Orthopedic wound care management system and method
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN LONGGANG DISTRICT EIGHTH PEOPLES HOSPITAL
- Filing Date
- 2025-09-04
- Publication Date
- 2026-07-24
Smart Images
Figure CN121148693B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of wound care, and in particular to an orthopedic wound care management system and method. Background Technology
[0002] Chronic wound care is a long-standing challenge in orthopedics, burn care, and endocrinology, especially for common chronic wounds such as diabetic foot ulcers, pressure injuries, and venous ulcers, which are characterized by slow healing, high recurrence rates, and complex treatment. With an aging population and rising prevalence of chronic diseases, the incidence of chronic wounds is increasing annually, becoming a global public health issue. Currently, there is no unified, standardized assessment and treatment process for wound care both domestically and internationally. Most medical institutions still rely on the personal experience of nursing staff for wound diagnosis and treatment, resulting in inconsistent quality of care.
[0003] In current wound care practices, common assessment methods rely primarily on visual observation, manual measurement, and paper records, lacking objective and quantitative assessment tools. For example, key indicators such as wound size, depth, and exudate volume are often roughly estimated using tools like rulers and cotton swabs, resulting in significant subjective influences. Furthermore, wound classification standards are inconsistent, and assessment tools and recording formats vary considerably between different hospitals and even different departments, hindering data sharing and comparison, and making multi-center studies and big data analysis difficult. Regarding nursing protocols, most institutions have not yet achieved personalization and differentiation, often employing a "one-size-fits-all" approach to dressing selection and dressing changes, failing to fully consider the impact of underlying diseases, nutritional status, age, and other factors on healing.
[0004] Most existing wound management systems have relatively simple functions, focusing on electronic recording and querying, and lacking intelligent analysis and decision support capabilities. While a few systems attempt to introduce image recognition technology for wound measurement, they are mostly limited to two-dimensional image processing, unable to accurately obtain three-dimensional information such as wound depth, volume, and subcutaneous tissue condition, nor can they integrate multimodal sensor data (such as temperature, humidity, pH, and bacterial biofilm) for comprehensive judgment. Furthermore, the outpatient continuity of care is particularly weak; wound monitoring at home relies mainly on patients' self-descriptions or family photos, resulting in poor data quality, low compliance, and difficulty in timely detection of healing abnormalities or infection risks.
[0005] The aforementioned problems lead to drawbacks in wound care, including inaccurate assessments, unscientific treatment plans, prolonged healing times, frequent patient visits to the hospital, and waste of medical resources. This is particularly problematic in primary care hospitals due to a lack of specialized personnel, inconsistent wound care standards, high patient referral rates, and overall poor treatment outcomes. Therefore, there is an urgent need in this field for an orthopedic wound care management system and methodology that integrates intelligent assessment, standardized management, personalized care, and continuous monitoring to achieve standardized, precise, and intelligent nursing processes. Summary of the Invention
[0006] The purpose of this invention is to provide an orthopedic wound care management system and method to solve the problems existing in the prior art.
[0007] To achieve the above objectives, the present invention provides the following solution:
[0008] This invention provides a method for the care and management of orthopedic wounds, comprising:
[0009] S1. Receive the patient's identity information and medical history information sent by the patient's user terminal. The medical history information includes basic disease data, medication history and allergy history.
[0010] S2. Receive wound feature information collected by the intelligent assessment terminal through multimodal sensing. The wound feature information includes wound image, wound depth, tissue type composition ratio, exudate volume and biochemical indicators.
[0011] S3. Based on a pre-set intelligent assessment model, the wound characteristic information is analyzed to generate a preliminary assessment report. The preliminary assessment report includes the wound staging results, the predicted healing time, and the personalized care plan. The intelligent assessment model uses the following healing prediction formula:
[0012]
[0013] Where, T h To predict healing time, A0 is the initial wound area, S0 is the initial severity score, and S... t The current severity score is given by Age, Alb is the serum albumin level, Hb is the hemoglobin level, GI is the glycemic index, and k1, k2, k3, and k4 are model adjustment coefficients.
[0014] S4. Send the preliminary assessment report and patient historical data to the healthcare user terminal; if a confirmation instruction is received from the healthcare user based on the preliminary assessment report, send the report to the patient user terminal.
[0015] Preferably, in step S2, the intelligent evaluation terminal includes:
[0016] A multispectral imaging module is used to acquire subcutaneous tissue images;
[0017] 3D scanning module, which is used to reconstruct the three-dimensional structure of the wound and calculate its volume;
[0018] A microenvironment sensor is used to monitor wound temperature, humidity, and pH.
[0019] Preferably, in step S3, the intelligent assessment model is constructed using a machine learning algorithm, and its input features further include: wound edge feature parameter E. d Exudation property index Ex i The proportion of tissue necrosis N p The calculation method is as follows:
[0020]
[0021] Ex i =text viscosity × text color depth;
[0022]
[0023] Preferably, in step S3, the personalized care plan includes:
[0024] A debridement method selection model, which outputs a debridement strategy based on the proportion of necrotic tissue and the patient's pain tolerance.
[0025] A dressing matching model that outputs dressing types based on exudate volume, infection risk, and cost constraints;
[0026] A dressing change frequency optimization model is provided, which dynamically adjusts the dressing change interval based on the exudate absorption rate and the healing stage.
[0027] Preferably, the optimal dressing change frequency optimization model uses the following formula to calculate the optimal dressing change cycle T. c :
[0028]
[0029] Among them, C textmax C0 is the maximum absorbent capacity of the dressing, and r is the initial exudate volume. e The value represents the rate of exudate production, and InfRisk is the infection risk coefficient, ranging from 0 to 1.
[0030] Preferably, it further includes:
[0031] S5. Generate a secondary assessment report based on the data uploaded by the home monitoring terminal and compare it with the expected healing trajectory; if the detected healing deviation exceeds the threshold, send an early warning message to the medical terminal.
[0032] The present invention also provides an orthopedic wound care management system, comprising:
[0033] Intelligent assessment terminal, used to collect wound feature information in a multimodal manner;
[0034] The patient user terminal is used to enter the patient's basic information and medical history, and to receive nursing plans;
[0035] Healthcare user terminals are used to review assessment reports and make clinical decisions.
[0036] Home monitoring terminal for continuously collecting data on patients' wounds outside the hospital;
[0037] The server is used to run orthopedic wound care management methods and coordinate data interaction and business logic between various terminals.
[0038] Preferably, the intelligent assessment terminal integrates an AR display module, which is used to overlay wound assessment results and treatment instructions in real time into the field of vision of medical staff.
[0039] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the above-described method.
[0040] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.
[0041] The present invention achieves the following beneficial technical effects compared to the prior art:
[0042] This invention provides an orthopedic wound care management system and method that deeply integrates intelligence, standardization, and personalization. It achieves objective and quantitative collection of wound characteristics through multimodal sensing terminals, integrates multidimensional patient data using an intelligent assessment model to output scientific assessment results, and dynamically optimizes nursing plans and dressing strategies based on algorithmic models, significantly improving the accuracy of wound assessment and the targeted nature of care. The system particularly emphasizes the continuity of care both inside and outside the hospital, achieving full monitoring of the healing process through home monitoring terminals and early warning mechanisms, effectively reducing the risk of complications and the number of patient return visits. Furthermore, the system is easy to operate and highly adaptable, applicable to multidisciplinary collaborative scenarios in large hospitals as well as standardized promotion in primary healthcare institutions, thereby comprehensively improving the quality and efficiency of wound care, reducing the workload of medical staff, and improving patient prognosis. Attached Figure Description
[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0044] Figure 1 The flowchart of the orthopedic wound care and management method provided by the present invention. Detailed Implementation
[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0046] The purpose of this invention is to provide an orthopedic wound care management system and method to solve the problems existing in the prior art.
[0047] This invention provides a method for the care and management of orthopedic wounds, such as... Figure 1 As shown, it includes:
[0048] S1. Receive the patient's identity information and medical history information sent by the patient's user terminal. The medical history information includes basic disease data, medication history and allergy history.
[0049] S2. Receive wound feature information collected by the intelligent assessment terminal through multimodal sensing. The wound feature information includes wound image, wound depth, tissue type composition ratio, exudate volume, and biochemical indicators. The intelligent assessment terminal includes:
[0050] A multispectral imaging module is used to acquire subcutaneous tissue images;
[0051] 3D scanning module, which is used to reconstruct the three-dimensional structure of the wound and calculate its volume;
[0052] A microenvironment sensor, used to monitor wound temperature, humidity, and pH value;
[0053] S3. Based on a pre-set intelligent assessment model, the wound characteristic information is analyzed to generate a preliminary assessment report. The preliminary assessment report includes the wound staging results, the predicted healing time, and the personalized care plan. The intelligent assessment model uses the following healing prediction formula:
[0054]
[0055] Where, T h To predict healing time, A0 is the initial wound area, S0 is the initial severity score, and S... t The current severity score is given, where Age is the patient's age, Alb is the serum albumin level, Hb is the hemoglobin level, GI is the glycemic index, and k1, k2, k3, and k4 are model adjustment coefficients. The intelligent assessment model is constructed using machine learning algorithms, and its input features also include: wound edge feature parameter E. d Exudation property index Ex i The proportion of tissue necrosis Np The calculation method is as follows:
[0056]
[0057] Ex i =text viscosity ×text color depth;
[0058]
[0059] Personalized care plans include:
[0060] A debridement method selection model, which outputs a debridement strategy based on the proportion of necrotic tissue and the patient's pain tolerance.
[0061] A dressing matching model that outputs dressing types based on exudate volume, infection risk, and cost constraints;
[0062] A dressing change frequency optimization model is used, which dynamically adjusts the dressing change interval based on the exudate absorption rate and the healing stage. The optimal dressing change cycle T is calculated using the following formula. c :
[0063]
[0064] Among them, C textmax C0 is the maximum absorbent capacity of the dressing, and r is the initial exudate volume. e InfRisk is the rate of exudate production and the infection risk coefficient, with a value ranging from 0 to 1.
[0065] S4. Send the preliminary assessment report and patient historical data to the healthcare user terminal; if a confirmation instruction is received from the healthcare user based on the preliminary assessment report, send the report to the patient user terminal.
[0066] S5. Generate a secondary assessment report based on the data uploaded by the home monitoring terminal and compare it with the expected healing trajectory; if the detected healing deviation exceeds the threshold, send an early warning message to the medical terminal.
[0067] The present invention also provides an orthopedic wound care management system, comprising:
[0068] Intelligent assessment terminal, used to collect wound feature information in a multimodal manner;
[0069] The patient user terminal is used to enter the patient's basic information and medical history, and to receive nursing plans;
[0070] Healthcare user terminals are used to review assessment reports and make clinical decisions.
[0071] Home monitoring terminal for continuously collecting data on patients' wounds outside the hospital;
[0072] The server is used to run orthopedic wound care management methods and coordinate data interaction and business logic between various terminals.
[0073] Preferably, the intelligent assessment terminal integrates an AR display module, which is used to overlay wound assessment results and treatment instructions in real time into the field of vision of medical staff.
[0074] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the above-described method.
[0075] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.
[0076] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0077] Example 1:
[0078] A 58-year-old male diabetic patient presented to the orthopedic clinic with a ulceration at the first metatarsophalangeal joint of his right foot three weeks prior. Before entering the examination room, the patient had completed identity registration via the "Patient User Terminal" WeChat mini-program: after uploading a photo of his ID card, the system automatically parsed his name, gender, date of birth, and other identity information. The patient further completed a structured questionnaire, selecting "Type II diabetes for 16 years, currently taking metformin orally, no history of drug allergies," and providing recent laboratory results: HbA1c 8.4%, serum albumin 32 g / L, and hemoglobin 97 g / L. This data was encrypted and immediately synchronized to the hospital's private cloud server. The server categorized the patient as a "high-risk chronic wound patient" and assigned him a unique ID.
[0079] The nurse led the patient to an examination bed equipped with an "intelligent assessment terminal." This terminal, in the form of an integrated cart, incorporates a multispectral imaging module, a 3D scanning module, and a microenvironment sensor array at its top. Medical staff first used the multispectral imaging module to image the skin and subcutaneous tissue in the 400-1000nm continuous band, acquiring images of the distribution of oxyhemoglobin, deoxyhemoglobin, and collagen. The system displayed a real-time grayscale and pseudo-color fused image, indicating a large area of low perfusion beneath the wound. Subsequently, the 3D scanning module was activated, employing a structured light and stereoscopic vision fusion algorithm to reconstruct a three-dimensional mesh of the wound within 2 seconds, accurately calculating the current wound surface area to be 4.18 cm². 2 Maximum depth is 0.67cm, volume is 1.34cm. 3The necrotic tissue (red, 38%), granulation tissue (green, 45%), and fibrous tissue (blue, 17%) were marked with different colors on the grid. Next, flexible temperature, humidity, and pH sensor pads from the microenvironment sensor array were attached to the wound edge. After 10 seconds, the sensor returned data: temperature 34.8°C, humidity 78%, and pH 7.6, indicating a slightly alkaline local environment and a potential risk of infection. All the sensor data, along with the high-resolution image, were uploaded to the server via a 5GHz Wi-Fi 6 encrypted channel.
[0080] The server runs a pre-trained "intelligent assessment model." The model first calls the image segmentation sub-network to extract features such as wound edge irregularity and exudate characteristics index. Then, combining these with the patient's age, serum albumin, hemoglobin, and blood glucose index, it inputs these into the healing prediction formula to calculate a predicted healing time of 32.4 days. Subsequently, the debridement method selection model, based on a 38% necrotic tissue ratio and the patient's VAS pain score of 4, outputs a "conservative surgical debridement + enzymatic debridement combined regimen." The dressing matching model, considering moderate exudate volume, an infection risk coefficient of 0.6, and medical insurance price limits, recommends "silver-containing carboxymethyl cellulose sodium dressing." The dressing change frequency optimization model, based on a maximum dressing absorption capacity of 10 mL, an initial exudate volume of 3 mL / 24h, and an exudate generation rate of 0.8 mL / h, calculates an optimal dressing change cycle of 47 hours, which the system rounds to 48 hours. Based on these results, the system generates a preliminary assessment report, presented in PDF format, including a 3D visualization model, color tissue distribution map, prediction curves, nursing protocols, and QR codes for educational videos.
[0081] The nurse received a notification about the pending task via the "Medical Staff User Terminal" iPad. The left side of the interface displays the patient's historical medical records and the current assessment report, while the right side is an editable area. After reviewing the report, the doctor determined that the actual percentage of necrotic tissue might be higher than 38%, and manually adjusted it to 45%. The system immediately recalculated, extending the healing time to 36.1 days and shortening the dressing change cycle to 42 hours. The doctor clicked "Confirm," and the server encrypted and pushed the updated report to the patient's WeChat account. The patient can view the care plan and schedule the next dressing change within the mini-program.
[0082] After discharge, the patient entered the "home monitoring" phase. The patient's family received a home monitoring terminal, including a disposable flexible pH temperature patch, smart dressing, and a 4G communication module. Every 12 hours, the terminal automatically collected wound temperature and pH values, uploading them to the patient's mobile phone via Bluetooth Low Energy, and then synchronizing them to the cloud via HTTPS. On the night of the 5th day, the system detected a local temperature rise to 36.9℃ and a pH rise to 8.1, deviating from the expected healing trajectory by more than the set threshold. The server immediately triggered an alert, pushing a "risk of infection" red alert to the on-duty nurse's mobile phone, along with a trend curve and treatment suggestions. After confirmation on the medical staff's end, the nurse sent a notification to the patient via a mini-program to arrange an additional outpatient appointment for the next day, achieving early intervention.
[0083] Throughout the nursing cycle, the AR display module on top of the intelligent assessment terminal provides real-time guidance to medical staff during dressing changes: in the AR glasses' field of view, the wound edge is highlighted with a green outline, and the necrotic tissue area is overlaid with a red grid. The system prompts "Debridement needs to be strengthened here," and simultaneously displays "Current dressing has 23% remaining absorption capacity." This function significantly shortens the training curve, enabling nurses in primary care hospitals to quickly master standardized operating procedures.
[0084] The server performs incremental learning on all inpatient and home-based patient data daily, automatically updating model parameters to dynamically adjust the adjustment coefficients α, β, and γ in the healing prediction formula according to regional population characteristics, ensuring high accuracy across different hospitals and seasons. Furthermore, the system employs a microservice architecture, allowing for horizontal scalability. It supports thousands of concurrent accesses from tertiary hospitals and can also be deployed as a standalone unit in county-level hospitals, enabling lightweight operation in resource-constrained environments.
[0085] This implementation method achieves closed-loop management of orthopedic chronic wounds from admission assessment and inpatient treatment to discharge follow-up through the synergy of multimodal sensing terminals, intelligent assessment models, personalized nursing strategies, and home monitoring and early warning mechanisms. It significantly improves the accuracy of nursing care and patient compliance, reduces infection and re-hospitalization rates, and has good scalability and prospects for promotion.
[0086] This invention has illustrated its principles and implementation methods using specific examples. The descriptions of these embodiments are merely illustrative of the method and its core ideas; furthermore, those skilled in the art will recognize that modifications may be made to the specific implementation methods and application scope based on the principles of this invention. Therefore, the content of this specification should not be construed as limiting the invention.
Claims
1. A method for the nursing and management of orthopedic wounds, characterized in that, include: S1. Receive the patient's identity information and medical history information sent by the patient's user terminal. The medical history information includes basic disease data, medication history and allergy history. S2. Receive wound feature information collected by the intelligent assessment terminal through multimodal sensing. The wound feature information includes wound image, wound depth, tissue type composition ratio, exudate volume and biochemical indicators. S3. Based on a pre-set intelligent assessment model, the wound characteristic information is analyzed to generate a preliminary assessment report. The preliminary assessment report includes the wound staging results, the predicted healing time, and the personalized care plan. The intelligent assessment model uses the following healing prediction formula: ； Where, in the formula, To predict healing time, This represents the initial wound area. For the initial severity score, This is the current severity score, where Age is the patient's age, Alb is the serum albumin level, Hb is the hemoglobin level, and GI is the glycemic index. , , , This is the model adjustment coefficient; S4. Send the preliminary assessment report and patient historical data to the healthcare user terminal; if a confirmation instruction is received from the healthcare user based on the preliminary assessment report, send the report to the patient user terminal. In step S3, the personalized care plan includes: A debridement method selection model, which outputs a debridement strategy based on the proportion of necrotic tissue and the patient's pain tolerance. A dressing matching model that outputs dressing types based on exudate volume, infection risk, and cost constraints; A dressing change frequency optimization model, wherein the dressing change frequency optimization model dynamically adjusts the dressing change interval based on the exudate absorption rate and the healing stage; The dressing change frequency optimization model uses the following formula to calculate the optimal dressing change cycle. : ； in, This is the maximum absorbent capacity of the dressing. This is the initial amount of seepage. The rate of exudate generation, The infection risk coefficient ranges from 0 to 1.
2. The orthopedic wound care and management method according to claim 1, characterized in that, In step S2, the intelligent evaluation terminal includes: A multispectral imaging module is used to acquire subcutaneous tissue images; 3D scanning module, which is used to reconstruct the three-dimensional structure of the wound and calculate its volume; A microenvironment sensor is used to monitor wound temperature, humidity, and pH.
3. The orthopedic wound care and management method according to claim 1, characterized in that, In step S3, the intelligent assessment model is constructed using machine learning algorithms, and its input features also include: wound edge feature parameters. Permeability index The proportion of tissue necrosis The calculation method is as follows: ； ； 。 4. The orthopedic wound care and management method according to claim 1, characterized in that, Also includes: S5. Generate a secondary assessment report based on the data uploaded by the home monitoring terminal and compare it with the expected healing trajectory; If a healing deviation is detected to exceed the threshold, an early warning message is sent to the medical terminal.
5. An orthopedic wound care management system, characterized in that, include: Intelligent assessment terminal, used to collect wound feature information in a multimodal manner; The patient user terminal is used to enter patient information and medical history, and to receive nursing plans; Healthcare user terminals are used to review assessment reports and make clinical decisions. Home monitoring terminal for continuously collecting data on patients' wounds outside the hospital; A server is used to run the orthopedic wound care management method according to any one of claims 1-4, and to coordinate data interaction and business logic between terminals.
6. The orthopedic wound care management system according to claim 5, characterized in that, The intelligent assessment terminal integrates an AR display module, which is used to overlay wound assessment results and treatment instructions in real time into the field of vision of medical staff.
7. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, When the processor executes the computer program, it implements the orthopedic wound care management method as described in any one of claims 1-4.
8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the orthopedic wound care management method as described in any one of claims 1-4.