Monitoring method, device, medium and electronic equipment for abnormal urine volume in urine bag

Abstract

The present application provides a monitoring method, device, medium and electronic device for abnormal urine volume in a urine bag, which relates to the field of medical data processing, including: collecting the pressure change value of the bracket for hanging the urine bag within the first historical time window to obtain the corresponding first feature vector list NQ; clustering NQ to obtain the corresponding cluster list set NH; in response to reaching the first target detection time point corresponding to the current target infusion task, determining the target evaluation label from the urine volume evaluation label corresponding to NH according to NH and a preset matching method; if the target evaluation label is an abnormal urine volume, a warning is issued to the target device. The present application improves the accuracy of target evaluation label matching, thereby improving the accuracy of target evaluation label determination, and then issuing a warning based on whether the target evaluation label is normal, so that relevant medical staff can adjust the treatment plan in time and reduce the probability of medical accidents.

Description

Background Art

[0002] In the practice of medical monitoring, urine monitoring of patients is one of the important means to evaluate their physiological state, renal function and water-salt balance. However, in a highly monitored environment such as the ICU (intensive care unit), patients are often in a specific, relatively fixed position, such as supine position, to maintain the stability of vital signs due to their condition. This fixed position greatly limits the patient's ability to change position autonomously to promote natural urination, and requires the use of a urine bag for urination.

[0003] Furthermore, ICU patients often need intravenous infusion to supplement body fluids, drugs or nutritional support during treatment. Due to individual differences, different patients may react very differently to the same drug solution, which is not only reflected in the absorption and metabolism of the drug, but also directly reflected in the changes in urine output. Therefore, accurate and timely monitoring of changes in urine volume during infusion is of vital importance for timely adjustment of treatment plans, prevention of complications and assessment of disease progression. However, due to the large individual differences among patients, it is impossible to accurately assess whether the patient is normal by relying solely on single urine output change data. Summary of the invention

[0004] In response to the above technical problems, the present application provides a method, device, medium and electronic equipment for monitoring abnormal urine volume in a urine bag, which at least partially solve the problems existing in the prior art.

[0005] In a first aspect of the present application, a method for monitoring abnormal urine volume in a urine bag is provided, which is applied to a patient in a target position, wherein the patient in the target position has a corresponding urine bag suspended on a target support, and a pressure sensor is provided on the target support;

[0006] The method comprises:

[0007] S100, collecting the pressure change values ​​of the urine bag hanging bracket corresponding to a number of patients in the target position when performing the historical target infusion task within the first historical time window, so as to obtain the corresponding first feature vector list NQ = (NQ1, NQ2, ..., NQ i ,…,NQ n ); i = 1, 2, ..., n; n is the number of times the historical target infusion task is executed; NQ i NQ is the first eigenvector corresponding to the first historical time window when the historical target infusion task is executed for the i-th time; i =((NQ i，1 , SQ i，1 ), (NQ i，2 , SQ i，2 ),…,(NQ i，j , SQ i，j ),…,(NQi，m , SQ i，m )), m is the number of consecutive first historical time periods included in the first historical time window; NQ i，j is the urine increase corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is performed for the i-th time; SQ i，j NQ is the average infusion speed corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is executed for the i-th time; i，j =f(YQ i，j ); f() is the preset urine volume calculation function; YQ i，j is the pressure change value of the bracket for hanging urine bag corresponding to the jth first historical time period of the first historical time window; each first eigenvector has a unique corresponding second eigenvector in the second historical time window; the end time of the first historical time window is the start time of the historical target infusion task; the end time of the first historical time window is the start time of the second historical time window; the end time of the second historical time window is the end time of the historical target infusion task; the time length of the first historical time window is equal to the time length of the second historical time window; the time length of the first historical time period is equal to the time length of the second historical time period;

[0008] S200, clustering NQ to obtain a corresponding cluster list set NH = (NH1, NH2, ..., NH x ,…,NH y ), x = 1, 2, ..., y, where y is the number of clusters obtained by clustering NQ; NH x is the cluster list corresponding to the xth cluster; NH x =(NH x，1 , NH x，2 ,…,NH x，a ,…,NH x，g(x) ), g(x) is the number of the first eigenvectors included in the x-th cluster; NH x，a is the second eigenvector corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; NH x，a =((NH x，a，1 , S.H. x，a，1 ), (NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，j , S.H. x，a，j ),…,(NH x，a，m , S.H. x，a，m )); NH x，a，jThe urine increase corresponding to the j-th second historical time period in the second historical time window of the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; SH x，a，j is the average infusion speed of the urine bag corresponding to the jth second historical time period in the second historical time window during the ath execution of the historical target infusion task included in the xth cluster; NH x，a，j =f(YH x，a，j );YH x，a，j The pressure change value of the bracket for hanging the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster in the j-th second historical time period in the second historical time window; the matching degree of any two first feature vectors corresponding to each cluster is greater than the preset matching degree threshold; each second feature vector has a corresponding urine volume evaluation label; the urine volume evaluation label includes normal urine volume and abnormal urine volume; each cluster has a corresponding central feature vector;

[0009] S300, in response to reaching the first target detection time point corresponding to the current target infusion task, determining the target evaluation label from the urine volume evaluation label of the second feature vector corresponding to NH according to NH and a preset matching method; wherein the preset matching method matches NH according to the first target feature vector corresponding to the current target infusion task in the first target time window and the second target feature vector corresponding to the second target time window; the end time of the first target time window is the time when the infusion start instruction corresponding to the current target infusion task is received; the time length of the first target time window is equal to the time length of the first historical time window; the start time of the second target time window is the end time of the first target time window, and the end time is the target detection time point corresponding to the current target infusion task;

[0010] S400: If the target evaluation tag is that the urine volume is abnormal, a warning is issued to the target device.

[0011] In a second aspect of the present application, there is provided a monitoring device for abnormal urine volume in a urine bag, which is applied to a patient in a target body position, wherein the patient in the target body position has a corresponding urine bag suspended on a target support, and a pressure sensor is provided on the target support;

[0012] The device comprises:

[0013] The collecting unit is used to collect the pressure change values ​​of the urine bag hanging bracket corresponding to a number of patients in the target position when performing the historical target infusion task within the first historical time window to obtain the corresponding first feature vector list NQ = (NQ1, NQ2, ..., NQ i ,…,NQ n); i = 1, 2, ..., n; n is the number of times the historical target infusion task is executed; NQ i NQ is the first eigenvector corresponding to the first historical time window when the historical target infusion task is executed for the i-th time; i =((NQ i，1 , SQ i，1 ), (NQ i，2 , SQ i，2 ),…,(NQ i，j , SQ i，j ),…,(NQ i，m , SQ i，m )), m is the number of consecutive first historical time periods included in the first historical time window; NQ i，j is the urine increase corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is performed for the i-th time; SQ i，j NQ is the average infusion speed corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is executed for the i-th time; i，j =f(YQ i，j ); f() is the preset urine volume calculation function; YQ i，j is the pressure change value of the bracket for hanging urine bag corresponding to the jth first historical time period of the first historical time window; each first eigenvector has a unique corresponding second eigenvector in the second historical time window; the end time of the first historical time window is the start time of the historical target infusion task; the end time of the first historical time window is the start time of the second historical time window; the end time of the second historical time window is the end time of the historical target infusion task; the time length of the first historical time window is equal to the time length of the second historical time window; the time length of the first historical time period is equal to the time length of the second historical time period;

[0014] The clustering unit is used to cluster NQ to obtain the corresponding cluster list set NH = (NH1, NH2, ..., NH x ,…,NH y ), x = 1, 2, ..., y, where y is the number of clusters obtained by clustering NQ; NH x is the cluster list corresponding to the xth cluster; NH x =(NH x，1 , NH x，2 ,…,NH x，a ,…,NH x，g(x) ), g(x) is the number of the first eigenvectors included in the x-th cluster; NH x，a is the second eigenvector corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; NH x，a =((NHx，a，1 , S.H. x，a，1 ), (NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，j , S.H. x，a，j ),…,(NH x，a，m , S.H. x，a，m )); NH x，a，j The urine increase corresponding to the j-th second historical time period in the second historical time window of the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; SH x，a，j is the average infusion speed of the urine bag corresponding to the jth second historical time period in the second historical time window during the ath execution of the historical target infusion task included in the xth cluster; NH x，a，j =f(YH x，a，j );YH x，a，j The pressure change value of the bracket for hanging the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster in the j-th second historical time period in the second historical time window; the matching degree of any two first feature vectors corresponding to each cluster is greater than the preset matching degree threshold; each second feature vector has a corresponding urine volume evaluation label; the urine volume evaluation label includes normal urine volume and abnormal urine volume; each cluster has a corresponding central feature vector;

[0015] A determination unit, configured to determine a target evaluation label from the urine volume evaluation label of the second feature vector corresponding to NH according to NH and a preset matching method in response to reaching the first target detection time point corresponding to the current target infusion task; wherein the preset matching method matches NH according to the first target feature vector corresponding to the current target infusion task in the first target time window and the second target feature vector corresponding to the second target time window; the end time of the first target time window is the time when the infusion start instruction corresponding to the current target infusion task is received; the time length of the first target time window is equal to the time length of the first historical time window; the start time of the second target time window is the end time of the first target time window, and the end time is the target detection time point corresponding to the current target infusion task;

[0016] A warning unit is used to issue a warning to the target device if the target evaluation tag is that the urine volume is abnormal.

[0017] In a third aspect of the present application, a non-transitory computer-readable storage medium is provided, in which at least one instruction or at least one program is stored, and the at least one instruction or at least one program is loaded and executed by a processor to implement the aforementioned method for monitoring abnormal urine volume in a urine bag.

[0018] In a fourth aspect of the present application, an electronic device is provided, comprising a processor and the above-mentioned non-transitory computer-readable storage medium.

[0019] This application has at least the following beneficial effects:

[0020] The monitoring method for abnormal urine volume in a urine bag provided by the present application first obtains the pressure change value and average infusion speed of the bracket for hanging urine bags corresponding to the historical target infusion task of the patient in the target position within the first historical time window to obtain the corresponding first feature vector list; secondly, clusters the first feature vector list to obtain the cluster list corresponding to each cluster cluster. Each cluster list contains the second feature vector corresponding to each first feature vector in the cluster cluster; then, in response to reaching the first target detection time point corresponding to the current target infusion task, the target evaluation label is determined from the urine volume evaluation label of the second feature vector corresponding to NH according to the NH and the preset matching method, and finally, if the target evaluation label is abnormal urine volume, a warning is issued to the target device.

[0021] In the present application, firstly, the pressure change value and the average infusion speed of each first historical time period of several historical target infusion tasks within a period of time before the start of infusion (first historical time window) are obtained; and multiple urination situations of patients in the target position within a period of time before the start of multiple historical target infusion tasks (no infusion or no continuous infusion) are obtained; and then the multiple urination situations are clustered, and the urination situation corresponding to each cluster before the start of the historical target infusion task is similar. Each cluster has a corresponding cluster list; the cluster list indicates the urination situation that may occur when executing the historical target infusion task and the urination situation that corresponds to the cluster before the start of the historical target infusion task. Afterwards, when judging whether the urine volume is normal when executing the current target infusion task, it is necessary to refer to the above historical data, not only the urine volume when executing the historical target infusion task, but also the urination situation before the execution of the historical target infusion task. Here, the urination situation before the execution of the historical target infusion task will also have an impact on the urine volume during the execution of the historical target infusion task. Therefore, the present application improves the accuracy of target evaluation label matching, and thus improves the accuracy of target evaluation label determination, and then issues a warning based on whether the target evaluation label is normal, so that relevant medical staff can adjust the treatment plan in time and reduce the probability of medical accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A flow chart of a method for monitoring abnormal urine volume in a urine bag provided in an embodiment of the present application;

[0024] Figure 2 This is a structural block diagram of a device for monitoring abnormal urine volume in a urine bag provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present application, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0028] Please refer to Figure 1 As shown, an embodiment of the present application provides a method for monitoring abnormal urine volume in a urine bag, which is applied to a patient in a target body position, wherein the patient in the target body position has a corresponding urine bag suspended on a target support, and a pressure sensor is provided on the target support;

[0029] S100, collecting the pressure change values ​​of the urine bag hanging bracket corresponding to a number of patients in the target position when performing the historical target infusion task within the first historical time window, so as to obtain the corresponding first feature vector list NQ = (NQ1, NQ2, ..., NQ i ,…,NQ n ); i = 1, 2, ..., n; n is the number of times the historical target infusion task is executed; NQ i NQ is the first eigenvector corresponding to the first historical time window when the historical target infusion task is executed for the i-th time; i =((NQ i，1 , SQ i，1 ), (NQ i，2 , SQ i，2 ),…,(NQ i，j , SQ i，j ),…,(NQ i，m , SQ i，m )), m is the number of consecutive first historical time periods included in the first historical time window; NQ i，j is the urine increase corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is performed for the i-th time; SQ i，j NQ is the average infusion speed corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is executed for the i-th time; i，j =f(YQ i，j ); f() is the preset urine volume calculation function; YQ i，j It is the pressure change value of the bracket for hanging urine bag corresponding to the j-th first historical time period of the first historical time window; each first eigenvector has a unique corresponding second eigenvector in the second historical time window; the end time of the first historical time window is the start time of the historical target infusion task; the end time of the first historical time window is the start time of the second historical time window; the end time of the second historical time window is the end time of the historical target infusion task; the time length of the first historical time window is equal to the time length of the second historical time window; the time length of the first historical time period is equal to the time length of the second historical time period.

[0030] Specifically, the target body position may be a supine position. Since the body position has a certain influence on the amount of urine output per unit time, in this embodiment, only the relevant historical data corresponding to the patient in the target body position is considered. Here, the historical target infusion task is an infusion task with a duration greater than the preset duration. As an example, the preset duration may be 2 hours. Then, in this embodiment, firstly, the pressure change value of the bracket for hanging urine bags corresponding to several patients in the target position when performing the historical target infusion task within the first historical time window is obtained. Here, each time the historical target infusion task is performed, a corresponding data can be obtained, and the same patient in the target position can perform multiple historical target infusion tasks; different patients in the target position may perform the historical target infusion task, thereby obtaining multiple groups of data (multiple first eigenvectors); here, the first eigenvector includes the urine increase and the average infusion speed corresponding to each first historical time period within a period of time (within the first historical time window) before each execution of the historical target infusion task; here, in the first historical time window, the corresponding patient may be in a non-infusion state, or may have performed other infusion tasks; the corresponding urine increase and average infusion speed may have multiple situations; in addition, in the first historical time window, the corresponding urination conditions such as whether the patient eats or drinks water may be different.

[0031] Furthermore, each first eigenvector has a unique corresponding second eigenvector in the second historical time window; the corresponding second eigenvector represents the increase in urine and the average infusion rate corresponding to each second historical time period in the second historical time window (within the execution time of the historical target infusion task); that is, the infusion rate and urination situation in the second historical time window.

[0032] S200, clustering NQ to obtain a corresponding cluster list set NH = (NH1, NH2, ..., NH x ,…,NH y ), x = 1, 2, ..., y, where y is the number of clusters obtained by clustering NQ; NH x is the cluster list corresponding to the xth cluster; NH x =(NH x，1 , NH x，2 ,…,NH x，a ,…,NH x，g(x) ), g(x) is the number of the first eigenvectors included in the x-th cluster; NH x，a is the second eigenvector corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; NH x，a =((NH x，a，1 , S.H. x，a，1 ), (NH x，a，2 , S.H. x，a，2 ),…,(NHx，a，j , S.H. x，a，j ),…,(NH x，a，m , S.H. x，a，m )); NH x，a，j The urine increase corresponding to the j-th second historical time period in the second historical time window of the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; SH x，a，j is the average infusion speed of the urine bag corresponding to the jth second historical time period in the second historical time window during the ath execution of the historical target infusion task included in the xth cluster; NH x，a，j =f(YH x，a，j );YH x，a，j The pressure change value of the bracket for hanging the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster in the j-th second historical time period in the second historical time window; the matching degree of any two first feature vectors corresponding to each cluster is greater than a preset matching degree threshold; each second feature vector has a corresponding urine volume evaluation label; the urine volume evaluation label includes normal urine volume and abnormal urine volume; each cluster has a corresponding central feature vector.

[0033] Specifically, NQ is clustered to obtain several clusters, each cluster contains at least one first eigenvector, and the matching degree between any two first eigenvectors corresponding to each cluster is greater than a preset matching degree threshold; in this embodiment, before each execution of the historical target infusion task, the corresponding first eigenvector in the corresponding first historical time window is obtained; and the urination situation in the first historical time window may have an impact on the relevant data in the second historical time window after the execution of the historical target infusion task begins, and the urination situation in the first historical time window may be different, and the impact on the relevant data in the second historical time window may be different; as an example: if a large amount of water is continuously drunk in the first historical time window, it may not only increase the urine volume in the first historical time window, but also increase the urine volume in the second historical time window; on the contrary, if no water is drunk in the first historical time window, the urine volume in the first historical time window may be normal, and the urine volume in the second historical time window may only be affected by the historical target infusion task. Or, if other infusion tasks (non-historical target infusion tasks) are performed in the first historical time window, it may not only increase the urine volume in the first historical time window, but also increase the urine volume in the second historical time window; on the contrary, if other infusion tasks are not performed in the first historical time window, the urine volume in the first historical time window may be normal, and the urine volume in the second historical time window may only be affected by the historical target infusion tasks. Infusion itself has a greater impact on urine volume, so in this embodiment, according to the urine volume data corresponding to each first historical time period in each first historical time window, and the average infusion speed (if no infusion, the average infusion speed is 0), the corresponding urination situation in the first historical time window is obtained.

[0034] In this embodiment, each cluster represents a type of urination situation before the start of the historical target infusion task (within the first historical time window); the urination situation before each execution of the historical target infusion task included in each cluster is similar. Furthermore, according to the second feature vector corresponding to the first feature vector included in each cluster, a cluster list corresponding to each cluster is obtained; each cluster list contains all the second feature vectors corresponding to the cluster; and each second feature vector has a corresponding urine volume evaluation label; the urine volume evaluation label includes normal urine volume and abnormal urine volume; wherein, the normal urine volume label indicates that the corresponding urine volume during the execution of the historical target infusion task (within the second historical time window) is normal; the abnormal urine volume label indicates that the corresponding urine volume during the execution of the historical target infusion task (within the second historical time window) is abnormal, wherein the abnormal may be too much or too little. In addition, each cluster has a corresponding central feature vector, which represents the average feature vector corresponding to all first feature vectors in the corresponding cluster. The central feature vector can be obtained by any method known to those skilled in the art, which will not be described here.

[0035] S300, in response to reaching the first target detection time point corresponding to the current target infusion task, the target evaluation label is determined from the urine volume evaluation label of the second feature vector corresponding to NH according to NH and a preset matching method; wherein the preset matching method matches NH according to the first target feature vector corresponding to the current target infusion task in the first target time window and the second target feature vector corresponding to the second target time window; the end time of the first target time window is the time when the infusion start instruction corresponding to the current target infusion task is received; the time length of the first target time window is equal to the time length of the first historical time window; the start time of the second target time window is the end time of the first target time window, and the end time is the target detection time point corresponding to the current target infusion task.

[0036] Specifically, step S300 also includes:

[0037] S310, in response to receiving the infusion start instruction corresponding to the current target infusion task, obtain the first target characteristic vector MQ=((MQ1, DQ1), (MQ2, DQ2), …, (MQj, DQj), …, (MQm, DQm)) of the target urine bag corresponding to the current target infusion task, wherein MQj is the increase in urine of the target urine bag corresponding to the j-th first target time period of the first target time window; DQj is the average infusion speed of the target urine bag corresponding to the j-th first target time period of the first target time window; MQj=f(LQj); LQj is the pressure change value of the bracket hanging the target urine bag in the j-th first target time period of the first target time window.

[0038] Here, in response to receiving the infusion start instruction corresponding to the current target infusion task, the urine volume data and average infusion speed corresponding to the target urine bag before the current target infusion task (within the first target time window) are first obtained to obtain the corresponding urination situation before the start of the current target infusion task, and whether infusion has been performed.

[0039] S320, according to MQ and NH, obtain the corresponding first matching list YP=(YP1, YP2, ..., YP x , …, YP y ), among which, YP x For MQ and NH x The corresponding central eigenvector NHZ x The degree of match between them.

[0040] Among them, YP x Meet the following conditions:

[0041] YP x =(MQ·NHZ x ) / (|MQ|×|NHZ x |).

[0042] S330, if MAX(YP)=YP x , then determine NH x is the target cluster list.

[0043] Here, YP x The larger the value is, the more the first target feature vector corresponding to the current target infusion task is consistent with NH x The corresponding central eigenvector NHZ x The greater the match between them, the more similar the two feature vectors are. x This indicates that the corresponding urination and infusion conditions in the first target time window before the current target infusion task is executed are consistent with NHZ x The corresponding urination and infusion conditions are most similar, which means that the corresponding urination and infusion conditions of the current target infusion task in the first target time window have the same influence on the urine volume of the current target infusion task in the second target time window as NHZ. x The corresponding urination conditions and infusion conditions in the first historical time window have the most similar effects on the urine volume in the second historical time window. x is the target cluster list.

[0044] S340, in response to reaching the first target detection time point corresponding to the current target infusion task, obtaining a second target feature vector MH corresponding to the target urine bag = ((MH1, DH1), (MH2, DH2), ..., (MH p, DH p ),…,(MH p , DH q )); p = 1, 2, ..., q; wherein q is the number of second target time periods included when the first target detection time point corresponding to the current target infusion task is reached; MH p DH is the urine increase corresponding to the pth second target time period when the first target detection time point corresponding to the current target infusion task is reached; p MH is the average infusion speed corresponding to the pth second target time period contained in the first target detection time point corresponding to the current target infusion task; p =f(BQ p );BQ p It is the pressure change value of the bracket hanging the target urine bag within the pth second target time period included when the first target detection time point corresponding to the current target infusion task is reached; the time length of the second target time period is equal to the time length of the first historical time period; q<m.

[0045] Here, the first target detection time point may be a time point before the current target infusion task ends, for example, 30 minutes before the current target infusion task starts. This embodiment obtains the second target feature vector corresponding to the first target detection time point corresponding to the current target infusion task.

[0046] S350, according to MH and NH x , get the corresponding second matching list EP x =(EP x，1 , E.P. x，2 , …, EP x，a , …, EP x，g(x) );EP x，a For MH and NHM x，a The matching degree between NHM x，a To detect NH according to the first target time point x The first intercepted feature vector obtained by interception; NHM x，a =((NH x，a，1 , S.H. x，a，1 ), (NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，p , S.H. x，a，p ),…,(NH x，a，q , S.H. x，a，q )).

[0047] EP x，a Meet the following conditions:

[0048] EP x，a =(MH·NHMx，a ) / (|MH|×|NHM x，a |).

[0049] S360, if MAX(EP x )=EP x，a NH x，a The corresponding urine volume evaluation label is used as the target evaluation label of the current urine volume of the target urine bag.

[0050] Here, from NH x The urine volume data and the average infusion speed data of the time length corresponding to the second target feature vector are intercepted from each corresponding second feature vector to obtain a plurality of first intercepted feature vectors. x，a It represents the similarity between the average infusion speed and urine volume data corresponding to the time when the current target infusion task reaches the first target detection time point and the first intercepted feature vector (the urine volume data and the average infusion speed data of the time length corresponding to the second target feature vector) intercepted according to the a-th second feature vector in the target cluster list. In this embodiment, since the target cluster list has corresponding multiple infusion conditions and urination conditions when executing historical target infusion tasks; and in order to be able to timely judge whether the urine volume corresponding to the current target infusion task is normal, the urine volume change data and the average infusion speed data after a period of time from the start of the current target infusion task are first obtained, and then matched with each second feature vector in the target cluster list that is similar to the urination situation before infusion, and in order to improve the accuracy of the matching, each second feature vector in the target cluster list is intercepted according to the first target detection time point, and then matched. If MAX(EP x )=EP x，a This means that NH x，a The corresponding changes in urine volume and average infusion speed from the start of the historical target infusion task to the first target detection time point are most similar to the changes in urine volume and average infusion speed from the start of the current target infusion task to the first target detection time point. x，a The corresponding label is likely to represent the status of the current target infusion task (normal or abnormal urine output).

[0051] S400: If the target evaluation tag is that the urine volume is abnormal, a warning is issued to the target device.

[0052] Specifically, if the target evaluation tag is that the urine volume is abnormal, a warning is issued to the target device, so as to remind the relevant medical staff.

[0053] In an exemplary embodiment of the present application, after step S300, the method further includes:

[0054] S500, if the target evaluation label is that the urine volume is normal, and the second target detection time point corresponding to the current target infusion task is reached, obtain the third target feature vector AH corresponding to the target urine bag = ((AH1, JH1), (AH2, JH2), ..., (AH r , J.H. r ),…,(AH s , J.H. s )); r = 1, 2, ..., s; where s is the number of third target time periods included when the second target detection time point corresponding to the current target infusion task is reached; AH r JH is the urine increase corresponding to the rth third target time period when the second target detection time point corresponding to the current target infusion task is reached; r AH is the average infusion speed corresponding to the rth third target time period when the second target detection time point corresponding to the current target infusion task is reached; r =f(CQ r );CQ r It is the pressure change value of the bracket hanging the target urine bag within the rth third target time period included when the second target detection time point corresponding to the current target infusion task is reached; the time length of the third target time period is equal to the time length of the first historical time period; q<s≤m.

[0055] S600, according to AH and NH x , get the corresponding third matching list AP x =(AP x，1 , A.P. x，2 , …, AP x，a , …, AP x，g(x) );AP x，a For AH and NHN x，a The matching degree between NHN x，a To detect the time point of NH according to the second target x The second intercepted feature vector obtained by interception; NHN x，a =((NH x，a，1 , S.H. x，a，1 ), (NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，r , S.H. x，a，r ),…,(NH x，a，s , S.H. x，a，s )).

[0056] Among them, AP x，a Meet the following conditions:

[0057] AP x，a =(AH·NHN x，a) / (|AH|×|NHN x，a |).

[0058] S360, if MAX(AP x )=AP x，a NH x，a The corresponding urine volume evaluation label is used as the target evaluation label of the current urine volume of the target urine bag; and the process jumps to step S400.

[0059] In this embodiment, if the target evaluation label is that the urine volume is normal, the monitoring will continue. If the second target detection time point corresponding to the current target infusion task is reached, that is, the next detection time point, all average infusion speed and urine volume change data before the second target detection time point are obtained to obtain the corresponding third target feature vector, and then the matching degree between the second intercepted feature vector obtained according to the second target detection time point in the target list is determined, and the label corresponding to the second feature vector with the highest matching degree is used as the target evaluation label. That is, the label corresponding to the second feature vector with the highest matching degree may be the label corresponding to the current target infusion task. In this way, the continuous monitoring of the urination situation corresponding to the current target infusion task is realized, and the corresponding label is assigned to the current target infusion task when it reaches the second target detection time point according to the historical data, so as to determine whether the urine volume of the current target infusion task when it reaches the second target detection time point may be abnormal, so as to remind the relevant medical staff.

[0060] It should be noted that the steps of continuously monitoring the entire current target infusion task according to the above embodiment are the same as above and will not be repeated here.

[0061] Please refer to Figure 2 As shown, an embodiment of the present application provides a monitoring device 100 for abnormal urine volume in a urine bag, which is applied to a patient in a target body position, wherein the patient in the target body position has a corresponding urine bag suspended on a target support, and a pressure sensor is provided on the target support;

[0062] The device comprises:

[0063] The collecting unit is used to collect the pressure change values ​​of the urine bag hanging bracket corresponding to a number of patients in the target position when performing the historical target infusion task within the first historical time window to obtain the corresponding first feature vector list NQ = (NQ1, NQ2, ..., NQ i ,…,NQ n ); i = 1, 2, ..., n; n is the number of times the historical target infusion task is executed; NQ i NQ is the first eigenvector corresponding to the first historical time window when the historical target infusion task is executed for the i-th time; i =((NQ i，1, SQ i，1 ), (NQ i，2 , SQ i，2 ),…,(NQ i，j , SQ i，j ),…,(NQ i，m , SQ i，m )), m is the number of consecutive first historical time periods included in the first historical time window; NQ i，j is the urine increase corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is performed for the i-th time; SQ i，j NQ is the average infusion speed corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is executed for the i-th time; i，j =f(YQ i，j ); f() is the preset urine volume calculation function; YQ i，j is the pressure change value of the bracket for hanging urine bag corresponding to the jth first historical time period of the first historical time window; each first eigenvector has a unique corresponding second eigenvector in the second historical time window; the end time of the first historical time window is the start time of the historical target infusion task; the end time of the first historical time window is the start time of the second historical time window; the end time of the second historical time window is the end time of the historical target infusion task; the time length of the first historical time window is equal to the time length of the second historical time window; the time length of the first historical time period is equal to the time length of the second historical time period;

[0064] The clustering unit is used to cluster NQ to obtain the corresponding cluster list set NH = (NH1, NH2, ..., NH x ,…,NH y ), x = 1, 2, ..., y, where y is the number of clusters obtained by clustering NQ; NH x is the cluster list corresponding to the xth cluster; NH x =(NH x，1 , NH x，2 ,…,NH x，a ,…,NH x，g(x) ), g(x) is the number of the first eigenvectors included in the x-th cluster; NH x，a is the second eigenvector corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; NH x，a =((NH x，a，1 , S.H. x，a，1 ), (NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，j , S.H. x，a，j ),…,(NHx，a，m , S.H. x，a，m )); NH x，a，j The urine increase corresponding to the j-th second historical time period in the second historical time window of the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; SH x，a，j is the average infusion speed of the urine bag corresponding to the jth second historical time period in the second historical time window during the ath execution of the historical target infusion task included in the xth cluster; NH x，a，j =f(YH x，a，j );YH x，a，j The pressure change value of the bracket for hanging the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster in the j-th second historical time period in the second historical time window; the matching degree of any two first feature vectors corresponding to each cluster is greater than the preset matching degree threshold; each second feature vector has a corresponding urine volume evaluation label; the urine volume evaluation label includes normal urine volume and abnormal urine volume; each cluster has a corresponding central feature vector;

[0065] A determination unit, configured to determine a target evaluation label from the urine volume evaluation label of the second feature vector corresponding to NH according to NH and a preset matching method in response to reaching the first target detection time point corresponding to the current target infusion task; wherein the preset matching method matches NH according to the first target feature vector corresponding to the current target infusion task in the first target time window and the second target feature vector corresponding to the second target time window; the end time of the first target time window is the time when the infusion start instruction corresponding to the current target infusion task is received; the time length of the first target time window is equal to the time length of the first historical time window; the start time of the second target time window is the end time of the first target time window, and the end time is the target detection time point corresponding to the current target infusion task;

[0066] A warning unit is used to issue a warning to the target device if the target evaluation tag is that the urine volume is abnormal.

[0067] An embodiment of the present application further provides a computer program product, which includes program code. When the program product is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the method according to various exemplary embodiments of the present application described above in this specification.

[0068] In addition, although the steps of the method in the present application are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0069] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0070] In an exemplary embodiment of the present application, an electronic device capable of implementing the above method is also provided.

[0071] Those skilled in the art will appreciate that various aspects of the present application may be implemented as a system, method or program product. Therefore, various aspects of the present application may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to as "circuit", "module" or "system" herein.

[0072] The electronic device according to this embodiment of the present application is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0073] The electronic device is presented in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: the at least one processor mentioned above, the at least one storage device mentioned above, and a bus connecting different system components (including storage devices and processors).

[0074] The storage stores program codes, which can be executed by the processor, so that the processor executes the steps described in the above “Exemplary Method” section of this specification according to various exemplary embodiments of the present application.

[0075] The memory may include readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read only memory (ROM).

[0076] The storage may also include a program / utility having a set (at least one) of program modules, such program modules including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0077] The bus may represent one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0078] The electronic device can also communicate with one or more external devices (such as keyboards, pointing devices, Bluetooth devices, etc.), and can also communicate with one or more devices that enable users to interact with the electronic device, and / or communicate with any device (such as routers, modems, etc.) that enables the electronic device to communicate with one or more other computing devices. This communication can be carried out through an input / output (I / O) interface. In addition, the electronic device can also communicate with one or more networks (such as local area networks (LANs), wide area networks (WANs) and / or public networks, such as the Internet) through a network adapter. As shown in the figure, the network adapter communicates with other modules of the electronic device through a bus. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0079] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0080] In an exemplary embodiment of the present application, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present application can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary implementations of the present application described in the above "Exemplary Method" section of the present specification.

[0081] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0082] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0083] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0084] Program code for performing the operations of the present application may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0085] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0086] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0087] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for monitoring abnormal urine volume in a urine bag, characterized in that: Applicable to a patient in a target position, the patient in the target position having a corresponding urine bag suspended on a target support, the target support being provided with a pressure sensor; The method comprises: S100, collecting the pressure change values ​​of the urine bag hanging bracket corresponding to a number of patients in the target position when performing the historical target infusion task within the first historical time window, so as to obtain the corresponding first feature vector list NQ=(NQ1, NQ2, ..., NQ i ,…,NQ n ); i = 1, 2, ..., n; n is the number of times the historical target infusion task is executed; NQ i NQ is the first eigenvector corresponding to the first historical time window when the historical target infusion task is executed for the i-th time; i =((NQ i，1 , SQ i，1 ), (NQ i，2 , SQ i，2 ),…,(NQ i，j , SQ i，j ),…,(NQ i，m , SQ i，m ), m is the number of consecutive first historical time periods included in the first historical time window; NQ i，j is the urine increase corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is performed for the i-th time; SQ i，j NQ is the average infusion speed corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is executed for the i-th time; i，j =f(YQ i，j ); f() is the preset urine volume calculation function; YQ i，j is the pressure change value of the bracket for hanging urine bag corresponding to the jth first historical time period of the first historical time window; each first eigenvector has a unique corresponding second eigenvector in the second historical time window; the end time of the first historical time window is the start time of the historical target infusion task; the end time of the first historical time window is the start time of the second historical time window; the end time of the second historical time window is the end time of the historical target infusion task; the time length of the first historical time window is equal to the time length of the second historical time window; the time length of the first historical time period is equal to the time length of the second historical time period; S200, clustering NQ to obtain a corresponding cluster list set NH = (NH1, NH2, ..., NH x ,…,NH y ), x=1, 2, …, y, where y is the number of clusters obtained by clustering NQ; NH x is the cluster list corresponding to the xth cluster; NH x =(NH x，1 , NH x，2 ,…,NH x，a ,…,NH x，g（x） ), g(x) is the number of the first eigenvectors included in the x-th cluster; NH x，a is the second eigenvector corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; NH x，a =(NH x，a，1 , S.H. x，a，1 ), NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，j , S.H. x，a，j ),…,(NH x，a，m , S.H. x，a，m )); NH x，a，j The urine increase corresponding to the j-th second historical time period in the second historical time window of the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; SH x，a，j is the average infusion speed of the urine bag corresponding to the jth second historical time period in the second historical time window during the ath execution of the historical target infusion task included in the xth cluster; NH x，a，j =f(YH x，a，j ); YH x，a，j The pressure change value of the bracket for hanging the urine bag corresponding to the jth second historical time period in the second historical time window of the urine bag corresponding to the ath execution of the historical target infusion task included in the xth cluster; the matching degree of any two first feature vectors corresponding to each cluster is greater than the preset matching degree threshold; each second feature vector has a corresponding urine volume evaluation label; the urine volume evaluation label includes normal urine volume and abnormal urine volume; each cluster has a corresponding central feature vector; the urination situation in the first historical time window will have an impact on the relevant data in the second historical time window after the execution of the historical target infusion task begins, and different urination situations in the first historical time window have different impacts on the relevant data in the second historical time window; S300, in response to reaching the first target detection time point corresponding to the current target infusion task, determining the target evaluation label from the urine volume evaluation label of the second feature vector corresponding to NH according to NH and a preset matching method; wherein the preset matching method matches NH according to the first target feature vector corresponding to the current target infusion task in the first target time window and the second target feature vector corresponding to the second target time window; the end time of the first target time window is the time when the infusion start instruction corresponding to the current target infusion task is received; the time length of the first target time window is equal to the time length of the first historical time window; the start time of the second target time window is the end time of the first target time window, and the end time is the target detection time point corresponding to the current target infusion task; S400: If the target evaluation tag is that the urine volume is abnormal, a warning is issued to the target device.

2. The method for monitoring abnormal urine volume in a urine bag according to claim 1, characterized in that: Step S300 also includes: S310, in response to receiving the infusion start instruction corresponding to the current target infusion task, obtaining the first target feature vector MQ=((MQ1, DQ1), (MQ2, DQ2), …, (MQj, DQj), …, (MQm, DQm)) of the target urine bag corresponding to the current target infusion task, wherein MQj is the urine increase corresponding to the j-th first target time period of the target urine bag in the first target time window; DQj is the average infusion speed corresponding to the j-th first target time period of the target urine bag in the first target time window; MQj=f(LQj); LQj is the pressure change value of the bracket hanging the target urine bag in the j-th first target time period of the first target time window; S320, according to MQ and NH, obtain the corresponding first matching list YP=(YP1, YP2, ..., YP x , …, YP y ), among which, YP x For MQ and NH x The corresponding central eigenvector NHZ x The degree of match between S330, if MAX(YP)=YP x , then determine NH x is the target cluster list; S340, in response to reaching the first target detection time point corresponding to the current target infusion task, obtaining a second target feature vector MH corresponding to the target urine bag = (MH1, DH1), (MH2, DH2), ..., (MH p , DH p ),…,(MH q , DH q )); p = 1, 2, ..., q; where q is the number of second target time periods included when the first target detection time point corresponding to the current target infusion task is reached; MH p DH is the urine increase corresponding to the pth second target time period when the first target detection time point corresponding to the current target infusion task is reached; p MH is the average infusion speed corresponding to the pth second target time period included when reaching the first target detection time point corresponding to the current target infusion task; p =f(BQ p );BQ p is the pressure change value of the bracket hanging the target urine bag in the pth second target time period when the first target detection time point corresponding to the current target infusion task is reached; the time length of the second target time period is equal to the time length of the first historical time period; q<m; S350, according to MH and NH x , get the corresponding second matching list EP x =(EP x，1 , E.P. x，2 , …, EP x，a , …, EP x，g（x） );EP x，a For MH and NHM x，a The matching degree between NHM x，a To detect NH according to the first target time point x The first intercepted feature vector obtained by interception; NHM x，a =(NH x，a，1 , S.H. x，a，1 ), NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，p , S.H. x，a，p ),…,(NH x，a，q , S.H. x，a，q )); S360, if MAX (EP x ) =EP x，a NH x，a The corresponding urine volume evaluation label is used as the target evaluation label of the current urine volume of the target urine bag.

3. The method for monitoring abnormal urine volume in a urine bag according to claim 2, characterized in that: YP x Meet the following conditions: YP x =(MQ·NHZ x ) / (|MQ|×|NHZ x |)。 4. The method for monitoring abnormal urine volume in a urine bag according to claim 2, characterized in that: EP x，a Meet the following conditions: EP x，a =(MH·NHM x，a ) / (|MH|×|NHM x，a |).

5. The method for monitoring abnormal urine volume in a urine bag according to claim 2, characterized in that: After step S300, the method further includes: S500, if the target evaluation label is that the urine volume is normal, and the second target detection time point corresponding to the current target infusion task is reached, obtain the third target feature vector AH corresponding to the target urine bag = ((AH1, JH1), (AH2, JH2), ..., (AH r , J.H. r ),…,(AH s , J.H. s )); r = 1, 2, ..., s; where s is the number of third target time periods included when the second target detection time point corresponding to the current target infusion task is reached; AH r JH is the urine increase corresponding to the rth third target time period when the second target detection time point corresponding to the current target infusion task is reached; r AH is the average infusion speed corresponding to the rth third target time period when the second target detection time point corresponding to the current target infusion task is reached; r =f(CQ r );CQ r is the pressure change value of the bracket hanging the target urine bag in the rth third target time period when the second target detection time point corresponding to the current target infusion task is reached; the time length of the third target time period is equal to the time length of the first historical time period; q<s≤m; S600, according to AH and NH x , get the corresponding third matching list AP x =(AP x，1 , A.P. x，2 , …, AP x，a , …, AP x，g（x） );AP x，a For AH and NHN x，a The matching degree between NHN x，a To detect the time point of NH according to the second target x The second intercepted feature vector obtained by interception; NHN x，a =(NH x，a，1 , S.H. x，a，1 ), NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，r , S.H. x，a，r ),…,(NH x，a，s , S.H. x，a，s )); S360, if MAX (AP x )=AP x，a NH x，a The corresponding urine volume evaluation label is used as the target evaluation label of the current urine volume of the target urine bag; and the process jumps to step S400.

6. The method for monitoring abnormal urine volume in a urine bag according to claim 5, characterized in that: AP x，a Meet the following conditions: AP x，a =(AH·NHN x，a ) / (|AH|×|NHN x，a |)。 7. A monitoring device for abnormal urine volume in a urine bag, characterized in that: Applicable to a patient in a target position, the patient in the target position having a corresponding urine bag suspended on a target support, the target support being provided with a pressure sensor; The device comprises: The collecting unit is used to collect the pressure change values ​​of the urine bag hanging bracket corresponding to a number of patients in the target position when performing the historical target infusion task within the first historical time window, so as to obtain the corresponding first feature vector list NQ=(NQ1, NQ2, ..., NQ i ,…,NQ n ); i = 1, 2, ..., n; n is the number of times the historical target infusion task is executed; NQ i NQ is the first eigenvector corresponding to the first historical time window when the historical target infusion task is executed for the i-th time; i =((NQ i，1 , SQ i，1 ), (NQ i，2 , SQ i，2 ),…,(NQ i，j , SQ i，j ),…,(NQ i，m , SQ i，m ), m is the number of consecutive first historical time periods included in the first historical time window; NQ i，j is the urine increase corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is performed for the i-th time; SQ i，j NQ is the average infusion speed corresponding to the jth first historical time period in the first historical time window when the historical target infusion task is executed for the i-th time; i，j =f(YQ i，j ); f() is the preset urine volume calculation function; YQ i，j is the pressure change value of the bracket for hanging urine bag corresponding to the jth first historical time period of the first historical time window; each first eigenvector has a unique corresponding second eigenvector in the second historical time window; the end time of the first historical time window is the start time of the historical target infusion task; the end time of the first historical time window is the start time of the second historical time window; the end time of the second historical time window is the end time of the historical target infusion task; the time length of the first historical time window is equal to the time length of the second historical time window; the time length of the first historical time period is equal to the time length of the second historical time period; Clustering unit, used to cluster NQ to obtain the corresponding cluster list set NH = (NH1, NH2, ..., NH x ,…,NH y ), x=1, 2, …, y, where y is the number of clusters obtained by clustering NQ; NH x is the cluster list corresponding to the xth cluster; NH x =(NH x，1 , NH x，2 ,…,NH x，a ,…,NH x，g（x） ), g(x) is the number of the first eigenvectors included in the x-th cluster; NH x，a is the second eigenvector corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; NH x，a =(NH x，a，1 , S.H. x，a，1 ), NH x，a，2 , S.H. x，a，2 ),…,(NH x，a，j , S.H. x，a，j ),…,(NH x，a，m , S.H. x，a，m )); NH x，a，j The urine increase corresponding to the j-th second historical time period in the second historical time window of the urine bag corresponding to the a-th execution of the historical target infusion task included in the x-th cluster; SH x，a，j is the average infusion speed of the urine bag corresponding to the jth second historical time period in the second historical time window during the ath execution of the historical target infusion task included in the xth cluster; NH x，a，j =f(YH x，a，j ); YH x，a，j The pressure change value of the bracket for hanging the urine bag corresponding to the jth second historical time period in the second historical time window of the urine bag corresponding to the ath execution of the historical target infusion task included in the xth cluster; the matching degree of any two first feature vectors corresponding to each cluster is greater than the preset matching degree threshold; each second feature vector has a corresponding urine volume evaluation label; the urine volume evaluation label includes normal urine volume and abnormal urine volume; each cluster has a corresponding central feature vector; the urination situation in the first historical time window will have an impact on the relevant data in the second historical time window after the execution of the historical target infusion task begins, and different urination situations in the first historical time window have different impacts on the relevant data in the second historical time window; A determination unit, configured to determine a target evaluation label from the urine volume evaluation label of the second feature vector corresponding to NH according to NH and a preset matching method in response to reaching the first target detection time point corresponding to the current target infusion task; wherein the preset matching method matches NH according to the first target feature vector corresponding to the current target infusion task in the first target time window and the second target feature vector corresponding to the second target time window; the end time of the first target time window is the time when the infusion start instruction corresponding to the current target infusion task is received; the time length of the first target time window is equal to the time length of the first historical time window; the start time of the second target time window is the end time of the first target time window, and the end time is the target detection time point corresponding to the current target infusion task; A warning unit is used to issue a warning to the target device if the target evaluation tag is that the urine volume is abnormal.

8. A non-transitory computer-readable storage medium, characterized in that: The storage medium stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the method according to any one of claims 1 to 6.

9. An electronic device, characterized in that: The invention comprises a processor and the non-transitory computer-readable storage medium as claimed in claim 8.

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