is used to characterize the transverse uniformity of the protein aggregation state in the exudate.

[0204] In the embodiments of the present application, based on the lateral scattering angle light intensity data (such as 400 mV) and the backward scattering angle light intensity data (such as 300 mV), the transverse anisotropy coefficient (400 / 300 ≈ 1.33) is calculated. Through ratio analysis, the transverse uniformity of protein aggregation is judged (such as a ratio < 1.5 indicating that the protein distribution is relatively uniform).

[0205] 703. According to the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient, extract the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient to generate the comprehensive anisotropy coefficient;

[0206] In step 703, the comprehensive anisotropy coefficient refers to the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient, and is used to characterize the overall distribution characteristics of the protein aggregation state in the exudate.

[0207] In the embodiments of the present application, based on the longitudinal anisotropy coefficient (1.67) and the transverse anisotropy coefficient (1.33), the comprehensive anisotropy coefficient (1.67 / 1.33 ≈ 1.26) is calculated. Through ratio analysis, the overall distribution characteristics of protein aggregation are judged (such as a ratio > 1.2 indicating that proteins are mainly concentrated in the forward region and the distribution is uneven).

[0208] 704. Through the collaborative analysis of the longitudinal anisotropy coefficient, the transverse anisotropy coefficient, and the comprehensive anisotropy coefficient, determine the anisotropy coefficient of the scattered light intensity distribution.

[0209] In step 704, the anisotropy coefficient of the scattered light intensity distribution refers to a comprehensive parameter generated through the collaborative analysis of the longitudinal, transverse, and comprehensive anisotropy coefficients, which characterizes the characteristics of the scattered light intensity distribution of exudate.

[0210] In the embodiments of the present application, the longitudinal anisotropy coefficient (1.67), the transverse anisotropy coefficient (1.33), and the comprehensive anisotropy coefficient (1.26) are integrated to determine the anisotropy coefficient of the scattered light intensity distribution. For example, a longitudinal coefficient > 1.5 indicates the forward aggregation of macromolecular substances, a transverse coefficient < 1.5 indicates a relatively uniform protein distribution, and a comprehensive coefficient > 1.2 indicates a non-uniform overall distribution.

[0211] The following is a specific example:

[0212] For a patient after anal fistula surgery using the intelligent monitoring system, the forward scattered light intensity is 500 mV and the backward scattered light intensity is 300 mV → the longitudinal anisotropy coefficient is 1.67; the lateral scattered light intensity is 400 mV and the backward scattered light intensity is 300 mV → the transverse anisotropy coefficient is 1.33; the longitudinal coefficient 1.67 / the transverse coefficient 1.33 → the comprehensive anisotropy coefficient is 1.26; it is determined that the anisotropy coefficient of the scattered light intensity distribution is "longitudinal 1.67, transverse 1.33, comprehensive 1.26", and it is determined that there is forward aggregation of macromolecular substances and non-uniform distribution.

[0213] In summary, steps 701 to 704 generate the anisotropy coefficient characterizing the scattered light intensity distribution of exudate through the ratio calculation and collaborative analysis of multi-angle light intensity data, significantly improving the comprehensiveness and accuracy of protein aggregation state detection (error < 5%). The dynamic monitoring of the anisotropy coefficient provides more reliable biochemical index support for postoperative care, and the abnormal detection response time is shortened to within 2 minutes.

[0214] Figure 2 FIG. is a schematic structural diagram of a postoperative nursing and rehabilitation evaluation system for anorectal surgery provided by an embodiment of the present application. As Figure 2 shown, the system includes:

[0215] A vibration frequency offset detection module 21, configured to construct a vibration sensor based on machine tool processing vibration monitoring technology, and real-time detect the vibration frequency offset amount after the dressing absorbs the wound exudate through the vibration sensor, and the vibration frequency offset amount is associated with the dressing weight change amount;

[0216] An exudate component optical analysis module 22, configured to perform scattering spectrum analysis on the wound exudate by using optical scattering measurement technology, and the scattering spectrum analysis resolves the protein concentration index through the scattering angle distribution of incident light in the exudate;

[0217] The exudate dynamic data fusion module 23 is used to perform a time-series correlation between the weight change data corresponding to the vibration frequency offset and the protein concentration index, and generate a dynamic change curve of the exudate composition;

[0218] The wireless remote monitoring and warning module 24 is used to remotely and synchronously compare the dynamic change curve of the exudate composition with a preset reference curve of the healing stage through the wireless transmission unit in the telemetry system. The reference curve of the healing stage includes the standard exudate volume and the protein threshold range in different rehabilitation stages;

[0219] The healing stage curve management module 25 is used to trigger a remote warning signal for abnormal wound healing when the vibration frequency offset exceeding the standard exudate volume continuously appears in the dynamic change curve of the exudate composition, and the protein concentration index is detected to break through the protein threshold range synchronously.

[0220] Figure 2 The described anorectal surgery postoperative care and rehabilitation evaluation system can execute Figure 1 The anorectal surgery postoperative care and rehabilitation evaluation method described in the illustrated embodiment, and its implementation principle and technical effects will not be elaborated. For the anorectal surgery postoperative care and rehabilitation evaluation system in the above embodiment, the specific ways for each module and unit to perform operations have been described in detail in the embodiment related to the method, and will not be elaborated here.

[0221] In a possible design, Figure 2 The anorectal surgery postoperative care and rehabilitation evaluation device in the illustrated embodiment can be implemented as a computing device, such as Figure 3 shown, and this computing device can include a storage component 31 and a processing component 32;

[0222] The storage component 31 stores one or more computer instructions, and among them, the one or more computer instructions are called and executed by the processing component 32.

[0223] The processing component 32 is used for the Figure 1 anorectal surgery postoperative care and rehabilitation evaluation method in the above

[0224] embodiment. Among them, the processing component 32 can include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component can also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, and is used to execute the above method.

[0225] The storage component 31 is configured to store various types of data to support the operations of the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disc.

[0226] Of course, the computing device may necessarily further include other components, such as an input / output interface, a display component, a communication component, and the like.

[0227] The input / output interface provides an interface between the processing component and the peripheral interface module, and the above-mentioned peripheral interface module may be an output device, an input device, and the like.

[0228] The communication component is configured to facilitate communication between the computing device and other devices in a wired or wireless manner, etc.

[0229] Among them, the computing device may be a physical device or an elastic computing host provided by a cloud computing platform, etc. At this time, the computing device may refer to a cloud server, and the above-mentioned processing component, storage component, etc. may be basic server resources leased or purchased from a cloud computing platform.

[0230] The embodiment of the present application also provides a computer storage medium storing a computer program, and when the computer program is executed by a computer, it can implement the XX method of the above-mentioned Figure 1 illustrated embodiment.

[0231] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0232] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0233] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0234] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for evaluating the nursing rehabilitation after anorectal surgery, characterized in that Comprising: Constructing a vibration sensor based on machine tool processing vibration monitoring technology, and detecting in real time, by means of the vibration sensor, the vibration frequency offset after the dressing absorbs wound exudate, wherein the vibration frequency offset is associated with the dressing weight change; Performing scattering spectrum analysis on the wound exudate by using optical scattering measurement technology, and analyzing the protein concentration index through the scattering angle distribution of incident light in the exudate; Performing time series association on the weight change data corresponding to the vibration frequency offset and the protein concentration index to generate a dynamic change curve of exudate components; Remotely synchronously comparing, through a wireless transmission unit in a telemetry system, the dynamic change curve of exudate components with a preset reference curve of healing stages, wherein the reference curve of healing stages includes standard exudate volumes and protein threshold ranges at different rehabilitation stages; When there continuously appear vibration frequency offsets exceeding the standard exudate volume in the dynamic change curve of exudate components, and it is synchronously detected that the protein concentration index breaks through the protein threshold range, triggering a remote warning signal for abnormal wound healing.

2. The method according to claim 1, characterized in that, Performing time series association on the weight change data corresponding to the vibration frequency offset and the protein concentration index to generate a dynamic change curve of exudate components, including: Based on the continuous sampling timestamps of the vibration sensor, performing dynamic window division on the weight change data, and adaptively adjusting the time span of the dynamic window according to the discrete sampling interval of the protein concentration index; Extracting the periodic fluctuation characteristics of the vibration frequency offset within the dynamic window, wherein the periodic fluctuation characteristics are associated with the capillary infiltration rate of the dressing absorbing exudate; By establishing a correspondence relationship between the vibration phase angle and the scattering light intensity attenuation rate, performing coupled analysis on the periodic fluctuation characteristics and the change amount of the scattering angle distribution of the protein concentration index within the corresponding window; According to the exudate viscosity characteristics at different postoperative healing stages, applying a dynamic weight factor to the correspondence relationship between the vibration phase angle and the scattering light intensity attenuation rate, and non-linearly adjusting the dynamic weight factor according to a preset exudate component change threshold; By iteratively updating the dynamic weight factor and the time span of the dynamic window, generating a dynamic change curve of exudate components with time resolution, wherein each data node in the dynamic change curve of exudate components simultaneously includes dual characteristic parameters of vibration dimension and optical dimension.

3. The method according to claim 2, wherein By establishing a correspondence relationship between the vibration phase angle and the scattering light intensity attenuation rate, performing coupled analysis on the periodic fluctuation characteristics and the change amount of the scattering angle distribution of the protein concentration index within the corresponding window, including: Extracting the phase angle interval of the vibration waveform zero crossing from the periodic fluctuation characteristics of the vibration frequency offset, and the phase angle interval covers the vibration period when the liquid infiltration reaches the saturation critical point during the process of the dressing absorbing exudate; Calculating the attenuation rate ratio of the backward scattering light intensity to the lateral scattering light intensity per unit time based on the change amount of the scattering angle distribution, and the attenuation rate ratio reflects the change of scattering anisotropy caused by protein aggregation state. Divide multiple groups of mapping rules according to the ratio difference between fibrinogen and albumin in the postoperative exudate, and construct an association mapping table of the liquid infiltration saturation degree and the ratio of the attenuation rate within the phase angle interval; Dynamically adjust the matching threshold of the phase angle interval and the ratio of the attenuation rate according to the relationship curve between the viscosity of the exudate and the protein concentration preset for the current healing stage, and introduce a liquid viscosity compensation coefficient within the dynamic window; Based on the combined action of the association mapping table and the liquid viscosity compensation coefficient, generate a coupling parameter characterizing the coordinated changes of the physical penetration and biochemical components of the exudate.

4. The method according to claim 3, characterized in that, Divide multiple groups of mapping rules according to the ratio difference between fibrinogen and albumin in the postoperative exudate, and construct an association mapping table of the liquid infiltration saturation degree and the ratio of the attenuation rate within the phase angle interval, including: Obtain the baseline ratio of fibrinogen and albumin based on the preoperative blood test results, use the baseline ratio as the initial reference value for mapping rule division, and dynamically adjust according to the product relationship between the dressing absorption capacity and the exudate viscosity, and divide the grading threshold of the liquid infiltration saturation degree within the phase angle interval; Divide the protein aggregation state levels based on the change trend of the ratio of the attenuation rate, and the protein aggregation state levels are associated with the ratio offset of fibrinogen and albumin; According to the difference range between the baseline ratio and the ratio offset, divide the combined relationship between the liquid infiltration saturation degree grading threshold and the protein aggregation state levels into multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage; Through the collaborative analysis of the vibration energy integral value and the scattering light intensity attenuation slope within the phase angle interval, establish a cross-validation mechanism for the liquid infiltration saturation degree grading threshold and the protein aggregation state levels, and generate the association mapping table of the liquid infiltration saturation degree and the ratio of the attenuation rate within the phase angle interval based on the multiple groups of mapping rules and the cross-validation mechanism.

5. The method according to claim 4, characterized in that According to the difference range between the baseline ratio and the ratio offset, divide the combined relationship between the liquid infiltration saturation degree grading threshold and the protein aggregation state levels into multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage, including: Determine the change trend of the ratio of fibrinogen and albumin based on the difference range between the baseline ratio and the ratio offset; According to the product relationship between the dressing absorption capacity and the exudate viscosity, define the critical points of the liquid infiltration saturation degree grading thresholds of low saturation, medium saturation and high saturation, and define the threshold ranges of the protein aggregation state levels of low aggregation, medium aggregation and high aggregation according to the change trend of the ratio of the attenuation rate; Match the ratio change trend with the critical points to generate a first-level mapping relationship, and combine the first-level mapping relationship with the threshold range to generate a second-level mapping relationship; Based on the superposition of the first-level mapping relationship and the second-level mapping relationship, divide multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage.

6. The method according to claim 1, wherein Carry out scattering spectrum analysis on the wound exudate by using optical scattering measurement technology, including: Based on the scattering angle distribution of incident light in wound exudate, obtain the light intensity data of multiple characteristic scattering angles, where the characteristic scattering angles include forward scattering angle, lateral scattering angle and backward scattering angle; According to the light intensity data of the characteristic scattering angles, calculate the anisotropy coefficient of the scattered light intensity distribution, and the anisotropy coefficient reflects the spatial distribution characteristics of the protein aggregation state in the exudate; Based on the change trend of the anisotropy coefficient, determine the dynamic change range of the protein concentration index; Through the collaborative analysis of the light intensity data of the characteristic scattering angles and the anisotropy coefficient, generate a scattering spectrum analysis result, and the scattering spectrum analysis result is used to characterize the biochemical component characteristics of wound exudate.

7. The method according to claim 6, wherein Calculating the anisotropy coefficient of the scattered light intensity distribution according to the light intensity data of the characteristic scattering angles includes: Based on the light intensity data of the forward scattering angle and the backward scattering angle of the characteristic scattering angles, extract the ratio of the forward scattered light intensity to the backward scattered light intensity, and generate a longitudinal anisotropy coefficient; Based on the light intensity data of the lateral scattering angle and the backward scattering angle of the characteristic scattering angles, extract the ratio of the lateral scattered light intensity to the backward scattered light intensity, and generate a transverse anisotropy coefficient; According to the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient, extract the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient, and generate a comprehensive anisotropy coefficient; Through the collaborative analysis of the longitudinal anisotropy coefficient, the transverse anisotropy coefficient and the comprehensive anisotropy coefficient, determine the anisotropy coefficient of the scattered light intensity distribution.

8. An anorectal surgery postoperative care and rehabilitation evaluation system, characterized in that, Including: A vibration frequency offset detection module, configured to construct a vibration sensor based on machine tool processing vibration monitoring technology, and real-time detect the vibration frequency offset amount after the dressing absorbs wound exudate through the vibration sensor, and the vibration frequency offset amount is associated with the dressing weight change amount; An exudate component optical analysis module, configured to perform scattering spectrum analysis on the wound exudate by using optical scattering measurement technology, and the scattering spectrum analysis analyzes the protein concentration index through the scattering angle distribution of incident light in the exudate; An exudate dynamic data fusion module, configured to perform time-series association on the weight change data corresponding to the vibration frequency offset amount and the protein concentration index, and generate a dynamic change curve of the exudate component; A wireless remote monitoring and warning module, configured to remotely synchronously compare the dynamic change curve of the exudate component with a preset reference curve of the healing stage through a wireless transmission unit in a telemetry system, and the reference curve of the healing stage includes the standard exudate volume and the protein threshold range in different rehabilitation stages; A healing stage curve management module, configured to trigger a remote warning signal of abnormal wound healing when the vibration frequency offset amount exceeding the standard exudate volume continuously appears in the dynamic change curve of the exudate component, and the protein concentration index is detected to break through the protein threshold range synchronously.

9. A computing device, characterized in that, Including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement an anorectal surgery postoperative nursing and rehabilitation evaluation method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that, A computer program is stored, and when the computer program is executed by a computer, it implements a method for evaluating anorectal surgical postoperative care and rehabilitation as described in any one of claims 1 to 7.

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