CN115414550A - Intelligent transfusion nursing system and method - Google Patents

Intelligent transfusion nursing system and method Download PDF

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CN115414550A
CN115414550A CN202211172524.XA CN202211172524A CN115414550A CN 115414550 A CN115414550 A CN 115414550A CN 202211172524 A CN202211172524 A CN 202211172524A CN 115414550 A CN115414550 A CN 115414550A
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CN115414550B (en
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蔡小凤
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First Affiliated Hospital of Zhejiang University School of Medicine
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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • A61M5/168Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body
    • A61M5/16831Monitoring, detecting, signalling or eliminating infusion flow anomalies
    • A61M5/1684Monitoring, detecting, signalling or eliminating infusion flow anomalies by detecting the amount of infusate remaining, e.g. signalling end of infusion
    • A61M5/16845Monitoring, detecting, signalling or eliminating infusion flow anomalies by detecting the amount of infusate remaining, e.g. signalling end of infusion by weight
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    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • A61M5/168Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body
    • A61M5/16886Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body for measuring fluid flow rate, i.e. flowmeters
    • A61M5/16895Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body for measuring fluid flow rate, i.e. flowmeters by monitoring weight change, e.g. of infusion container
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06KGRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K17/00Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
    • G06K17/0022Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
    • G06K17/0025Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement consisting of a wireless interrogation device in combination with a device for optically marking the record carrier
    • GPHYSICS
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    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M2205/00General characteristics of the apparatus
    • A61M2205/60General characteristics of the apparatus with identification means
    • A61M2205/6009General characteristics of the apparatus with identification means for matching patient with his treatment, e.g. to improve transfusion security

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Abstract

The invention provides an intelligent transfusion nursing system and method, belonging to the technical field of intelligent hospitals, and specifically comprising the following steps: reading the weight of a transfusion bottle to be input at a nurse station, and confirming the input time of the transfusion bottle based on the weight of the transfusion bottle; based on the age of the patient, the severity of the disease and the self-care ability of the body, obtaining the identity characteristics of the patient by adopting a prediction model based on a machine learning algorithm, confirming the input time threshold of the infusion bottle based on the identity characteristics of the patient and the time input by the infusion bottle, and confirming the residual input time of the infusion bottle by combining an infusion bottle weight measuring device and an image processing device in a ward when the time input by the infusion bottle is greater than the input time threshold; when the residual input time of the transfusion bottle is less than the first time threshold value, the nurse station is reminded to perform corresponding nursing operation, and the measuring accuracy and the safety of patients are improved.

Description

Intelligent transfusion nursing system and method
Technical Field
The invention belongs to the technical field of intelligent hospitals, and particularly relates to an intelligent transfusion nursing system and method.
Background
Infusion and injection are important treatment methods for maintaining the fluid balance of critically ill patients and are also the most common methods used in hospitals during ordinary treatment work. In hospitals all over the country, the number of patients needing infusion is not large, medical accidents caused by improper infusion happen occasionally, and the correct infusion mode directly concerns the treatment effect of the patients. Anesthesia infusion and ICU infusion are special infusion modes, and unnecessary injuries and even death of patients can be caused by slight negligence in the infusion process.
In order to realize online monitoring of a patient infusion process and provide targeted care according to a monitoring result, a weight-based infusion monitor is designed by a writer, named sheng and ji in a transfusion process monitoring system based on a ZigBee wireless sensor network in a master thesis, and through the weight-based infusion monitor, infusion weight data and related operation conditions can be transmitted to a server side in real time, and a client side of a nurse station can receive infusion monitoring data in real time and provide corresponding care service according to the infusion monitoring data, but the following technical problems exist:
1. neglected the difference of different patients, set up the same warning threshold value of changing dressings to the patient of different ages, disease severity to possibly can lead to some disease severity comparatively serious and the older patient can not change dressings on time, thereby cause unnecessary injury to patient.
2. Only rely on weight monitoring, not only the rate of accuracy is not high, and power consumption is great moreover, appears easily that the battery changes the unable normal monitoring that leads to in time to make the unable accurate reliable realization to the monitoring of infusion process.
Based on the technical problems, an intelligent transfusion nursing system and method need to be designed.
Disclosure of Invention
The invention aims to provide an intelligent transfusion nursing system and method.
The invention provides an intelligent infusion nursing method, which is characterized by comprising the following steps:
s11, reading the weight of a hanging bottle to be input at a nurse station, and confirming the input time of the hanging bottle based on the weight of the hanging bottle;
s12, based on the age of a patient, the severity of a disease and the self-care ability of a body, obtaining the identity characteristics of the patient by adopting a prediction model based on a machine learning algorithm, confirming the input time threshold of a transfusion bottle based on the identity characteristics of the patient and the time input by the transfusion bottle, and when the time input by the transfusion bottle is greater than the input time threshold, combining a transfusion bottle weight measuring device and an image processing device in a ward to confirm the residual input time of the transfusion bottle;
s13, when the remaining input time of the infusion bottle is smaller than a first time threshold value, reminding the nurse station to carry out corresponding nursing operation.
The method comprises the steps of reading the weight of a hanging bottle at a nurse station, obtaining the input time of the hanging bottle according to the reading result, obtaining the input time threshold value of the hanging bottle by adopting the identity characteristics of a patient and the input time of the hanging bottle, solving the technical problem that unnecessary body injury is caused to the patient due to the fact that the identity difference of different patients is not considered when the threshold value is set originally, and performing targeted nursing to the patient more purposefully.
Through the age based on patient, the severity of disease, the identity characteristic of patient is built to health self-care ability, and set up the input time threshold of transfusion bottle according to patient's identity characteristic, thereby make can be pertinence provide nursing service to patient, it is older to some ages, and the patient that the severity is comparatively serious, identity characteristic is less, it is littleer to input time threshold setting, guaranteed that patient can obtain priority nursing, patient's experience has been improved, the harm to patient has been reduced.
By adopting the input time threshold, the infusion bottle weight measuring device and the image processing device in the ward do not need to work constantly, so that the electric energy consumption is greatly saved, the measuring precision is ensured, the technical problem of inaccurate measuring result caused by damage or power shortage of a certain device is prevented, and the measuring reliability and accuracy are improved.
The further technical scheme is that the specific steps for confirming the input time of the transfusion bottle comprise:
s21, extracting a two-dimensional code label of the transfusion bottle body, and confirming the medicine type of the transfusion bottle, the weight of the transfusion bottle, the bed number corresponding to the transfusion bottle and the disease type of a patient by adopting a two-dimensional code recognition device;
s22, matching the types of the infusion bottles with the types of the infusion bottles in a database based on the types of the infusion bottles, and determining the historical input efficiency of the infusion bottles according to the matching result;
s23, obtaining the infusion bottle input time based on the historical input efficiency and the weight of the infusion bottle.
Through the setting of two-dimensional code label to the weight of the discernment transfusion bottle medicine type that can be convenient and accurate, the bed number and the patient disease type that the transfusion bottle corresponds, and prevented because the medicine mistake leads to the fact the appearance of the problem of injury to patient, promoted stability.
Historical input efficiency is obtained through the matching result based on the types of the infusion bottles in the database, so that infusion bottle input time can be obtained based on historical data, and the infusion bottle input time result is more accurate.
The further technical scheme is that a time correction coefficient is obtained based on the disease type of the patient, and the time input by the hanging bottle is corrected based on the time correction coefficient to obtain the correction time input by the hanging bottle.
Due to the fact that different diseases have different requirements on the time input by the infusion bottle, through the construction of the time correction coefficient, the patient can be nursed more pertinently, and reliability and consistency are improved.
The further technical scheme is that the specific steps for confirming the identity characteristics of the patient are as follows:
s31, extracting the age, the severity of diseases and the self-care ability of the patient to construct an input set;
s32, inputting the input set into a prediction model based on a GRU algorithm to obtain a prediction result;
s33, obtaining the identity characteristics of the patient based on the prediction result.
The further technical scheme is that the learning rate of the GRU algorithm is optimized based on a WOA algorithm.
By optimizing the learning rate, the convergence rate of the GRU algorithm is further improved, the technical problem of too low convergence caused by too high or too low learning rate is prevented, and the stability and efficiency of algorithm convergence are ensured.
The further technical scheme is that a convergence factor of the WOA algorithm is improved, wherein the calculation formula of the convergence factor is as follows:
Figure BDA0003863842720000031
wherein K 1 As a weight value, the value is more than 1, T is the current iteration number, T max Is the maximum number of iterations.
The further technical scheme is that the calculation formula of the input time threshold is as follows:
Figure BDA0003863842720000032
wherein X 1 The identity of the patient is evaluated as K and K is between 0 and 1 2 And T and Y are constant, and are respectively the time for inputting the infusion bottle and the initial time threshold.
The further technical scheme is that the specific steps for confirming the residual input time of the transfusion bottle comprise:
s41, when the input time of the transfusion bottle is greater than an input time threshold value, the step S42 is executed;
s42, measuring the weight of the infusion bottle by adopting an infusion bottle weight measuring device in a ward, confirming the initial residual input time of the infusion bottle based on the weight of the infusion bottle, and entering a step S43 when the initial residual input time is smaller than a second time threshold, wherein the first time threshold is smaller than the second time threshold;
s43, an image processing device is adopted to perform recognition processing on the image of the hanging bottle to obtain a processing result, and the remaining input time of the hanging bottle is obtained according to the processing result.
The initial residual input time of the transfusion bottle is confirmed by adopting the transfusion bottle weight measuring device, and when the initial residual input time is smaller than the second time threshold value, the residual input time of the transfusion bottle is obtained by adopting the image processing device, so that the accuracy of the detection result can be ensured on the basis of saving unnecessary detection.
The invention provides an intelligent transfusion nursing system, which adopts the intelligent transfusion nursing method and specifically comprises the following steps:
the device comprises a time determining module, a threshold determining module, a residual input time determining module and a result reminding module;
wherein the time determination module is responsible for confirming the time of the transfusion bottle input;
the threshold determination module is responsible for constructing identity characteristics of a patient and confirming an input time threshold of the infusion bottle based on the identity characteristics of the patient and the time input by the infusion bottle;
the residual input time determining module is responsible for determining the residual input time of the infusion bottle by combining the infusion bottle weight measuring device and the image processing device in the ward;
the result reminding module is responsible for reminding the nurse station to carry out corresponding nursing operation.
In another aspect, a computer-readable storage medium is provided in the embodiments of the present application, and has a computer program stored thereon, where the computer program is used to make a computer execute one of the intelligent infusion nursing methods described above when the computer program is executed in the computer.
In another aspect, a computer program product is provided in an embodiment of the present application, where the computer program product stores instructions that, when executed by a computer, cause the computer to implement an intelligent infusion care method as described above.
Additional features and advantages will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
Fig. 1 is a flow chart of a method of intelligent infusion care according to example 1;
FIG. 2 is a flow chart showing the specific steps for confirming the time of infusion of the transfusion bottle in example 1;
FIG. 3 is a flowchart showing the detailed steps of confirming the identity of the patient in example 1;
FIG. 4 is a flow chart showing the specific steps of confirming the remaining input time of the transfusion bottle in example 1;
fig. 5 is a block diagram of an intelligent infusion care system according to embodiment 2.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus a detailed description thereof will be omitted.
The terms "a," "an," "the," "said" are used to indicate the presence of one or more elements/components/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.
Example 1
In order to solve the above problem, according to an aspect of the present invention, as shown in fig. 1, there is provided an intelligent infusion nursing method, which is characterized by specifically including:
s11, reading the weight of a hanging bottle to be input at a nurse station, and confirming the input time of the hanging bottle based on the weight of the hanging bottle;
for example, the infusion time can be obtained by combining a set average infusion rate or a set infusion rate with a set average infusion rate or a set infusion rate, such as weighing or labeling.
S12, based on the age of a patient, the severity of a disease and the self-care ability of a body, obtaining the identity characteristics of the patient by adopting a prediction model based on a machine learning algorithm, confirming the input time threshold of a transfusion bottle based on the identity characteristics of the patient and the time input by the transfusion bottle, and when the time input by the transfusion bottle is greater than the input time threshold, combining a transfusion bottle weight measuring device and an image processing device in a ward to confirm the residual input time of the transfusion bottle;
for example, the value of the patient's identity is between 0.9 and 1.3, wherein the greater the age of the patient, the greater the severity of the disease, the poorer the self-care ability of the patient, and the greater the patient's identity.
For example, the remaining input time of the infusion bottle may be determined by measuring the remaining weight of the infusion bottle with a infusion bottle weight measuring device, determining the weight of the remaining drug to be input, and determining the remaining input time of the infusion bottle, and identifying the amount of the remaining drug in the infusion bottle with an image processing device, and determining the remaining input time of the infusion bottle by combining the remaining input time of the infusion bottle obtained in the two ways.
S13, when the remaining input time of the infusion bottle is smaller than a first time threshold value, reminding the nurse station to carry out corresponding nursing operation.
For example, the first time threshold may be based on a combination of average nurse treatment time and distance from the nurse station.
The method comprises the steps of reading the weight of a hanging bottle at a nurse station, obtaining the input time of the hanging bottle according to the reading result, obtaining the input time threshold value of the hanging bottle by adopting the identity characteristics of a patient and the input time of the hanging bottle, solving the technical problem that unnecessary body injury is caused to the patient due to the fact that the identity difference of different patients is not considered when the threshold value is set originally, and performing targeted nursing to the patient more purposefully.
Through the age based on patient, the severity of disease, the identity characteristic of health self-care ability constitution patient to set up the input time threshold value of transfusion bottle according to patient's identity characteristic, thereby make can be pertinence provide nursing service to patient, it is older to some ages, and the patient that the severity is comparatively serious moreover, it is bigger to input time threshold value setting, guaranteed that patient can obtain priority nursing, improved patient's experience, reduced the harm to patient.
By adopting the setting of the input time threshold, the infusion bottle weight measuring device and the image processing device in the ward do not need to work all the time, so that the electric energy consumption is greatly saved, the measuring precision is ensured, the technical problem of inaccurate measuring result caused by damage or power shortage of a certain device is prevented, and the measuring reliability and accuracy are improved.
In another possible embodiment, as shown in fig. 2, the specific steps for confirming the time of the infusion bottle are as follows:
s21, extracting a two-dimensional code label of the transfusion bottle body, and confirming the medicine type of the transfusion bottle, the weight of the transfusion bottle, the bed number corresponding to the transfusion bottle and the disease type of a patient by adopting a two-dimensional code recognition device;
s22, matching the types of the infusion bottles with the types of the infusion bottles in a database based on the types of the infusion bottles, and determining the historical input efficiency of the infusion bottles according to the matching result;
specifically, for example, the infusion bottle drug types in the database have average input efficiency, and after matching is successful, the average input efficiency is used as historical input efficiency according to the infusion bottle drug types successfully matched.
S23, obtaining the infusion bottle input time based on the historical input efficiency and the weight of the infusion bottle.
Through the setting of two-dimensional code label to the weight of the discernment transfusion bottle medicine type that can be convenient and accurate, the bed number and the patient disease type that the transfusion bottle corresponds, and prevented because the medicine mistake leads to the fact the appearance of the problem of injury to patient, promoted stability.
Historical input efficiency is obtained through the matching result based on the types of the infusion bottles in the database, so that infusion bottle input time can be obtained based on historical data, and the infusion bottle input time result is more accurate.
In another possible embodiment, a time correction factor is obtained based on the disease type of the patient, and the time input by the hanging bottle is corrected based on the time correction factor to obtain the correction time input by the hanging bottle.
Due to the fact that different diseases have different requirements on the time input by the infusion bottle, through the construction of the time correction coefficient, the patient can be nursed more pertinently, and reliability and consistency are improved.
In another possible embodiment, as shown in fig. 3, the specific steps of confirming the identity of the patient are:
s31, extracting the age, the severity of diseases and the self-care ability of the patient to construct an input set;
s32, inputting the input set into a prediction model based on a GRU algorithm to obtain a prediction result;
s33, obtaining the identity characteristics of the patient based on the prediction result.
In another possible embodiment, a WOA-based algorithm is used to optimize the learning rate of the GRU algorithm.
By optimizing the learning rate, the convergence rate of the GRU algorithm is further improved, the technical problem of too low convergence caused by too high or too low learning rate is prevented, and the stability and efficiency of algorithm convergence are ensured.
In another possible embodiment, the convergence factor of the WOA algorithm is improved, wherein the calculation formula of the convergence factor is:
Figure BDA0003863842720000071
wherein K is 1 As a weight value, a value greater than 1, T is the current iteration number, T max Is the maximum number of iterations.
In another possible embodiment, the input time threshold is calculated by the following formula:
Figure BDA0003863842720000072
wherein X 1 The identity of the patient is evaluated as K and K is between 0 and 1 2 And T and Y are constant, and are respectively the time for inputting the infusion bottle and the initial time threshold.
In another possible embodiment, as shown in fig. 4, the specific steps for confirming the remaining input time of the infusion bottle are:
s41, when the input time of the infusion bottle is greater than the input time threshold, the step S42 is carried out;
s42, measuring the weight of the infusion bottle by adopting an infusion bottle weight measuring device in a ward, confirming the initial residual input time of the infusion bottle based on the weight of the infusion bottle, and entering the step S43 when the initial residual input time is smaller than a second time threshold, wherein the first time threshold is smaller than the second time threshold;
s43, an image processing device is adopted to perform recognition processing on the image of the infusion bottle to obtain a processing result, and the residual input time of the infusion bottle is obtained according to the processing result.
The initial residual input time of the transfusion bottle is confirmed by the transfusion bottle weight measuring device, and when the initial residual input time is smaller than the second time threshold value, the residual input time of the transfusion bottle is obtained by the image processing device, so that the accuracy of a detection result can be ensured on the basis of saving unnecessary detection.
Example 2
As shown in fig. 5, the present invention provides an intelligent infusion nursing system, and the intelligent infusion nursing method specifically includes:
the device comprises a time determining module, a threshold determining module, a residual input time determining module and a result reminding module;
wherein the time determining module is responsible for confirming the time input by the transfusion bottle;
the threshold determination module is responsible for constructing the identity characteristics of the patient and confirming the input time threshold of the hanging bottle based on the identity characteristics of the patient and the time input by the hanging bottle;
the residual input time determining module is responsible for determining the residual input time of the infusion bottle by combining the infusion bottle weight measuring device and the image processing device in the ward;
the result reminding module is responsible for reminding the nurse station to carry out corresponding nursing operation.
Example 3
In an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed in a computer, the computer is caused to execute a method for intelligent infusion care as described above.
Example 4
In an embodiment, a computer program product is provided, which is characterized by storing instructions that, when executed by a computer, cause the computer to implement an intelligent infusion nursing method as described above.
In embodiments of the present invention, the term "plurality" means two or more unless explicitly defined otherwise. The terms "mounted," "connected," "secured," and the like are to be construed broadly, and for example, "connected" may be a fixed connection, a removable connection, or an integral connection. Specific meanings of the above terms in the embodiments of the present invention may be understood by those of ordinary skill in the art according to specific situations.
In the description of the embodiments of the present invention, it should be understood that the terms "upper", "lower", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the embodiments of the present invention and simplifying the description, but do not indicate or imply that the referred devices or units must have a specific direction, be configured in a specific orientation, and operate, and thus, should not be construed as limiting the embodiments of the present invention.
In the description herein, the appearances of the phrase "one embodiment," "a preferred embodiment," or the like, are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the embodiments of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the embodiments of the present invention should be included in the protection scope of the embodiments of the present invention.

Claims (10)

1. An intelligent infusion nursing method is characterized by specifically comprising the following steps:
s11, reading the weight of a transfusion bottle to be input at a nurse station, and confirming the input time of the transfusion bottle based on the weight of the transfusion bottle;
s12, based on the age of a patient, the severity of a disease and the self-care ability of a body, obtaining the identity characteristics of the patient by adopting a prediction model based on a machine learning algorithm, confirming the input time threshold of a transfusion bottle based on the identity characteristics of the patient and the time input by the transfusion bottle, and when the time input by the transfusion bottle is greater than the input time threshold, combining a transfusion bottle weight measuring device and an image processing device in a ward to confirm the residual input time of the transfusion bottle;
s13, when the remaining input time of the transfusion bottle is smaller than a first time threshold value, the nurse station is reminded to carry out corresponding nursing operation.
2. The intelligent infusion nursing method according to claim 1, wherein the specific steps of confirming the time of infusion of the infusion bottle comprise:
s21, extracting a two-dimensional code label of the infusion bottle body, and confirming the drug type of the infusion bottle, the weight of the infusion bottle, the bed number corresponding to the infusion bottle and the disease type of a patient by adopting a two-dimensional code recognition device;
s22, matching the types of the infusion bottles with the types of the infusion bottles in a database based on the types of the infusion bottles, and determining the historical input efficiency of the infusion bottles according to the matching result;
s23, obtaining the input time of the hanging bottle based on the historical input efficiency and the weight of the hanging bottle.
3. The intelligent infusion nursing method according to claim 1, wherein a time correction factor is obtained based on the disease type of the patient, and the time inputted by the infusion bottle is corrected based on the time correction factor to obtain the corrected time inputted by the infusion bottle.
4. The intelligent infusion care method according to claim 1, wherein the specific steps of confirming the identity of the patient are:
s31, extracting the age, the severity of diseases and the self-care ability of the patient to construct an input set;
s32, inputting the input set into a prediction model based on a GRU algorithm to obtain a prediction result;
s33, obtaining the identity characteristics of the patient based on the prediction result.
5. The intelligent infusion care method according to claim 4, wherein a WOA-based algorithm is used to optimize the learning rate of the GRU algorithm.
6. The intelligent infusion nursing method according to claim 5, wherein a convergence factor of the WOA algorithm is improved, wherein the convergence factor is calculated by the following formula:
Figure FDA0003863842710000021
wherein K is 1 As a weight value, a value greater than 1, T is the current iteration number, T max Is the maximum number of iterations.
7. The intelligent infusion care method according to claim 1, wherein the input time threshold is calculated by the formula:
Figure FDA0003863842710000022
wherein X 1 The identity of the patient is evaluated as K between 0 and 1 2 Constant, T and Y are respectively the time of infusion of the transfusion bottle and the initial time thresholdThe value is obtained.
8. The intelligent infusion care method according to claim 1, wherein the specific steps of confirming the remaining input time of the infusion bottle are as follows:
s41, when the input time of the transfusion bottle is greater than an input time threshold value, the step S42 is executed;
s42, measuring the weight of the infusion bottle by adopting an infusion bottle weight measuring device in a ward, confirming the initial residual input time of the infusion bottle based on the weight of the infusion bottle, and entering S43 when the initial residual input time is less than a second time threshold;
s43, an image processing device is adopted to perform recognition processing on the image of the infusion bottle to obtain a processing result, and the residual input time of the infusion bottle is obtained according to the processing result.
9. The intelligent infusion care method of claim 8, wherein the first time threshold is less than the second time threshold.
10. An intelligent infusion care system, which adopts the intelligent infusion care method as claimed in any one of claims 1 to 9, and comprises:
the device comprises a time determining module, a threshold determining module, a residual input time determining module and a result reminding module;
wherein the time determination module is responsible for confirming the time of the transfusion bottle input;
the threshold determination module is responsible for constructing identity characteristics of a patient and confirming an input time threshold of the infusion bottle based on the identity characteristics of the patient and the time input by the infusion bottle;
the residual input time determining module is responsible for determining the residual input time of the infusion bottle by combining the infusion bottle weight measuring device and the image processing device in the ward;
the result reminding module is responsible for reminding the nurse station to carry out corresponding nursing operation.
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