Automatic diabetes wound cleaning and managing device based on artificial intelligence technology

Abstract

The invention discloses an automatic diabetes wound cleaning and managing device based on an artificial intelligence technology, and relates to the technical field of medical health. According to the technical scheme, the system is characterized by comprising an intelligent sensing and wound surface recognition module, a personalized cleaning scheme module, an automatic cleaning system module, a wound surface healing monitoring and early warning module, a data storage and remote management module and a patient safety and comfort guarantee module. Through the integrated sensor, the AI algorithm, the automatic cleaning system and the data management module, the wound surface type and the cleaning degree can be autonomously recognized, and the cleaning strategy is intelligently adjusted according to the wound surface healing state of a patient. In addition, the device is provided with a wound surface monitoring system, wound surface healing progress is tracked in real time, and data are synchronized to a cloud end, so that a doctor can remotely diagnose and adjust a treatment scheme.

Description

Technical Field

[0001] The present invention relates to the field of medical health technology, and more specifically, to an automated diabetic wound cleaning and management device based on artificial intelligence technology. Background Art

[0002] Diabetic wounds, as a chronic and difficult-to-heal wound, are crucial to the recovery of patients. With the rapid development of artificial intelligence (AI) technology, especially the advancement of image recognition, data analysis and automation technology, it is now possible to develop devices that can automatically identify wound types and cleaning levels, and intelligently adjust cleaning strategies according to the patient's wound healing status. The development of these technologies provides new solutions for diabetic wound management, making automated and personalized wound cleaning and management possible.

[0003] At present, the cleaning and management of diabetic wounds mainly rely on manual operations, including the use of image sensors for wound identification, but these methods lack the deep integration and automation of AI technology. Existing cleaning solutions may not fully utilize AI algorithms and patient historical data to customize personalized cleaning solutions, resulting in limited consistency and effectiveness of treatment plans. Some automated cleaning tools on the market may not have the ability to automatically select and execute multiple cleaning modes, and cannot be adjusted according to the specific conditions of the wound. In addition, existing monitoring systems may rely on regular inspections rather than real-time monitoring of the wound environment and healing conditions, which limits timely response to dynamic changes in the wound. Existing data storage and remote management systems may not realize real-time upload and cloud storage of data, limiting the timeliness of remote access and treatment plan adjustments.

[0004] Therefore, the present invention aims to provide an automated diabetic wound cleaning and management device that can autonomously identify wound type and cleaning degree, and intelligently adjust the cleaning strategy according to the patient's wound healing status by integrating high-precision sensors, advanced AI algorithms, multifunctional automated cleaning systems and efficient data management modules, so as to overcome the shortcomings of the prior art, improve the accuracy and effect of wound cleaning, realize personalized care, real-time monitoring and early warning, and remote management and data sharing. Summary of the invention

[0005] The purpose of the present invention is to provide an automated diabetic wound cleaning and management device based on artificial intelligence technology to solve the problems of low efficiency, poor accuracy and insufficient personalized care in traditional wound cleaning in the prior art.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions: an automated diabetic wound cleaning and management device based on artificial intelligence technology, comprising the following modules:

[0007] The intelligent sensing and wound recognition module is used to automatically identify the size, shape, depth and infection status of diabetic wounds through high-precision image sensors and AI image recognition technology;

[0008] The personalized cleaning solution module is used to customize personalized wound cleaning solutions by combining AI algorithms with patient historical data;

[0009] The automated cleaning system module integrates a variety of wound cleaning tools to automatically perform cleaning operations;

[0010] The wound healing monitoring and early warning module is used to monitor the wound environment and healing status in real time;

[0011] The data storage and remote management module is used to upload cleaning and monitoring data to the cloud in real time for remote access by doctors and nursing staff;

[0012] The patient safety and comfort assurance module has a built-in AI safety algorithm that dynamically evaluates the wound condition during each cleaning process and adjusts the cleaning intensity and method in real time.

[0013] The present invention is further configured as follows: the intelligent sensing and wound surface recognition module includes a high-precision image sensor and an AI image recognition algorithm, the high-precision image sensor is used to capture wound surface images; the AI ​​image recognition algorithm is used to analyze images and identify wound surface features.

[0014] The present invention is further configured as follows: the automatic cleaning system module includes spray cleaning, ultrasonic cleaning and negative pressure cleaning modes.

[0015] The present invention is further configured as follows: the wound healing monitoring and early warning module includes a variety of sensors for monitoring the wound environment and an AI algorithm for analyzing monitoring data and identifying early signs of infection or deterioration.

[0016] The present invention is further configured as follows: the sensor includes a temperature sensor, a humidity sensor and a pH value sensor.

[0017] The present invention is further configured as follows: the device has a built-in AI algorithm module, which communicates with the intelligent sensing and wound surface identification module to analyze the sensing data and determine the best cleaning method.

[0018] Another object of the present invention is to provide an automated diabetic wound cleaning and management method based on artificial intelligence technology, comprising the following steps:

[0019] a. Use high-precision image sensors and AI image recognition technology to automatically identify the size, shape, depth and infection status of diabetic wounds;

[0020] b. Combine AI algorithms with patient historical data to customize personalized wound cleaning solutions and automatically select the appropriate cleaning mode;

[0021] c. Automatically perform cleaning operations through integrated multiple wound cleaning tools;

[0022] d. Use multiple built-in sensors, such as temperature, humidity, and pH sensors, to monitor the wound environment and healing status in real time;

[0023] e. Analyze monitoring data through AI algorithms to identify early signs of infection or deterioration and automatically issue early warning signals;

[0024] f. Upload all cleaning and monitoring data to the cloud in real time, allowing doctors and nurses to remotely access and adjust treatment plans;

[0025] g. The built-in AI safety algorithm dynamically evaluates the wound condition during each cleaning process and adjusts the cleaning intensity and method in real time.

[0026] By adopting the above technical solution, the present invention uses high-precision image sensors and AI image recognition technology to automatically identify the size, shape, depth and infection of diabetic wounds. This intelligent sensing and wound recognition module significantly improves the accuracy of cleaning work. By combining AI algorithms to analyze sensor data, the device can determine the best cleaning method to ensure that the wound is cleaned thoroughly and not over-operated, thereby reducing the risk of wound infection and promoting accelerated healing; by combining AI algorithms with patient historical data, the present invention can customize personalized wound cleaning solutions and automatically select appropriate cleaning modes, such as spray, ultrasound, negative pressure cleaning, etc., to meet the needs of different patients. This personalized cleaning solution module helps to improve the effectiveness of treatment because it can adapt to the wound characteristics and healing process of different patients.

[0027] The automated cleaning system module of the present invention integrates a variety of wound cleaning tools and can automatically perform cleaning operations, reducing the problem of insufficient or excessive cleaning caused by human factors. This automated operation not only improves cleaning efficiency, but also helps reduce the risk of pain and infection caused by the cleaning process; the wound healing monitoring and early warning module of the present invention monitors the wound environment and healing status in real time through a variety of built-in sensors, and the AI ​​algorithm analyzes the data to identify early signs of infection or deterioration, and automatically sends out early warning signals. This real-time monitoring and early warning mechanism enables doctors to adjust treatment plans in a timely manner to reduce the possibility of worsening of the disease;

[0028] The data storage and remote management module of the present invention uploads all cleaning and monitoring data to the cloud in real time, allowing doctors and caregivers to remotely access the patient's wound healing data through mobile devices or computers. This remote management function improves nursing efficiency and reduces the burden of patients going back and forth for medical treatment; the patient safety and comfort guarantee module has a built-in AI safety algorithm that can dynamically evaluate the wound condition during each cleaning process and adjust the cleaning intensity and method in real time. This dynamic evaluation and adjustment mechanism ensures the safety and comfort of wound repair and improves the patient's treatment experience.

[0029] In summary, the present invention has the following beneficial effects:

[0030] 1. The present invention can effectively reduce errors in cleaning through AI's precise identification and automated cleaning technology, ensuring that the wound surface is cleaned thoroughly without excessive operation, thereby greatly reducing the risk of wound infection and promoting accelerated healing. The device of the present invention can dynamically adjust the cleaning method according to the individual patient's wound surface condition, provide precise personalized treatment, and help improve the effectiveness of treatment.

[0031] 2. Through the combination of sensors and AI technology, the present invention can monitor the wound healing situation 24 hours a day, issue timely warnings when abnormalities are found, reduce the possibility of disease deterioration, and enable doctors to adjust treatment plans in time; through cloud data storage and remote management functions, doctors can obtain patients' wound healing data in real time, facilitate timely adjustment of treatment plans, improve nursing efficiency and reduce the burden of patients going back and forth for medical treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is an architectural diagram of an automated diabetic wound cleaning and management device based on artificial intelligence technology in an embodiment of the present invention.

[0033] Figure 2 It is a flow chart of an automated diabetic wound cleaning and management method based on artificial intelligence technology in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The following is combined with Figure 1 The present invention is described in further detail.

[0035] Embodiment 1: Automated diabetic wound cleaning and management device based on artificial intelligence technology, such as Figure 1 As shown, the system component setting: the device includes six main modules: intelligent sensing and wound recognition module, personalized cleaning solution module, automatic cleaning system module, wound healing monitoring and early warning module, data storage and remote management module, and patient safety and comfort assurance module.

[0036] Intelligent sensing and wound recognition module: A high-precision image sensor is installed at the front end of the device to capture high-definition images of diabetic wounds. This sensor is responsible for capturing high-resolution images of diabetic wounds. It is able to provide enough details so that the AI ​​algorithm can accurately analyze the characteristics of the wound. The AI ​​image recognition algorithm integrated in the module is trained through deep learning technology and can identify and classify the size, shape, depth and infection of the wound. These algorithms are able to extract key features from the image and compare them with known wound types in the database to determine the status of the wound.

[0037] Personalized cleaning program module: This module uses AI algorithms to analyze data from the intelligent sensing and wound recognition modules, and combines the patient's historical data (such as previous wound healing conditions, drug reactions, etc.) to develop a personalized cleaning program. The AI ​​algorithm can adjust the cleaning intensity, frequency and method according to the specific characteristics of the wound.

[0038] Automated cleaning system module: This module contains a variety of cleaning tools and can automatically select the appropriate cleaning mode according to the personalized cleaning plan. For example, spray cleaning may be selected for lightly contaminated wounds, while ultrasonic or negative pressure cleaning may be required for deeper wounds. The automated system ensures the consistency and accuracy of the cleaning operation.

[0039] Wound healing monitoring and early warning module: includes a variety of sensors (temperature, humidity, pH sensors) to monitor the environmental conditions of the wound. These sensors provide real-time data, and AI algorithms analyze this data to identify early signs of infection or deterioration. If an abnormality is detected, the system will automatically issue an early warning signal to prompt medical staff to take action.

[0040] Data storage and remote management module: Cleaning and monitoring data are collected in real time and uploaded to a secure cloud database. This allows doctors and nurses to remotely access patients' wound healing data and adjust treatment plans in a timely manner.

[0041] Patient safety and comfort module: The built-in AI safety algorithm continuously monitors the wound surface and dynamically adjusts the cleaning intensity and method based on the monitoring results. For example, if the sensor detects that the wound surface is too sensitive or has signs of bleeding, the AI ​​algorithm will reduce the cleaning intensity to avoid discomfort or harm to the patient.

[0042] Embodiment 2: An automated diabetic wound cleaning and management method based on artificial intelligence technology, as shown in the attached Figure 2 As shown, the following steps are included:

[0043] 1. Wound surface identification: The patient points the device at the wound surface, the high-precision image sensor captures the image, and the AI ​​image recognition algorithm analyzes and identifies the wound surface features.

[0044] 2. Plan formulation: Based on the recognition results and patient historical data, the AI ​​algorithm generates a personalized cleaning plan.

[0045] 3. Cleaning execution: The automated cleaning system selects the appropriate cleaning mode (spray, ultrasonic, negative pressure) according to the plan to perform the cleaning operation.

[0046] 4. Monitoring and early warning: During the cleaning process, sensors monitor the wound environment in real time, and AI algorithms analyze data and provide real-time early warnings.

[0047] 5. Data management: Cleaning and monitoring data are recorded and uploaded to the cloud, where doctors and caregivers can access them remotely and adjust treatment plans in a timely manner.

[0048] 6. Safety and comfort guarantee: AI safety algorithm dynamically adjusts the cleaning intensity and method based on monitoring data to ensure that the cleaning process is both effective and comfortable.

[0049] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. An automated diabetic wound cleaning and management device based on artificial intelligence technology, characterized by: Includes the following modules: The intelligent sensing and wound recognition module is used to automatically identify the size, shape, depth and infection status of diabetic wounds through high-precision image sensors and AI image recognition technology; The personalized cleaning solution module is used to customize personalized wound cleaning solutions by combining AI algorithms with patient historical data; The automated cleaning system module integrates a variety of wound cleaning tools to automatically perform cleaning operations; The wound healing monitoring and early warning module is used to monitor the wound environment and healing status in real time; The data storage and remote management module is used to upload cleaning and monitoring data to the cloud in real time for remote access by doctors and nursing staff; The patient safety and comfort assurance module has a built-in AI safety algorithm that dynamically evaluates the wound condition during each cleaning process and adjusts the cleaning intensity and method in real time.

2. The automated diabetic wound cleaning and management device based on artificial intelligence technology according to claim 1 is characterized by: The intelligent sensing and wound surface recognition module includes a high-precision image sensor and an AI image recognition algorithm. The high-precision image sensor is used to capture wound surface images; the AI ​​image recognition algorithm is used to analyze images and identify wound surface features.

3. The automated diabetic wound cleaning and management device based on artificial intelligence technology according to claim 1 is characterized by: The automated cleaning system module includes spray cleaning, ultrasonic cleaning and negative pressure cleaning modes.

4. The automated diabetic wound cleaning and management device based on artificial intelligence technology according to claim 1 is characterized by: The wound healing monitoring and early warning module includes a variety of sensors for monitoring the wound environment and an AI algorithm for analyzing monitoring data and identifying early signs of infection or deterioration.

5. The automated diabetic wound cleaning and management device based on artificial intelligence technology according to claim 4 is characterized by: The sensors include a temperature sensor, a humidity sensor and a pH sensor.

6. The automated diabetic wound cleaning and management device based on artificial intelligence technology according to claim 1 is characterized by: The device has a built-in AI algorithm module that communicates with the intelligent sensor and wound surface recognition module to analyze the sensor data and determine the best cleaning method.

7. An automated diabetic wound cleaning and management method based on artificial intelligence technology, characterized in that: The method comprises the following steps: a. Use high-precision image sensors and AI image recognition technology to automatically identify the size, shape, depth and infection status of diabetic wounds; b. Combine AI algorithms with patient historical data to customize personalized wound cleaning solutions and automatically select the appropriate cleaning mode; c. Automatically perform cleaning operations through integrated multiple wound cleaning tools; d. Use multiple built-in sensors, such as temperature, humidity, and pH sensors, to monitor the wound environment and healing status in real time; e. Analyze monitoring data through AI algorithms to identify early signs of infection or deterioration and automatically issue early warning signals; f. Upload all cleaning and monitoring data to the cloud in real time, allowing doctors and nurses to remotely access and adjust treatment plans; g. The built-in AI safety algorithm dynamically evaluates the wound condition during each cleaning process and adjusts the cleaning intensity and method in real time.

Images