A pipeline pulling identification non-planned extubation nursing early warning method and system

Abstract

The application relates to the field of medical care information processing and discloses a pipeline pulling identification unplanned extubation care early warning method and system; the method acquires pipeline constraint chain data, continuous pulling monitoring data and nursing operation records of a target patient, generates an individualized pulling baseline, calculates a current pipeline margin and pipeline margin consumption, and carries out event segmentation on the continuous pulling monitoring data to extract a pulling fingerprint; according to the pulling fingerprint, the current pipeline margin, the individualized pulling baseline and a nursing operation window, pulling of an extubation risk, fixed point failure pulling, nursing operation pulling, equipment pulling and body position pulling are identified; when the pulling is identified as fixed point failure pulling or pulling of an extubation risk, a graded nursing early warning is generated, and the individualized pulling baseline and early warning parameters are updated according to a disposal result fed back by a nurse terminal. The application can distinguish normal nursing disturbance and pulling of an extubation risk, and reduce false positives and false negatives.

Description

Technical Field

[0001] This invention relates to the field of medical and nursing information processing, specifically to a method and system for early warning of unplanned extubation nursing based on tubing traction identification. Background Technology

[0002] Hospitalized patients receiving intensive care, postoperative recovery, intravenous therapy, drainage care, or respiratory support typically require indwelling tubing such as endotracheal tubes, central venous catheters, PICC lines, drainage tubes, gastric tubes, and urinary catheters. One end of these tubing connects to the patient's insertion site or a surface fixation point, while the other end connects to external devices such as infusion pumps, drainage bottles, urine bags, or ventilator interfaces. These tubing is easily pulled during patient turning, nursing procedures, and equipment movement.

[0003] Current methods for early warning of unplanned extubation mostly rely on manual risk assessment, camera recognition of patient hand movements, catheter position change detection, or single-point traction alarms. Manual risk assessment mainly reflects static factors such as patient consciousness, catheter type, and level of care; video recognition is easily affected by occlusion, lighting, and clothing coverage; single-point traction alarms are usually triggered based on fixed thresholds, making it difficult to reflect the continuous changes in tubing capacity, traction direction, micro-movements at the fixed point, and movement of external equipment.

[0004] In actual nursing care, normal patient turning, suctioning, changing IV fluids, and adjusting the position of external equipment can all cause short-term traction. Loosening of dressings, gradual shift of fixation points, or continuous reduction of tubing capacity can gradually destabilize the tubing. Current methods struggle to promptly distinguish between normal nursing disturbances, equipment traction, fixation point failure, and traction caused by the risk of extubation, leading to false alarms, missed alarms, or delayed alarms. This increases the burden of bedside verification for nurses and hinders the early management of unplanned extubation risks. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method and system for identifying unplanned extubation and providing early warnings, thereby resolving the technical problems existing in the prior art.

[0006] The above-mentioned technical objective of the present invention is achieved through the following technical solution: A method for identifying unplanned extubation care warnings by identifying tubing pull issues includes the following steps: S1: Obtain the tubing constraint chain data corresponding to the target patient. The tubing constraint chain data includes catheter type, catheter insertion site, tubing fixation point location, free segment length, external device location, initial tubing margin, and tubing risk level. S2: Acquire continuous traction monitoring data and nursing operation records corresponding to the tubing constraint chain data. The continuous traction monitoring data includes tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data. S3: During the baseline acquisition period after catheter fixation, an individualized traction baseline matching the target patient and corresponding tubing is generated based on continuous traction monitoring data. The individualized traction baseline includes the baseline tension range, the baseline tension change rate range, the baseline fixation point micro-motion range, and the baseline tubing margin change range. S4: Calculate the current pipeline margin and pipeline margin consumption based on pipeline constraint chain data, pipeline displacement data, fixed point micro-motion data, and external equipment position data; S5: Segment the continuous traction monitoring data into events and extract the traction fingerprints corresponding to the traction events. The traction fingerprints include traction amplitude, traction duration, traction rise rate, traction release rate, traction direction, pipeline margin consumption, and fixed point micro-motion. S6: Determine the nursing operation window based on the nursing operation record. The nursing operation window includes the operation start time, operation end time, and recovery period after the operation ends. S7: Based on the event identification priority, identify the traction event type according to the traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window. The traction event types include postural traction, equipment traction, nursing operation traction, fixation point failure traction, and extubation risk traction. S8: When the traction event type is fixed point failure traction or tube removal risk traction, a graded nursing warning is generated based on the tube risk level, current tube balance, tube balance consumption, fixed point micro-movement and responsible nurse response status, and the graded nursing warning is pushed to the nurse station terminal and the responsible nurse terminal. S9: Receives the treatment results from the responsible nurse's terminal and updates the individualized traction baseline and early warning parameters of the corresponding tubing for the target patient based on the treatment results.

[0007] Preferably, obtaining the tubing constraint chain data corresponding to the target patient includes: Obtain the target patient's bed number, patient identification, catheter type, catheter insertion site, and catheter exposed length; Obtain the location of the catheter fixation point on the patient's body surface, the length of the free segment of the catheter from the fixation point to the external device, the position of the external device relative to the bed reference point, and the direction of the catheter in the bedside area; Based on the catheter insertion site, fixation point location, free tube length, external equipment location, and catheter routing within the bedside area, a tubing constraint chain is formed, consisting of the catheter insertion end, fixation point, free tube length, and external equipment end. The risk level of the tubing is determined based on the type of catheter and the insertion site. The risk levels include Level 1 risk, Level 2 risk, and Level 3 risk.

[0008] Preferably, during the baseline acquisition period after catheter fixation, an individualized traction baseline matching the target patient and corresponding tubing is generated based on continuous traction monitoring data, including: After the catheter is secured and the responsible nurse confirms the fixation via the terminal, the baseline acquisition period begins. During the baseline acquisition period, tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data were collected when the target patient was in a supine, left lateral, right lateral, and head-of-bed elevated position. For the data collected under each condition, calculate the average tension, tension fluctuation range, tension change rate range, fixed point micro-motion range, and pipeline margin change range respectively. The mean tension, tension fluctuation range, tension change rate range, fixed point micro-motion range, and tubing margin change range corresponding to each state are written into the individualized traction baseline of the tubing corresponding to the target patient.

[0009] Preferably, based on pipeline constraint chain data, pipeline displacement data, fixed point micro-motion data, and external equipment position data, the current pipeline margin and pipeline margin consumption are calculated, including: Determine the current pipeline path length from the fixed point to the external equipment end based on the location of the fixed point, the location of the external equipment, and the direction of the conduit in the bedside area; Calculate the current pipeline margin based on the difference between the length of the free pipe segment and the current pipeline path length; Calculate the pipeline margin consumption based on the difference between the initial pipeline margin and the current pipeline margin; When the fixed point micro-motion data indicates that the fixed point position has moved, the current pipeline path length is re-determined based on the fixed point position after the move, and the current pipeline margin and pipeline margin consumption are recalculated.

[0010] Preferably, the continuous traction monitoring data is segmented into events, and the traction fingerprints corresponding to the traction events are extracted, including: Read the continuous traction monitoring data in chronological order of collection time; When one of the following conditions is met: the pipeline tension data exceeds the baseline tension range, the fixed point micro-motion data exceeds the baseline fixed point micro-motion range, or the pipeline margin change exceeds the baseline pipeline margin change range, the corresponding moment will be determined as the start moment of the traction event. When the pipeline tension data, fixed point micro-motion data, and pipeline margin change all return to the range corresponding to the individualized traction baseline, the corresponding time will be determined as the end time of the traction event. Based on continuous traction monitoring data from the start to the end of the traction event, the traction amplitude, traction duration, traction rise rate, traction release rate, traction direction, pipeline margin consumption, and fixed point micro-motion are calculated, and a traction fingerprint is formed. Among them, when the pipeline margin consumption is greater than the pipeline margin consumption corresponding to the previous sampling period in three consecutive sampling periods, it is determined that the pipeline margin consumption is continuously increasing; when the fixed point micro-motion is greater than the fixed point micro-motion corresponding to the previous sampling period in three consecutive sampling periods, it is determined that the fixed point micro-motion is continuously increasing.

[0011] Preferably, the pulling direction is determined based on the path vector from the fixed point to the external equipment end, the micro-motion direction of the fixed point, and the pipeline displacement direction, including: Establish a path vector from the fixed point to the external device based on the location of the fixed point and the location of the external device; The direction of the fixed point's micro-motion is determined based on the change in the fixed point's position between adjacent sampling times; The direction of pipeline displacement is determined based on pipeline displacement data at adjacent sampling times; When both the direction of the fixed point micro-motion and the direction of the pipeline displacement are in the same direction as the path vector, the pulling direction is determined to point towards the external equipment end; When both the direction of the fixed point micro-motion and the direction of the pipeline displacement deviate from the path vector and point to the outside of the catheter insertion site, the pulling direction is determined to point to the outside of the catheter insertion end.

[0012] Preferably, the nursing operation window is determined based on the nursing operation record, including: Read the bedside scanning records, turning care records, suction care records, infusion change records, catheter fixation inspection records and restraint status inspection records generated by the responsible nurse's terminal; Match nursing operation records corresponding to the same bed number, the same patient identification, and the same catheter type with the tubing constraint chain data corresponding to the target patient; The start time of the operation is determined based on the start time of the operation in the matched nursing operation record, and the end time of the operation is determined based on the completion time of the operation. Based on the type of nursing procedure, the recovery time corresponding to the type of nursing procedure is read from the warning parameters of the corresponding tubing for the target patient; The recovery period is defined as the time after the end of the operation, and the nursing operation window is formed by the start time of the operation, the end time of the operation, and the recovery period.

[0013] Preferably, the step of identifying the traction event type according to event identification priority, based on traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window, includes: When the patient's position data changes before the tubing tension data, and after the traction event ends, the tubing tension data, fixation point micro-motion data, and current tubing margin all return to the range corresponding to the individualized traction baseline, the traction event is identified as positional traction. When the location data of the external device changes before the pipeline tension data, and the pulling direction is towards the end of the external device, the pulling event is identified as device pulling. When a traction event occurs within the nursing operation window, and the tubing tension data, fixation point micro-motion data, and current tubing margin all recover to the range corresponding to the individualized traction baseline during the recovery period, the traction event is identified as nursing operation traction. When the micromoment of the fixed point continues to increase, and the direction of the micromoment of the fixed point is consistent with the direction of the pull, the pull event is identified as fixed point failure pull. When the consumption of tubing margin continues to increase, the pulling direction is directed to the outside of the catheter insertion end, the micromotion of the fixation point exceeds the baseline fixation point micromotion range, and the pulling release rate is lower than the lower limit of the release rate in the baseline tension change rate range, the pulling event is identified as a tube removal risk pulling event. When the same traction event simultaneously meets the identification conditions corresponding to fixed-point failure traction and tube removal risk traction, the same traction event is identified as tube removal risk traction.

[0014] Preferably, a graded nursing early warning system is generated based on the pipeline risk level, current pipeline balance, pipeline balance consumption, fixed-point micro-movement, and the responsible nurse's response status, including: When the traction event type is fixed point failure traction, and the current pipeline margin is not lower than the margin lower limit, a level 1 nursing warning is generated; When the traction event type is extubation risk traction, and one of the following conditions is met: the current tubing balance is lower than the lower limit of the balance, or the micro-motion of the fixation point exceeds the baseline micro-motion range of the fixation point, a level 2 nursing warning is generated. When the traction event type is extubation risk traction, and all three conditions are met—the current tubing remaining amount is lower than the lower limit of the remaining amount, the micro-movement of the fixation point exceeds the baseline fixation point micro-movement range, and the responsible nurse's terminal does not provide feedback confirmation within the response time—a level three nursing warning is generated. The lower limit of the margin is determined based on the catheter type, catheter insertion site, and initial tubing margin, and is written into the warning parameters of the corresponding tubing for the target patient; The response time is determined based on the risk level of the tubing and is written into the early warning parameters of the tubing corresponding to the target patient.

[0015] A nursing early warning system for identifying unplanned extubation by identifying tubing traction includes a nursing early warning server, a nurse station terminal, and a terminal for the responsible nurse; The nursing early warning server includes a processor, memory, a traction monitoring data access interface, a nursing operation record access interface, and an early warning push interface; The memory stores computer programs, tubing constraint chain data, continuous traction monitoring data, nursing operation records, individualized traction baselines, and early warning parameters. The traction monitoring data access interface is used to receive continuous traction monitoring data corresponding to the target patient. The continuous traction monitoring data includes tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data. The nursing operation record access interface is used to receive nursing operation records generated by the responsible nurse's terminal; When a processor executes a computer program, it performs the following steps: Obtain the tubing constraint chain data corresponding to the target patient; An individualized traction baseline is generated based on continuous traction monitoring data, matching the target patient and corresponding tubing. Based on pipeline constraint chain data, pipeline displacement data, fixed point micro-motion data, and external equipment position data, calculate the current pipeline margin and pipeline margin consumption. The continuous traction monitoring data is segmented into events, and the traction fingerprints corresponding to the traction events are extracted. Determine the nursing operation window based on the nursing operation record; The pulling direction is determined based on the path vector from the fixed point to the external equipment end, the direction of the fixed point's micro-motion, and the direction of the pipeline displacement. Based on the event identification priority, the traction event type is identified according to the traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window; When the traction event type is fixation failure traction or tube removal risk traction, a graded nursing warning is generated based on the tube risk level, current tube balance, tube balance consumption, fixation point micro-movement, and the responsible nurse's response status. The tiered nursing care alerts are sent to the nurse station terminal and the responsible nurse terminal via the alert push interface; Receive the treatment results from the responsible nurse's terminal and update the individualized traction baseline and early warning parameters of the corresponding tubing for the target patient based on the treatment results.

[0016] In summary, the present invention has the following main beneficial effects: This application establishes a tubing constraint chain consisting of the catheter insertion end, tubing fixation point, free tubing segment, and external device end. It then calculates the current tubing reserve and its consumption by combining tubing tension data, tubing displacement data, fixation point micro-motion data, and external device position data. This allows for the identification of continuous tubing reserve consumption before the tubing is completely removed. Compared to methods that only trigger alarms when the tension exceeds a fixed threshold or the catheter position changes significantly, this application transforms the tubing pulling process into a continuously assessable data state, enabling nursing warnings to correspond earlier to the process of tubing fixation instability and the formation of extubation risk.

[0017] This application creates a traction fingerprint by extracting traction amplitude, traction duration, traction ascent rate, traction release rate, traction direction, tubing residual consumption, and fixation point micromotion. It then identifies traction event types in the order of extubation risk traction, fixation point failure traction, nursing operation traction, equipment traction, and body position traction, thus distinguishing different traction sources. Therefore, the system will not directly identify unplanned extubation risk simply because the patient turns over, the nurse changes the infusion, performs suctioning, or moves external equipment, nor will it miss fixation failure due to slow loosening of the fixation point but a low peak traction force. This makes the warning results more relevant to bedside nursing scenarios.

[0018] This application transforms nursing operation records into a nursing operation window that includes the start time, end time, and recovery period of the operation. It then updates the individualized traction baseline and early warning parameters based on the treatment results reported by the responsible nurse's terminal, achieving continuous correction of the patient's individual tubing fixation status. Data corresponding to normal position changes, equipment traction, and nursing operation traction are entered into the individualized traction baseline update sample, while data corresponding to fixation point failure traction and extubation risk traction are entered into the early warning parameter update sample. False alarms are removed from the update sample, enabling the system to reduce invalid alarms in subsequent warnings while retaining the ability to identify actual extubation risks and fixation point failure states. Attached Figure Description

[0019] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1 refer to Figure 1 A method for identifying unplanned extubation care using tubing traction, comprising the following steps: S1: Obtain the tubing constraint chain data corresponding to the target patient. The tubing constraint chain data includes catheter type, catheter insertion site, tubing fixation point location, free segment length, external device location, initial tubing margin, and tubing risk level. S2: Acquire continuous traction monitoring data and nursing operation records corresponding to the tubing constraint chain data. The continuous traction monitoring data includes tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data. S3: During the baseline acquisition period after catheter fixation, an individualized traction baseline matching the target patient and corresponding tubing is generated based on continuous traction monitoring data. The individualized traction baseline includes the baseline tension range, the baseline tension change rate range, the baseline fixation point micro-motion range, and the baseline tubing margin change range. S4: Calculate the current pipeline margin and pipeline margin consumption based on pipeline constraint chain data, pipeline displacement data, fixed point micro-motion data, and external equipment position data; S5: Segment the continuous traction monitoring data into events and extract the traction fingerprints corresponding to the traction events. The traction fingerprints include traction amplitude, traction duration, traction rise rate, traction release rate, traction direction, pipeline margin consumption, and fixed point micro-motion. S6: Determine the nursing operation window based on the nursing operation record. The nursing operation window includes the operation start time, operation end time, and recovery period after the operation ends. S7: Based on the event identification priority, identify the traction event type according to the traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window. The traction event types include postural traction, equipment traction, nursing operation traction, fixation point failure traction, and extubation risk traction. S8: When the traction event type is fixed point failure traction or tube removal risk traction, a graded nursing warning is generated based on the tube risk level, current tube balance, tube balance consumption, fixed point micro-movement and responsible nurse response status, and the graded nursing warning is pushed to the nurse station terminal and the responsible nurse terminal. S9: Receives the treatment results from the responsible nurse's terminal and updates the individualized traction baseline and early warning parameters of the corresponding tubing for the target patient based on the treatment results.

[0022] This application is applied to a nursing early warning server. The method is used to identify the tubing traction status of patients with indwelling catheters in inpatient wards, intensive care units, and postoperative recovery wards, and to generate nursing early warnings to the nurse station terminal and the responsible nurse terminal based on the identification results.

[0023] The tubing described in this embodiment includes endotracheal tubes, central venous catheters, PICC catheters, drainage tubes, gastric tubes, urinary catheters, and other nursing tubing that needs to be fixed to the patient's body surface or bedside. The unplanned extubation nursing warning does not diagnose the patient's disease or directly provide a treatment decision. Instead, it identifies whether the tubing is prone to traction instability based on the force, displacement, and fixation status of the tubing, the patient's position, and nursing operation records, and translates the identification results into nursing intervention prompts.

[0024] In this embodiment, the nursing early warning server is communicatively connected to the nurse station terminal, the responsible nurse terminal, the tubing tension acquisition unit, the tubing displacement acquisition unit, the fixed-point micro-motion acquisition unit, the patient position acquisition unit, and the external device position acquisition unit. The tubing tension acquisition unit is used to acquire changes in tubing tension near the fixed point or on the free segment of the tubing; the tubing displacement acquisition unit is used to acquire changes in the position of the free segment of the tubing in the bedside area; the fixed-point micro-motion acquisition unit is used to acquire changes in the position of the fixed point of the tubing between adjacent sampling times; the patient position acquisition unit is used to acquire information about the patient's supine, lateral, head-of-bed elevation, and direction of positional changes; and the external device position acquisition unit is used to acquire the positions of the infusion pump, drainage bottle, urine bag holder, ventilator tubing interface, and other external devices relative to the bed reference point.

[0025] In one specific implementation, the tubing tension acquisition unit employs a flexible tension acquisition component fixed to the outer wall of the tubing or the tubing retainer; the tubing displacement acquisition unit employs positioning marks set on the free section of the tubing and a bedside positioning module; the fixed-point micro-motion acquisition unit employs displacement acquisition marks set on the edge of the fixed dressing, the fixing clip, or the catheter retainer; the patient position acquisition unit employs bed angle data, mattress pressure data, and positional nursing data recorded by the responsible nurse's terminal; and the external device position acquisition unit employs a positioning tag set on the external device or a bedside device position acquisition interface. The specific model of the above acquisition units is not limited, but their output data needs to be convertible into data records containing bed number, patient identification, catheter type, sampling time, and acquisition value.

[0026] The nursing early warning server establishes a bed-based coordinate system at the target patient's bedside. This system uses a fixed reference point on the bed as its origin and the head, foot, left, right, and vertical directions as its coordinate axes. The locations of catheter insertion sites, tubing fixation points, free segment points of the tubing, and external device locations are all mapped to the same bed-based coordinate system. This approach ensures that data from different acquisition units can enter a unified data processing flow, preventing ambiguity in traction direction determination due to inconsistencies in coordinate systems.

[0027] The nursing early warning server first obtains the tubing constraint chain data corresponding to the target patient. This data includes bed number, patient identification, catheter type, catheter insertion site, tubing fixation point location, free segment length, external device location, initial tubing margin, and tubing risk level. This data is entered by the responsible nurse through their terminal after catheter fixation, and can also be retrieved from the nursing record system, medical order system, infusion management system, and bedside equipment management system.

[0028] Among them, the catheter insertion site refers to the location where the catheter enters the patient's body or is adjacent to the entrance on the patient's body surface; the tubing fixation point location refers to the location where the catheter is restrained on the patient's body surface, in a fixation dressing, fixator, or bedside fixation structure; the free tubing length refers to the actual length of the tubing from the tubing fixation point to the external device end; the external device location refers to the position of the infusion pump, drainage bottle, urine bag, ventilator tubing interface, and other external devices connected to the tubing in the bed coordinate system; the initial tubing margin refers to the remaining tubing length after deducting the initial tubing path length from the fixation point to the external device end from the free tubing length after the catheter is fixed.

[0029] The nursing early warning server generates a tubing constraint chain based on the catheter insertion site, tubing fixation point location, free tubing length, external device location, and the catheter's routing within the bedside area. This chain consists of the catheter insertion point, fixation point, free tubing length, and external device end. The tubing constraint chain describes the spatial constraints between the tubing insertion point and the external device end, serving as the basis for subsequent tubing margin calculations, traction direction identification, and event classification.

[0030] The risk level of a catheter is determined based on the type of catheter and the insertion site. Risk levels are categorized into Level 1, Level 2, and Level 3. The risk level configuration table is derived from hospital nursing management regulations, catheter product instructions, departmental catheter fixation standards, and ward nursing procedures. Endotracheal tubes, ventricular drainage tubes, and central venous catheters are classified as Level 1 risk; PICC catheters, chest drainage tubes, and abdominal drainage tubes are classified as Level 2 risk; and gastric tubes and urinary catheters are classified as Level 3 risk. In practice, hospitals adjust the configuration table according to different departmental nursing standards and input the adjusted table into the warning parameters of the nursing early warning server.

[0031] The nursing early warning server acquires continuous traction monitoring data and nursing operation records corresponding to the tubing constraint chain data. Continuous traction monitoring data includes tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data. Nursing operation records include bedside barcode scanning records, turning care records, suctioning care records, infusion change records, catheter fixation inspection records, and constraint status inspection records.

[0032] After catheter fixation is completed, the responsible nurse confirms the fixation is complete via their terminal, and the nursing alert server initiates the baseline acquisition period. The baseline acquisition period is used to collect basic tubing traction data for the target patient under the current catheter fixation state. The initial configuration of the baseline acquisition period is derived from hospital nursing procedures, routine post-catheter fixation observation duration, equipment stabilization time, and departmental management requirements, and is incorporated into the alert parameters.

[0033] During the baseline data collection period, the nursing early warning server collects tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data for the target patient in supine, left lateral, right lateral, and head-up positions. If the patient is unable to maintain a certain position due to their condition, the responsible nurse's terminal records the uncollected state and reason, and the nursing early warning server uses only the confirmed position data to form an individualized traction baseline.

[0034] The nursing early warning server generates an individualized traction baseline that matches the target patient and corresponding tubing based on data collected during the baseline acquisition period. The individualized traction baseline includes the baseline tension range, the baseline tension change rate range, the baseline fixation point micro-motion range, and the baseline tubing margin change range.

[0035] Specifically, the nursing early warning server sorts the tubing tension data, tension change rate data, fixation point micro-motion data, and tubing balance change data within the baseline acquisition period, and determines the baseline tension range, baseline tension change rate range, baseline fixation point micro-motion range, and baseline tubing balance change range using the 5th to 95th percentiles of the corresponding data samples. This method can eliminate initial acquisition jitter, short-term contact disturbances, and transient equipment noise. All the above baseline ranges are derived from the target patient's own baseline acquisition data, and fixed thresholds without a source are not used.

[0036] The nursing early warning server calculates the current pipeline reserve and pipeline reserve consumption based on pipeline constraint chain data, pipeline displacement data, fixed point micro-motion data, and external equipment location data.

[0037] Let the location of the fixed point be... The location of the external device is The intermediate path point of the free section of the pipeline is ,in Indicates the sampling time. This indicates the number of path segments between the fixed point and the external device. The current pipeline path length, current pipeline margin, and pipeline margin consumption are determined according to the following formula: ; ; ; In the formula, Indicates the sampling time The current pipeline path length; Indicates the sampling time The One pipeline path point; Indicates the sampling time The previous pipeline path point; Indicates the spatial distance between two adjacent path points; Indicates the sampling time Current pipeline capacity; This indicates the length of the free section of the conduit from the fixed point to the end of the external device; Indicates the sampling time Pipeline spare capacity consumption; This indicates the initial tubing allowance after the conduit is fixed in place.

[0038] Whether the fixed point position has shifted is determined based on the displacement distance between adjacent sampling times. When the displacement distance between adjacent sampling times exceeds the upper limit of the positioning error of the fixed point micro-motion acquisition unit, the nursing early warning server determines that the fixed point position has shifted. The upper limit of the positioning error is derived from the device manual and bedside calibration records of the fixed point micro-motion acquisition unit and is written into the early warning parameters of the corresponding tubing for the target patient. When the fixed point position shifts, the nursing early warning server re-determines the current tubing path length based on the shifted fixed point position and recalculates the current tubing reserve and tubing reserve consumption.

[0039] The nursing early warning server segments the continuous traction monitoring data into events and extracts the traction fingerprints corresponding to the traction events.

[0040] The nursing early warning server reads continuous traction monitoring data in chronological order of acquisition time. When the tubing tension data exceeds the baseline tension range, the corresponding time is designated as the start time of the traction event. When the fixed-point micro-motion data exceeds the baseline fixed-point micro-motion range, the corresponding time is designated as the start time of the traction event. When the change in tubing margin exceeds the baseline tubing margin change range, the corresponding time is designated as the start time of the traction event. If any of the above conditions are met, the event is recorded in the traction event log.

[0041] When the pipeline tension data, fixed-point micro-motion data, and pipeline margin change all return to the range corresponding to the individualized traction baseline, the corresponding time is determined as the end time of the traction event. The data segment between the start time and the end time of the traction event is considered as the data segment of the same traction event.

[0042] The nursing early warning server calculates the traction fingerprint based on the traction event data segment. The traction fingerprint includes traction amplitude, traction duration, traction rise rate, traction release rate, traction direction, tubing margin consumption, and micromotion at the fixed point.

[0043] Specifically, the traction amplitude is determined by the difference between the maximum tension value within the traction event and the tension value at the start of the traction event; the traction duration is determined by the time difference between the end of the traction event and the start of the traction event; the traction ascent rate is determined by the tension change and time difference between the start of the traction event and the moment when maximum tension occurs; the traction release rate is determined by the tension change and time difference between the moment when maximum tension occurs and the end of the traction event; the fixed point micro-motion is determined by the cumulative displacement of the fixed point position between adjacent sampling moments within the traction event; and the pipeline margin change is determined by the difference in the current pipeline margin between adjacent sampling moments. All of the above parameters are calculated from continuous traction monitoring data in the traction event data segment.

[0044] The number of consecutive judgment periods is written into the early warning parameters. The number of consecutive judgment periods is three to five sampling periods, and the specific value is configured according to the sampling period of the acquisition equipment, the pipeline risk level, and the alarm response requirements of the ward. When the pipeline remaining capacity consumption is greater than the pipeline remaining capacity consumption corresponding to the previous sampling period within the consecutive judgment periods, it is determined that the pipeline remaining capacity consumption is continuously increasing. When the fixed point micro-motion is greater than the fixed point micro-motion corresponding to the previous sampling period within the consecutive judgment periods, it is determined that the fixed point micro-motion is continuously increasing.

[0045] The nursing early warning server determines the traction direction based on the path vector from the fixed point to the external device, the exposed direction vector of the catheter insertion end, the micro-motion direction of the fixed point, and the displacement direction of the tubing.

[0046] Let the location of the fixed point be... The location of the external device is The catheter insertion site is The path vector from the fixed point to the external device is... The direction vector of the catheter insertion end is The direction of the fixed point micro-motion is The direction of pipeline displacement is The nursing early warning server calculates the angle between two direction vectors using the following formula: ; In the formula, Representing vectors with vector The angle between them; Representing vectors with vector The dot product; Representing vectors The model; Representing vectors The model.

[0047] in, From the fixed point location to the external device location; The direction from the catheter insertion site to the fixation point; Determined based on the positional change of the fixed point between adjacent sampling times; The position of the representative displacement point of the free section of the pipeline is determined based on the positional change between adjacent sampling times.

[0048] When the fixed point moves slightly in the direction With path vector The included angle is less than the included angle threshold written in the warning parameters, and the pipeline displacement direction With path vector When the included angle is less than the included angle threshold written in the warning parameters, the pulling direction is determined to point to the external device.

[0049] When the fixed point moves slightly in the direction Vector of the exposed direction of the catheter insertion end The included angle is less than the included angle threshold written in the warning parameters, and the pipeline displacement direction is... Vector of the exposed direction of the catheter insertion end When the included angle is less than the included angle threshold written in the warning parameters, and the current pipeline margin is less than the pipeline margin corresponding to the previous sampling time, the pulling direction is determined to be pointing to the outside of the catheter insertion end.

[0050] The included angle threshold is derived from the positioning errors of the tubing displacement acquisition unit and the fixed-point micro-motion acquisition unit, the bedside calibration results, and the actual deployment records in the ward. During system deployment, technicians write the included angle threshold according to the upper limit of positioning error in the acquisition unit manual and the bedside calibration records. The included angle threshold is used to compensate for directional deviations caused by bedside positioning errors, natural tubing bends, and slight patient movements. The included angle threshold does not change automatically based on a single alarm event; when the responsible nurse's terminal continuously reports false alarms of equipment traction or tube removal risk traction for the same tubing, the nursing early warning server writes the relevant events into the early warning parameter update sample and prompts system administrators to review the included angle threshold.

[0051] The nursing early warning server determines the nursing operation window based on the nursing operation records. The nursing early warning server reads the bedside scanning records, turning care records, suction care records, infusion change records, catheter fixation inspection records, and restraint status inspection records generated by the responsible nurse's terminal, and matches the nursing operation records corresponding to the same bed number, the same patient identification, and the same catheter type with the tubing restraint chain data corresponding to the target patient.

[0052] In the matched nursing operation record, the operation start time is determined as the operation start moment, and the operation completion time is determined as the operation end moment. The nursing early warning server reads the recovery time from the early warning parameters of the corresponding tubing for the target patient, based on the nursing operation type, catheter type, and tubing risk level. The recovery time is read from the recovery time parameter table according to the nursing operation type, catheter type, and tubing risk level. The initial content of the recovery time parameter table comes from the hospital's nursing operation procedures, catheter fixation specifications, and ward debugging records. The nursing operation window is formed by the operation start time, operation end time, and the recovery period after the operation.

[0053] After the system is operational, the nursing early warning server statistically analyzes the recovery times of events identified by the responsible nurse as postural traction, equipment traction, and nursing procedure traction, and updates the corresponding recovery time based on the 95th percentile of the recovery time sample for the same type of event. If the number of updated samples for the same nursing procedure type, catheter type, and tubing risk level does not reach the minimum number of samples written in the early warning parameters, the recovery time will not be automatically updated.

[0054] The nursing early warning server identifies traction event types based on the event recognition priority written into the early warning parameters, using factors such as traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window. The event recognition priority is as follows: traction with extubation risk, traction due to fixation point failure, traction due to nursing operation, traction due to equipment, and traction due to body position. This recognition order prioritizes high-risk traction events, preventing the actual extubation risk from being masked by the nursing operation window, equipment movement, or changes in body position.

[0055] When the remaining tubing volume continues to increase, the pulling direction points to the outside of the catheter insertion end, the micromotion of the fixation point exceeds the baseline fixation point micromotion range, and the pulling release rate is lower than the lower limit of the release rate in the baseline tension change rate range, the nursing early warning server will identify the pulling event as a risky extubation pulling event.

[0056] When the same traction event is not identified as a risky traction event for tube removal, and the micromotion at the fixation point continues to increase, with the direction of the micromotion consistent with the traction direction, the nursing early warning server will identify the traction event as a fixation point failure traction. Fixation point failure traction corresponds to situations such as dressing loosening, fixator slippage, and gradual movement of the tube fixation position. This type of event may not have a significant instantaneous tension peak, but it will continuously deplete the current tube capacity, therefore it needs to be identified independently.

[0057] When the same traction event is not identified as extubation risk traction or fixation point failure traction, and the traction event occurs within the nursing operation window, and the tubing tension data, fixation point micro-motion data, and current tubing balance all recover to the range corresponding to the individualized traction baseline during the recovery period, the nursing early warning server will identify the traction event as nursing operation traction.

[0058] When the same traction event is not identified as extubation risk traction, fixation point failure traction, or nursing operation traction, and the external device location data changes before the tubing tension data, and the traction direction points towards the external device end, the nursing early warning server will identify the traction event as device traction.

[0059] When the same traction event is not identified as extubation risk traction, fixation point failure traction, nursing operation traction, or equipment traction, and the patient's position data changes before the tubing tension data, and after the traction event ends, the tubing tension data, fixation point micro-motion data, and current tubing balance all return to the range corresponding to the individualized traction baseline, the nursing early warning server will identify the traction event as position traction.

[0060] When the same traction event does not meet any of the identification criteria among extubation risk traction, fixation point failure traction, nursing operation traction, equipment traction, and postural traction, the nursing early warning server records the traction event as an unclassified traction event and sends it to the responsible nurse's terminal for manual confirmation. Unclassified traction events are not included in the updated sample of individualized traction baseline or the updated sample of early warning parameters until confirmed by the responsible nurse's terminal.

[0061] When the traction event type is fixed point failure traction or tube removal risk traction, the nursing early warning server generates a graded nursing early warning based on the tube risk level, current tube balance, tube balance consumption, fixed point micro-movement, and the responsible nurse's response status.

[0062] When the traction event type is "fixed point failure traction" and the current tubing clearance is not below the lower limit, the nursing early warning server generates a Level 1 nursing early warning and sends it to the responsible nurse's terminal. The Level 1 nursing early warning is used to prompt the responsible nurse to check the status of the catheter fixation point and the clearance of the free segment.

[0063] When the traction event type is extubation risk traction, and the current tubing clearance is below the lower limit, the nursing warning server generates a level-two nursing warning. When the traction event type is extubation risk traction, and the micro-motion of the fixation point exceeds the baseline fixation point micro-motion range, the nursing warning server generates a level-two nursing warning. Level-two nursing warnings are sent to the responsible nurse's terminal and the nurse station terminal.

[0064] When the traction event type is extubation risk traction, and all three conditions are met—the current tubing volume is below the lower limit, the micro-motion at the fixation point exceeds the baseline micro-motion range, and the responsible nurse's terminal does not provide confirmation of receipt within the response time—the nursing early warning server generates a Level 3 nursing early warning. The Level 3 nursing early warning is sent to the nurse station terminal and the responsible nurse's terminal, and the nurse station terminal displays the bed number, patient identification, catheter type, traction event type, current tubing volume, fixation point micro-motion status, and tubing treatment sequence.

[0065] The lower limit of the margin is determined based on the catheter type, catheter insertion site, and initial tubing margin. Let the lower limit of the margin for the target patient's tubing be... The minimum retention margin corresponding to the catheter type and catheter insertion site is: The initial pipeline margin is The allowance ratio is ,but: ; In the formula, Indicates the lower limit of the margin; This indicates the minimum allowable retention determined based on the catheter type and insertion site. This represents the margin ratio coefficient determined based on the pipeline risk level; Indicates the initial piping margin; Indicates taking and The larger values.

[0066] in, The information is derived from catheter product manuals, hospital catheter fixation guidelines, and departmental nursing procedures. The values ​​are written into the early warning parameter table, and their initial values ​​are configured by the hospital based on the catheter risk level and bedside commissioning records. During system operation, Instead of being changed directly by a single alarm event, the system updates the sample based on the warning parameters confirmed by the responsible nurse.

[0067] The response time is read from the response time parameter table according to the pipeline risk level. The response time parameter table is derived from the hospital's nursing emergency response system and departmental catheter management specifications. The response time for a Level 1 risk pipeline is shorter than that for a Level 2 risk pipeline, and the response time for a Level 2 risk pipeline is shorter than that for a Level 3 risk pipeline. When the response time is updated, the nursing early warning server retains the parameter version before the update, the update time, the sample quantity, and the responsible nurse's confirmation record. If the updated sample quantity does not reach the minimum sample quantity written in the early warning parameters, the response time will not be automatically updated.

[0068] When multiple tubing constraint chains correspond to the same target patient, the nursing early warning server calculates the current tubing capacity, tubing capacity consumption, fixation point micromotion, and traction event type for each constraint chain. Based on the tubing risk level, current tubing capacity, tubing capacity consumption, fixation point micromotion, and traction event type for each constraint chain, it generates a tubing treatment order. When traction event types are the same, the constraint chain with the higher risk level is prioritized; when risk levels are the same, the constraint chain with the smaller current tubing capacity is prioritized; when current tubing capacity is the same, the constraint chain with the larger fixation point micromotion is prioritized.

[0069] After receiving a triage-based nursing alert, the responsible nurse confirms the alert at the bedside and reports the treatment result through the responsible nurse's terminal. The treatment result includes confirmation results for postural traction, equipment traction, nursing procedure traction, fixation point failure traction, extubation risk traction, and false alarm.

[0070] When the outcome of the intervention is a confirmation of postural traction, equipment traction, or nursing procedure traction, the nursing early warning server writes the corresponding traction event's tubing tension data, tubing displacement data, fixation point micro-motion data, and tubing margin change data into the updated sample of the individualized traction baseline. This type of sample represents the recoverable disturbance state after changes in patient positioning, equipment position, or nursing procedures, and can be used to refine the individualized traction baseline.

[0071] When the outcome of the intervention is a confirmation of fixation point failure or a confirmation of tube removal risk, the nursing early warning server will write the corresponding tube tension data, fixation point micro-motion data, tube margin consumption, and traction direction into the updated sample of the early warning parameters. This type of sample will not be included in the updated sample of the individualized traction baseline to prevent abnormal risk states from being written into the normal baseline range.

[0072] When the handling result is a false alarm confirmation, the nursing early warning server will remove the corresponding traction event from the updated sample of the individualized traction baseline and the updated sample of the early warning parameters. False alarm events retain event logs, removal records, the responsible nurse's terminal identifier, and confirmation time for subsequent manual review.

[0073] When the nursing early warning server recalculates the individualized traction baseline based on updated samples of the individualized traction baseline, it uses a sliding sample window. The sliding sample window includes samples from the most recent baseline acquisition period and recoverable traction event samples confirmed by the responsible nurse. Recoverable traction event samples include data corresponding to positional traction confirmation results, equipment traction confirmation results, and nursing procedure traction confirmation results.

[0074] During recalculation, the nursing early warning server sorts the tubing tension data, tension change rate data, fixed point micro-motion data, and tubing margin change data respectively, and updates the baseline tension range, baseline tension change rate range, baseline fixed point micro-motion range, and baseline tubing margin change range using the 5th percentile to the 95th percentile.

[0075] Data corresponding to the fixed-point failure traction confirmation results and the tube removal risk traction confirmation results are not included in the updated sample of the individualized traction baseline, but only in the updated sample of the early warning parameters. Data corresponding to false alarm confirmation results are removed from the updated samples of the individualized traction baseline and the updated samples of the early warning parameters.

[0076] When the number of updated samples falls below the minimum number of samples specified in the warning parameters, the nursing warning server retains the original individualized traction baseline and the original warning parameters, and does not perform automatic updates. When warning parameters are updated, the nursing warning server retains the parameter versions before and after the update, the update time, the number of updated samples, the responsible nurse's confirmation record, and the update source.

[0077] Through the above closed-loop update, the system can distinguish between normal disturbances, fixation point failures, extubation risks, and false alarms based on the bedside confirmation results of the responsible nurse, and write different types of events into the individualized traction baseline update sample or early warning parameter update sample to avoid abnormal risk events being mistaken for normal baselines.

[0078] Example 2 This embodiment provides a nursing early warning system for identifying unplanned extubation due to tubing traction, used to implement the method described in Embodiment 1. The system includes a nursing early warning server, a nurse station terminal, a responsible nurse terminal, a tubing tension acquisition unit, a tubing displacement acquisition unit, a fixed-point micro-motion acquisition unit, a patient position acquisition unit, and an external device position acquisition unit.

[0079] The nursing early warning server includes a processor, memory, a traction monitoring data access interface, a nursing operation record access interface, and an early warning push interface. The memory stores computer programs, tubing constraint chain data, continuous traction monitoring data, nursing operation records, individualized traction baselines, and early warning parameters.

[0080] The traction monitoring data access interface is communicatively connected to the tubing tension acquisition unit, tubing displacement acquisition unit, fixed-point micro-motion acquisition unit, patient position acquisition unit, and external device position acquisition unit. The traction monitoring data access interface receives data output from these acquisition units and converts it into data records containing bed number, patient identification, catheter type, sampling time, and acquired values.

[0081] The nursing operation record access interface communicates with the responsible nurse's terminal to receive bedside barcode scanning records, turning care records, suctioning care records, infusion change records, catheter fixation inspection records, and restraint status inspection records. The nursing operation record access interface matches the nursing operation records with the tubing constraint chain data and forms a nursing operation window.

[0082] The early warning push interface communicates with both the nurse station terminal and the responsible nurse terminal, and is used to send triage nursing warnings, catheter treatment sequence, and traction event types. Upon receiving a warning, the responsible nurse terminal displays the bed number, patient identification, catheter type, traction event type, current catheter remaining capacity, fixation point micro-motion status, suggested fixation point locations for inspection, and a feedback entry point for treatment results. The nurse station terminal displays a sorted list of untreated warnings within the same ward.

[0083] When the processor executes the computer program stored in memory, it acquires the tubing constraint chain data corresponding to the target patient; generates an individualized traction baseline matching the target patient and corresponding tubing based on continuous traction monitoring data; calculates the current tubing balance and tubing balance consumption based on the tubing constraint chain data, tubing displacement data, fixation point micro-motion data, and external device position data; segments the continuous traction monitoring data into events and extracts the traction fingerprints corresponding to the traction events; determines the nursing operation window based on the nursing operation record; and determines the traction fingerprint based on the path vector from the fixation point to the external device end, the catheter insertion end exposure direction vector, the fixation point micro-motion direction, and the tubing displacement direction. Determine the traction direction; identify the traction event type according to the event identification priority written into the warning parameters, based on the traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window; when the traction event type is fixation failure traction or extubation risk traction, generate a graded nursing warning based on the tubing risk level, current tubing balance, tubing balance consumption, fixation point micro-motion, and the responsible nurse's response status; send the graded nursing warning to the nurse station terminal and the responsible nurse's terminal through the warning push interface; receive the treatment results from the responsible nurse's terminal, and update the individualized traction baseline and warning parameters of the corresponding tubing for the target patient based on the treatment results.

[0084] In this embodiment, the system units form a closed-loop data flow from bedside data collection, server identification, terminal alerts, nurse confirmation, to parameter updates. Each unit has clearly defined data inputs, processing content, and output results, ensuring that the system is not simply a stack of functional modules, but rather a collaborative process centered around pipeline constraint chains, traction fingerprints, nursing operation windows, and closed-loop updates.

[0085] Example 3 This embodiment uses the placement of a central venous catheter in a target patient as an example to illustrate the system operation process.

[0086] After the central venous catheter is secured, the responsible nurse enters the bed number, patient identification, catheter type, catheter insertion site, exposed catheter length, tubing fixation point location, free segment length, and external device location through the responsible nurse's terminal. Based on this data, the nursing early warning server establishes a tubing constraint chain corresponding to the target patient and determines the tubing risk level from the tubing risk level configuration table according to the catheter type and insertion site.

[0087] After catheter fixation is completed, the responsible nurse's terminal sends a confirmation message indicating that fixation is complete. The nursing early warning server initiates the baseline acquisition period, collecting data on tubing tension, tubing displacement, fixation point micro-motion, patient position, and external device position for the target patient in supine, left lateral, right lateral, and head-up positions, and generates an individualized traction baseline.

[0088] When the patient slightly turns over, the patient's position data changes first, followed by a brief change in tubing tension data. After the traction event ends, the tubing tension data, fixation point micro-motion data, and current tubing margin all return to the range corresponding to the individualized traction baseline. The nursing alert server, after judging the events according to their priority, identifies this event as postural traction and does not generate a high-level nursing alert.

[0089] When the responsible nurse changes an IV infusion, the nurse's terminal generates an IV change record. The nursing early warning server then creates a nursing operation window based on the start time, end time, and recovery period of the operation. During the IV change, tubing tension and displacement data change, but within the recovery period, they all return to the range corresponding to the individualized traction baseline. The nursing early warning server identifies this event as a nursing operation involving traction.

[0090] When an external device is moved, the device's location data changes before the tubing tension data, and the pulling direction points towards the external device. The nursing early warning server recognizes this event as device pulling and prompts the responsible nurse's terminal to verify the external device's location.

[0091] When the micro-motion at the fixed point continuously increases within a certain number of consecutive judgment cycles, and the direction of the micro-motion is consistent with the direction of traction, the nursing early warning server identifies it as a fixed point failure traction. If the current tubing clearance is not lower than the lower limit of clearance, the nursing early warning server generates a Level 1 nursing early warning, prompting the responsible nurse to check the status of the fixed point.

[0092] When the remaining tubing volume continues to increase, the traction direction points outward from the catheter insertion end, the micromotion of the fixation point exceeds the baseline fixation point micromotion range, and the traction release rate is lower than the lower limit of the release rate within the baseline tension change rate range, the nursing warning server identifies this as a risky traction for catheter removal. If the current remaining tubing volume is lower than the lower limit, or the micromotion of the fixation point exceeds the baseline fixation point micromotion range, the nursing warning server generates a Level 2 nursing warning. If the current remaining tubing volume is lower than the lower limit, the micromotion of the fixation point exceeds the baseline fixation point micromotion range, and the responsible nurse's terminal does not provide confirmation of receipt within the response time, a Level 3 nursing warning is generated.

[0093] After the responsible nurse checks at the bedside and confirms that the dressing is loose and re-secures the tubing, the nurse reports the confirmation of fixation point failure via their terminal. The nursing alert server writes this event into the updated sample of alert parameters, but not into the updated sample of individualized traction baseline. If the responsible nurse confirms that the traction is recoverable due to a change in patient position, the event is written into the updated sample of individualized traction baseline. If the responsible nurse confirms that it is a false alarm, the event is removed from both the updated sample of individualized traction baseline and the updated sample of alert parameters.

[0094] Through the above operation process, the system can identify different types of traction events before the tubing is dislodged, based on the consumption of tubing remaining volume, micro-movement of fixed points, traction direction, and nursing operation window, and convert the identification results into graded nursing warnings that the responsible nurse can handle.

[0095] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for identifying unplanned extubation and providing early warning during tube traction, characterized in that, Includes the following steps: S1: Obtain the tubing constraint chain data corresponding to the target patient. The tubing constraint chain data includes catheter type, catheter insertion site, tubing fixation point location, free segment length, external device location, initial tubing margin, and tubing risk level. S2: Acquire continuous traction monitoring data and nursing operation records corresponding to the tubing constraint chain data. The continuous traction monitoring data includes tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data. S3: During the baseline acquisition period after catheter fixation, an individualized traction baseline matching the target patient and corresponding tubing is generated based on continuous traction monitoring data. The individualized traction baseline includes the baseline tension range, the baseline tension change rate range, the baseline fixation point micro-motion range, and the baseline tubing margin change range. S4: Calculate the current pipeline margin and pipeline margin consumption based on pipeline constraint chain data, pipeline displacement data, fixed point micro-motion data, and external equipment position data; S5: Segment the continuous traction monitoring data into events and extract the traction fingerprints corresponding to the traction events. The traction fingerprints include traction amplitude, traction duration, traction rise rate, traction release rate, traction direction, pipeline margin consumption, and fixed point micro-motion. S6: Determine the nursing operation window based on the nursing operation record. The nursing operation window includes the operation start time, operation end time, and recovery period after the operation ends. S7: Based on the event identification priority, identify the traction event type according to the traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window. The traction event types include postural traction, equipment traction, nursing operation traction, fixation point failure traction, and extubation risk traction. S8: When the traction event type is fixed point failure traction or tube removal risk traction, a graded nursing warning is generated based on the tube risk level, current tube balance, tube balance consumption, fixed point micro-movement and responsible nurse response status, and the graded nursing warning is pushed to the nurse station terminal and the responsible nurse terminal. S9: Receives the treatment results from the responsible nurse's terminal and updates the individualized traction baseline and early warning parameters of the corresponding tubing for the target patient based on the treatment results.

2. The method for identifying unplanned extubation and providing early warning of tube pulling according to claim 1, characterized in that, The acquisition of the tubing constraint chain data corresponding to the target patient includes: Obtain the target patient's bed number, patient identification, catheter type, catheter insertion site, and catheter exposed length; Obtain the location of the catheter fixation point on the patient's body surface, the length of the free segment of the catheter from the fixation point to the external device, the position of the external device relative to the bed reference point, and the direction of the catheter in the bedside area; Based on the catheter insertion site, fixation point location, free tube length, external equipment location, and catheter routing within the bedside area, a tubing constraint chain is formed, consisting of the catheter insertion end, fixation point, free tube length, and external equipment end. The risk level of the tubing is determined based on the type of catheter and the insertion site. The risk levels include Level 1 risk, Level 2 risk, and Level 3 risk.

3. The method for identifying unplanned extubation and providing early warning of tube pulling according to claim 2, characterized in that, During the baseline acquisition period after catheter fixation, an individualized traction baseline matching the target patient and corresponding tubing is generated based on continuous traction monitoring data, including: After the catheter is secured and the responsible nurse confirms the fixation via the terminal, the baseline acquisition period begins. During the baseline acquisition period, tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data were collected when the target patient was in a supine, left lateral, right lateral, and head-of-bed elevated position. For the data collected under each condition, calculate the average tension, tension fluctuation range, tension change rate range, fixed point micro-motion range, and pipeline margin change range respectively. The mean tension, tension fluctuation range, tension change rate range, fixed point micro-motion range, and tubing margin change range corresponding to each state are written into the individualized traction baseline of the tubing corresponding to the target patient.

4. The method for identifying unplanned extubation and providing early warning of tube pulling according to claim 3, characterized in that, Based on pipeline constraint chain data, pipeline displacement data, fixed point micro-motion data, and external equipment location data, calculate the current pipeline margin and pipeline margin consumption, including: Determine the current pipeline path length from the fixed point to the external equipment end based on the location of the fixed point, the location of the external equipment, and the direction of the conduit in the bedside area; Calculate the current pipeline margin based on the difference between the length of the free pipe segment and the current pipeline path length; Calculate the pipeline margin consumption based on the difference between the initial pipeline margin and the current pipeline margin; When the fixed point micro-motion data indicates that the fixed point position has moved, the current pipeline path length is re-determined based on the fixed point position after the move, and the current pipeline margin and pipeline margin consumption are recalculated.

5. The method for identifying unplanned extubation and providing early warning of tube pulling according to claim 4, characterized in that, The continuous traction monitoring data is segmented into events, and the traction fingerprints corresponding to the traction events are extracted, including: Read the continuous traction monitoring data in chronological order of collection time; When one of the following conditions is met: the pipeline tension data exceeds the baseline tension range, the fixed point micro-motion data exceeds the baseline fixed point micro-motion range, or the pipeline margin change exceeds the baseline pipeline margin change range, the corresponding moment will be determined as the start moment of the traction event. When the pipeline tension data, fixed point micro-motion data, and pipeline margin change all return to the range corresponding to the individualized traction baseline, the corresponding time will be determined as the end time of the traction event. Based on continuous traction monitoring data from the start to the end of the traction event, the traction amplitude, traction duration, traction rise rate, traction release rate, traction direction, pipeline margin consumption, and fixed point micro-motion are calculated, and a traction fingerprint is formed. Among them, when the pipeline margin consumption is greater than the pipeline margin consumption corresponding to the previous sampling period in three consecutive sampling periods, it is determined that the pipeline margin consumption is continuously increasing; when the fixed point micro-motion is greater than the fixed point micro-motion corresponding to the previous sampling period in three consecutive sampling periods, it is determined that the fixed point micro-motion is continuously increasing.

6. The method for identifying unplanned extubation and providing early warning of tube pulling according to claim 5, characterized in that, The pulling direction is determined based on the path vector from the fixed point to the external equipment end, the micro-motion direction of the fixed point, and the pipeline displacement direction, including: Establish a path vector from the fixed point to the external device based on the location of the fixed point and the location of the external device; The direction of the fixed point's micro-motion is determined based on the change in the fixed point's position between adjacent sampling times; The direction of pipeline displacement is determined based on pipeline displacement data at adjacent sampling times; When both the direction of the fixed point micro-motion and the direction of the pipeline displacement are in the same direction as the path vector, the pulling direction is determined to point towards the external equipment end; When both the direction of the fixed point micro-motion and the direction of the pipeline displacement deviate from the path vector and point to the outside of the catheter insertion site, the pulling direction is determined to point to the outside of the catheter insertion end.

7. The method for identifying unplanned extubation and providing early warning of tube pulling according to claim 6, characterized in that, The nursing procedure window is determined based on the nursing procedure record, including: Read the bedside scanning records, turning care records, suction care records, infusion change records, catheter fixation inspection records and restraint status inspection records generated by the responsible nurse's terminal; Match nursing operation records corresponding to the same bed number, the same patient identification, and the same catheter type with the tubing constraint chain data corresponding to the target patient; The start time of the operation is determined based on the start time of the operation in the matched nursing operation record, and the end time of the operation is determined based on the completion time of the operation. Based on the type of nursing procedure, the recovery time corresponding to the type of nursing procedure is read from the warning parameters of the corresponding tubing for the target patient; The recovery period is defined as the time after the end of the operation, and the nursing operation window is formed by the start time of the operation, the end time of the operation, and the recovery period.

8. The method for identifying unplanned extubation and providing early warning of tube pulling according to claim 7, characterized in that, The process involves identifying traction event types based on event recognition priority, including traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window. When the patient's position data changes before the tubing tension data, and after the traction event ends, the tubing tension data, fixation point micro-motion data, and current tubing margin all return to the range corresponding to the individualized traction baseline, the traction event is identified as positional traction. When the location data of the external device changes before the pipeline tension data, and the pulling direction is towards the end of the external device, the pulling event is identified as device pulling. When a traction event occurs within the nursing operation window, and the tubing tension data, fixation point micro-motion data, and current tubing margin all recover to the range corresponding to the individualized traction baseline during the recovery period, the traction event is identified as nursing operation traction. When the micromoment of the fixed point continues to increase, and the direction of the micromoment of the fixed point is consistent with the direction of the pull, the pull event is identified as fixed point failure pull. When the consumption of tubing margin continues to increase, the pulling direction is directed to the outside of the catheter insertion end, the micromotion of the fixation point exceeds the baseline fixation point micromotion range, and the pulling release rate is lower than the lower limit of the release rate in the baseline tension change rate range, the pulling event is identified as a tube removal risk pulling event. When the same traction event simultaneously meets the identification conditions corresponding to fixed-point failure traction and tube removal risk traction, the same traction event is identified as tube removal risk traction.

9. A method for identifying unplanned extubation and providing early warning of tube pulling according to claim 8, characterized in that, A tiered nursing care alert is generated based on the pipeline risk level, current pipeline capacity, pipeline consumption, micro-movement at fixed points, and the responsible nurse's response status. This alert includes: When the traction event type is fixed point failure traction, and the current pipeline margin is not lower than the margin lower limit, a level 1 nursing warning is generated; When the traction event type is extubation risk traction, and one of the following conditions is met: the current tubing balance is lower than the lower limit of the balance, or the micro-motion of the fixation point exceeds the baseline micro-motion range of the fixation point, a level 2 nursing warning is generated. When the traction event type is extubation risk traction, and all three conditions are met—the current tubing remaining amount is lower than the lower limit of the remaining amount, the micro-movement of the fixation point exceeds the baseline fixation point micro-movement range, and the responsible nurse's terminal does not provide feedback confirmation within the response time—a level three nursing warning is generated. The lower limit of the margin is determined based on the catheter type, catheter insertion site, and initial tubing margin, and is written into the warning parameters of the corresponding tubing for the target patient; The response time is determined based on the risk level of the tubing and is written into the early warning parameters of the tubing corresponding to the target patient.

10. A tubing traction identification and unplanned extubation nursing early warning system, applicable to the tubing traction identification and unplanned extubation nursing early warning method according to any one of claims 1-9, characterized in that, This includes a nursing early warning server, nurse station terminals, and responsible nurse terminals; The nursing early warning server includes a processor, memory, a traction monitoring data access interface, a nursing operation record access interface, and an early warning push interface; The memory stores computer programs, tubing constraint chain data, continuous traction monitoring data, nursing operation records, individualized traction baselines, and early warning parameters. The traction monitoring data access interface is used to receive continuous traction monitoring data corresponding to the target patient. The continuous traction monitoring data includes tubing tension data, tubing displacement data, fixation point micro-motion data, patient position data, and external device position data. The nursing operation record access interface is used to receive nursing operation records generated by the responsible nurse's terminal; When a processor executes a computer program, it performs the following steps: Obtain the tubing constraint chain data corresponding to the target patient; An individualized traction baseline is generated based on continuous traction monitoring data, matching the target patient and corresponding tubing. Based on pipeline constraint chain data, pipeline displacement data, fixed point micro-motion data, and external equipment position data, calculate the current pipeline margin and pipeline margin consumption. The continuous traction monitoring data is segmented into events, and the traction fingerprints corresponding to the traction events are extracted. Determine the nursing operation window based on the nursing operation record; The pulling direction is determined based on the path vector from the fixed point to the external equipment end, the direction of the fixed point's micro-motion, and the direction of the pipeline displacement. Based on the event identification priority, the traction event type is identified according to the traction fingerprint, current tubing balance, individualized traction baseline, and nursing operation window; When the traction event type is fixation failure traction or tube removal risk traction, a graded nursing warning is generated based on the tube risk level, current tube balance, tube balance consumption, fixation point micro-movement, and the responsible nurse's response status. The tiered nursing care alerts are sent to the nurse station terminal and the responsible nurse terminal via the alert push interface; Receive the treatment results from the responsible nurse's terminal and update the individualized traction baseline and early warning parameters of the corresponding tubing for the target patient based on the treatment results.

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