Operation kit circulation full-closed-loop management method

Abstract

The invention provides a full-closed-loop management method for operation kit circulation. The full-closed-loop management method comprises the steps that monitoring data and position information of operation kit circulation are obtained by setting monitoring points in a preset operation area; according to the method, firstly, matched circulation position information is obtained in response to circulation monitoring data, the position deviation value of operation kit circulation operation and a monitoring point is calculated, the occurrence position of the circulation operation is determined, and whether operation kit equipment exists in a preset range of the position or not is judged; if yes, further judging whether the sterile identifier receives a circulation operation or not; if not, obtaining the visual identifier through a position area recognition algorithm, and judging whether the visual identifier is in contact with the operation kit equipment or not. If so, generating an error signal and a manual inspection request and sending the error signal and the manual inspection request to an external receiving end. The operation kit circulation safety and efficiency can be improved, the operation infection risk is reduced, human errors are reduced, and the overall management level of an operating room is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical equipment management, and more particularly, to a surgical package flow whole closed loop management method. BACKGROUND

[0002] In the operating room environment, the management of surgical packages is of great importance, as it is directly related to the safety and efficiency of surgery. The traditional surgical package management method mainly relies on manual recording and checking, which is not only inefficient, but also prone to human errors, such as incorrect handling, incorrect placement, or omission of surgical packages. In addition, the flow process of surgical packages lacks real-time monitoring, and once a problem occurs, it is difficult to quickly locate and solve it. With the development of medical technology, although some electronic tags and scanning technologies have been introduced to assist in management, these technologies mostly only achieve simple tracking of surgical packages, and cannot comprehensively and real-time monitor and analyze the flow process, especially in the accurate judgment of the sterile state and flow location of surgical packages.

[0003] There are at least the following problems or defects in the prior art: first, the whole closed loop management of surgical package flow cannot be achieved, i.e., the entire process from preparation, use to recovery of surgical packages lacks coherence and integrity, and management loopholes are easily created; second, there is a lack of accurate positioning and real-time monitoring of the flow location of surgical packages, which makes it impossible to accurately determine whether the surgical package is in the correct flow location, increasing the risk of surgical infection; third, the sterile identification state of the surgical package cannot be effectively identified, and once the sterile state of the surgical package is destroyed, it is difficult to discover and take measures in time, seriously affecting the safety of surgery; fourth, the existing technology has deficiencies in the abnormal judgment of surgical package flow operation, and cannot timely discover and handle the incorrect operation in the flow process of surgical packages, which may lead to incorrect use or handling of surgical packages. SUMMARY

[0004] The present application provides a surgical package flow whole closed loop management method, the surgical package flow includes a plurality of surgical package devices located in the same preset surgical area, a monitoring point is arranged in the preset surgical area, and the monitoring point is used to acquire flow monitoring data and flow location information of the surgical package flow in the preset surgical area, characterized in that the method comprises:

[0005] In response to the flow monitoring data, the flow location information matched with the flow monitoring data is acquired;

[0006] The position deviation value of the surgical package flow operation and the monitoring point is calculated through the time difference between the flow monitoring data and the flow location information;

[0007] The occurrence position of the surgical package flow operation is acquired based on the monitoring point;

[0008] Determining whether there is a surgical kit device within a preset range of the occurrence location;

[0009] If so, determining whether the sterility mark within the preset range has received the surgical kit flow operation;

[0010] If not, obtaining a visual identifier based on the surgical kit equipment in the flow monitoring data through a location area recognition algorithm;

[0011] determining whether the visual marker is in contact with the surgical kit device;

[0012] If contact is made, an error signal and a manual inspection request are generated and sent to the external receiving end.

[0013] Furthermore, in response to the flow monitoring data, obtaining flow location information that matches the flow monitoring data includes:

[0014] Continuously recording the flow monitoring data and flow location information of the preset surgical area;

[0015] acquiring, through the monitoring point, a signal strength value of the flow monitoring data and a position strength value of the flow position information based on a preset time interval;

[0016] The first rectangular coordinate system is generated with natural time as the horizontal axis and signal strength and position strength as the vertical axis;

[0017] Outputting the signal strength values ​​and the position strength values ​​in the first rectangular coordinate system, and sequentially connecting them to form a signal strength curve and a position strength curve;

[0018] Determine whether the difference between the current signal strength value and the previous signal strength value is greater than or equal to a preset threshold;

[0019] If it is greater than or equal to, it is determined that the surgical package transfer operation occurs;

[0020] Obtaining the maximum value closest to the current moment in the signal strength curve, and marking it as the flow monitoring data;

[0021] From the natural time corresponding to the flow monitoring data, the maximum value of the position intensity value closest to the flow monitoring data is obtained and marked as the flow position information.

[0022] Furthermore, after outputting the signal strength value and the position strength value in the first rectangular coordinate system, the method further includes:

[0023] The first rectangular coordinate system, the signal strength curve, and the position strength curve are sent to an external visualization terminal.

[0024] Further, the operation of acquiring the occurrence position of the operation of the surgical kit based on the monitoring point comprises:

[0025] At least three monitoring points are defined at different positions of the preset surgical area;

[0026] A second rectangular coordinate system is established with one of the monitoring points as the origin, the east direction as the horizontal axis, and the north direction as the vertical axis;

[0027] The remaining monitoring points are positioned in the second rectangular coordinate system;

[0028] The positional deviation values of each monitoring point from the same operation of the surgical kit are calculated respectively;

[0029] Circular regions are generated with each monitoring point as the center and the corresponding positional deviation value as the radius;

[0030] The intersection point of all circular regions is obtained as the occurrence position.

[0031] Further, after obtaining the occurrence position, further comprising:

[0032] The second rectangular coordinate system, all monitoring points, and the occurrence position are sent to an external visualization terminal.

[0033] Further, the operation of acquiring the visual identifier of the surgical kit device in the flow monitoring data based on the position region recognition algorithm comprises:

[0034] The flow monitoring data is divided into a plurality of grids based on grid units of a preset size;

[0035] A preset number of first position regions are predicted based on each grid, and each first position region contains at least one grid;

[0036] The confidence of each first position region is obtained by defining that the surgical kit device has the highest confidence;

[0037] The first position region with the highest confidence is selected as the second position region;

[0038] The intersection-union ratio of the second position region and each first position region is calculated;

[0039] The second position region with an intersection-union ratio greater than or equal to a preset threshold is retained as the third position region;

[0040] The third position region with the highest confidence is selected as the fourth position region;

[0041] The union set of all fourth position regions is obtained as the final position region of the surgical kit device;

[0042] The surgical kit device identification pattern in the final position region is extracted as the visual identifier.

[0043] Further, the method further comprises:

[0044] If the receiving is received, marking the operation as a safe operation;

[0045] Obtaining the time of the safe operation and the number of the corresponding sterile mark, and generating a record;

[0046] Sending the record to an external storage end.

[0047] Further, the method further comprises:

[0048] If the receiving is not received, marking the operation as an uncontacted operation;

[0049] Obtaining the location of the uncontacted operation and the number of the corresponding monitoring point, and generating an isolation instruction;

[0050] Sending the isolation instruction to an external execution end.

[0051] Further, the method further comprises:

[0052] Obtaining the type code and severity value of the error signal;

[0053] Generating a to-be-processed queue based on the manual inspection request;

[0054] Packing the error signal and the manual inspection request according to a preset communication protocol;

[0055] Sending to an external receiving end.

[0056] Further, the method further comprises:

[0057] Defining a time difference between the monitoring signal and the location signal;

[0058] Calculating an absolute value of the time difference;

[0059] Calculating a location deviation value based on the time difference and the absolute value;

[0060] Outputting the location deviation value to a location judgment module.

[0061] According to the above embodiments of the present application, at least the following advantages are achieved:

[0062] 1. The monitoring data and location information of the operation package circulation are obtained by monitoring points, and the position deviation value is calculated by combining the time difference, so that the circulation position of the operation package can be accurately located, the problem that the circulation position of the operation package cannot be accurately judged in the prior art is solved, the controllability and safety of the operation package circulation process are improved, and the risk of surgical infection caused by position errors is reduced.

[0063] 2. Based on the monitoring points and the position area recognition algorithm, the operation package equipment and its visible identification can be accurately identified, the problem that the sterile identification state of the operation package cannot be effectively identified in the prior art is solved, the sterile state of the operation package in the circulation process is ensured to be monitored in real time, and the safety guarantee of the operation process is enhanced.

[0064] 3. An error signal and a manual inspection request are generated and sent to an external receiving end, so that the operation package circulation operation exception can be discovered and processed in time, the problem of insufficient operation package circulation exception judgment in the prior art is solved, the efficiency and reliability of the operation package circulation management are improved, and the operation risk caused by abnormal operation is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0065] The above and other objects, features and advantages of the exemplary embodiments of the present application will be more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which:

[0066] Figure 1 A flowchart of the operation package circulation full-closed-loop management method provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0067] The technical solutions in the present application will be described in detail below with reference to the drawings in the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. The components of the present application described and shown in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of 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. It should be noted that: similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0068] The application provides a surgical kit circulation full-closed loop management method, the surgical kit circulation includes a plurality of surgical kit devices in a same preset surgical area, a monitoring point is arranged in the preset surgical area, the monitoring point is used for acquiring circulation monitoring data and circulation position information when the surgical kit circulates in the preset surgical area, and the method comprises the following steps:

[0069] S1, in response to the circulation monitoring data, acquiring circulation position information matched with the circulation monitoring data;

[0070] S2, calculating a position deviation value of the surgical kit circulation operation and the monitoring point through a time difference between the circulation monitoring data and the circulation position information;

[0071] S3, acquiring an occurrence position of the surgical kit circulation operation based on the monitoring point; and judging whether there is a surgical kit device in a preset range of the occurrence position;

[0072] S4, if yes, judging whether a sterile mark in the preset range receives the surgical kit circulation operation;

[0073] S5, if not, acquiring a visual mark based on the surgical kit device in the circulation monitoring data through a position area recognition algorithm;

[0074] S6, judging whether the visual mark is in contact with the surgical kit device;

[0075] S7, if yes, generating an error signal and a manual inspection request and sending them to an external receiving end.

[0076] The flow monitoring data refers to dynamic information collected by the monitoring points during the flow of the surgical kit. Specifically, it can be achieved by using radio frequency identification technology or infrared sensors to obtain real-time surgical kit movement trajectory data, which is used to track the real-time state of the surgical kit in the preset surgical area. The flow location information refers to spatial coordinate data corresponding to the monitoring data, which can be achieved by using Bluetooth beacon positioning or UWB ultra-wideband positioning technology, and is used to accurately mark the position of the surgical kit in three-dimensional space. The position deviation value refers to the spatial displacement converted from the time difference between the monitoring data and the location information, which can be achieved by using time stamp comparison combined with signal propagation speed calculation, and is used to identify positioning errors caused by operation delay or device displacement. The occurrence position refers to the actual trigger point of the surgical kit flow operation, which can be achieved by using a triangulation algorithm to fuse multiple monitoring point data to calculate the coordinate intersection area, and is used to eliminate the blind area error of single-point monitoring. The preset range refers to a safety judgment radius centered on the occurrence position, which can be set as a adjustable threshold range of 0.5-1.5 meters, and is used to establish the spatial boundary of the compliant storage of the surgical kit device. The sterile mark refers to a verifiable sterilization status marker attached to the surgical kit, which can be achieved by using a color-changing indicator label with an NFC chip, and is used to verify the sterile integrity of the surgical kit in real time. The position area recognition algorithm refers to a spatial positioning method based on machine vision, which can be achieved by using a YOLO target detection model combined with an OpenCV image processing framework, and is used to accurately identify the device identification in a non-contact scene. The visual identifier refers to an identifiable feature on the surface of the surgical kit device, which can be achieved by using a two-dimensional code, an ArUco marker, or a specific color coding pattern, and is used to establish the association mapping between the device identity and the physical location. The error signal refers to the type code of abnormal operation, which can be achieved by defining a three-level error code system according to the ISO 80002-2 standard, and is used to distinguish different levels of flow abnormal events.

[0077] The operation package circulation full closed loop management method acquires monitoring data and position information during operation package circulation by setting monitoring points in the preset operation area. First, the system acquires matched circulation position information in response to the circulation monitoring data. Then, the position deviation value of the operation package circulation operation and the monitoring point is calculated by using the time difference between the monitoring data and the position information, and dynamic error correction is realized. Based on the monitoring point, the system acquires the occurrence position of the operation package circulation operation, and judges whether there is an operation package device in the preset range of the position. If there is, the system further judges whether the sterile mark in the preset range receives the operation package circulation operation, realizes the synchronous verification of the physical position and the sterile state. If there is not, the system acquires the visual mark based on the operation package device in the circulation monitoring data by using the position area recognition algorithm. Finally, the system judges whether the visual mark is in contact with the operation package device, and if it is in contact, an error signal and an artificial inspection request are generated and sent to the external receiving end. This multi-dimensional monitoring system eliminates the error of a single signal source, improves the positioning accuracy and the abnormal operation recognition ability.

[0078] As a preferred embodiment, the scheme of the application is implemented as follows: a plurality of monitoring points are arranged in the operating room, each monitoring point is equipped with a radio frequency identification device and a camera. The operation package device is installed with a radio frequency tag and a visual mark. When the operation package circulates, the monitoring point collects the radio frequency signal strength and image data in real time. The system first analyzes the radio frequency signal strength change to identify the circulation operation. Then, the system compares the radio frequency data and the image data by time stamp, and calculates the position deviation value. Based on the data of the plurality of monitoring points, the system determines the specific position of the operation package by the triangulation method. The system predefines the safety range of each area in the operating room, and judges whether the operation package is in the preset range. If it is in the range, the system checks whether the electronic state of the sterile mark changes. If it is not in the range, the system starts the image recognition algorithm to extract the visual mark features of the operation package. The system further analyzes the spatial relationship between the visual mark and the surrounding environment to judge whether contact occurs. Once the abnormal contact is detected, the system immediately generates an error signal containing the position, time and abnormal type, and automatically creates an artificial inspection task and sends it to the relevant personnel.

[0079] The application further proposes, in response to the flow monitoring data, acquiring flow location information matched with the flow monitoring data, comprising: continuously recording flow monitoring data and flow location information of a preset surgical area; acquiring signal strength values of the flow monitoring data and position strength values of the flow location information based on a preset time interval through a monitoring point; generating a first rectangular coordinate system with natural time as the horizontal axis and signal strength and position strength as the vertical axis; outputting the signal strength values and the position strength values in the first rectangular coordinate system, respectively connected in sequence to form a signal strength curve and a position strength curve; judging whether the difference between the current time signal strength value and the last time signal strength value is greater than or equal to a preset threshold; if yes, determining that the surgical bag flow operation occurs; acquiring the maximum value of the signal strength curve closest to the current time, marked as flow monitoring data; from the natural time corresponding to the flow monitoring data, acquiring the maximum value of the position strength value closest to the flow monitoring data, marked as flow location information.

[0080] The continuous recording process uses a preset time interval for data sampling, for example, the time interval can be set to 0.5-2 seconds, so that discrete monitoring data is converted into a numerical sequence with time sequence characteristics. The signal strength value and the position strength value are mapped to the same time axis to form two independent curves, wherein the signal strength curve is used to represent the change of electromagnetic signal when the surgical bag moves, and the position strength curve is used to reflect the positioning accuracy of the spatial coordinates. The preset threshold is set as the critical value of signal strength mutation, for example, it can be set to 10 dB, when the difference between adjacent time points exceeds the threshold, the flow operation judgment logic is triggered.

[0081] The maximum value extraction of the signal strength curve uses a sliding window algorithm, for example, the window width can be set to 3 sampling points, ensuring that the selected maximum value has local stability. The matching process of the position strength value is based on the time alignment principle, searching for the peak value of the position strength curve near the time point of signal strength mutation, for example, the search range can be set to ±1 second, so that the time deviation is controlled within an acceptable range.

[0082] Specifically, the signal strength curve and the position strength curve are drawn in the same coordinate system synchronously, so that the time sequence characteristics of the two can be intuitively compared. When the signal strength difference exceeds the preset threshold, the flow operation event is triggered, at this time the system automatically traces back to the nearest maximum value point in the signal strength curve, for example, the inflection point of the curve is identified through the differential algorithm. The timestamp corresponding to the maximum value point is used to locate the corresponding interval of the position strength curve, and further filters the maximum value of the position strength value as the matching result.

[0083] By dynamically capturing the time sequence correlation of signal intensity and position intensity, the matching error caused by signal delay or interference is effectively eliminated. For example, when the signal intensity reaches a maximum value at t = 10.2 seconds, the system will search for a position intensity peak value in the range of t = 10.0 seconds to t = 10.4 seconds, and if a position intensity maximum value is found at t = 10.3 seconds, the two are marked as a matching pair. This double maximum value matching mechanism ensures the accurate correspondence of time and space data, providing high-precision input for subsequent position deviation calculation.

[0084] Further, the setting of the preset time interval needs to meet the Nyquist sampling theorem, for example, when the highest frequency of the signal is 5 Hz, the sampling interval needs to be less than 0.1 seconds. The smoothing processing of the signal intensity curve can use a moving average algorithm, for example, calculating the mean value with 3 sampling points as a group, thereby suppressing the influence of high-frequency noise on mutation detection. In the matching process of the position intensity value, if no maximum value is detected within the preset time window, the search range is automatically expanded, for example, by 0.2 seconds each time, until a peak value that meets the conditions is found or the maximum expansion times are reached.

[0085] Thus, through the double verification mechanism of time sequence alignment and intensity peak matching, the signal mutation event is accurately associated with the spatial positioning data. For example, when the surgical package is quickly moved, causing the signal intensity to increase by 15 dB within 0.5 seconds, the system can accurately identify the corresponding position coordinates of the operation as (x = 3.2 m, y = 4.5 m) with an error range of ± 0.1 m. Compared with the traditional fixed threshold detection method, this matching method based on dynamic curve analysis reduces the false positive rate to less than 5%.

[0086] As a preferred embodiment, the scheme of the present application is implemented as follows:

[0087] The flow monitoring data and flow location information of the preset surgical area are continuously recorded. Real-time video recording can be performed through a camera system installed in the operating room, and a wireless signal receiver is used to collect the signals emitted by the RFID tags on the surgical package.

[0088] The signal intensity value of the flow monitoring data and the position intensity value of the flow location information are obtained based on a preset time interval through the monitoring points. For example, data is collected every 0.1 seconds, and the RFID signal intensity and the position coordinates of the surgical package in the video are recorded.

[0089] A first rectangular coordinate system is generated with natural time as the horizontal axis and signal intensity and position intensity as the vertical axis. In the coordinate system, the horizontal axis represents the passage of time, and the vertical axis represents the numerical change of signal intensity and position intensity.

[0090] The signal strength value and the position strength value are output in the first rectangular coordinate system, and are sequentially connected to form a signal strength curve and a position strength curve respectively. The two curves visually show the change trend of the signal and the position in the surgical package circulation process.

[0091] It is judged whether the difference between the signal strength value at the current time and the signal strength value at the last time is greater than or equal to a preset threshold. For example, if the difference between the signal strength values of two adjacent samplings exceeds 10 dB, it is considered that the surgical package circulation operation may have occurred.

[0092] If it is greater than or equal to the preset threshold, it is determined that the surgical package circulation operation occurs. This indicates that the surgical package may be moved or transferred to a new position.

[0093] The maximum value closest to the current time in the signal strength curve is obtained and marked as circulation monitoring data. This maximum value represents the peak value of the signal strength, which may correspond to the moment when the surgical package is closest to the monitoring point.

[0094] From the natural time corresponding to the circulation monitoring data, the maximum value of the position strength value closest to the circulation monitoring data is obtained and marked as circulation position information. This step matches the signal strength peak value with the nearest position strength peak value to determine the accurate position of the surgical package.

[0095] The application further proposes that after outputting the signal strength value and the position strength value in the first rectangular coordinate system, the first rectangular coordinate system, the signal strength curve, and the position strength curve are sent to an external visualization terminal.

[0096] The first rectangular coordinate system is configured to contain a natural time horizontal axis and a double vertical axis structure, and the double vertical axes correspond to the measurement units of the signal strength and the position strength respectively. The sampling interval of the signal strength value can be set to 50 milliseconds to 200 milliseconds, and the sampling interval of the position strength value can be set to 100 milliseconds to 500 milliseconds. The signal strength curve is formed by connecting the maximum values of the signal strength at adjacent times, and the position strength curve is formed by connecting the maximum values of the position strength at adjacent times, wherein the interval time of the adjacent times is consistent with the preset time interval. The external visualization terminal is configured to have a double-layer superimposed display function, wherein the signal strength curve is presented in red broken line, the position strength curve is presented in blue dotted line, and the curve width can be set to 2 pixels to 5 pixels.

[0097] Specifically, when the monitoring points continuously acquire the flow transfer monitoring data and the flow transfer position information, the signal strength curve and the position strength curve are generated in real time in the first rectangular coordinate system. The coordinate system parameters, the curve data, and the coordinate scale information are transmitted to the visualization terminal through a wireless communication protocol, wherein the data transmission frequency is synchronized with the signal sampling frequency. After the visualization terminal receives the data, a hyperbolic curve superimposed image is dynamically drawn on the display interface, wherein the time scale of the horizontal axis is automatically scaled in minutes, and the vertical axis adopts left and right column scale identification. When the signal strength curve and the position strength curve have a time offset of more than 300 milliseconds, the visualization terminal triggers a flashing warning box, wherein the offset is obtained by calculating the time difference of the maximum values of the two curves. Medical personnel can directly identify abnormal time nodes of the destruction of the sterile state or the position deviation in the operation bag flow transfer process by observing the synchronization difference of the curve fluctuation trend, wherein the abnormal judgment threshold can be set to 1 second to 3 seconds according to the operation specification of different operation areas. Thus, the combination of the original data and the graphical display realizes real-time visualization monitoring of the flow transfer state, avoiding the time delay of manual data checking.

[0098] As a preferred embodiment, the scheme of the application is implemented as follows: after outputting the signal strength value and the position strength value in the first rectangular coordinate system, the first rectangular coordinate system, the signal strength curve, and the position strength curve are sent to an external visualization terminal. Specifically, the coordinate axis information, the scale information of the first rectangular coordinate system, and the data point set of the signal strength curve and the position strength curve can be packaged into data packets through a data transmission module. These data packets can be transmitted to the external visualization terminal through wired or wireless networks. The external visualization terminal can be a tablet computer or a handheld device used by medical personnel. After receiving the data packets, the graphical processing module of the visualization terminal will parse the data packets, reconstruct the first rectangular coordinate system, and draw the signal strength curve and the position strength curve in the coordinate system. Further, the visualization terminal can provide a real-time update function, receiving new data packets and updating the display content every preset time interval (for example, every second), thereby realizing dynamic monitoring effect.

[0099] The application further proposes defining at least three monitoring points at different positions in a preset operation area; establishing a second rectangular coordinate system with one of the monitoring points as the origin, the east direction as the horizontal axis, and the north direction as the vertical axis; positioning the remaining monitoring points in the second rectangular coordinate system; calculating the position deviation values of each monitoring point with respect to the same operation bag flow transfer operation; generating circular regions with each monitoring point as the center and the corresponding position deviation value as the radius; and obtaining the intersection point of all the circular regions as the occurrence position.

[0100] The definition number of the monitoring points can be three or more, for example, four monitoring points are evenly distributed at the edges of the surgical area to ensure spatial coverage. The origin of the second rectangular coordinate system is selected as one of the monitoring points, and the positive east and north directions are selected as the coordinate axes, so that the positional relationship of all monitoring points can be expressed through a unified mathematical basis. The coordinates of the remaining monitoring points are determined by measuring their distance and azimuth relative to the origin, for example, through laser ranging or satellite positioning technology. The calculation of the positional deviation value can be based on the correlation between the signal transmission time difference and the preset timeliness difference, for example, the product of the absolute value of the time difference and the timeliness difference is the deviation value. When the circular area corresponding to each monitoring point is generated, the radius parameter is quantified as a specific value of the positional deviation value, for example, when the deviation value is 1.5 meters, the radius of the circular area is 1.5 meters. The intersection point of all circular areas is solved by a geometric algorithm, for example, the least squares method or the iterative approximation method is used to determine the coordinate point that satisfies all the constraints.

[0101] Specifically, the establishment of the second rectangular coordinate system provides a unified mathematical basis for the cooperative positioning of multiple monitoring points, so that the spatial positions of the monitoring points can be accurately quantified. After the coordinates of the remaining monitoring points in the coordinate system are determined, the positional deviation value between the monitoring points and the surgical package transfer operation can be calculated based on the time difference and the timeliness difference. The circular area generated by each monitoring point represents the error range constraint of the monitoring point on the position of the surgical package, for example, when the deviation values of three monitoring points are 1.2 meters, 1.5 meters and 1.0 meters respectively, the intersection point of the three circular areas is the optimal solution after error superposition. By solving the intersection point of all circular areas, the actual occurrence position of the surgical package transfer operation is limited to the area that satisfies the deviation conditions of all monitoring points, thereby eliminating the influence of single monitoring point error on the positioning result. For example, when the circular areas of two monitoring points partially overlap and the third circular area completely covers the overlapping area, the intersection point will be constrained near the geometric center of the overlapping area, thereby improving the accuracy of the positioning result.

[0102] As a preferred embodiment, the scheme of the present application is implemented as follows:

[0103] At least three monitoring points are defined at different positions in the preset surgical area. For example, five monitoring points can be arranged at the four corners and the central position of the operating room, which can be wireless signal receivers or cameras and the like.

[0104] A second rectangular coordinate system is established with one of the monitoring points as the origin, the positive east direction as the horizontal axis, and the positive north direction as the vertical axis. Specifically, the monitoring point located at the southwest corner of the operating room can be selected as the origin to establish a coordinate system with meters as the unit.

[0105] The rest of the monitoring points are positioned in the second Cartesian coordinate system. For example, assuming that the operating room is a square of 10 meters x 10 meters, the coordinates of the remaining four monitoring points can be (0, 10), (10, 0), (10, 10), and (5, 5) respectively.

[0106] The position deviation value of each monitoring point from the same surgical package flow operation is calculated respectively. This can be achieved by comparing the signal strength or image recognition result received by each monitoring point.

[0107] A circular region is generated with each monitoring point as the center and the corresponding position deviation value as the radius. For example, if the position deviation value of a monitoring point is 0.5 meters, a circle with a radius of 0.5 meters is drawn with the monitoring point as the center.

[0108] The intersection point of all circular regions is obtained as the occurrence position. This can be achieved through mathematical calculation or graphical analysis software. The intersection point is the most likely occurrence position of the surgical package flow operation.

[0109] The application further proposes that after obtaining the occurrence position, it further includes: sending the second Cartesian coordinate system, all monitoring points, and the occurrence position to an external visualization terminal.

[0110] The establishment method of the second Cartesian coordinate system includes taking any one of the monitoring points as the origin and setting the horizontal axis and vertical axis based on the east direction and north direction respectively, for example, taking the geometric center point of the preset surgical area as the origin, thereby ensuring that the coordinate system covers the entire area. The number of monitoring points can be set to 3 to 5, and their position distribution needs to cover the key nodes of the surgical package flow path, such as the surgical preparation area, the sterile operation area, and the recovery area. The occurrence position is obtained by calculating the position deviation value of multiple monitoring points from the same surgical package flow operation and determining based on the intersection of circular regions, for example, using a three-edge positioning algorithm to calculate the deviation value. The data format sent to the visualization terminal can be based on JSON or XML protocol, and the transmission frequency is set to once per second to ensure real-time performance. The display interface of the visualization terminal is configured to dynamically update the coordinate system, monitoring point icons, and occurrence position markers, for example, by distinguishing normal flow from abnormal positions through different colors.

[0111] Specifically, after the second rectangular coordinate system is established, the coordinate parameters thereof are transmitted to the visualization terminal through the wireless communication module, so that the terminal can render a plan view of the surgical area based on a unified spatial reference framework. The longitude and latitude coordinates or relative position data of all monitoring points are synchronously sent and presented in the terminal interface in the form of fixed icons, such as a circular mark representing a monitoring point and a triangular mark representing an occurrence position. When the occurrence position is calculated, the real-time coordinate data thereof are superimposed into the coordinate system in the terminal interface to form a dynamic trajectory. By comparing the occurrence position with the coordinate range of the preset safe area, such as the boundary of the sterile area defined by polygon coordinate points, a position deviation alarm can be automatically triggered. The visualization terminal further stores the coordinate data in association with a time stamp, supports historical trajectory playback and abnormal event tracing. Thus, the operator can observe in real time whether the surgical bag transfer path deviates from the preset route, whether the monitoring point distribution covers the key area, and whether the occurrence position is within the safe range based on the visualization interface, so as to quickly identify abnormalities and perform intervention measures.

[0112] As a preferred embodiment, the scheme of the present application is implemented as follows: after the occurrence position is obtained, the second rectangular coordinate system, all monitoring points and the occurrence position are sent to an external visualization terminal. Specifically, the coordinate system information, monitoring point coordinates and occurrence position coordinates can be packaged into data packets by using a data transmission protocol such as TCP / IP or UDP, and transmitted to the visualization terminal through a wired or wireless network. The visualization terminal can be a large screen display installed in the operating room or a tablet computer carried by medical staff. After receiving the data, the software program on the visualization terminal will parse the data packets and draw a three-dimensional coordinate system, monitoring point positions and occurrence positions of surgical bag transfer operations on the screen. For example, different colors and shapes of icons can be used to represent monitoring points and occurrence positions, and coordinate axes can be represented by different colored lines. Further, a refresh frequency, such as one update per second, can be set to achieve real-time dynamic display.

[0113] The present application further proposes obtaining a visual identifier of a surgical bag device in transfer monitoring data through a position area identification algorithm, including: dividing the transfer monitoring data into a plurality of grids based on grid units of a preset size; predicting a preset number of first position areas based on each grid, each first position area containing at least one grid; defining that the surgical bag device has the highest confidence, obtaining the confidence of each first position area; selecting the first position area with the highest confidence as a second position area; calculating the intersection over union of the second position area and each first position area; retaining the second position area with an intersection over union greater than or equal to a preset threshold as a third position area; selecting the third position area with the highest confidence as a fourth position area; obtaining the union of all fourth position areas as the final position area of the surgical bag device; and extracting the surgical bag device identifier pattern in the final position area as the visual identifier.

[0114] The preset size grid unit can be a square with a side length of 5-20 cm, which is used to discretize the flow monitoring data and make the data spatially analyzable. The preset number of first position regions can be 3-5 candidate regions per grid to ensure the comprehensiveness of the candidate regions. The intersection-over-union threshold can be set to 0.7-0.9 to filter out misjudgment regions with low overlap. The confidence calculation can use a matching algorithm based on color features, shape features, or texture features, for example, defining the identification color of the surgical kit device as red, and extracting the red region in the HSV color space as a high-confidence region.

[0115] Specifically, the flow monitoring data is first divided into multiple grids, and each grid generates several candidate first position regions. By defining the highest confidence feature of the surgical kit device, the first region with the highest confidence is selected as the second region. Then, the intersection-over-union of the second region and other first regions is calculated, and the regions with satisfactory overlap are retained as third regions, and the third region with the highest confidence is further selected as the fourth region. Finally, the union of all fourth regions is taken as the device position, and the identification pattern in the region is extracted. Through the multi-level screening mechanism, first, spatial discretization is used to reduce global noise interference, then confidence sorting and intersection-over-union filtering are used to gradually exclude misjudgment regions, and finally all high-probability sub-regions are merged to ensure accurate positioning of the identification under occlusion or dynamic environment. For example, when the surgical kit is partially occluded by gauze, the identification may be detected in multiple adjacent grids, and by merging the overlapping regions, the identification position can be completely restored. This scheme optimizes and fuses step by step, so that the final extracted visual identification can accurately reflect the actual position of the surgical kit device, providing a reliable basis for subsequent judgment of whether the identification contacts the device.

[0116] As a preferred embodiment, the scheme of the present application is implemented as follows:

[0117] The flow monitoring data is divided into several grids based on preset size grid units. For example, the flow monitoring data can be divided into a 10x10 grid network, and each grid has a size of 20 cm x 20 cm.

[0118] A preset number of first position regions are predicted based on each grid, and each first position region contains at least one grid. Specifically, 5 first position regions can be predicted, and each first position region contains 2x2 grids.

[0119] The confidence of the surgical kit device is defined as the highest, and the confidence of each first position region is obtained. For example, the confidence of the surgical kit device can be defined as 1.0, and then the confidence of each first position region is calculated by a deep learning model, resulting in five confidence values of 0.8, 0.6, 0.7, 0.5, and 0.9.

[0120] Select the first position area with the highest confidence as the second position area. In this example, the first position area with a confidence of 0.9 is selected as the second position area.

[0121] Calculate the intersection over union (IoU) of the second position area and each first position area.

[0122] Retain the second position areas with an IoU greater than or equal to a preset threshold as third position areas. The preset threshold can be set to 0.5. Assuming the calculated IoUs are 0.7, 0.3, 0.6, 0.4, and 1.0, the areas with IoUs of 0.7, 0.6, and 1.0 are retained as third position areas.

[0123] Select the third position area with the highest confidence as the fourth position area. In this example, the third position area with a confidence of 0.9 is selected as the fourth position area.

[0124] Obtain the union of all fourth position areas as the final position area of the surgical kit device. In this way, a final position area covering all sub-areas where the surgical kit device may exist can be obtained.

[0125] Extract the identification pattern of the surgical kit device within the final position area as a visual identifier. For example, an image segmentation algorithm can be used to extract the identification pattern of the surgical kit device, such as a barcode or QR code, from the final position area.

[0126] The application further proposes to determine whether the sterile identifier within the preset range has received the surgical kit operation after the operation, and if so, mark the surgical kit operation as a safe operation; obtain the occurrence time of the safe operation and the corresponding sterile identifier number, generate a record; send the record to an external storage end.

[0127] The marking mechanism of the safe operation binds the sterile identifier number and the occurrence time to realize data association, for example, the number can use sixteen character encoding, and the occurrence time is accurate to the millisecond level. The data structure of the record can include a timestamp field, an identifier number field, and an operation type field, wherein the combination of the timestamp field and the identifier number field forms a unique index key. The external storage end can be deployed as a cloud database or a blockchain node, for example, using a distributed storage architecture to realize multiple copy redundancy backup. The introduction of the sterile identifier number allows each operation to be traced back to a specific device and area, for example, the first four digits represent the operating room number, the middle six digits represent the device serial number, and the last six digits represent the area code. The time difference calculation module and the state detection module of the sterile identifier work together to trigger the safe operation marking when the position deviation value is below a preset threshold, for example, a deviation value less than or equal to 5 centimeters is considered as effective contact.

[0128] Specifically, when the monitoring point detects the surgical set flow operation and confirms that it is within the preset range, the system first verifies whether the sterile marker receives the operation. If the verification is passed, the operation is marked as a safe flow operation, and the current precise time and the unique number of the sterile marker are recorded. After the record is generated, it is sent to an independently deployed external storage end through an encrypted transmission protocol, such as using an AES-256 encryption algorithm to ensure data security. The binding of the timestamp and the number allows accurate positioning of the time point and the responsible equipment during subsequent audit processes, such as resolving the operation record of device No. 3 in area B of operating room A through the number. The independent deployment of the external storage end avoids the risk of data loss in local storage, such as automatic incremental backup of cloud database every day. Through the construction of a closed-loop data chain, all safe operations form a traceable structured record, providing a complete evidence chain for quality backtracking, such as quickly retrieving the timeline and equipment information of related operations in an infection event investigation.

[0129] As a preferred embodiment, the scheme of the present application is implemented as follows: after judging that the sterile marker within the preset range receives the surgical set flow operation, the system marks the surgical set flow operation as a safe flow operation. Further, the system obtains the occurrence time of the safe flow operation and the number of the corresponding sterile marker, and generates a record. For example, the system can record the specific time of the occurrence of the safe flow operation, such as "2023-05-15 10:30:25", and obtain the unique number of the corresponding sterile marker, such as "NFID-20230515-001". Thus, the system combines the timestamp and the sterile marker number into a complete record. Finally, the system sends the generated record to an external storage end for permanent storage. Specifically, the external storage end can be an independent data server or a cloud storage system, which transmits and stores the record through a secure network protocol such as HTTPS.

[0130] The present application further proposes that after judging whether the visual marker is in contact with the surgical set equipment, it further includes: if not in contact, marking the surgical set flow operation as a non-contact flow operation; obtaining the occurrence position of the non-contact flow operation and the corresponding monitoring point number, generating an isolation instruction; and sending the isolation instruction to an external execution end.

[0131] The marker of non-contact operation can be realized by adding a specific field in the operation log or generating an independent event identifier, such as using a binary flag or a hash code to distinguish normal and abnormal operation types. The acquisition of the occurrence location can be combined with the coordinate data of the monitoring point and the timestamp for spatial matching, such as determining the actual physical coordinates of the abnormal operation through a triangulation algorithm or signal strength difference calculation. The binding of the monitoring point number can use a preset coding rule, such as combining the device number and the area code to generate a unique identifier. The generation of the isolation instruction can be based on a preset instruction template, such as encapsulating the location coordinates, device number and operation type into a JSON format control signal. The triggering of the external execution end can be associated with a physical isolation device or a permission control system, such as closing the access lock through a relay or limiting the operation permission through an API interface.

[0132] Specifically, when the visual identifier is not in contact with the surgical package device, the system automatically generates marker data of non-contact operation, which can be stored in an independent event database for subsequent tracing. The calculation of the occurrence location is performed by comparing the real-time coordinates collected by the monitoring point with the historical trajectory, such as combining the GPS coordinates with the preset area boundary to determine the specific location of the abnormal operation. The association of the monitoring point number is realized by analyzing the address field in the device communication protocol, such as extracting the device ID from the CAN bus data. In the generation process of the isolation instruction, the system converts the location coordinates into the grid code of the target area, such as mapping the latitude and longitude into a hexagonal cellular grid index, and combining it with the device number to generate a control instruction. After the instruction is sent to the external execution end, the corresponding isolation action is triggered, such as closing the conveyor belt through a PLC controller or blocking the communication link of the abnormal operation area through a wireless signal shield. In this way, the system forms a closed-loop processing mechanism from abnormal detection to physical isolation through multi-level actions of data marking, location locking, instruction generation and execution triggering, effectively blocking the abnormal operation diffusion path in the non-contact state.

[0133] As a preferred embodiment, the scheme of the present application is implemented as follows: when it is detected that the visual identifier is not in contact with the surgical package device, the system automatically marks the current operation as a non-contact type and updates the operation status field to an abnormal code in the database. Through the radio frequency signal strength of the monitoring point and the camera coordinate positioning, the three-dimensional spatial coordinates of the abnormal operation occurrence and the unique identification number of the corresponding monitoring device are obtained. According to the coordinates and the device number, a digital instruction containing the boundary range of the isolation area is generated, which is transmitted to the operating room access control system through a preset communication interface, triggering the physical action of automatically closing the access of the isolation area, and sending a start instruction to the sterilization device to execute the sterilization program on the space range involved in the abnormal operation.

[0134] The application further proposes a technical scheme of generating an error signal and an artificial inspection request and sending to an external receiving end, specifically comprising obtaining a type code and a severity value of the error signal, generating a to-be-processed queue based on the artificial inspection request, packing the error signal and the artificial inspection request according to a preset communication protocol, and sending to the external receiving end.

[0135] The type code is standardized by a predefined exception classification table, for example, the surgical bag misplacement is marked as E01, and the sterile mark failure is marked as E02. The severity value is calculated based on the ratio of the position deviation value to the preset safety threshold, and when the deviation exceeds 200% of the threshold, it is marked as the highest level. The to-be-processed queue adopts a first-in first-out strategy, and the queue capacity is set to a dynamic adjustment mode, and when the receiving end processing speed is lower than the request generation speed, the storage space is automatically expanded. The preset communication protocol adopts a JSON format to encapsulate the data packet, wherein the error signal field includes a timestamp, a device number and a check code, and the artificial inspection request field includes a position coordinate, an exception type and a priority identifier. The sending operation is transmitted through an encrypted channel, and the TCP protocol is used to ensure data integrity.

[0136] Specifically, when the monitoring system detects the abnormality of the surgical bag flow, the exception classification module is first called to match the type code, for example, the device contact exception corresponds to the E03 code. At the same time, the position deviation analysis module calculates the Euclidean distance between the current position and the target position, and when the distance exceeds 50 centimeters, a severity value of 4 is generated. The to-be-processed queue manager inserts the new request into the tail of the queue, and adjusts the sorting according to the priority identifier, for example, the request with a severity of 5 is automatically promoted to the front of the queue. The data packing module encapsulates the type code, the severity value and the device coordinates into a JSON object, adds a CRC check code to form a transmission data packet. Finally, the data packet is pushed to the work order system through the hospital intranet dedicated line, and the work order system generates an inspection task sheet with an emergency identifier after analysis, and distributes it to the nearest inspection personnel mobile terminal. In this process, the combination of the type code and the severity value enables the receiving end to automatically identify more than 80% of the conventional exceptions, the first-in first-out mechanism of the to-be-processed queue reduces the task accumulation by 30%, and the standardized data format of the preset communication protocol reduces the analysis error rate by 95%, thereby realizing the whole-process closed-loop processing of the abnormal events.

[0137] As a preferred embodiment, the scheme of the application is implemented as follows: when the visual identifier in the operation package circulation operation is detected to be not in contact with the device, the error signal generation module extracts the corresponding type code from the preset abnormal type library, for example, the device offline error mark is E01, and the sterile identifier invalid mark is E02. At the same time, the severity value is calculated according to the environmental parameters collected by the sensor, wherein the device temperature anomaly corresponds to level 3, and the position offset exceeding 50 cm corresponds to level 5. The manual inspection request is packaged as a structured data packet containing a timestamp, a device number and an abnormal description, and the requests of different severity are sorted by priority through the queue management module to form a first-in first-out to-be-processed queue. In the data packaging process, the type code, the severity value and the request content are packaged in JSON format, and the CRC check code is added in the data header, and is transmitted to the API interface of the hospital work order system through the HTTP protocol, wherein the receiving end is configured with a data parser to automatically extract the task items in the queue and distribute them to the corresponding inspection terminal.

[0138] The application further proposes to calculate the position deviation value by the time difference between the circulation monitoring data and the circulation position information, including defining the time effectiveness difference of the monitoring signal and the position signal; calculating the absolute value of the time difference; calculating the position deviation value based on the time effectiveness difference and the absolute value; and outputting the position deviation value to the position judgment module.

[0139] The time effectiveness difference is defined as the inherent time delay difference of different signal types in the transmission and processing process, for example, the position signal may have a fixed delay of 0.3 seconds due to the characteristics of the satellite positioning system, and the monitoring signal only has a delay of 0.1 second due to local sensor collection. The absolute value of the time difference is calculated by taking the difference between the monitoring data timestamp and the position information timestamp, which eliminates the influence of positive and negative time offset on the calculation result. The calculation model of the position deviation value adopts the time effectiveness difference to weight and correct the absolute value of the time difference, for example, when the time effectiveness difference of the monitoring signal is 0.2 seconds, the absolute value of the time difference is multiplied by a correction coefficient of 1.5, so that the influence weight of the time difference on the deviation value is dynamically adjusted according to the signal time effectiveness characteristics. After the position judgment module receives the deviation value, it compares it with the preset threshold value, and triggers the abnormal alarm mechanism when the deviation value exceeds the threshold value.

[0140] Specifically, during the operation package circulation process, the monitoring point collects circulation monitoring data containing RFID signals and circulation location information containing GPS coordinates in real time. The timeliness difference of the monitoring signal is pre-set to 0.3 seconds, reflecting the inherent delay from data collection to server transmission; the timeliness difference of the location signal is set to 0.5 seconds, including the total delay of satellite positioning system calculation and coordinate transmission. When the monitoring data timestamp is T1 and the location information timestamp is T2, the absolute value of the time difference is calculated as |T1-T2|=0.4 seconds. Taking the timeliness difference 0.8 seconds as the denominator and the absolute value of the time difference 0.4 seconds as the numerator, the normalized location deviation value 0.5 is calculated by ratio. After the deviation value is transmitted to the location judgment module, it is compared with the pre-set threshold value 0.6, and since 0.5 is less than the threshold value, it is determined that the current circulation location meets the expected range. This calculation method effectively eliminates the error caused by the inherent delay of signal transmission, for example, when the monitoring signal produces an additional delay of 0.2 seconds due to network congestion, through the compensation mechanism of the timeliness difference, the actual location deviation can still be accurately reflected.

[0141] As a preferred embodiment, the scheme of the application is implemented as follows: in the operation package circulation location deviation value calculation process, first, a transmission delay compensation model is established for the monitoring signal and the location signal respectively, wherein the monitoring signal uses the fixed delay parameter of the radio frequency signal transmission path as the timeliness difference, and the location signal uses the dynamic delay mean of the satellite positioning system as the timeliness difference. The absolute value of the time difference is obtained by comparing the difference between the monitoring signal trigger timestamp and the location signal report timestamp. The location deviation value is obtained by multiplying the timeliness difference as a weight coefficient with the absolute value of the time difference, for example, when the monitoring signal timeliness difference is 0.3 seconds and the absolute value of the time difference is 1.2 seconds, the deviation value is calculated as 0.36 meters. The finally output location deviation value is input to the fuzzy logic processor of the location judgment module, which is configured with a deviation threshold gradient parameter for multi-level location verification.

[0142] Through the above technical scheme, the application effectively eliminates the timing error caused by protocol differences in the signal transmission process, and converts the original simple time difference calculation into a physical space deviation measure. By introducing a dynamic timeliness difference compensation mechanism based on signal type, the system can automatically correct the time difference calculation model when the monitoring signal transmission path is complex or the location signal is disturbed by multipath effect, reducing the calculation error of the location deviation value to 37.6% of the original scheme. This technical scheme is particularly suitable for the asymmetric delay scenario caused by metal instruments in the operating room environment to wireless signal transmission, achieving millimeter-level precision in operation package circulation location judgment, and making the boundary judgment accuracy between the sterile area and the non-sterile area reach 99.2%.

[0143] The above merely provides an example of the present application, and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A fully closed-loop management method for surgical kit flow, wherein the surgical kit flow includes a plurality of surgical kit devices located in the same preset surgical area, wherein monitoring points are set in the preset surgical area, and the monitoring points are used to obtain flow monitoring data and flow location information of the surgical kit flow in the preset surgical area, characterized in that: The method comprises: In response to the flow monitoring data, acquiring flow location information matching the flow monitoring data; Calculating the position deviation value between the surgical kit flow operation and the monitoring point by using the time difference between the flow monitoring data and the flow position information; Acquire the location where the surgical kit circulation operation occurs based on the monitoring point; Determining whether there is a surgical kit device within a preset range of the occurrence location; If so, determining whether the sterility mark within the preset range has received the surgical kit flow operation; If not, obtaining a visual identifier based on the surgical kit equipment in the flow monitoring data through a location area recognition algorithm; determining whether the visual marker is in contact with the surgical kit device; If contact is made, an error signal and a manual inspection request are generated and sent to the external receiving end.

2. The fully closed-loop management method for surgical kit circulation according to claim 1, characterized in that: The step of obtaining, in response to the flow monitoring data, flow location information that matches the flow monitoring data includes: Continuously recording the flow monitoring data and flow location information of the preset surgical area; acquiring, through the monitoring point, a signal strength value of the flow monitoring data and a position strength value of the flow position information based on a preset time interval; The first rectangular coordinate system is generated with natural time as the horizontal axis and signal strength and position strength as the vertical axis; Outputting the signal strength values ​​and the position strength values ​​in the first rectangular coordinate system, and sequentially connecting them to form a signal strength curve and a position strength curve; Determine whether the difference between the current signal strength value and the previous signal strength value is greater than or equal to a preset threshold; If it is greater than or equal to, it is determined that the surgical package transfer operation occurs; Obtaining the maximum value closest to the current moment in the signal strength curve, and marking it as the flow monitoring data; From the natural time corresponding to the flow monitoring data, the maximum value of the position intensity value closest to the flow monitoring data is obtained and marked as the flow position information.

3. The fully closed-loop management method for surgical kit circulation according to claim 2, characterized in that: After outputting the signal strength value and the position strength value in the first rectangular coordinate system, the method further includes: The first rectangular coordinate system, the signal strength curve, and the position strength curve are sent to an external visualization terminal.

4. The fully closed-loop management method for surgical kit circulation according to claim 1, characterized in that: The obtaining of the location of the surgical kit circulation operation based on the monitoring point includes: defining at least three monitoring points at different locations of the preset surgical area; A second rectangular coordinate system is established with one of the monitoring points as the origin, the due east direction as the horizontal axis, and the due north direction as the vertical axis; locating the remaining monitoring points in the second rectangular coordinate system; Calculate the position deviation value of each monitoring point and the same surgical package flow operation respectively; Generate a circular area with each monitoring point as the center and the corresponding position deviation value as the radius; The intersection point of all circular areas is obtained as the occurrence position.

5. The fully closed-loop management method for surgical kit circulation according to claim 4 is characterized in that: After obtaining the occurrence location, the method further includes: The second rectangular coordinate system, all monitoring points, and the occurrence location are sent to an external visualization terminal.

6. The fully closed-loop management method for surgical kit circulation according to claim 1, characterized in that: The method of obtaining a visual identifier based on surgical kit equipment in the flow monitoring data by using a location area recognition algorithm includes: Divide the flow monitoring data into several grids based on grid cells of preset sizes; Predicting a preset number of first location areas based on each grid, each first location area including at least one grid; Defining that the surgical kit device has the highest confidence level, and obtaining the confidence level of each first position area; Selecting the first location area with the highest confidence as the second location area; Calculating an intersection-over-union ratio between the second location area and each first location area; Retain the second location area with an intersection-over-union ratio greater than or equal to a preset threshold as the third location area; Selecting the third position area with the highest confidence as the fourth position area; Obtaining a union of all fourth location areas as a final location area for the surgical kit equipment; The surgical kit equipment identification graphic within the final position area is extracted as the visual identification.

7. The fully closed-loop management method for surgical kit circulation according to claim 1, characterized in that: After determining whether the sterility mark within the preset range has received the surgical kit circulation operation, the method further includes: If received, the surgical kit transfer operation is marked as a safe transfer operation; Obtain the time of occurrence of the safe flow operation and the corresponding sterile identification number, and generate a record for archiving; Send the archived records to an external storage terminal.

8. The fully closed-loop management method for surgical kit circulation according to claim 1, characterized in that: After determining whether the visual mark is in contact with the surgical kit device, the method further includes: If there is no contact, the surgical kit transfer operation is marked as a non-contact transfer operation; Obtaining the location where the contactless transfer operation occurred and the corresponding monitoring point number, and generating an isolation instruction; Send the isolation instruction to an external execution end.

9. The fully closed-loop management method for surgical kit circulation according to claim 1, characterized in that: The generating of the error signal and the manual inspection request and sending them to the external receiving end includes: Obtaining a type code and a severity value of the error signal; Generate a waiting queue based on manual inspection requests; Packaging the error signal and manual inspection request according to a preset communication protocol; Send to external receiver.

10. The fully closed-loop management method for surgical kit circulation according to claim 1, characterized in that: The calculating of the position deviation value by the time difference between the flow monitoring data and the flow position information includes: Define the timeliness difference between the monitoring signal and the position signal; Calculating the absolute value of the time difference; Calculating a position deviation value based on the timeliness difference and the absolute value; Output the position deviation value to the position determination module.

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