Diabetic wound composite material detection method and system

Abstract

The present application relates to the technical field of diabetic wound detection, and in particular to a diabetic wound composite material detection method and system, the method comprising the following steps: obtaining original first detection information of the first functional area and original second detection information of the second functional area in a time-related manner through an external non-invasive detection device; determining a background reference quantity based on the obtained original second detection information, the background reference quantity representing the combined effect of the detection information caused by the absorption of exudate by the dressing and the local physical form difference caused by uneven dressing; combining the non-invasive detection method capable of obtaining the detection information of the two areas and removing the background interference through comparative analysis, thereby effectively dealing with the interference of the physical changes of the dressing itself and uneven dressing on the detection signal of the biochemical indicators of the wound.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of diabetic wound detection, in particular to a diabetic wound composite material detection method and system. BACKGROUND

[0002] Diabetic skin ulcers, especially in areas with poor blood circulation, heal slowly and are susceptible to infection, which can lead to serious complications such as amputation. Traditional care requires frequent removal of dressings to assess wound size, depth, color, granulation, and exudate, but is highly dependent on experience and subjective, and destroys the wet healing environment, increases the risk of infection and nursing burden. In response to this, the industry has proposed a new detection scheme: using a special composite material dressing containing a response unit. In addition to the basic functions, the response unit in the matrix of the dressing can sense specific biochemical indicators (such as abnormal pH, specific enzyme activity, bacterial metabolites) in the wound exudate and trigger detectable changes in its own or local dressing physical properties (such as optical, electrical, thermal properties)

[0003] In order to achieve non-invasive monitoring of these changes in the physical properties of the dressing caused by the response unit, the scheme also includes a matching external detection device. This device can obtain information by scanning or locally detecting the surface of the dressing without removing the dressing. For example, the detection device can emit a detection signal and receive a return signal or a transmission signal, and by analyzing the changes in the signal, it can indirectly sense the changes in the physical properties of a specific area inside the dressing, and thus infer the state of the response unit.

[0004] However, in practical applications, this scheme faces significant technical challenges. The amount and nature of the diabetic wound exudate changes dramatically during the healing process, and the physical state of the composite material dressing changes significantly when it absorbs the exudate. After the dressing absorbs a large amount of exudate, its macroscopic physical parameters such as water content, thickness, density, dielectric properties, and electrical conductivity will change significantly. These changes in physical properties caused by the overall absorption behavior of the dressing may be much larger than the small local physical property changes caused by the response unit's reaction to specific biochemical indicators, thus forming strong background interference in the original detection signal obtained by the external detection device, severely affecting the extraction of the effective signal. In addition, the irregular shape of the wound leads to uneven dressing application (local fit, pressure, or deformation differences), resulting in different physical properties such as thickness, density, and contact efficiency in different areas of the dressing. This unevenness further complicates the modulation of the detection signal.

[0005] Therefore, simply measuring changes in a certain physical property of the dressing and directly attributing them to the response unit's reaction will not guarantee the reliability and accuracy of the detection results. This approach urgently needs an advanced information processing method that can effectively distinguish and compensate for signal fluctuations caused by differences in the degree of exudate absorption by the dressing itself and the differences in the physical morphology of the dressing at different locations. This would allow for the stable and accurate extraction, from strong background interference and complex modulation, of the specific changes in the local physical properties of the dressing caused solely by the actual response of the response unit to the target biochemical indicator, thus enabling a reliable assessment of the condition of diabetic wounds.

[0006] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0007] The purpose of this invention is to address the shortcomings of existing technologies by proposing a method and system for detecting composite materials in diabetic wounds.

[0008] In a first aspect, the present invention provides a method for detecting composite materials in diabetic wounds, applied to a composite dressing, the composite dressing having at least one first functional area and at least one second functional area, characterized in that the method includes the following steps:

[0009] Using an external non-invasive detection device, the original first detection information of the first functional area and the original second detection information of the second functional area are acquired in a time-correlated manner.

[0010] Based on the acquired original second detection information, a background reference quantity is determined. The background reference quantity characterizes the combined influence on the detection information formed by the dressing's absorption of exudate and the local physical morphological differences caused by uneven application of the dressing.

[0011] Based on the acquired original first detection information and the determined background reference quantity, a target feature quantity is extracted through a preset comparative analysis operation. The target feature quantity characterizes the specific change in the detectable physical property of the response unit in the first functional region due to the response to a specific biochemical index.

[0012] Secondly, a composite material detection system for diabetic wounds is provided, the system comprising:

[0013] The information acquisition module is used to acquire the original first detection information of the first functional area and the original second detection information of the second functional area in a time-correlated manner through an external non-invasive detection device.

[0014] The background reference determination module is used to determine a background reference based on the acquired original second detection information;

[0015] The target feature extraction module is used to extract a target feature based on the acquired original first detection information and the determined background reference quantity through a preset comparative analysis operation. The target feature quantity characterizes the specific change in the detectable physical property of the response unit in the first functional region due to the response to a specific biochemical index.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] By acquiring detection information from the first and second functional regions, determining a background reference quantity based on the information from the second functional region, and then using the background reference quantity to extract target feature quantities from the information from the first functional region, the interference of changes in the physical state of the dressing itself (such as liquid absorption or uneven application) on the detection signal is effectively eliminated. This allows for the accurate extraction of the specific response information of the response unit to specific biochemical indicators, thus improving the accuracy and reliability of the detection. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method of the present invention.

[0019] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0020] In the diagram: 201, Information Acquisition Module; 202, Background Reference Quantity Determination Module; 203, Target Feature Quantity Extraction Module. Detailed Implementation

[0021] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0022] This application is as follows Figure 1The method for detecting composite materials in diabetic wounds is applied to a composite dressing. The composite dressing has at least one first functional region and at least one second functional region. The first functional region includes a response unit sensitive to a specific biochemical indicator of the wound. After the response unit reacts with the specific biochemical indicator, it causes a change in the locally detectable physical properties of the dressing in the first functional region. The physical properties of the matrix material of the second functional region have a predetermined correlation with the physical properties of the matrix material of the first functional region. The second functional region does not respond to the specific biochemical indicator, or its response characteristics have a predetermined distinguishable difference from the response characteristics of the first functional region. Furthermore, the second functional region and the first functional region have a predetermined relative spatial relationship. The method includes the following steps:

[0023] Using an external non-invasive detection device, the original first detection information of the first functional area and the original second detection information of the second functional area are acquired in a time-correlated manner.

[0024] Based on the acquired original second detection information, a background reference value is determined. The background reference value characterizes the combined influence on the detection information formed by the dressing's absorption of exudate and the local physical morphological differences caused by uneven application of the dressing.

[0025] Based on the acquired original first detection information and the determined background reference quantity, a target feature quantity is extracted through a preset comparative analysis operation. The target feature quantity characterizes the specific change in detectable physical properties of the response unit in the first functional region due to the response to a specific biochemical index.

[0026] Composite dressings refer to medical dressings composed of multiple layers or components, which can be achieved by combining materials such as hydrogels, foams, fiber meshes, and films. Their primary purpose is to cover and protect the wound while also possessing specific functionalities. The first functional area refers to a region on the dressing specifically designed to sense biochemical changes in the wound. This can be achieved by uniformly dispersing or locally concentrating response units within the dressing matrix, primarily to convert wound biochemical signals into detectable physical signals. Response units sensitive to specific biochemical indicators of the wound refer to components capable of chemically or physically interacting with specific substances (such as pH, enzymes, and metabolites) in the wound exudate. These can be achieved using chemical indicators, biomolecules, etc. The first functional area is achieved through probes and functionalized nanomaterials, primarily for the specific identification and response to key indicators of the wound microenvironment. The change in the locally detectable physical properties of the dressing in the first functional area refers to the measurable change in a certain physical property (e.g., dielectric constant, conductivity, optical properties, thermal conductivity) caused by the response unit. This can be achieved by altering the structure of the response unit or releasing substances that affect the physical properties of the matrix, primarily to provide a non-invasive detection method. The second functional area refers to the area on the dressing used as a reference or control. It can be achieved by using the same matrix material as the first functional area but without response units or containing insensitive response units, primarily to... A benchmark for assessing background interference is provided; the physical properties of the matrix material in the second functional area have a pre-defined correlation with those in the first functional area, meaning that the dressing matrices in the two areas exhibit similar or predictable relationships in physical behaviors such as exudate absorption and pressure deformation. This can be achieved by using materials with the same or similar physical properties, primarily to ensure that the second functional area can effectively simulate the non-biochemical factors affecting the first functional area; the second functional area does not respond to specific biochemical indicators or its response characteristics have a pre-defined, distinguishable difference from the response characteristics of the first functional area, meaning that the second functional area is not affected or is minimally affected by specific biochemical indicators of the wound, or its response... The method differs significantly from that of the first functional area. It can be achieved by not adding or adding non-sensitive components to the second functional area, mainly to isolate biochemical signals so that they are primarily reflected in the first functional area. The second functional area and the first functional area have a preset relative spatial relationship, meaning that the positions of the two areas on the dressing are fixed and known. This can be achieved by setting the two areas adjacent to each other or at a certain distance, mainly to facilitate synchronous or correlated detection by external detection devices. External non-invasive detection devices refer to devices that can obtain information without penetrating the dressing. These can be implemented using electromagnetic wave detectors, capacitive sensors, infrared thermal imagers, etc., mainly to avoid interfering with the wound by removing the dressing.Acquiring information in a time-correlated manner refers to detecting two areas at similar or synchronous time points. This can be achieved through scanning or simultaneous multi-point detection, primarily to ensure that the acquired information reflects the dressing's condition under similar physical conditions. The original first and second detection information refer to the unprocessed raw signals directly acquired by the external detection device from the two areas. These can be implemented using voltage signals, current signals, reflected / transmitted wave parameters, etc., primarily to provide input for subsequent data processing. The background reference quantity refers to the numerical value or model extracted from the information of the second functional area to quantify the impact of the dressing's own physical changes on the detection signal. This can be implemented using the original detection information of the second functional area itself or processed parameters, primarily to characterize the signal changes caused by the dressing absorbing exudate and uneven application. The dressing absorbs exudate... The combined effect of uneven dressing application leading to local physical morphological differences on detection information refers to the comprehensive interference generated by factors such as increased dressing moisture content, changes in thickness, and density on external detection signals, which is mainly the primary source of background noise. The preset comparative analysis operation refers to the processing algorithm or model used to remove or compensate for noise from the original first detection information containing both signal and noise, extracting the target signal. This can be achieved using differential, ratio, regression analysis, machine learning models, etc., primarily to separate effective information from the mixed signal. The target feature quantity refers to the numerical value or parameter extracted after comparative analysis that accurately reflects the changes in the true state of the response unit. This can be achieved using signal strength difference, parameter change rate, model output value, etc., primarily used to characterize the specific changes in the physical properties of the dressing caused by specific biochemical indicators of the wound.

[0027] This application's solution establishes a first functional region and a second functional region with different response characteristics on a composite dressing, and uses an external non-invasive detection device to acquire detection information from these two regions, thus providing a foundation for subsequent data processing. The reason for having two regions is that the first functional region is used to sense wound biochemical indicators, and its detection information includes signals caused by biochemical reactions as well as background interference caused by physical changes in the dressing itself (such as absorption and uneven application). The second functional region, on the other hand, is designed to primarily reflect the physical changes in the dressing itself, and is insensitive to biochemical indicators or exhibits significant response differences; therefore, its detection information mainly characterizes background interference. It is precisely because information from these two regions can be acquired separately when they are temporally correlated that a background reference value can be determined based on the information from the second functional region. This background reference value can quantify the combined effect of the dressing's physical changes on the detection signal. Furthermore, by performing pre-defined comparative analysis operations—such as difference calculation, scaling correction, or more complex model processing—on the acquired raw first detection information and the determined background reference quantity, background interference components can be effectively removed from the raw first detection information. This allows for the extraction of the specific changes in detectable physical properties truly caused by the response unit within the first functional area in response to specific biochemical indicators; that is, the target characteristic quantity. This target characteristic quantity eliminates interference from the physical changes of the dressing itself, and can more accurately reflect the biochemical state of the wound microenvironment, thereby achieving a reliable assessment of the condition of diabetic wounds.

[0028] As one embodiment of the present invention, based on the acquired original first detection information and the determined background reference quantity, a target feature quantity is extracted through a preset comparative analysis operation. The step of the target feature quantity characterizing the specific change in the detectable physical properties of the response unit in the first functional region due to the response to a specific biochemical index includes:

[0029] Obtain state parameters that characterize the physical environment of the composite dressing in the first and second functional regions. The state parameters include information derived from the original second detection information.

[0030] Based on a predetermined first correspondence and a second correspondence, wherein the first correspondence characterizes the association between the state parameter and the response sensitivity or response amplitude of the response unit to a specific biochemical indicator, and the second correspondence characterizes the association between the state parameter and the background reference quantity on the accuracy of characterizing the background interference component in the original first detection information;

[0031] Based on the acquired state parameters and according to the first and second correspondences, adjust the preset comparative analysis operation's calculation factors or calculation process for extracting target features based on the acquired original first detection information and the determined background reference quantity;

[0032] The adjusted comparative analysis operation is performed. Using the acquired original first detection information, the determined background reference quantity, and the adjusted operation factor or operation process, the target feature quantity is extracted. The target feature quantity characterizes the specific change in the detectable physical properties of the response unit in the first functional region due to the response to a specific biochemical index.

[0033] Among them, the state parameters refer to the values ​​or sets of indicators used to quantitatively describe the physical environmental state of the composite dressing in the first and second functional regions. These can be physical quantities such as temperature, humidity, and pressure, or characterized by environmentally relevant signal features extracted from the original second detection information. The information derived from the original second detection information refers to the extraction of signal components related to environmental factors through analysis and processing of the detection signals in the second functional region. This can be achieved using techniques such as signal processing, feature extraction, and model analysis. The first correspondence relationship refers to the preset rules, models, or data structures characterizing the relationship between the state parameters and the response sensitivity or response amplitude of the response unit to a specific biochemical indicator. This can be predetermined using methods such as experimental calibration, data fitting, and machine learning. The second correspondence relationship refers to the relationship between the state parameters and the accuracy of the background reference quantity in characterizing the background interference components in the original first detection information. The pre-defined rules, models, or data structures of the comparison analysis can be predetermined using methods such as experimental calibration, data fitting, and machine learning. The operational factors refer to the numerical parameters used in the pre-defined comparison analysis operation to process the original first detection information and background reference quantities; these can take the form of coefficients, weights, thresholds, etc. The operational process refers to the sequence of steps or algorithmic logic executed in the pre-defined comparison analysis operation; these can employ specific calculation formulas, filtering algorithms, noise reduction methods, or feature combinations. Adjusting the operational factors or operational process used in the pre-defined comparison analysis operation to extract target features based on the acquired original first detection information and determined background reference quantities refers to dynamically modifying the operational factors or operational process used to process the original first detection information and background reference quantities according to the acquired state parameters and based on the first and second correspondences. This can be achieved by modifying the operational factor values, switching operational process branches, or adjusting processing parameters.

[0034] The solution proposed in this application overcomes the influence of physical environment conditions on the accuracy of target feature extraction in existing technologies because it further incorporates consideration of the physical environment conditions of the dressing, building upon the aforementioned detection information from the first and second functional regions and background reference values. By acquiring state parameters characterizing the physical environment conditions, and by including information derived from the original second detection information, the influence of environmental factors on the detection signal can be accurately quantified. Simultaneously, the insensitivity of the second functional region to biochemical indicators is utilized to more purely reflect environmental interference. Based on pre-determined first and second correspondences, these correspondences establish a relationship between the environmental state and the response sensitivity of the response unit, as well as the accuracy of the environmental state and the background reference value, enabling the system to understand the signal variation patterns under different environmental conditions. By dynamically adjusting the computational factors or processes used to extract target features in the pre-defined comparative analysis operation based on the acquired state parameters and these correspondences, the comparative analysis process can adapt to the specific environmental conditions, thereby more effectively deducting or compensating for the interference components represented by the background reference value from the original first detection information, and accurately separating the specific changes caused by the response unit's response to specific biochemical indicators. It is by performing this adjusted comparative analysis operation, using the original first detection information, the determined background reference quantity, and the adjusted operation factor or operation process, that more accurate target feature quantities can be extracted, truly reflecting the biochemical changes of the wound microenvironment.

[0035] As one embodiment of the present invention, the step of adjusting the operation factor or operation process in the preset comparison analysis operation for extracting target feature quantities based on the acquired original first detection information and the determined background reference quantity, according to the acquired state parameters and based on the first correspondence and the second correspondence, includes:

[0036] Acquire the detection information of the first functional area, the detection information of the second functional area, and the calibration period status parameters when the preset calibration conditions are met. The calibration period status parameters characterize the physical environment state of the composite material dressing in the first and second functional areas when the preset calibration conditions are met.

[0037] To obtain a reference baseline for specific biochemical indicators of the wound when the preset calibration conditions are met;

[0038] Based on the detection information of the first functional area when the preset calibration conditions are met, the status parameters during the calibration period, and the reference benchmarks of specific biochemical indicators of the wound, the first correspondence is updated to obtain the updated first correspondence.

[0039] Based on the first functional area detection information when the preset calibration conditions are met, the second functional area detection information when the preset calibration conditions are met, and the calibration period status parameters, the second correspondence is updated to obtain the updated second correspondence.

[0040] Based on the acquired state parameters and according to the updated first correspondence and the updated second correspondence, adjust the preset comparative analysis operation's calculation factors or calculation process used to extract target features based on the acquired original first detection information and the determined background reference quantity.

[0041] Among them, "when the preset calibration conditions are met" refers to the achievement of specific conditions or states set in advance to initiate the calibration process. These conditions or states can be based on time intervals, dressing usage duration, changes in specific state parameters, or abnormal signals detected by the detection system. The purpose is to trigger the calibration process when the system deems it necessary or opportune for calibration. "Calibration period state parameters" refers to indicators characterizing the physical environment state of the composite dressing in the first and second functional areas when the preset calibration conditions are met. These parameters can include the dressing's moisture content, temperature, pressure, and thickness. Their purpose is to reflect the dressing's physical state at the time of calibration, serving as an important input for correcting the correspondence during the calibration process. "Reference benchmarks for specific biochemical indicators of the wound" refers to indicators obtained independently of dressing detection when the preset calibration conditions are met. The first correspondence is calibrated by obtaining the true or reference values ​​of specific biochemical indicators of the wound through a measurement system. These values ​​are used as known quantities to evaluate the actual response of the dressing response unit under these specific state parameters. Updating the first and second correspondences refers to the process of correcting or adjusting the predetermined first and second correspondences based on information obtained during the calibration period. The purpose is to make the correspondences more accurately reflect the current or recent situation and improve their predictive or mapping capabilities. The updated first and second correspondences refer to the first and second correspondences corrected through the calibration process. These updated correspondences are used for subsequent comparative analysis adjustments to improve the accuracy of target feature extraction.

[0042] Specifically, when the preset calibration conditions are met, the system acquires the detection information of the first functional area, the detection information of the second functional area, and the calibration period state parameters, while simultaneously acquiring a reference benchmark for specific biochemical indicators of the wound. This calibration period data provides actual detection information under known wound biochemical and dressing physical states. Based on this calibration period data, the system can calculate the actual response of the first functional area response unit under the current state and the actual characterization capability of the background reference quantity against background interference. Based on these actual conditions, the system updates the pre-determined first correspondence (the correlation between characterizing state parameters and the response unit's sensitivity / amplitude) and second correspondence (the correlation between characterizing state parameters and the accuracy of the background reference quantity's characterization of background interference). The updated correspondence more accurately reflects the dynamic correlation between state parameters, dressing response, and background interference. Subsequently, during routine testing, the system acquires the current state parameters and, based on the updated first and second correspondences, more precisely adjusts the computational factors or computational processes used to extract target features from the original first detection information and background reference quantity. It is precisely because of this dynamic calibration and update mechanism that the system can adapt to the differences and changes in dressing use and between different individuals, effectively compensate for the influence of dressing status changes and background interference, and thus more accurately separate the target feature quantity generated by the actual response of the response unit from the original detection information.

[0043] As one embodiment of the present invention, the step of obtaining a reference benchmark for specific biochemical indicators of a wound when preset calibration conditions are met includes:

[0044] Identify the corresponding target calibration area of ​​the first functional area on the composite dressing on the wound surface;

[0045] Within the identified target calibration area, targeted measurements of specific biochemical indicators of the wound are performed to collect measurement data that characterizes the local biochemical state of the wound sensed by the first functional area.

[0046] Based on the collected measurement data, reference benchmarks for specific biochemical indicators of the wound were determined.

[0047] Among them, "identifying the corresponding target calibration area of ​​the first functional area on the composite dressing on the wound surface" refers to determining the precise location or range of a specific sensing area on the dressing on the actual wound surface. This can be achieved using image recognition technology, marker point positioning, or matching analysis based on the physical structure of the dressing and the morphology of the wound, with the aim of ensuring the spatial correspondence of subsequent measurement data. "Wound-specific biochemical indicators" refer to biochemical substances or their activity levels closely related to the healing or infection status of diabetic wounds, such as the pH value of wound exudate, matrix metalloproteinase (MMP) activity, glucose concentration, or concentration of certain inflammatory factors. These can be detected using chemical reagent reactions, enzymatic reactions, or biosensor principles, with the aim of reflecting the microenvironmental state of the wound. "Targeted measurement" refers to obtaining specific biochemical indicators of the reference benchmark as needed and performing precise measurements using specialized detection methods or equipment. This can be achieved using micro-sampling combined with... The purpose of this method is to obtain quantitative data directly related to the target indicator, either through volume analysis or by using a portable detector capable of detecting specific indicators for local detection. "Measurement data that characterizes the local biochemical state of the wound sensed by the first functional area" refers to numerical values ​​or signals obtained through targeted measurements that reflect the actual level of specific biochemical indicators in the wound microenvironment beneath the first functional area of ​​the dressing. These values ​​can be expressed as concentration values, activity units, changes in optical density, or electrochemical signals, and their purpose is to provide an objective basis for determining the reference benchmark. "Determining the reference benchmark for specific biochemical indicators of the wound" refers to calculating or setting a standard value or reference range representing that specific biochemical indicator under the current preset calibration conditions based on the collected measurement data. This can be achieved through methods such as averaging, statistical analysis, or comparison with preset standard values, and its purpose is to provide a reliable reference point for subsequent calibration processes.

[0048] The proposed solution first identifies the corresponding target calibration area on the wound surface of the first functional area on the composite dressing. This ensures the spatial accuracy of subsequent measurement data, enabling the collected data to truly reflect the local wound state sensed by that specific functional area. Next, within this identified area, targeted measurements of specific biochemical indicators of the wound are performed to collect measurement data characterizing the local biochemical state sensed by the first functional area. This targeted measurement ensures the relevance and reliability of the data, avoiding interference from irrelevant factors. Finally, based on the collected measurement data, a reference benchmark for the specific biochemical indicators of the wound is determined. This reference benchmark is based on values ​​obtained from actual measurements that reflect the true local biochemical state of the wound. It is precisely this precise spatial positioning, targeted data collection, and reference benchmark determination based on actual measurements that allows the acquired reference benchmark to accurately reflect the true biochemical state of the wound when the preset calibration conditions are met. This accurate reference benchmark is then used to update the first correspondence, thereby improving the accuracy of the first correspondence in characterizing the correlation between state parameters and the response sensitivity or amplitude of the response unit. This accurate correspondence allows for more precise adjustment of the computational factors or processes during subsequent target feature extraction, thereby more effectively separating the specific changes generated by the actual response of the response unit from the original detection information. This overcomes background interference caused by the dressing's own absorption of liquid and uneven application, and improves the reliability of the detection results.

[0049] As one embodiment of the present invention, the step of updating the first correspondence relationship based on the first functional area detection information when the preset calibration conditions are met, the calibration period status parameters, and the reference benchmark of specific biochemical indicators of the wound, to obtain the updated first correspondence relationship includes:

[0050] Retrieve parameters of at least one historical first correspondence that was determined in a previous calibration cycle;

[0051] Based on the first functional area detection information obtained when the current preset calibration conditions are met, the calibration period status parameters, and the reference benchmark of specific biochemical indicators of the wound, a first correspondence indication parameter for the current calibration cycle is calculated.

[0052] Based on the preset parameter fusion mechanism, the parameters of the historical first correspondence are integrated with the calculated first correspondence indication parameters of the current calibration cycle to generate updated first correspondence parameters. The parameter fusion mechanism enables the updated first correspondence parameters to reflect the changing trend of historical parameters and incorporate the indication parameters of the current calibration cycle. Thus, based on the first functional area detection information when the preset calibration conditions are met, the calibration period status parameters, and the reference benchmark of specific biochemical indicators of the wound, the first correspondence is updated to obtain the updated first correspondence.

[0053] Among them, the parameter of the historical first correspondence refers to the numerical representation of the first correspondence determined and stored through the calibration process in at least one previous calibration period. It can be represented in the form of vector, matrix, or model coefficients. The first correspondence indication parameter of the current calibration period refers to a quantity that reflects the trend or value of the first correspondence under the current calibration state, calculated based on the calibration data obtained in the current calibration period. It can be represented in the form of vector, numerical, or index, which may be the same as or different from the historical parameter. The preset parameter fusion mechanism refers to a pre-set algorithm or rule used to mathematically or logically combine the parameter of the historical first correspondence with the first correspondence indication parameter of the current calibration period to generate a first correspondence parameter that is more representative of the current and future states. It can be implemented using methods such as weighted average, exponential smoothing, Kalman filtering, or machine learning models.

[0054] Specifically, the system first acquires historical first correspondence parameters accumulated from previous calibration cycles. These historical parameters contain calibration information from different time points and environmental conditions, reflecting the trend of first correspondence changes over time or under different environments. Simultaneously, based on the latest detection information, state parameters, and reference benchmarks acquired when the current preset calibration conditions are met, the system calculates a first correspondence indication parameter for the current calibration cycle. This parameter reflects the system's calibration requirements in the current state. Subsequently, according to a preset parameter fusion mechanism, the historical parameters are integrated with the current indication parameter. This integration process is not a simple averaging or direct replacement, but rather, through a fusion mechanism, the final updated first correspondence parameter inherits the smoothness and trend information of historical data while also responding promptly to the latest changes indicated by the current calibration data. For example, the fusion mechanism can assign a higher weight to current data to quickly adapt to sudden changes, or a higher weight to historical data to resist transient noise. In this way, the updated first correspondence parameter can more accurately and stably characterize the relationship between the state parameter and the sensitivity of the response unit. Thus, in the subsequent target feature extraction process, the acquired state parameter can be used more effectively. Based on the updated first and second correspondences, the operation factors or processes in the comparative analysis can be adjusted, so that the target features extracted from the original detection information can more accurately reflect the specific changes of the response unit to specific biochemical indicators. This effectively suppresses background interference caused by dressing absorption and uneven application, and improves the accuracy and reliability of detection.

[0055] As one embodiment of the present invention, the step of adjusting the operation factor or operation process in the preset comparison analysis operation for extracting target feature quantities based on the acquired original first detection information and the determined background reference quantity, according to the acquired state parameters and the updated first correspondence and the updated second correspondence, includes:

[0056] A parameterized computation execution structure is established. The computation execution structure is used to accommodate and execute the computation logic for extracting target feature quantities from the original first detection information and the determined background reference quantity. The computation logic can be configured through computation parameters or path selection.

[0057] Based on the updated first correspondence, the updated second correspondence, and the obtained status parameters, determine the operation parameters used to configure the parameterized operation execution structure or select the preset operation path within the parameterized operation execution structure;

[0058] The determined computational parameters are applied to the parameterized computational execution structure, or the parameterized computational execution structure is configured according to the selected computational path, thereby adjusting the computational factors or computational process used in the preset comparative analysis operation to extract target features based on the acquired original first detection information and the determined background reference quantity.

[0059] In this context, a parameterized computation execution structure refers to a module or unit capable of performing computational tasks. Its internal computational processes or algorithms can be modified or selected through external input. Specifically, it can be a software module, a programmable logic device (such as an FPGA), or a dedicated integrated circuit. Its purpose is to provide a flexible computing platform to adapt to different data processing needs. The configurable computational logic, which can be selected through computational parameters or path selection, means that the computational steps, formulas, or algorithms executed within the computation execution structure are not fixed but can be adjusted based on input parameter values ​​(computational parameters) or different preset computational flows (preset computational paths) based on input instructions. Its purpose is to enable the computational process to be dynamically adjusted according to external conditions. Computational parameters refer to the specific values ​​or configuration information used to control the computational logic within the parameterized computation execution structure. Their purpose is to finely adjust coefficients, thresholds, or other computational elements during the computational process. Preset computational paths refer to predefined, selectable sequences of computational flows or algorithms within the parameterized computation execution structure. Their purpose is to provide different computational strategies to cope with different types of data or processing scenarios.

[0060] The solution proposed in this application provides a flexibly adjustable computational platform for extracting target features by establishing a parameterized computational execution structure. This structure can accommodate and execute the computational logic for extracting target features from the original first detection information and the determined background reference quantity. Crucially, this logic can be configured through computational parameters or path selection, meaning that the specific values ​​in the computation process can be changed or different computational flows can be selected based on different input conditions. This configurability makes subsequent dynamic adjustments possible. Based on the updated first correspondence, the updated second correspondence, and the acquired state parameters, the system can determine the computational parameters used to configure the parameterized computational execution structure or select the preset computational path within the parameterized computational execution structure. The updated first correspondence reflects the correlation between the state parameters and the response sensitivity or response amplitude of the response unit to a specific biochemical indicator, while the updated second correspondence reflects the correlation between the state parameters and the accuracy of the background reference quantity in representing background interference components in the original first detection information. By comprehensively utilizing information reflecting the dressing's response characteristics and background interference characteristics under the current physical environment, the system can intelligently determine how to adjust the computational execution structure to maximize the removal of background interference from the original detection information and accurately extract target features. Finally, the determined computational parameters are applied to the parameterized computational execution structure, or a parameterized computational execution structure is configured according to the selected computational path, thereby adjusting the computational factors or computational flow used to extract target features in the preset comparative analysis operation. This adjustment allows the extraction process of target features to dynamically adapt to the actual physical environment of the dressing and changes in the dressing's own characteristics, thus improving the accuracy and reliability of the extraction results. This dynamic adjustment mechanism, combined with the steps of obtaining original detection information, determining background reference quantities, and initially extracting target features in the basic scheme, forms a complete solution that effectively addresses background interference caused by dressing absorption and uneven application, significantly improving the robustness of the detection method.

[0061] As one embodiment of the present invention, the step of determining the operation parameters for configuring the parameterized operation execution structure or selecting the preset operation path within the parameterized operation execution structure based on the updated first correspondence, the updated second correspondence, and the obtained state parameters includes:

[0062] Construct a multidimensional mapping function;

[0063] The updated first correspondence, the updated second correspondence, and the obtained state parameters are used as inputs to the multidimensional mapping function;

[0064] The computational parameters or computational paths used to configure the parameterized computational execution structure are calculated through the multidimensional mapping function.

[0065] The multidimensional mapping function refers to a mathematical or logical relationship that maps multiple input variables (e.g., the updated first correspondence, the updated second correspondence, and state parameters) to one or more output variables (e.g., operational parameters or operational paths). It can be implemented using lookup tables, mathematical formulas, neural network models, or rule-based expert systems, with the aim of determining an appropriate configuration output based on the comprehensive information of the inputs. The updated first correspondence, after calibration, represents the data or model characterizing the relationship between state parameters and the response sensitivity or response amplitude of the response unit to a specific biochemical indicator, aiming to provide information on the response characteristics of the response unit under the current physical environment. The updated second correspondence, after calibration, represents the relationship between state parameters and the background reference... The data or model relating the accuracy of the representation of background interference components in the original first detection information to the quantity aims to provide information on the background compensation capability of the background reference quantity under the current physical environment conditions; the state parameter refers to the data representing the physical environment state indicators of the composite dressing in the first and second functional areas, which includes information derived from the original second detection information, and aims to reflect the current physical environment state of the dressing, such as moisture content, temperature, and pressure conditions; the operation parameter refers to the specific values ​​or configuration items used to adjust the operation logic in the parameterized operation execution structure, and aims to finely control the calculation process of the comparative analysis operation; the operation path refers to the preset and selectable operation flow branches in the parameterized operation execution structure, and aims to select and execute different calculation flows according to the input information.

[0066] The proposed solution constructs a multidimensional mapping function, using the updated first correspondence, the updated second correspondence, and state parameters as inputs to calculate the computational parameters or paths for configuring the parameterized computational execution structure. Since the updated first correspondence reflects the response characteristics of the response unit in the current physical environment, the updated second correspondence reflects the background compensation capability of the background reference in the current physical environment, and the state parameters directly characterize the current physical environment state, this information is comprehensively input into the multidimensional mapping function. This function can learn or pre-set how to determine the optimal computational parameters or paths based on this comprehensive information. This allows the parameterized computational execution structure to adaptively adjust according to the dynamic changes in the dressing and wound surface, as well as the calibrated correlation, thereby performing the most suitable comparative analysis operation for the current state.

[0067] As one embodiment of the present invention, the step of calculating the operation parameters or operation path for configuring the parameterized operation execution structure through a multidimensional mapping function includes:

[0068] By using a multidimensional mapping function and applying a preset combination of weighting coefficients and offsets, the updated first correspondence, the updated second correspondence, and the obtained state parameters are transformed into operation parameters, thereby calculating the operation parameters used to configure the parameterized operation execution structure.

[0069] Alternatively, by using a multidimensional mapping function, the updated first correspondence, the updated second correspondence, and the obtained state parameters are compared with a preset threshold or range to determine and select the operation path, thereby calculating the operation path used to configure the parameterized operation execution structure.

[0070] Among them, a multidimensional mapping function refers to a mathematical model or algorithm used to map multiple input variables to one or more output variables. It can be implemented using lookup tables, mathematical formulas, machine learning models, etc., and its purpose is to transform complex input information into parameters or paths that can be used to configure the computational execution structure. Preset weighting coefficients and offset combinations refer to the coefficients and constants used to perform linear or nonlinear transformations on the input of the multidimensional mapping function, aiming to adjust the influence weights and benchmarks of different input parameters on the output computational parameters. Computational parameters refer to variables used to adjust the internal computational logic or numerical values ​​of the parameterized computational execution structure, aiming to finely configure the computational execution structure to optimize comparative analysis operations. Computational paths refer to the preset, selectable different computational flows or algorithm branches within the parameterized computational execution structure, aiming to... The system can quickly switch computational strategies based on input parameters to adapt to different dressings and environmental conditions. The preset threshold or range refers to the criteria used to compare with the input of the multidimensional mapping function to determine which computational path to select. Its purpose is to provide a basis for path selection based on input parameters. The updated first correspondence, the updated second correspondence, and the state parameters refer to the input of the multidimensional mapping function. They respectively characterize the correlation between the state parameters and the response sensitivity or response amplitude of the response unit to a specific biochemical indicator, the correlation between the state parameters and the background reference quantity to the accuracy of characterizing the background interference components in the original first detection information, and the physical environmental state indicators of the composite dressing in the first and second functional regions. Their purpose is to provide the multidimensional mapping function with key information reflecting the dressing and environmental state.

[0071] The proposed solution uses a multi-dimensional mapping function to take the updated first correspondence, the updated second correspondence, and state parameters as inputs. In the first implementation, the multi-dimensional mapping function applies a preset combination of weighting coefficients and offsets to transform these inputs into computational parameters. These computational parameters are then used to configure the parameterized computational execution structure, adjusting its internal computational logic or values. Since the input parameters reflect background interference caused by dressing absorption of exudate, uneven application, etc., as well as the sensitivity of the response unit, the combination of weighting and offsets allows for fine-tuning of the computational parameters based on this actual state information. This enables the comparative analysis operation to more accurately subtract background interference from the original first detection information and highlight the specific changes in the response unit. In the second implementation, the multi-dimensional mapping function compares the input parameters with a preset threshold or range, and determines and selects a preset computational path within the parameterized computational execution structure based on the comparison result. Different computational paths can correspond to different background subtraction algorithms, signal enhancement methods, or feature extraction strategies. By comparing with the threshold or range, the system can quickly switch to a computational path suitable for the current situation based on the category or degree of the dressing and environmental state, thereby improving the robustness and accuracy of the comparative analysis operation. Both methods utilize multidimensional mapping functions to effectively transform complex input information into a configuration of the computation execution structure, thereby optimizing the comparative analysis operation and extracting target features more accurately.

[0072] As one embodiment of the present invention, the step of integrating the parameters of the retrieved historical first correspondence with the calculated first correspondence indication parameters of the current calibration period according to a preset parameter fusion mechanism to generate updated parameters of the first correspondence includes:

[0073] Determine the historical parameter information used for the current parameter fusion calculation, including: designating the smoothed estimate vector of the "first correspondence" parameter determined in the previous calibration period, which is included in the parameters of the retrieved historical first correspondence, as the historical smoothed estimate vector S_historical, and designating the smoothed estimate vector of the change trend of the "first correspondence" parameter determined in the previous calibration period as the historical trend smoothed estimate vector B_historical; if the parameters of the retrieved historical first correspondence do not contain parameter information from the previous calibration period, then the historical smoothed estimate vector S_historical is the preset initial smoothed estimate vector S_init of the "first correspondence" parameter, and the historical trend smoothed estimate vector B_historical is the preset initial smoothed estimate vector B_init of the change trend of the "first correspondence" parameter;

[0074] Obtain the first correspondence indicator parameter P_indicator_curr of the current calibration cycle obtained from the calculation;

[0075] Based on the preset horizontal smoothing coefficient alpha, the preset trend smoothing coefficient beta, the obtained first correspondence indicator parameter P_indicator_curr of the current calibration period, the historical smoothing estimate vector S_historical, and the historical trend smoothing estimate vector B_historical, the updated parameters of the first correspondence are generated through the following calculations:

[0076] Calculate the smoothed estimate vector S_curr of the "first correspondence" parameters for the current calibration period. This S_curr represents the updated parameters of the first correspondence. The calculation formula is as follows:

[0077] S_curr=alpha*P_indicator_curr+(1-alpha)*(S_historical+B_historical);

[0078] The smoothed estimate vector B_curr of the changing trend of the "first correspondence" parameter for the current calibration period, which will be used in subsequent calibration periods, is calculated using the following formula:

[0079] B_curr=beta*(S_curr-S_historical)+(1-beta)*B_historical;

[0080] The parameters of the historical first correspondence refer to the set of parameters determined and stored during the calibration process in previous calibration cycles, used to characterize the correlation between state parameters and the sensitivity or amplitude of the response unit. These parameters can be represented using vectors, matrices, or other data structures. The smoothed estimate vector S_historical of the parameters of the "first correspondence" determined in the previous calibration cycle refers to the smoothed estimate of the current value of the "first correspondence" parameters calculated through the parameter fusion mechanism at the end of the calibration cycle immediately preceding the current calibration cycle. This can be represented using a multi-dimensional vector. The smoothed estimate vector B_historical of the changing trend of the parameters of the "first correspondence" determined in the previous calibration cycle refers to the smoothed estimate of the changing trend of the parameters of the "first correspondence" calculated through the parameter fusion mechanism at the end of the calibration cycle immediately preceding the current calibration cycle. This can be represented using a vector of the same dimension as S_historical. The preset initial smoothed estimate vector S_init for the "first correspondence" parameter refers to a predetermined starting value set for the smoothed estimate of the "first correspondence" parameter when performing parameter fusion for the first time or when historical data is missing. It can be set based on prior knowledge or experimental data. The preset initial smoothed estimate vector B_init for the change trend of the "first correspondence" parameter refers to a predetermined starting value set for the smoothed estimate of the change trend of the "first correspondence" parameter when performing parameter fusion for the first time or when historical data is missing. It can be set based on prior knowledge or experimental data, and can usually be set as a zero vector. The first correspondence indication parameter P_indicator_curr for the current calibration period refers to an instantaneous or preliminary indicator reflecting the current "first correspondence" status, which is directly calculated or estimated based on the calibration data (first functional area detection information, calibration period status parameters, and wound-specific biochemical index reference benchmarks) obtained within the current calibration period. It can be represented by a vector. The preset horizontal smoothing coefficient alpha is a coefficient used to adjust the weight of the current indicator parameter P_indicator_curr when calculating the current smoothed estimate. Its value ranges from 0 to 1, and it is used to balance the relative influence of current data and historical data. The preset trend smoothing coefficient beta is a coefficient used to adjust the weight of the current smoothed value change (S_curr - S_historical) when calculating the current trend smoothed estimate. Its value ranges from 0 to 1, and it is used to balance the relative influence of current trend changes and historical trends. The smoothed estimate vector S_curr of the "first correspondence" parameter for the current calibration period refers to the updated estimate of the current value of the "first correspondence" parameter calculated through the parameter fusion mechanism at the end of the current calibration period. It is the updated parameter of the first correspondence.The smoothed estimate vector B_curr of the parameter change trend of the "first correspondence" of the current calibration period, which is used for subsequent calibration periods, refers to the trend estimate calculated by the parameter fusion mechanism at the end of the current calibration period and used for parameter fusion in the next calibration period.

[0081] like Figure 2 The system shown is a composite material detection system for diabetic wounds, comprising:

[0082] The information acquisition module 201 is used to acquire the original first detection information of the first functional area and the original second detection information of the second functional area in a time-related manner through an external non-invasive detection device.

[0083] Background reference determination module 202 is used to determine a background reference based on the acquired original second detection information;

[0084] The target feature extraction module 203 is used to extract a target feature based on the acquired original first detection information and the determined background reference quantity through a preset comparative analysis operation. The target feature quantity characterizes the specific change in the detectable physical properties of the response unit in the first functional region due to the response to a specific biochemical index.

[0085] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for detecting composite materials in diabetic wounds, applied to a composite dressing, wherein the composite dressing has at least one first functional area and at least one second functional area, characterized in that, The method includes the following steps: Using an external non-invasive detection device, the original first detection information of the first functional area and the original second detection information of the second functional area are acquired in a time-correlated manner. Based on the acquired original second detection information, a background reference quantity is determined. The background reference quantity characterizes the combined influence on the detection information formed by the dressing's absorption of exudate and the local physical morphological differences caused by uneven application of the dressing. Based on the acquired original first detection information and the determined background reference quantity, a target feature quantity is extracted through a preset comparative analysis operation. The target feature quantity characterizes the specific change in detectable physical properties of the response unit in the first functional area due to the response to a specific biochemical index. The first functional area includes a response unit that is sensitive to specific biochemical indicators of the wound. After the response unit reacts with the specific biochemical indicators, it causes a change in the locally detectable physical properties of the dressing in the first functional area. The physical properties of the matrix material of the second functional region are related to the physical properties of the matrix material of the first functional region by a predetermined correlation. The second functional region does not respond to a specific biochemical indicator or its response characteristics have a predetermined difference from the response characteristics of the first functional region that can be distinguished. Furthermore, the second functional region and the first functional region have a predetermined relative positional relationship in space.

2. The method for detecting composite materials in diabetic wounds according to claim 1, characterized in that, The step of extracting a target feature quantity based on the acquired original first detection information and the determined background reference quantity through a preset comparative analysis operation, wherein the target feature quantity characterizes the specific change in the detectable physical property of the response unit in the first functional region due to the response to a specific biochemical index, includes: Obtain state parameters characterizing the physical environment state of the composite dressing in the first functional region and the second functional region, the state parameters including information derived from the original second detection information; Based on a predetermined first correspondence and a second correspondence, wherein the first correspondence characterizes the association between the state parameter and the response sensitivity or response amplitude of the response unit to the specific biochemical indicator, and the second correspondence characterizes the association between the state parameter and the background reference quantity on the accuracy of characterizing the background interference component in the original first detection information; Based on the acquired state parameters and according to the first and second correspondences, adjust the preset comparison analysis operation's calculation factor or calculation process for extracting the target feature quantity based on the acquired original first detection information and the determined background reference quantity; The adjusted comparative analysis operation is performed, and the target feature quantity is extracted using the acquired original first detection information, the determined background reference quantity, and the adjusted operation factor or operation process. The target feature quantity characterizes the specific change in the detectable physical properties of the response unit in the first functional region due to the response to a specific biochemical index.

3. The method for detecting composite materials in diabetic wounds according to claim 2, characterized in that, The step of adjusting the calculation factor or calculation process in the preset comparison analysis operation, based on the acquired state parameters and according to the first correspondence and the second correspondence, for extracting the target feature quantity based on the acquired original first detection information and the determined background reference quantity, includes: Acquire the first functional area detection information, the second functional area detection information, and the calibration period status parameters when the preset calibration conditions are met. The calibration period status parameters characterize the physical environment state of the composite material dressing in the first functional area and the second functional area when the preset calibration conditions are met. To obtain a reference baseline for specific biochemical indicators of the wound when the preset calibration conditions are met; Based on the first functional area detection information when the preset calibration conditions are met, the calibration period status parameters, and the reference benchmarks of specific biochemical indicators of the wound, the first correspondence is updated to obtain the updated first correspondence. Based on the first functional area detection information when the preset calibration conditions are met, the second functional area detection information when the preset calibration conditions are met, and the calibration period status parameters, the second correspondence is updated to obtain the updated second correspondence. Based on the acquired state parameters, and according to the updated first correspondence and the updated second correspondence, adjust the computational factors or computational processes used in the preset comparative analysis operation to extract the target feature quantity based on the acquired original first detection information and the determined background reference quantity.

4. The method for detecting composite materials in diabetic wounds according to claim 3, characterized in that, The step of obtaining a reference baseline for specific biochemical indicators of the wound when the preset calibration conditions are met includes: Identify the corresponding target calibration area on the wound surface of the first functional area on the composite dressing; Within the identified target calibration area, measurement data that characterizes the local biochemical state of the wound sensed by the first functional area is collected by performing targeted measurements on specific biochemical indicators of the wound. Based on the collected measurement data, a reference benchmark for specific biochemical indicators of the wound is determined.

5. The method for detecting composite materials in diabetic wounds according to claim 3, characterized in that, The step of updating the first correspondence based on the first functional area detection information when the preset calibration conditions are met, the calibration period status parameters, and the reference benchmark of specific biochemical indicators of the wound to obtain the updated first correspondence includes: Retrieve parameters of at least one historical first correspondence that was determined in a previous calibration cycle; Based on the first functional area detection information obtained when the current preset calibration conditions are met, the calibration period status parameters, and the reference benchmark of specific biochemical indicators of the wound, a first correspondence indication parameter for the current calibration cycle is calculated. According to the preset parameter fusion mechanism, the parameters of the historical first correspondence are integrated with the calculated first correspondence indication parameters of the current calibration cycle to generate updated first correspondence parameters. The parameter fusion mechanism enables the updated first correspondence parameters to reflect the changing trend of historical parameters and incorporate the indication parameters of the current calibration cycle. Thus, based on the first functional area detection information when the preset calibration conditions are met, the calibration period status parameters, and the reference benchmark of specific biochemical indicators of the wound, the first correspondence is updated to obtain the updated first correspondence.

6. The method for detecting composite materials in diabetic wounds according to claim 3, characterized in that, The step of adjusting the computational factor or computational process in the preset comparative analysis operation, which is used to extract the target feature quantity based on the acquired original first detection information and the determined background reference quantity, according to the acquired state parameters and the updated first correspondence and the updated second correspondence, includes: A parameterized computation execution structure is established, which is used to accommodate and execute the computation logic for extracting the target feature quantity from the original first detection information and the determined background reference quantity, and the computation logic can be configured through computation parameters or path selection; Based on the updated first correspondence, the updated second correspondence, and the obtained state parameters, determine the operation parameters for configuring the parameterized operation execution structure or select the preset operation path within the parameterized operation execution structure; The determined operation parameters are applied to the parameterized operation execution structure, or the parameterized operation execution structure is configured according to the selected operation path, thereby adjusting the operation factors or operation process used to extract the target feature quantity based on the acquired original first detection information and the determined background reference quantity in the preset comparative analysis operation.

7. The method for detecting composite materials in diabetic wounds according to claim 6, characterized in that, The step of determining the operation parameters for configuring the parameterized operation execution structure or selecting a preset operation path within the parameterized operation execution structure based on the updated first correspondence, the updated second correspondence, and the obtained state parameters includes: Construct a multidimensional mapping function; The updated first correspondence, the updated second correspondence, and the obtained state parameters are used as inputs to the multidimensional mapping function; The multidimensional mapping function is used to calculate the operation parameters or the operation path used to configure the parameterized operation execution structure.

8. The method for detecting composite materials in diabetic wounds according to claim 7, characterized in that, The step of calculating the operation parameters or operation path used to configure the parameterized operation execution structure through the multidimensional mapping function includes: By using the multidimensional mapping function and applying a preset combination of weighting coefficients and offsets, the updated first correspondence, the updated second correspondence, and the obtained state parameters are transformed into the operation parameters, thereby calculating the operation parameters used to configure the parameterized operation execution structure. Alternatively, the updated first correspondence, the updated second correspondence, and the obtained state parameters can be compared with a preset threshold or range using the multidimensional mapping function to determine and select the computation path, thereby calculating the computation path used to configure the parameterized computation execution structure.

9. A detection system for composite materials in diabetic wounds, used to perform a method for detecting composite materials in diabetic wounds as described in any one of claims 1-8, characterized in that, The system includes: The information acquisition module is used to acquire the original first detection information of the first functional area and the original second detection information of the second functional area in a time-correlated manner through an external non-invasive detection device. The background reference determination module is used to determine a background reference based on the acquired original second detection information; The target feature extraction module is used to extract a target feature based on the acquired original first detection information and the determined background reference quantity through a preset comparative analysis operation. The target feature quantity characterizes the specific change in the detectable physical property of the response unit in the first functional region due to the response to a specific biochemical index.

Images