Wound healing monitoring platform combining biosensing and artificial intelligence analysis

Abstract

The invention relates to the technical field of biomedical engineering, in particular to a wound healing monitoring platform combining biosensing and artificial intelligence analysis, which comprises an arc-shaped detection plate and a monitoring system, a biosensor for detecting biological parameters of a wound is arranged on the detection plate, and the monitoring system is electrically connected with the biosensor; a position adjusting assembly used for adjusting the position of the detector is arranged on the outer side of the detection plate. Biological parameters are deeply analyzed through an artificial intelligence algorithm of the monitoring system, the biological parameters of the wound surface are collected in real time through a sensor, training analysis is conducted through a deep learning algorithm, the wound surface healing state is predicted in real time, different stages and potential risks of wound surface healing can be accurately recognized, and the wound surface healing quality is improved. The pertinence and effectiveness of wound treatment are improved, and blindness and uncertainty in the treatment process are reduced. Personalized treatment suggestions and rehabilitation guidance can be provided for the patient, and the patient is helped to better understand the illness state of the patient and actively participate in the treatment process.

Description

Technical Field

[0001] The present invention relates to the field of biomedical engineering technology, and in particular to a wound healing monitoring platform combining biosensing and artificial intelligence analysis. Background Art

[0002] Wound healing is a complex physiological process involving multiple stages, including hemostasis, inflammation, proliferation, and remodeling. Effective wound management is essential to promote healing, prevent infection, and reduce complications. Traditional methods mainly rely on the doctor's experience and regular visual observation, which is highly subjective and difficult to quantify and monitor in real time.

[0003] Biosensing technology uses microsensors to monitor biological parameters of the wound surface in real time, such as temperature, humidity, pH value, oxygen level, etc. These biosensors are usually highly sensitive and specific, and can accurately reflect the physiological and pathological status of the wound surface in real time.

[0004] In the prior art, biosensors are usually attached to the wound surface or implanted near the wound surface, which is easy to cause secondary damage. In addition, this type of method is usually fixed and cannot be adjusted. For larger wounds, the collected information may not be comprehensive, resulting in inaccurate judgment.

[0005] In summary, how to solve the problem that the existing technology uses biosensors in an attached manner, which is prone to cause secondary damage and leads to inaccurate judgment has become a difficult problem that needs to be solved urgently in this field. Therefore, it is necessary to propose a wound healing monitoring platform that combines biosensors and artificial intelligence analysis. Summary of the invention

[0006] To solve the above problems, the present invention provides a wound healing monitoring platform that combines biosensing with artificial intelligence analysis. Through the cooperation of various mechanical components, the detector can move along an arc path, better adapt to wounds of different positions and shapes, and improve the comprehensiveness and accuracy of detection. The artificial intelligence algorithm of the monitoring system is used to conduct in-depth analysis of biological parameters, which can accurately identify the different stages and potential risks of wound healing, help improve the pertinence and effectiveness of wound treatment, and reduce blindness and uncertainty in the treatment process.

[0007] In order to achieve the above-mentioned purpose, the technical solution of the present invention is as follows: a wound healing monitoring platform combining biosensing and artificial intelligence analysis, comprising an arc-shaped detection plate, on which is provided a detector for detecting biological parameters of the wound, and also comprising a monitoring system, which is electrically connected to the detector; a positioning component for adjusting the position of the detector is provided on the outer side of the detection plate.

[0008] The positioning assembly includes a bracket, a controller, a rotating member and a plurality of straight rods hinged to each other, the controller is used to control the operation of the rotating member; the rotating member is fixedly connected to the bracket, and the output shaft of the rotating member passes through the bracket and is fixedly connected to one of the straight rods; one end of the straight rod away from the rotating member is rotatably matched with a plurality of hinged rods, and one end of the hinged rod away from the straight rod is hinged to each other; the plurality of hinged rods constitute a movable quadrilateral structure.

[0009] The bracket is also rotatably equipped with a swing rod, and the end of the swing rod away from the bracket is hinged to the hinge rod adjacent to it; the bottom end of the movable quadrilateral is rotatably equipped with an L-shaped extension rod, the extension rod passes through the detection plate and slides with the detection plate, and both ends of the detection plate are fixedly connected with blocks; the extension rod is also provided with an angle adjustment component for adjusting the angle of the detector.

[0010] The technical principles of the above scheme are as follows:

[0011] The rotating member drives the straight rod fixedly connected to it to rotate. Since the straight rods are hinged to each other, the other ends of the straight rods are rotated with the hinged rods; therefore, when the straight rods rotate, the hinged rods that rotate with it can be driven to rotate together. Since the adjacent hinged rods are hinged to each other, the hinged rods are rotated with the extension rods, which penetrate the detection plate and slide with the detection plate, and the two ends of the detection plate are fixedly connected with the block; and the hinged rods are also hinged with swing rods, and the other ends of the swing rods are rotated with the bracket; therefore, when the hinged rods rotate to drive the extension rods to contact the block, the straight rods on both sides can squeeze the hinged rods, and when squeezing, the movement trajectory of the extension rods moves to the side away from the swing rods, thereby generating an arc-shaped movement trajectory. In this process, the swing rods provide a limiting function. Then, the angle of the detector is adjusted by the angle adjustment component, so that the detector can achieve multi-angle detection effects. In addition, the monitoring system performs intelligent monitoring of the wound surface, provides continuous and real-time biological parameter monitoring, ensures that doctors can understand the latest status of the wound surface at any time, and set different thresholds according to the specific conditions of different patients to achieve personalized monitoring and management.

[0012] The above scheme has the following beneficial effects:

[0013] 1. The present invention forms a mechanical structure that can produce an arc-shaped motion trajectory through the cooperation of a straight rod, a hinged rod, a swing rod and an extension rod; this design enables the detector to move along an arc path and better adapt to wounds of different positions and shapes. By cooperating with the angle adjustment component, the angle adjustment range of the detector is further increased, ensuring that different areas of the wound surface can be fully covered, thereby improving the comprehensiveness and accuracy of the detection.

[0014] 2. The present invention uses the artificial intelligence algorithm of the monitoring system to conduct in-depth analysis of biological parameters, which can accurately identify the different stages and potential risks of wound healing, help improve the pertinence and effectiveness of wound treatment, and reduce the blindness and uncertainty in the treatment process. It can also provide patients with personalized treatment suggestions and rehabilitation guidance, help patients better understand their own conditions, and actively participate in the treatment process.

[0015] 3. The present invention makes the monitoring process more in line with the actual needs of patients through flexible detector positioning and multi-angle detection capabilities, helps to obtain more comprehensive biological parameter information, and provides support for the formulation of personalized treatment plans.

[0016] Furthermore, the angle adjustment assembly includes a base plate, which is fixedly connected to the extension rod; a rotating rod is rotatably cooperated with the side of the base plate away from the extension rod, a driving assembly for driving the rotating rod to rotate is provided on the base plate, a connecting plate is fixedly connected to the rotating rod, and a rotating assembly for rotating the detector is provided on the connecting plate.

[0017] Beneficial effect: Since there is a rotating rod on the bottom plate for rotation, and a driving assembly for driving the rotating rod to rotate is also provided on the bottom plate, and a connecting plate is fixedly connected to the rotating rod, the driving assembly can drive the rotating rod to rotate, and the connecting plate will be driven to rotate along with it when rotating, and then the detector is rotated by using the rotating assembly, thereby increasing the flexibility of the detector.

[0018] Furthermore, the driving assembly includes a gear, a rack and a telescopic part, and the controller is used to control the movement of the telescopic part; the telescopic part is fixedly connected to the side of the base plate close to the rotating rod, and the output shaft of the telescopic part is fixedly connected to the rack; the rack and the gear are meshed with each other, and the gear is coaxially fixedly connected to the rotating rod.

[0019] Beneficial effect: the rack is driven to move by the telescopic member, and since the rack and the gear are meshed with each other, the gear and the rotating rod are coaxially fixedly connected; therefore, the linear movement of the rack can be utilized to rotate the gear, and the gear drives the rotating rod to rotate, thereby allowing the connecting plate on the rotating rod to rotate at multiple angles.

[0020] Furthermore, the rotating assembly includes a driving member and a rotating disk. The controller is used to control the operation of the driving member. The driving member is fixedly connected to one end of the connecting plate away from the rotating rod; the output shaft of the driving member is fixedly connected to the rotating disk, and the side of the rotating disk away from the driving member is fixedly connected to the detector.

[0021] Beneficial effect: The rotating disk is driven to rotate by the driving member. Since the rotating disk is fixedly connected to the detector, the detector can rotate along with the rotating disk to adjust the angle of the detector. The angle of the detector can be dynamically adjusted according to the healing condition of the wound and actual needs to ensure the timeliness and accuracy of the detection results.

[0022] Furthermore, a clamp is fixedly connected to the bracket, and the clamp is detachably connected to the hospital bed.

[0023] Beneficial effect: Through the design of the clamp, the monitoring device can be fixed on the bed to ensure that the device will not fall off or shift due to patient movement or external interference during use.

[0024] Furthermore, a symmetrically arranged rotating plate is fixedly connected to one side of the bottom plate near the rotating rod, and the rotating rods are all rotatably matched with the rotating plates. The rotating rods near the gear side penetrate the rotating plates and are all rotatably matched with the rotating plates. The connecting plate is located on the rotating rods between adjacent rotating plates.

[0025] Beneficial effect: The design of the rotating plate helps to balance and disperse the force generated by the rotating rod during rotation, thereby improving the stability of the entire structure.

[0026] Furthermore, a sliding plate is fixedly connected to one side of the bottom plate close to the rack, and a sliding groove is provided on the sliding plate for the rack to move.

[0027] Beneficial effects: The slide groove provided on the sliding plate provides a clear movement trajectory for the rack; when the rack moves in the slide groove, it can be constrained and guided by the slide groove, thereby ensuring that the movement direction of the rack is accurate and stable.

[0028] Furthermore, one end of the sliding plate away from the rack is fixedly connected to the limiting block.

[0029] Beneficial effects: The limit block fixedly connected to the sliding plate ensures that the rack moves within a predetermined range, prevents the rack from exceeding the slide slot, provides additional protection, and further increases the stability of the device.

[0030] Furthermore, the monitoring system includes a real-time monitoring module, a data transmission module, a data analysis module, an early warning module and an interaction module.

[0031] The real-time monitoring module is used to monitor the biological parameters around the wound in real time, including temperature, humidity, pH value, trimethylamine, uric acid and wound moisture.

[0032] The data transmission module is used to transmit the biological parameters collected by the detector to the mobile terminal using wireless communication technology; the wireless communication technology includes 4G, 5G, Bluetooth and WiFi.

[0033] The data analysis module is used to analyze biological parameters using artificial intelligence algorithms to identify different stages of wound healing and potential risks.

[0034] The early warning module is used to set thresholds for different stages of wound healing and potential risks, and issue early warning information when the wound status becomes abnormal.

[0035] The interactive module is used to use a mobile terminal to view the wound healing status in real time and receive treatment suggestions.

[0036] Beneficial effects: By real-time monitoring of biological parameters around the wound, using advanced artificial intelligence algorithms to conduct in-depth analysis of biological parameters, automatically identifying different stages of wound healing, providing scientific evaluation results, helping doctors to promptly discover and deal with problems, and improving treatment effects. Different thresholds can be set according to the specific conditions of different patients to achieve personalized monitoring and management. The wound healing status can be viewed in real time through mobile terminals to improve the transparency and timeliness of information.

[0037] Furthermore, the artificial intelligence algorithm uses deep learning technology for analysis, and its specific steps are as follows:

[0038] S1. Data preprocessing: data cleaning, data standardization and feature extraction of the collected biological parameters.

[0039] S2. Model training: Select a suitable deep learning model, divide the data into training set, validation set and test set; and use cross-validation to obtain hyperparameter combinations.

[0040] S3. Model evaluation: Use the test set to evaluate the model's accuracy, recall, F1 score, and AUC-ROC curve indicators to evaluate the model performance; check for cases where the model predicts incorrectly.

[0041] S4. Prediction and decision-making: Input the newly collected biological parameters into the trained model to predict the status and development trend of wound healing; provide treatment recommendations based on the prediction results; and issue early warning signals when potential risks that may affect wound healing are detected.

[0042] S5. Feedback loop: Regularly collect new case data, update the training set, and retrain the model based on the new data; and collect feedback from doctors and patients to continuously optimize the algorithm and system functions.

[0043] Beneficial effects: By using deep learning algorithms to train biological parameters, the trained deep learning model can accurately predict the state and development trend of wound healing based on the newly collected biological parameters. Based on the prediction results, the algorithm can provide patients with personalized treatment recommendations and help doctors develop more scientific and effective treatment plans.

[0044] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is an axonometric diagram of a wound healing monitoring platform that combines biosensing and artificial intelligence analysis in an embodiment of the present invention.

[0046] Figure 2 It is an axonometric view of the angle adjustment assembly in an embodiment of the present invention.

[0047] Figure 3 4 is a structural block diagram of a controller in an embodiment of the present invention.

[0048] Figure 4 Schematic diagram of the process of the artificial intelligence algorithm in the embodiment of the present invention.

[0049] The figure marks in the drawings of the specification include: 1. detection plate; 2. bracket; 3. rotating motor; 4. straight rod; 5. hinged rod; 6. swing rod; 7. extension rod; 8. bottom plate; 9. rotating rod; 10. connecting plate; 11. gear; 12. rack; 13. electric telescopic rod; 14. driving motor; 15. rotating disk; 16. rotating plate; 17. sliding plate; 18. limit block. DETAILED DESCRIPTION

[0050] The following is further described in detail through specific implementation methods:

[0051] Embodiment 1:

[0052] As attached Figure 1-Figure 2 As shown: A wound healing monitoring platform combining biosensing and artificial intelligence analysis includes an arc-shaped detection board 1 and a monitoring system. The detection board 1 is provided with a detector for detecting biological parameters of the wound. In this embodiment, the detector is a biosensor, which is used to collect data about the wound status, such as temperature, humidity, pH value, oxygen level, etc. The monitoring system is electrically connected to the biosensor; a positioning component for adjusting the position of the detector is provided on the outside of the detection board 1.

[0053] The positioning assembly includes a bracket 2, a controller, a rotating part and a plurality of straight rods 4 hinged to each other. In this embodiment, the rotating part is a rotating motor 3, and the controller is used to control the operation of the rotating motor 3; the rotating motor 3 is bolted and fixedly connected to the bracket 2, and the output shaft of the rotating motor 3 passes through the bracket 2 and is fixedly connected to one of the straight rods 4; the bottom ends of the straight rods 4 are rotatably matched with a plurality of hinged rods 5, and the other ends of the hinged rods 5 are hinged to each other; the plurality of hinged rods 5 constitute a movable quadrilateral structure.

[0054] The bracket 2 is also rotatably equipped with a swing rod 6, and the bottom end of the swing rod 6 is hinged to the adjacent hinge rod 5; the bottom end of the movable quadrilateral is rotatably equipped with an L-shaped extension rod 7, the extension rod 7 passes through the detection plate 1 and slides with the detection plate 1, and both ends of the detection plate 1 are integrally formed with stoppers; the extension rod 7 is also provided with an angle adjustment component for adjusting the angle of the detector.

[0055] like Figure 2As shown, the angle adjustment assembly includes a base plate 8, which is fixedly connected to the extension rod 7 with bolts; a rotating rod 9 is rotatably matched on the base plate 8, and a driving assembly for driving the rotating rod 9 to rotate is provided on the base plate 8, and a connecting plate 10 is fixedly clamped on the rotating rod 9, and a rotating assembly for rotating the detector is provided on the connecting plate 10.

[0056] The driving assembly includes a gear 11, a rack 12 and a telescopic member. In this embodiment, the telescopic member is an electric telescopic rod 13, and the controller is used to control the movement of the electric telescopic rod 13; the electric telescopic rod 13 is bolted fixedly connected to the base plate 8, and the output shaft of the electric telescopic rod 13 is bolted fixedly connected to the rack 12; the rack 12 and the gear 11 are meshed with each other, and the gear 11 is coaxially fixedly connected to the rotating rod 9.

[0057] The rotating assembly includes a driving member and a rotating disk 15. In this embodiment, the driving member is a driving motor 14. The controller is used to control the operation of the driving motor 14. The driving motor 14 is bolted and fixedly connected to the top of the connecting plate 10; the output shaft of the driving motor 14 is fixedly engaged with the rotating disk 15, and the top of the rotating disk 15 is fixedly connected with the detector screw.

[0058] The electric telescopic rod 13 drives the rack 12 to move. Since the rack 12 and the gear 11 are meshed with each other, and the gear 11 is coaxially fixed with the rotating rod 9, the linear movement of the rack 12 can be used to rotate the gear 11, and the gear 11 drives the rotating rod 9 to rotate, so that the connecting plate 10 on the rotating rod 9 can rotate at multiple angles. Figure 2 For example, when the electric telescopic rod 13 drives the rack 12 to move upward, the gear 11 can rotate counterclockwise, and the counterclockwise rotation of the gear 11 drives the connecting plate 10 to rotate below the rotating rod 9. Conversely, it can drive the connecting plate 10 to rotate above the rotating rod 9.

[0059] After the connecting plate 10 moves to the corresponding angle, the driving motor 14 drives the rotating disk 15 to rotate. Since the rotating disk 15 is fixedly connected to the detector screw, the detector can rotate along with the rotating disk 15, thereby realizing multi-angle adjustment of the detector. The angle of the detector can be dynamically adjusted according to the healing condition of the wound and actual needs, thereby ensuring the timeliness and accuracy of the detection results.

[0060] The specific implementation process is as follows: First, before monitoring, the detection plate 1 is installed above the patient's wound surface, such as the thigh position, and the straight rod 4 fixedly connected to it is driven to rotate by the rotating motor 3. Since the straight rods 4 are hinged to each other, the other ends of the straight rods 4 are rotated and matched with the hinge rods 5; therefore, when the straight rods 4 rotate, they can drive the hinge rods 5 that rotate with them to rotate together. Since the adjacent hinge rods 5 are hinged to each other, the hinge rods 5 are rotated and matched with the extension rods 7, the extension rods 7 penetrate the detection plate 1 and slide with the detection plate 1, and the two ends of the detection plate 1 are integrally formed with stoppers; and the hinge rods 5 are also hinged with the swing rods 6, and the other end of the swing rods 6 is rotated and matched with the bracket 2; therefore, when the hinge rods 5 rotate to drive the extension rods 7 to contact the stoppers, the straight rods 4 on both sides can squeeze the hinge rods 5, and when squeezing, the movement trajectory of the extension rods 7 moves downward, thereby generating an arc-shaped movement trajectory. In this process, the swing rods 6 provide a limiting function. The angle of the detector is then adjusted by rotating the rod 9, so that the detector can achieve multi-angle detection effects. In addition, the monitoring system can intelligently monitor the wound surface, provide continuous and real-time biological parameter monitoring, ensure that the doctor can understand the latest status of the wound surface at any time, and set different thresholds according to the specific conditions of different patients to achieve personalized monitoring and management.

[0061] The present invention forms a mechanical structure capable of generating an arc-shaped motion trajectory through the mutual cooperation of the straight rod 4, the hinged rod 5, the swing rod 6 and the extension rod 7; this design enables the detector to move along the arc path and better adapt to wounds of different positions and shapes. By cooperating with the rotating rod 9 and the drive motor 14, the angle adjustment range of the detector is further increased to ensure that different areas of the wound can be fully covered, thereby improving the comprehensiveness and accuracy of the detection. The use of flexible detector positioning and multi-angle detection capabilities makes the monitoring process more in line with the actual needs of the patient, helps to obtain more comprehensive biological parameter information, and provides support for the formulation of personalized treatment plans. Through the in-depth analysis of biological parameters by the artificial intelligence algorithm of the monitoring system, the different stages and potential risks of wound healing can be accurately identified, which helps to improve the pertinence and effectiveness of wound treatment and reduce the blindness and uncertainty in the treatment process. It can also provide patients with personalized treatment suggestions and rehabilitation guidance to help patients better understand their own conditions and actively participate in the treatment process.

[0062] Embodiment 2:

[0063] The difference from the above embodiment is that a clamp is fixedly connected to the bracket 2 with bolts, and the clamp is detachably snap-fitted to the bed.

[0064] The specific implementation process is as follows: Through the design of the clamp, the monitoring device can be fixed on the bed to ensure that the device will not fall off or shift due to patient movement or external interference during use.

[0065] Embodiment 3:

[0066] like Figure 2 As shown, the difference from the above embodiment is that the left side of the base plate 8 is bolted and fixedly connected with the symmetrically arranged rotating plates 16, the rotating rods 9 are all rotatably matched with the rotating plates 16, the rotating rods 9 on the right side penetrate the rotating plates 16 and are rotatably matched with the rotating plates 16, and the connecting plate 10 is located on the rotating rods between adjacent rotating plates 16.

[0067] The specific implementation process is as follows: the design of the rotating plate 16 helps to balance and disperse the force generated by the rotating rod 9 during rotation, thereby improving the stability of the entire structure.

[0068] Embodiment 4:

[0069] like Figure 1 As shown, the difference from the above embodiment is that a sliding plate 17 is fixedly connected to the right side of the bottom plate 8 by bolts, and a sliding groove for the rack 12 to move is opened on the sliding plate 17.

[0070] The specific implementation process is as follows: the slide groove provided on the sliding plate 17 provides a clear movement trajectory for the rack 12; when the rack 12 moves in the slide groove, it can be constrained and guided by the slide groove, thereby ensuring that the movement direction of the rack 12 is accurate and stable.

[0071] Embodiment 5:

[0072] like Figure 2 As shown, the difference from the above embodiment is that the upper end of the sliding plate 17 is fixedly connected to the limiting block 18 by screws.

[0073] The specific implementation process is as follows: the limit block 18 connected by screws to the sliding plate 17 can ensure that the rack 12 moves within a predetermined range, prevent the rack 12 from exceeding the sliding groove, provide additional protection, and further increase the stability of the device.

[0074] Embodiment 6:

[0075] like Figure 3 and Figure 4 As shown, the difference from the above embodiment is that the monitoring system includes a real-time monitoring module, a data transmission module, a data analysis module, an early warning module and an interactive module; wherein the real-time monitoring module is mainly used to monitor the biological parameters around the wound in real time. The data transmission module is used to transmit the biological parameters collected by the detector to the mobile terminal. The data analysis module is used to analyze the biological parameters and identify the different stages and potential risks of wound healing. The early warning module is used to issue an early warning message when the wound state is abnormal. The interactive module is used to use the mobile terminal to view the healing status of the wound in real time and receive treatment suggestions.

[0076] The following is a detailed explanation of the functions of each module:

[0077] The real-time monitoring module is used to monitor the biological parameters around the wound in real time, including temperature, humidity, pH value, trimethylamine, uric acid and wound moisture.

[0078] The data transmission module is used to transmit the biological parameters collected by the detector to the mobile terminal using wireless communication technology; the wireless communication technology includes 4G, 5G, Bluetooth and WiFi.

[0079] The data analysis module is used to analyze biological parameters using artificial intelligence algorithms to identify different stages of wound healing and potential risks.

[0080] Specifically, the artificial intelligence algorithm uses deep learning technology for analysis, and its specific steps are as follows:

[0081] S1. Data preprocessing: The collected biological parameters were cleaned, Z-score normalized, and features extracted. Missing values, outliers, and noise data were removed, and features with significant effects on wound healing were extracted and constructed.

[0082] S2. Model training: Select the convolutional neural network (CNN) deep learning model, divide the data into training set, validation set, and test set; and use cross-validation to obtain the hyperparameter combination.

[0083] S3. Model evaluation: Use the test set to evaluate the model's accuracy, recall, F1 score, and AUC-ROC curve indicators to evaluate the model performance; check for cases where the model predicts incorrectly.

[0084] S4. Prediction and decision-making: Input the newly collected biological parameters into the trained model to predict the status and development trend of wound healing; provide treatment recommendations based on the prediction results; and issue early warning signals when potential risks that may affect wound healing are detected.

[0085] S5. Feedback loop: Regularly collect new case data, update the training set, and retrain the model based on the new data; and collect feedback from doctors and patients to continuously optimize the algorithm and system functions.

[0086] The early warning module is used to set thresholds for different stages of wound healing and potential risks, and issue early warning information when the wound status becomes abnormal.

[0087] The interactive module is used to use a mobile terminal to view the wound healing status in real time and receive treatment suggestions.

[0088] The specific implementation process is as follows: by real-time monitoring of biological parameters around the wound, using advanced artificial intelligence algorithms to conduct in-depth analysis of biological parameters, automatically identifying different stages of wound healing, providing scientific evaluation results, helping doctors to promptly discover and deal with problems, and improving treatment effects. Different thresholds can be set according to the specific conditions of different patients to achieve personalized monitoring and management. And the healing status of the wound can be viewed in real time through mobile terminals to improve the transparency and timeliness of information.

[0089] By using deep learning algorithms to train biological parameters, the trained deep learning model can accurately predict the state and development trend of wound healing based on the newly collected biological parameters. Based on the prediction results, the algorithm can provide patients with personalized treatment recommendations and help doctors develop more scientific and effective treatment plans.

[0090] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A wound healing monitoring platform combining biosensing and artificial intelligence analysis, comprising an arc-shaped detection plate (1), on which a detector for detecting biological parameters of the wound is provided, characterized in that: It also includes a monitoring system, which is electrically connected to the detector; an adjustment component for adjusting the position of the detector is provided on the outer side of the detection plate (1); The positioning assembly comprises a bracket (2), a controller, a rotating member and a plurality of mutually hinged straight rods (4), wherein the controller is used to control the operation of the rotating member; the rotating member is fixedly connected to the bracket (2), and the output shaft of the rotating member passes through the bracket (2) and is fixedly connected to one of the straight rods (4); one end of the straight rod (4) away from the rotating member is rotatably matched with a plurality of hinged rods (5); one end of the hinged rod (5) away from the straight rod (4) is hinged to each other, and the plurality of hinged rods (5) form a movable quadrilateral structure; The bracket (2) is also rotatably engaged with a swing rod (6), and one end of the swing rod (6) away from the bracket (2) is hingedly connected to the hinge rod (5) adjacent thereto; the bottom end of the movable quadrilateral is rotatably engaged with an L-shaped extension rod (7), the extension rod (7) penetrates the detection plate (1) and is slidably engaged with the detection plate (1), and both ends of the detection plate (1) are fixedly connected with stoppers; the extension rod (7) is also provided with an angle adjustment component for adjusting the angle of the detector.

2. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 1 is characterized in that: The angle adjustment component comprises a base plate (8), the base plate (8) being fixedly connected to the extension rod (7); a rotating rod (9) is rotatably matched with a side of the base plate (8) away from the extension rod (7); a driving component for driving the rotating rod (9) to rotate is provided on the base plate (8); a connecting plate (10) is fixedly connected to the rotating rod (9); and a rotating component for rotating a detector is provided on the connecting plate (10).

3. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 2 is characterized in that: The driving assembly comprises a gear (11), a rack (12) and a telescopic member, and a controller is used to control the movement of the telescopic member; the telescopic member is fixedly connected to a side of a bottom plate (8) close to a rotating rod (9), and an output shaft of the telescopic member is fixedly connected to the rack (12); the rack (12) and the gear (11) are meshed with each other, and the gear (11) and the rotating rod (9) are coaxially fixedly connected.

4. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 3 is characterized in that: The rotating assembly comprises a driving member and a rotating disk (15); a controller is used to control the operation of the driving member; the driving member is fixedly connected to an end of the connecting plate (10) away from the rotating rod (9); an output shaft of the driving member is fixedly connected to the rotating disk (15); and a side of the rotating disk (15) away from the driving member is fixedly connected to the detector.

5. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 4 is characterized in that: The bracket (2) is also fixedly connected with a clamp, and the clamp is detachably connected to the hospital bed.

6. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 5 is characterized in that: A symmetrically arranged rotating plate (16) is fixedly connected to a side of the bottom plate (8) close to the rotating rod (9); the rotating rods (9) are all rotatably matched with the rotating plates (16); the rotating rods (9) on a side close to the gear (11) penetrate the rotating plate (16) and are all rotatably matched with the rotating plate 16; and the connecting plate (10) is located on the rotating rods (9) between adjacent rotating plates (16).

7. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 6 is characterized in that: A sliding plate (17) is fixedly connected to one side of the bottom plate (8) close to the rack (12), and a sliding groove for the rack (12) to move is provided on the sliding plate (17).

8. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 7 is characterized in that: One end of the sliding plate (17) away from the rack (12) is fixedly connected to a limiting block (18).

9. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 8, characterized in that: The monitoring system includes real-time monitoring module, data transmission module, data analysis module, early warning module and interaction module; Real-time monitoring module, used to monitor biological parameters around the wound surface in real time, including temperature, humidity, pH value, trimethylamine, uric acid and wound moisture; A data transmission module is used to transmit the biological parameters collected by the detector to a mobile terminal using wireless communication technology; the wireless communication technology includes 4G, 5G, Bluetooth and WiFi; Data analysis module, which uses artificial intelligence algorithms to analyze biological parameters and identify different stages of wound healing and potential risks; The early warning module is used to set the thresholds for different stages of wound healing and potential risks, and issue early warning information when the wound state is abnormal; The interactive module is used to use a mobile terminal to view the wound healing status in real time and receive treatment suggestions.

10. The wound healing monitoring platform combining biosensing and artificial intelligence analysis according to claim 9, characterized in that: The artificial intelligence algorithm uses deep learning technology for analysis, and its specific steps are as follows: S1. Data preprocessing: data cleaning, data standardization and feature extraction of the collected biological parameters; S2. Model training: Select a suitable deep learning model, divide the data into training set, validation set and test set; and use cross-validation to obtain hyperparameter combinations; S3. Model evaluation: Use the test set to evaluate the model's accuracy, recall, F1 score, and AUC-ROC curve indicators to evaluate the model performance; check for cases where the model predicts errors; S4. Prediction and decision-making: Input the newly collected biological parameters into the trained model to predict the state and development trend of wound healing; provide treatment recommendations based on the prediction results; and issue warning signals when potential risks that may affect wound healing are detected; S5. Feedback loop: Regularly collect new case data, update the training set, and retrain the model based on the new data; and collect feedback from doctors and patients to continuously optimize the algorithm and system functions.

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