Automatic calibrating device for multi-parameter monitor

Abstract

The invention discloses an automatic calibrating device for a multi-parameter monitor, and relates to the technical field of medical monitoring equipment calibration, and the device comprises an image collection device which is used for collecting a screen image of the monitor and transmitting the screen image to an upper computer; the standard vital sign simulation device is used for simulating a standard vital sign signal under the control of the upper computer and transmitting the standard vital sign signal to the multi-parameter monitor to be verified; the upper computer is used for controlling the standard vital sign simulation device to generate a standard vital sign signal matched with a to-be-verified item, controlling the image acquisition device to acquire a screen image of the monitor, and detecting and identifying waveform parameters; and judging whether the error between the detection value of the multi-parameter monitor and the output value of the standard vital sign simulation device is within a preset range or not. According to the invention, the waveform parameters of the monitor can be efficiently and accurately extracted and analyzed, and the full-automatic operation of the verification process is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of verification of medical monitoring devices, and particularly relates to an automatic verification device for a multi-parameter monitor. Background Art

[0002] A multi-parameter monitor is a monitoring device widely used in clinical practice, providing reliable data and timely and accurate real-time alarms for medical institutions to diagnose, treat patients and provide life support care, etc. If the measured values of the multi-parameter monitor are inaccurate or the alarms are not timely, it will bring great potential hazards to the treatment and even the life safety of patients. Therefore, it is of great significance to carry out metrological verification on it to ensure the accurate and reliable use of the multi-parameter monitor in clinical practice. However, the traditional verification process of the multi-parameter monitor usually relies on manual operations, including setting parameters, observing waveforms, recording data, etc., and there are some problems and challenges. First, due to the large number of verification items and the complex verification process of the multi-parameter monitor, staff need to undergo long-term training; second, when a verification task is completed, if another verification task is to be carried out, the process needs to be repeated; finally, for the interpretation of the verification results, the verification results are mainly obtained by means of visual observation by human eyes and measurement with a steel straightedge, etc., and need to be manually measured and recorded by the verification personnel, and the verification results are easily affected by the subjective factors of the verification personnel. Facing the increasing number of multi-parameter monitors, the use of manual verification will inevitably increase the workload of verification personnel.

[0003] With the development of medical technology, automatic verification devices are increasingly widely used in the field of medical equipment. However, the existing technologies still need to be improved in terms of verification accuracy and verification efficiency. Summary of the Invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, the present invention provides an automatic verification device for a multi-parameter monitor, which can solve all or part of the technical problems mentioned in the background art.

[0005] In one aspect of the present invention, an automatic verification device for a multi-parameter monitor is provided, including: an image acquisition device for acquiring a screen image of the multi-parameter monitor and transmitting the acquired screen image to a host computer; a standard vital sign simulation device for simulating a standard vital sign signal under the control of the host computer and transmitting the simulated standard vital sign signal to the multi-parameter monitor to be verified; a host computer for controlling the standard vital sign simulation device to generate a standard vital sign signal matching the item to be verified, controlling the image acquisition device to acquire the screen image of the multi-parameter monitor, and detecting and identifying waveform parameters in the screen image to determine whether the error between the detected value of the multi-parameter monitor and the output value of the standard vital sign simulation device is within a predetermined range.

[0006] Further, the image acquisition device includes a camera and a fixing bracket, and the camera is detachably connected to the multi-parameter monitor to be calibrated through the fixing bracket.

[0007] Further, the image acquisition device further includes a video capture card, and the video capture card is used to acquire the screen video signal of the multi-parameter monitor and send the screen video signal to the host computer.

[0008] Further, the standard vital sign simulation device includes a standard vital sign signal generator and a vital sign simulator.

[0009] Further, the vital sign simulator includes at least one of a blood oxygen simulation finger, an electrocardiogram lead wire, a respiration simulator, and a blood pressure simulation arm.

[0010] Further, the host computer is further configured to obtain calibration item information before detecting and identifying the waveform parameters in the screen image, perform initial settings on the multi-parameter monitor and the standard vital sign simulation device according to the calibration items, and control the standard vital sign simulation device to output standard vital sign simulation signals.

[0011] Further, the host computer is further configured to generate a calibration certificate file after all calibration items are completed and save all calibration data to a database.

[0012] Further, the initial settings include setting the waveform gain and / or waveform scanning speed of the multi-parameter monitor, and setting the simulation type of the standard vital sign simulation device.

[0013] Further, the host computer is further configured to generate operation instructions for simulating a mouse and / or a keyboard according to the calibration items to control the operations of the multi-parameter monitor and the standard vital sign simulation device.

[0014] Further, the host computer is further configured to extract waveform images and numerical images in the screen image through the YOLOv11 network integrated with the BiFPN module; wherein, the BiFPN module is arranged before each C3k2 module in the neck network of YOLOv11; identify the pixel difference of the average amplitude of the waveform signal and the pixel difference of the average period width of the waveform signal in the waveform image, and calculate the actual values of the waveform amplitude and waveform wavelength according to the unit pixel size, the pixel difference of the average amplitude of the waveform signal, and the pixel difference of the average amplitude of the waveform signal; identify the numerical values in the numerical image through the OCR model; compare the recognition results of the waveform image and the numerical image with the output values of the standard vital sign simulation device to determine whether the error between the two is within a predetermined range.

[0015] Further, the host computer is further configured to detect all the feature points of the rising edge and the falling edge of the square wave signal, obtain the ordinate values of all the feature points, sort them according to the ordinate size, and screen out the upper inflection point of the rising edge, the lower inflection point of the rising edge, the upper inflection point of the falling edge, and the lower inflection point of the falling edge from the ordinate values of the feature points according to a preset threshold; and, detect all the feature points of the rising edge and the falling edge of the sine wave signal, obtain the ordinate values of all the feature points, sort them according to the ordinate size, and screen out the peak point and the valley point from the ordinate values of the feature points.

[0016] Further, the host computer is further configured to calculate the pixel difference of the average amplitude of the square wave signal according to the following formula : where p represents the number of upper inflection points of the rising edge, q represents the number of lower inflection points of the rising edge, represents the ordinate value of the i-th upper inflection point of the rising edge, represents the ordinate value of the i-th lower inflection point of the rising edge; or, p represents the number of upper inflection points of the falling edge, q represents the number of lower inflection points of the falling edge, represents the ordinate value of the i-th upper inflection point of the falling edge, represents the ordinate value of the i-th lower inflection point of the falling edge.

[0017] Further, the host computer is further configured to calculate the pixel difference of the average amplitude of the sine wave signal according to the following formula : where p represents the number of peak points, q represents the number of valley points, represents the ordinate value of the i-th peak point, represents the ordinate value of the i-th valley point.

[0018] Further, when the scanning speed of the square wave signal is lower than the preset threshold, the host computer is further configured to calculate the pixel difference of the average period width of the waveform signal according to the following formula : where, represents the total number of upper inflection points of the rising edge in the square wave signal, represents the abscissa value of the (i + 4)-th upper inflection point of the rising edge, represents the abscissa value of the i-th upper inflection point of the rising edge; or, represents the total number of upper inflection points of the falling edge in the square wave signal, represents the abscissa value of the (i + 4)-th upper inflection point of the falling edge, represents the abscissa value of the i-th upper inflection point of the falling edge; When the scanning speed of the square wave signal is higher than the preset threshold, calculate the pixel difference of the average period width of the square wave signal according to the following formula : where represents the total number of upper inflection points of the rising edge in the square wave signal, represents the abscissa value of the (i + 2)-th upper inflection point of the rising edge, represents the abscissa value of the i-th upper inflection point of the rising edge; or represents the total number of upper inflection points of the falling edge in the square wave signal, represents the abscissa value of the (i + 2)-th upper inflection point of the falling edge, represents the abscissa value of the i-th upper inflection point of the falling edge.

[0019] Furthermore, when the scanning speed of the sine wave signal is lower than the preset threshold, the host computer is further configured to calculate the pixel difference of the average period width of the sine wave signal according to the following formula : where represents the total number of peak points of the sine wave signal, represents the abscissa value of the (i + 4)-th peak point, represents the abscissa value of the i-th peak point; or represents the total number of valley points of the sine wave signal, represents the abscissa value of the (i + 4)-th valley point, represents the abscissa value of the i-th valley point; When the scanning speed of the sine wave signal is higher than the preset threshold, calculate the pixel difference of the average period width of the sine wave signal according to the following formula : where represents the total number of peak points of the sine wave signal, represents the abscissa value of the (i + 2)-th peak point, represents the abscissa value of the i-th peak point; or represents the total number of valley points of the sine wave signal, represents the abscissa value of the (i + 2)-th valley point, represents the abscissa value of the i-th valley point.

[0020] Further, the host computer is further configured to obtain polygon information of the text area using a text detection algorithm; crop, perform perspective transformation and perspective correction on the text area, convert the text area after perspective correction into a rectangular box, and correct the text direction within the rectangular box using a direction classifier; and recognize the text within the rectangular box to obtain the recognition result of the numerical image.

[0021] The multi-parameter monitor automatic calibration device provided by the present invention has the following beneficial effects: (1) By using a detachable camera and a video capture card to obtain the screen image of the monitor, and obtaining the measurement result through image recognition, the defects of unstable communication and complex protocol adaptation brought by obtaining monitoring parameters through the communication protocol adaptation method in the prior art are avoided.

[0022] (2) By adopting an original image waveform parameter detection algorithm, it can efficiently and accurately extract and analyze the waveform parameters of the monitor.

[0023] (3) By using an automatic operation control to simulate the operations of a mouse and a keyboard, and automatically controlling the monitor and the vital sign simulation device, no additional mechanical control device is required throughout the process, thereby realizing the automation of all links in the multi-parameter monitor calibration process. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] By reading the detailed description of the non-restrictive embodiments with reference to the following drawings, other features, objects, and advantages of the present application will become more apparent: Figure 1 is the system structure diagram of the multi-parameter monitor automatic calibration device provided by an embodiment of the present application; Figure 2 is the schematic diagram of the waveform parameter detection function module of the multi-parameter monitor automatic calibration device provided by an embodiment of the present application; Figure 3 is the schematic diagram of the screen image of the multi-parameter monitor provided by an embodiment of the present application; Figure 4 is the structure schematic diagram of the target detection network provided by an embodiment of the present application; Figure 5 is the schematic diagram of the square wave signal detection result provided by an embodiment of the present application; Figure 6 is the schematic diagram of the detection result of the sine wave signal provided by an embodiment of the present application; Figure 7 is the calibration flow chart of the multi-parameter monitor automatic calibration device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0026] The terms used in the embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention are also intended to include the plural forms unless the context clearly indicates otherwise.

[0027] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present invention to describe the acquisition modules, these acquisition modules should not be limited to these terms. These terms are only used to distinguish the acquisition modules from each other.

[0028] Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detected (stated condition or event)" or "in response to detecting (stated condition or event)".

[0029] It should be noted that the orientation terms such as "upper", "lower", "left", "right", etc. described in the embodiments of the present invention are described from the angles shown in the accompanying drawings and should not be construed as limiting the embodiments of the present invention. In addition, in the context, it should also be understood that when it is mentioned that an element is formed "on" or "under" another element, it can not only be directly formed "on" or "under" another element, but also be indirectly formed "on" or "under" another element through an intermediate element.

[0030] See Figure 1, an embodiment of the present application provides a multi-parameter monitor automatic calibration device 100, including an image acquisition device 101, a standard vital sign simulation device 102, and a host computer 103. Among them, the image acquisition device 101 is used to acquire the screen image of the multi-parameter monitor 104 and transmit the acquired screen image to the host computer 103. The standard vital sign simulation device 102 is used to simulate standard vital sign signals under the control of the host computer 103 and transmit the simulated standard vital sign signals to the multi-parameter monitor 104 to be calibrated. The host computer 103 is used to control the standard vital sign simulation device 102 to generate standard vital sign signals matching the items to be calibrated, and control the image acquisition device 101 to acquire the screen image of the multi-parameter monitor 104, detect and identify the waveform parameters in the screen image, so as to judge whether the error between the detected value of the multi-parameter monitor 104 and the output value of the standard vital sign simulation device 102 is within a predetermined range.

[0031] Furthermore, for multi-parameter monitors without a video output interface, it is preferably to use a camera to capture the screen image. The image acquisition device 101 includes a camera and a fixing bracket. The camera is detachably connected to the multi-parameter monitor to be calibrated through the fixing bracket. Preferably, the fixing bracket includes a camera fixing arm and a bayonet arm. One end of the fixing arm is connected to the camera, and the other end is arranged on the bayonet arm. The bayonet of the bayonet arm is connected by a spring to adapt to different sizes of monitor bayonet positions. The camera fixing arm is used to ensure that the distance between the camera and the monitor screen is fixed, so that the captured screen image is clear and complete.

[0032] Furthermore, for the multi-parameter monitor 104 with a video output interface, a video capture card can be used to collect the monitor video signal, send the video data to the host computer 103, and then extract the screen image from the video data. The video capture card model in this embodiment is TC-5A0N1, which uses a mini-PCIe interface, is small in size and can be built into the host computer. The highest acquisition resolution can reach 1920×1080, and the refresh rate is 60fps. This video capture card collects digital video signals and analog video signals, and has HDMI and VGA inputs, meeting the acquisition requirements of most monitor video signals. For some multi-parameter monitors with a DVI video output interface, a conversion plug can be used to achieve lossless conversion from DVI to HDMI.

[0033] Further, the standard vital sign simulation device 102 includes a standard vital sign signal generator and a vital sign simulator. Among them, the vital sign simulator includes at least one of a blood oxygen simulation finger, an electrocardiogram lead wire, a respiration simulator, and a blood pressure simulation arm. The standard vital sign signal generator is connected to the multi-parameter monitor 104 through the blood oxygen simulation finger, the electrocardiogram lead wire, the respiration simulator, and / or the blood pressure simulation arm, so that the multi-parameter monitor 104 can obtain the simulated standard vital sign signals in real time.

[0034] Further, before detecting and identifying the waveform parameters in the screen image, the host computer 103 first obtains the information of the verification items to be tested, initializes the multi-parameter monitor 104 and the standard vital sign simulation device 102 according to the verification items, and controls the standard vital sign simulation device 102 to output standard vital sign simulation signals. Specifically, the host computer 103 generates operation instructions for simulating a mouse and / or a keyboard, and controls the operations of the multi-parameter monitor 104 and the standard vital sign simulation device 102 through the operation instructions. For example, the waveform gain and / or waveform scanning speed of the multi-parameter monitor 104 are set, and the simulation type of the standard vital sign simulation device 102 is set, etc. Since the operations of the monitor and the standard vital sign simulation device are through the operation instructions for simulating a mouse and / or a keyboard, the host computer can edit different types of control instructions for different models of instruments, so that different parameters of different models of monitors can be set without external mechanical operation devices such as a mouse and a keyboard, thereby realizing the automation of all links in the verification process of the multi-parameter monitor.

[0035] See Figure 2 , in order to achieve efficient and accurate extraction and analysis of the waveform parameters of the monitor screen image in Figure 3 , the host computer 103 of the present invention is further configured to include the following functional modules.

[0036] The first module is used to extract the waveform image and the numerical image in the monitor screen image through the YOLOv11 network integrated with the BiFPN module; wherein, the BiFPN module is arranged before each C3k2 module in the neck network of YOLOv11.

[0037] See Figure 4 , in this embodiment, the network architecture of YOLOv11+BiFPN is selected as the improved object detection network. The improved object detection network includes a backbone network, a neck network, and a detection head.

[0038] Among them, the main task of the backbone network is to extract multi-dimensional features from the input monitor screen image and generate a high-dimensional feature map.

[0039] Among them, the neck network is located between the backbone network and the detection head. Its main function is to further enhance the features extracted by the backbone network and provide richer and more suitable features for the detection head for the object detection task. In this embodiment, a BiFPN module is introduced before each C3k2 module in the YOLOv11 neck network. On the one hand, the multi-scale feature fusion of the BiFPN module can more effectively improve the global nature of feature expression, making the subsequent C3K2 module more efficient in extracting features. On the other hand, by optimizing the feature map in advance through the BiFPN module, the processing burden of the C3K2 module can be reduced, thereby improving the overall robustness of the network. On the other hand, the BiFPN module set before the C3K2 module can also better fuse the detailed features of small targets and improve the detection performance of small targets. Finally, the BiFPN module fuses multi-dimensional features and uses its efficient weighted feature convergence to input the enhanced feature map into the subsequent detection head for accurate object localization and classification, which can achieve enhanced box selection for various types in the classification label parameters, extract and return the color and position coordinates, and at the same time divide the trend parameters into waveform parameters and numerical parameters for further processing.

[0040] Among them, the detection head is the last part of the object detection network, directly responsible for generating the final detection results, including the category and position of the object, enabling the features targeted at image classification extracted from the backbone network to be effectively transformed into features suitable for object detection, and further enhancing the network's performance in dealing with complex scenes and diverse objects.

[0041] Finally, the improved object detection network is used to extract the waveform image and numerical image in the monitor screen image.

[0042] The second module is used to identify the pixel difference of the average amplitude of the waveform signal and the pixel difference of the average period width of the waveform signal in the waveform image, and calculate the actual values of the waveform amplitude and waveform wavelength according to the unit pixel size, the pixel difference of the average amplitude of the waveform signal, and the pixel difference of the average amplitude of the waveform signal. Specifically, the second module identifies the waveform amplitude and waveform wavelength of the square wave signal and sine wave signal in the obtained waveform image. The following details the extraction steps of the amplitude and wavelength of various waveform signals in this embodiment.

[0043] (1) Inflection point detection See Figure 5, the Harris corner detection algorithm is used to detect all the feature points of the rising edge and falling edge of the square wave signal in the waveform image, obtain the ordinate values of all the feature points, sort them according to the ordinate size, and screen out four types of inflection points, namely, the upper inflection point of the rising edge (type A), the lower inflection point of the rising edge (type B), the upper inflection point of the falling edge (type C), and the lower inflection point of the falling edge (type D) from the ordinate values of the feature points. Among them, the preset screening threshold can filter out the points with lower response values and only retain the feature points that may be real inflection points.

[0044] See Figure 6 , using a method similar to that for detecting the square wave signal, the Harris corner detection algorithm is used to detect all the feature points of the rising edge and falling edge of the sine wave signal in the waveform image (the inflection point of the rising edge of the sine wave signal is also the inflection point of the falling edge), obtain the ordinate values of all the feature points, sort them according to the ordinate size, and screen out the peak points and valley points from the ordinate values of the feature points.

[0045] (2) Pixel difference of the average amplitude of the waveform Calculate the pixel difference of the average amplitude of the square wave signal according to the following formula : Among them, p represents the number of upper inflection points of the rising edge, q represents the number of lower inflection points of the rising edge, represents the ordinate value of the i-th upper inflection point of the rising edge, represents the ordinate value of the i-th lower inflection point of the rising edge; or, p represents the number of upper inflection points of the falling edge, q represents the number of lower inflection points of the falling edge, represents the ordinate value of the i-th upper inflection point of the falling edge, represents the ordinate value of the i-th lower inflection point of the falling edge. That is to say, the effect of calculating with two inflection points of the rising edge of the square wave and calculating with two inflection points of the falling edge of the square wave is the same.

[0046] Calculate the pixel difference of the average amplitude of the sine wave signal according to the following formula : Among them, p represents the number of peak points, q represents the number of valley points, represents the ordinate value of the i-th peak point, represents the ordinate value of the i-th valley point.

[0047] (3) Pixel difference of the average period width of the waveform The waveforms on the monitor have a certain scanning speed, which represents the moving speed of the waveforms on the screen. For example: 25 mm / s, 50 mm / s, etc. For a scanning speed of 25 mm / s, the horizontal compression of the waveform signal is less, and a longer cycle distance (such as four cycles from A0 to A4) can be selected to calculate the cycle width; for a scanning speed of 50 mm / s, the waveform signal is horizontally compressed more, and a long cycle distance will increase the error. Therefore, a shorter cycle distance (such as two cycles from A0 to A2) is selected to calculate the cycle width, which is more suitable for the current scanning speed. In summary, the technical solution can also be summarized as: when the scanning speed is greater than the preset threshold, a shorter cycle distance is selected to calculate the cycle width; when the scanning speed is less than the preset threshold, a longer cycle distance is selected to calculate the cycle width. Among them, the preset threshold and the cycle distance can be determined according to experience and the actual scanning speed.

[0048] Specifically: When the scanning speed of the square wave signal is lower than the preset threshold, calculate the pixel difference of the average cycle width of the waveform signal according to the following formula : Among them, represents the total number of upper inflection points of the rising edge in the square wave signal, represents the abscissa value of the (i + 4)-th upper inflection point of the rising edge, represents the abscissa value of the i-th upper inflection point of the rising edge; or, represents the total number of upper inflection points of the falling edge in the square wave signal, represents the abscissa value of the (i + 4)-th upper inflection point of the falling edge, represents the abscissa value of the i-th upper inflection point of the falling edge. That is to say, the effect of calculating with the inflection points of the rising edge of the square wave and calculating with the inflection points of the falling edge of the square wave is the same.

[0049] When the scanning speed of the square wave signal is higher than the preset threshold, calculate the pixel difference of the average cycle width of the square wave signal according to the following formula : Among them, represents the total number of upper inflection points of the rising edge in the square wave signal, represents the abscissa value of the (i + 2)-th upper inflection point of the rising edge, represents the abscissa value of the i-th upper inflection point of the rising edge; or, represents the total number of upper inflection points of the falling edge in the square wave signal, represents the abscissa value of the (i + 2)-th upper inflection point of the falling edge, represents the abscissa value of the upper inflection point of the i-th falling edge; that is to say, the calculation effect using the inflection point of the rising edge of the square wave and the calculation effect using the inflection point of the falling edge of the square wave are the same.

[0050] When the scanning speed of the sine wave signal is lower than the preset threshold, calculate the pixel difference of the average period width of the sine wave signal according to the following formula : where represents the total number of peak points of the sine wave signal, represents the abscissa value of the (i + 4)-th peak point, represents the abscissa value of the i-th peak point; or represents the total number of valley points of the sine wave signal, represents the abscissa value of the (i + 4)-th valley point, represents the abscissa value of the i-th valley point; that is to say, the calculation effect using the peak points of the sine wave and the calculation effect using the valley points of the sine wave are the same.

[0051] When the scanning speed of the sine wave signal is higher than the preset threshold, calculate the pixel difference of the average period width of the sine wave signal according to the following formula : where represents the total number of peak points of the sine wave signal, represents the abscissa value of the (i + 2)-th peak point, represents the abscissa value of the i-th peak point; or represents the total number of valley points in the sine wave signal, represents the abscissa value of the (i + 2)-th valley point, represents the abscissa value of the i-th valley point; that is to say, the calculation effect using the peak points of the sine wave and the calculation effect using the valley points of the sine wave are the same.

[0052] (4) Actual value calculation Calculate the actual values of the waveform amplitude and the waveform wavelength based on the unit pixel size, the pixel difference of the average amplitude of the waveform signal, and the pixel difference of the average amplitude of the waveform signal.

[0053] The third module is used to recognize the numerical values in the numerical image through the OCR model.

[0054] Specifically, the OCR text detection and recognition model is a technology based on image processing and machine learning, which is used to extract text information from images. In this embodiment, the OCR system is divided into three parts: text detection, text recognition, and direction classifier. First, use the text detection algorithm to obtain the polygon information of the text area; then, crop, perform perspective transformation and perspective correction on the text area, convert the text area after perspective correction into a rectangular box, and use the direction classifier to correct the text direction within the rectangular box; finally, recognize the text within the rectangular box to obtain the recognition result of the numerical image. Preferably, a segmentation-based text detection algorithm and a CRNN text recognition algorithm are adopted.

[0055] The fourth module is used to compare the recognition results of the waveform image and the numerical image with the output value of the standard vital sign simulation device to determine whether the error between the two is within a predetermined range.

[0056] Specifically, after accurately identifying the waveform parameter values in the screen image, compare the recognition results with the output value of the standard vital sign simulation device to determine whether the error between the two is within a predetermined range. If the error is within the predetermined range, the verification item of the multi-parameter monitor passes the test. If the error is outside the predetermined range, the verification item of the multi-parameter monitor fails the test. The host computer saves each verification result to the database and automatically performs the test of the next verification item until all verification items are completed.

[0057] Furthermore, the host computer is also used to generate a verification certificate file after all verification items are completed.

[0058] Specifically, after all verification items are completed, the report module in the host computer compares the results with the standard values, determines whether they are qualified, and issues an electronic verification certificate, which is saved in the form of a PDF file to the host computer, and the verification certificate supports online preview.

[0059] See Figure 7 , the verification process of the multi-parameter monitor automatic verification device of the present invention is as follows: Step S101, after the verification starts, log in to the multi-parameter monitor automatic verification device through the login interface of the host computer, and select the verification item and fill in the basic information through the basic information filling interface; Step S102, set the monitor parameters and the parameters of the standard vital sign simulation device according to the selected verification item; Step S103: The standard vital sign simulation device outputs corresponding analog signals to the multi-parameter monitor, and the multi-parameter monitor starts the verification; Step S104: After waiting for the verification result of the monitor to stabilize, the image acquisition device acquires the real-time screen image of the multi-parameter monitor and uploads it to the host computer; Step S105: The image capture and parameter recognition module of the host computer starts to capture the screen of the monitor and interpret it. By judging whether the recognition result and the standard value are within the error range, it is determined whether the current verification item passes. Repeat this operation until all verification items are completed; Step S106: When all verification items are completed, the reporting module compares the results with the standard values, judges whether it is qualified and issues a verification certificate, which is stored and displayed in the host computer in the form of a PDF file. The verification certificate supports online preview, and at the same time, the verification data information is saved to the database.

[0060] The embodiment of the present invention uses a detachable camera and a video capture card to obtain the screen image of the monitor, and obtains the measurement result through image recognition, thus avoiding the defects of unstable communication and complex protocol adaptation brought by obtaining monitoring parameters through the communication protocol adaptation method in the prior art; adopting an original image waveform parameter detection algorithm, it can efficiently and accurately extract and analyze the waveform parameters of the monitor; using an automatic operation control to simulate the operations of the mouse and keyboard, automatically controlling the monitor and the vital sign simulation device, and no additional mechanical control device is required throughout the process, thereby realizing the automation of all links in the verification process of the multi-parameter monitor.

[0061] The above description is only the preferred embodiment of the present invention. Those skilled in the art should understand that the disclosed scope of the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the technical solutions formed by mutually replacing the above features with the (but not limited to) technical features with similar functions disclosed in the present invention.

Claims

1. An automatic calibration device for a multi-parameter monitor, characterized in that: include: An image acquisition device, used to acquire screen images of the multi-parameter monitor and transmit the acquired screen images to a host computer; A standard vital sign simulation device, used to simulate standard vital sign signals under the control of a host computer, and transmit the simulated standard vital sign signals to a multi-parameter monitor to be tested; The host computer is used to control the standard vital sign simulation device to generate a standard vital sign signal matching the item to be tested, and to control the image acquisition device to acquire the screen image of the multi-parameter monitor, and to detect and identify the waveform parameters in the screen image to determine whether the error between the detection value of the multi-parameter monitor and the output value of the standard vital sign simulation device is within a predetermined range.

2. The multi-parameter monitor automatic calibration device according to claim 1, characterized in that: The image acquisition device comprises a camera and a fixing frame, and the camera is detachably connected to the multi-parameter monitor to be tested via the fixing frame.

3. The multi-parameter monitor automatic calibration device according to claim 2, characterized in that: The image acquisition device also includes a video acquisition card, which is used to acquire the screen video signal of the multi-parameter monitor and send the screen video signal to the host computer.

4. The multi-parameter monitor automatic calibration device according to claim 1, characterized in that: The standard vital sign simulation device comprises a standard vital sign signal generator and a vital sign simulator.

5. The multi-parameter monitor automatic calibration device according to claim 4, characterized in that: The vital sign simulator includes at least one of a blood oxygen simulation finger, an electrocardiogram lead wire, a breathing simulator and a blood pressure simulation arm.

6. The multi-parameter monitor automatic calibration device according to claim 1, characterized in that: The host computer is also used to obtain verification item information, perform initial settings on the multi-parameter monitor and the standard vital sign simulation device according to the verification items, and control the standard vital sign simulation device to output a standard vital sign simulation signal.

7. The multi-parameter monitor automatic calibration device according to claim 6, characterized in that: The host computer is also used to generate a verification certificate file after all verification items are completed, and save all verification data to a database.

8. The multi-parameter monitor automatic calibration device according to claim 6, characterized in that: The initial settings include setting the waveform gain and / or waveform scanning speed of the multi-parameter monitor, and setting the simulation type of the standard vital sign simulation device.

9. The multi-parameter monitor automatic calibration device according to claim 6, characterized in that: The host computer is also used to generate operation instructions for simulating a mouse and / or keyboard according to the verification items to control the operation of the multi-parameter monitor and the standard vital sign simulation device.

10. The multi-parameter monitor automatic calibration device according to claim 1, characterized in that: The host computer is also used to extract a waveform image and a numerical image in a screen image through a YOLOv11 network integrated with a BiFPN module; wherein the BiFPN module is arranged before each C3k2 module of the neck network of YOLOv11; identify the pixel difference of the average amplitude of the waveform signal and the pixel difference of the average cycle width of the waveform signal in the waveform image, and calculate the actual values ​​of the waveform amplitude and the waveform wavelength according to the unit pixel size, the pixel difference of the average amplitude of the waveform signal and the pixel difference of the average amplitude of the waveform signal; identify the numerical value in the numerical image through an OCR model; compare the recognition results of the waveform image and the numerical image with the output value of the standard vital sign simulation device to determine whether the error between the two is within a predetermined range.

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