A method and system for real-time collection and monitoring of health of medical equipment

Abstract

The present application discloses a method and system for real-time health collection and monitoring of medical equipment, the method comprising: a network-side device obtains information that the medical equipment is connected to the network-side device through an interface of the network-side device; the network-side device obtains model information of the medical equipment; the network-side device searches for a corresponding API data interface according to the model information, wherein the API data interface is used to interact with the medical equipment for data; the network-side device converts the data received from the API interface into a predetermined format; the network-side device processes the data in the predetermined format. This application solves the problems caused by the inconsistency of interfaces and protocols of medical equipment manufacturers in the prior art, thereby improving the transformation of health monitoring of medical equipment into active monitoring, and further providing technical guarantees for the normal operation of medical equipment.

Description

Technical Field

[0001] The present application relates to the field of medical data processing, and more specifically, to a method and system for real-time data collection and monitoring of the health of medical equipment. Background Art

[0002] With the development of science and technology, modern medicine has entered a new field. The introduction of large medical equipment has made modern medicine enter a new stage. Advanced medical equipment is an important symbol of the modernization of a hospital and a basic condition for the continuous improvement of medical technology. Therefore, the maintenance of medical equipment is extremely important. Only the normal operation of medical equipment can ensure the smooth progress of clinical treatment and rescue work. Faced with such a huge medical equipment maintenance work, there are many types of equipment manufacturers, complex management, and high difficulty in fault diagnosis. The maintenance methods of traditional post-maintenance and planned maintenance by operation and maintenance personnel have fallen behind. Traditional operation and maintenance personnel deal with many repetitive work processes every day, with heavy workload, low work efficiency, and high cost. In addition, the traditional manual inspection table cannot monitor the operation status of medical equipment in real time and intuitively. Manual operation inspection may lead to irregular operation, affect the normal use of equipment, and increase workload and risk. With the rapid development of the intelligentization and automation of hospital medical equipment, higher requirements are put forward for its maintenance and guarantee capabilities.

[0003] Traditional equipment maintenance methods are insufficient:

[0004] There are many types of medical equipment manufacturers, and the interfaces and protocols of each manufacturer's equipment are not unified. The equipment is used in a scattered manner. The traditional manual inspection cycle is long, which requires high technical capabilities of operation and maintenance personnel and has high labor costs. In addition, manual inspections cannot monitor the health status of medical equipment in real time and intuitively. In addition, the inspection work efficiency is low and the workload is repetitive. Summary of the invention

[0005] The embodiments of the present application provide a method and system for real-time health collection and monitoring of medical equipment, so as to at least solve the problems caused by the inconsistency of interfaces and protocols of medical equipment manufacturers in the prior art.

[0006] According to one aspect of the present application, a method for real-time health collection and monitoring of medical devices is provided, including: a network-side device obtains information that a medical device is connected to the network-side device through an interface of the network-side device; the network-side device obtains model information of the medical device; the network-side device searches for a corresponding API data interface based on the model information, wherein the API data interface is used to interact with the medical device for data; the network-side device converts the data received from the API interface into a predetermined format; and the network-side device processes the data in the predetermined format.

[0007] Furthermore, the network side device processes the data in the predetermined format, including: the network side device obtains the operating status information of the medical device from the data in the predetermined format; the network side device determines whether the medical device has an abnormality based on the operating status information; and the network side device issues an alarm when an abnormality occurs.

[0008] Furthermore, the network side device processes the data in the predetermined format, including: the network side device displays the data in the predetermined format, wherein the operating status information based on which the abnormality of the medical device is judged is displayed using a first display mode, and the remaining operating status information is displayed using a second display mode, and the first display mode and the second display mode are different.

[0009] Furthermore, the network side device sends an alarm when an abnormality occurs, including: the network side device determines the fault of the medical device based on the operating status information based on which the abnormality of the medical device is determined; the network side device sends the fault to a pre-configured contact method.

[0010] Furthermore, the operation status information includes at least one of the following: hardware operation health status information, device load operation status information, application operation status information, and data transmission status information.

[0011] According to another aspect of the present application, a real-time health collection and monitoring system for medical devices is also provided, which runs on a network side device and includes: the system is used to obtain the medical device connected to the network side device through an interface of the network side device; the system is used to obtain the model information of the medical device; the system is used to search for the corresponding API data interface according to the model information, wherein the API data interface is used to interact with the medical device for data; the system is used to convert the data received from the API interface into a predetermined format; the system is used to process the data in the predetermined format.

[0012] Furthermore, the system is used to process the data in the predetermined format, including: the system is used to obtain the operating status information of the medical device from the data in the predetermined format; the system is used to determine whether the medical device has an abnormality based on the operating status information; the system is used to issue an alarm in the event of an abnormality.

[0013] Furthermore, the system is used to process the data in the predetermined format, including: the system is used to display the data in the predetermined format, wherein the operating status information based on which the abnormality of the medical device is judged is displayed using a first display mode, and the remaining operating status information is displayed using a second display mode, and the first display mode and the second display mode are different.

[0014] Furthermore, the system is used to issue an alarm in the event of an abnormality, including: the system is used to determine the fault of the medical device based on the operating status information based on which the abnormality of the medical device is determined; the system is used to send the fault to a pre-configured contact method.

[0015] Furthermore, the operation status information includes at least one of the following: hardware operation health status information, device load operation status information, application operation status information, and data transmission status information.

[0016] In the embodiment of the present application, a network-side device is used to obtain the medical device connected to the network-side device through the interface of the network-side device; the network-side device obtains the model information of the medical device; the network-side device searches for the corresponding API data interface according to the model information, wherein the API data interface is used to interact with the medical device for data; the network-side device converts the data received from the API interface into a predetermined format; the network-side device processes the data in the predetermined format. This application solves the problems caused by the inconsistency of interfaces and protocols of medical device manufacturers in the prior art, thereby improving the transformation of health monitoring of medical devices into active monitoring, thereby providing technical guarantees for the normal operation of medical devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 is a flowchart of the method involved according to an embodiment of the present application;

[0019] Figure 2 This is a schematic diagram of an edge intelligent gateway process according to an embodiment of the present application;

[0020] Figure 3 It is a flowchart of a method for real-time health collection and monitoring of medical equipment according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0022] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0023] In this embodiment, a method for real-time monitoring of the health of medical equipment is provided. Figure 3 is a flow chart of a method for real-time health collection and monitoring of medical equipment according to an embodiment of the present application. Figure 3 The process includes the following steps:

[0024] Step S302, the network side device obtains that the medical device is connected to the network side device through the interface of the network side device;

[0025] Step S304, the network side device obtains the model information of the medical device;

[0026] Step S306, the network-side device searches for a corresponding API data interface according to the model information, wherein the API data interface is used to perform data interaction with the medical device;

[0027] As an optional implementation, in this step, the model information and the corresponding API data interface are pre-configured. For example, the correspondence between multiple model information and API data interfaces can be pre-configured. In the case that the network side device fails to obtain the API data interface according to the model information, the network side device searches for an API data interface corresponding to another model information similar to the model information according to the model information. After finding the API data interface corresponding to the other model information, a test message is sent to the API data interface. If a response message to the test message is received, it means that the API interface is correct, and the correspondence between the API data interface and the model information is saved.

[0028] When the network side device searches for the correspondence between the model information and the API data interface, the network side device obtains the process name for searching for the correspondence, and determines whether the process name is in the whitelist; if the process name is not in the whitelist, the network side device does not allow the process corresponding to the process name to search for the correspondence.

[0029] Step S308, the network side device converts the data received from the API interface into a predetermined format;

[0030] Step S310: the network side device processes the data in the predetermined format.

[0031] There are many ways to perform processing. For example, the network side device obtains the operating status information of the medical device from the data in the predetermined format; the network side device determines whether the medical device has an abnormality based on the operating status information (the operating status information may include at least one of the following: hardware operating health status information, device load operating status information, application operating status information, data transmission status information); and the network side device issues an alarm when an abnormality occurs.

[0032] In an optional embodiment, it is possible to determine whether an abnormality occurs by means of artificial intelligence. A neural network-based machine learning model is trained using multiple sets of training data, each of which includes input data and output data, wherein the input data is operating status information, and the output data is whether the medical device status corresponding to the operating status information is normal. After the machine learning model training converges, the operating status information is input into the machine learning model, and the machine learning model outputs whether the medical device is abnormal.

[0033] In this embodiment, the network-side device determines the fault of the medical device based on the operating status information based on which the abnormality of the medical device is determined; the network-side device sends the fault to a pre-configured contact method.

[0034] Alternatively, the network side device displays the data in the predetermined format, wherein the operating status information based on which the abnormality of the medical device is judged is displayed using a first display mode, and the remaining operating status information is displayed using a second display mode, and the first display mode and the second display mode are different.

[0035] This application solves the problems caused by the inconsistency of interfaces and protocols of medical equipment manufacturers in the prior art, thereby improving the health monitoring of medical equipment to active monitoring, thereby providing technical guarantee for the normal operation of medical equipment.

[0036] The following is an explanation in conjunction with an optional embodiment. In this optional embodiment, a multi-interface device is customized to support it, and a development application is installed and deployed on this device. This device (edge ​​intelligent gateway) supports common medical device interfaces on the market. By deploying an edge intelligent gateway at the edge of the medical device, the manufacturer model of the accessed medical device can be obtained through the application program, and the obtained manufacturer model is matched to the relevant API data interface in the API library. The hardware operation health status, device load operation status, application operation status, data transmission status and other data of the access device are obtained in real time through the API data interface, and the data obtained from the device is pre-processed according to a unified data format, and the processed data is sent to the data analysis module. The data analysis module analyzes whether there is abnormal information and error code output. If there is no abnormality, the data is displayed through the visualization module. If there is abnormal information and error code, the diagnosis method and automatic repair method are matched by querying the fault knowledge base. If the repair fails, the relevant information of the faulty device is sent to the operation and maintenance personnel for processing through the alarm module.

[0037] like Figure 1 As shown, this embodiment provides a medical equipment monitoring system, including an edge intelligent gateway, an API application interface information library, a fault case knowledge base, a data acquisition module, a data analysis module, a fault automatic repair module, a visualization display module, a log storage module, and an alarm module. The system is described below.

[0038] Edge Intelligent Gateway

[0039] There are many types of hospital medical equipment manufacturers, and the ports, protocols, and API interfaces for data acquisition are not unified. By developing and deploying edge gateway devices, the gateway device supports multiple protocols and communication interfaces, and is compatible with various data acquisition port accesses. Data acquisition and data preprocessing modules are installed and deployed on the gateway device to collect real-time health data of the equipment and perform unified data preprocessing operations on the acquired data.

[0040] API application interface information library;

[0041] The API application program interface information library stores the medical manufacturer's device interface information library, stores the API (Application Programming Interface) interfaces of medical device manufacturers, and stores them by functional type, which are divided into hardware operation health status, equipment load operation status, application operation status, and data transmission status. The edge intelligent gateway obtains the manufacturer and model of the acquisition equipment, and matches the corresponding API access interface in the API application program interface information library through the manufacturer and device model.

[0042] Troubleshooting Case Knowledge Base

[0043] The fault case and knowledge base storage collects and organizes the fault error codes, fault error log output information, fault diagnosis methods, fault repair methods and common cases of medical manufacturers' equipment. Through the fault case knowledge base, the fault automatic repair module can automatically repair the equipment by matching the fault information to the diagnosis and repair methods.

[0044] Data acquisition module

[0045] A data collection module is deployed in the edge intelligent gateway device to collect real-time data from connected medical devices, and the data is classified according to the hardware health status, load status, application operation status, and data transmission status. The classified data is then sent to the data preprocessing module to preprocess the real-time collected data logs in a unified format, and the preprocessed data is sent to the data analysis module;

[0046] Data Analysis Module

[0047] The data acquisition and preprocessing module sends the data to the data analysis module through network transmission. The data analysis module analyzes and judges the data log. If the data is in a normal and healthy state, the data is transmitted to the visualization module and displayed. If there is fault error information, the fault information is sent to the fault automatic repair module.

[0048] Fault automatic repair module

[0049] The automatic fault repair module is divided into fault identification, diagnosis, and repair functions. The fault identification function first identifies the fault type from the faulty device output information transmitted by the data analysis module. The fault diagnosis module matches the fault case and fault diagnosis method according to the fault type, and sends the fault diagnosis method to the edge intelligent gateway. The edge intelligent gateway sends instructions to the faulty device and monitors the device diagnosis process. The fault repair module matches the repair method and case according to the error information judged by the diagnosis, sends the repair method to the edge intelligent gateway, and starts the automatic repair of the faulty device. If the repair is successful, the device is displayed as healthy through visualization. If the device is repaired, the alarm module is used to report the repair to the manufacturer to the operation and maintenance personnel. After the manufacturer repairs the fault, the fault information and repair process method are sorted out and uploaded to the fault case knowledge base to improve the knowledge base information.

[0050] Visual display module

[0051] The visualization processing module displays the health status and automated repair process of the monitoring equipment in real time on the large screen. If there is an abnormality in the equipment, it will be marked in red on the large screen, and the abnormal error report of the equipment will be displayed for maintenance personnel to repair and handle.

[0052] Log storage module

[0053] Build and deploy a log storage cluster to store all medical equipment data by hardware health status, port traffic, application operation, etc., which can be used as a reference for monitoring. For example, by comparing the historical traffic in the past seven days, if a sudden increase in traffic is found, it can be displayed as a yellow alarm to notify the operation and maintenance personnel to check whether it is an abnormal access.

[0054] Alarm module

[0055] If the equipment fault cannot be repaired through the automatic fault repair module, the alarm module can be called to send the location of the faulty equipment, equipment S / N number, manufacturer model, whether the warranty has expired and other information to the operation and maintenance personnel. The operation and maintenance personnel report the fault to the manufacturer and assist the manufacturer's technicians in resolving the fault. After the fault is resolved, the fault error information and processing process are uploaded to the fault case knowledge base.

[0056] Combined with Figure 2 The edge intelligent gateway in the present invention is further described.

[0057] Figure 2 The edge intelligent gateway device in the system is based on a customizable development device that can match the ports of common medical devices. Figure 2 As shown, it includes the following parts:

[0058] Embedded Linux system

[0059] Embed the Linux system on the customized device, tune the Linux kernel to ensure that the Linux system does not occupy too many resources after installation, and then deploy various port drivers on the Linux system to support plug-and-play of ports.

[0060] API programming interface

[0061] The function of the API programming interface is to detect the medical equipment connected to the port, detect the manufacturer model of the connected medical equipment, and use the manufacturer model to match the data API application interface of this manufacturer model in the API application interface information library.

[0062] Data Acquisition Pre-Module

[0063] This module obtains the data API application interface of the matched connected medical device through the API programming interface, obtains the health data of the connected medical device in real time, and pre-processes the data according to a unified format.

[0064] Fault diagnosis module

[0065] The fault automatic repair module searches the fault knowledge base through the abnormal information and error code of the faulty medical device to match the fault diagnosis process, and then sends the fault diagnosis process method to the fault diagnosis module of the edge intelligent gateway. The fault diagnosis module sends the fault diagnosis method to the faulty medical device for fault judgment and monitors the output of the diagnosis process in real time, and sends the detailed diagnosis results to the fault automatic repair module. The fault automatic repair module matches the fault repair method more accurately in the fault knowledge base based on the diagnosis results, and sends the fault repair method to the fault diagnosis module. The fault diagnosis module repairs the faulty medical device through the fault repair method, and feeds back the repair process and results to the fault automatic repair module.

[0066] This embodiment has the following effects: it reduces the manpower maintenance cost, eliminates the need for operation and maintenance personnel to frequently enter and exit the hospital working environment to regularly inspect equipment, and reduces the safety risks of inspection operations in and out of the hospital working environment. By establishing a medical manufacturer API library, the API interface can be automatically matched for new medical equipment, and the new equipment can be added to the monitoring platform. Through the display of the visualization module, the healthy operation status of the medical equipment can be displayed and mastered in real time, and the operation and maintenance personnel can monitor and locate problems more intuitively and quickly. Through the fault diagnosis and repair function, the equipment fault repair time can be reduced, and the repetitive work of contacting different equipment manufacturers to report problems and then waiting for the manufacturer to arrange technicians to come to the site to check the fault and repair it is solved, thereby improving the efficiency of handling abnormalities. From traditional passive inspections to active detection, preventive maintenance can be easily implemented, unplanned downtime can be reduced, and the healthy and orderly operation of medical equipment can be guaranteed.

[0067] In this embodiment, an electronic device is provided, including a memory and a processor. The memory stores a computer program, and the processor is configured to run the computer program to execute the method in the above embodiment.

[0068] The above program can be run in the processor, or it can be stored in the memory (or computer-readable medium), which includes permanent and non-permanent, removable and non-removable media. Information storage can be achieved by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0069] These computer programs can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps of the functions specified in one or more blocks can be implemented by different modules corresponding to different steps.

[0070] Such a device or system is provided in this embodiment. The system is called a real-time health collection and monitoring system based on medical equipment, which runs on a network-side device and includes: the system is used to obtain the medical equipment connected to the network-side device through the interface of the network-side device; the system is used to obtain the model information of the medical equipment; the system is used to find the corresponding API data interface according to the model information, wherein the API data interface is used to interact with the medical equipment for data; the system is used to convert the data received from the API interface into a predetermined format; the system is used to process the data in the predetermined format.

[0071] The system or device is used to implement the functions of the method in the above-mentioned embodiment. Each module in the system or device corresponds to each step in the method, which has been explained in the method and will not be repeated here.

[0072] For example, the system is used to process the data in the predetermined format, including: the system is used to obtain the operating status information of the medical device from the data in the predetermined format; the system is used to determine whether the medical device is abnormal based on the operating status information; the system is used to alarm in the event of an abnormality. Optionally, the system is used to process the data in the predetermined format, including: the system is used to display the data in the predetermined format, wherein the operating status information based on which the abnormality of the medical device is determined is displayed using a first display mode, and the remaining operating status information is displayed using a second display mode, and the first display mode and the second display mode are different.

[0073] For another example, the system is used to issue an alarm in the event of an abnormality, including: the system is used to determine the fault of the medical device based on the operating status information based on which the abnormality of the medical device is determined; the system is used to send the fault to a pre-configured contact method.

[0074] This application solves the problems caused by the inconsistency of interfaces and protocols of medical equipment manufacturers in the prior art, thereby improving the health monitoring of medical equipment to active monitoring, thereby providing technical guarantee for the normal operation of medical equipment.

[0075] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A real-time health monitoring method based on medical equipment, characterized in that: include: The network side device obtains that the medical device is connected to the network side device through the interface of the network side device; The network side device obtains the model information of the medical device; The network side device searches for the corresponding API data interface according to the model information, wherein the API data interface is used to perform data interaction with the medical device; wherein, a plurality of correspondences between model information and API data interfaces are pre-configured; in the case where the network side device fails to obtain the API data interface according to the model information, the network side device searches for an API data interface corresponding to another model information similar to the model information according to the model information, and after finding the API data interface corresponding to the other model information, sends a test message to the API data interface, and if a response message to the test message is received, it means that the API data interface is correct, and the correspondence between the API data interface and the model information is saved; when the network side device searches for the correspondence between the model information and the API data interface, the network side device obtains the process name for searching for the correspondence, and determines whether the process name is in the white list. If the process name is not in the white list, the network side device does not allow the process corresponding to the process name to search for the correspondence; The network side device converts the data received from the API interface into a predetermined format; The network side device processes the data in the predetermined format, including: the network side device obtains the operating status information of the medical device from the data in the predetermined format; the network side device determines whether the medical device is abnormal according to the operating status information; the network side device issues an alarm in the event of an abnormality; the network side device displays the data in the predetermined format, wherein the operating status information based on which the abnormality of the medical device is determined is displayed using a first display mode, and the remaining operating status information is displayed using a second display mode, and the first display mode and the second display mode are different; The network side device alarming in the event of an abnormality includes: the network side device determining the fault of the medical device according to the operating status information based on which the abnormality of the medical device is determined; the network side device sending the fault to a pre-configured contact method; the operating status information includes at least one of the following: hardware operating health status information, equipment load operating status information, application operating status information, and data transmission status information; Among them, whether an abnormality occurs is determined by artificial intelligence, wherein a plurality of sets of training data are used to train a machine learning model based on a neural network, wherein each set of training data includes input data and output data, wherein the input data is operating status information, and the output data is whether the state of the medical device corresponding to the operating status information is normal. After the training of the machine learning model converges, the operating status information is input into the machine learning model, and the machine learning model outputs whether the medical device has an abnormality.

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