CN113823396A

CN113823396A - Medical equipment management method and device, computer equipment and storage medium

Info

Publication number: CN113823396A
Application number: CN202111088020.5A
Authority: CN
Inventors: 谢国栋
Original assignee: Wuhan United Imaging Healthcare Co Ltd
Current assignee: Wuhan United Imaging Healthcare Co Ltd
Priority date: 2021-09-16
Filing date: 2021-09-16
Publication date: 2021-12-21

Abstract

The application relates to a medical equipment management method, a medical equipment management device, computer equipment and a storage medium. The method comprises the following steps: the method comprises the steps that the computer equipment obtains operation parameters of all medical equipment in a monitoring range, the operation parameters of all the medical equipment are input into a preset virtual model, fault information of the fault medical equipment is determined according to the operation parameters of all the medical equipment, the operation parameters and the fault information of the fault medical equipment are input into a preset fault decision model, and a fault solution of the fault medical equipment is obtained. In the method, the computer equipment displays the real-time operation condition of the medical equipment based on the virtual model, determines the fault medical equipment according to the operation parameters, and outputs the corresponding fault solution in the virtual model based on the fault decision model, so that the quick positioning and the preliminary maintenance of the fault medical equipment are realized, and the management efficiency of the medical equipment is improved.

Description

Medical equipment management method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of medical technology, and in particular, to a medical device management method, apparatus, computer device, and storage medium.

Background

With the rapid development of medical technology, the medical technology field relates to various medical devices. How to monitor and manage all medical devices in a designated area in a centralized manner is important for providing higher-quality services for subsequent upgrading and optimization of the medical devices. In the medical field, the above problems are currently solved by a digital twin technology, and a device management system is generally constructed based on the digital twin technology to realize remote monitoring of medical devices.

However, the existing equipment management system has low management precision, and when equipment fails, the equipment management system can only call operation and maintenance personnel remotely to realize fault maintenance of the equipment, so that the equipment management efficiency is low.

Disclosure of Invention

In view of the above, it is necessary to provide a medical device management method, an apparatus, a computer device, and a storage medium that can improve medical device management efficiency.

In a first aspect, a medical device management method is provided, the method comprising:

acquiring the operating parameters of each medical device in the monitoring range, and inputting the operating parameters of each medical device into a preset virtual model;

determining fault information of the faulty medical equipment according to the operating parameters of the medical equipment;

and inputting the operating parameters and the fault information of the faulty medical equipment into a preset fault decision model to obtain at least one fault solution of the faulty medical equipment.

In one optional embodiment, the method for training the preset fault decision model includes:

acquiring a sample data set of a plurality of faulty medical devices; the sample data set comprises sample operation parameters of the faulty medical equipment, sample fault information and a sample fault solution;

and training an initial fault decision model according to the sample data sets of the plurality of faulty medical devices to obtain a preset fault decision model.

In one optional embodiment, the method further comprises:

according to a preset data processing rule, performing data processing on the sample data set to obtain the sample data set after the data processing;

training an initial fault decision model according to a sample data set of a plurality of faulty medical devices to obtain a preset fault decision model, wherein the method comprises the following steps:

training an initial fault decision model according to the sample data set after data processing to obtain a preset fault decision model.

In one optional embodiment, the data processing includes a standardization process, and performs data processing on the sample data set according to a preset data processing rule to obtain the sample data set after the data processing, and the data processing includes:

and discretizing the sample data set according to a preset data format and a preset character length to obtain the sample data set after the standardization processing.

In one optional embodiment, the data processing includes data denoising processing and similarity processing, and performs data processing on the sample data set according to a preset data processing rule to obtain a sample data set after data processing, including:

denoising the sample data set according to a preset denoising algorithm to obtain denoised first data;

and according to a preset similarity algorithm, carrying out similarity calculation processing on the first data to obtain a sample data set after data processing.

In one optional embodiment, the method further comprises:

acquiring a preset optimal fault solution of the faulty medical equipment;

updating a preset fault decision model according to the optimal fault solution of the faulty medical equipment; and the optimal fault solution of the fault medical equipment is used as the optimal reference value of the preset fault decision model.

In one optional embodiment, the method further comprises:

updating the operation condition of the faulty medical equipment according to the fault information of the faulty medical equipment and at least one fault solution;

displaying the updated operation condition of each medical device in a display interface of the virtual model;

and acquiring an operation instruction triggered by a display interface based on the virtual model, and executing corresponding operation according to the equipment identification in the operation instruction.

In one optional embodiment, obtaining an operation instruction triggered by a display interface based on a virtual model, and executing a corresponding operation according to a device identifier in the operation instruction includes:

determining a target medical device and/or a target assembly corresponding to the device identifier in the operation instruction;

if the target medical equipment and/or the medical equipment where the target component is located is faulty medical equipment, outputting fault information and at least one fault solution of the faulty medical equipment;

and if the target medical equipment and/or the medical equipment where the target component is located is normal medical equipment, outputting equipment information of the normal medical equipment.

In one optional embodiment, the virtual model is a model of all medical devices in a monitoring range constructed based on a digital twin technology.

In a second aspect, there is provided a medical device management apparatus, the apparatus comprising:

the acquisition module is used for acquiring the operating parameters of each medical device in the monitoring range and inputting the operating parameters of each medical device into a preset virtual model;

the first determining module is used for determining fault information of the faulty medical equipment according to the operating parameters of the medical equipment;

and the second determination module is used for inputting the operating parameters and the fault information of the faulty medical equipment into a preset fault decision model to obtain at least one fault solution of the faulty medical equipment.

In a third aspect, there is provided a computer device comprising a memory storing a computer program and a processor implementing the method of any of the first aspects when the processor executes the computer program.

In a fourth aspect, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of any of the first aspects described above.

According to the medical equipment management method, the medical equipment management device, the computer equipment and the storage medium, the computer equipment obtains the operation parameters of each piece of medical equipment in the monitoring range, inputs the operation parameters of each piece of medical equipment into the preset virtual model, determines the fault information of the faulty medical equipment according to the operation parameters of each piece of medical equipment, and inputs the operation parameters and the fault information of the faulty medical equipment into the preset fault decision model to obtain at least one fault solution of the faulty medical equipment. In the method, the computer equipment can acquire the operating parameters of the medical equipment within the monitoring range and input the operating parameters into the virtual model corresponding to the medical equipment, the virtual model can intuitively display the real-time operating condition of the medical equipment, after the fault medical equipment is determined based on the operating parameters, the equipment information of the fault medical equipment in the virtual model can be updated, the purposes of fault early warning and fault reminding are achieved, further, the fault solution of the fault medical equipment is obtained based on the preset fault decision model, the fault solution of the fault medical equipment can also be displayed in the virtual model, the purpose of outputting the fault solution in time is achieved, the nearby working personnel can quickly position and maintain the fault medical equipment based on the fault solution, and the trouble of debugging and maintenance of the operation and maintenance personnel is avoided, the efficiency of daily management, fault handling of medical equipment has been improved.

Drawings

FIG. 1 is a diagram of an exemplary medical device management system;

FIG. 2 is a schematic flow chart diagram illustrating a method for medical device management in one embodiment;

FIG. 3 is a flow diagram illustrating a method for medical device management in one embodiment;

FIG. 4 is a flow diagram illustrating a method for medical device management in one embodiment;

FIG. 5 is a flow diagram illustrating a method for medical device management in one embodiment;

FIG. 6 is a flow diagram illustrating a method for medical device management in one embodiment;

FIG. 7 is a flow diagram illustrating a method for medical device management in one embodiment;

FIG. 8 is a schematic diagram of an interface of a medical device management system in one embodiment;

FIG. 9 is a schematic diagram of an interface of a medical device management system in one embodiment;

FIG. 10 is a block diagram showing the construction of a medical device management apparatus according to an embodiment;

FIG. 11 is a block diagram showing the construction of a medical device management apparatus according to an embodiment;

FIG. 12 is a block diagram showing the construction of a medical device management apparatus according to an embodiment;

fig. 13 is a block diagram showing the construction of a medical device management apparatus according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The medical device management method provided by the application can be applied to the application environment shown in fig. 1. In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 1. The computer device comprises a processor, a memory, a communication interface, a display screen and an input device which are connected through a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a medical device management method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.

Those skilled in the art will appreciate that the architecture shown in FIG. 1 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices in which the disclosed aspects may be implemented, as a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

The following describes in detail how to solve the above technical problems by using embodiments and with reference to the accompanying drawings. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. It should be noted that, the execution subject of the medical device management method provided in the embodiments of fig. 2 to fig. 9 of the present application is a computer device, and may also be a medical device management apparatus, and the medical device management apparatus may be a part or all of the computer device by software, hardware, or a combination of software and hardware. In the following method embodiments, the execution subject is a computer device as an example.

In one embodiment, as shown in fig. 2, there is provided a medical device management method comprising the steps of:

s201, obtaining the operation parameters of each medical device in the monitoring range, and inputting the operation parameters of each medical device into a preset virtual model.

The virtual model can be models of all medical devices in a monitoring range constructed based on a digital twin technology, and can also be a virtual model of each medical device constructed based on an internet of things technology. In the process of constructing the virtual model, the computer device may be constructed according to basic information and operating parameters of each medical device, the basic information may be attribute parameters, position parameters and the like of the medical device, the attribute parameters include a device name, a device number, device structure information, device component information and the like, and the position parameters include a coordinate position where the device is located and the like. The operating parameters of the medical equipment comprise the temperature, water cooling, pressure and the like of the medical equipment, and the operating parameters corresponding to different medical equipment are different.

In this embodiment, the computer device obtains the basic information and the operating parameters of each medical device within the monitoring range, performs three-dimensional modeling, restores details such as the shape, material, texture, and the like of each medical device and complex internal structures, and realizes high-precision and ultra-fine visual rendering to obtain a digital twin virtual model of the medical device. Optionally, to take a hospital as a dimension, the monitoring range may be all medical devices for the whole hospital; the manufacturer is used as a dimension, and the monitoring range can be all medical equipment produced by a certain manufacturer. This embodiment is not limited to this.

S202, determining fault information of the faulty medical equipment according to the operating parameters of the medical equipment.

The fault information includes a fault location or a fault component of the faulty medical device, a fault cause, occurrence time of the fault, and abnormal operation data.

In this embodiment, during the process of acquiring the operating parameters of each medical device in real time, the computer device may perform data analysis on the acquired operating parameters, and determine that the medical device with abnormal data is a faulty medical device, for example, if the value of the operating parameter acquired by the computer device is far from the mean value of the operating parameter, it is determined that the operating parameter of the medical device is abnormal, a part or component of the medical device corresponding to the operating parameter is acquired, the time when a fault occurs is recorded, and fault information of the medical device is output. Or, the computer device may further input the operating parameters of the medical device into a preset fault diagnosis model, determine a faulty medical device with abnormal data, and obtain an output result of the fault diagnosis model, where the output result includes information such as the faulty medical device, a faulty part or a faulty component corresponding to the faulty medical device, a fault cause, a fault occurrence time, and abnormal operating data, and this embodiment is not limited thereto.

S203, inputting the operation parameters and the fault information of the fault medical equipment into a preset fault decision model to obtain at least one fault solution of the fault medical equipment.

The preset fault decision model refers to a model of a fault solution corresponding to fault information of the medical equipment for outputting faults, which is obtained through training.

In this embodiment, after determining the faulty medical device, the computer device inputs the operating parameters and the fault information of the faulty medical device into a preset fault decision model to obtain an output result of the fault decision model, where the output result may be one fault solution or multiple fault solutions. Optionally, after obtaining the failure solution corresponding to the failed medical device, the computer device may input the failure solution into the digital twin virtual model to show the failure solution to the operator, where the showing manner includes multiple manners, for example, the failure solution may be displayed by skipping a presentation box in a main display interface, or the failure solution may be given in the form of tooltip in a corresponding failure part or a failure component of the failed medical device, which is not limited in this embodiment.

In the medical equipment management method, the computer equipment acquires the operating parameters of each medical equipment in the monitoring range, inputs the operating parameters of each medical equipment into a preset virtual model, determines the fault information of the faulty medical equipment according to the operating parameters of each medical equipment, and inputs the operating parameters and the fault information of the faulty medical equipment into a preset fault decision model to obtain at least one fault solution of the faulty medical equipment. In the method, the computer equipment can acquire the operating parameters of the medical equipment within the monitoring range and input the operating parameters into the virtual model corresponding to the medical equipment, the virtual model can intuitively display the real-time operating condition of the medical equipment, after the fault medical equipment is determined based on the operating parameters, the equipment information of the fault medical equipment in the virtual model can be updated, the purposes of fault early warning and fault reminding are achieved, further, the fault solution of the fault medical equipment is obtained based on the preset fault decision model, the fault solution of the fault medical equipment can also be displayed in the virtual model, the purpose of timely outputting the fault solution is achieved, the nearby working personnel can quickly position and maintain the fault medical equipment based on the fault solution, and the trouble of debugging and maintenance of the operation and maintenance personnel is avoided, the efficiency of daily management, fault handling of medical equipment has been improved.

The computer device may determine a fault solution based on a preset fault decision model, and in an alternative embodiment, as shown in fig. 3, the training method of the preset fault decision model includes:

s301, acquiring a sample data set of a plurality of fault medical devices; the sample data set includes sample operating parameters of the malfunctioning medical device, sample failure information, and a sample failure solution.

In this embodiment, the computer device may acquire, as a sample data set, the operating parameters, the fault information, and the fault solutions of the faulty medical devices that have failed within a certain monitoring range in a certain historical period of time, for example, the operating parameters, the fault information, and the fault solutions of all the faulty medical devices in a certain hospital in the past year are acquired, or, in order to expand the data dimensions of the sample data set, the operating parameters, the fault information, and the fault solutions of all the faulty medical devices in a plurality of hospitals in a certain area in the past year are acquired; alternatively, the operating parameters, the fault information, and the fault solution of all faulty medical devices of a manufacturer of a certain medical device in the past year may also be obtained, which is not limited in this embodiment.

S302, training an initial fault decision model according to the sample data sets of the plurality of fault medical devices to obtain a preset fault decision model.

In this embodiment, after obtaining the sample data set, the computer device takes the operating parameters and the fault information of the faulty medical device in the sample data set as inputs, takes the fault solution in the sample data set as a reference output, and trains the initial fault decision model, thereby obtaining the fault decision model.

In this embodiment, the computer device trains the initial fault decision model according to the sample data set to obtain the fault decision model, so that in the real-time monitoring process of the medical device, a fault solution corresponding to the faulty medical device can be output based on the fault decision model under the condition that the faulty medical device is determined to be generated, rapid response of the fault is realized, and the fault processing efficiency of the medical device is improved.

In order to further improve the accuracy of the model training, in an alternative embodiment, as shown in fig. 4, the method further includes:

s401, according to a preset data processing rule, performing data processing on the sample data set to obtain the sample data set after the data processing.

The preset data processing rules comprise data format standardization processing, data normalization processing, data noise reduction processing and the like, and the computer equipment performs data processing on the sample data set according to the preset data processing rules to obtain the sample data set with good quality after data processing, so that the accuracy of model training is further improved.

Optionally, in one of the scenarios, the data processing includes a normalization process, including: and discretizing the sample data set according to a preset data format and a preset character length to obtain the sample data set after standardization processing.

In this embodiment, the computer device may perform format standardization processing on all information in the sample data set according to a preset data format and a character length, for example, the computer device defines a data standard format as 10-bit discrete data, that is, a character string with a length of 10, where the character string is composed of discretization data corresponding to a type, a location, and a fault type of a faulty medical device, for example, the faulty medical device is CT, and the discretization data corresponding to the faulty medical device is 001, the location in the CT is a detector, the discretization data corresponding to the detector is 0001, the fault type corresponding to the location is a high inlet temperature, and the discretization data corresponding to the high inlet temperature is 000, so the character string corresponding to the high inlet temperature of the faulty medical device detector is 0010001000; if the fault type corresponding to the part is that the right side temperature is higher, and the discretization data corresponding to the higher right side temperature is 001, the character string corresponding to the higher right side temperature of the fault medical equipment detector is 0010001001; if the fault type corresponding to the part is that the middle temperature is higher, and the discretization data corresponding to the higher middle temperature is 002, the character string corresponding to the higher middle temperature of the fault medical equipment detector is 0010001002; if the fault type corresponding to the part is that the left side temperature is higher, and the discretization data corresponding to the left side temperature is 003, the character string corresponding to the left side temperature of the faulty medical equipment detector is 0010001003. For the fault solutions in the sample data set, the fault solutions may be classified according to their types, for example, fault solution 1 belongs to a first type, and the discretization data corresponding to the first type is 0; the

failure solutions

2 and 3 belong to a second type, and the discretization data corresponding to the second type is 1, which is not limited in this embodiment. Thus, discrete data of data standardization processing is obtained, and a sample data set after the standardization processing is obtained.

Optionally, in another scenario, the data processing includes data denoising processing and similarity processing, as shown in fig. 5, including:

s501, denoising the sample data set according to a preset denoising algorithm to obtain denoised first data.

In this embodiment, the computer device divides data with the same fault solution into a group according to the fault solutions in the sample data set, that is, obtains data subsets corresponding to different fault solutions, performs superposition averaging for the data in each data subset, removes white noise interference summarized by each data subset according to a preset denoising algorithm, and obtains mean data Average of each data subset, which is the first data.

And S502, according to a preset similarity calculation method, performing similarity calculation processing on the first data to obtain a sample data set after data processing.

In this embodiment, the computer device performs Dot product processing on the data in each data subset according to the data subsets obtained by the division in the above steps, obtains similarity dots of different fault types under the same fault solution, and obtains a characteristic matrix, that is, a sample data set after the data processing, according to the similarity dots and the mean data Average.

S402, training an initial fault decision model according to the sample data set after data processing to obtain a preset fault decision model.

In this embodiment, the computer device takes the obtained characteristic matrix as a model input, takes a fault solution of the faulty medical device in the sample data set after data processing as a model reference output, and trains an initial fault decision model, thereby obtaining a fault decision model.

In this embodiment, the computer device trains the initial fault decision model according to the sample data set after data processing to obtain the fault decision model, and the sample data set after data processing improves the precision of data, thereby improving the accuracy of model training.

To further improve the accuracy of the fault solution, the computer device may perform adjustment updating on the preset fault decision model based on the optimal fault solution, as shown in fig. 6, and in one optional embodiment, the method further includes:

s601, acquiring a preset optimal fault solution of the faulty medical equipment.

Wherein, the preset optimal fault solution can be an optimal fault solution which is input by a user and acquired by the computer equipment, or an optimal fault solution which is determined by the running state of the fault medical equipment after the fault solution is implemented by the computer equipment and corresponds to a certain fault type, the computer device solves the malfunctioning medical device of the malfunction type a according to the malfunction solution 1, for example, after the resolution, the operating state thereof is good, but the duration is 1 month, i.e., a failure occurs after one month of normal operation, the failed medical device of failure type a is solved according to failure solution 2, and after the solution, the operating conditions were good, but the duration was 1 year or more, in which case, namely, the optimal fault solution of the fault type a obtained by data analysis is considered as a scheme 1. Or, directly obtaining the optimal fault solution 3 of the fault type a recommended in the expert recommendation system, which is not limited in this embodiment.

S602, updating a preset fault decision model according to the optimal fault solution of the faulty medical equipment; and the optimal fault solution of the fault medical equipment is used as the optimal reference value of the preset fault decision model.

In this embodiment, the optimal fault solution corresponding to the faulty medical device is used as the feedback data of the fault decision model to strengthen the training of the fault decision model, so as to obtain the updated fault decision model.

In the embodiment, the training fault decision model is updated according to the optimal fault solution serving as a reference value, the fault decision model is adjusted and perfected, and the fault decision model is updated in real time, so that the self-adjustment of the fault decision model is realized, and the robustness of the fault decision model is enhanced.

After determining the failure solution for the failed medical device, the computer device may also display the failure solution in a virtual model, in one of the alternative embodiments, as shown in fig. 7, the method further comprising:

s701, updating the running condition of the faulty medical equipment according to the fault information of the faulty medical equipment and at least one fault solution.

In this embodiment, after obtaining at least one failure solution of the failed medical device, the computer device inputs the at least one failure solution and the failure information of the failed medical device into the digital twin virtual model to update the real-time operation condition of the corresponding medical device in the digital twin virtual model.

And S702, displaying the updated running conditions of the medical equipment in a display interface of the virtual model.

In this embodiment, the computer device inputs the fault information of the faulty medical device and the corresponding fault solution into the virtual model, and the virtual model updates the display interface according to the information, and displays each medical device in the virtual model on the display interface, including the real-time operating condition of the faulty medical device, for example, the computer device may mark the faulty medical device with a color different from that of the normal medical device based on the virtual model to indicate that the faulty medical device has a fault, or add a prompt tag and a prompt control to the faulty medical device or the faulty medical component based on the virtual model to indicate that the faulty medical device or the faulty medical component has a fault, which is not limited in this embodiment.

And S703, acquiring an operation instruction triggered by the display interface based on the virtual model, and executing corresponding operation according to the equipment identifier in the operation instruction.

The operation instruction may be a click instruction, a slide instruction, a touch instruction, a selection instruction, and the like triggered by a user based on a display interface of the virtual model, and after the computer device obtains the triggered operation instruction, different operations are executed according to an operation type after the operation and a device identifier corresponding to the operation type. For example, when the operation type is single click, acquiring device information corresponding to a device identifier in a click instruction, and displaying the information in a prompt box or tooltip form, wherein the device information includes basic information, operation parameters, fault information and the like of the device; if the operation type is a double-click operation, acquiring a device identifier in a double-click instruction or a click position of the double-click operation in the virtual model, and enlarging or reducing a device or a device component corresponding to the click position, which is not limited in this embodiment.

Optionally, in one optional embodiment, obtaining an operation instruction triggered by a display interface based on a virtual model, and executing a corresponding operation according to a device identifier in the operation instruction includes:

In this embodiment, the computer device determines, according to the operation instruction, a target medical device and/or a target component corresponding to a device identifier in the operation instruction, optionally, the computer device may further determine whether the target medical device or the target component is a faulty medical device or a faulty component, where the medical device where the target medical device and/or the target component is located is a faulty medical device, and in this case, the computer device outputs basic information, operating parameters, fault information, and a fault solution of the faulty medical device through a prompt box or other forms; if the target medical equipment and/or the medical equipment where the target component is located is normal medical equipment, in this case, the computer device outputs basic information, operation parameters, and the like of the normal medical equipment through a prompt box or other forms, which is not limited in this embodiment.

In this embodiment, the computer device may implement interaction with the user based on the display interface of the virtual model, so as to implement display of the omnidirectional operation conditions of each medical device in the virtual model, for example, the operation parameters, the basic information, the fault solution, and the like, and enable the user to more intuitively obtain the real-time operation conditions of the medical device.

In order to better explain the above method, the present embodiment provides a medical device management system, which includes a data acquisition module, a digital twin module, a fault handling decision module, an interaction module, and a cloud storage module.

The interaction module is used for providing a display interface based on the digital twin virtual model, acquiring an operation instruction triggered by a user based on the display interface, performing corresponding operation on the medical equipment in the digital twin virtual model according to the operation instruction, and feeding back corresponding instruction response operation based on the display interface of the virtual model. The display interface of the digital twin virtual model comprises an equipment monitoring area, a data billboard area, an alarm information area and the like. A medical device, such as uMR790, is selected and entered into a three-dimensional twin real-time visual monitoring interface of the device, as shown in fig. 8, and an alarm prompt is given once the data is abnormal or an abnormality is early warned. For example, if the water cooling is abnormal, the water cooling statistical chart can be prompted by an alarm. The computer equipment can respond to the dragging operation triggered by the user based on the display interface, locate the abnormal point of the dragged equipment according to the dragging operation, respond to the rolling operation triggered by the user based on the display interface and realize the function of local magnification and shrinkage of the equipment. One column below the device: in the "current state", if there is an abnormality, an abnormal part is also displayed. The computer device can also respond to the focusing position of a cursor of a user on the display interface, determine the target device according to the focusing position, and provide a fault solution of the target device in the form of a prompt bar tooltip.

The data acquisition module is configured to acquire operating parameters of the medical device in real time, the computer device may construct a digital twin virtual model corresponding to the medical device based on the operating parameters, and the display interface of the digital twin virtual model displays the operating conditions of each operating parameter of each medical device, which may be as shown in fig. 8. Optionally, the data acquisition module can also send the acquired operating parameters of the medical equipment to the cloud storage module, and the cloud storage module is used for encrypting the received operating parameters and storing the encrypted data to the cloud end so as to reduce the pressure of local storage.

The digital twin module is configured to perform modeling of a digital twin virtual model by obtaining basic information and operation parameters of the medical devices, and update operation conditions of each medical device in the digital twin virtual model according to the operation parameters acquired and transmitted by the data acquisition module in real time, where the digital twin virtual model may include a total number of the medical devices, available devices, warranty devices, brand distribution, work order statistics, maintenance records, and the like in a current monitoring range, as shown in fig. 9. Optionally, after the computer device obtains the failure solution, the failure solution is transmitted to the digital twin module, and the digital twin module updates the failure solution to the digital twin virtual model. And fault early warning, recommendation of fault solutions and remote management of medical equipment are realized.

And the fault processing decision module is used for determining whether the fault medical equipment exists according to the acquired operating parameters and the acquired basic information of the medical equipment, and determining at least one fault solution corresponding to the fault medical equipment according to the fault information of the fault medical equipment. The fault solution is transmitted to a digital twin module, which updates the fault solution to a digital twin virtual model.

In addition, the medical equipment management system endows different levels of management authorities according to different user identities, and the functional modules of the medical equipment management system are different under different management authorities. For example, when the user identity is a hospital organization, the visual page of the medical equipment management system can display equipment position information, equipment asset use information, movement track tracking, equipment utilization rate and idleness rate analysis, equipment inspection amount and the like, so that fixed asset management of the hospital can be enhanced, the asset management level of the hospital is improved, the existing fixed assets are effectively controlled, the asset utilization rate is improved, the operating cost of the hospital is reduced, the operating efficiency of the hospital is improved, and the optimal configuration of resources is promoted. For example, if the user identity is manufacturer, the visualized page of the medical device management system may show the distribution, failure, etc. sold by each device.

In this embodiment, the computer device can obtain the operation parameters of the medical device within the monitoring range, and input the operation parameters into the virtual model corresponding to the medical device, the virtual model can visually display the real-time operation condition of the medical device, and after the faulty medical device is determined based on the operation parameters, the device information of the faulty medical device in the virtual model can be updated, so as to achieve the purposes of fault early warning and fault reminding, further, the fault solution of the faulty medical device is obtained based on the preset fault decision model, and the fault solution of the faulty medical device can also be displayed in the virtual model, so as to achieve the purpose of outputting the fault solution in time, so that the nearby staff can quickly position and maintain the faulty medical device based on the fault solution, and avoid the trouble of debugging and maintenance of the operation and maintenance staff, the efficiency of daily management, fault handling of medical equipment has been improved.

The implementation principle and technical effect of the medical device management method provided by the above embodiment are similar to those of the above method embodiment, and are not described herein again.

It should be understood that although the various steps in the flow charts of fig. 2-9 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-9 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps or stages.

In one embodiment, as shown in fig. 10, there is provided a medical device management apparatus including: an obtaining module 01, a first determining module 02 and a second determining module 03, wherein:

the acquisition module 01 is used for acquiring the operating parameters of each medical device in the monitoring range and inputting the operating parameters of each medical device into a preset virtual model;

the first determining module 02 is used for determining fault information of the faulty medical equipment according to the operating parameters of the medical equipment;

the second determining module 03 is configured to input the operating parameters and the fault information of the faulty medical device into a preset fault decision model, so as to obtain at least one fault solution of the faulty medical device.

In an alternative embodiment, as shown in fig. 11, the medical device management apparatus further includes a training module 04;

the training module 04 is used for acquiring a sample data set of a plurality of faulty medical devices; the sample data set comprises sample operation parameters of the faulty medical equipment, sample fault information and a sample fault solution; and training an initial fault decision model according to the sample data sets of the plurality of faulty medical devices to obtain a preset fault decision model.

In an alternative embodiment, as shown in fig. 12, the medical device management apparatus further includes a data processing module 05;

the data processing module 05 is configured to perform data processing on the sample data set according to a preset data processing rule to obtain the sample data set after the data processing;

the training module 04 is further configured to train the initial fault decision model according to the sample data set after the data processing, so as to obtain a preset fault decision model.

In one optional embodiment, the data processing includes a normalization process, and the data processing module 05 is configured to discretize the sample data set according to a preset data format and a preset character length to obtain the sample data set after the normalization process.

In one optional embodiment, the data processing includes data denoising and similarity processing, and the data processing module 05 is configured to perform denoising processing on the sample data set according to a preset denoising algorithm to obtain denoised first data; and according to a preset similarity algorithm, carrying out similarity calculation processing on the first data to obtain a sample data set after data processing.

In one optional embodiment, the training module 04 is further configured to obtain a preset optimal fault solution of the faulty medical device; updating a preset fault decision model according to the optimal fault solution of the faulty medical equipment; and the optimal fault solution of the fault medical equipment is used as the optimal reference value of the preset fault decision model.

In an alternative embodiment, as shown in fig. 13, the medical device management apparatus further includes an interaction module 06;

the interaction module 06 is used for updating the operation condition of the faulty medical equipment according to the fault information of the faulty medical equipment and at least one fault solution; displaying the updated operation condition of each medical device in a display interface of the virtual model; and acquiring an operation instruction triggered by a display interface based on the virtual model, and executing corresponding operation according to the equipment identifier in the operation instruction.

In one optional embodiment, the interaction module 06 is configured to determine that the device identifier in the operation instruction corresponds to the target medical device and/or the target component; if the target medical equipment and/or the medical equipment where the target component is located is faulty medical equipment, outputting fault information and at least one fault solution of the faulty medical equipment; and if the target medical equipment and/or the medical equipment where the target component is located is normal medical equipment, outputting equipment information of the normal medical equipment.

For specific limitations of the medical device management apparatus, reference may be made to the above limitations of the medical device management method, which are not described herein again. The modules in the medical device management apparatus may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:

The implementation principle and technical effect of the computer device provided by the above embodiment are similar to those of the above method embodiment, and are not described herein again.

In one embodiment, a computer-readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, performs the steps of:

The implementation principle and technical effect of the computer-readable storage medium provided by the above embodiments are similar to those of the above method embodiments, and are not described herein again.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent application shall be subject to the appended claims.

Claims

1. A medical device management method, the method comprising:

acquiring the operating parameters of each medical device in a monitoring range, and inputting the operating parameters of each medical device into a preset virtual model;

and inputting the operation parameters and the fault information of the faulty medical equipment into a preset fault decision model to obtain at least one fault solution of the faulty medical equipment.

2. The method of claim 1, wherein the method for training the predetermined fault decision model comprises:

acquiring a sample data set of a plurality of faulty medical devices; the sample data set comprises sample operating parameters, sample fault information and a sample fault solution of the faulty medical device;

and training an initial fault decision model according to the sample data sets of the plurality of faulty medical devices to obtain the preset fault decision model.

3. The method of claim 2, further comprising:

training an initial fault decision model according to the sample data set of the plurality of faulty medical devices to obtain the preset fault decision model, including:

training an initial fault decision model according to the sample data set after the data processing to obtain the preset fault decision model.

4. The method according to claim 3, wherein the data processing includes a normalization process, and the data processing the sample data set according to a preset data processing rule to obtain the sample data set after the data processing includes:

5. The method according to claim 3, wherein the data processing includes data denoising processing and similarity processing, and the data processing the sample data set according to a preset data processing rule to obtain the sample data set after data processing includes:

and according to a preset similarity algorithm, carrying out similarity calculation processing on the first data to obtain a sample data set after the data processing.

6. The method of claim 1, further comprising:

acquiring a preset optimal fault solution of the faulty medical equipment;

updating the preset fault decision model according to the optimal fault solution of the faulty medical equipment; and the optimal fault solution of the faulty medical equipment is used as the optimal reference value of the preset fault decision model.

7. The method of claim 1, further comprising:

updating the operating conditions of the faulty medical device according to the fault information of the faulty medical device and the at least one fault solution;

and acquiring an operation instruction triggered by a display interface based on the virtual model, and executing corresponding operation according to the equipment identifier in the operation instruction.

8. The method according to claim 7, wherein the obtaining of the operation instruction triggered by the display interface based on the virtual model, and executing corresponding operation according to a device identifier in the operation instruction comprises:

determining a target medical device and/or a target component corresponding to the device identifier in the operation instruction;

if the target medical equipment and/or the medical equipment where the target component is located is faulty medical equipment, outputting fault information of the faulty medical equipment and the at least one fault solution;

9. The method according to any one of claims 1-8, wherein the virtual model is a model of all medical devices within the monitoring range constructed based on digital twinning techniques.

10. A medical device management apparatus, characterized in that the apparatus comprises:

11. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 1 to 9 when executing the computer program.