Systems and methods for vascular access management

Abstract

A system and method for vascular access management may: acquire images of a plurality of medical devices acquired by an image acquisition device; determining position information associated with a three-dimensional (3D) position of the plurality of medical devices relative to an image acquisition device based on the image; determining a plurality of pairs of mutually connected medical apparatuses in the plurality of medical apparatuses based on the position information; and generating a representation of at least one intravenous (IV) line comprising the plurality of pairs of medical devices determined to be interconnected based on the plurality of pairs of medical devices determined to be interconnected.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the priority of Indian Provisional Patent Application No. 202211042859, filed on July 26, 2022, titled “System and Method for Vascular Access Management”, the entire disclosure of which is incorporated herein by reference in its entirety. Background Art

[0003] When a patient is admitted to the hospital, various disposable drug delivery devices (e.g., needleless connectors, intravenous (IV) tubing, extension kits, catheters, etc.) can be attached to the patient to deliver drugs from an infusion pump to the patient at one or more catheter insertion sites. A single IV line can be made up of multiple instruments. A catheter with multiple lumens can form portions of multiple IV lines, which can be referred to as a "catheter tree." Nurses can mark IV lines with colored stickers (or other methods) to track the drugs infused into each IV line from each individual pump module of the infusion pump.

[0004] Multiple IV lines attached to a patient may affect the patient's drug compatibility. In addition, during a patient's hospital stay, components of the IV line may be replaced and / or the line configuration may be changed to accommodate different patient care needs. Nurses may need to track these changes to the IV line by recording the dwell time of the components and / or their connections to ensure line cleanliness and drug compatibility. Summary of the invention

[0005] Accordingly, improved systems, devices, products, apparatus and / or methods for vascular access management are provided.

[0006] According to some non-limiting embodiments or aspects, a system is provided, the system comprising at least one processor programmed and / or configured to: acquire an image of a plurality of medical devices acquired by an image acquisition device; determine, based on the image, position information associated with three-dimensional (3D) positions of the plurality of medical devices relative to the image acquisition device; determine, based on the position information, a plurality of pairs of medical devices that are interconnected among the plurality of medical devices; and, based on the plurality of pairs of medical devices determined to be interconnected, generate a representation of at least one IV line including the plurality of pairs of medical devices determined to be interconnected.

[0007] In some non-limiting embodiments or aspects, the at least one processor is programmed and / or configured to determine multiple pairs of interconnected medical devices in the following manner: for each pair of medical devices in the multiple medical devices, based on location information associated with the pair of medical devices, determine a probability that the pair of medical devices are connected to each other.

[0008] In some non-limiting embodiments or aspects, the at least one processor is programmed and / or configured to determine multiple pairs of interconnected medical devices in the following manner: for each pair of medical devices in the multiple medical devices, determine the following parameters based on the position information associated with the pair of medical devices: the distance between center points associated with the pair of medical devices; the angular difference between the orientations of the pair of medical devices; and the angle of deviation from collinearity of the pair of medical devices, wherein the probability that the pair of medical devices are connected is determined based on the distance between the center points of the pair of medical devices, the angular difference between the orientations of the pair of medical devices, and the angle of deviation from collinearity of the pair of medical devices.

[0009] In some non-limiting embodiments or aspects, for each medical device in a plurality of medical devices, the medical device is determined to be connected to another medical device in a pair of medical devices that includes the medical device, the pair of medical devices being associated with a highest probability of multiple pairs of medical devices that include the medical device.

[0010] In some non-limiting embodiments or aspects, the at least one processor is programmed and / or configured to determine position information associated with the 3D positions of multiple medical devices relative to the image acquisition device in the following manner: determining a type of each of the multiple medical devices based on the image, wherein, for a pair of medical devices in the multiple medical devices, a probability that the pair of medical devices are connected to each other is also determined based on the type of each of the pair of medical devices.

[0011] In some non-limiting embodiments or aspects, the at least one processor is programmed and / or configured to determine multiple pairs of interconnected medical devices by: identifying a group of medical devices in the multiple medical devices that are associated with a preferred IV line architecture based on a type of each medical device in the multiple medical devices; and for a pair of medical devices included in the group of medical devices associated with the preferred IV line architecture, adjusting a weight used to determine whether the pair of medical devices are connected to each other.

[0012] In some non-limiting embodiments or aspects, the at least one processor is programmed and / or configured to determine multiple pairs of interconnected medical devices by: determining, based on a type of each of the multiple medical devices, that no medical device in the multiple medical devices is associated with a preferred IV line architecture; and in response to determining that no medical device in the multiple medical devices is associated with the preferred IV line architecture, prompting a user to acquire another image.

[0013] In some non-limiting embodiments or aspects, a first group of medical devices among the multiple medical devices are associated with multiple reference markers, wherein the multiple reference markers encapsulate multiple identifiers associated with the first group of medical devices and posture information associated with the 3D positions of the multiple reference markers, and wherein the at least one processor is programmed and / or configured to determine the position information associated with the 3D positions of the multiple medical devices relative to the image acquisition device in the following manner: based on the image, determine the multiple identifiers associated with the first group of medical devices and the posture information associated with the 3D positions of the multiple reference markers, wherein, for each medical device in the first group of medical devices, the position information associated with the 3D position of the medical device relative to the image acquisition device is determined as the 3D position of the reference marker associated with the medical device relative to the image acquisition device.

[0014] In some non-limiting embodiments or aspects, the plurality of fiducial markers includes a plurality of AprilTags.

[0015] In some non-limiting embodiments or aspects, for each medical device in the first group of medical devices, the 3D position of the reference marker associated with the medical device relative to the image acquisition device includes: the x, y and z coordinates of the reference marker and the direction vectors of the Z axis, Y axis and X axis of the reference marker.

[0016] In some non-limiting embodiments or aspects, the plurality of identifiers are associated with multiple types of medical devices.

[0017] In some non-limiting embodiments or aspects, the plurality of identifiers includes a plurality of unique identifiers.

[0018] In some non-limiting embodiments or aspects, a second group of medical devices in the plurality of medical devices are not associated with a fiducial marker, and wherein the at least one processor is programmed and / or configured to determine position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device by, for each medical device in the second group of medical devices, determining, based on the image, using object recognition technology, the type of the medical device and the 3D position of the medical device relative to the image acquisition device.

[0019] In some non-limiting embodiments or aspects, the at least one processor is programmed and / or configured to further acquire images of the plurality of medical modalities by: acquiring images of the plurality of medical modalities using an image acquisition device.

[0020] In some non-limiting embodiments or aspects, the image includes a series of images.

[0021] In some non-limiting embodiments or aspects, the image acquisition device uses a continuous shooting acquisition technique to acquire the series of images.

[0022] In some non-limiting embodiments or aspects, the image acquisition device includes a stereo camera, and wherein position information associated with the 3D positions of multiple medical devices relative to the image acquisition device is determined using a Structure from Motion (SfM) algorithm.

[0023] In some non-limiting embodiments or aspects, the image acquisition device comprises a laser radar (LiDAR) system, and wherein the image comprises a LiDAR point cloud.

[0024] In some non-limiting embodiments or aspects, the at least one processor is programmed and / or configured to generate a representation of at least one IV by automatically displaying on the image lines connecting multiple pairs of medical devices determined to be connected to each other in the at least one IV line.

[0025] In some non-limiting embodiments or aspects, the at least one IV line is associated with at least one pump of the infusion pumps in the representation.

[0026] In some non-limiting embodiments or aspects, the plurality of fiducial markers are rigidly fixed to a rigid portion of the first set of medical instruments such that the plurality of fiducial markers cannot translate along and rotate about the first set of medical instruments.

[0027] In some non-limiting embodiments or aspects, the at least one processor is programmed and / or configured to: determine a dwell time based on the plurality of pairs of medical devices determined to be connected to each other, the dwell time indicating a duration that a medical device in the plurality of medical devices is connected to another medical device in the plurality of medical devices; and in response to the dwell time satisfying a threshold dwell time, provide an alert associated with the medical device via the user device. The dwell time may also indicate whether the marked disposable has been replaced since the last time the system scanned the marked disposable, or whether the marked disposable has been detected for a duration specified by a service provider or hospital.

[0028] According to some non-limiting embodiments or aspects, a method is provided, comprising: using at least one processor to acquire an image of a plurality of medical devices acquired by an image acquisition device; using the at least one processor to determine, based on the image, position information associated with three-dimensional (3D) positions of the plurality of medical devices relative to the image acquisition device; using the at least one processor to determine, based on the position information, a plurality of pairs of medical devices connected to each other among the plurality of medical devices; and using the at least one processor to generate, based on the plurality of pairs of medical devices determined to be connected to each other, a representation of at least one IV line including the plurality of pairs of medical devices determined to be connected to each other.

[0029] In some non-limiting embodiments or aspects, determining multiple pairs of medical devices connected to each other further includes: for each pair of medical devices in the multiple medical devices, determining a probability that the pair of medical devices are connected to each other based on location information associated with the pair of medical devices.

[0030] In some non-limiting embodiments or aspects, determining multiple pairs of medical devices that are connected to each other further includes: for each pair of medical devices in the multiple medical devices, determining the following parameters based on position information associated with the pair of medical devices: the distance between center points associated with the pair of medical devices; the angular difference between the orientations of the pair of medical devices; and the angle of deviation from collinearity of the pair of medical devices, wherein the probability that the pair of medical devices are connected is determined based on the distance between the center points of the pair of medical devices, the angular difference between the orientations of the pair of medical devices, and the angle of deviation from collinearity of the pair of medical devices.

[0031] In some non-limiting embodiments or aspects, for each medical device in a plurality of medical devices, the medical device is determined to be connected to another medical device in a pair of medical devices that includes the medical device, the pair of medical devices being associated with a highest probability of multiple pairs of medical devices that include the medical device.

[0032] In some non-limiting embodiments or aspects, determining position information associated with the 3D positions of multiple medical devices relative to the image acquisition device further includes: determining a type of each of the multiple medical devices based on the image, wherein, for a pair of medical devices in the multiple medical devices, a probability that the pair of medical devices are connected to each other is also determined based on the type of each of the pair of medical devices.

[0033] In some non-limiting embodiments or aspects, determining multiple pairs of interconnected medical devices further includes: identifying a group of medical devices in the multiple medical devices that are associated with a preferred IV line architecture based on the type of each medical device in the multiple medical devices; and for a pair of medical devices included in the group of medical devices associated with the preferred IV line architecture, adjusting a weight used to determine whether the pair of medical devices are connected to each other.

[0034] In some non-limiting embodiments or aspects, determining multiple pairs of interconnected medical devices further includes: determining that none of the multiple medical devices are associated with a preferred IV line architecture based on a type of each of the multiple medical devices; and in response to determining that none of the multiple medical devices are associated with the preferred IV line architecture, prompting a user to acquire another image.

[0035] In some non-limiting embodiments or aspects, a first group of medical devices among the multiple medical devices are associated with multiple reference markers, wherein the multiple reference markers encapsulate multiple identifiers associated with the first group of medical devices and posture information associated with the 3D positions of the multiple reference markers, and wherein determining the position information associated with the 3D positions of the multiple medical devices relative to the image acquisition device includes: based on the image, determining the multiple identifiers associated with the first group of medical devices and the posture information associated with the 3D positions of the multiple reference markers, wherein, for each medical device in the first group of medical devices, the position information associated with the 3D position of the medical device relative to the image acquisition device is determined as the 3D position of the reference marker associated with the medical device relative to the image acquisition device.

[0036] In some non-limiting embodiments or aspects, the plurality of fiducial markers includes a plurality of AprilTags.

[0037] In some non-limiting embodiments or aspects, for each medical device in the first group of medical devices, the 3D position of the reference marker associated with the medical device relative to the image acquisition device includes: the x, y and z coordinates of the reference marker and the direction vectors of the Z axis, Y axis and X axis of the reference marker.

[0038] In some non-limiting embodiments or aspects, the plurality of identifiers are associated with multiple types of medical devices.

[0039] In some non-limiting embodiments or aspects, the plurality of identifiers includes a plurality of unique identifiers.

[0040] In some non-limiting embodiments or aspects, a second group of medical devices in the plurality of medical devices are not associated with a reference marker, and wherein determining position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device further comprises: for each medical device in the second group of medical devices, determining the type of the medical device and the 3D position of the medical device relative to the image acquisition device based on the image using object recognition technology.

[0041] In some non-limiting embodiments or aspects, acquiring images of the plurality of medical devices further comprises: acquiring images of the plurality of medical devices using an image acquisition device.

[0042] In some non-limiting embodiments or aspects, the image includes a series of images.

[0043] In some non-limiting embodiments or aspects, the image acquisition device uses a continuous shooting acquisition technique to acquire the series of images.

[0044] In some non-limiting embodiments or aspects, the image acquisition device includes a stereo camera, and wherein position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device is determined using a structure from motion (SfM) algorithm.

[0045] In some non-limiting embodiments or aspects, the image acquisition device comprises a LiDAR system, and wherein the image comprises a LiDAR point cloud.

[0046] In some non-limiting embodiments or aspects, generating the representation of the at least one IV includes automatically displaying on the image lines connecting pairs of medical devices in the at least one IV line that are determined to be connected to each other.

[0047] In some non-limiting embodiments or aspects, the at least one IV line is associated with at least one pump of the infusion pumps in the representation.

[0048] In some non-limiting embodiments or aspects, the plurality of fiducial markers are rigidly fixed to a rigid portion of the first set of medical instruments such that the plurality of fiducial markers cannot translate along and rotate about the first set of medical instruments.

[0049] In some non-limiting embodiments or aspects, the method further includes: using at least one processor to determine a dwell time based on multiple pairs of medical devices determined to be connected to each other, the dwell time indicating a duration that one of the multiple medical devices is connected to another of the multiple medical devices; and in response to the dwell time satisfying a threshold dwell time, using the at least one processor to provide an alert associated with the medical device via a user device.

[0050] Other non-limiting embodiments or aspects are set forth in the following numbered clauses:

[0051] Article 1: A system comprising at least one processor programmed and / or configured to: acquire an image of a plurality of medical devices captured by an image capture device; determine, based on the image, position information associated with three-dimensional (3D) positions of the plurality of medical devices relative to the image capture device; determine, based on the position information, a plurality of pairs of medical devices that are connected to each other among the plurality of medical devices; and, based on the plurality of pairs of medical devices determined to be connected to each other, generate a representation of at least one IV line that includes the plurality of pairs of medical devices determined to be connected to each other.

[0052] Article 2: A system according to Article 1, wherein the at least one processor is programmed and / or configured to determine multiple pairs of interconnected medical devices in the following manner: for each pair of medical devices in the multiple medical devices, based on location information associated with the pair of medical devices, determine the probability that the pair of medical devices are connected to each other.

[0053] Article 3: A system according to any one of Articles 1 and 2, wherein the at least one processor is programmed and / or configured to determine multiple pairs of medical devices connected to each other in the following manner: for each pair of medical devices in the multiple medical devices, determine the following parameters based on position information associated with the pair of medical devices: the distance between center points associated with the pair of medical devices; the angular difference between the orientations of the pair of medical devices; and the angle of deviation from collinearity of the pair of medical devices, wherein the probability that the pair of medical devices are connected is determined based on the distance between the center points of the pair of medical devices, the angular difference between the orientations of the pair of medical devices, and the angle of deviation from collinearity of the pair of medical devices.

[0054] Article 4: A system according to any one of Articles 1 to 3, wherein, for each medical device in a plurality of medical devices, the medical device is determined to be connected to another medical device in a pair of medical devices that includes the medical device, the pair of medical devices being associated with a highest probability in a plurality of pairs of medical devices that includes the medical device.

[0055] Article 5: A system according to any one of Articles 1 to 4, wherein the at least one processor is programmed and / or configured to determine position information associated with the 3D positions of multiple medical devices relative to the image acquisition device in the following manner: determining the type of each medical device in the multiple medical devices based on the image, wherein, for a pair of medical devices in the multiple medical devices, the probability that the pair of medical devices are connected to each other is also determined based on the type of each medical device in the pair of medical devices.

[0056] Article 6: A system according to any one of Articles 1 to 5, wherein the at least one processor is programmed and / or configured to determine multiple pairs of interconnected medical devices by: identifying a group of medical devices in the multiple medical devices that are associated with a preferred IV pipeline architecture based on the type of each medical device in the multiple medical devices; and for a pair of medical devices included in the group of medical devices associated with the preferred IV pipeline architecture, adjusting the weights used to determine whether the pair of medical devices are connected to each other.

[0057] Article 7: A system according to any one of Articles 1 to 6, wherein the at least one processor is programmed and / or configured to determine multiple pairs of interconnected medical devices by: determining that no medical device in the multiple medical devices is associated with a preferred IV line architecture based on the type of each medical device in the multiple medical devices; and in response to determining that no medical device in the multiple medical devices is associated with the preferred IV line architecture, prompting a user to acquire another image.

[0058] Article 8: A system according to any one of Articles 1 to 7, wherein a first group of medical devices in the plurality of medical devices is associated with a plurality of fiducial markers, wherein the plurality of fiducial markers encapsulate a plurality of identifiers associated with the first group of medical devices and pose information associated with the 3D positions of the plurality of fiducial markers, and wherein the at least one processor is programmed and / or configured to determine position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device by: determining, based on the image, a plurality of identifiers associated with the first group of medical devices and pose information associated with the 3D positions of the plurality of fiducial markers, wherein, for each medical device in the first group of medical devices, the position information associated with the 3D position of the medical device relative to the image acquisition device is determined as the 3D position of the fiducial marker associated with the medical device relative to the image acquisition device.

[0059] Clause 9: The system of any one of Clauses 1 to 8, wherein the plurality of fiducial markers comprises a plurality of AprilTags.

[0060] Article 10: A system according to any one of Articles 1 to 9, wherein, for each medical device in the first group of medical devices, the 3D position of the reference marker associated with the medical device relative to the image acquisition device includes: the x, y and z coordinates of the reference marker and the direction vectors of the Z axis, Y axis and X axis of the reference marker.

[0061] Article 11: A system as described in any of Articles 1 to 10, wherein the plurality of identifiers are associated with multiple types of medical devices.

[0062] Clause 12: The system of any one of Clauses 1 to 11, wherein the plurality of identifiers comprises a plurality of unique identifiers.

[0063] Article 13: A system according to any one of Articles 1 to 12, wherein a second group of medical devices in the plurality of medical devices are not associated with a fiducial marker, and wherein the at least one processor is programmed and / or configured to determine position information associated with the 3D position of the plurality of medical devices relative to the image acquisition device by: for each medical device in the second group of medical devices, using object recognition technology to determine the type of the medical device and the 3D position of the medical device relative to the image acquisition device based on the image.

[0064] Article 14: A system according to any one of Articles 1 to 13, wherein the at least one processor is programmed and / or configured to further acquire images of multiple medical devices by: acquiring images of multiple medical devices using an image acquisition device.

[0065] Clause 15: A system as described in any of Clauses 1 to 14, wherein the image comprises a series of images.

[0066] Article 16: A system according to any one of Articles 1 to 15, wherein the image acquisition device uses a continuous shooting acquisition technology to acquire a series of images.

[0067] Article 17: A system as described in any of Articles 1 to 16, wherein the image acquisition device includes a stereo camera, and wherein the position information associated with the 3D position of multiple medical devices relative to the image acquisition device is determined using a structure from motion (SfM) algorithm.

[0068] Clause 18: The system of any one of clauses 1 to 17, wherein the image acquisition device comprises a LiDAR system, and wherein the image comprises a LiDAR point cloud.

[0069] Clause 19: A system according to any one of Clauses 1 to 18, wherein the at least one processor is programmed and / or configured to: generate a representation of the at least one IV by automatically displaying on the image lines connecting multiple pairs of medical devices determined to be connected to each other in the at least one IV line.

[0070] Clause 20: The system of any of Clauses 1 to 19, wherein the at least one IV line is associated with at least one pump of the infusion pump in question.

[0071] Clause 21: A system according to any one of Clauses 1 to 20a, wherein the plurality of fiducial markers are rigidly fixed to a rigid portion of the first group of medical instruments such that the plurality of fiducial markers cannot translate along and rotate around the first group of medical instruments.

[0072] Article 22: A system according to any one of Articles 1 to 21, wherein the at least one processor is programmed and / or configured to: determine a dwell time based on multiple pairs of medical devices determined to be connected to each other, the dwell time indicating a duration that one of the multiple medical devices is connected to another of the multiple medical devices; and in response to the dwell time satisfying a threshold dwell time, provide an alert associated with the medical device via a user device.

[0073] Article 23: A method comprising: using at least one processor to acquire an image of a plurality of medical devices acquired by an image acquisition device; using the at least one processor to determine, based on the image, position information associated with the three-dimensional (3D) positions of the plurality of medical devices relative to the image acquisition device; using the at least one processor to determine, based on the position information, a plurality of pairs of medical devices among the plurality of medical devices that are connected to each other; and using the at least one processor to generate, based on the plurality of pairs of medical devices that are determined to be connected to each other, a representation of at least one IV line that includes the plurality of pairs of medical devices that are determined to be connected to each other.

[0074] Article 24: The method according to Article 23, wherein determining multiple pairs of medical devices that are connected to each other further includes: for each pair of medical devices in the multiple medical devices, determining the probability that the pair of medical devices are connected to each other based on location information associated with the pair of medical devices.

[0075] Article 25: A method according to any one of Articles 23 and 24, wherein determining multiple pairs of medical devices connected to each other further includes: for each pair of medical devices in the multiple medical devices, determining the following parameters based on the position information associated with the pair of medical devices: the distance between the center points associated with the pair of medical devices; the angular difference between the orientations of the pair of medical devices; and the angle of deviation from collinearity of the pair of medical devices, wherein the probability that the pair of medical devices are connected is determined based on the distance between the center points of the pair of medical devices, the angular difference between the orientations of the pair of medical devices, and the angle of deviation from collinearity of the pair of medical devices.

[0076] Article 26: A method according to any one of Articles 23 to 25, wherein, for each medical device in a plurality of medical devices, the medical device is determined to be connected to another medical device in a pair of medical devices that includes the medical device, the pair of medical devices being associated with a highest probability of multiple pairs of medical devices that include the medical device.

[0077] Article 27: A method according to any one of Articles 23 to 26, wherein determining the position information associated with the 3D positions of multiple medical devices relative to the image acquisition device further includes: determining the type of each medical device in the multiple medical devices based on the image, wherein, for a pair of medical devices in the multiple medical devices, the probability that the pair of medical devices are connected to each other is also determined based on the type of each medical device in the pair of medical devices.

[0078] Article 28: A method according to any one of Articles 23 to 27, wherein determining multiple pairs of interconnected medical devices further includes: identifying a group of medical devices in the multiple medical devices that are associated with a preferred IV pipeline architecture based on the type of each medical device in the multiple medical devices; and for a pair of medical devices included in the group of medical devices associated with the preferred IV pipeline architecture, adjusting the weights used to determine whether the pair of medical devices are connected to each other.

[0079] Article 29: A method according to any one of Articles 23 to 28, wherein determining multiple pairs of interconnected medical devices further includes: based on the type of each medical device in the multiple medical devices, determining that no medical device in the multiple medical devices is associated with the preferred IV line architecture; and in response to determining that no medical device in the multiple medical devices is associated with the preferred IV line architecture, prompting a user to obtain another image.

[0080] Article 30: A method according to any one of Articles 23 to 29, wherein a first group of medical devices among a plurality of medical devices are associated with a plurality of reference markers, wherein the plurality of reference markers encapsulate a plurality of identifiers associated with the first group of medical devices and posture information associated with the 3D positions of the plurality of reference markers, and wherein determining the position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device comprises: determining, based on the image, a plurality of identifiers associated with the first group of medical devices and posture information associated with the 3D positions of the plurality of reference markers, wherein, for each medical device in the first group of medical devices, the position information associated with the 3D position of the medical device relative to the image acquisition device is determined as the 3D position of the reference marker associated with the medical device relative to the image acquisition device.

[0081] Clause 31: The method of any one of Clauses 23 to 30, wherein the plurality of fiducial markers comprises a plurality of AprilTags.

[0082] Article 32: A method according to any one of Articles 23 to 31, wherein, for each medical device in the first group of medical devices, the 3D position of the reference marker associated with the medical device relative to the image acquisition device includes: the x, y and z coordinates of the reference marker and the direction vectors of the Z axis, Y axis and X axis of the reference marker.

[0083] Article 33: A method according to any one of Articles 23 to 32, wherein the plurality of identifiers are associated with a plurality of types of medical devices.

[0084] Clause 34: The method of any one of Clauses 23 to 33, wherein the plurality of identifiers comprises a plurality of unique identifiers.

[0085] Article 35: A method according to any one of Articles 23 to 34, wherein a second group of medical devices in the multiple medical devices are not associated with a reference marker, and wherein determining the position information associated with the 3D position of the multiple medical devices relative to the image acquisition device further includes: for each medical device in the second group of medical devices, using object recognition technology to determine the type of the medical device and the 3D position of the medical device relative to the image acquisition device based on the image.

[0086] Article 36: The method according to any one of Articles 23 to 35, wherein acquiring images of multiple medical devices further comprises: using an image acquisition device to acquire images of multiple medical devices.

[0087] Clause 37: A method according to any one of clauses 23 to 36, wherein the image comprises a series of images.

[0088] Article 38: A method according to any one of Articles 23 to 37, wherein the image acquisition device uses continuous shooting acquisition technology to acquire a series of images.

[0089] Article 39: A method according to any one of Articles 23 to 38, wherein the image acquisition device includes a stereo camera, and wherein the position information associated with the 3D position of multiple medical devices relative to the image acquisition device is determined using a structure from motion (SfM) algorithm.

[0090] Clause 40: The method of any one of clauses 23 to 39, wherein the image acquisition device comprises a LiDAR system, and wherein the image comprises a LiDAR point cloud.

[0091] Clause 41: The method of any of Clauses 23 to 40, wherein generating a representation of at least one IV comprises automatically displaying on the image lines connecting multiple pairs of medical devices determined to be interconnected in the at least one IV line.

[0092] Clause 42: The method of any one of Clauses 23 to 41, wherein the at least one IV line is associated with at least one pump of the infusion pump in question.

[0093] Article 43: A method according to any one of Articles 23 to 42, wherein the plurality of reference markers are rigidly fixed to a rigid portion of the first group of medical instruments such that the plurality of reference markers cannot translate along and rotate around the first group of medical instruments.

[0094] Article 44: The method according to any one of Articles 23 to 43 further includes: using at least one processor to determine a dwell time based on multiple pairs of medical devices determined to be connected to each other, the dwell time indicating the duration of time that one medical device among the multiple medical devices is connected to another medical device among the multiple medical devices; and using at least one processor to provide an alarm associated with the medical device via a user device in response to the dwell time satisfying a threshold dwell time. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] Additional advantages and details are explained in more detail below with reference to an exemplary embodiment shown in the attached schematic drawings, in which:

[0096] Figure 1A are schematic diagrams of non-limiting embodiments or aspects of environments in which the systems, devices, products, apparatuses, and / or methods described herein may be implemented;

[0097] Figure 1B are schematic diagrams of non-limiting examples or aspects of implementation of environments in which the systems, devices, products, apparatuses, and / or methods described herein may be implemented;

[0098] Figure 2 yes Figure 1A and Figure 1B Schematic diagrams of non-limiting embodiments or aspects of one or more devices and / or components of one or more systems;

[0099] Figure 3A are perspective views of implementations of non-limiting examples or aspects of a plurality of medical devices;

[0100] Figure 3B yes Figure 3A A perspective view of a non-limiting example or aspect of an embodiment in which multiple medical devices are connected together;

[0101] Figure 4 is a flow chart of a non-limiting embodiment or aspect of a process of vascular access management;

[0102] Figure 5An example image of a catheter insertion site including multiple medical devices is shown.

[0103] Figure 6 Non-limiting examples or aspects of implementations of fiducial markers are shown;

[0104] Figure 7 is a stereogram of an example image of a catheter insertion site on a patient;

[0105] Figure 8 Example parameters used in implementation of a non-limiting embodiment or aspect of a process for vascular access management are shown;

[0106] Fig. 9 is a diagram of examples of atypical but possible connections between medical devices;

[0107] Fig.10 A non-limiting example or aspect embodiment of a representation of an IV line is shown; and

[0108] Fig.11 An example catheter tree building sequence for a process of vascular access management according to a non-limiting embodiment or aspect is shown. DETAILED DESCRIPTION

[0109] It should be understood that, unless expressly provided to the contrary, the present disclosure may employ various alternative variations and step sequences. It should also be understood that the specific devices and processes shown in the accompanying drawings and described in the following specification are merely exemplary and non-limiting embodiments or aspects. Therefore, specific dimensions and other physical characteristics associated with the embodiments or aspects disclosed herein should not be considered limiting.

[0110] For the purposes of description hereinafter, the terms "end", "upper", "lower", "right side", "left side", "vertical", "horizontal", "top", "bottom", "lateral", "longitudinal" and their derivatives shall relate to the various embodiments or aspects as they are oriented in the accompanying drawings. However, it will be understood that various alternative variations and step sequences may be employed in the various embodiments or aspects unless expressly specified to the contrary. It will also be understood that the specific devices and processes shown in the accompanying drawings and described in the following specification are merely non-limiting exemplary embodiments or aspects. Therefore, unless otherwise indicated, specific dimensions and other physical characteristics associated with the embodiments or aspects of the embodiments or aspects disclosed herein should not be considered limiting.

[0111] Aspects, parts, elements, structures, actions, steps, functions and / or instructions etc. used herein should not be interpreted as critical or necessary unless explicitly described as such. In addition, as used herein, the articles "one" and "an" are intended to include one or more items, and can be used interchangeably with "one or more" and "at least one". In addition, as used herein, the term "set" is intended to include one or more items (e.g., related items, unrelated items, combinations of related items and unrelated items, etc.), and can be used interchangeably with "one or more" or "at least one". In the case of only one item being meant, the term "one" or similar language is used. In addition, as used herein, the terms "have", "have" or "have" etc. are intended to be open terms. In addition, unless otherwise explicitly stated, the phrase "based on" is intended to mean "based at least in part on".

[0112] As used herein, the terms "communication" and "communicate" may refer to the reception, receipt, transmission, transfer and / or provision of information (e.g., data, signals, messages, instructions and / or commands, etc.). A unit (e.g., a device, a system, a component of a device or system and / or a combination thereof, etc.) communicating with another unit means that the unit is able to directly or indirectly receive information from another unit and / or transmit information to another unit. This may refer to a direct or indirect connection that is essentially wired and / or wireless. In addition, although the transmitted information may be modified, processed, relayed and / or routed between a first unit and a second unit, the two units may communicate with each other. For example, even if the first unit passively receives information and does not actively transmit information to the second unit, the first unit may communicate with the second unit. As another example, if at least one intermediate unit (e.g., a third unit located between the first unit and the second unit) processes the received information from the first unit and transmits the processed information to the second unit, the first unit may communicate with the second unit. In some non-limiting embodiments or aspects, a message may refer to a network packet (e.g., a data packet, etc.) comprising data. It will be appreciated that many other arrangements are possible.

[0113] As used herein, the term "computing device" may refer to one or more electronic devices that are configured to communicate directly or indirectly with one or more networks or to communicate through one or more networks. A computing device may be a mobile or portable computing device, a desktop computer and / or a server, etc. In addition, the term "computer" may refer to any computing device that includes the necessary components for receiving, processing and outputting data, and typically includes a display, a processor, a memory, an input device and a network interface. A "computing system" may include one or more computing devices or computers. An "application" or "application program interface (API)" refers to a computer code or other data stored on a computer-readable medium, which may be executed by a processor to facilitate interaction between software components, such as a client-side front end and / or a server-side back end for receiving data from a client. An "interface" refers to a generated display, such as one or more graphical user interfaces (GUIs) with which a user may interact directly or indirectly (e.g., via a keyboard, a mouse, a touch screen, etc.). In addition, a plurality of computers (e.g., servers or other computerized devices) that communicate directly or indirectly in a network environment may constitute a "system" or a "computing system."

[0114] It will be apparent that the systems and / or methods described herein may be implemented in various forms of hardware, software, or a combination of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods is not limited to these embodiments. Therefore, the operation and behavior of the systems and / or methods are described herein without reference to specific software code, and it should be understood that software and hardware can be designed to implement the systems and / or methods based on the description herein.

[0115] Some non-limiting embodiments or aspects are described herein in conjunction with threshold values. As used herein, satisfying a threshold value may refer to a value being greater than a threshold value, more than a threshold value, above a threshold value, greater than or equal to a threshold value, less than a threshold value, less than a threshold value, below a threshold value, less than or equal to a threshold value, equal to a threshold value, etc.

[0116] Reference now Figure 1A , Figure 1A 1 is a schematic diagram of an example environment 100 in which the devices, systems, methods, and / or products described herein may be implemented. Figure 1A As shown, environment 100 includes user devices 102, management system 104, and / or communication network 110. Systems and / or devices of environment 100 may be interconnected via wired connections, wireless connections, or a combination of wired and wireless connections.

[0117] Also refer to Figure 1B , Figure 1B is a schematic diagram of a non-limiting example or aspect of an implementation of an environment 100 in which the systems, devices, products, apparatuses, and / or methods described herein may be implemented. Figure 1B As shown, the environment 100 may include a patient room including: a patient, one or more medical devices 108, one or more fiducial markers 110 associated with the one or more medical devices 108, and / or a caregiver (eg, a nurse, etc.).

[0118] The user device 102 may include one or more devices that are capable of receiving information and / or data from the management system 104 (e.g., via the communication network 106, etc.) and / or transmitting information and / or data to the management system 104 (e.g., via the communication network 106, etc.). For example, the user device 106 may include one or more computing systems that include one or more processors (e.g., one or more computing devices, one or more server computers, one or more mobile computing devices, one or more tablet computers, etc.). In some non-limiting embodiments or aspects, the user device 102 may include a tablet computer or a mobile computing device, such as Tablet( iPad), cell phone( iPhone), Android tablet ( tablet), cell phone( phone), etc.

[0119] The user device 102 may include one or more image acquisition devices (e.g., one or more cameras, one or more sensors, etc.) configured to acquire one or more images of an environment (e.g., environment 100, etc.) surrounding the one or more image acquisition devices. For example, the user device 102 may include one or more image acquisition devices configured to acquire one or more images of one or more medical devices 108, one or more fiducial markers 110 associated with the one or more medical devices 108, and / or a patient. As an example, the user device 102 may include at least one of the following image acquisition devices: a camera; a stereo camera; a LiDAR sensor; or any combination thereof.

[0120] The management system 104 may include one or more devices that are capable of receiving information and / or data from the user device 102 (e.g., via the communication network 106, etc.) and / or transmitting information and / or data to the user device 102 (e.g., via the communication network 110, etc.). For example, the management system 104 may include one or more computing systems that include one or more processors (e.g., one or more computing devices, one or more server computers, one or more mobile computing devices, etc.). In some non-limiting embodiments or aspects, the management system 104 includes a nurse station or terminal in a hospital and / or is accessible via a nurse station or terminal in a hospital. For example, the management system 104 may provide bedside nurse support, nurse station administrator support, and / or retrospective reporting of nursing management, etc.

[0121] The communication network 106 may include one or more wired networks and / or wireless networks. For example, the communication network 110 may include a cellular network (e.g., a long-term evolution (LTE) network, a third generation (3G) network, a fourth generation (4G) network, a fifth generation (5G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., a public switched telephone network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, a fiber-based network and / or a cloud computing network, etc., and / or a combination of these or other types of networks.

[0122] Figure 1A and Figure 1B The number and arrangement of the systems and devices shown in are provided as examples. Figure 1A and Figure 1B There may be additional systems and / or devices, fewer systems and / or devices, different systems and / or devices, or differently arranged systems and / or devices compared to the systems and / or devices shown in . In addition, Figure 1A and Figure 1B Two or more systems or devices shown in the figure may be implemented in a single system or a single device, or Figure 1A and Figure 1B A single system or a single device shown in the environment 100 may be implemented as multiple distributed systems or devices. Additionally or alternatively, a group of systems or a group of devices (e.g., one or more systems, one or more devices, etc.) of the environment 100 may perform one or more functions described as being performed by another group of systems or another group of devices of the environment 100.

[0123] Reference now Figure 2 , Figure 2 2 is a schematic diagram of example components of device 200. Device 200 may correspond to user device 102 (e.g., one or more devices of a system of user device 102, etc.) and / or one or more devices of management system 104. In some non-limiting embodiments or aspects, user device 102 (e.g., one or more devices of a system of user device 102, etc.) and / or one or more devices of management system 104 may include at least one device 200 and / or at least one component of device 200. Figure 2 As shown, device 200 may include a bus 202 , a processor 204 , a memory 206 , a storage component 208 , an input component 210 , an output component 212 , and a communication interface 214 .

[0124] The bus 202 may include components that allow communication between the components of the device 200. In some non-limiting embodiments or aspects, the processor 204 may be implemented in hardware, software, or a combination of hardware and software. For example, the processor 204 may include a processor (e.g., a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), etc.), a microprocessor, a digital signal processor (DSP), and / or any processing component that can be programmed to perform a function (e.g., a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), etc.). The memory 206 may include a random access memory (RAM), a read-only memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, optical memory, etc.) that stores information and / or instructions for use by the processor 204.

[0125] The storage component 208 may store information and / or software related to the operation and use of the device 200. For example, the storage component 208 may include a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optical disk, a solid-state disk, etc.), a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of computer-readable medium, and a corresponding drive.

[0126] Input components 210 may include components that allow device 200 to receive information, for example, via a user input (e.g., a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, a microphone, etc.). Additionally or alternatively, input components 210 may include sensors for sensing information (e.g., a global positioning system (GPS) component, an accelerometer, a gyroscope, an actuator, etc.). Output components 212 may include components that provide output information from device 200 (e.g., a display, a speaker, one or more light-emitting diodes (LEDs), etc.).

[0127] The communication interface 214 may include a transceiver-like component (e.g., a transceiver, a separate receiver and transmitter, etc.) that enables the device 200 to communicate with other devices, for example, via a wired connection, a wireless connection, or a combination of a wired connection and a wireless connection. The communication interface 214 may allow the device 200 to receive information from another device and / or provide information to another device. For example, the communication interface 214 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, interface and / or cellular network interface, etc.

[0128] The device 200 can perform one or more processes described herein. The device 200 can perform these processes based on the processor 204 executing software instructions stored by a computer-readable medium (e.g., memory 206 and / or storage component 208). Computer-readable media (e.g., non-transitory computer-readable media) are defined herein as non-transitory storage devices. Storage devices include storage space located within a single physical storage device or storage space spread across multiple physical storage devices.

[0129] The software instructions may be read into the memory 206 and / or storage component 208 from another computer-readable medium or from another device via the communication interface 214. The software instructions stored in the memory 206 and / or storage component 208, when executed, may cause the processor 204 to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Therefore, the embodiments or aspects described herein are not limited to any specific combination of hardware circuitry and software.

[0130] The memory 206 and / or storage component 208 may include a data storage device or one or more data structures (e.g., a database, etc.). The device 200 may be capable of receiving information from the data storage device or one or more data structures in the memory 206 and / or storage component 208, storing information in the data storage device or one or more data structures, transmitting information to the data storage device or one or more data structures, or searching for information stored in the data storage device or one or more data structures.

[0131] Figure 2 The number and arrangement of components shown are provided as examples. In some non-limiting embodiments or aspects, Figure 2 Device 200 may include additional components, fewer components, different components, or differently arranged components than those shown in . Additionally or alternatively, a set of components (e.g., one or more components) of device 200 may perform one or more functions described as being performed by another set of components of device 200.

[0132] Reference now Figure 3A and Figure 3B , Figure 3A are perspective views of implementations of non-limiting examples or aspects of a plurality of medical devices, and Figure 3B yes Figure 3A A perspective view of an implementation of a non-limiting example or aspect in which multiple medical devices are connected together.

[0133] The medical devices 108 may include at least one of the following types of medical devices: a peripheral IV catheter (PIVC); a peripherally inserted central catheter (PICC); a midline catheter; a central venous catheter (CVC); a needleless connector; a catheter dressing; a catheter stabilization device; a disinfectant cap; a disinfectant swab or wipe; an IV tubing set; an extension set; a Y-connector; a stopcock; an infusion pump; a flush syringe; a drug delivery syringe; an IV fluid bag; an inner lumen adapter (e.g., the number of inner lumen adapters associated with a catheter may indicate the number of lumens included in the catheter, etc.); or any combination thereof.

[0134] A fiducial marker 110 (e.g., a label, tag, code, etc.) can be associated with a medical device 108 (e.g., removably attached to the medical device, permanently attached to the medical device, integrated with the medical device, implemented on the medical device, etc.). In some non-limiting embodiments or aspects, each medical device 108 in the environment 100 can be associated with a fiducial marker 110. In some non-limiting embodiments or aspects, only a portion of the medical devices 108 in the environment 100 can be associated with a fiducial marker 110. In some non-limiting embodiments or aspects, none of the multiple medical devices 108 in the environment 100 can be associated with a fiducial marker 110.

[0135] The fiducial marker 110 may encapsulate an identifier associated with the type of medical device 108 associated with the fiducial marker 110 and / or uniquely identify the medical device 108 associated with the fiducial marker 110 from other medical devices. For example, the fiducial marker 110 may encapsulate an identifier associated with at least one of the following types of medical devices: a peripheral IV catheter (PIVC); a peripherally inserted central catheter (PICC); a midline catheter; a central venous catheter (CVC); a needleless connector; a sterile cap; a sterile swab or wipe; an IV tubing set; an extension set; a Y-connector; a stopcock; an infusion pump; a flushing syringe; a drug delivery syringe; an IV fluid bag; or any combination thereof, and / or the fiducial marker may uniquely identify the medical device 108 (e.g., a first needleless connector, etc.) from other medical devices (e.g., a second needleless connector, etc.) that include an identifier associated with the same type of medical device.

[0136] The fiducial markers 110 may encapsulate pose information associated with the 3D position of the fiducial markers 110. For example, the fiducial markers 110 may include markers that, when captured in an image, enable calculation of the precise 3D position of the fiducial marker relative to an image capture device that captured the image (e.g., the x, y, z coordinate position of the fiducial marker, etc.) and / or the precise two-dimensional (2D) position of the fiducial marker in the image itself (e.g., the x, y coordinate position of the fiducial marker in the image, etc.).

[0137] In some non-limiting embodiments or aspects, the fiducial marker 110 may include an AprilTag. For example, the fiducial marker 110 may include an AprilTag V3 of type customTag 48h12, which enables the use of AprilTag V3 detection to determine a unique ID and / or position of the fiducial marker 110 in the field-of-view (FOV) of the image acquisition device (e.g., x, y, and z coordinates, direction vectors of the Z axis, Y axis, and X axis, etc.), the unique ID may indicate (e.g., in leading digits, etc.) the type of medical device 108 associated with the fiducial marker and / or (e.g., in trailing digits, etc.) a unique serial number of the specific medical device 108. However, non-limiting embodiments or aspects are not limited to this, and the reference marker 110 may include a two-dimensional (QR) code, a barcode (e.g., a one-dimensional (1D) barcode, a 2D barcode, etc.), an Aztec code, a Data Matrix code, an ArUco mark, a color pattern, a reflective pattern, a fluorescent pattern, a predefined shape and / or color (e.g., a red pentagon, a blue hexagon, etc.), an LED pattern and / or a hologram, etc., which encapsulates an identifier associated with the type of medical device 108 associated with the reference marker 110, uniquely identifies the medical device 108 associated with the reference marker 110 from other medical devices, and / or encapsulates posture information associated with the 3D position of the reference marker 110.

[0138] In some non-limiting embodiments or aspects, the fiducial marker 110 may include a color calibration region located adjacent to the variable color region to calibrate the color under a wider range of lighting conditions. For example, for a 2×2 grid, the cell (1,1) at the upper left corner of the grid may include a predefined and / or standard calibration color region (e.g., neutral gray, etc.) that the user device 102 and / or the management system 104 may use to calibrate the colors in the images for detecting or determining the fiducial marker 110 in the images and / or detecting or determining color changes in patient tissue (e.g., patient tissue near an insertion site, etc.) in the images. In such an example, the user device 102 and / or the management system 104 may use the predefined and / or standard calibration color region to orient the fiducial marker 110, to determine how to properly rotate the fiducial marker 110, and to decode the colors in the fiducial marker 110 to decode an identifier encapsulated by the fiducial marker 110 and / or to track the fiducial marker 110 within the environment 100.

[0139] like Figure 3A and Figure 3B As shown, the fiducial markers 110 can be arranged in a ring symmetrically around the axis of the medical device 108 associated with the fiducial markers, which can enable at least one fiducial marker 110 to be presented to the FOV of the image acquisition device regardless of the orientation of the medical device 108. The fiducial marker 110 can be locked so that the direction of the marker (e.g., indicated by its pose information, etc.) is aligned with the proximal direction or distal direction of the fluid flowing through the medical device 108 associated with the fiducial marker. The fiducial marker 110 can be rigidly fixed to the medical device 108 so that the fiducial marker 110 cannot translate along the medical device 108 and / or rotate around the medical device 108 (e.g., rigidly fixed to a rigid portion of the medical device 108 and / or a catheter tree including the medical device 108, etc.), which can reduce the movement and / or distance change of the fiducial marker relative to other fiducial markers and / or medical devices.

[0140] The fiducial markers 110 may be located at or just adjacent to the connection points or ports of the various medical devices 108, such that the fiducial markers 110 on the connected plurality of medical devices 108 are collinear (e.g., parallel, etc.). For example, the fiducial markers 110 on the connected plurality of medical devices 108 that are collinear (e.g., parallel, etc.) in this manner may also be continuous or spaced a known distance apart.

[0141] A single medical device 108 may include one or more sets of fiducial markers 110. For example, Figure 3A and Figure 3BAs shown, the rightmost cap in each of these figures includes a single set of fiducial markers 110 (e.g., where each fiducial marker 110 in the set is identical and / or encapsulates the same information, etc.), and the tube to the immediate left of the cap includes two sets of fiducial markers 110 located at respective connection points of the tube and separated by the tube. In such an example, collinearity between the fiducial markers 110 at each end of the tube may not be guaranteed, and connections between the fiducial markers 110 at each end of the tube may be established by a predefined scheme (e.g., where each fiducial marker 110 in each set of fiducial markers 110 on the same medical device 110 has the same value or different but adjacent values, etc.). Note that the spacing between the connected multiple medical devices 108 may vary (e.g., as shown in FIG. 1 ). Figure 3B ); however, for each possible connection between the medical devices, the interval can be determined and known by the user device 102 and / or the management system 104.

[0142] Reference now Figure 4 , Figure 4 is a flow chart of a non-limiting embodiment or aspect of a process 400 for vascular access management; in some non-limiting embodiments or aspects, one or more of the multiple steps of process 400 may be performed by user device 102 (e.g., one or more devices of a system of user device 102, etc.) (e.g., completely, partially, etc.). In some non-limiting embodiments or aspects, one or more of the multiple steps of process 400 may be performed by another device or group of devices (e.g., management system 104 (e.g., one or more devices of management system 104, etc.)) that is separate from or includes user device 102 (e.g., completely, partially, etc.).

[0143] like Figure 4 As shown, at step 402, process 400 includes acquiring an image. For example, user device 102 may acquire images (e.g., a single image, multiple images, a series of images, etc.) of multiple medical devices 108 acquired by an image acquisition device. As an example, the image acquisition device of user device 102 may acquire images of multiple medical devices 108. In such an example, a nurse may use user device 102 to capture one or more images of a patient's catheter site and / or an infusion pump connected to the catheter site. For example, Figure 5 An example image of a catheter insertion site including multiple medical devices is shown.

[0144] In some non-limiting embodiments or aspects, the image may include a series of images. For example, the image acquisition device of the user device 102 may use a burst acquisition technique (e.g., a "burst mode," a continuous shooting mode, etc.) to acquire a series of images, which may enable the user device 102 to create a second likelihood layer for determining the probability that multiple pairs of medical devices 108 are connected as described in more detail below, thereby improving motion artifacts, angles, distances, and / or missed fiducial marker detection. As an example, the image acquisition device of the user device 102 may acquire a series of images as a live video feed to identify multiple pairs of medical devices 108 that are connected to each other (e.g., identify catheter tree components and generate catheter trees, etc.) when the live video feed is acquired.

[0145] like Figure 4 As shown, at step 404, process 400 includes determining position information. For example, user device 102 may determine position information associated with 3D positions of multiple medical devices 108 relative to the image acquisition device and / or 2D positions of the medical devices 108 in the image itself based on the image. In such an example, determining position information associated with 3D positions of multiple medical devices 108 relative to the image acquisition device and / or 2D positions of multiple medical devices 108 in the image itself may further include determining a type of each medical device in the multiple medical devices 108 based on the image.

[0146] In some non-limiting embodiments or aspects, a first group of medical devices in the plurality of medical devices 108 are associated with a plurality of fiducial markers 110. The plurality of fiducial markers 110 may encapsulate a plurality of identifiers associated with the first group of medical devices and pose information associated with the 3D positions and / or 2D positions of the plurality of fiducial markers 110. In such an example, the user device 102 may determine position information associated with the 3D positions of the first group of medical devices relative to the image acquisition device and / or the 2D positions of the plurality of medical devices 108 in the image itself by determining or identifying the plurality of identifiers 110 associated with the first group of medical devices and the pose information associated with the 3D positions and / or 2D positions of the plurality of fiducial markers 110 based on the image. For example, also refer to Figure 6, the plurality of fiducial markers 110 may include a plurality of AprilTags, and the user device 102 may process the image using AprilTag detection software to determine the type of medical device 108 associated with the plurality of fiducial markers 110 and / or a unique serial number of the particular medical device 108, and calculate the precise 3D position, orientation, and / or identity of the plurality of fiducial markers 110 relative to the image acquisition device that acquired the image, and / or the precise 2D position of the plurality of fiducial markers 110 in the image itself. As an example, for each medical device 108 in the first group of medical devices, the position information associated with the 3D position of the medical device 108 relative to the image acquisition device may be determined as the 3D position of the fiducial marker 110 associated with the medical device 108 relative to the image acquisition device, and / or the position information associated with the 2D position of the medical device 108 in the image itself may be determined as the 2D position of the fiducial marker 110 associated with the medical device 108. In such an example, for each medical device 108 in the first group of medical devices, the 3D position of the fiducial marker 110 associated with the medical device relative to the image acquisition device may include: the x, y, and z coordinates of the fiducial marker 110 and / or the direction vectors of the Z axis, Y axis, and X axis of the fiducial marker 110. In such an example, for each medical device 108 in the first group of medical devices, the 2D position of the fiducial marker 110 in the image itself may include: the x, y coordinates of the fiducial marker 110 in the image and / or the direction vectors of the Y axis and X axis of the fiducial marker.

[0147] In some non-limiting embodiments or aspects, a second group of medical instruments in the plurality of medical instruments are not associated with a fiducial marker. In such an example, the user device 102 may determine or identify the type of the medical instrument, the 3D position of the medical instrument relative to the image acquisition device, and / or the 2D position of the medical instrument in the image itself for each medical instrument in the second group of medical instruments based on the image using one or more existing object detection techniques, thereby determining position information associated with the 3D position of the second group of medical instruments relative to the image acquisition device and / or the 2D position of the second group of medical instruments in the image itself. For example, a medical device 108 without a reference mark or identifier tag can be identified by a user device 102, which processes an image using one or more object detection techniques (e.g., deep learning techniques, image processing techniques, image segmentation techniques, etc.) to identify or determine the medical device 108 in the image, as well as position information associated with the 3D position of the identified medical device 108 relative to the image acquisition device (e.g., including the x, y, and z coordinates of the medical device and the direction vectors of the Z, Y, and X axes of the medical device 108, etc.) and / or the 2D position of the identified medical device in the image itself. For example, deep learning techniques may include bounding box techniques for generating box labels for objects of interest in an image (e.g., medical devices 108, etc.), image masking techniques (e.g., masked fast regional convolutional neural networks (FRCNN) (regional convolutional neural networks (RCNN) or convolutional neural networks (CNN))) for capturing objects of specific shapes in an image (e.g., medical devices 108, etc.), trained neural networks for identifying objects in an image (e.g., medical devices 108, etc.), and / or classifiers for classifying the identified objects into multiple categories or types of objects, etc. As an example, image processing techniques may include cross-correlation image processing techniques, image contrast techniques, and / or binary or color filtering techniques, etc. As an example, different catheter lumens may include unique colors, and image processing may use the color to identify the type of catheter.

[0148] In some non-limiting embodiments or aspects, the user device 102 may process the image data using stereo imaging technology and / or shadow distance technology to determine object data including the distance from the image acquisition system to the detected object and / or the distance between each detected object, and / or the image acquisition system 102 may use multiple cameras, laser focusing technology, LiDAR sensors and / or camera physical magnification functions to acquire image data to determine object data including the distance from the image acquisition system to the detected object and / or the distance between each detected object. In some non-limiting embodiments or aspects, the image acquisition system 102 may use a 3D optical profiler to acquire image data and / or object data including a 3D profile of an object.

[0149] For example, the image acquisition device may include a stereo camera, and / or the position information associated with the 3D position of the plurality of medical devices relative to the image acquisition device may be determined using a structure from motion (SfM) algorithm. As an example, the user device 102 may include a stereo camera setup, which is available in many mobile devices, such as Tablet computer, cell phone, Tablets and / or Mobile phones, etc. The user device 102 can process the images from the stereo camera using an SfM algorithm to extract 3D information that can enhance object feature recognition of the fiducial markers 110 of the first group of medical devices and / or object feature recognition of medical devices in the second group of medical devices without fiducial markers. As an example, the SfM processing can improve the extraction of 3D features of medical devices in the second group of medical devices without fiducial markers, which can improve the chance of image feature accumulation, for example, by using a continuous image acquisition / video mode that acquires images with appropriate orientation / alignment (e.g., pan / tilt, etc.) based on the settings or positions of the medical devices 108 and / or the anatomical locations of these medical devices on the patient, wherein a catheter tree is constructed by starting from a dressing tag and connecting the center point or centroid of the medical device 108 detected using object recognition technology to other medical devices 108 with or without fiducial markers 110. As another example, these 3D features extracted using SfM processing can be used to calculate the coplanarity of the medical device 108 (e.g., for generating catheter trees, etc.), which can provide additional advantages in multi-lumen and multi-tube catheter settings by reducing missed connections that may occur in 2D single-plane space due to pseudo-collinearity.

[0150] For example, the image acquisition device may include a LiDAR system, and the image may include a LiDAR point cloud. As an example, the user device 102 may include a mini-LiDAR system, which is used in many mobile devices (e.g., Tablet computer, cell phone, Tablets and / or In such an example, the use of LiDAR images can improve the accuracy of 3D feature detection because LiDAR images directly provide 3D world information as a point cloud, which can accelerate 3D data collection with reduced or minimal protocols compared to stereo settings. For example, user device 102 can use existing image registration and / or transformation techniques to overlay 2D object information (e.g., color and / or texture, etc.) from camera images with the 3D LiDAR point cloud to detect 3D features for enhancing duct tree generation and connection accuracy, which can also improve augmented reality generation and environment reconstruction, as well as guide duct tree generation and connectivity determination.

[0151] For example, also refer to Figure 7 , Figure 7 is a stereoscopic image of an example catheter insertion site on a patient, due to the positioning of the AprilTag and the different tubes, the likelihood of mismatched tree generation (e.g., incorrect determination of connections between medical devices, etc.) is high because the fiducial markers 110 and / or medical devices 108 appear to be co-linear in 2D due to their proximity. The user device 102 can use the above-described stereo / SfM and / or LiDAR image-based methods for determining 3D features of the fiducial markers 110 and / or medical devices 108 to improve coplanar information and / or provide more accurate catheter tree generation (e.g., more accurate determination of connections between devices, etc.).

[0152] like Figure 4 As shown, at step 406, the process 400 includes determining a plurality of pairs of medical devices that are connected to each other. For example, the user device 102 may determine a plurality of pairs of medical devices that are connected to each other among the plurality of medical devices 108 based on the position information and / or the type of the plurality of medical devices 108. As an example, for each pair of medical devices among the plurality of medical devices 108, the user device 102 may determine a probability that the pair of medical devices are connected to each other based on the 3D position information associated with the pair of medical devices, the 2D position information associated with the pair of medical devices, and / or the type of the pair of medical devices. In such an example, the user device 102, for each medical device among the plurality of medical devices 108, the medical device may be determined to be connected to another medical device in a pair of medical devices that includes the medical device, and the pair of medical devices is associated with the highest probability of the plurality of pairs of medical devices that include the medical device.

[0153] For example, for each pair of medical devices among the plurality of medical devices, the user device 102 may determine the following parameters based on the location information associated with the pair of medical devices: the distance between the center points associated with the pair of medical devices; the angular difference between the orientations of the pair of medical devices; and / or the angle of deviation of the pair of medical devices from the collinearity, and the probability that the pair of medical devices are connected may be determined based on the distance between the center points of the pair of medical devices, the angular difference between the orientations of the pair of medical devices, and / or the angle of deviation of the pair of medical devices from the collinearity. As an example, also refer to Figure 8 , for each pair of reference markers among the multiple reference markers 110a, 110b and 110c, the user device 102 can determine the following parameters based on the 3D position information and / or 2D position information associated with the pair of reference markers: the distance between the center points of the pair of reference markers (e.g., proximity, etc.); the angular difference between the orientations of the pair of reference markers (e.g., orientation, etc.); and / or the angle of deviation from collinearity of the pair of reference markers (e.g., collinearity, etc.), and the probability that a pair of medical devices associated with the pair of reference markers are connected can be determined based on the determined proximity, orientation and / or collinearity (e.g., the angular difference in orientation and angle generated by the tag orientation and the connection vector, etc.). Although in Figure 8 110, but the non-limiting embodiments or aspects are not limited thereto, and the proximity, orientation and / or colinearity between medical devices may be determined between multiple pairs of medical devices without reference markers, and / or between multiple pairs of medical devices including a single medical device associated with a reference marker and a single medical device without a reference marker.

[0154] In some non-limiting embodiments or aspects, the user device 102 may use probability-based tree building logic or rule sets (e.g., predefined rule sets, etc.) to determine a pair of interconnected medical devices 108. As an example, the user device 102 may use the above parameters: proximity, orientation, and / or colinearity (and / or one or more additional parameters, such as the X-axis distance and the Y-axis distance between the pair of medical devices, and / or the depth difference between the pair of medical devices and the image acquisition device, etc.) to determine the probability of each medical device 108 connecting to each of the other medical devices, and when applying the probability-based tree building logic or rule set to determine the pair of interconnected medical devices 108, the user device 102 may assign a predefined weight to each parameter for the total probability of the pair of medical devices being connected to each other (e.g., the sum of the weights of the various parameters may be 1, etc.). In such an example, the user device 102 can process multiple pairs of medical devices 108 by using the dressing tags and / or intraluminal adapters as starting points or anchors for generating a catheter tree or a representation of one or more IV lines, and for each medical device, the medical device can be determined to be connected to the other medical device in the pair of medical devices that has the highest probability of connection to the medical device.

[0155] In such an example, the user device 102 can identify a group of medical devices associated with a preferred IV line architecture from among the plurality of medical devices based on the type of each of the plurality of medical devices. For a pair of medical devices included in the group of medical devices associated with the preferred IV line architecture, the user device 102 can adjust the weights used to determine whether the pair of medical devices are connected to each other (e.g., a known preferred architecture can receive a higher weight in the connection determination logic, etc.). As an example, if the user device identifies in an image each of the plurality of medical devices or disposables required to generate a preferred architecture connection for each IV line, the user device 102 can determine the connection between the pair of medical devices by assigning a higher probability to a preferred connection including a plurality of pairs of medical devices connected in a preferred architecture (e.g., an inner cavity adapter connected to an IV tube, etc.). For example, when the medical devices are determined to be within a threshold proximity or distance of each other, a proximity or distance parameter of a pair of preferred architecture components can be assigned a higher weight than other parameters (e.g., orientation, colinearity, etc.). In some non-limiting embodiments or aspects, the user device 102 can prompt the user to retake an image and / or provide the user with a notification of these atypical parameters (e.g., asking whether there are multiple catheter components in a single image, etc.) in response to determining atypical parameters associated with a pair of medical devices (e.g., the distance between the dressing and the inner cavity adapter is a threshold distance, such as 30 cm, etc.).

[0156] In some non-limiting embodiments or aspects, the user device 102 may adjust the weight used to determine whether a pair of medical devices are connected to each other based on a determination that one medical device in a pair of medical devices is connected to another medical device (e.g., another medical device in a preferred IV line architecture that includes the pair of medical devices). For example, for a pair of medical devices including a first medical device and a second medical device, if the user device determines that the first medical device has been connected to a third medical device in a preferred IV line architecture (the preferred IV line architecture includes the first medical device, the second medical device, and the third medical device), the user device 102 may assign a higher probability that the first medical device and the second medical device are connected because such a connection implements the preferred IV line architecture.

[0157] In such an example, if the user device 102 identifies in the image only a portion of the multiple medical devices or disposables required to generate a preferred architecture connection for each IV line, the user device 102 may determine a connection between a pair of medical devices by assigning a greater probability to the preferred connections, which include multiple pairs of medical devices connected in the preferred architecture and having medical devices of predefined types (e.g., devices that are not caps, etc.). For example, if a triple lumen catheter is expected for the preferred architecture and only a single IV tube is identified in the image, the user device 102 may automatically expect other lumens or caps on lumen adapters, and if the user device 102 does not identify a cap in the image, the user device 102 may prompt the user to retake the image and / or provide a notification to the user requesting clarification.

[0158] In such an example, the user device 102 can determine that none of the multiple medical devices are associated with the preferred IV line architecture based on the type of each of the multiple medical devices. For example, in response to determining that none of the multiple medical devices are associated with the preferred IV line architecture, the user device 102 can prompt the user to acquire another image.

[0159] In such an example, the user device 102 can determine that the number of medical devices in the multiple medical devices is greater than the number of medical devices associated with the preferred IV line architecture based on the type of each medical device in the multiple medical devices. For example, if the number of identified medical devices is greater than the number required to generate the preferred architecture connection for each inner cavity or IV line, it means that there may be daisy-chaining or multiple marked components in the image. As an example, if the user device 102 identifies more IV tube sets than catheter lumens, the user device 102 can give a greater weight to multiple tubes to IV tube y-port connections in the probability-based tree building logic. As another example, if the user device 102 identifies a threshold number of caps, the user device 102 can give a greater weight to a proximity parameter used to detect the distance of a medical device to an open port.

[0160] Reference now Fig. 9 , Fig. 9 is a diagram of examples of atypical but possible connections between medical devices. For example, the connection probability of medical devices of the same category or type may be zero (tubes may be an exception - however, tubes may have secondary tube Y-port labels). For example, an atypical connection between medical devices 108 may be an unexpected and / or purposeless connection between medical devices; however, such a connection may not be incorrect and / or may be potentially initiated by some users. Loose dressings and / or dressing fiducial markers 110 may be left around the catheter insertion site and appear to be close to the tube set or other identified medical devices, and the user device 102 may adjust the weight or prioritize the proximity or distance between the dressing label and the catheter lumen adapter, and the label vector angle between each other in the probability-based tree building logic to determine that these loose fiducial markers or labels are not attached to any medical device in multiple medical devices. Loose caps may float around on a bed or patient near other labeled objects, and if the distance between the cap and another medical device meets the predefined threshold distance, the user device 102 may automatically determine that the cap is not connected to the other medical device. Loose tubing on the bed or patient may be handled in the same or similar manner as loose caps. It is atypical, but possible, for the lumen adapters to be connected to each other, and the user device 102 may determine whether the two adapters are connected to each other based on the distance and / or colinearity between the two adapters.

[0161] In some non-limiting embodiments or aspects, the user device 102 may process the location information and / or type of the plurality of medical devices 108 with a machine learning model to determine the probability that the plurality of pairs of medical devices are connected. For example, the user device 102 may generate a prediction model (e.g., an estimator, a classifier, a prediction model, a detector model, etc.) using a machine learning technique including, for example, supervised and / or unsupervised techniques, such as decision trees (e.g., gradient boosted decision trees, random forests, etc.), logistic regression, artificial neural networks (e.g., convolutional neural networks, etc.), Bayesian statistics, learning automata, hidden Markov modeling, linear classifiers, quadratic classifiers, and / or association rule learning, etc. The prediction machine learning model may be trained to provide an output including a prediction of whether a pair of medical devices are connected to each other. In such an example, the prediction may include the probability (e.g., likelihood, etc.) that the pair of medical devices are connected to each other.

[0162] The user device 102 may generate a prediction model based on the location information associated with each medical device and / or the type of each medical device (e.g., training data, etc.). In some embodiments, the prediction model is designed to receive the location information associated with each medical device in a pair of medical devices (e.g., the proximity between each device, the orientation between each device, the collinearity between each device, etc.) as input, and provide a prediction (e.g., probability, possibility, binary output, yes-no output, score, prediction score, classification, etc.) about whether the pair of medical devices are connected to each other as output. In some non-limiting embodiments or aspects, the user device 102 stores the prediction model (e.g., stores the model for subsequent use). In some non-limiting embodiments or aspects, the user device 102 stores the initial prediction model in a data structure (e.g., a database, a linked list, a tree, etc.). In some non-limiting embodiments, the data structure is located inside the user device 102 or outside the user device 102 (e.g., away from the user device 102) (e.g., in the management system 104, etc.).

[0163] like Figure 4 As shown, at step 408, process 400 includes generating a representation of at least one IV line. For example, user device 102 may generate a representation of at least one IV line including the plurality of pairs of medical devices determined to be connected to each other based on the plurality of pairs of medical devices determined to be connected to each other. As an example, also refer to Fig.10 , Fig.10In a non-limiting embodiment or aspect of a representation of IV lines (e.g., a catheter tree, etc.), the user device 102 can automatically draw lines connecting various medical devices (e.g., catheter tree components, etc.) for each IV line, and / or display identification information associated with each IV line and / or various medical devices 108 in each IV line. In such an example, the user device 102 can automatically draw and display lines on an image of a medical device / catheter insertion site and / or within a series of images (e.g., a live video feed, etc.). For example, the user device 102 can generate a digital representation of each IV line including each pair of medical devices in each IV line based on multiple pairs of medical devices determined to be connected to each other. In such an example, the user device 102 can associate each IV line with a fluid source or pump of an infusion pump and monitor fluid flow in one or more IV lines based at least in part on the representation of the fluid flow path. As an example, the user device 102 can control an audio output device and / or a visual output device to output an audible indication and / or a visual indication, wherein the audible indication and / or the visual indication indicates the status of the IV line and / or the fluid flowing therethrough. For example, the user device 102 can generate a catheter tree or a logical IV branching structure that is mapped onto the physical IV branching structure and includes a unique node identifier for each medical device of the physical IV branching structure, each connector or entry / exit point of a fluid flow path formed by the medical device, and / or each element of the medical device associated with an action that can affect the fluid flow path (e.g., a valve in a medical device).

[0164] In some non-limiting embodiments or aspects, the image acquisition device of the user device 102 can acquire multiple images from multiple different fields of view or positions. Fig.11 , Fig.11 An example catheter tree construction sequence is shown, and the image acquisition device of the user device 102 can use a burst acquisition technique to acquire a series of images from multiple different fields of view or positions (e.g., a first field of view or position including an insertion site on a patient, a second field of view or position including an infusion pump, etc.). The series of images can include marked and / or unmarked medical devices 108. The user device 102 can continuously integrate and / or combine the position information associated with the medical device 108 determined from each image in the series of images and each series of images acquired from each field of view or position, and use the integrated position information to determine multiple pairs of medical devices 108 that are connected to each other, and build a catheter tree that includes IV lines formed by multiple pairs of medical devices that are determined to be connected to each other (e.g., a catheter tree including medical devices from an insertion site and / or a dressing tag to an infusion pump or module, etc.).

[0165] In some non-limiting embodiments or aspects, the user device 102 can compare the medication, medication dose, medication delivery route or IV line, and / or medication delivery time associated with the IV line to an approved patient, approved medication, approved medication dose, approved medication delivery route or IV line, and / or approved medication delivery time associated with a patient identifier and / or medication identifier to reduce medication errors. The user device 102 can issue an alarm and / or cause an infusion pump to stop fluid flow and / or adjust fluid flow based on a current representation of at least one IV line (e.g., based on a current state of a catheter tree, etc.). For example, if a drug arranged for or loaded into an infusion pump at an entry point into a fluid flow path is determined to be an inappropriate drug for the patient, an inappropriate dosage for the patient and / or drug, an inappropriate drug delivery route for the patient and / or drug (e.g., an inappropriate entry point into the fluid flow path), and / or an inappropriate drug delivery time for the patient and / or drug, the user device 102 can issue an alarm and / or control the infusion pump to stop or prevent fluid flow.

[0166] In some non-limiting embodiments or aspects, the user device 102 may determine the dwell time of the medical device 108 (e.g., in the environment 100, etc.) and / or the dwell time of its connection (e.g., the amount of time or duration that the medical device is connected to another medical device and / or patient, etc.). For example, the user device 102 may determine the time when the medical device 108 enters the environment 100 and / or is connected to another medical device and / or patient based on the probability that multiple pairs of medical devices are connected. As an example, the user device 102 may automatically determine and / or record the time when the medical device 108 is connected to another medical device and / or patient, the duration from the connection time to the current time to which the medical device 108 has been connected, and / or the time when the medical device is disconnected from another medical device and / or patient based on multiple pairs of medical devices that are determined to be connected to each other (e.g., over a period of time, over a series of images, over a live video feed, etc.).

[0167] In some non-limiting embodiments or aspects, user device 102 may automatically determine and / or record the frequency with which medical device 108 is connected to another medical device or a particular type of medical device based on multiple pairs of medical devices that are determined to be connected to each other (e.g., over a period of time, over a series of images, over a live video feed, etc.). For example, user device 102 may determine the frequency with which one or more sterile caps are connected to an IV access port and / or luer tip, etc. and / or the duration that each cap is connected to an IV access port and / or luer tip.

[0168] In some non-limiting embodiments or aspects, the user device 102 may compare the dwell time and / or connection frequency associated with the medical device to a dwell time threshold and / or frequency threshold associated with the medical device and / or the connection including the medical device, and if the dwell time and / or connection frequency meets the dwell time threshold and / or frequency threshold, provide an alert related thereto (e.g., via the user device 102, etc.). For example, the user device 102 may provide an alert indicating that it is time to replace the medical device in the catheter tree with a new medical device and / or that the medical device should be sterilized and / or flushed.

[0169] Although various embodiments or aspects have been described in detail for the purposes of illustration and description, it will be understood that such details are for the purposes of such illustration and description only, and that the embodiments or aspects are not limited to the disclosed embodiments or aspects, but, on the contrary, are intended to cover modifications and equivalent arrangements within the spirit and scope of the appended claims. For example, it will be understood that the present disclosure contemplates that, to the extent possible, one or more features of any embodiment or aspect may be combined with one or more features of any other embodiment or aspect. In fact, many of these features may be combined in ways that are not specifically recited in the claims and / or disclosed in the specification. Although each dependent claim listed below may be directly subordinate to only one claim, the disclosure of possible implementations includes the combination of each dependent claim with each other claim in the claim set.

Claims

1. A system comprising: at least one processor programmed and / or configured to: Acquiring images of a plurality of medical devices acquired by an image acquisition device; determining, based on the image, position information associated with a three-dimensional (3D) position of the plurality of medical devices relative to the image acquisition device; Based on the location information, determining a plurality of pairs of medical devices connected to each other among the plurality of medical devices; as well as Based on the plurality of pairs of medical devices determined to be connected to each other, a representation of at least one intravenous (IV) line including the plurality of pairs of medical devices determined to be connected to each other is generated.

2. The system according to claim 1, wherein: The at least one processor is programmed and / or configured to determine the plurality of pairs of medical devices connected to each other by: For each pair of medical devices in the plurality of medical devices, a probability that the pair of medical devices are connected to each other is determined based on the position information associated with the pair of medical devices.

3. The system according to claim 2, wherein: The at least one processor is programmed and / or configured to determine the plurality of pairs of medical devices connected to each other by: For each pair of medical devices among the multiple medical devices, the following parameters are determined based on the position information associated with the pair of medical devices: the distance between center points associated with the pair of medical devices; the angular difference between the orientations of the pair of medical devices; and the angle of deviation of the pair of medical devices from collinearity, wherein the probability that the pair of medical devices are connected is determined based on the distance between center points of the pair of medical devices, the angular difference between the orientations of the pair of medical devices, and the angle of deviation of the pair of medical devices from collinearity.

4. The system according to claim 2, wherein: For each medical device in the plurality of medical devices, the medical device is determined to be connected to another medical device in a pair of medical devices that includes the medical device, the pair of medical devices being associated with a highest probability of multiple pairs of medical devices that include the medical device.

5. The system according to claim 2, wherein: The at least one processor is programmed and / or configured to determine the position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device by: A type of each of the plurality of medical devices is determined based on the image, wherein, for a pair of medical devices in the plurality of medical devices, the probability that the pair of medical devices are connected to each other is also determined based on the type of each of the pair of medical devices.

6. The system according to claim 5, wherein: The at least one processor is programmed and / or configured to determine the plurality of pairs of medical devices connected to each other by: identifying, based on the type of each medical device in the plurality of medical devices, a set of medical devices in the plurality of medical devices that are associated with a preferred IV line architecture; as well as For a pair of medical devices included in the set of medical devices associated with the preferred IV line architecture, weights used to determine whether the pair of medical devices are connected to each other are adjusted.

7. The system according to claim 5, wherein: The at least one processor is programmed and / or configured to determine the plurality of pairs of medical devices connected to each other by: determining, based on the type of each medical device in the plurality of medical devices, that no medical device in the plurality of medical devices is associated with a preferred IV line architecture; as well as In response to determining that none of the plurality of medical devices is associated with the preferred IV line architecture, a user is prompted to acquire another image.

8. The system according to claim 1, wherein: A first group of medical devices of the plurality of medical devices is associated with a plurality of fiducial markers, wherein the plurality of fiducial markers encapsulate a plurality of identifiers associated with the first group of medical devices and pose information associated with 3D positions of the plurality of fiducial markers, and wherein the at least one processor is programmed and / or configured to determine the position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device by: determining, based on the image, the plurality of identifiers associated with the first set of medical devices and the pose information associated with the 3D positions of the plurality of fiducial markers, Wherein, for each medical device in the first group of medical devices, the position information associated with the 3D position of the medical device relative to the image acquisition device is determined as the 3D position of a reference marker associated with the medical device relative to the image acquisition device.

9. The system according to claim 8, wherein: The plurality of fiducial markers include a plurality of AprilTags.

10. The system according to claim 8, wherein: For each medical device in the first group of medical devices, the 3D position of the reference marker associated with the medical device relative to the image acquisition device includes: the x, y and z coordinates of the reference marker and the direction vectors of the Z axis, Y axis and X axis of the reference marker.

11. The system according to claim 8, wherein: The plurality of identifiers are associated with a plurality of types of medical devices.

12. The system according to claim 8, wherein: The plurality of identifiers includes a plurality of unique identifiers.

13. The system according to claim 8, wherein: A second group of medical devices in the plurality of medical devices are not associated with a fiducial marker, and wherein the at least one processor is programmed and / or configured to determine the position information associated with the 3D position of the plurality of medical devices relative to the image acquisition device by: For each medical device in the second group of medical devices, a type of the medical device and a 3D position of the medical device relative to the image acquisition device are determined based on the image using object recognition techniques.

14. The system of claim 1, wherein: The at least one processor is programmed and / or configured to further acquire the images of the plurality of medical devices by: The images of the plurality of medical devices are acquired using the image acquisition device.

15. The system of claim 14, wherein: The image comprises a series of images.

16. The system of claim 15, wherein: The image acquisition device uses continuous shooting acquisition technology to acquire the series of images.

17. The system of claim 14, wherein: The image acquisition device comprises a stereo camera, and wherein the position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device is determined using a structure from motion (SfM) algorithm.

18. The system of claim 14, wherein: The image acquisition device comprises a LiDAR system, and wherein the image comprises a LiDAR point cloud.

19. The system of claim 1, wherein: The at least one processor is programmed and / or configured to generate a representation of the at least one IV by automatically displaying on the image lines connecting the plurality of pairs of medical devices determined to be connected to each other in the at least one IV line.

20. The system of claim 1, wherein: The at least one IV line is associated with at least one pump of the infusion pumps in the representation.

21. The system of claim 8, wherein: The plurality of fiducial markers are rigidly fixed to a rigid portion of the first group of medical instruments such that the plurality of fiducial markers cannot translate along and rotate about the first group of medical instruments.

22. The system of claim 1, wherein: The at least one processor is programmed and / or configured to: determining a dwell time based on the plurality of pairs of medical devices determined to be connected to each other, the dwell time indicating a duration of time that one of the plurality of medical devices is connected to another of the plurality of medical devices; and In response to the dwell time satisfying a threshold dwell time, providing an alert associated with the medical instrument via the user device.

23. A method comprising: acquiring, using at least one processor, images of a plurality of medical devices acquired by an image acquisition device; determining, using at least one processor, position information associated with three-dimensional (3D) positions of the plurality of medical devices relative to the image acquisition device based on the image; using the at least one processor, determining a plurality of pairs of medical devices connected to each other among the plurality of medical devices based on the position information; as well as Using the at least one processor, based on the plurality of pairs of medical devices determined to be connected to each other, a representation of at least one intravenous (IV) line including the plurality of pairs of medical devices determined to be connected to each other is generated.

24. The method according to claim 23, wherein: Determining the plurality of pairs of medical devices connected to each other further comprises: For each pair of medical devices in the plurality of medical devices, a probability that the pair of medical devices are connected to each other is determined based on the position information associated with the pair of medical devices.

25. The method according to claim 24, wherein: Determining the plurality of pairs of medical devices connected to each other further comprises: For each pair of medical devices among the multiple medical devices, the following parameters are determined based on the position information associated with the pair of medical devices: the distance between center points associated with the pair of medical devices; the angular difference between the orientations of the pair of medical devices; and the angle of deviation of the pair of medical devices from collinearity, wherein the probability that the pair of medical devices are connected is determined based on the distance between center points of the pair of medical devices, the angular difference between the orientations of the pair of medical devices, and the angle of deviation of the pair of medical devices from collinearity.

26. The method according to claim 24, wherein: For each medical device in the plurality of medical devices, the medical device is determined to be connected to another medical device in a pair of medical devices that includes the medical device, the pair of medical devices being associated with a highest probability of the plurality of pairs of medical devices that include the medical device.

27. The method according to claim 24, wherein: Determining the position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device further comprises: A type of each of the plurality of medical devices is determined based on the image, wherein, for a pair of medical devices in the plurality of medical devices, the probability that the pair of medical devices are connected to each other is also determined based on the type of each of the pair of medical devices.

28. The method according to claim 27, wherein: Determining the plurality of pairs of medical devices connected to each other further comprises: identifying, based on the type of each medical device in the plurality of medical devices, a set of medical devices in the plurality of medical devices that are associated with a preferred IV line architecture; and For a pair of medical devices included in the set of medical devices associated with the preferred IV line architecture, weights used to determine whether the pair of medical devices are connected to each other are adjusted.

29. The method according to claim 27, wherein: Determining the plurality of pairs of medical devices connected to each other further comprises: determining, based on a type of each of the plurality of medical devices, that no medical device in the plurality of medical devices is associated with a preferred IV line architecture; and In response to determining that none of the plurality of medical devices is associated with the preferred IV line architecture, a user is prompted to acquire another image.

30. The method of claim 23, wherein: A first group of medical devices of the plurality of medical devices is associated with a plurality of fiducial markers, wherein the plurality of fiducial markers encapsulate a plurality of identifiers associated with the first group of medical devices and pose information associated with 3D positions of the plurality of fiducial markers, and wherein determining the position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device comprises: determining, based on the image, the plurality of identifiers associated with the first set of medical devices and the pose information associated with the 3D positions of the plurality of fiducial markers, Wherein, for each medical device in the first group of medical devices, the position information associated with the 3D position of the medical device relative to the image acquisition device is determined as the 3D position of a reference marker associated with the medical device relative to the image acquisition device.

31. The method according to claim 30, wherein: The plurality of fiducial markers include a plurality of AprilTags.

32. The method of claim 30, wherein: For each medical device in the first group of medical devices, the 3D position of the reference marker associated with the medical device relative to the image acquisition device includes: the x, y and z coordinates of the reference marker and the direction vectors of the Z axis, Y axis and X axis of the reference marker.

33. The method of claim 30, wherein: The plurality of identifiers are associated with a plurality of types of medical devices.

34. The method of claim 30, wherein: The plurality of identifiers includes a plurality of unique identifiers.

35. The method of claim 30, wherein: A second group of the plurality of medical devices is not associated with a fiducial marker, and wherein determining the position information associated with the 3D position of the plurality of medical devices relative to the image acquisition device further comprises: For each medical device in the second group of medical devices, a type of the medical device and a 3D position of the medical device relative to the image acquisition device are determined based on the image using object recognition techniques.

36. The method of claim 23, wherein: Acquiring the images of the plurality of medical devices further comprises: The images of the plurality of medical devices are acquired using the image acquisition device.

37. The method of claim 36, wherein: The image comprises a series of images.

38. The method of claim 37, wherein: The image acquisition device uses continuous shooting acquisition technology to acquire the series of images.

39. The method of claim 36, wherein: The image acquisition device comprises a stereo camera, and wherein the position information associated with the 3D positions of the plurality of medical devices relative to the image acquisition device is determined using a structure from motion (SfM) algorithm.

40. The method of claim 36, wherein: The image acquisition device comprises a LiDAR system, and wherein the image comprises a LiDAR point cloud.

41. The method of claim 23, wherein: Generating the representation of the at least one IV includes automatically displaying on the image lines connecting the plurality of pairs of medical devices determined to be connected to each other in the at least one IV line.

42. The method of claim 23, wherein: The at least one IV line is associated with at least one pump of the infusion pumps in the representation.

43. The method of claim 30, wherein: The plurality of fiducial markers are rigidly fixed to a rigid portion of the first group of medical instruments such that the plurality of fiducial markers cannot translate along and rotate about the first group of medical instruments.

44. The method of claim 23, further comprising: determining, using the at least one processor, a dwell time based on the plurality of pairs of medical devices determined to be connected to each other, the dwell time indicating a duration that a medical device in the plurality of medical devices is connected to another medical device in the plurality of medical devices; as well as Using the at least one processor, in response to the dwell time satisfying a threshold dwell time, providing, via the user device, an alert associated with the medical instrument.

Images