Intelligent AI equipment and system for full-flow damage judgment of medical apparatus and instruments

Abstract

The invention relates to the field of medical equipment, in particular to an intelligent AI device and system for full-flow damage judgment of a medical instrument, and the device comprises a detection device which comprises an image collection assembly, an illumination assembly and a main control board, the detection device works according to an instruction of the main control board, and the illumination assembly is used for adjusting the illumination intensity. The image acquisition assembly is used for acquiring image data of the current medical instrument; the control terminal comprises an identification module, an image acquisition module and an image damage judgment module, the identification module carries out verification according to the identity information of the operator input by the identification module, and after the verification is passed, the image acquisition module acquires the state information of the image data received by the main control board in the detection device; and the image damage judgment module analyzes and compares the image data, and judges and records the current damage condition of the medical instrument. The damage degree of the medical instrument is automatically detected, subjective errors and time consumption of manual inspection are reduced, and the tracking capacity of the medical instrument in the handover stage is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of medical equipment, and in particular to an intelligent AI device and system for whole-process damage identification of medical devices. Background Art

[0002] In the current medical environment, medical device management must not only ensure that the equipment will not be lost during use and handover, but also maintain its intact state. Medical devices are usually handled by nurses in a unified manner, and are uniformly recycled after use and sent to the sterilization supply center for necessary cleaning and functional inspections. However, in this process, there are two problems with the existing technology. First, the existing inspection methods for medical devices usually rely on manual inspection, which is not only time-consuming but may also miss minor damage, resulting in possible safety risks in actual use. In addition, the inefficiency of manual inspection will also increase the cost and complexity of hospital operations. Second, in the process of recovering the equipment from the doctor and preparing to send it to the sterilization supply center, due to the lack of an effective tracking and management mechanism, the problem of equipment loss occurs frequently. This loss problem not only leads to asset loss, but also often causes unclear division of responsibilities, thereby causing responsibility disputes and coordination problems between nurses, doctors and supply centers.

[0003] Therefore, it is necessary to develop an intelligent AI device and system for the whole process of medical device damage identification, which can automatically detect and manage the damage of medical devices and track the status of medical devices, so as to ensure that medical devices meet all safety and functional standards before reuse. This will greatly improve the efficiency and safety of medical device management, reduce labor costs, and improve the quality of overall medical services. Summary of the invention

[0004] In view of the defects in the prior art, the purpose of the present invention is to provide an intelligent AI device and system for the whole process of medical device damage identification. By controlling the program and detection device of the terminal, real-time recording and ensuring that medical machinery can be accurately monitored during the handover stage are carried out. The current medical device image is automatically calculated and analyzed to detect its damage in time, and its status and operator information are updated in real time. The efficiency of medical device management and damage identification capabilities are significantly improved, while also reducing the risk of device loss during the handover process.

[0005] The present invention provides an intelligent AI device for whole-process damage identification of medical devices, comprising: The detection device comprises an image acquisition component, a lighting component and a main control board, wherein the image acquisition component and the lighting component are respectively connected to the main control board through electronic circuits, the detection device works according to the instructions of the main control board when working, the lighting component is used to adjust the lighting intensity, and the image acquisition component is used to collect image data of the current medical device; The control terminal includes an identification module, an image acquisition module and an image damage judgment module, wherein the identification module performs verification according to the identity information of the operator entered by the identification module. After verification, the image acquisition module collects the status information of the image data received by the main control board in the detection device; the image damage judgment module analyzes and compares the image data, judges and records the damage status of the current medical device.

[0006] Furthermore, it also includes a transparent plate, which is located at the front end of the body and is used to place the medical machine for detection; wherein a marking area is provided on the transparent plate for calibrating with the first main camera and the second main camera of the image acquisition component.

[0007] Furthermore, the image acquisition component is fixed in the body and is used to capture image data of medical devices in different orientations on the transparent plate; wherein the image acquisition component includes a plurality of adjustable cameras, each of which includes a small motor, a gear unit in a bracket, a movable slide rail and a base; the motor is embedded in the bracket and realizes angle and rotation adjustment of the adjustable camera through the gear unit, and the lens of the adjustable camera is connected to the movable slide rail to adjust the focal length.

[0008] Furthermore, several adjustable cameras are symmetrically arranged above, below, around the edges and at specific angles of inclination of the transparent plate for collecting all-round image data; wherein the first main camera and the second main camera are respectively located above and below the transparent plate to ensure comprehensive image data capture, calibration and capture of the medical device from a vertical direction.

[0009] Furthermore, the lighting assembly is integrated in the machine body and is equipped with an adjustment function to adjust the lighting level according to the actual working conditions; wherein, The lighting assembly includes several optical lighting units and a light intensity regulation control panel. The optical lighting unit is composed of a light source, a reflector and a diffuser and is uniformly regulated by the light intensity regulation control panel for uniform and adjustable lighting effects. The light source is installed on the inner side of the reflector to enhance the brightness of the light and point it to a specific area. The diffuser is located between the light source and the medical device to be inspected to ensure uniform distribution of light. Among them, the first optical lighting unit in the optical lighting unit is located directly above the transparent plate and is equipped with a light source that can change color and flashing speed to indicate whether multiple medical devices are placed correctly on the transparent plate.

[0010] Furthermore, the identification module includes an identity recognition unit and an item recognition unit, wherein the identity recognition unit includes a face recognition camera, a fingerprint scanner and a card reader for verifying the identity of the operator; the item recognition unit includes a barcode scanner and an RFID reader for identifying and registering the label information of the medical device.

[0011] Furthermore, the detection device and the control terminal are connected by wired / wireless communication, and the detection device and the control terminal are provided with an Ethernet interface, a USB interface, wireless communication and Bluetooth technology; the control terminal sends instructions to the main control board of the detection device for debugging the detection device and collecting image data; the control terminal analyzes the image data, identifies and manages the damage of the medical device; The detection device and the control terminal also include an image storage unit, wherein the image storage unit of the detection device is used to store image data of the detection device; the image storage unit of the control terminal is used to store image data of the detection device and the mobile device terminal.

[0012] Furthermore, the detection device and the control terminal are directly connected to the main power supply for AC power supply, and an integrated backup power supply, namely a battery, is used to prevent the main power supply from being interrupted.

[0013] Furthermore, the control terminal also includes a data feedback module and a data management module; the data feedback module performs damage registration and feedback operations based on the analysis results of the image damage judgment module; the data management module integrates the identity registration information and label information in the recognition module and the analysis results of the image damage judgment module to perform unified management of medical device data.

[0014] Based on the same inventive concept, the present invention also provides an intelligent AI system for whole-process damage identification of medical devices, which is applied to the above-mentioned intelligent AI device, including: Identification module, used to verify the identity of the operator and recognize the label information of the registered medical device.

[0015] An image acquisition module, used to receive multi-directional image data of the current medical device acquired by the detection device or mobile device according to the instruction, and perform data preprocessing on the multi-directional image data according to a preset standard; The image damage discrimination module includes an adjustment analysis unit and a damage discrimination analysis unit, wherein: An adjustment and analysis unit is used to calibrate the placement of one or more medical devices in the detection device; the position adjustment is determined by the light prompt emitted by the first optical lighting unit, and the light intensity and mode of the lighting assembly in the detection device are self-adjusted according to the calibration result and the control terminal synchronously displays the position prompt and adjustment instruction of the medical device; A damage discrimination and analysis unit, which is used to receive calibrated image data, identify the type of medical device through a deep learning algorithm, perform feature scoring on the damage on the medical device, and generate damage degree data and analysis results; The data feedback module is used to perform damage registration and feedback operations according to the analysis results of the damage discrimination and analysis unit.

[0016] The data management module is used to receive the identity registration information input from the identification module, perform the current entry and exit registration of medical devices, and also includes the full process query and update of the current medical device inventory status.

[0017] Compared with the prior art, the present invention has at least one of the following technical effects: The present invention automatically detects the degree of damage of medical devices through intelligent detection devices and control terminal programs, accurately identifies minor damage, ensures that all devices meet safety standards before being used again, reduces subjective errors and time consumption of traditional manual inspections, and greatly improves the accuracy and work efficiency of detection. In addition, through the identification module of the control terminal, the system can not only effectively enter medical devices, but also realize the identity verification of operators, thereby enhancing the tracking ability of medical devices during use and handover, effectively preventing the loss of devices, and ensuring the safety and efficiency of the medical environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. 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 work. In the drawings: Figure 1 It is a working principle diagram of the intelligent AI device for whole-process damage identification of medical devices of the present invention. DETAILED DESCRIPTION

[0019] The following will describe in detail an intelligent AI device for full-process damage identification of medical devices provided by the present invention in conjunction with the accompanying drawings. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given. However, the protection scope of the present invention is not limited to the following embodiments. Those skilled in the art can modify and polish it without changing the spirit and content of the present invention.

[0020] First embodiment In the existing technology, the management of medical devices mainly relies on manual inspection and record keeping, which is not only time-consuming but also prone to errors, especially in high-pressure and fast-paced medical environments. In addition, traditional methods also face problems of inefficiency and lack of accuracy in tracking the use, disinfection and storage of devices. The lack of effective tracking and management mechanisms in the process of recycling devices after use and sending them to disinfection centers may lead to the loss or misuse of devices, which not only increases medical costs but also poses a threat to patient safety. In response to the above problems, after an in-depth analysis of the limitations of existing technologies, a new technical solution was proposed based on this. This solution uses intelligent AI devices and systems to automatically and accurately identify the damage and loss of medical devices by integrating automated image acquisition, efficient lighting and multi-dimensional data analysis. A high-resolution camera is used to take all-round photos of the device, and the image data is analyzed through a deep learning algorithm to detect and mark any potential damage or defects in real time. At the same time, the integrated RFID technology and barcode scanning functions ensure the tracking and management of the device throughout the entire circulation process, significantly improving the efficiency and safety of medical device management. In addition, the system also includes identity recognition modules, such as face recognition and fingerprint scanning, which are used to verify the identity of the operator, and an integrated information management module is used to register the entry and exit of medical devices, effectively tracking the use history of the device, which can not only reduce labor costs, but also monitor the entry and exit history of the entire process to reduce errors and omissions. The specific implementation method is as follows: The present invention provides an intelligent AI device for whole-process damage identification of medical devices, comprising: The detection device includes an image acquisition component, a lighting component and a main control board; the image acquisition component and the lighting component are respectively connected to the main control board through electronic circuits. When working, the detection device works according to the instructions of the main control board. The lighting component is used to adjust the lighting intensity, and the image acquisition component is used to collect image data of the current medical device. At the same time, the object placement table of the detection device is a transparent plate, which is located at the front end of the body and is used to place the medical machine for detection; a marking area is provided on the transparent plate for calibrating with the first main camera and the second main camera of the image acquisition component.

[0021] The image acquisition component is fixed in the body and is responsible for obtaining image information from the medical device. This component includes multiple sets of high-resolution cameras installed in strategic locations of the detection device to capture images of medical devices from multiple angles to capture subtle features on the surface of the device, including any wear, cracks or other forms of damage.

[0022] Specifically, the image acquisition component includes several adjustable cameras, and each camera is mounted on a bracket containing a gear unit and fixed on a base. Each adjustable camera is equipped with a small motor, which drives the gear unit in the bracket to adjust the angle of rotation and tilt control. In addition, the lens part of the camera is mounted on a slide rail that can move back and forth, which is used to adjust the focal length to ensure that medical devices of different sizes and shapes can be clearly captured. The adjustment of the slide rail is controlled by another small motor, which enhances the flexible adjustment ability of the focus.

[0023] Several adjustable cameras are symmetrically arranged above, below, around the edges and at specific angles of the transparent plate for collecting all-round image data; among them, the first main camera and the second main camera are respectively located above and below the transparent plate to ensure comprehensive image data capture, calibration and capture of the medical device from a vertical direction.

[0024] The lighting assembly is integrated in the body and is equipped with an adjustment function to adjust the lighting level according to actual working conditions; wherein, the lighting assembly includes a plurality of optical lighting units and a light intensity adjustment control panel, the optical lighting unit is composed of a light source, a reflector and a diffuser and is uniformly regulated by the light intensity adjustment control panel for uniform and adjustable lighting effects; the light source is installed on the inner side of the reflector to enhance the brightness of the light and point it to a specific area; the diffuser is located between the light source and the medical device to be detected to ensure uniform distribution of light; wherein, the first optical lighting unit in the optical lighting unit is located directly above the transparent plate and is equipped with a light source that can change color and flashing speed to indicate whether multiple medical devices are correctly placed on the transparent plate.

[0025] Specifically, in the lighting assembly, a number of light sensors are installed, located on the side and top of the body, close to the light source device. These sensors are responsible for real-time monitoring of the ambient light intensity and the light intensity emitted by the device, and adjusting the brightness and mode of the light source according to the collected data. This configuration ensures that the light sensors can accurately capture the ambient and device light. Based on this data, the light intensity regulation control board will automatically adjust the light source to keep the lighting effect within the optimal threshold range, thereby optimizing the quality of image acquisition.

[0026] The control terminal includes an identification module, an image acquisition module and an image damage judgment module, wherein the identification module performs verification according to the identity information of the operator entered by the identification module. After verification, the image acquisition module collects the status information of the image data received by the main control board in the detection device; the image damage judgment module analyzes and compares the image data, judges and records the damage status of the current medical device.

[0027] The identification module includes an identity recognition unit and an item recognition unit. The identity recognition unit includes a face recognition camera, a fingerprint scanner and a card reader for verifying the identity of the operator; the item recognition unit includes a barcode scanner and an RFID reader for identifying and registering the label information of the medical device.

[0028] The detection device and the control terminal are connected by wired / wireless communication. The detection device and the control terminal are provided with Ethernet interface, USB interface, wireless communication and Bluetooth technology. The control terminal sends instructions to the main control board of the detection device to debug the detection device and collect image data. The control terminal analyzes the image data to identify and manage the damage of the medical device. The detection device and the control terminal also include an image storage unit, wherein the image storage unit of the detection device is used to store image data of the detection device; the image storage unit of the control terminal is used to store image data of the detection device and the mobile device terminal.

[0029] The detection device and control terminal are directly connected to the main power supply for AC power supply, and an integrated backup power supply, namely battery power supply, is used to prevent the main power supply from being interrupted.

[0030] The control terminal also includes a data feedback module and a data management module; the data feedback module performs damage registration and feedback operations based on the analysis results of the image damage discrimination module; the data management module integrates the identity registration information and label information in the recognition module and the analysis results of the image damage discrimination module to perform unified management of medical device data.

[0031] Second embodiment Based on the same inventive concept, the present invention also provides an intelligent AI system for whole-process damage identification of medical devices, which is applied to the above-mentioned intelligent AI device, including: Identification module, used to verify the identity of the operator and recognize the label information of the registered medical device.

[0032] An image acquisition module, used to receive multi-directional image data of the current medical device acquired by the detection device or mobile device according to the instruction, and perform data preprocessing on the multi-directional image data according to a preset standard; The image damage discrimination module includes an adjustment analysis unit and a damage discrimination analysis unit, wherein: An adjustment and analysis unit is used to calibrate the placement of one or more medical devices in the detection device; the position adjustment is determined by the light prompt emitted by the first optical lighting unit, and the light intensity and mode of the lighting assembly in the detection device are self-adjusted according to the calibration result and the control terminal synchronously displays the position prompt and adjustment instruction of the medical device; A damage discrimination and analysis unit, which is used to receive calibrated image data, identify the type of medical device through a deep learning algorithm, perform feature scoring on the damage on the medical device, and generate damage degree data and analysis results; The data feedback module is used to perform damage registration and feedback operations according to the analysis results of the damage discrimination and analysis unit.

[0033] The data management module is used to receive the identity registration information input from the identification module, perform the current entry and exit registration of medical devices, and also includes the full process query and update of the current medical device inventory status.

[0034] Third embodiment In order to further explain the intelligent AI device of the present invention and its practical application, this article will introduce the use scenarios and specific operation processes of the device in hospital outpatient clinics and departments through the third embodiment. This embodiment will show how to use the present invention to solve common problems in medical device management, including device damage detection, identity authentication, and device usage records, thereby improving the safety and efficiency of medical services.

[0035] In the outpatient clinics and departments of hospitals, medical devices are used frequently and in various ways on a daily basis, involving multiple operators, including those who borrow and return the devices. These devices must be strictly inspected for damage before and after use to ensure the functionality and safety of the devices.

[0036] First of all, regarding the use process of medical machinery, identity authentication is performed through the identity recognition unit, which is authenticated through a face recognition camera, fingerprint scanner and card reader to ensure that each operation is recorded and the corresponding authority management is carried out, thereby preventing unauthorized operators from accessing and using it. The card reader is used to identify the employee's identity card, allowing temporary login and authorization. When medical personnel such as nurses or technicians need to borrow or return medical equipment, their identity can be quickly verified by swiping the card. This method not only improves the convenience of the process, but also enhances the security of the system, ensuring that only authorized personnel can access and operate medical equipment. For example, setting a temporary identity in the identity recognition unit, in some cases such as when temporary workers or visiting scholars need to access restricted medical equipment. The system administrator can issue limited-time or specific permissions to these temporary users. After identity authentication, these users can use the relevant equipment within the authorized time. Such functions ensure facility security while allowing flexibility and adaptation to specific situations, avoiding unnecessary allocation of long-term permissions, while maintaining strict control over the use of equipment.

[0037] The system design of this intelligent AI device includes multi-level permission settings to ensure the security of the device and data and their reasonable use. Specific permissions may include: Administrators can configure system settings, including the allocation of user rights, setting of system parameters, and maintenance and upgrade of equipment. Administrators are also responsible for monitoring the operating status and security of the system and handling abnormal situations in the system.

[0038] Operators are mainly responsible for daily equipment operations, such as the storage and retrieval of medical devices, including the registration, return, inspection and cleaning of devices. Operators can access limited system functions, mainly those directly related to device management.

[0039] Auditors are responsible for auditing and checking the usage and history of equipment to ensure that all operations comply with regulations and standards. They also include viewing operation logs and conducting compliance checks, but cannot modify data or system settings.

[0040] Temporary permissions. These can be set up for visitors or temporary employees to allow them to use specific devices or access specific data for a limited time. These permissions are controlled by specific identification methods such as card readers, ensuring access is only provided when necessary.

[0041] Through such a permission hierarchy, smart AI devices can ensure the security and efficiency of operations while properly protecting sensitive data and devices.

[0042] After passing the identity verification, the intelligent AI device is operated. The device system specifically includes registration and deletion registration, entry and exit registration, damage detection, inventory management, and usage history tracking. Specifically, Regarding the registration process of new medical devices entering the warehouse, the process can be carried out in two ways. First, the administrator can register the information and prepare the data of the new product in the system background. Secondly, the operator can use the item identification unit directly on the control terminal to scan the barcode or RFID electronic tag on the medical device through a barcode scanner or RFID reader to complete the information input and note registration, and the detection device will confirm its shape and size by collecting image data of the medical device to assist in completing the registration process. At the same time, use a mobile device to collect images of medical devices according to system instructions and record any damaged features. These images and related data will be used in the back-end as part of the product training set to train the AI ​​model, thereby optimizing the system's ability to identify and assess the status of new devices. This integration process ensures that each newly registered medical device can be accurately identified by the system. As for the cancellation process of the used medical devices, the process is carried out by the administrator through system operations and cancellation operations.

[0043] Regarding the medical device in and out registration, after passing the identity recognition, the vertical direction calibration is performed by the first main camera and the second main camera of the image acquisition component according to the marking area on the transparent plate of the detection device to ensure completely unobstructed observation from the vertical direction. The camera directly below can clearly see the bottom view of the medical device placed on the transparent plate, while the camera directly above can capture the top view without obstacles, eliminating the blind spots that may be caused by improper placement of the equipment or camera angle restrictions, thereby improving the accuracy of damage detection.

[0044] When the medical device on the transparent plate is correctly placed according to the instructions, the image acquisition module is immediately activated and starts to collect detailed image data of the device. The image damage identification module is responsible for calibrating the placement of the device in the detection device. In this process, the light prompts emitted by the first optical lighting unit in the adjustment and analysis unit help determine the precise position of the device. At the same time, the light intensity and mode of the lighting component will be automatically adjusted according to the calibration results, and the control terminal will synchronously display the position prompts and adjustment instructions.

[0045] Once the device is correctly placed, the damage identification and analysis unit starts working and receives calibrated image data. Using the deep learning algorithm, the system not only identifies the type of device, but also performs detailed feature scoring on the damage and generates comprehensive data and analysis results on the degree of damage. These results include the total number of devices, the number of severely damaged devices, the number of slightly damaged devices, and the number of devices that can still be used again, which facilitates subsequent storage registration. The steps of the deep learning algorithm include the following: Step S1: Preprocessing the multi-directional image data, including denoising, color correction, and contrast enhancement, to prepare the data for more precise analysis.

[0046] When specific instructions are needed, considering that the detection device may encounter abnormalities or insufficient processing capacity, the design includes a key redundancy mechanism: the backup operation function on the mobile device side. The following is a detailed implementation of this function: Each authorized mobile device (such as a tablet or smartphone) will be installed with special management software and equipped with an image upload port. This allows operators to directly use their own devices to operate when the main detection device encounters technical failures or data processing bottlenecks. For example, when the detection device is abnormal, such as camera failure, data transmission delay or processing capacity overload, the operator can use the mobile device to capture real-time images of the medical device, where the real-time image is the front photo, back photo and various necessary tilt angle photos of the medical device uploaded by the mobile device according to the instruction prompt. The image is sent directly to the control terminal through the upload port on the device. After receiving the image, the control terminal will start the backup image processing and analysis program. After receiving the image uploaded by the mobile device, the control terminal will perform corresponding damage detection and classification. The processing results will be fed back to the operator to provide an assessment of the degree of damage of the device and subsequent processing suggestions, including whether it needs to be repaired, whether it can continue to be used or whether it should be scrapped.

[0047] Step S2: Use convolutional neural network (CNN) to segment the image and accurately separate the individual medical devices in the image from the background or other devices; the segmented image is fed into the deep learning model for further feature extraction to identify various types of damage (such as cracks, scratches, fractures, etc.). In this stage, the trained neural network is used to classify and score according to the known damage features.

[0048] Step S3: Based on the image features and the trained model output, the degree of damage of each instrument is assessed and classified as "severely damaged", "slightly damaged" or "reusable".

[0049] Step S4: Online learning mechanism, which can continuously optimize and adjust model parameters according to new data samples to adapt to new damage types or different instrument styles.

[0050] At the same time, the classified instruments are manually confirmed to see if they are damaged. When querying data, the instrument type, damage score and status classification will be automatically recorded in the system database. The system also provides a visual feedback interface, allowing operators to quickly view and handle the damage status of the instrument.

[0051] When medical equipment needs to be loaned out, the operator first registers the equipment to be loaned out, places the equipment on the detection device, and starts automatic inspection of the current status of the equipment. If damage is detected, the system will guide the operator to complete the damage registration to ensure that all information is updated completely. If the equipment is intact, the loan operation is carried out, it is marked as loaned out and the loan details are recorded, and inventory management statistics are performed at the same time.

[0052] Similarly, when the device is returned, it needs to be registered for storage. The operator places the device on the transparent plate of the detection device, and the image acquisition module is activated again to collect the image of the device, and the damage identification module is used to check whether the device has been newly damaged during use. The system updates the status information of the device based on the detection results, such as confirming whether the device can continue to be used or needs to be repaired and scrapped, and performs inventory management statistics at the same time.

[0053] Regarding the data management module, it is applied to the identity relationship of the operator to facilitate data statistics in the entire process of equipment return and loan. Specifically, this data management module not only tracks the circulation status of medical devices, but also tracks the specific borrower and return status of each device. The following is the specific implementation and operation of this process: Personnel management unit, when operators such as doctors or nurses borrow or return medical devices from the equipment library, identity verification is performed through the identification unit, and this information is recorded in the system together with the medical device status information. Every movement of the device is recorded, including the borrowing and expected return time and quantity.

[0054] The device management unit is used to record the quantity and detailed circulation of each medical device, including its usage frequency, maintenance cycle and current status. It ensures the tracking accuracy of each device and updates its status and location in a timely manner to reduce loss and misuse.

[0055] The exception handling unit automatically monitors the return status of each instrument. If the instrument is not returned after the scheduled return time, the system will automatically mark and notify the relevant doctors or nurses, and send an alarm to the management staff to promptly discover and solve the problem of overdue instruments. At the same time, in the case that the instrument is returned by someone other than the borrower, the operator can enter a special description and adjustment request through the control terminal. For example, if a doctor returns an instrument on his behalf due to an emergency, the operator can record this information and mark it in the system for review and confirmation of the administrator to ensure the accuracy and completeness of the record. Specific reports are also generated to analyze the deviations in instrument borrowing and returning behavior and propose improvement measures.

[0056] System Notification Unit: Automatically sends notifications to the mobile devices or emails of relevant doctors or nurses to remind them of the borrowing status and return requirements of the equipment. In addition, a feedback mechanism can be provided for users to report any problems or abnormalities regarding the use of the equipment.

[0057] The embodiments of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above embodiments. Even if various changes are made to the present invention, if these changes fall within the scope of the claims of the present invention and their equivalents, they still fall within the protection scope of the present invention.

Claims

1. An intelligent AI device for full-process damage identification of medical devices, characterized in that: include: A detection device, comprising an image acquisition component, a lighting component and a main control board, wherein the image acquisition component and the lighting component are respectively connected to the main control board through electronic circuits, the detection device works according to the instructions of the main control board when working, the lighting component is used to adjust the lighting intensity, and the image acquisition component is used to collect image data of the current medical device; The control terminal includes an identification module, an image acquisition module and an image damage judgment module, wherein the identification module performs verification according to the identity information of the operator entered by the identification module. After verification, the image acquisition module collects the status information of the image data received by the main control board in the detection device; the image damage judgment module analyzes and compares the image data, judges and records the current damage status of the medical device.

2. The intelligent AI device according to claim 1, characterized in that: It also includes a transparent plate, which is located at the front end of the body and is used to place the medical machine for detection; wherein a marking area is provided on the transparent plate for calibrating with the first main camera and the second main camera of the image acquisition component.

3. The intelligent AI device according to claim 1, characterized in that: The image acquisition component is fixed in the body and is used to capture image data of the medical device at different positions on the transparent plate; wherein the image acquisition component includes a plurality of adjustable cameras, each of which includes a small motor, a gear unit in a bracket, a movable slide rail and a base; the motor is embedded in the bracket and the gear unit is used to adjust the angle and rotation of the adjustable camera, and the lens of the adjustable camera is connected to the movable slide rail to adjust the focal length.

4. The intelligent AI device according to claim 2, characterized in that: Several adjustable cameras are symmetrically arranged above, below, around the edges and at specific angles of the transparent plate for collecting all-round image data; wherein the first main camera and the second main camera are respectively located above and below the transparent plate to ensure comprehensive image data capture, calibration and capture of the medical device from a vertical direction.

5. The intelligent AI device according to claim 1, characterized in that: The lighting assembly is integrated in the machine body and is configured with an adjustment function to adjust the lighting level according to actual working conditions; wherein, The lighting assembly includes a plurality of optical lighting units and a light intensity adjustment control panel. The optical lighting unit is composed of a light source, a reflector and a diffuser and is uniformly regulated by the light intensity adjustment control panel for uniform and adjustable lighting effects. The light source is installed on the inner side of the reflector to enhance the brightness of the light and direct it to a specific area; the diffuser is located between the light source and the medical device to be detected to ensure uniform distribution of the light; wherein the first optical lighting unit in the optical lighting unit is arranged directly above the transparent plate and is equipped with a light source that can change color and flashing speed to indicate whether the multiple medical devices are correctly placed on the transparent plate.

6. The intelligent AI device according to claim 1, characterized in that: The identification module includes an identity recognition unit and an object recognition unit, wherein the identity recognition unit includes a face recognition camera, a fingerprint scanner and a card reader for verifying the identity of the operator; the object recognition unit includes a barcode scanner and an RFID reader for identifying and registering the label information of the medical device.

7. The intelligent AI device according to claim 1, characterized in that: The detection device and the control terminal are connected by wired / wireless communication, and the detection device and the control terminal are provided with Ethernet interface, USB interface, wireless communication and Bluetooth technology; the control terminal sends the instructions to the main control board of the detection device, which are used to debug the detection device and collect the image data; the control terminal analyzes the image data, identifies and manages the damage of the medical device; The detection device and the control terminal also include an image storage unit, wherein the image storage unit of the detection device is used to store the image data of the detection device; the image storage unit of the control terminal is used to store the image data of the detection device and the mobile device terminal.

8. The intelligent AI device according to claim 1, characterized in that: The detection device and the control terminal are directly connected to a main power supply for AC power supply, and an integrated backup power supply, ie, a battery, is used to prevent the main power supply from being interrupted.

9. The intelligent AI device according to claim 6, characterized in that: The control terminal also includes a data feedback module and a data management module; the data feedback module performs damage registration and feedback operations according to the analysis results of the image damage judgment module; the data management module integrates the identity registration information and the label information in the identification module and the analysis results of the image damage judgment module to perform unified management of the medical device data.

10. An intelligent AI system for full-process damage identification of medical devices, applied to any one of the intelligent AI devices described in claims 1 to 9, characterized in that: include: Identification module, used to verify the identity of the operator and recognize the label information of the registered medical device; An image acquisition module, used for receiving multi-directional image data of the current medical device acquired by the detection device or the mobile device according to the instruction, and performing data preprocessing on the multi-directional image data according to a preset standard; The image damage discrimination module includes an adjustment analysis unit and a damage discrimination analysis unit, wherein: The adjustment analysis unit is used to calibrate the placement of one or more medical devices in the detection device; determine the position adjustment through the light prompt emitted by the first optical lighting unit, and at the same time, the light intensity and mode of the lighting component in the detection device are self-adjusted according to the calibration result and the control terminal synchronously displays the position prompt and adjustment instruction of the medical device; The damage discrimination and analysis unit is used to receive the calibrated image data, identify the type of the medical device through a deep learning algorithm, perform feature scoring on the damage on the medical device, and generate damage degree data and analysis results; A data feedback module, used for performing damage registration and feedback operations according to the analysis results of the damage discrimination and analysis unit; The data management module is used to receive the identity registration information input from the identification module, perform the current entry and exit registration of the medical device, and also includes the full process query and update of the current inventory status of the medical device.

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