阅读说明：本技术 一种用于患者肠内营养输入的控制系统及方法 (Control system and method for enteral nutrition input of patient ) 是由 秦燕 于 2020-12-18 设计创作，主要内容包括：本发明公开了一种用于患者肠内营养输入的控制系统及方法,应用于一患者管理系统,其中,所述方法包括：获得第一患者信息和进行肠内营养输入的第一方案信息；依据所述第一方案信息对所述第一患者进行营养输入,将第一时间阈值内所述第一患者的胃肠道耐受度信息、胃内残余液量输入至第一神经网络模型,获得第一调整信息,由所述第一调整信息对所述第一方案信息进行调整；将所述第一患者面部胃鼻管固定的第一图像信息、所述第一胃鼻管的第一压力信息输入第二神经网络模型,确定是否获得第一预警信息。解决了现有技术中对患者进行肠内营养输入的方案调整不够智能化,输入过程监测不够及时的技术问题。(The invention discloses a control system and a method for enteral nutrition input of a patient, which are applied to a patient management system, wherein the method comprises the following steps: obtaining first patient information and first regimen information for enteral nutrition infusion; inputting nutrition of the first patient according to the first scheme information, inputting gastrointestinal tract tolerance information and residual liquid amount in the stomach of the first patient within a first time threshold to a first neural network model to obtain first adjustment information, and adjusting the first scheme information according to the first adjustment information; and inputting first image information of the fixation of the stomach-nose tube of the face of the first patient and first pressure information of the first stomach-nose tube into a second neural network model, and determining whether first early warning information is obtained or not. The technical problems that in the prior art, adjustment of a scheme for enteral nutrition input of a patient is not intelligent enough, and monitoring of an input process is not timely enough are solved.)

1. A control system for enteral nutrition input to a patient for use in a patient management system, the system comprising:

a first obtaining unit for obtaining first patient information;

a second obtaining unit for obtaining first plan information for enteral nutrition input by the first patient;

a third obtaining unit, configured to perform nutrition input on the first patient according to the first scheme information, and obtain first gastrointestinal tract tolerance information of the first patient within a first time threshold;

a fourth obtaining unit for obtaining a first amount of intragastric residual liquid;

a first input unit for inputting the first gastrointestinal tract tolerance information, the first scheme information, and the first intragastric residual liquid amount into a first neural network model to obtain first adjustment information;

a fifth obtaining unit, configured to obtain second scheme information from the first adjustment information;

a sixth obtaining unit for obtaining first image information of stomach-nose tube fixation of the first patient face;

a seventh obtaining unit for obtaining first pressure information of the first nasogastric tube;

and the second input unit is used for inputting the first image information and the first pressure information into a second neural network model and determining whether first early warning information is obtained or not.

2. The system of claim 1, wherein first protocol information for enteral nutrition entry by the first patient is obtained, the system comprising:

an eighth obtaining unit for obtaining first gastrointestinal tract function level information of the first patient;

a ninth obtaining unit for obtaining first physiological characteristic information of the first patient;

a tenth obtaining unit, configured to determine formula information of the first nutritional liquid from the first gastrointestinal tract function grade information and the first physiological characteristic information;

an eleventh obtaining unit for obtaining characteristic information of the first nasogastric tube;

a twelfth obtaining unit for obtaining the first prescription information from prescription information of the first nutrient solution and characteristic information of the first stomach-nose tube.

3. The system of claim 2, wherein the system further comprises:

a thirteenth obtaining unit for obtaining first medical history information of the first patient;

a fourteenth obtaining unit, configured to obtain second adjustment information according to the first medical history information;

and the first adjusting unit adjusts the formula information of the first nutrient solution according to the second adjusting information.

4. The system of claim 1, wherein first gastrointestinal tolerance information is obtained for the first patient within a first time threshold, the system further comprising:

a fifteenth obtaining unit configured to obtain first abnormal physiological phenomenon information;

a sixteenth obtaining unit configured to obtain first severity information of the first abnormal physiological phenomenon;

a seventeenth obtaining unit, configured to obtain first frequency information of the first abnormal physiological phenomenon within the first time threshold;

a third input unit, configured to input the first severity information and the first frequency information into a third neural network model, so as to obtain the first gastrointestinal tract tolerance information.

5. The system of claim 1, wherein the system comprises:

an eighteenth obtaining unit for obtaining first real-time temperature information of the first nasogastric tube;

the first judging unit is used for judging whether the first real-time temperature information is in a second threshold value;

a nineteenth obtaining unit, configured to obtain the second warning information if the first warning information is not in the preset state.

6. The system of claim 1, wherein first image information of the first patient's facial gastro-nasal tube fixation is obtained, the system further comprising:

a twentieth obtaining unit for obtaining first facial information of the first patient from the first image information;

a twenty-first obtaining unit for obtaining pain level information of the first patient from the first facial information;

a twenty-second obtaining unit configured to obtain third warning information if the pain level information of the first patient exceeds a third threshold.

7. The system of claim 1, wherein determining whether first pre-warning information is obtained further comprises:

a first sending unit, configured to send the first warning information to a first nurse, where the first nurse is a nurse closest to the first patient;

a twenty-third obtaining unit configured to obtain second image information after the first nurse performs care;

a second judgment unit configured to judge whether or not the care of the first nurse is qualified from the second image information;

and the twenty-fourth obtaining unit is used for obtaining fourth early warning information if the fourth early warning information is unqualified, and sending the fourth early warning information to a second nurse.

8. A method for controlling enteral nutrition input of a patient, applied to a patient management system:

obtaining first patient information;

obtaining first protocol information for enteral nutrition infusion by the first patient;

performing nutrition input on the first patient according to the first scheme information to obtain first gastrointestinal tract tolerance information of the first patient within a first time threshold;

obtaining a first amount of intragastric residual fluid;

inputting the first gastrointestinal tract tolerance information, the first scheme information and the first intragastric residual liquid amount into a first neural network model to obtain first adjustment information;

obtaining second scheme information according to the first adjustment information;

obtaining first image information of the first patient's facial nasogastric tube fixation;

obtaining first pressure information for the first nasogastric tube;

and inputting the first image information and the first pressure information into a second neural network model, and determining whether first early warning information is obtained or not.

9. A control system for enteral feeding of a patient, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the system of any one of claims 1-7 when executing the program.

Technical Field

The invention relates to the field of enteral nutrition input, in particular to a control system and a control method for enteral nutrition input of a patient.

Background

Enteral nutrition is the nutritional support for supplying nutrients and other various nutrients needed for metabolism via the gastrointestinal tract. The enteral nutrition input mode comprises enteral nutrition pump input, disposable administration and intermittent gravity input. Enteral nutrition is introduced into the gastrointestinal tract by: oral administration and tube feeding. When the feeding is carried out through tube feeding, the configuration of nutrient solution, the position and the specification of a stomach tube, the feeding time, the frequency and the like of the nutrient solution are comprehensively formulated according to the self condition of a patient, so that the tube feeding effect is ensured, and the risk of complications is reduced.

However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:

the scheme for enteral nutrition input of patients is not intelligent enough, and the input process is not timely enough.

Disclosure of Invention

The embodiment of the application solves the technical problems that in the prior art, the adjustment of the scheme for enteral nutrition input to the patient is not intelligent enough and the monitoring of the input process is not timely enough, and achieves the technical purposes of improving the adjustment intelligence of the scheme for enteral nutrition input to the patient and monitoring the input process safely and timely.

In view of the above, embodiments of the present application provide a control system and method for enteral nutrition input of a patient.

In a first aspect, the present application provides a control system for enteral nutrition input of a patient, applied to a patient management system, the system comprising: a first obtaining unit for obtaining first patient information; a second obtaining unit for obtaining first plan information for enteral nutrition input by the first patient; a third obtaining unit, configured to perform nutrition input on the first patient according to the first scheme information, and obtain first gastrointestinal tract tolerance information of the first patient within a first time threshold; a fourth obtaining unit for obtaining a first amount of intragastric residual liquid; a first input unit for inputting the first gastrointestinal tract tolerance information, the first scheme information, and the first intragastric residual liquid amount into a first neural network model to obtain first adjustment information; a fifth obtaining unit, configured to obtain second scheme information from the first adjustment information; a sixth obtaining unit for obtaining first image information of stomach-nose tube fixation of the first patient face; a seventh obtaining unit for obtaining first pressure information of the first nasogastric tube; and the second input unit is used for inputting the first image information and the first pressure information into a second neural network model and determining whether first early warning information is obtained or not.

In another aspect, the present application further provides a method for controlling enteral nutrition input of a patient, applied to a patient management system: obtaining first patient information; obtaining first protocol information for enteral nutrition infusion by the first patient; performing nutrition input on the first patient according to the first scheme information to obtain first gastrointestinal tract tolerance information of the first patient within a first time threshold; obtaining a first amount of intragastric residual fluid; inputting the first gastrointestinal tract tolerance information, the first scheme information and the first intragastric residual liquid amount into a first neural network model to obtain first adjustment information; obtaining second scheme information according to the first adjustment information; obtaining first image information of the first patient's facial nasogastric tube fixation; obtaining first pressure information for the first nasogastric tube; and inputting the first image information and the first pressure information into a second neural network model, and determining whether first early warning information is obtained or not.

In a third aspect, the present invention provides a control device for enteral feeding of a patient, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the system of the first aspect.

One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

when the first patient carries out enteral nutrition input, the measured amount of the residual liquid in the stomach and the evaluation value of the gastrointestinal tract tolerance of the first patient by the patient management system are input to a neural network model to obtain the adjustment information of the enteral nutrition input scheme of the first patient, the position and the pressure condition of the stomach-nose tube during the enteral nutrition input of the first patient are monitored by an image capturing device and a pressure sensor, and the patient management system carries out real-time early warning, so that the technical aims of improving the adjustment intelligence of the enteral nutrition input scheme of the patient and carrying out safe and timely monitoring on the input process are fulfilled.

The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.

Drawings

FIG. 1 is a schematic flow chart of a method for controlling enteral feeding to a patient according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a control system for enteral feeding of a patient according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.

Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a first input unit 15, a fifth obtaining unit 16, a sixth obtaining unit 17, a seventh obtaining unit 18, a second input unit 19, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, a bus interface 305.

Detailed Description

The embodiment of the application solves the technical problems that in the prior art, the adjustment of the scheme for enteral nutrition input to the patient is not intelligent enough and the monitoring of the input process is not timely enough, and achieves the technical purposes of improving the adjustment intelligence of the scheme for enteral nutrition input to the patient and monitoring the input process safely and timely. Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.

Summary of the application

Enteral nutrition is introduced into the gastrointestinal tract by: oral administration and tube feeding. When the feeding is carried out through tube feeding, the configuration of nutrient solution, the position and the specification of a stomach tube, the feeding time, the frequency and the like of the nutrient solution are comprehensively formulated according to the self condition of a patient, so that the tube feeding effect is ensured, and the risk of complications is reduced. However, the technical problems that the adjustment of the scheme for enteral nutrition input of the patient is not intelligent enough and the monitoring of the input process is not timely enough exist in the prior art.

In view of the above technical problems, the technical solution provided by the present application has the following general idea:

the embodiment of the application provides a control system for enteral nutrition input of a patient, which is applied to a patient management system, and the system comprises: a first obtaining unit for obtaining first patient information; a second obtaining unit for obtaining first plan information for enteral nutrition input by the first patient; a third obtaining unit, configured to perform nutrition input on the first patient according to the first scheme information, and obtain first gastrointestinal tract tolerance information of the first patient within a first time threshold; a fourth obtaining unit for obtaining a first amount of intragastric residual liquid; a first input unit for inputting the first gastrointestinal tract tolerance information, the first scheme information, and the first intragastric residual liquid amount into a first neural network model to obtain first adjustment information; a fifth obtaining unit, configured to obtain second scheme information from the first adjustment information; a sixth obtaining unit for obtaining first image information of stomach-nose tube fixation of the first patient face; a seventh obtaining unit for obtaining first pressure information of the first nasogastric tube; and the second input unit is used for inputting the first image information and the first pressure information into a second neural network model and determining whether first early warning information is obtained or not.

Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.

Example one

As shown in fig. 1, the present application provides a control method for enteral nutrition input of a patient, applied to a patient management system, wherein the method includes:

step S100: obtaining first patient information;

specifically, the first patient information includes identity information, bed information, medical record information, and the like of the first patient. Uploading, by a doctor or nurse responsible for the first patient, the first patient information to the patient management system. By obtaining the first patient information, a foundation is laid for accurately detecting the process of enteral nutrition input of the patient and carrying out early warning in time.

Step S200: obtaining first protocol information for enteral nutrition infusion by the first patient;

specifically, the first prescription information for enteral nutrition input by the first patient includes information on nutrient solution used for enteral input, feeding speed, duration, period, feeding concentration, feeding temperature, type and size of a stomach-nasal tube, position of a tube end, and a required amount of nutrients. Giving first plan information for enteral nutrition input by the first patient according to the diagnosis condition of the first patient by a doctor, and inputting the first plan information to the patient management system.

Step S300: performing nutrition input on the first patient according to the first scheme information to obtain first gastrointestinal tract tolerance information of the first patient within a first time threshold;

specifically, after the first plan information is specified, the nurse performs the operation procedures such as accurate use of the product, checking of patient information, and preparation of a nutrient solution in order based on the first plan information, and inputs enteral nutrition to the first patient. The first gastrointestinal tolerance of the first patient is the severity of gastrointestinal complications of the first patient caused by improper nutrient solution concentration, infusion speed, infusion temperature and the like during infusion. Common gastrointestinal complications are: nausea, vomiting, abdominal pain, abdominal distension, diarrhea, constipation, etc., by obtaining first gastrointestinal tolerance information for the first patient within the first threshold, and then adjusting first regimen information for enteral nutritional infusion for the first patient on a targeted basis. The first time threshold is a time threshold preset by a system for observing gastrointestinal tract reaction in the process of enteral nutrition input of the first patient.

Step S400: obtaining a first amount of intragastric residual fluid;

specifically, the first intragastric residual liquid amount is measured by sampling the first patient's intragastric residual liquid amount at regular time intervals during the period of enteral nutrition input for the first patient, and data of the first intragastric residual liquid amount is input to the patient management system. Whether the value of the first intragastric residual liquid amount is suitable or not and whether the input mode of the nutrient solution in the first scheme information is suitable or not lay a foundation for carrying out scheme adjustment.

Step S500: inputting the first gastrointestinal tract tolerance information, the first scheme information and the first intragastric residual liquid amount into a first neural network model to obtain first adjustment information;

in particular, a neural network is a complex network system formed by a large number of simple processing units (called neurons) widely connected to each other, which reflects many basic features of human brain functions, and is a highly complex nonlinear dynamical learning system. The first neural network model is a machine learning model, after the first gastrointestinal tract tolerance information, the first scheme information and the first intragastric residual liquid amount are input into the first neural network model, the first neural network model is continuously corrected and optimized through training data, the accuracy of the machine learning model for processing the data is improved through a supervised learning process, and the first adjusting information is used for adjusting the first scheme information and comprises adjusting information of the input speed, the input amount, the input duration and the like of the first nutrient solution.

Step S600: obtaining second scheme information according to the first adjustment information;

specifically, the patient management system adjusts the first protocol information according to the first adjustment information obtained by the first neural network model, so as to obtain the second protocol information.

Step S700: obtaining first image information of a first stomach-nose tube fixation of the face of the first patient;

specifically, the patient management system is connected with an image acquisition device, the first image information is obtained by the image acquisition device, and the first image information is the position information of the first stomach-nose tube of the first patient during the enteral nutrition input process. The first image information is used for judging whether the first stomach-nose tube is properly fixed or not, whether a shedding phenomenon exists or not and the like.

Step S800: obtaining first pressure information for the first nasogastric tube;

specifically, the first pressure information is pressure information of the first nasogastric tube, and the pressure information is measured by a pressure sensor built in the first nasogastric tube and transmitted to the patient management system. If the first stomach-nose tube is pressed in the inputting process, the normal inputting of nutrient solution can be influenced, even the stomach-nose tube is blocked, and other complications can be caused seriously.

Step S900: and inputting the first image information and the first pressure information into a second neural network model, and determining whether first early warning information is obtained or not.

Specifically, the first image information and the first pressure information are input into the second neural network model, and data are processed based on the characteristics that the second neural network model can continuously learn and acquire experience, so that whether the first stomach-nose tube is safely fixed and whether the first stomach-nose tube is pressed in the first image information is accurately evaluated, and the first early warning information is acquired after an abnormal condition is detected. The technical purpose of carrying out safe and real-time monitoring on the enteral nutrition input process of the first patient is achieved.

Further, obtaining the first scheme information of enteral nutrition input of the first patient, step S200 of the embodiment of the present application further includes:

step S201: obtaining first gastrointestinal tract function grade information of the first patient;

step S202: obtaining first physiological characteristic information of the first patient;

step S203: determining formula information of a first nutrient solution from the first gastrointestinal tract function grade information and the first physiological characteristic information;

step S204: obtaining characteristic information of the first stomach-nose tube;

step S205: obtaining the first scheme information from the formula information of the first nutrient solution and the characteristic information of the first stomach-nose tube.

In particular, the first gastrointestinal tract function level information of the first patient is the result of an assessment of various functions of the first patient's gastrointestinal tract, including digestion, absorption and secretion, and immune functions. The main physiological functions of the gastrointestinal tract are the intake, transport and digestion of food, the absorption of nutrients and the excretion of waste products, and the gastrointestinal tract function of the first patient differs, the enteral nutrition input method chosen differs and the nutrient solution formulation also differs. The first physiological characteristic information of the first patient comprises characteristic information of the first patient, such as nutritional state, metabolic condition, immune function and the like. Determining formula information of a first nutrient solution according to the first gastrointestinal tract function grade information and the first physiological characteristic information, and obtaining characteristic information of the first nasogastric tube, wherein the characteristic information of the first nasogastric tube comprises the tube diameter, material and the like of the first nasogastric tube. Different stomach and nose tube characteristics determine different nutrient solution types and tube feeding modes, and if a feeding tube with soft texture and small tube diameter is adopted, the feeding tube is not suitable for enteral nutrition with high viscosity or mixed with ground medicines. After obtaining the formula information of the first nutrient solution, the characteristic information of the first stomach-nose tube, thereby determining the first formula information.

Further, step S203 in the embodiment of the present application further includes:

step S2031: obtaining first medical history information for the first patient;

step S2032: acquiring second adjustment information according to the first medical history information;

step S2033: and adjusting the formula information of the first nutrient solution according to the second adjustment information.

Further, the formula of the first nutrient solution is adjusted according to the past medical history of the first patient. If the first patient has lung disease, diabetes, kidney disease, etc., a special formula meal needs to be prepared according to the medical history so as to meet the requirement of the first patient on special nutrition.

Further, step S300 in the embodiment of the present application further includes:

step S301: obtaining first abnormal physiological phenomenon information;

step S302: obtaining first severity information for the first abnormal physiological phenomenon;

step S303: obtaining first frequency information of the first abnormal physiological phenomenon within the first time threshold;

step S304: and inputting the first severity information and the first frequency information into a third neural network model to obtain the first gastrointestinal tract tolerance information.

Specifically, the first abnormal physiological phenomenon includes gastrointestinal complications of the first patient due to inappropriate nutrient solution concentration, infusion speed, infusion temperature, and the like during enteral nutrition infusion, and the common gastrointestinal complications are: nausea, vomiting, abdominal pain, abdominal distension, diarrhea, constipation, etc., and adjusting the first scenario information by assessing a severity of the first abnormal physiological phenomenon and a frequency of occurrence of the first abnormal physiological phenomenon within the first time threshold to determine the first gastrointestinal tract tolerance information via the third neural network model.

Further, step S400 in the embodiment of the present application further includes:

step S401: obtaining first real-time temperature information of the first nasogastric tube;

step S402: judging whether the first real-time temperature information is in a second threshold value;

step S403: and if not, obtaining second early warning information.

Specifically, the temperature of the stomach-nose tube in the enteral nutrition input process of the first patient is monitored in real time through a temperature sensor, the temperature information is transmitted to the patient management system, early warning is carried out if the first real-time temperature is not in the second threshold value through real-time judgment, and the temperature of the first stomach-nose tube is adjusted in time.

Further, step S700 in the embodiment of the present application further includes:

step S701: obtaining first facial information of the first patient from the first image information;

step S702: obtaining pain level information of the first patient from the first facial information;

step S703: and if the pain level information of the first patient exceeds a third threshold value, third early warning information is obtained.

Specifically, the first image information is obtained by the image capturing device, the system automatically identifies the facial information of the first patient according to the first image information based on an artificial intelligence face identification technology, and analyzes and processes the first facial information, so as to evaluate the pain level of the first patient during the enteral input, obtain the pain level information of the first patient, and if the pain level exceeds the third threshold, timely early warning is carried out through the third early warning information, so as to remind a nurse of timely adjusting the enteral nutrition input of the first patient. Thereby ensuring the safety of the enteral feeding procedure of said first patient.

Further, step S900 in the embodiment of the present application further includes:

step S901: sending the first early warning information to a first nurse, wherein the first nurse position is a nurse closest to the first patient;

step S902: after the first nurse carries out nursing, obtaining second image information;

step S903: judging whether the nursing of the first nurse is qualified or not according to the second image information;

step S904: and if the fourth warning information is not qualified, obtaining fourth warning information and sending the fourth warning information to a second nurse.

Specifically, if the system obtains the first warning information through the second neural network model, based on a global positioning technology, the system sends the first patient information and the first warning information to the first nurse by obtaining nurse information closest to the first patient, where the first patient information includes basic information, ward information, bed number information, and the like of the first patient. When the first nurse adjusts the position and the pressure condition of the first nasogastric tube of the first patient, obtaining operation image information of the first nurse through the image capturing device, then analyzing nursing of the first nurse in real time by the system based on an artificial intelligence image processing technology to judge whether the nursing of the first nurse is qualified, if not, obtaining fourth early warning information, and sending the fourth early warning information to the second nurse, wherein the second nurse is another nurse closest to the first patient.

In summary, the control system and method for enteral nutrition input of a patient provided by the embodiments of the present application have the following technical effects:

when the first patient carries out enteral nutrition input, the measured amount of the residual liquid in the stomach and the evaluation value of the gastrointestinal tract tolerance of the first patient by the patient management system are input to a neural network model to obtain the adjustment information of the enteral nutrition input scheme of the first patient, the position and the pressure condition of the stomach-nose tube during the enteral nutrition input of the first patient are monitored by an image capturing device and a pressure sensor, and the patient management system carries out real-time early warning, so that the technical aims of improving the adjustment intelligence of the enteral nutrition input scheme of the patient and carrying out safe and timely monitoring on the input process are fulfilled.

Example two

Based on the same inventive concept as the control method for enteral nutrition input of a patient in the previous embodiment, the present invention also provides a control system for enteral nutrition input of a patient, as shown in fig. 2, the system comprising:

a first obtaining unit 11, the first obtaining unit 11 being configured to obtain first patient information;

a second obtaining unit 12, the second obtaining unit 12 being configured to obtain first protocol information for enteral nutrition input by the first patient;

a third obtaining unit 13, where the third obtaining unit 13 is configured to perform nutrition input on the first patient according to the first prescription information, and obtain first gastrointestinal tract tolerance information of the first patient within a first time threshold;

a fourth obtaining unit 14, said fourth obtaining unit 14 being configured to obtain a first intragastric residual liquid amount;

a first input unit 15, wherein the first input unit 15 is configured to input the first gastrointestinal tract tolerance information, the first scheme information, and the first intragastric residual liquid amount into a first neural network model to obtain first adjustment information;

a fifth obtaining unit 16, where the fifth obtaining unit 16 is configured to obtain second scheme information from the first adjustment information;

a sixth obtaining unit 17, the sixth obtaining unit 17 being configured to obtain first image information of stomach-nose tube fixation of the first patient face;

a seventh obtaining unit 18, said seventh obtaining unit 18 being configured to obtain first pressure information of said first nasogastric tube;

a second input unit 19, where the second input unit 19 is configured to input the first image information and the first pressure information into a second neural network model, and determine whether to obtain first warning information.

Further, the system further comprises:

an eighth obtaining unit for obtaining first gastrointestinal tract function level information of the first patient;

a ninth obtaining unit for obtaining first physiological characteristic information of the first patient;

a tenth obtaining unit, configured to determine formula information of the first nutritional liquid from the first gastrointestinal tract function grade information and the first physiological characteristic information;

an eleventh obtaining unit for obtaining characteristic information of the first nasogastric tube;

a twelfth obtaining unit for obtaining the first prescription information from prescription information of the first nutrient solution and characteristic information of the first stomach-nose tube.

Further, the system further comprises:

a thirteenth obtaining unit for obtaining first medical history information of the first patient;

a fourteenth obtaining unit, configured to obtain second adjustment information according to the first medical history information;

and the first adjusting unit adjusts the formula information of the first nutrient solution according to the second adjusting information.

Further, the system further comprises:

a fifteenth obtaining unit configured to obtain first abnormal physiological phenomenon information;

a sixteenth obtaining unit configured to obtain first severity information of the first abnormal physiological phenomenon;

a seventeenth obtaining unit, configured to obtain first frequency information of the first abnormal physiological phenomenon within the first time threshold;

a third input unit, configured to input the first severity information and the first frequency information into a third neural network model, so as to obtain the first gastrointestinal tract tolerance information.

Further, the system further comprises:

an eighteenth obtaining unit for obtaining first real-time temperature information of the first nasogastric tube;

the first judging unit is used for judging whether the first real-time temperature information is in a second threshold value;

a nineteenth obtaining unit, configured to obtain the second warning information if the first warning information is not in the preset state.

Further, the system further comprises:

a twentieth obtaining unit for obtaining first facial information of the first patient from the first image information;

a twenty-first obtaining unit for obtaining pain level information of the first patient from the first facial information;

a twenty-second obtaining unit configured to obtain third warning information if the pain level information of the first patient exceeds a third threshold.

Further, the system further comprises:

a first sending unit, configured to send the first warning information to a first nurse, where the first nurse is a nurse closest to the first patient;

a twenty-third obtaining unit configured to obtain second image information after the first nurse performs care;

a second judgment unit configured to judge whether or not the care of the first nurse is qualified from the second image information;

and the twenty-fourth obtaining unit is used for obtaining fourth early warning information if the fourth early warning information is unqualified, and sending the fourth early warning information to a second nurse.

Various modifications and embodiments of a control method for enteral nutrition input of a patient in the first embodiment of fig. 1 are also applicable to the control system for enteral nutrition input of a patient in the present embodiment, and the implementation of the control system for enteral nutrition input of a patient in the present embodiment will be clear to those skilled in the art from the foregoing detailed description of the control method for enteral nutrition input of a patient, so that the detailed description is omitted here for the sake of brevity.

Exemplary electronic device

The electronic device of the embodiment of the present application is described below with reference to fig. 3.

Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.

Based on the inventive concept of a control method for enteral nutrition input of a patient according to the preceding embodiments, the invention further provides a control device for enteral nutrition input of a patient, on which a computer program is stored which, when being executed by a processor, carries out the steps of a control method for enteral nutrition input of a patient as described above.

Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium.

The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.

The embodiment of the application provides a control system for enteral nutrition input of a patient, which is applied to a patient management system, and the system comprises: a first obtaining unit for obtaining first patient information; a second obtaining unit for obtaining first plan information for enteral nutrition input by the first patient; a third obtaining unit, configured to perform nutrition input on the first patient according to the first scheme information, and obtain first gastrointestinal tract tolerance information of the first patient within a first time threshold; a fourth obtaining unit for obtaining a first amount of intragastric residual liquid; a first input unit for inputting the first gastrointestinal tract tolerance information, the first scheme information, and the first intragastric residual liquid amount into a first neural network model to obtain first adjustment information; a fifth obtaining unit, configured to obtain second scheme information from the first adjustment information; a sixth obtaining unit for obtaining first image information of stomach-nose tube fixation of the first patient face; a seventh obtaining unit for obtaining first pressure information of the first nasogastric tube; and the second input unit is used for inputting the first image information and the first pressure information into a second neural network model and determining whether first early warning information is obtained or not.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.