Cloud platform-based medical device information transmission monitoring system

Abstract

The present application belongs to the technical field of medical equipment supervision, and is specifically a medical equipment information transmission supervision system based on a cloud platform, comprising a cloud platform, an information collection module, a wireless transmission module, a transmission stability detection module, a transmission security detection module and a background terminal; the present application sends medical equipment information to the cloud platform for storage via the wireless transmission module through the information collection module, the transmission stability detection module performs transmission stability detection analysis on the information transmission process, and the transmission security detection module performs transmission security analysis on the transmission network, which is conducive to ensuring the safe and stable transmission of medical equipment information, and the medical equipment management comprehensive evaluation module comprehensively judges the management status of the medical equipment based on the transmitted medical equipment information, which is highly intelligent and conducive to ensuring the service life of the medical equipment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical equipment supervision, in particular to a medical equipment information transmission supervision system based on a cloud platform. BACKGROUND

[0002] With the rapid development of medical technology, medical equipment is used more and more widely, and the operation management and supervision of medical equipment have become an important problem faced by medical institutions. When medical equipment is managed, relevant medical equipment information needs to be collected.

[0003] At present, when medical equipment information is transmitted, the transmission speed performance and transmission security cannot be reasonably analyzed and timely warned, and the management condition of the medical equipment cannot be comprehensively judged based on the transmitted medical equipment information, which is low in intelligent degree and is not conducive to ensuring the service life of the medical equipment.

[0004] In view of the above technical defects, a solution is proposed. SUMMARY

[0005] The present application aims to provide a medical equipment information transmission supervision system based on a cloud platform, which solves the problem that the prior art cannot reasonably analyze and timely warn the transmission performance and transmission security when transmitting medical equipment information, and cannot comprehensively judge the management condition of the medical equipment based on the transmitted medical equipment information, which is low in intelligent degree.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0007] The medical equipment information transmission supervision system based on the cloud platform comprises a cloud platform, an information collection module, a wireless transmission module, a transmission stability detection module, a transmission security detection module and a background terminal. The information collection module is used to collect medical equipment information and send the medical equipment information to the cloud platform for storage through the wireless transmission module. The management personnel accesses the cloud platform through the background terminal and queries and supervises the medical equipment information.

[0008] In the process of transmitting the medical equipment information to the cloud platform by the wireless transmission module, the transmission stability detection module detects and analyzes the transmission stability of the information transmission process, generates a transmission stability qualified signal or a transmission stability abnormal signal, and sends the transmission stability normal signal or the transmission stability abnormal signal to the background terminal.

[0009] The transmission security detection module obtains the network for information transmission of the wireless transmission module and marks it as a transmission network, analyzes the transmission security of the transmission network to generate a transmission security qualified signal or a transmission security abnormal signal, and sends the transmission security qualified signal or the transmission security abnormal signal to the background terminal. When the background terminal receives the transmission stability abnormal signal or the transmission security abnormal signal, a corresponding early warning is issued.

[0010] Further, the specific analysis process of the transmission stability detection analysis is as follows:

[0011] In the medical device information transmission process, the real-time transmission speed curve in the medical device information transmission process is placed in the rectangular coordinate system located in the first quadrant, and the corresponding rectangular coordinate system is marked as a transmission speed coordinate system, and the transmission speed coordinate system takes time as the X axis and transmission speed as the Y axis.

[0012] All peak points and all valley points in all transmission speed coordinate systems are collected, the ordinate of all peak points and the ordinate of all valley points are subjected to variance calculation to obtain a peak-valley stability value, and the peak-valley stability value is compared with a preset peak-valley stability threshold value. If the peak-valley stability value exceeds the preset peak-valley stability threshold value, a transmission stability abnormal signal is generated.

[0013] Further, if the peak-valley stability value does not exceed the preset peak-valley stability threshold value, a ray parallel to the X axis and having its end point on the Y axis is drawn in the transmission speed coordinate system, and the drawn ray is marked as a transmission speed detection ray. All areas of the corresponding closed regions located below the transmission speed detection ray and surrounded by the transmission detection ray are obtained, the areas of the corresponding closed regions are collected and marked as closed face detection values, and the closed face detection values are compared with a preset closed face detection threshold value. If the closed face detection value exceeds the preset closed face detection threshold value, the corresponding closed region is marked as a buffer table region.

[0014] The number of buffer table regions is obtained and marked as a buffer table detection value, all closed face detection values are summed to obtain a closed face condition value, and the ratio of the peak-valley stability value to the preset peak-valley stability threshold value is marked as a peak-valley stability occupancy value. The peak-valley stability occupancy value, the buffer table detection value, and the closed face condition value are subjected to numerical calculation to obtain a transmission speed abnormal condition value, and the transmission speed abnormal condition value is compared with a preset transmission speed abnormal condition threshold value. If the transmission speed abnormal condition value exceeds the preset transmission speed abnormal condition threshold value, a transmission stability abnormal signal is generated. If the transmission speed abnormal condition value does not exceed the preset transmission speed abnormal condition threshold value, a transmission stability qualified signal is generated.

[0015] Further, the specific analysis process of the transmission security analysis is as follows:

[0016] The number of network attacks on the transmission network per unit time is collected and marked as an attack frequency value, and the start time and end time of each network attack are calculated to obtain the attack duration. The number of attack durations that exceed the preset attack duration threshold is marked as an attack high frequency value;

[0017] The network scanning tool scans the security vulnerabilities of the transmission network, and the number of security vulnerabilities of the transmission network per unit time is marked as a vulnerability frequency value. The network repair tool repairs the security vulnerabilities, and the repair start time and repair completion time of the corresponding security vulnerabilities are calculated to obtain the repair duration. The number of repair durations that exceed the preset repair duration threshold is marked as a repair high frequency value. The attack frequency value, attack high frequency value, vulnerability frequency value, and repair high frequency value are calculated to obtain the transmission network risk value. The transmission network risk value is compared with the preset transmission network risk threshold value. If the transmission network risk value exceeds the preset transmission network risk threshold value, a transmission security anomaly signal is generated. If the transmission network risk value does not exceed the preset transmission network risk threshold value, a transmission security qualified signal is generated.

[0018] Further, the cloud platform includes a medical device state analysis module, a medical device environment analysis module, a medical device supervision analysis module, and a medical device management comprehensive evaluation module. The medical device state analysis module analyzes the device state of the medical device based on the corresponding medical device information, obtains a state detection value through analysis, and sends the state detection value to the medical device management comprehensive evaluation module;

[0019] The medical device environment analysis module analyzes the running environment of the medical device based on the corresponding medical device information, obtains an environment detection value through analysis, and sends the environment detection value to the medical device management comprehensive evaluation module. The medical device supervision analysis module analyzes the operation supervision performance of the medical device based on the corresponding medical device information, obtains a supervision detection value through analysis, and sends the supervision detection value to the medical device management comprehensive evaluation module;

[0020] The medical device management comprehensive evaluation module compares the state detection value, the environment detection value, and the supervision detection value with the preset state detection threshold, the preset environment detection threshold, and the preset supervision detection threshold, respectively. If the state detection value, the environment detection value, or the supervision detection value exceeds the corresponding preset threshold, a device difficult-to-manage signal of the corresponding medical device is generated;

[0021] If the state detection value, the environment detection value and the supervision detection value do not exceed the corresponding preset threshold value, the state detection value, the environment detection value and the supervision detection value are calculated to obtain a medical equipment management detection value, the medical equipment management detection value is compared with the corresponding preset medical equipment management detection threshold value, if the medical equipment management detection value exceeds the preset medical equipment management detection threshold value, a device difficult management signal of the corresponding medical equipment is generated; if the medical equipment management detection value does not exceed the preset medical equipment management detection threshold value, a device easy management signal of the corresponding medical equipment is generated, and the device difficult management signal or the device easy management signal of the corresponding medical equipment is sent to the background terminal.

[0022] Further, the specific analysis process of the medical equipment state analysis module is as follows:

[0023] The fault records of the corresponding medical equipment in the detection period are collected, all fault types of the medical equipment are obtained based on the fault records, the occurrence number of the corresponding fault type in the detection period is marked as a fault detection value, a set of preset fault weight values corresponding to each group of fault types is set in advance, the product of the fault detection value of the corresponding fault type and the matched preset fault weight value is marked as a fault preliminary detection value, and the sum of the fault preliminary detection values of all fault types is marked as a fault re-detection value.

[0024] The single continuous duration that the corresponding medical equipment is suspended due to the fault is obtained, the sum of all single continuous durations in the detection period is marked as a total temporary operation time value, and the number of single continuous durations that exceed the preset single continuous duration threshold value is marked as a high stop detection value, and the fault re-detection value, the total temporary operation time value and the high stop detection value are calculated to obtain the state detection value.

[0025] Further, the specific analysis process of the medical equipment environment analysis module is as follows:

[0026] The environment parameters that need to be monitored in the environment of the medical equipment are obtained, the real-time detection data of the corresponding environment parameters are collected, the real-time detection data are compared with the corresponding preset data requirements, if the real-time detection data do not meet the corresponding preset data requirements, the corresponding environment parameters are marked as parameters to be adjusted; the deviation value of the real-time detection data of the corresponding parameters to be adjusted from the corresponding preset data requirements is marked as a distance detection value to be adjusted, and the adjustment duration for adjusting the corresponding parameters to be adjusted and restoring them to meet the corresponding preset data requirements is collected, and the ratio of the distance detection value to be adjusted to the adjustment duration is marked as an efficiency detection value to be adjusted;

[0027] The all need-to-adjust efficiency detection values of the corresponding environment parameters in the detection period are obtained, and the mean value calculation is performed to obtain a need-to-adjust efficiency detection value, and the number of times of adjustment of the corresponding environment parameters in the detection period is obtained and marked as a need-to-adjust frequency detection value, the need-to-adjust efficiency detection value and the need-to-adjust frequency detection value are calculated to obtain a need-to-adjust detection condition value, the need-to-adjust detection condition value is compared with the corresponding preset need-to-adjust detection condition threshold value, and if the need-to-adjust detection condition value exceeds the corresponding preset need-to-adjust detection condition threshold value, the corresponding environment parameter is marked as an abnormal condition parameter.

[0028] The number of abnormal condition parameters in the environment of the corresponding medical device in the detection period is obtained and marked as an abnormal condition detection value, the ratio calculation is performed on the need-to-adjust detection condition value of the corresponding environment parameter and the corresponding preset need-to-adjust detection condition threshold value to obtain a need-to-adjust detection occupation value, the mean value calculation is performed on the need-to-adjust detection occupation values of all environment parameters to obtain a need-to-adjust occupation analysis value, and the need-to-adjust detection occupation value with the maximum value is marked as a need-to-adjust occupation amplitude value, and the numerical calculation is performed on the abnormal condition detection value, the need-to-adjust occupation analysis value and the need-to-adjust occupation amplitude value to obtain an environment detection value.

[0029] Further, the specific analysis process of the medical device supervision analysis module is as follows:

[0030] The operation record of the corresponding medical device in the detection period is obtained, all operators are obtained based on the operation record, whether the corresponding operator has the right to operate the corresponding medical device is collected, and if not, the corresponding operator is marked as an unauthorized person;

[0031] The number of operations of all unauthorized persons is collected and marked as an unauthorized frequency, and the number of error operations in the corresponding operation process of the medical device is collected, the number of operation processes exceeding the preset error operation number is marked as a high failure operation frequency value, and the mean value calculation is performed on the error operation numbers of all operation processes in the detection period to obtain an operation error condition value, and the numerical calculation is performed on the unauthorized frequency, the high failure operation frequency value and the operation error condition value to obtain a supervision detection value.

[0032] Compared with the prior art, the beneficial effects of the present application are:

[0033] 1、In the present application, the medical device information is sent to the cloud platform for storage through the wireless transmission module by the information collection module, the transmission stability detection module performs transmission stability detection analysis on the information transmission process, the transmission safety detection module performs transmission safety analysis on the transmission network, and when a transmission stability abnormal signal or a transmission safety abnormal signal is generated, the background terminal issues a corresponding early warning, which can reasonably analyze the transmission speed performance and transmission safety of the medical device information and timely warn, and ensure the safe and stable transmission of the medical device information.

[0034] 2、In the present application, the management performance of the corresponding medical equipment in the detection period is analyzed by the medical equipment management comprehensive evaluation module to judge the management difficulty, and the monitoring and supervision of the corresponding medical equipment are strengthened when the device difficult management signal is generated, which can comprehensively judge the management condition of the medical equipment based on the transmitted medical equipment information, significantly reduce the safety hidden danger of the corresponding medical equipment, prolong the service life of the corresponding medical equipment, and has high intelligent degree. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to facilitate those skilled in the art to understand, the present application will be further described below in conjunction with the drawings;

[0036] Figure 1 The system block diagram of example one in the present application is shown in the figure;

[0037] Figure 2 The system block diagram of example two, example three and example four in the present application is shown in the figure. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0039] Example one: as shown in the figure, the medical equipment information transmission supervision system based on cloud platform proposed by the present application includes cloud platform, information collection module, wireless transmission module, transmission stability detection module, transmission safety detection module and background terminal; Figure 1

[0040] Among them, the information collection module is used for collecting medical equipment information (including equipment running information, environment information, operation information, etc.), and sending the medical equipment information to the cloud platform for storage through the wireless transmission module; the management personnel accesses the cloud platform through the background terminal, and queries and supervises the medical equipment information;

[0041] In the process of transmitting the medical equipment information to the cloud platform by the wireless transmission module, the transmission stability detection module detects and analyzes the transmission stability of the information transmission process, generates a transmission stability qualified signal or a transmission stability abnormal signal through analysis, and sends the transmission stability normal signal or the transmission stability abnormal signal to the background terminal. When the background terminal receives the transmission stability abnormal signal, it issues a corresponding early warning to remind the management personnel to investigate the transmission condition in time, and to take corresponding improvement measures according to the need, so as to facilitate to ensure the transmission efficiency of the medical equipment information in the future; the specific analysis process of transmission stability detection analysis is as follows:​

[0042] In the medical device information transmission process, the real-time transmission speed curve in the medical device information transmission process is placed in the rectangular coordinate system located in the first quadrant, and the corresponding rectangular coordinate system is marked as a transmission speed coordinate system, and the transmission speed coordinate system takes time as the X axis and transmission speed as the Y axis;

[0043] All peak points and all valley points in all transmission speed coordinate systems are collected, and the variances of the ordinates of all peak points and the ordinates of all valley points are calculated to obtain a peak-valley stability value. It should be noted that the greater the peak-valley stability value, the more unstable the transmission speed in the medical device information transmission process. The peak-valley stability value is compared with the preset peak-valley stability threshold value. If the peak-valley stability value exceeds the preset peak-valley stability threshold value, it indicates that the transmission speed fluctuation in the medical device information transmission process is large, and a transmission stability abnormal signal is generated.

[0044] Further, if the peak-valley stability value does not exceed the preset peak-valley stability threshold value, it indicates that the transmission speed fluctuation in the medical device information transmission process is small, then a ray parallel to the X axis and with its endpoints on the Y axis is drawn in the transmission speed coordinate system, and the drawn ray is marked as a transmission speed detection ray. It should be noted that the Y axis coordinate of the transmission speed detection ray represents the preset real-time transmission speed lower threshold value;

[0045] All areas of the closed regions located below the transmission speed detection ray and surrounded by the transmission detection ray are obtained, the areas of the corresponding closed regions are collected and marked as closed surface detection values, and the closed surface detection values are compared with the preset closed surface detection threshold value. If the closed surface detection value exceeds the preset closed surface detection threshold value, the corresponding closed region is marked as a buffer table region;

[0046] The number of buffer table regions is obtained and marked as a buffer table detection value, all closed surface detection values are summed to obtain a closed surface condition value, and the ratio of the peak-valley stability value to the preset peak-valley stability threshold value is marked as a peak-valley stability value;

[0047] The peak-valley stability value FK, the buffer table detection value FL, and the closed surface condition value FS are numerically calculated by the formula FX=a1*FK+a2*FL+a3*FS / a2 to obtain a transmission speed condition value FX, where a1, a2, and a3 are preset proportionality coefficients, and a1>a2>a3>0. The greater the transmission speed condition value FX, the worse the transmission of the medical device information;

[0048] The transmission speed abnormality value FX is compared with a preset transmission speed abnormality threshold value. If the transmission speed abnormality value FX exceeds the preset transmission speed abnormality threshold value, it indicates that the transmission of the medical equipment information is poor, and a transmission stability abnormality signal is generated. If the transmission speed abnormality value FX does not exceed the preset transmission speed abnormality threshold value, it indicates that the transmission of the medical equipment information is good, and a transmission stability qualified signal is generated.

[0049] The transmission security detection module obtains the network used by the wireless transmission module for information transmission and marks it as a transmission network. Transmission security analysis is performed on the transmission network to generate a transmission security qualified signal or a transmission security abnormality signal, and the transmission security qualified signal or the transmission security abnormality signal is sent to the background terminal. When the background terminal receives the transmission security abnormality signal, it issues a corresponding early warning, so that the management personnel can timely strengthen the transmission risk monitoring and control, and ensure the subsequent transmission security of the medical equipment information. The specific analysis process of the transmission security analysis is as follows:

[0050] The number of times of network attacks on the transmission network per unit time is collected and marked as an attack frequency detection value. The start time and end time of each network attack are calculated to obtain the attack duration. The number of attack durations that exceed the preset attack duration threshold value is marked as an attack high frequency value.

[0051] The transmission network is scanned for vulnerabilities by a network scanning tool, and the number of security vulnerabilities existing in the transmission network per unit time is obtained and marked as a vulnerability frequency detection value. The security vulnerabilities are repaired by a network repair tool, and the start time and completion time of the repair for the corresponding security vulnerabilities are calculated to obtain the repair duration. The number of repair durations that exceed the preset repair duration threshold value is marked as a repair high frequency value.

[0052] The attack frequency detection value RF, the attack high frequency value RY, the vulnerability frequency detection value RL, and the repair high frequency value RP are numerically calculated by the formula RX=(ew1*RF+ew2*RY+ew3*RL+ew4*RP) / 2 to obtain a transmission network risk value RX, wherein ew1, ew2, ew3, and ew4 are preset proportion coefficients, and ew2>ew4>ew1>ew3>0. The greater the value of the transmission network risk value RX, the greater the security risk of the transmission network.

[0053] The transmission network risk value RX is compared with a preset transmission network risk threshold value. If the transmission network risk value RX exceeds the preset transmission network risk threshold value, it indicates that the security risk of the transmission network is large, and a transmission security abnormality signal is generated. If the transmission network risk value RX does not exceed the preset transmission network risk threshold value, it indicates that the security risk of the transmission network is small, and a transmission security qualified signal is generated.

[0054] Furthermore, the cloud platform includes a medical device management comprehensive evaluation module. This module is used to set the testing cycle, obtain the status detection value, environmental detection value, and regulatory detection value of the corresponding medical device within the testing cycle, and compare the status detection value, environmental detection value, and regulatory detection value with the preset status detection threshold, preset environmental detection threshold, and preset regulatory detection threshold respectively. If the status detection value, environmental detection value, or regulatory detection value exceeds the corresponding preset threshold, it indicates that the management of the corresponding medical device is more difficult and the supervision of the corresponding medical device needs to be strengthened, thus generating a signal that the corresponding medical device is difficult to manage.

[0055] If the status detection value, environmental detection value, and regulatory detection value do not exceed the corresponding preset thresholds, the medical equipment management and inspection value GX is calculated using the formula GX = fg1*GK + fg2*GP + fg3*GS. Here, fg1, fg2, and fg3 are preset proportional coefficients, and all fg1, fg2, and fg3 are positive numbers. Furthermore, the larger the value of the medical equipment management and inspection value GX, the greater the overall management difficulty of the corresponding medical equipment and the greater the potential safety hazards.

[0056] The medical equipment inspection value GX is compared with the corresponding preset medical equipment inspection threshold. If the medical equipment inspection value GX exceeds the preset medical equipment inspection threshold, it indicates that the management of the corresponding medical equipment is more difficult and requires stronger supervision. In this case, a signal indicating that the medical equipment is difficult to manage is generated. If the medical equipment inspection value GX does not exceed the preset medical equipment inspection threshold, it indicates that the management of the corresponding medical equipment is less difficult. In this case, a signal indicating that the medical equipment is easy to manage is generated.

[0057] Furthermore, the system sends the corresponding medical equipment's difficult-to-manage or easy-to-manage signal to the back-end terminal. When the administrator receives the corresponding medical equipment's difficult-to-manage signal, they will subsequently strengthen the monitoring and supervision of the corresponding medical equipment to ensure its safe and stable operation, significantly reduce the potential safety hazards of the corresponding medical equipment, and help extend the service life of the corresponding medical equipment.

[0058] Example 2: Figure 2 As shown, the difference between this embodiment and Embodiment 1 is that the cloud platform also includes a medical device status analysis module. This module analyzes the device status of the medical devices based on relevant medical device information, obtains status detection values ​​through analysis, and sends these values ​​to the medical device management and evaluation module. This not only accurately reflects the operational fault status of the corresponding medical devices within the detection period but also provides data support for the analysis process of the medical device management and evaluation module, ensuring the accuracy of its analysis results. The specific analysis process of the medical device status analysis module is as follows:

[0059] The system collects fault records of the corresponding medical equipment within the testing period, obtains all fault types of the medical equipment based on the fault records, and marks the occurrence of the corresponding fault type within the testing period as the fault count value. Each fault type is pre-set to correspond to a set of preset fault weight values, where the preset fault weight values ​​are all greater than zero. Furthermore, the greater the safety hazard posed by the corresponding fault type, the larger the corresponding preset fault weight value. The product of the fault count value of the corresponding fault type and the matched preset fault weight value is marked as the initial fault detection value, and the sum of the initial fault detection values ​​of all occurring fault types is marked as the re-fault detection value.

[0060] It also obtains the duration of a single instance of medical equipment being temporarily out of service due to a malfunction, marks the sum of all single instances of duration within the detection period as the total temporary operation time, compares the duration of a single instance with a preset single instance duration threshold, and marks the number of single instances of duration exceeding the preset single instance duration threshold as high-stop detection values.

[0061] The status detection value GK is obtained by numerically calculating the fault re-inspection value GF, the total temporary operation time value GR, and the high-speed shutdown detection value GN using the formula GK=ry1*GF+ry2*GR / (ry1+ry3)+ry3*GR. Here, ry1, ry2, and ry3 are preset proportional coefficients, and the values ​​of ry1, ry2, and ry3 are all greater than zero. Furthermore, the larger the value of the status detection value GK, the worse the operating status of the corresponding medical equipment is within the detection cycle.

[0062] Example 3: Figure 2 As shown, the difference between this embodiment and Embodiments 1 and 2 is that the cloud platform also includes a medical device environment analysis module. This module analyzes the operating environment of the medical device based on relevant medical device information, obtains environmental detection values, and sends these values ​​to the medical device management and evaluation module. This not only accurately reflects the performance of the environment in which the corresponding medical device operates within the detection period but also provides data support for the analysis process of the medical device management and evaluation module, ensuring the accuracy of its analysis results. The specific analysis process of the medical device environment analysis module is as follows:

[0063] The environment parameters (such as temperature, humidity, etc.) in the environment of the medical device that need to be monitored are acquired, real-time detection data of the corresponding environment parameters are collected, the real-time detection data are compared with the corresponding preset data requirements, if the real-time detection data do not meet the corresponding preset data requirements, it is indicated that the corresponding environment parameters need to be regulated, the corresponding environment parameters are marked as parameters to be regulated; and the deviation value of the real-time detection data of the corresponding parameters to be regulated from the corresponding preset data requirements is marked as a distance detection value to be regulated, and the regulation time length for regulating the corresponding parameters to be regulated and restoring the corresponding parameters to meet the corresponding preset data requirements is collected, and the ratio of the distance detection value to be regulated to the regulation time length is marked as an efficiency measurement value to be regulated;

[0064] All efficiency measurement values to be regulated for the corresponding environment parameters in the detection period are acquired and the mean value is calculated to obtain an efficiency detection value to be regulated, and the number of regulations for the corresponding environment parameters in the detection period is acquired and marked as a frequency detection value to be regulated, and the efficiency detection value to be regulated XF and the frequency detection value to be regulated XK are numerically calculated by the formula XP=b2*XK+(b1+b2) 2 / (b1*XF+0.635) to obtain a regulation condition value to be regulated XP;

[0065] Wherein, b1 and b2 are preset proportion coefficients, the values of b1 and b2 are positive numbers; and the larger the value of the regulation condition value to be regulated XP is, the greater the risk brought by the corresponding environment parameters to the medical device is; the regulation condition value to be regulated is compared with the corresponding preset regulation condition threshold value, if the regulation condition value to be regulated exceeds the corresponding preset regulation condition threshold value, it is indicated that the risk brought by the corresponding environment parameters to the medical device is greater, and the corresponding environment parameters are marked as abnormal condition parameters;

[0066] The number of abnormal condition parameters in the environment of the corresponding medical device in the detection period is acquired and marked as an abnormal condition detection value, the ratio of the regulation condition value to be regulated of the corresponding environment parameters to the corresponding preset regulation condition threshold value is calculated to obtain a regulation detection occupancy value, the regulation detection occupancy values of all environment parameters are mean calculated to obtain a regulation analysis value, and the regulation analysis value with the largest value is marked as a regulation occupancy amplitude;

[0067] The abnormal condition detection value HY, the regulation analysis value HL and the regulation occupancy amplitude HP are numerically calculated by the formula GP=kp1*HY+(kp2*HL+kp3*HP) / 2 to obtain an environment detection value GP; wherein, kp1, kp2 and kp3 are preset proportion coefficients, the values of kp1, kp2 and kp3 are positive numbers; and the larger the value of the environment detection value GP is, the greater the security risks existing in the environment of the corresponding medical device in the detection period is.

[0068] Embodiment four: as Figure 2As shown, the difference between the embodiment and embodiments 1, 2, and 3 is that the cloud platform further comprises a medical equipment supervision analysis module, which analyzes the operation supervision performance of the medical equipment based on the corresponding medical equipment information, obtains a supervision detection value through the analysis, and sends the supervision detection value to the medical equipment management comprehensive evaluation module. Not only can the operation performance condition of the corresponding medical equipment in the detection period be accurately fed back, but also data support can be provided for the analysis process of the medical equipment management comprehensive evaluation module to ensure the accuracy of the analysis result. The specific analysis process of the medical equipment supervision analysis module is as follows:

[0069] After obtaining the operation records of the corresponding medical equipment in the detection period, all operators are obtained based on the operation records, and whether the corresponding operator has the right to operate the corresponding medical equipment is collected. If the corresponding operator does not have the right to operate the corresponding medical equipment, the corresponding operator is marked as an unauthorized person. The operation frequency of all unauthorized persons in the detection period is collected and marked as an unauthorized frequency (i.e. the number of operation processes of all unauthorized persons for the corresponding medical equipment in the detection period), and the number of error operations in the corresponding operation process for the medical equipment is collected. The number of error operations is compared with the preset error operation number threshold value, and the number of operation processes that exceed the preset error operation number is marked as a high failure operation frequency value.

[0070] The error operation number of all operation processes in the detection period is averaged to obtain an operation error value. The unauthorized frequency QX, the high failure operation frequency value QY, and the operation error value QM are calculated by the formula GS=rq1*QX+rq2*QY+rq3*QM to obtain the supervision detection value GS. Wherein, rq1, rq2, and rq3 are preset proportion coefficients, and the values of rq1, rq2, and rq3 are positive numbers. Moreover, the larger the value of the supervision detection value GS is, the worse the operation supervision performance of the corresponding medical equipment in the detection period is, and the more timely operation supervision for the corresponding medical equipment is needed.

[0071] The working principle of the present application: in use, the medical equipment information is sent to the cloud platform for storage through the information acquisition module via the wireless transmission module, in the process of transmitting the medical equipment information to the cloud platform by the wireless transmission module, the transmission stability detection module detects and analyzes the transmission stability of the information transmission process, the transmission security detection module analyzes the transmission security of the transmission network, and the background terminal issues the corresponding early warning when the transmission stability abnormal signal or the transmission security abnormal signal is generated, which can reasonably analyze the transmission speed performance and transmission security of the medical equipment information and timely warning, ensure the safe and stable transmission of the medical equipment information; and the management performance of the corresponding medical equipment in the detection period is analyzed by the medical equipment management comprehensive evaluation module to judge its management difficulty, and the monitoring and supervision of the corresponding medical equipment is strengthened when the equipment difficult management signal is generated, to ensure the safe and stable operation of the corresponding medical equipment, significantly reduce the safety hidden danger of the corresponding medical equipment, prolong the service life of the corresponding medical equipment, and have high intelligent degree.

[0072] The above formulas are dimensionless values calculated, and the formulas are obtained by software simulation of a large amount of data to obtain a formula of the most recent real situation, and the preset parameters in the formula are set by a person skilled in the art according to the actual situation. The preferred embodiments of the application disclosed above are only used to help explain the application. The preferred embodiments do not describe all the details and limit the application to the specific embodiments. Obviously, according to the content of the specification, many modifications and changes can be made. The present application selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is limited by the claims and their entire scope and equivalents.

Claims

1. A cloud-based medical device information transmission monitoring system, characterized in that, It includes a cloud platform, an information collection module, a wireless transmission module, a transmission stability detection module, a transmission security detection module, and a back-end terminal. The information collection module is used to collect medical device information and send it to the cloud platform for storage via the wireless transmission module. Administrators access the cloud platform through the back-end terminal to query and monitor medical device information. During the process of the wireless transmission module transmitting medical device information to the cloud platform, the transmission stability detection module performs transmission stability detection and analysis on the information transmission process, generates a transmission stability qualified signal or a transmission stability abnormal signal through analysis, and sends the transmission stability normal signal or transmission stability abnormal signal to the back-end terminal. The transmission security detection module obtains the network through which the wireless transmission module transmits information and marks it as a transmission network. It performs transmission security analysis on the transmission network to generate a transmission security qualified signal or a transmission security abnormal signal, and sends the transmission security qualified signal or transmission security abnormal signal to the back-end terminal. When the back-end terminal receives the transmission stability abnormal signal or the transmission security abnormal signal, it issues a corresponding warning. The specific analysis process for transmission stability detection and analysis is as follows: During the information transmission process of medical equipment, the real-time transmission speed curve of the medical equipment information transmission process is placed in a rectangular coordinate system located in the first quadrant, and the corresponding rectangular coordinate system is marked as the transmission speed coordinate system, with time as the X-axis and transmission speed as the Y-axis. All peak points and all trough points in all transmission velocity coordinate systems are collected. The variance of the ordinates of all peak points and all trough points is calculated to obtain the peak-trough stability anomaly value. If the peak-trough stability anomaly value exceeds the preset peak-trough stability anomaly threshold, a transmission stability anomaly signal is generated. If the peak-valley stability value does not exceed the preset peak-valley stability threshold, a ray parallel to the X-axis with its endpoint on the Y-axis is drawn in the transmission speed coordinate system, and the drawn ray is marked as the transmission speed detection ray; all closed areas of the real-time transmission speed curve located below the transmission speed detection ray and enclosed by the transmission detection ray are obtained, the area of ​​the corresponding closed area is collected and marked as the closed area inspection value, and the closed area inspection value is compared with the preset closed area inspection threshold. If the closed area inspection value exceeds the preset closed area inspection threshold, the corresponding closed area is marked as the buffer area. The number of buffer areas is obtained and marked as buffer detection value. All closed surface detection values ​​are summed to obtain closed surface condition value. The ratio of peak-valley stability anomaly value to preset peak-valley stability anomaly threshold is marked as peak-valley stability value. Transmission speed anomaly value is obtained by numerically calculating peak-valley stability value, buffer detection value and closed surface condition value. Transmission speed anomaly value is numerically compared with preset transmission speed anomaly threshold. If transmission speed anomaly value exceeds preset transmission speed anomaly threshold, a transmission stability anomaly signal is generated. If the transmission speed anomaly value does not exceed the preset transmission speed anomaly threshold, a transmission stability qualified signal is generated.

2. The cloud-based medical device information transmission monitoring system according to claim 1, characterized in that, The specific analysis process for transmission security analysis is as follows: The number of times the transmission network is attacked per unit time is collected and marked as the attack frequency detection value. The attack duration is calculated by the time difference between the start and end times of each attack. The number of attack durations that exceed the preset attack duration threshold is marked as the attack high frequency value. Furthermore, the network scanning tool is used to scan the transmission network for vulnerabilities, thereby obtaining the security vulnerabilities existing in the transmission network within a unit of time and marking their number as vulnerability frequency detection values. The network repair tool is used to repair the security vulnerabilities, and the time difference between the start time and the completion time of the repair for the corresponding security vulnerability is calculated to obtain the repair duration. The number of repair durations exceeding the preset repair duration threshold is marked as repair high frequency values. The transmission network risk value is obtained by numerically calculating the attack frequency detection value, attack high frequency value, vulnerability frequency detection value, and repair high frequency value. The transmission network risk value is then compared with a preset transmission network risk threshold. If the transmission network risk value exceeds the preset transmission network risk threshold, a transmission security anomaly signal is generated. If the transmission network risk value does not exceed the preset transmission network risk threshold, a transmission security qualified signal is generated.

3. The cloud-based medical device information transmission and monitoring system according to claim 1, characterized in that, The cloud platform includes a medical equipment status analysis module, a medical equipment environment analysis module, a medical equipment supervision and analysis module, and a medical equipment management comprehensive evaluation module. The medical equipment status analysis module analyzes the equipment status of medical equipment based on relevant medical equipment information, obtains status detection values ​​through analysis, and sends the status detection values ​​to the medical equipment management comprehensive evaluation module. The medical equipment environment analysis module analyzes the operating environment of medical equipment based on relevant medical equipment information, obtains environmental monitoring values, and sends these values ​​to the medical equipment management comprehensive evaluation module. The medical equipment supervision analysis module analyzes the operational supervision performance of medical equipment based on relevant medical equipment information, obtains supervision monitoring values, and sends these values ​​to the medical equipment management comprehensive evaluation module. The medical equipment management comprehensive evaluation module compares the status detection value, environmental detection value, and regulatory detection value with the preset status detection threshold, preset environmental detection threshold, and preset regulatory detection threshold respectively. If the status detection value, environmental detection value, or regulatory detection value exceeds the corresponding preset threshold, a signal indicating that the corresponding medical equipment is difficult to manage is generated. If the status detection value, environmental detection value, and regulatory detection value do not exceed the corresponding preset threshold, the status detection value, environmental detection value, and regulatory detection value are numerically calculated to obtain the medical device management inspection value. If the medical device management inspection value exceeds the preset medical device management inspection threshold, a difficult-to-manage signal for the corresponding medical device is generated; if the medical device management inspection value does not exceed the preset medical device management inspection threshold, an easy-to-manage signal for the corresponding medical device is generated, and the difficult-to-manage signal or easy-to-manage signal for the corresponding medical device is sent to the back-end terminal.

4. The cloud-based medical device information transmission and monitoring system according to claim 3, characterized in that, The specific analysis process of the medical equipment status analysis module is as follows: The system collects fault records of the corresponding medical equipment within the testing period, obtains all fault types of the medical equipment based on the fault records, marks the number of occurrences of the corresponding fault type within the testing period as the fault count value, pre-sets a set of preset fault weight values ​​for each fault type, marks the product of the fault count value of the corresponding fault type and the matched preset fault weight value as the initial fault detection value, and marks the sum of the initial fault detection values ​​of all fault types as the fault re-detection value. It also obtains the duration of a single instance of medical equipment being temporarily suspended due to a fault, marks the sum of all single instances of duration within the detection period as the total temporary operation time value, and marks the number of single instances of duration exceeding the preset threshold as the high-stop detection value. The status detection value is obtained by numerically calculating the fault re-detection value, the total temporary operation time value, and the high-stop detection value.

5. The cloud-based medical device information transmission and monitoring system according to claim 3, characterized in that, The specific analysis process of the medical equipment environment analysis module is as follows: The system acquires the environmental parameters that need to be monitored in the environment where the medical device is located, collects real-time detection data of the corresponding environmental parameters, compares the real-time detection data with the corresponding preset data requirements, and marks the corresponding environmental parameter as a parameter that needs to be adjusted if the real-time detection data does not meet the corresponding preset data requirements. The deviation value of the real-time detection data of the corresponding parameter that needs to be adjusted from the corresponding preset data requirements is marked as the adjustment distance test value. The system also collects the adjustment time required to adjust the corresponding parameter that needs to be adjusted and restore it to meet the corresponding preset data requirements, and marks the ratio of the adjustment distance test value to the adjustment time as the adjustment effect test value. The system acquires all required adjustment performance values ​​for the corresponding environmental parameter within the detection period and calculates their average to obtain the required adjustment performance test value. It also acquires the number of adjustments for the corresponding environmental parameter within the detection period and marks them as required adjustment frequency test values. The system calculates the required adjustment performance test value and the required adjustment frequency test value to obtain the required adjustment condition value. The system compares the required adjustment condition value with the corresponding preset required adjustment condition threshold. If the required adjustment condition value exceeds the corresponding preset required adjustment condition threshold, the corresponding environmental parameter is marked as an abnormal condition parameter. The system acquires the number of abnormal parameters in the environment of the corresponding medical equipment within the detection period and marks them as abnormal detection values. It also calculates the ratio of the required detection value of the corresponding environmental parameter to the corresponding preset required detection threshold to obtain the required detection percentage. The system calculates the average of the required detection percentages of all environmental parameters to obtain the required detection analysis value. Finally, it marks the required detection percentage with the largest value as the required detection amplitude value. The system obtains the environmental detection value by numerically calculating the abnormal detection value, the required detection analysis value, and the required detection amplitude value.

6. The cloud-based medical device information transmission monitoring system according to claim 3, characterized in that, The specific analysis process of the medical device regulatory analysis module is as follows: The system acquires operation records for the corresponding medical equipment within the testing period, acquires all operators based on the operation records, collects the number of operations performed by all unauthorized personnel and marks them as unauthorized frequencies, and collects the number of erroneous operations during the corresponding operation process for the medical equipment. The number of operation processes that exceed the preset number of erroneous operations is marked as a high error operation frequency value. The average number of erroneous operations in all operations within the detection period is used to calculate the operation error value. The regulatory detection value is obtained by numerically calculating the unauthorized frequency, high error frequency value, and operation error value.

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