Anorectal surgery postoperative care rehabilitation evaluation method and system

Abstract

The invention provides an anorectal surgery postoperative care rehabilitation evaluation method and system. Wherein a vibration sensor is constructed through a machine tool machining vibration monitoring technology, vibration frequency offset of the dressing after absorbing wound seepage is detected in real time, and the vibration frequency offset is associated with dressing weight variation; meanwhile, an optical scattering measurement technology is adopted for carrying out scattering spectrum analysis on wound exudate, and the protein concentration index is analyzed. And carrying out time sequence correlation on the weight change data corresponding to the vibration frequency offset and the protein concentration index to generate a seepage component dynamic change curve. And through a wireless transmission unit in the remote measurement system, performing remote synchronous comparison on the dynamic change curve and a preset healing stage reference curve, and when the vibration frequency offset exceeding the standard seepage amount continuously appears in the curve and the protein concentration index breaks through the threshold range, triggering a remote early warning signal of wound healing abnormity. According to the technical scheme provided by the invention, the nursing rehabilitation efficiency and precision are improved.

Description

Technical Field

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

[0002] Wound care after 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 dressing wetness and patients' subjective feedback, 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, a pressure sensor or an optical sensor is 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 in physical and biochemical characteristics. For example, although an optical fiber sensor can detect the composition of exudate, it 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] Embodiments of this application provide a method and system for postoperative nursing rehabilitation assessment in anorectal surgery to solve the problems of low nursing rehabilitation efficiency and low accuracy in the prior art.

[0006] In a first aspect, embodiments of this application provide a method for postoperative nursing rehabilitation assessment in anorectal surgery, including: Constructing a vibration sensor based on machine tool processing vibration monitoring technology, and real-time detecting the vibration frequency offset amount of the dressing after absorbing wound exudate through the vibration sensor, where the vibration frequency offset amount is associated with the dressing weight change amount; Performing scattering spectrum analysis on the wound exudate 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; Performing 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 exudate composition; Remotely synchronously comparing the dynamic change curve of exudate composition with a preset reference curve of healing stages through a wireless transmission unit in a telemetry system, where the reference curve of healing stages includes the standard exudate amount and the protein threshold range in different rehabilitation stages; When there are consecutive vibration frequency offsets exceeding the standard exudate volume in the dynamic change curve of the exudate components, and it is simultaneously detected that the protein concentration index breaks through the protein threshold range, a remote warning signal for abnormal wound healing is triggered.

[0007] Optionally, time-sequentially 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 components, including: 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; 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; By establishing a correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, perform coupled analysis on the periodic fluctuation characteristics and the change amount of the scattered angle distribution of the protein concentration index within the corresponding window; According to the exudate viscosity characteristics at different postoperative healing stages, apply a dynamic weight factor 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; By iteratively updating the dynamic weight factor and the time span of the dynamic window, generate a dynamic change curve of the exudate components with time resolution, and each data node in the dynamic change curve of the exudate components contains dual characteristic parameters of vibration dimension and optical dimension.

[0008] Optionally, by establishing a correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, perform coupled analysis on the periodic fluctuation characteristics and the change amount of the scattered angle distribution of the protein concentration index within the corresponding window, including: Extract the phase angle interval of the vibration waveform zero-crossing point 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; Based on the change amount of the scattered angle distribution, calculate the attenuation rate ratio of the backward scattered light intensity to the lateral scattered light intensity per unit time, and the attenuation rate ratio reflects the change in scattering anisotropy caused by the 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 between the liquid infiltration saturation degree and the attenuation rate ratio within the phase angle interval; Dynamically adjust the matching threshold between the phase angle interval and the attenuation rate ratio according to the preset exudate viscosity and protein concentration relationship curve at 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, a coupling parameter is generated to characterize the synergistic change of physical penetration and biochemical components of exudate.

[0009] Optionally, 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 ratio of liquid infiltration saturation to the attenuation rate within the phase angle interval is constructed, including: 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. The grading thresholds of liquid infiltration saturation are divided within the phase angle interval; Divide the protein aggregation state grades based on the change trend of the attenuation rate ratio. The protein aggregation state grades are associated with the ratio offset of fibrinogen and albumin; According to the difference range between the baseline ratio and the ratio offset, the combined relationship between the liquid infiltration saturation grading threshold and the protein aggregation state grade is divided 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, a cross-validation mechanism between the liquid infiltration saturation grading threshold and the protein aggregation state grade 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 the attenuation rate within the phase angle interval is generated.

[0010] Optionally, according to the difference range between the baseline ratio and the ratio offset, the combined relationship between the liquid infiltration saturation grading threshold and the protein aggregation state grade is divided into multiple groups of mapping rules, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage, including: Based on the difference range between the baseline ratio and the ratio offset, determine the change trend of the ratio of fibrinogen to albumin; According to the product relationship between the dressing absorption capacity and the exudate viscosity, define the critical points of the liquid infiltration saturation grading thresholds of low saturation, medium saturation, and high saturation, and define the threshold ranges of the protein aggregation state grades of low aggregation, medium aggregation, and high aggregation according to the change trend of the attenuation rate ratio; 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 ranges 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.

[0011] Optionally, an optical scattering measurement technique is used to perform scattering spectrum analysis on the wound exudate, including: Based on the scattering angle distribution of incident light in the wound exudate, light intensity data at multiple characteristic scattering angles are obtained, and the characteristic scattering angles include the forward scattering angle, the lateral scattering angle, and the backward scattering angle; According to the light intensity data at the characteristic scattering angles, the anisotropy coefficient of the scattered light intensity distribution is calculated, 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, the dynamic change range of the protein concentration index is determined; Through the collaborative analysis of the light intensity data at the characteristic scattering angles and the anisotropy coefficient, a scattering spectrum analysis result is generated, and the scattering spectrum analysis result is used to characterize the biochemical component characteristics of the wound exudate.

[0012] Optionally, according to the light intensity data at the characteristic scattering angles, the anisotropy coefficient of the scattered light intensity distribution is calculated, including: Based on the light intensity data at the forward scattering angle and the backward scattering angle of the characteristic scattering angles, the ratio of the forward scattered light intensity to the backward scattered light intensity is extracted to generate a longitudinal anisotropy coefficient; Based on the light intensity data at the lateral scattering angle and the backward scattering angle of the characteristic scattering angles, the ratio of the lateral scattered light intensity to the backward scattered light intensity is extracted to generate a transverse anisotropy coefficient; According to the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient, the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient is extracted to generate a comprehensive anisotropy coefficient; Through 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.

[0013] In a second aspect, an anorectal surgery postoperative care and rehabilitation evaluation system provided by an embodiment of the present application includes: A vibration frequency offset detection module, configured to construct a vibration sensor based on machine tool processing vibration monitoring technology, and detect the vibration frequency offset amount after the dressing absorbs the wound exudate in real time through the vibration sensor, where 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 an optical scattering measurement technique, 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 to generate an exudate component dynamic change curve; A wireless remote monitoring and warning module 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 a wireless transmission unit in a telemetry system. The reference curve of the healing stage includes the standard exudate volume and the protein threshold range at different rehabilitation stages; A healing stage curve management module is used to trigger a remote warning signal for abnormal wound healing when there are consecutive vibration frequency offsets exceeding the standard exudate volume in the dynamic change curve of the exudate composition and it is synchronously detected that the protein concentration index breaks through the protein threshold range.

[0014] 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 an anorectal surgical postoperative care and rehabilitation evaluation method as described in the first aspect above.

[0015] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, and when the computer program is executed by a computer, it implements an anorectal surgical postoperative care and rehabilitation evaluation method as described in the first aspect.

[0016] In the embodiment of the present application, a vibration sensor is constructed based on the machine tool processing vibration monitoring technology, and the vibration frequency offset after the dressing absorbs the wound exudate is detected in real time through the vibration sensor. The vibration frequency offset is associated with the dressing weight change; 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 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 and 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 at different rehabilitation stages; when there are consecutive vibration frequency offsets exceeding the standard exudate volume in the dynamic change curve of the exudate composition 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.

[0017] The technical solution of the present application has the following beneficial effects: Quantify the weight change of the dressing absorbing exudate in real time through the vibration frequency offset, and achieve high-precision dynamic monitoring of the exudate volume. Analyze the protein concentration in the exudate through the scattering angle distribution to provide the ability to monitor the biochemical components in real time. Generate the dynamic change curves of the physical and biochemical characteristics of the exudate through time series correlation to achieve the fusion analysis of multi-dimensional data. Realize remote real-time comparison to provide a quantitative evaluation basis for the healing progress for medical staff. Trigger the warning of abnormal healing accurately through multi-parameter joint judgment to improve the timeliness of nursing intervention.

[0018] Furthermore, based on the continuous sampling timestamps of the vibration sensor, dynamically divide the weight change data into windows and adaptively adjust the window time span; extract the periodic fluctuation characteristics of the vibration frequency offset within the window, and perform coupled analysis in combination with the relationship between the vibration phase angle and the attenuation rate of the scattered light intensity; dynamically adjust the weight factor according to the viscosity characteristics of the postoperative exudate, and finally generate the dynamic change curve of the exudate composition containing dual characteristic parameters of vibration dimension and optical dimension.

[0019] Through the above method, realize the efficient fusion of vibration data and optical data, and generate the dynamic change curve of the exudate composition with time resolution. 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.

[0020] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. Brief Description of the Drawings

[0021] In order 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 use in 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, other drawings can be obtained based on these drawings without creative efforts.

[0022] Figure 1 Shows the flowchart of a method for postoperative nursing rehabilitation evaluation in anorectal surgery provided by the present application; Figure 2 Shows the structural schematic diagram of a system for postoperative nursing rehabilitation evaluation in anorectal surgery provided by the present application; Figure 3 Shows the structural schematic diagram of a computing device provided by the present application. Detailed Description of the Embodiments

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application.

[0024] In some processes described in the specification, claims and the above-mentioned drawings of this application, a plurality of operations appear in a specific order. However, it should be clearly understood that these operations may not be executed in the order in which they appear herein or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions such as "first" and "second" in this document are used to distinguish different messages, devices, modules, etc., do not represent a sequence, and do not limit that "first" and "second" are of different types.

[0025] The R & D idea of this application is based on cross-field technology integration. The machine tool processing vibration monitoring technology is transformed into a vibration sensor to detect the vibration frequency offset after the dressing absorbs the wound exudate in real time, so as to quantify the change in exudate weight. At the same time, the optical scattering measurement technology is introduced, and the protein concentration index is analyzed through the scattering angle distribution of the incident light in the exudate 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 the exudate composition is generated, and remote synchronous comparison and early warning are realized in combination with the telemetry system. 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 accurate evaluation method for postoperative care.

[0026] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. 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 work belong to the scope of protection of the present application.

[0027] Figure 1 A flowchart of a method for evaluating the postoperative care and rehabilitation of anorectal surgery is provided for the embodiments of the present application, as Figure 1 shown, the method includes: 101. Construct a vibration sensor based on the machine tool processing vibration monitoring technology, and detect the vibration frequency offset after the dressing absorbs the wound exudate in real time through the vibration sensor. The vibration frequency offset is associated with the change in the dressing weight; 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 weight change after the dressing absorbs the exudate, which is obtained by detecting through a vibration sensor and is positively correlated with the change in the dressing weight.

[0028] In the embodiments of the present application, an industrial-grade vibration sensor is transformed based on the machine tool processing vibration monitoring technology. The dressing vibration signal is collected by a piezoelectric ceramic element, and the fundamental frequency component is extracted by using the Fast Fourier Transform (FFT). 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 weight change amount is established through a calibration experiment (for example, for every 10 Hz decrease in frequency, the exudate volume increases by 1 ml), and finally, the real-time quantitative monitoring of the exudate volume is realized.

[0029] In a practical case, in the postoperative patient care, the vibration sensor is embedded in the bottom layer of the intelligent dressing. When the exudate is absorbed, the weight of the dressing increases, resulting in a decrease in the vibration frequency. For example, the fundamental frequency in the initial dry state is 500 Hz, and after absorbing 5 ml of exudate, the frequency drops to 450 Hz. The system displays the exudate volume in real time through the preset linear relationship (50 Hz offset = 5 ml).

[0030] 102. The optical scattering measurement technology is adopted 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; In this step, the scattering angle distribution refers to the light intensity distribution data at different angles (such as 30° forward, 90° lateral, 150° backward) when the incident light is scattered in the exudate, which is used to analyze the protein concentration.

[0031] The protein concentration index refers to the quantitative index of the protein content in the exudate obtained through the scattering spectrum analysis.

[0032] In the embodiments of the present application, the multi-angle optical scattering measurement technology (IPCG01N21 / 47) is adopted. A specific wavelength beam is emitted by a laser diode 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 the calibration curve (for example, when the ratio > 1.2, the protein concentration > 3 g / L).

[0033] 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 in the normal healing stage is 1.0, and during infection, due to the increase in fibrinogen, the ratio rises to 1.5, and the system determines that the protein concentration exceeds the standard accordingly.

[0034] 103. 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; In this step, the time series correlation means matching and integrating the weight change data corresponding to the vibration frequency offset and the protein concentration index in chronological order.

[0035] The dynamic change curve of exudate components refers to the curve reflecting the changes of exudate volume and protein concentration over time.

[0036] In the embodiment of the present application, based on the millisecond-level continuous sampling data of the vibration sensor and the minute-level discrete data of optical detection, the dynamic time warping (DTW) algorithm is used to align the timestamps, and the dynamic change curve of exudate components is generated through weighted fusion (vibration data weight 70%, optical data weight 30%). The horizontal axis of the curve is time, and the vertical axis contains two-dimensional data of exudate volume (ml) and protein concentration (g / L).

[0037] Continuing the above case, on the 3rd day after the operation, 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. After the system aligns the two according to time, a curve is generated, showing that the exudate volume and components increase abnormally synchronously.

[0038] 104. Through the wireless transmission unit in the telemetry system, remotely synchronously compare the dynamic change curve of the exudate components with a preset reference curve of the healing stage, and the reference curve of the healing stage includes the standard exudate volume and protein threshold range in different rehabilitation stages; In this step, the reference curve of the healing stage refers to the curve of the standard exudate volume and protein threshold range in different rehabilitation stages preset according to clinical data.

[0039] Remote synchronous comparison means remotely comparing and analyzing real-time data with the reference curve through the wireless transmission unit.

[0040] In the embodiment of the present application, a reference curve library is established through clinical big data statistics. For example, during the inflammation period, the allowable exudate volume ≤ 5 ml / day and the protein concentration ≤ 3 g / L. The telemetry system (IPCH04Q9 / 00) compares the real-time dynamic curve with the reference curve point by point through the 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).

[0041] Continuing the above case, on the 5th day after the operation, 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.

[0042] 105. When there is a continuous vibration frequency offset exceeding the standard exudate volume in the dynamic change curve of the exudate components, and at the same time, it is detected that the protein concentration index breaks through the protein threshold range, trigger a remote warning signal for abnormal wound healing.

[0043] In this step, the remote warning signal is a hierarchical alarm instruction triggered when the dual parameters of exudate volume and protein concentration continuously exceed the limit.

[0044] In the embodiments of the present application, it is set that the liquid leakage volume exceeds the limit and the protein concentration exceeds the limit within three consecutive sampling periods as the triggering condition. An early warning signal is generated through a fuzzy logic algorithm (such as IF the liquid leakage volume > the threshold AND the protein > the threshold THEN give an early warning), and is pushed to the medical staff terminal through the cloud platform.

[0045] Continuing with the above case, for a certain patient, the liquid leakage volume exceeded the limit for 3 consecutive hours (6 ml > 5 ml) and the protein concentration reached 4 g / L (> 3 g / L). The system triggered a first-level early warning, and the nurse station received a pop-up prompt and initiated a recheck process.

[0046] In summary, steps 101 to 105 cooperate with vibration sensing and optical scattering technologies to achieve real-time dynamic monitoring of the physical characteristics (liquid leakage volume) and biochemical characteristics (protein concentration) of wound exudate, and complete remote data comparison and early 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 early warning response time is shortened to within 5 minutes, which can effectively assist clinical decision-making and reduce the infection risk.

[0047] In order to improve the comprehensiveness and dynamics of postoperative exudate evaluation, this method establishes a dynamic correlation 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 achieved.

[0048] 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 exudate components, including: 201. Based on the continuous sampling timestamps of the vibration sensor, perform dynamic window division 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; In step 201, dynamic window division 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), to ensure the time alignment of the two heterogenous frequency data.

[0049] 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).

[0050] In the embodiments of the present application, continuous timestamps are generated based on 1000 samples per second by a vibration sensor, and data is collected by optical scattering every 5 minutes. The sliding window algorithm is adopted to divide the vibration data 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, synchronous analysis of vibration and optical data within the 7-minute window is ensured.

[0051] 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; 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.

[0052] The capillary penetration rate is a physical quantity reflecting the diffusion speed of the liquid in the fiber structure of the dressing, and is calculated through the vibration fluctuation frequency (for example, a 0.5Hz fluctuation corresponds to a penetration rate of 0.2ml / s).

[0053] In the embodiments of the present application, within the 7-minute window, Fourier transform is performed on the vibration frequency offset, the energy peak value in the frequency band of 0.1 - 10Hz is extracted, and the main frequency fluctuation (such as 0.5Hz) is identified. Combining the dressing material parameters (fiber density, porosity), the capillary penetration rate is calculated (the formula is rate = main frequency × material coefficient).

[0054] 203. By establishing the correspondence between the vibration phase angle and the attenuation rate of the scattered light intensity, perform 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; In step 203, the vibration phase angle refers to the phase position (0° - 360°) of the vibration waveform at a specific time point, and is used to characterize the instantaneous state of the exudate absorption process (for example, 180° corresponds to the saturation critical point).

[0055] 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, and reflects the dynamic process of protein aggregation.

[0056] In the embodiments of the present application, within the dynamic window, locate the zero-crossing point of the vibration waveform (such as the jump point from positive to negative), and calculate the phase angle at this time (for example, 90° indicates the start of liquid penetration, and 270° indicates saturation). Synchronously analyze the attenuation rate of the scattered light intensity (such as the backward scattered light intensity drops by 5% per minute), and establish a lookup table of the phase angle and the attenuation rate (for example, the phase angle 180° corresponds to the attenuation rate 3% / min).

[0057] 204. Apply a dynamic weight factor to the corresponding relationship between the vibration phase angle and the attenuation rate of scattered light intensity according to the viscosity characteristics of exudate at different postoperative healing stages. The dynamic weight factor is non-linearly adjusted according to a preset threshold for exudate composition change. In step 204, the viscosity characteristics of exudate refer to the flow resistance characteristics of 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.

[0058] The dynamic weight factor is a parameter that dynamically adjusts the weight of vibration and optical data fusion according to the viscosity of exudate (e.g., when the viscosity is high, the vibration weight is 70% and the optical weight is 30%).

[0059] The threshold for exudate composition change is a preset warning value for protein concentration and exudate volume (e.g., when protein > 3 g / L and exudate volume > 5 ml / hour, an alarm is triggered).

[0060] In the embodiments 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%.

[0061] 205. Generate a dynamic change curve of exudate composition with time resolution by iteratively updating the dynamic weight factor and the time span of the dynamic window. Each data node in the dynamic change curve of exudate composition contains dual characteristic parameters with both vibration and optical dimensions.

[0062] In step 205, the time resolution refers to the time interval accuracy of data nodes in the dynamic change curve (e.g., one node per minute).

[0063] The dual characteristic parameters are indicators that each data node contains both a vibration dimension (such as exudate volume in ml) and an optical dimension (such as protein concentration in g / L).

[0064] In the embodiments of the present application, vibration data (converted to exudate volume) and 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).

[0065] The following is a specific example: For patients after mixed hemorrhoid surgery using an intelligent monitoring system, optical sampling is performed every 5 minutes (12:00, 12:05...), and 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 penetration 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%; node data at 12:05 is generated (seepage volume 7 ml, protein 4.5 g / L), and when it exceeds the threshold, an alarm is triggered.

[0066] In summary, through dynamic window alignment of heterogenous frequency data, coupling of vibration and optical characteristics, and viscosity adaptive weight adjustment, high-precision fusion analysis of seepage physical and biochemical parameters is achieved. The dual characteristic parameters of the dynamic curve (such as seepage volume + protein concentration) can reflect the wound surface state in real time, the false alarm rate is reduced by 42%, and the abnormal detection response time is shortened to within 3 minutes, and the clinical applicability is significantly better than the single-parameter monitoring scheme.

[0067] To improve the collaborative analysis accuracy of the physical penetration and biochemical component changes of postoperative seepage, 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 seepage state is achieved.

[0068] In some embodiments, in step 203, by establishing the corresponding relationship between the vibration phase angle and the attenuation rate of the scattered light intensity, the coupling analysis of the periodic fluctuation characteristics and the change amount of the scattering angle distribution of the protein concentration index within the corresponding window is carried out, including: 301. Extract the phase angle interval of the vibration waveform zero-crossing point from the periodic fluctuation characteristics of the vibration frequency offset amount, and the phase angle interval covers the vibration period when the liquid infiltration reaches the saturation critical point during the dressing absorption of seepage; 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.

[0069] The saturation critical point refers to the state where the dressing absorbs seepage to the maximum capacity, corresponding to a specific phase angle of the vibration waveform (such as 180° - 270°).

[0070] 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 adsorption process, and 180° - 270° corresponds to the saturation critical point). The zero crossing point is 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.

[0071] 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, and the attenuation rate ratio reflects the change in scattering anisotropy caused by the protein aggregation state; In step 302, the attenuation rate ratio refers to the ratio of the attenuation rates of the backward scattered light intensity and the lateral scattered light intensity per unit time, and is used to characterize the change in scattering anisotropy caused by the protein aggregation state.

[0072] In the embodiments of the present application, based on the change amount of the scattering angle distribution, calculate the attenuation rate ratio of the backward scattered light intensity (150° - 180°) to the lateral scattered light intensity (90° ± 10°). For example, if the backward scattered light intensity decreases by 8% per minute and the lateral scattered light intensity decreases by 5% per minute, then the attenuation rate ratio is 8 / 5 = 1.6. This ratio reflects the enhanced scattering anisotropy caused by protein aggregation.

[0073] 303. 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 between the liquid infiltration saturation degree and the attenuation rate ratio within the phase angle interval; In step 303, the mapping rule refers to dividing the corresponding relationship between the liquid infiltration saturation degree and the attenuation rate ratio according to the ratio difference between fibrinogen and albumin.

[0074] The association mapping table is a lookup table that stores the corresponding relationship between the phase angle interval, the liquid infiltration saturation degree, and the attenuation rate ratio.

[0075] 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) types. For different types of exudates, an association mapping table is constructed. For fibrinogen-dominated exudates, phase angle > 200° and attenuation rate ratio > 1.5 → high saturation; for albumin-dominated exudates, phase angle > 240° and attenuation rate ratio > 1.2 → high saturation.

[0076] 304. Dynamically adjust the matching threshold between 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; In step 304, the liquid viscosity compensation coefficient is a parameter for dynamically adjusting the matching threshold of the ratio of the phase angle interval to the attenuation rate according to the seepage fluid viscosity.

[0077] 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), a relationship curve between the seepage fluid viscosity and the protein concentration is preset. For example, in the early high-viscosity stage (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 low-viscosity stage (viscosity < 20 cP), the phase angle interval is extended to 150° - 270°, and the attenuation rate ratio threshold is decreased by 5%.

[0078] 305. Generate a coupling parameter characterizing the coordinated change of the physical penetration and biochemical components of the seepage fluid based on the combined action of the association mapping table and the liquid viscosity compensation coefficient.

[0079] 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).

[0080] In the embodiments of the present application, a coupling parameter is generated based on the association mapping table and the liquid viscosity compensation coefficient. For example, with a phase angle of 220° and an attenuation rate ratio of 1.8, combined with the viscosity compensation coefficient (weight of 70% in the early high-viscosity stage), a coupling parameter of "high saturation + high protein aggregation" is generated.

[0081] The following is a specific example: For a patient after anal fistula surgery using the intelligent monitoring system, the phase angle interval of the zero-crossing point of the vibration waveform is extracted as 180° - 270°, determining that the liquid penetration is close to saturation; the attenuation rate of the backscattered light intensity is calculated as 8% / min, and the attenuation rate of the side-scattered light intensity is 5% / min, with an attenuation rate ratio of 1.6; the preoperative fibrinogen / albumin ratio of the patient is 0.06 (fibrinogen-dominated), and according to the mapping rule, a phase angle of 220° and an attenuation rate ratio of 1.6 → high saturation; on the 2nd day after surgery (viscosity 45 cP), the phase angle interval is compressed to 180° - 240°, and the attenuation rate ratio threshold is increased to 1.7; a coupling parameter of "high saturation + high protein aggregation" is generated, triggering an alarm.

[0082] In summary, steps 301 to 305 achieve the coordinated analysis of the physical penetration and biochemical component changes of the seepage fluid through the corresponding relationship between the vibration phase angle and the attenuation rate of the scattered light intensity. The generation of the coupling parameter significantly improves the evaluation accuracy (error < 5%), and the alarm response time is shortened to within 5 minutes, providing more comprehensive and accurate decision support for postoperative care.

[0083] To further improve the personalization and dynamic adaptability of postoperative effusion assessment, this method constructs an association mapping table based on the individual characteristics of patients through the collaborative analysis of preoperative blood indicators and real-time monitoring data. Specifically, through dynamic adjustment of the baseline ratio, protein aggregation grading, and cross-validation mechanism, multi-dimensional accurate mapping of the effusion state is achieved.

[0084] 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 effusion, and an association mapping table of the ratio of the liquid infiltration saturation to the attenuation rate within the phase angle interval is constructed, including: 401. Obtain the baseline ratio of fibrinogen to 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 effusion viscosity, and the grading threshold of the liquid infiltration saturation is divided within the phase angle interval; In step 401, the baseline ratio refers to the concentration ratio of fibrinogen to albumin in the preoperative blood test (such as fibrinogen 3 g / L: albumin 40 g / L → ratio 0.075).

[0085] The grading threshold of the liquid infiltration saturation is the effusion saturation level divided according to the product of the dressing absorption capacity (ml) and the effusion viscosity (cP) (such as low saturation is capacity × viscosity < 100, high saturation is ≥ 300).

[0086] In the embodiments of the present application, the baseline ratio is initialized based on the preoperative blood test results (such as fibrinogen / albumin = 0.08), combined with the dressing absorption capacity (vibration data) and the effusion viscosity (optical data) monitored in real time, calculate the capacity × viscosity value (such as capacity 5 ml × viscosity 50 cP = 250), and dynamically divide the saturation grading threshold (250 ∈ medium saturation). Adjust the phase angle interval range by the linear interpolation method (such as medium saturation corresponds to the phase angle 150° - 240°).

[0087] 402. Divide the protein aggregation state levels based on the change trend of the attenuation rate ratio; 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 (such as real-time ratio 0.10 → offset + 0.02).

[0088] The protein aggregation state level is divided into three levels of low, medium, and high according to the attenuation rate ratio (such as ratio < 1.0 is low aggregation, 1.0 - 1.2 is medium aggregation, ≥ 1.2 is high aggregation).

[0089] In the embodiments of the present application, based on the change trend of the attenuation rate ratio (such as rising from 1.0 to 1.5), the ratio offset is calculated in combination with 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 increased by one level), the protein aggregation state level is divided (offset +0.04 → high aggregation).

[0090] 403. According to the difference range between the baseline ratio and the ratio offset, the combined relationship between the liquid infiltration saturation grading threshold and the protein aggregation state level is divided into multiple groups of mapping rules, and each group of mapping rules corresponds to specific characteristics of the postoperative healing stage; In step 403, the difference range refers to the absolute difference between the baseline ratio and the ratio offset (such as baseline 0.08, real-time 0.12 → difference 0.04).

[0091] The mapping rule is the combined relationship between the liquid infiltration saturation grading threshold (low / medium / high) and the protein aggregation state level (low / medium / high) (such as high saturation + high aggregation → infection risk period).

[0092] 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.

[0093] 404. Through the collaborative analysis of the vibration energy integral value within the phase angle interval and the attenuation slope of the scattered light intensity, a cross-validation mechanism between the liquid infiltration saturation grading threshold and the protein aggregation state level is established. Based on the multiple groups of mapping rules and the cross-validation mechanism, an association mapping table of the liquid infiltration saturation and the attenuation rate ratio within the phase angle interval is generated.

[0094] In step 404, the vibration energy integral value refers to the energy accumulation amount of the vibration waveform within the phase angle interval, which is used to verify the accuracy of the liquid infiltration saturation grading.

[0095] The attenuation slope of the scattered light intensity refers to the decreasing rate of the scattered light intensity per unit time, which is used to verify the reliability of the protein aggregation state level.

[0096] In the embodiments of the present application, within the phase angle interval, the root mean square energy of the vibration waveform is calculated (such as the energy integral value of 1200 mV² in the interval of 150° - 240°), and the saturation level is verified (energy > 1000 mV² → high saturation). The attenuation slope of the scattered light intensity is calculated synchronously (such as a decrease of 8% per minute), and the aggregation level is verified (slope > 5% / min → high aggregation). The validity of the mapping rule is confirmed through a logical AND operation (high saturation AND high aggregation), and finally an associated mapping table is generated.

[0097] The following is a specific example: 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), 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), the scattered attenuation slope is 9% / min (> 5% → high aggregation), and the cross-validation confirms the validity of the mapping rule, generating an entry in the associated mapping table (medium saturation + high aggregation → the inflammatory reaction period).

[0098] In summary, steps 401 to 404 construct a personalized associated 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.

[0099] In order to further improve the accuracy and dynamic adaptability of postoperative exudate assessment, this method constructs multiple groups 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, the accurate determination of the postoperative healing stage is realized.

[0100] 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 groups of mapping rules, and each group of mapping rules corresponds to specific characteristics of the postoperative healing stage, including: 501. Determine the ratio change trend of fibrinogen to albumin based on the difference range between the baseline ratio and the ratio offset; In step 501, the ratio change trend refers to the change direction of the ratio of fibrinogen to albumin relative to the baseline ratio (a positive offset means an increase in the ratio; a negative offset means a decrease in the ratio).

[0101] In the embodiments of the present application, based on the preoperative blood test results, the baseline ratio of fibrinogen to albumin is obtained (such as fibrinogen 3.2 g / L: albumin 40 g / L → ratio 0.08), and the ratio offset is calculated by combining real-time monitoring data (such as real-time ratio 0.11 → offset +0.03). The ratio change trend is determined by 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 trend analysis.

[0102] 502. Define the critical points of the grading thresholds of the liquid infiltration saturation levels of low saturation, medium saturation, and high saturation according to the product relationship between the dressing absorption capacity and the exudate viscosity, 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 attenuation rate ratio; The critical point refers to the boundary value of the grading threshold of the liquid infiltration saturation level (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, and high saturation is ≥300).

[0103] 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, and high aggregation is ≥1.2).

[0104] 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 level are divided. Low saturation is when the capacity × viscosity <100 (such as capacity 2 ml × viscosity 30 cP = 60); medium saturation is when 100 ≤ capacity × viscosity <300 (such as capacity 5 ml × viscosity 50 cP = 250); high saturation is when the capacity × viscosity ≥300 (such as capacity 6 ml × viscosity 60 cP = 360); at the same time, based on the change trend of the attenuation rate ratio (such as rising from 1.0 to 1.5), the protein aggregation state levels are divided as follows: low aggregation is when the ratio <1.0 (such as 0.8); medium aggregation is when 1.0 ≤ ratio <1.2 (such as 1.1); high aggregation is when the ratio ≥1.2 (such as 1.5); by dynamically adjusting the grading thresholds and level ranges, the requirements of different postoperative healing stages are adapted.

[0105] 503. 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; In step 503, the first-level mapping relationship refers to the combined relationship between the proportional change trend (positive / negative offset) and the liquid infiltration saturation grading threshold (low / middle / high).

[0106] The second-level mapping relationship refers to the combined relationship between the first-level mapping relationship and the protein aggregation state level (low / middle / high).

[0107] In the embodiment of the present application, the proportional change trend (such as positive offset) is matched with the liquid infiltration saturation grading threshold (such as medium saturation) to generate the first-level mapping relationship (positive offset + medium saturation). For example, a positive offset indicates an increase in the fibrinogen ratio, and medium saturation indicates a moderate amount of exudate. After combination, it reflects the possibility of an inflammatory response.

[0108] The first-level mapping relationship (positive offset + medium saturation) is combined with the protein aggregation state level (such as high aggregation) to generate the second-level mapping relationship (positive offset + medium saturation + high aggregation). For example, high aggregation indicates a significant increase in protein concentration. After combination, it further confirms the characteristics of the inflammatory response period.

[0109] 504. Based on the superposition of the first-level mapping relationship and the second-level mapping relationship, multiple groups of mapping rules are divided, and each group of mapping rules corresponds to the characteristics of a specific postoperative healing stage.

[0110] 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.

[0111] In the embodiment 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 response 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 performance and accuracy of the evaluation results.

[0112] The following is a specific example: For a patient 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 proportional change trend is a 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; the first-level mapping relationship (positive offset + medium saturation) and the second-level mapping relationship (positive offset + medium saturation + high aggregation) are generated; the mapping rule "positive offset + medium saturation + high aggregation → inflammatory response period" is divided.

[0113] In summary, steps 501 to 504 construct an accurate postoperative healing stage determination rule through multi-level mapping of the proportional 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-making support for clinical practice.

[0114] 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 optical scattering measurement technology, combined with the calculation of multi-angle light intensity data and the anisotropy coefficient. Specifically, through the collection of light intensity at characteristic scattering angles, the calculation of the anisotropy coefficient, and the determination of the dynamic change range, a scattering spectrum analysis result representing the biochemical components of the exudate is generated.

[0115] In some embodiments, in step 102, the optical scattering measurement technology is used to perform scattering spectrum analysis on the wound exudate, including: 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, where the characteristic scattering angles include the forward scattering angle, the lateral scattering angle, and the backward scattering angle; 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°).

[0116] In the embodiments of the present application, the multi-angle optical scattering measurement technology is adopted. A specific wavelength beam (such as 650 nm) is emitted by a laser diode 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 acquisition consistency of multi-angle data is ensured through time synchronization technology.

[0117] 602. Calculate the anisotropy coefficient of the scattered light intensity distribution according to the light intensity data at the characteristic scattering angles, where the anisotropy coefficient reflects the spatial distribution characteristics of the protein aggregation state in the exudate; 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).

[0118] In the embodiments of the present application, the anisotropy coefficient is calculated based on the light intensity data of the characteristic scattering angle. For example, the ratio of the forward scattering light intensity (0° - 30°) to the backward scattering light intensity (150° - 180°) is 1.8, and the ratio of the lateral scattering light intensity (90° ± 10°) to the backward scattering light intensity is 1.2. Through ratio analysis, the spatial distribution characteristics of protein aggregation are determined (for example, a forward / backward ratio > 1.5 indicates that protein aggregation is mainly distributed in the forward region).

[0119] 603. Determine the dynamic change range of the protein concentration index based on the change trend of the anisotropy coefficient; 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).

[0120] 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.

[0121] 604. Generate a scattering spectrum analysis result through the collaborative analysis of the light intensity data of the characteristic scattering angle and the anisotropy coefficient, and the scattering spectrum analysis result is used to characterize the biochemical component characteristics of wound exudate.

[0122] In step 604, the scattering spectrum analysis result refers to the biochemical component characteristics of exudate (such as protein concentration, aggregation state) generated through the collaborative analysis of the light intensity data of the characteristic scattering angle and the anisotropy coefficient.

[0123] In the embodiments of the present application, the light intensity data of the characteristic scattering angle (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 a scattering spectrum analysis result. For example, when the forward light intensity is significantly higher than the backward light intensity (ratio > 1.5), combined with the dynamic change range (protein concentration of 3.5 g / L), it is determined as a high protein aggregation state.

[0124] The following is a specific example: For patients after anal fistula surgery, the intelligent monitoring system is used to collect the light intensity of 500 mV at the forward scattering angle (0° - 30°), 400 mV at the lateral scattering angle (90° ± 10°), and 300 mV at the backward scattering angle (150° - 180°); calculate the forward / backward ratio of 1.67 and the lateral / backward ratio of 1.33; according to the ratio of 1.67, determine the protein concentration of 3.5 g / L (> 3.0 g / L → abnormal range); generate the scattering spectrum analysis result "forward light intensity 500 mV, backward light intensity 300 mV, protein concentration 3.5 g / L → high protein aggregation state".

[0125] 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 scattering 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.

[0126] To improve the comprehensiveness and accuracy of the analysis of the scattering light intensity distribution of wound exudate, this method calculates the ratios of multi-angle light intensity data to generate longitudinal, transverse, and comprehensive anisotropy coefficients, realizing multi-dimensional characterization of the protein aggregation state. Specifically, through the ratio extraction and collaborative analysis of the forward, lateral, and backward scattering light intensities, the anisotropy coefficient of the scattering light intensity distribution is determined.

[0127] In some embodiments, in step 602, calculating the anisotropy coefficient of the scattering light intensity distribution based on the light intensity data at the characteristic scattering angle includes: 701. Based on the light intensity data of the forward scattering angle and the backward scattering angle at the characteristic scattering angle, extract the ratio of the forward scattering light intensity to the backward scattering light intensity to generate the longitudinal anisotropy coefficient; 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.

[0128] 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), calculate the longitudinal anisotropy coefficient (500 / 300 ≈ 1.67). Through ratio analysis, judge the distribution characteristics of macromolecular substances in the longitudinal direction (forward - backward) (such as a ratio > 1.5 indicating that macromolecular substances are mainly distributed in the forward region).

[0129] 702. Based on the light intensity data of the lateral scattering angle and 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; 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 backscattering angle (150° - 180°), and is used to characterize the transverse uniformity of the protein aggregation state in the seepage liquid.

[0130] In the embodiments of the present application, based on the light intensity data at the lateral scattering angle (such as 400 mV) and the light intensity data at the backscattering angle (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 (for example, a ratio < 1.5 indicates that the protein distribution is relatively uniform).

[0131] 703. Extract the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient according to the ratio of the longitudinal anisotropy coefficient to the transverse anisotropy coefficient, and generate a comprehensive anisotropy coefficient; 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 seepage liquid.

[0132] 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 (for example, a ratio > 1.2 indicates that the protein is mainly concentrated in the forward region and the distribution is uneven).

[0133] 704. Determine the anisotropy coefficient of the scattered light intensity distribution through the collaborative analysis of the longitudinal anisotropy coefficient, the transverse anisotropy coefficient and the comprehensive anisotropy coefficient.

[0134] 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, and is used to characterize the scattered light intensity distribution characteristics of the seepage liquid.

[0135] 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 forward aggregation of macromolecular substances, a transverse coefficient < 1.5 indicates relatively uniform protein distribution, and a comprehensive coefficient > 1.2 indicates uneven overall distribution.

[0136] The following is a specific example: For patients 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 → longitudinal anisotropy coefficient is 1.67; the lateral scattered light intensity is 400 mV, and the backward scattered light intensity is 300 mV → transverse anisotropy coefficient is 1.33; longitudinal coefficient 1.67 / transverse coefficient 1.33 → comprehensive anisotropy coefficient is 1.26; the anisotropy coefficients determining the scattered light intensity distribution are "longitudinal 1.67, transverse 1.33, comprehensive 1.26", and it is determined that there is forward aggregation of macromolecules and uneven distribution.

[0137] In summary, steps 701 to 704 calculate and perform collaborative analysis on the ratios of multi-angle light intensity data to generate anisotropy coefficients characterizing the scattered light intensity distribution of exudate, significantly improving the comprehensiveness and accuracy of protein aggregation state detection (error < 5%). The dynamic monitoring of anisotropy coefficients provides more reliable biochemical index support for postoperative care, and the abnormal detection response time is shortened to within 2 minutes.

[0138] Figure 2 The following 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: 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 wound exudate through the vibration sensor, where the vibration frequency offset amount is associated with the dressing weight change amount; An exudate component optical analysis module 22, configured to perform scattering spectrum analysis on the wound exudate 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; An exudate dynamic data fusion module 23, 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 exudate components; A wireless remote monitoring and warning module 24, configured to remotely synchronously compare the dynamic change curve of exudate components 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 protein threshold range at different rehabilitation stages; A healing stage curve management module 25, configured to trigger a remote warning signal for abnormal wound healing when there are continuously vibration frequency offset amounts exceeding the standard exudate volume in the dynamic change curve of exudate components and the protein concentration index is detected to break through the protein threshold range.

[0139] Figure 2 The described postoperative nursing and rehabilitation evaluation system for anorectal surgery can execute Figure 1For a method for evaluating the postoperative nursing and rehabilitation of anorectal surgery described in the illustrated embodiment, its implementation principle and technical effects will not be elaborated further. For a system for evaluating the postoperative nursing and rehabilitation of anorectal surgery in the above embodiment, the specific manners in which each module and unit perform operations have been described in detail in the embodiments related to this method, and will not be elaborated here.

[0140] In a possible design, Figure 2 An apparatus for evaluating the postoperative nursing and rehabilitation of anorectal surgery in the illustrated embodiment can be implemented as a computing device, such as Figure 3 shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32.

[0141] The processing component 32 is used for the Figure 1 method for evaluating the postoperative nursing and rehabilitation of anorectal surgery in the above

[0142] embodiment. Among them, the processing component 32 may 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 may 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 for executing the above method.

[0143] The storage component 31 is configured to store various types of data to support operations on 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 disk.

[0144] Of course, the computing device may also necessarily include other components, such as input / output interfaces, display components, communication components, etc.

[0145] The input / output interface provides an interface between the processing component and the peripheral interface module, and the above peripheral interface module may be an output device, an input device, etc.

[0146] The communication component is configured to facilitate wired or wireless communication between the computing device and other devices, etc.

[0147] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server. The above processing components, storage components, etc. can be basic server resources leased or purchased from a cloud computing platform.

[0148] The embodiments of the present application also provide 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 Figure 1 shown embodiment.

[0149] Those skilled in the art can clearly understand that for the convenience and brevity 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.

[0150] 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 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.

[0151] 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 this 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. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0152] 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. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment 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 amount; Performing scattering spectrum analysis on the wound exudate by using optical scattering measurement technology, and analyzing the protein concentration index by resolving 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, by means of 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 vibration frequency offsets exceeding the standard exudate volume continuously appear 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, wherein 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 partitioning 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, characterized in that, 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, wherein 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 the 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 exudate viscosity 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, wherein 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. 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. 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. 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. 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.

5. The method according to claim 4, wherein 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 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 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 ranges 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, characterized in that Perform scattering spectrum analysis on the wound exudate 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, characterized in that, According to the light intensity data of the characteristic scattering angles, calculating the anisotropy coefficient of the scattered light intensity distribution 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 to 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 to 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 to 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 detect the vibration frequency offset amount after the dressing absorbs wound exudate in real time 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 to generate a dynamic change curve of exudate components; A wireless remote monitoring and warning module, configured to remotely synchronously compare the dynamic change curve of exudate components 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 protein threshold range at different rehabilitation stages; 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 exudate components and the protein concentration index is detected to break through the protein threshold range at the same time.

9. A computing device, characterized in that, It includes 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 method for evaluating postoperative nursing and rehabilitation in anorectal surgery as described in 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 the postoperative nursing and rehabilitation of anorectal surgery as described in any one of claims 1 to 7.

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