Stomach tube track monitoring system and device

Abstract

The invention relates to a stomach tube track monitoring system and device, and the system comprises a track collection module which is used for obtaining the moving track of the insertion end of a stomach tube based on a real-time position; the trajectory analysis module is used for obtaining a real-time deviation between the target trajectory and the moving trajectory, and determining a deviation position and an adjustment angle according to the real-time deviation; the trajectory topological graph construction module is used for constructing a trajectory point cloud set according to the moving trajectory and determining an abnormal point set according to a trajectory topological graph group based on a continuous coherence mechanism; the real-time risk early warning module is used for synchronizing the moving track to a pre-obtained trachea-esophagus model and performing real-time risk early warning according to the position of the abnormal point set in the trachea-esophagus model; and the potential risk early warning module is used for inputting the real-time position into a preset trajectory prediction model to obtain a prediction trajectory at the next moment, and performing potential risk early warning according to the deviation between the prediction trajectory and the target trajectory.

Description

Technical Field

[0001] The present application relates to the field of medical assistance technology, and in particular to a gastric tube trajectory monitoring system and equipment. Background Art

[0002] Gastric tube insertion is a common medical procedure in clinical practice. Inserting a gastric tube into the patient's stomach provides nutritional support, medication infusion, and gastrointestinal function restoration. Traditional gastric tube insertion techniques rely on the medical staff's experience, with tube placement determined by observing the insertion depth and the patient's response to the insertion. In complex cases, there is a risk of the tube being misplaced into the trachea or other inappropriate locations.

[0003] Existing nasogastric tube positioning technologies primarily rely on imaging or physical positioning devices. Imaging methods, such as X-rays or CT scans, provide real-time images of the tube's position, but these methods pose radiation exposure and complex procedures. Physical positioning methods, on the other hand, use pressure sensors or electromagnetic positioning systems to provide medical staff with a trajectory path, but these methods offer limited accuracy and real-time performance. Therefore, achieving real-time and accurate trajectory monitoring during nasogastric tube insertion has become an urgent issue. Summary of the Invention

[0004] The embodiments of the present application provide a gastric tube trajectory monitoring system and device to at least solve the problem in the related art that the trajectory cannot be monitored in real time and accurately during the insertion of the gastric tube.

[0005] In a first aspect, an embodiment of the present application provides a gastric tube trajectory monitoring system, characterized in that the monitoring system is applied to a gastric tube trajectory monitoring device, the device including a gastric tube, the insertion end of the gastric tube being provided with a metal ring, and the monitoring system comprising: a trajectory acquisition module, configured to acquire the real-time position of the metal ring during the insertion of the gastric tube, and acquire the running trajectory of the insertion end of the gastric tube based on the real-time position; a trajectory analysis module, configured to determine a target trajectory based on a pre-acquired gastric tube insertion path model, obtain a real-time deviation between the target trajectory and the running trajectory, and determine an offset position and an adjustment angle according to the real-time deviation; A trajectory topology map construction module is used to construct a trajectory point cloud set according to the running trajectory, construct a trajectory topology map group based on a preset radius sequence and the trajectory point cloud set, and determine an abnormal point set according to the trajectory topology map group based on a continuous coherence mechanism; A real-time risk warning module is used to synchronize the running trajectory to a pre-acquired trachea-esophagus model and perform a real-time risk warning based on the position of the abnormal point set on the trachea-esophagus model; The potential risk warning module is used to input the real-time position into a preset trajectory prediction model to obtain the predicted trajectory at the next moment, and to issue a potential risk warning based on the deviation between the predicted trajectory and the target trajectory.

[0006] In one embodiment, constructing a trajectory topology graph group based on a preset radius sequence and the trajectory point cloud set includes: Under any of the preset radiuses, if the distance between any two points in the trajectory point cloud set is less than or equal to the preset radius, an edge between the two points is obtained; If the distance between any pair of points in any point set in the trajectory point cloud set is less than or equal to the preset radius, a simplex is obtained, and the number of points in the point set is greater than or equal to 3; Constructing a trajectory topology graph of the current preset radius according to the points, the edges and the simplex; According to the preset radius sequence, a trajectory topology map group constructed by the trajectory topology maps under each of the preset radii is obtained.

[0007] In one embodiment, the determining of an outlier point set based on the trajectory topology graph group based on the continuous coherence mechanism includes: Based on the trajectory topology graph group, determining the topological features of each of the trajectory topology graphs; A coordinate system is constructed with the preset radius sequence as the abscissa and the topological feature as the ordinate, and the life cycle of the topological feature is determined based on the preset radius at which the topological feature first appears as a starting point and the preset radius at which the topological feature disappears as an end point. The life cycle of each topological feature is displayed using the coordinate system to obtain a persistent bar graph; The life cycle distribution in the persistent bar graph is analyzed to determine abnormal topological features, and the abnormal topological features are mapped to the trajectory point cloud set to determine an abnormal point set.

[0008] In one embodiment, the topological features include connected components, analyzing the life cycle distribution in the persistent bar graph to determine abnormal topological features, mapping the abnormal topological features to the trajectory point cloud set, and determining the abnormal point set includes: If the life cycle of any connected component is less than a preset life cycle threshold, the connected component is an unstable connected component; In the persistence bar graph, determining the breakpoints of all the unstable connected components, and clustering the breakpoints to obtain a plurality of clusters; A target breakpoint is determined in each of the clusters, a first topological graph is reconstructed based on the target breakpoint and the trajectory point cloud set, vertex coordinates of the unstable connected component are determined in the first topological graph, and a first abnormal point set in the trajectory point cloud set is determined based on the vertex coordinates.

[0009] In one embodiment, the topological feature includes a ring, analyzing the life cycle distribution in the persistent bar graph to determine an abnormal topological feature, mapping the abnormal topological feature to the trajectory point cloud set, and determining the abnormal point set includes: If the life cycle of any ring is greater than or equal to the preset life cycle threshold, the ring is a stable ring; All the stable rings are determined in the persistence bar graph, generators of the stable rings are extracted, coordinates constituting the stable rings are determined based on the generators, and a second abnormal point set in the trajectory point cloud set is determined based on the coordinates of the rings.

[0010] In one embodiment, performing real-time risk warning based on the position of the abnormal point set in the trachea-esophagus model includes: If the center of the first abnormal point set is located in the esophageal stenosis area in the trachea-esophagus model, a real-time insertion path deviation risk warning is issued; If the geometric center of the second abnormal point set is located in the trachea area in the tracheogastric tube model, a real-time risk warning of misentering the trachea is issued.

[0011] In one embodiment, synchronizing the running trajectory to a pre-acquired trachea-esophagus model includes: Determining the esophageal inlet position and the cardia position in the tracheoesophageal model, and obtaining a first point set of the esophageal inlet position and a second point set of the cardia position, wherein the esophageal inlet position is the position where the esophagus and pharynx are connected, and the cardia position is the position where the esophagus and stomach are connected; Determining, from the trajectory point cloud set, a third point set at the esophagus position and a fourth point set at the cardia position in the running trajectory, and aligning and matching the first point set with the third point set, and the second point set with the fourth point set using an ICP algorithm to obtain a rotation matrix and a translation vector; The running trajectory is adjusted based on the rotation matrix and the translation vector to synchronize the running trajectory with the pre-acquired trachea-esophagus model.

[0012] In one embodiment, the issuing of a potential risk warning based on the deviation between the predicted trajectory and the target trajectory includes: Acquire target coordinates based on the target trajectory, acquire predicted coordinates based on the predicted trajectory, and obtain a distance deviation between the target coordinates and the predicted coordinates; determining a target turning angle based on the target coordinates, determining a predicted turning angle based on the predicted coordinates, and obtaining an angular deviation between the target turning angle and the predicted turning angle; When the distance deviation is greater than a preset distance threshold, a potential risk warning is issued; and / or When the angular deviation is greater than a preset angular threshold, a potential risk warning is issued.

[0013] In one embodiment, the gastric tube trajectory monitoring device further includes a processing terminal, and the method further includes: The running trajectory and the predicted trajectory are displayed in the processing terminal.

[0014] In a second aspect, an embodiment of the present application provides a gastric tube trajectory monitoring device, the device comprising: a processing terminal, a camera device, a metal ring, and a metal detection head; The metal ring is located outside the gastric tube insertion end and surrounds the gastric tube insertion end; The metal detector includes a receiving coil and a transmitting coil, wherein the transmitting coil is used to generate a variable magnetic field, and the receiving coil is used to receive the changing magnetic flux of the metal ring when the variable magnetic field moves, and obtain an induced voltage. The metal detector is electrically connected to the processing terminal and transmits the induced voltage of the receiving coil to the processing terminal; The processing terminal is used to receive the induced voltage to obtain the moving trajectory of the metal ring and display the moving trajectory of the metal ring; The gastric tube trajectory monitoring system and device provided in the embodiments of the present application have at least the following technical effects.

[0015] The trajectory acquisition module captures the real-time position of the metal ring to obtain the trajectory of the gastric tube insertion end. The real-time deviation between the running trajectory and the target trajectory determines the offset position and adjustment angle, allowing the operator to make timely adjustments. A trajectory topology map is constructed from the trajectory point cloud collection, and a continuous synchronization mechanism is used to identify outlier points within the trajectory point cloud collection. By processing complex geometric and topological information, the continuous synchronization mechanism can identify points that do not follow the overall pattern or violate the expected structural consistency, thereby improving the accuracy of the outlier point collection. Based on the location of outlier points in the tracheoesophageal model, real-time risk warnings are issued to monitor the trajectory of the gastric tube insertion end in real time, thereby promptly detecting abnormal risks during intubation. Based on the deviation between the running trajectory and the predicted trajectory, potential risk warnings are issued to proactively identify the risk of deviation during intubation. These potential risk warnings can help prevent intubation errors and insertion of the gastric tube into other organs. The continuous synchronization mechanism accurately identifies outlier trajectories within the trajectory, enabling precise control of the gastric tube insertion operation. Real-time and potential risk warnings ensure risk prevention during intubation.

[0016] The details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 is a schematic diagram of a gastric tube trajectory monitoring system according to an exemplary embodiment; Figure 2 is a schematic diagram illustrating a gastric tube trajectory monitoring device according to an exemplary embodiment.

[0018] In the above drawings, the meanings of the reference numerals are as follows: 1. Metal ring, 2. Metal detector, 3. Fixing belt, 4. Processing terminal, 5. Gastric tube, 6. Camera equipment. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is described and illustrated below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely used to explain this application and are not intended to limit this application. Based on the embodiments provided in this application, all other embodiments obtained by those of ordinary skill in the art without making any creative efforts are within the scope of protection of this application.

[0020] Obviously, the drawings described below are merely examples or embodiments of the present application. Those skilled in the art can, without inventive effort, apply the present application to other similar scenarios based on these drawings. Furthermore, it is also understood that, although the effort involved in such a development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, changes in design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as an insufficiency of the content disclosed in this application.

[0021] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it refer to independent or alternative embodiments that are mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments unless there is a conflict.

[0022] Unless otherwise defined, technical or scientific terms used herein shall have the ordinary meaning as understood by persons of ordinary skill in the art to which this application belongs. The terms "a," "an," "an," "the," and similar expressions used herein do not denote quantitative limitations and may refer to either the singular or the plural. The terms "comprise," "include," "have," and any variations thereof, used herein, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or modules (units) is not limited to the listed steps or units but may also include steps or units not listed, or may include other steps or units inherent to the process, method, product, or apparatus. The terms "connected," "connected," "coupled," and similar expressions used herein are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. As used herein, "plurality" means two or more. "And / or" describes an association between associated objects, indicating that three possible relationships exist. For example, "A and / or B" may mean: A exists alone; A and B exist simultaneously; or B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific order for the objects.

[0023] In a first aspect, an embodiment of the present application provides a gastric tube trajectory monitoring system. Figure 1 is a schematic diagram of a gastric tube trajectory monitoring system according to an exemplary embodiment. Figure 1As shown, the monitoring system is applied to a gastric tube trajectory monitoring device, the device includes a gastric tube, and a metal ring is provided at the insertion end of the gastric tube. The gastric tube trajectory monitoring system includes: The trajectory acquisition module is used to obtain the real-time position of the metal ring during the insertion of the gastric tube, and obtain the running trajectory of the gastric tube insertion end based on the real-time position.

[0024] The gastric tube trajectory monitoring device includes a gastric tube provided with a metal ring, a metal detection probe, and an inductive coil array provided in the metal detection head. The insertion process of the gastric tube is equivalent to the movement process of the metal ring. The inductive coil array in the metal detection head generates a magnetic field, and each inductive coil covers a different range. When the metal ring moves in the magnetic field, the metal ring causes the magnetic flux of the magnetic field to change, thereby causing the induced voltage of the inductive coils in the inductive coil array to change. The real-time position of the metal ring is determined based on the changes in the induced voltages of different coils. The real-time position of the metal ring is the spatial position at each moment, and different real-time positions constitute the running trajectory of the insertion end of the gastric tube. Among them, the real-time position of the metal ring is the three-dimensional coordinate of the geometric center of the metal ring, and the running trajectory is composed of several three-dimensional coordinates.

[0025] Furthermore, the insertion speed and turning angle of the gastric tube can be determined based on the trajectory. For the turning angle, three consecutive points are selected from the trajectory, a vector is determined between two adjacent points, and the turning angle formed by the three points is obtained based on the vector. Alternatively, a curve fitting can be performed on several consecutive points, and the curvature is obtained from the fitted curve. The turning angle is then calculated from the curvature.

[0026] For insertion speed, the real-time insertion speed of the gastric tube is obtained by position differential analysis based on the time and coordinates of the metal ring's real-time position. The obtained real-time insertion speed is then smoothed using a sliding window or Kalman filter to reduce noise and obtain a more accurate insertion speed.

[0027] As for the insertion depth, the exposed scale of the gastric tube is photographed by the camera of the gastric tube trajectory monitoring device to obtain the current insertion depth of the gastric tube.

[0028] The trajectory acquisition module collects the running trajectory of the gastric tube in the body in real time, and obtains the turning angle and insertion speed to provide a comprehensive and accurate basis for subsequent analysis of the running trajectory.

[0029] A trajectory analysis module is used to determine the target trajectory based on a pre-acquired gastric tube insertion path model, obtain the real-time deviation between the target trajectory and the running trajectory, and determine the offset position and adjustment angle based on the real-time deviation; Using 3D computed tomography, the area the gastric tube will pass through in the patient's body is scanned to create a model of the tube's insertion path. Within this model, a target trajectory is determined, ensuring that the path avoids all potential risk points, such as weak areas of blood vessels and organs, and scar tissue from previous surgeries, while remaining feasible.

[0030] The real-time coordinates of the target trajectory and the running trajectory are obtained and smoothed to remove the noise caused by the acquisition of the real-time coordinates. The time of each coordinate in the target trajectory and the running trajectory is synchronized to ensure that the coordinates in the target trajectory and the running trajectory correspond one to one.

[0031] The real-time path deviation between the target trajectory and the real-time coordinates of the running trajectory is calculated using the Euclidean distance, and the real-time turning angle deviation between the target trajectory and the running trajectory is calculated using the turning angle difference formula. The real-time path deviation specifically satisfies the following formula:

[0032] Where D(t) represents the path deviation distance at time t, x r (t) represents the x-axis coordinate of the running trajectory at time t, y r (t) represents the y-axis coordinate of the running trajectory at time t, z r (t) represents the z-axis coordinate of the running trajectory at time t; x i (t) represents the x-axis coordinate of the target trajectory at time t, y i (t) represents the y-axis coordinate of the target trajectory at time t, z i (t) represents the z-axis coordinate of the target trajectory at time t The real-time turning angle deviation specifically satisfies the following formula:

[0033] Among them, Δ θ ( t ) represents the turning angle deviation between the running trajectory and the target trajectory at time t, θ r ( t ) represents the turning angle of the running track at time t, θ i ( t ) represents the turning angle of the target trajectory at time t, Indicates the direction vector of the first segment of the running path in the running trajectory, Indicates the direction vector of the second segment of the running path in the running trajectory, Indicates the direction vector of the first segment of the target trajectory. The direction vector of the second segment of the target trajectory.

[0034] The real-time path deviation is compared with a preset path deviation threshold, and the real-time turning angle deviation is compared with a preset turning angle threshold. If either the real-time path deviation is greater than the preset path deviation threshold or the real-time turning angle deviation is greater than the preset turning angle threshold, the deviation coordinates causing the real-time deviation are determined within the trajectory, and an adjustment angle is determined based on the real-time turning angle deviation. A "minor trajectory deviation" prompt is displayed, and the deviation coordinates and adjustment angle are displayed on the processing terminal. This allows the operator to adjust the inserted gastric tube based on the deviation during intubation, preventing the gastric tube's trajectory from deviating from the target trajectory and preventing the tube from accidentally entering the trachea or penetrating tissue.

[0035] The trajectory topology map construction module is used to construct a trajectory point cloud set based on the running trajectory, construct a trajectory topology map group based on the preset radius sequence and the trajectory point cloud set, and determine the abnormal point set based on the trajectory topology map group based on the continuous coherence mechanism.

[0036] The trajectory data of each position in the running trajectory is subjected to noise filtering and normalization processing, and the position coordinates of each moment in the processed running trajectory are regarded as a trajectory point. A trajectory point cloud set is constructed based on all the trajectory points in the running trajectory.

[0037] Calculate the distance between any two trajectory points and determine the maximum distance among all distances. Use half of the maximum distance as the maximum radius threshold of the preset radius sequence to prevent the topology from being too dense. The preset radius sequence is an increasing radius sequence. Each preset radius satisfies the following formula: ,in, is the kth preset radius, is a fixed step size, is a natural number, , T.

[0038] Under any preset radius, if the distance between any two trajectory points in the trajectory point cloud set is less than or equal to the preset radius, the two points are connected to form an edge in the trajectory topology graph.

[0039] If the distance between any pair of points in any point set in the trajectory point cloud set is less than or equal to the preset radius, a simplex is obtained, and the number of points in the point set is greater than or equal to 3. For example, if there are three trajectory points in a point set in the trajectory point cloud set, and the distance between any two of the three trajectory points is less than or equal to the preset radius, a two-dimensional simplex is obtained, that is, a triangular surface formed by connecting the three trajectory points.

[0040] By using all trajectory points as vertices of the trajectory topology graph and the distances between the trajectory points to determine the edges and simplexes, a trajectory topology graph of the current preset radius is constructed. According to the preset radius sequence, the trajectory topology graph under each preset radius is obtained, and these trajectory topology graphs form a trajectory topology graph group.

[0041] Continue to refer to the module for building trajectory topology maps to determine the abnormal point set based on the trajectory topology map group based on the continuous synchronization mechanism, specifically including: Based on the trajectory topology graph group, the topological features of each trajectory topology graph are determined. Homology groups are calculated based on the trajectory topology graphs, including zero-order homology groups and first-order homology groups. The topological features of the trajectory graph are determined based on the homology groups. The topological features determined by the zero-order homology group are connected components, which represent the connection between any two trajectory points in the topology graph. The topological features determined by the first-order homology group are rings, which represent closed paths formed by the trajectory points in the topology graph.

[0042] A coordinate system is constructed with a preset radius sequence as the horizontal axis and the topological feature as the vertical axis. The lifecycle of a topological feature is determined based on the preset radius where the topological feature first appears and the preset radius where the topological feature disappears. The lifecycle of each topological feature is displayed in the coordinate system to obtain a persistent bar chart. In the trajectory topology chart, the same topological feature may appear in multiple quantities, and the lifecycle of the topological feature in the persistent bar chart may also vary. Therefore, in the persistent bar chart, the same topological feature will display different lifecycles, and the lifecycle is displayed as a horizontal line segment parallel to the horizontal axis.

[0043] The life cycle distribution in the persistent bar graph is analyzed to determine the abnormal topological features, and the abnormal topological features are mapped to the trajectory point cloud set to determine the abnormal point set.

[0044] Regarding the lifecycle of connected components, if any connected component's lifecycle is less than a preset lifecycle threshold, the connected component is considered unstable. Breaks or deviations in the trajectory will result in the formation of more connected components in the trajectory graph. Connected components resulting from deviations or breaks are generally unstable. Therefore, determining unstable connected components can indicate the presence of abnormal trajectories.

[0045] In the persistent bar graph, the endpoints of unstable connected components are determined based on their lifecycles, and the preset radius corresponding to the endpoints is used as the breakpoint. Density clustering is used to cluster all breakpoints into several clusters. Within each cluster, a target breakpoint, also known as the target radius, is determined. A trajectory topology is reconstructed based on the target radius and the trajectory point cloud collection. The vertex coordinates of the unstable connected components are determined within the trajectory topology. Based on the vertex coordinates, the first outlier point set in the trajectory point cloud collection is determined.

[0046] For loop lifecycles, if the lifecycle of any loop is greater than or equal to a preset lifecycle threshold, the loop is considered stable. A stable loop indicates that the trajectory forms a closed path. All stable loops are identified in the persistence bar chart, and their generators are extracted. The coordinates of the stable loops are determined based on the generators. The coordinates of the loops are then used to determine the second outlier point set in the trajectory point cloud. Each point in the second outlier point set forms a closed loop in terms of distribution.

[0047] Continuing with the Build Trajectory Topology module, we use the continuous coherence mechanism to obtain the topological features of the trajectory. This allows us to identify anomalous points in the trajectory point cloud. These anomalous points reflect risks within the trajectory. Promptly alerting these risks can help operators make timely adjustments. Specific alerting methods are described in the Real-time Risk Alert module.

[0048] The real-time risk warning module is used to synchronize the running trajectory to the pre-acquired trachea-esophagus model and provide real-time risk warning based on the position of the abnormal point set in the trachea-esophagus model.

[0049] The pre-acquired trachea-esophagus model is obtained by scanning the patient using computed tomography. The running trajectory is synchronized to the pre-acquired trachea-esophagus model, including: The esophageal inlet position and the cardia position in the tracheoesophageal model are determined, and a first point set of the esophageal inlet position and a second point set of the cardia position are obtained, wherein the esophageal inlet position is the position where the esophagus and pharynx are connected, and the cardia position is the position where the esophagus and stomach are connected.

[0050] The 3D coordinates of the esophageal inlet and cardia are determined in the tracheoesophageal model through annotation or automatic segmentation, obtaining a first point set at the esophageal inlet and a second point set at the cardia. When synchronizing the trajectory to the tracheoesophageal model, the esophageal inlet and cardia are used as alignment points to ensure accurate localization of abnormal trajectories within the tracheoesophageal model.

[0051] In the trajectory point cloud set, determine the third point set of the esophagus position and the fourth point set of the cardia position in the running trajectory, and use the ICP algorithm to achieve alignment and matching of the first and third point sets, and the second and fourth point sets to obtain the rotation matrix and translation vector; The esophageal inlet and cardia positions are determined in the trajectory by pre-calibration or estimation, obtaining a third point set in the esophageal inlet region and a fourth point set in the cardia region. Points in the first and third point sets are matched one-to-one to obtain a number of first point pairs, and points in the second and fourth point sets are matched one-to-one to obtain a number of second point pairs. The ICP algorithm is then used to minimize the distance between the two points in each first point pair and the distance between the two points in each second point pair, achieving alignment and matching between the first and third point sets, and between the second and fourth point sets, and obtaining a rotation matrix and a translation vector.

[0052] The running trajectory is adjusted based on the rotation matrix and translation vector, and the running trajectory is synchronized to the pre-acquired trachea-esophagus model.

[0053] The running trajectory is adjusted through the rotation matrix and translation vector so that the running trajectory fits the trachea-esophagus model, so that abnormal warnings can be issued based on the position of the running trajectory in the trachea-esophagus model. The abnormal warnings include real-time risk warnings of insertion path deviation and real-time risk warnings of misentering the trachea.

[0054] If the center of the first abnormal point set is located in the esophageal stenosis area in the trachea-esophagus model, a real-time risk warning of insertion path deviation is performed.

[0055] The first abnormal point set is determined by its topological feature, which is a connected component. This indicates that the points within the first abnormal point set have deviated from the trajectory. If the trajectory deviates within the esophageal stricture, the gastric tube will not reach the stomach. Furthermore, the deviated gastric tube will remain in the tube, which can easily damage the esophageal wall and cause pain to the patient. Therefore, when the center of the first abnormal point set is located in the esophageal stricture area in the tracheoesophageal model, a real-time insertion path deviation risk warning is issued to inform the operator of the deviation in gastric tube insertion and make timely adjustments.

[0056] If the geometric center of the second abnormal point set is located in the trachea area in the tracheogastric tube model, a real-time risk warning of misentering the trachea is issued.

[0057] The second abnormal point set is determined by the topological feature of a stable ring, which characterizes that the points in the second abnormal point set form a closed path. During the insertion of the gastric tube, after the gastric tube is wrapped around the ring, it is easy to deviate from the original path, so there is a risk of entering the trachea by mistake. The mean of the coordinates of all the points that constitute the ring in the second abnormal point set is used as the geometric center coordinate. When the geometric center coordinate is located in the tracheal area, it means that the gastric tube has entered the trachea after wrapping around the ring, and then the risk of mechanical energy entering the trachea by mistake is warned in real time to remind the operator that the gastric tube has entered the trachea by mistake and the insertion direction of the gastric tube needs to be adjusted.

[0058] Continuing to refer to the real-time risk warning module, a real-time risk warning is performed based on the locations of the first abnormal point set and the second abnormal point set to remind the operator that there is a fault in the gastric tube path so that adjustments can be made.

[0059] The potential risk warning module is used to input the real-time position into the preset trajectory prediction model to obtain the predicted trajectory at the next moment, and issue a potential risk warning based on the deviation between the predicted trajectory and the target trajectory.

[0060] Obtaining the preset trajectory prediction model includes: The historical data of the gastric tube's trajectory is collected and preprocessed and features are extracted. The features include the rate of change of coordinates of each point in the trajectory, the change of turning angle, the change of gastric tube insertion depth, and the change of gastric tube insertion speed.

[0061] The obtained features are used as training data to train the long short-term memory network model. The trained long short-term memory network model is the preset trajectory prediction model.

[0062] The real-time position of the gastric tube is input into the preset trajectory prediction model to obtain the predicted trajectory at the next moment. The deviation is obtained by comparing the predicted trajectory with the target trajectory, and potential risk warnings are issued, including: The target coordinates are obtained based on the target trajectory, the predicted coordinates are obtained based on the predicted trajectory, and the distance deviation between the target coordinates and the predicted coordinates is calculated. The distance deviation represents the distance between the predicted trajectory and the target trajectory. When the distance deviation is greater than the preset distance threshold, it means that continuing to insert the gastric tube under the current trajectory will result in the tube being inserted into another part of the body.

[0063] A target turning angle is determined based on a number of target coordinates, and a predicted turning angle is determined based on a number of predicted coordinates. The angular deviation between the target turning angle and the predicted turning angle is then obtained. This angular deviation indicates a significant inconsistency between the turns of the predicted trajectory and the target trajectory. The predicted turning angle may be significantly greater than the target turning angle, or the threshold turning angle may be significantly less than the target turning angle. Significant differences in the predicted turning angles can cause the gastric tube to be inserted at different locations, significantly deviating from the insertion path.

[0064] Based on the deviation between the predicted trajectory and the target trajectory, a potential risk warning is issued, indicating that the current trajectory of the gastric tube does not pose a direct threat to the human body, but has the tendency to evolve into a threat to the human body. To avoid this dangerous trend, a potential risk warning is required. Therefore, if the deviation between the predicted trajectory and the target trajectory meets any of the following conditions, a potential risk warning is issued: When the distance deviation is greater than the preset distance threshold, a potential risk warning is issued.

[0065] When the angular deviation is greater than the preset angular threshold, a potential risk warning is issued.

[0066] Continue to refer to the potential risk warning module, predict the direction of the running trajectory through the preset trajectory prediction model, identify potential risks in the gastric tube insertion process in advance, and issue a warning to prevent mistakes or risks during the gastric tube insertion process.

[0067] It should be noted that real-time risk warnings are anomaly warnings based on topological features, while potential risk warnings are anomaly warnings for trajectories that do not yet pose a direct threat but have the potential to evolve into abnormal trajectories. For both types of risk warnings, a multi-factor scoring mechanism is used to quantify the risk status of the current trajectory, specifically including: When the second abnormal point set is located in the trachea area, the risk score is 5 points and the risk level is high risk.

[0068] When the first abnormal point set is located in the esophageal stenosis area and near the aortic arch pressure mark, the risk score is 4 points, and the risk level is high risk.

[0069] When the distance deviation is greater than the preset distance threshold, the risk score is 3 points and the risk level is medium risk.

[0070] When the turning angle deviation is greater than the preset turning angle threshold, the risk score is 4 points and the risk level is high risk.

[0071] When the running trajectory is too close to the esophageal border, the risk score is 1 point and the risk level is low risk.

[0072] According to the above risk scores, early warning prompts are given:

[0073] If the risk is low, a green prompt will appear, indicating that the running trajectory is stable and there are no deviation anomalies. The system background will continue to monitor.

[0074] If the risk is medium, a yellow warning prompt will be displayed, indicating that a slight trajectory deviation has been detected, suggesting slowing down the insertion speed, and displaying the offset coordinates and adjustment angle.

[0075] If the risk is higher, an orange alert will be issued, showing the deviation distance of the positions of three consecutive points, marking the risk area on the trajectory map, and indicating the potential risk of penetration.

[0076] If the risk is high, a red alarm will be issued, and an audible and visual alarm will be issued to prevent the gastric tube from being inserted further. At the same time, the second point set will be displayed in the tracheal area, indicating that there is a high possibility of accidental insertion into the trachea. It is recommended to stop the insertion immediately and confirm the current insertion position of the gastric tube.

[0077] The gastric tube trajectory monitoring device also includes a processing terminal for displaying the expected and predicted trajectory and providing warnings. The processing terminal displays the gastric tube's trajectory and predicted trajectory in three dimensions, highlights wind direction areas, and provides guidance on the predicted trajectory. This provides the operator with an intuitive trajectory view, visualizing the gastric tube insertion process and ensuring safe insertion.

[0078] In summary, the gastric tube trajectory monitoring system provided in the embodiment of the present application uses a trajectory analysis module to adjust the deviation between the running trajectory and the target trajectory in real time to ensure that the gastric tube can be accurately inserted into the stomach. The coherence mechanism is used to process complex geometric and topological information, and the position of the abnormal point cloud is accurately identified through topological features. A real-time risk warning is issued based on the location of the abnormal point set, and a potential risk warning is issued based on the deviation between the running trajectory and the predicted trajectory, so as to avoid mistakes during the insertion of the gastric tube and thus achieve risk prevention and control. In addition, the running trajectory and predicted trajectory of the gastric tube are displayed through the processing terminal, providing the operator with a visual insertion path, thereby ensuring the safety and accuracy of the gastric tube insertion process, thereby improving the safety and accuracy of the gastric tube insertion operation and reducing human operation errors in traditional surgical methods.

[0079] In a second aspect, an embodiment of the present application provides a gastric tube trajectory detection device. Figure 2 FIG. 1 is a schematic diagram showing a gastric tube trajectory monitoring device according to an exemplary embodiment. Figure 2 As shown, the gastric tube trajectory monitoring device includes: a gastric tube 5, a processing terminal 4, a camera device 6, a metal ring 1 and a metal detection head 2.

[0080] The metal ring 1 is located outside the insertion end of the gastric tube 5 and surrounds the outside of the insertion end. When the gastric tube 5 is inserted, the metal ring 1 can indicate the trajectory of the gastric tube 5. The metal detector 2 is internally provided with a receiving coil and a transmitting coil. The transmitting coil is used to generate a variable magnetic field. The metal ring 1 is located in the variable magnetic field. When the metal ring 1 moves, the magnetic flux of the variable magnetic field changes. The receiving coil receives the induced voltage generated by the movement of the metal ring 1. The metal detector 2 is electrically connected to the processing end point and transmits the induced voltage to the processing terminal 4. The processing terminal 4 receives and processes the induced voltage, obtains the movement trajectory generated by the movement of the metal ring 1, and displays the movement trajectory. The processing terminal 4 is internally provided with a gastric tube trajectory detection system to monitor the movement trajectory. The processing terminal 4 and the metal detector 2 are fixed by a fixing belt 3. The camera 6 is located on the metal detector 2 and is used to determine the depth of the gastric tube 5 entering the stomach. The mounting bracket for the camera 6 is pluggable, and whether to use the camera 6 can be determined based on the specific application scenario.

[0081] To sum up, the gastric tube trajectory detection equipment provided in the present application determines the running trajectory of the gastric tube 5 through the metal ring 1 and the metal detection head 2. The gastric tube trajectory detection system provided in the processing terminal 4 can monitor the running trajectory and display the running trajectory on the processing terminal in a visual manner to provide the operator with a visual running path, thereby improving the accuracy of gastric tube insertion and reducing the risk of gastric tube insertion operation.

[0082] It should be noted that the gastric tube trajectory detection device provided in this embodiment is used to implement the above-mentioned embodiments, and the details that have been explained will not be repeated. As used above, the terms "module", "unit", "subunit", etc. can be a combination of software and / or hardware that implements the predetermined functions. Although the device described in the above embodiments is preferably implemented in software, it is also possible and conceivable to implement it in hardware, or a combination of software and hardware.

[0083] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A gastric tube trajectory monitoring system, characterized in that: The monitoring system is applied to a gastric tube trajectory monitoring device, the device comprising a gastric tube, the insertion end of which is provided with a metal ring, and the monitoring system comprises: a trajectory acquisition module, configured to acquire the real-time position of the metal ring during the insertion of the gastric tube, and acquire the running trajectory of the insertion end of the gastric tube based on the real-time position; a trajectory analysis module, configured to determine a target trajectory based on a pre-acquired gastric tube insertion path model, obtain a real-time deviation between the target trajectory and the running trajectory, and determine an offset position and an adjustment angle according to the real-time deviation; A trajectory topology map construction module is used to construct a trajectory point cloud set according to the running trajectory, construct a trajectory topology map group based on a preset radius sequence and the trajectory point cloud set, and determine an abnormal point set according to the trajectory topology map group based on a continuous coherence mechanism; A real-time risk warning module is used to synchronize the running trajectory to a pre-acquired trachea-esophagus model and perform a real-time risk warning based on the position of the abnormal point set on the trachea-esophagus model; The potential risk warning module is used to input the real-time position into a preset trajectory prediction model to obtain the predicted trajectory at the next moment, and to issue a potential risk warning based on the deviation between the predicted trajectory and the target trajectory.

2. The gastric tube trajectory monitoring system according to claim 1, characterized in that: The constructing of a trajectory topology graph group based on a preset radius sequence and the trajectory point cloud set includes: Under any of the preset radiuses, if the distance between any two points in the trajectory point cloud set is less than or equal to the preset radius, an edge between the two points is obtained; If the distance between any pair of points in any point set in the trajectory point cloud set is less than or equal to the preset radius, a simplex is obtained, and the number of points in the point set is greater than or equal to 3; Constructing a trajectory topology graph of the current preset radius according to the points, the edges and the simplex; According to the preset radius sequence, a trajectory topology map group constructed by the trajectory topology maps under each of the preset radii is obtained.

3. The gastric tube trajectory monitoring system according to claim 2, characterized in that: The determining of an abnormal point set according to the trajectory topology graph group based on the continuous coherence mechanism includes: Based on the trajectory topology graph group, determining the topological features of each of the trajectory topology graphs; A coordinate system is constructed with the preset radius sequence as the abscissa and the topological feature as the ordinate, and the life cycle of the topological feature is determined based on the preset radius at which the topological feature first appears as a starting point and the preset radius at which the topological feature disappears as an end point. The life cycle of each topological feature is displayed using the coordinate system to obtain a persistent bar graph; The life cycle distribution in the persistent bar graph is analyzed to determine abnormal topological features, and the abnormal topological features are mapped to the trajectory point cloud set to determine an abnormal point set.

4. The gastric tube trajectory monitoring system according to claim 3, characterized in that: The topological feature includes a connected component, analyzing the life cycle distribution in the persistent bar graph to determine an abnormal topological feature, mapping the abnormal topological feature to the trajectory point cloud set, and determining the abnormal point set includes: If the life cycle of any connected component is less than a preset life cycle threshold, the connected component is an unstable connected component; In the persistence bar graph, determining the breakpoints of all the unstable connected components, and clustering the breakpoints to obtain a plurality of clusters; A target breakpoint is determined in each of the clusters, a first topological graph is reconstructed based on the target breakpoint and the trajectory point cloud set, vertex coordinates of the unstable connected component are determined in the first topological graph, and a first abnormal point set in the trajectory point cloud set is determined based on the vertex coordinates.

5. The gastric tube trajectory monitoring system according to claim 4, characterized in that: The topological feature includes a ring, the analyzing the life cycle distribution in the persistent bar graph to determine an abnormal topological feature, mapping the abnormal topological feature to the trajectory point cloud set, and determining the abnormal point set includes: If the life cycle of any ring is greater than or equal to the preset life cycle threshold, the ring is a stable ring; All the stable rings are determined in the persistence bar graph, generators of the stable rings are extracted, coordinates constituting the stable rings are determined based on the generators, and a second abnormal point set in the trajectory point cloud set is determined based on the coordinates of the rings.

6. The gastric tube trajectory monitoring system according to claim 5, characterized in that: The performing of real-time risk warning according to the position of the abnormal point set in the trachea-esophagus model includes: If the center of the first abnormal point set is located in the esophageal stenosis area in the trachea-esophagus model, a real-time insertion path deviation risk warning is issued; If the geometric center of the second abnormal point set is located in the trachea area in the tracheogastric tube model, a real-time risk warning of misentering the trachea is issued.

7. The gastric tube trajectory monitoring system according to claim 1, characterized in that: Synchronizing the running trajectory to the pre-acquired trachea-esophagus model includes: Determining the esophageal inlet position and the cardia position in the tracheoesophageal model, and obtaining a first point set of the esophageal inlet position and a second point set of the cardia position, wherein the esophageal inlet position is the position where the esophagus and pharynx are connected, and the cardia position is the position where the esophagus and stomach are connected; Determining, from the trajectory point cloud set, a third point set at the esophagus position and a fourth point set at the cardia position in the running trajectory, and aligning and matching the first point set with the third point set, and the second point set with the fourth point set using an ICP algorithm to obtain a rotation matrix and a translation vector; The running trajectory is adjusted based on the rotation matrix and the translation vector to synchronize the running trajectory with the pre-acquired trachea-esophagus model.

8. The gastric tube trajectory monitoring system according to claim 1, characterized in that: The step of providing a potential risk warning based on the deviation between the predicted trajectory and the target trajectory includes: Acquire target coordinates based on the target trajectory, acquire predicted coordinates based on the predicted trajectory, and obtain a distance deviation between the target coordinates and the predicted coordinates; determining a target turning angle based on the target coordinates, determining a predicted turning angle based on the predicted coordinates, and obtaining an angular deviation between the target turning angle and the predicted turning angle; When the distance deviation is greater than a preset distance threshold, a potential risk warning is issued; and / or When the angular deviation is greater than a preset angular threshold, a potential risk warning is issued.

9. The gastric tube trajectory monitoring system according to claim 1, characterized in that: The gastric tube trajectory monitoring device further includes a processing terminal, and the method further includes: The running trajectory and the predicted trajectory are displayed in the processing terminal.

10. A gastric tube trajectory monitoring device, characterized in that: Applicable to the gastric tube trajectory monitoring system according to any one of claims 1 to 7, the device comprising: a processing terminal, a camera device, a metal ring and a metal detection head; The metal ring is located outside the gastric tube insertion end and surrounds the gastric tube insertion end; The metal detector includes a receiving coil and a transmitting coil, wherein the transmitting coil is used to generate a variable magnetic field, and the receiving coil is used to receive the changing magnetic flux of the metal ring when the variable magnetic field moves, and obtain an induced voltage. The metal detector is electrically connected to the processing terminal and transmits the induced voltage of the receiving coil to the processing terminal; The processing terminal is used to receive the induced voltage to obtain the moving trajectory of the metal ring and display the moving trajectory of the metal ring; The imaging device is electrically connected to the processing terminal and is used to photograph the scale of the gastric tube.

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