CN112116967B - Information processing method and device for improving urine sample collection efficiency - Google Patents

Information processing method and device for improving urine sample collection efficiency Download PDF

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CN112116967B
CN112116967B CN202011020879.8A CN202011020879A CN112116967B CN 112116967 B CN112116967 B CN 112116967B CN 202011020879 A CN202011020879 A CN 202011020879A CN 112116967 B CN112116967 B CN 112116967B
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顾梅
裴小锐
王燕
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Suzhou Municipal Hospital
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    • G08B21/24Reminder alarms, e.g. anti-loss alarms
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
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Abstract

The invention discloses an information processing method and device for improving urine sample collection efficiency, wherein the information processing method comprises the following steps: obtaining physical sign characteristic information of a first user; obtaining sign characteristic information of a first user, and obtaining historical urination rule information of the first user; inputting the sign characteristic information as first input information and the historical defecation rule information as second input information into a first training model to obtain first output information of the first training model, wherein the first output information comprises a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate; when the first output information is a first output result, obtaining a first reminding instruction; and collecting urine of the first user according to the first reminding instruction. The technical problem that urine examination time is delayed due to the fact that urine samples are difficult to collect in the prior art is solved.

Description

Information processing method and device for improving urine sample collection efficiency
Technical Field
The invention relates to the field of urine sample collection, in particular to an information processing method and device for improving urine sample collection efficiency.
Background
Urine examination is a medical detection method. Comprises the steps of conventional analysis of urine, detection of visible components in urine (such as urine red blood cells, leucocytes and the like), quantitative determination of protein components, detection of urease and the like. Urine tests have important values for clinical diagnosis, judgment of curative effect and prognosis.
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 technical problem that urine examination time is delayed due to the fact that urine samples are difficult to collect in the prior art exists.
Disclosure of Invention
The embodiment of the application provides the information processing method and the information processing device for improving the collection efficiency of the urine sample, solves the technical problem that in the prior art, the collection of the urine sample is difficult, so that the urine examination time is delayed, and achieves the technical effect of improving the collection efficiency of the urine sample.
In view of the above problems, the embodiments of the present application provide an information processing method and apparatus for improving urine sample collection efficiency.
In a first aspect, an embodiment of the present application provides an information processing method for improving collection efficiency of a urine sample, where the method includes: obtaining physical sign characteristic information of a first user; obtaining historical urination rule information of the first user; using the physical sign characteristic information as first input information, and using the historical defecation rule information as second input information to be input into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the physical sign characteristic information, the historical defecation rule information and identification information used for identifying whether the first user needs to urinate or not; obtaining first output information of the first training model, wherein the first output information comprises a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate; when the first output information is a first output result, a first reminding instruction is obtained; and collecting urine for the first user according to the first reminding instruction.
In another aspect, the present application further provides an information processing apparatus for improving urine sample collection efficiency, wherein the apparatus includes: a first obtaining unit, configured to obtain sign characteristic information of a first user; a second obtaining unit, configured to obtain historical urination rule information of the first user; a first input unit, configured to use the sign characteristic information as first input information, and use the historical defecation law information as second input information to input a first training model, where the first training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: the physical sign characteristic information, the historical defecation rule information and identification information used for identifying whether the first user needs to urinate; a third obtaining unit, configured to obtain first output information of the first training model, where the first output information includes a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate; a fourth obtaining unit, configured to obtain a first prompting instruction when the first output information is a first output result; the first collection unit is used for collecting urine of the first user according to the first reminding instruction.
In a third aspect, the present invention provides an information processing apparatus for improving urine sample collection efficiency, 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 method of the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the physical sign characteristic information of the first user is used as first input information, the historical urination law is used as second input information, the first training model is input, and the feature of continuous self-correction and adjustment of the training model is used, so that the technical effects of accurately judging the urination discharge time of the first user and reminding the first user to collect urine according to the discharge time are achieved.
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.
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FIG. 1 is a schematic flow chart illustrating an information processing method for improving urine sample collection efficiency according to an embodiment of the present disclosure;
FIG. 2 is a schematic structural diagram of an information processing apparatus for improving urine sample collection efficiency according to an embodiment of the present disclosure;
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 first input unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a first collecting unit 16, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 306.
Detailed Description
The embodiment of the application provides the information processing method and the information processing device for improving the urine sample collection efficiency, solves the technical problem that urine sample collection is difficult and urine examination time is delayed in the prior art, and achieves the technical effect of improving the urine sample collection efficiency. 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
Urine examination is a medical detection method. Comprises the steps of conventional analysis of urine, detection of visible components in urine (such as urine red blood cells, leucocytes and the like), quantitative determination of protein components, detection of urease and the like. Urine tests have important values for clinical diagnosis, judgment of curative effect and prognosis. However, the prior art has the technical problem that the urine sample collection is difficult, so that the urine examination time is delayed.
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 an information processing method for improving collection efficiency of a urine sample, and the method comprises the following steps: obtaining physical sign characteristic information of a first user; obtaining historical urination rule information of the first user; using the physical sign characteristic information as first input information, and using the historical defecation rule information as second input information to be input into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the physical sign characteristic information, the historical defecation rule information and identification information used for identifying whether the first user needs to urinate or not; obtaining first output information of the first training model, wherein the first output information comprises a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate; when the first output information is a first output result, obtaining a first reminding instruction; and collecting urine of the first user according to the first reminding instruction.
Having described the 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, an embodiment of the present application provides an information processing method for improving collection efficiency of a urine sample, wherein the method includes:
step S100: obtaining physical sign characteristic information of a first user;
specifically, the first user is a user who needs to collect a urine sample, the physical characteristic information includes information such as identity information and real-time body state information of the first user, and a basis is provided for subsequently and accurately judging whether the urine sample is collected and tamped by the first user according to the physical characteristic information of the first user.
Step S200: obtaining historical urination rule information of the first user;
specifically, the historical urination law is obtained by monitoring the urination times and the urination time information of the first user according to the daily life and the dietary habits of the first user, the urination time comprises the time information of urination and the urination duration information, the urination amount of the first user is estimated and recorded according to the urination duration information, and the historical urination law information of the first user is obtained according to the urination times, the urination time and the urination discharge amount.
Step S300: using the physical sign characteristic information as first input information, and using the historical defecation rule information as second input information to input into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the physical sign characteristic information, the historical defecation rule information and identification information used for identifying whether the first user needs to urinate or not;
specifically, the first training model is a model capable of performing continuous self-training learning according to training data, and further, the first training model is a Neural network model, which is a Neural network model in machine learning, and a Neural Network (NN) is a complex Neural network device formed by widely connecting a large number of simple processing units (called neurons), reflects many basic features of human brain functions, and is a highly complex nonlinear dynamics learning device. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (Artificial Neural Networks) are a description of the first-order properties of human brain devices. Briefly, it is a mathematical model. Training based on a large amount of training data, wherein each set of training data in the training data comprises the sign characteristic information, the historical defecation rule information and identification information used for identifying whether the first user needs to urinate; the neural network model is continuously self-corrected, and when the output information of the neural network model reaches a preset accuracy rate/reaches a convergence state, the supervised learning process is ended. Through data training of the neural network model, the neural network model can process the input data more accurately, and the output judgment of whether the first user needs urine information is more accurate. The physical sign characteristic information is used as first input information, the historical defecation rule information is used as second input information and is input into the training model based on the characteristic that the data is more accurate after the training model is trained, and whether the first user needs to urinate or not is judged through output information of the training model, so that the judgment result is more accurate, and the technical effect of improving the urine sample collection efficiency is achieved.
Step S400: obtaining first output information of the first training model, wherein the first output information comprises a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate;
specifically, the output information includes a first output result and a second output result, the first output result is a result that the first user needs to urinate, the second result is a result that the first user does not need to urinate, and a foundation is laid for subsequent accurate prompt of collection of a urine sample according to the output result.
Step S500: when the first output information is a first output result, obtaining a first reminding instruction;
step S600: and collecting urine of the first user according to the first reminding instruction.
Specifically, when the first output information is the first output result, a first reminding instruction is obtained, the first reminding instruction is an instruction which has a reminding function or can trigger other devices to remind through the instruction, and urine collection is performed on the first user according to the first reminding instruction.
Further, the embodiment of the present application further includes:
step S710: obtaining daily water intake information of the first user;
step S720: obtaining daily eating water content information of the first user;
step S730: taking the daily drinking water amount information as first input information, and taking the daily eating water content information as second input information to be input into a second training model, wherein the second training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the daily drinking water amount information, the daily eating water content information and identification information for identifying the urination amount of the first user;
step S740: and obtaining second output information of the second training model, wherein the second output information is daily urination information of the first user.
Specifically, the daily water intake of the first user is information of the daily drinking water amount of the first user, the eating water content is eating water content information obtained according to the content of water in eating of the first user, the daily water intake information is used as first input information, the daily eating water content information is used as second input information and is input into a second training model, the second training model is also a training model obtained by continuously performing supervised learning based on a neural network model, and a description is not expanded here, so that second output information of the second training model is obtained, wherein the second output information is daily urination amount information of the first user. By obtaining the daily urination amount information of the first user, a foundation is laid for the subsequent accurate analysis of the urination time.
Further, in the step S740 of obtaining the second output information of the second training model in the embodiment of the present application further includes:
step S741: obtaining a first correction parameter according to the sign characteristic information of the first user;
step S742: and correcting the daily urination information of the first user according to the first correction parameter.
Specifically, the input water amount and the output water amount have certain differences according to different physical sign information of the first user. For example, the consumption of water may be different according to the difference between the energy consumption speed and the real-time action consumption of the first user, and further, the consumption of water is related to the perspiration amount of the first user, so that a first correction parameter is obtained according to the physical sign characteristic information of the first user, and the daily urination amount information of the first user is corrected.
Further, in the obtaining the daily food moisture content information of the first user, embodiment S720 of the present application further includes:
step S721: obtaining daily eating category information of the first user;
step S722: obtaining daily food intake information of the first user;
step S723: and obtaining the daily food intake and water content information of the first user according to the daily food intake type information and the daily food intake information of the first user.
Specifically, the food type information of the first user is food type information that the first user eats on the same day, the type information covers a wide range, for example, the types may be classified into grains and potatoes, vegetables and fruits, animal food, soybeans and products thereof, pure energy food, and the like, and the food intake information of the first user is information of amounts of different types of food eaten by the first user on the same day, and the daily eating water content information of the first user is obtained according to different amounts of the different types of food, so as to achieve a technical effect of obtaining accurate daily eating water content information of the first user.
Further, the embodiment of the present application further includes:
step S750: obtaining absorbent capacity information of the first user's care article;
step S760: obtaining a preset water absorption threshold value;
step S770: judging whether the water absorption reaches the preset water absorption threshold value;
step S780: if the water absorption amount reaches the preset water absorption amount threshold value, a second reminding instruction is obtained;
step S790: and collecting urine of the first user according to the second reminding instruction.
Specifically, the nursing article is a nursing product with a water absorption characteristic, and may be, for example, a diaper, a pull-up diaper, a urine isolation pad, and the like, the predetermined water absorption threshold is a predetermined threshold of urine excretion obtained in real time according to a physical state of the first user, when the water absorption reaches the predetermined threshold of water absorption, the information of the urine content of the first user is determined according to the information of the water absorption, when the information of the water absorption reaches the predetermined threshold of water absorption, a second reminding instruction is obtained, and urine is collected for the first user according to the second reminding instruction.
Further, before obtaining the information on the water absorption capacity of the care product of the first user, step S750 of the embodiment of the present application further includes:
step S751: obtaining gender information of a first user;
step S752: acquiring first water absorption position information according to the gender information, wherein the first water absorption position information is the water absorption position information of the first user care product;
step S753: and obtaining the water absorption capacity information of the nursing article of the first user according to the first water absorption position information.
Specifically, the user may be a user with senile dementia or bedridden, the water absorption position information of the urine isolation pad is obtained according to the difference of the gender of the user, and the water absorption amount information of the nursing user product of the first user is obtained according to the water absorption position and the obtained water absorption position, so that the technical effect of accurately judging the water absorption amount information is achieved.
Further, the embodiment of the present application further includes:
step S810: acquiring daily total water inflow information of the first user according to the daily drinking water amount information and the daily eating water content information of the first user;
step S820: acquiring urine conversion rate information of the first user according to the daily total water inflow information and the daily urination information;
step S830: acquiring a second correction parameter according to the urine conversion rate information;
step S840: and correcting the daily urination information of the first user according to the second correction parameter.
Specifically, the urine conversion rate information of the first user is obtained according to the total water inflow information and the total daily urination information of the first user, and the daily urination is estimated according to the continuous urine conversion rate information of several consecutive days, so that the second correction parameter is generated, and the second correction parameter is used for correcting the daily urination information of the first user. The technical effect of improving the urine sample collection efficiency is achieved by estimating and correcting the daily urination amount information of the first user based on the urine conversion rate.
Further, before the sign characteristic information is used as the first input information and the historical defecation law information is used as the second input information and input into the first training model, step S300 in the embodiment of the present application further includes:
step S310: taking the first body characteristic information and the first historical defecation rule information as a first block, taking the second body characteristic information and the second historical defecation rule information as a second block, and so on to obtain an Nth block, wherein N is a natural number greater than 1;
step S320: generating a first verification code according to the first block, wherein the first verification code corresponds to the first block one by one, generating a second verification code according to the second block and the first verification code, and generating an Nth verification code according to the Nth block and the (N-1) th verification code by the same way;
step S330: and respectively copying and storing all the blocks and the verification codes on M electronic devices, wherein M is a natural number greater than 1.
In particular, the blockchain technique, also referred to as a distributed ledger technique, is an emerging technique in which several computing devices participate in "accounting" together, and maintain a complete distributed database together. The blockchain technology has been widely used in many fields due to its characteristics of decentralization, transparency, participation of each computing device in database records, and rapid data synchronization between computing devices. Generating a first verification code according to the first block, wherein the first verification code corresponds to the first block one by one; generating a second verification code according to the second block and the first verification code, wherein the second verification code corresponds to the second block one by one; and in the same way, generating an Nth verification code according to the Nth block and the Nth-1 verification code, wherein N is a natural number greater than 1. When the block needs to be called, after each subsequent node receives data stored by a previous node, the data is verified through a common identification mechanism and then stored, each storage unit is connected in series through a hash function, so that the training data is not easy to lose and damage, the training data is encrypted through logic of a block chain, the safety of the block information is guaranteed, the block information is stored on a plurality of pieces of equipment, the data stored on the plurality of pieces of equipment is processed through the common identification mechanism, namely a small number of the data is subject to majority, when one or more pieces of equipment are tampered, as long as the number of the equipment storing correct data is larger than the number of the equipment storing the correct data, the obtained information still achieves the accuracy of the block information, the safety of the block information is further guaranteed, and the accuracy of the training data is further guaranteed, and the first user needs to obtain the first training data.
To sum up, the information processing method and the information processing device for improving the urine sample collection efficiency provided by the embodiment of the application have the following technical effects:
1. the physical sign characteristic information of the first user is used as first input information, the historical urination law is used as second input information, the first training model is input, and the feature of continuous self-correction and adjustment of the training model is used, so that the technical effects of accurately judging the urination discharge time of the first user and reminding the first user to collect urine according to the discharge time are achieved.
2. Due to the adoption of the mode of obtaining the daily urination amount information of the first user, a foundation is laid for the subsequent accurate analysis of the urination time.
3. The second correction parameter is generated by estimating the daily urination amount through the continuous urine conversion rate information of the continuous days, and the second correction parameter is used for correcting the daily urination amount information of the first user. The technical effect of improving the urine sample collection efficiency is achieved by estimating and correcting the daily urination amount information of the first user based on the urine conversion rate.
Example two
Based on the same inventive concept as the information processing method for improving the urine sample collection efficiency in the previous embodiment, the present invention further provides an information processing device for improving the urine sample collection efficiency, as shown in fig. 2, the device includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain sign characteristic information of a first user;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain historical urination rule information of the first user;
a first input unit 13, where the first input unit 13 is configured to use the sign characteristic information as first input information, and use the historical defecation law information as second input information to input into a first training model, where the first training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: the physical sign characteristic information, the historical defecation rule information and identification information used for identifying whether the first user needs to urinate or not;
a third obtaining unit 14, where the third obtaining unit 14 is configured to obtain first output information of the first training model, where the first output information includes a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain a first reminding instruction when the first output information is a first output result;
a first collection unit 16, wherein the first collection unit 16 is configured to collect urine from the first user according to the first reminding instruction.
Further, the apparatus further comprises:
a fifth obtaining unit configured to obtain daily drinking water amount information of the first user;
a sixth obtaining unit configured to obtain daily eating water content information of the first user;
a second input unit, configured to use the daily drinking water amount information as first input information, and use the daily eating water content information as second input information to be input into a second training model, where the second training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: the daily drinking water amount information, the daily eating water content information and identification information for identifying the urine output of the first user;
a seventh obtaining unit, configured to obtain second output information of the second training model, where the second output information is daily urination information of the first user.
Further, the apparatus further comprises:
an eighth obtaining unit, configured to obtain a first correction parameter according to the sign characteristic information of the first user;
a first correcting unit for correcting the daily urination amount information of the first user based on the first correction parameter.
Further, the apparatus further comprises:
a ninth obtaining unit configured to obtain daily eating category information of the first user;
a tenth obtaining unit configured to obtain daily food intake information of the first user;
an eleventh obtaining unit configured to obtain daily eating water content information of the first user from the daily eating species information and the daily eating amount information of the first user.
Further, the apparatus further comprises:
a twelfth obtaining unit configured to obtain information on the water absorption amount of the care product of the first user;
a thirteenth obtaining unit for obtaining a predetermined water-absorption-amount threshold;
a first judgment unit configured to judge whether the water absorption amount reaches the predetermined water absorption amount threshold;
a fourteenth obtaining unit, configured to obtain a second reminding instruction if the water absorption amount reaches the predetermined water absorption amount threshold;
and the second collection unit is used for collecting urine of the first user according to the second reminding instruction.
Further, the apparatus further comprises:
a fifteenth obtaining unit, configured to obtain gender information of the first user;
a sixteenth obtaining unit, configured to obtain first water absorption position information according to the gender information, where the first water absorption position information is water absorption position information of the first user care product;
a seventeenth obtaining unit configured to obtain information on the water absorption amount of the care product of the first user according to the first water absorption position information.
Further, the apparatus further comprises:
an eighteenth obtaining unit, configured to obtain daily total intake water amount information of the first user according to the daily intake water amount information and the daily eating water content information of the first user;
a nineteenth obtaining unit, configured to obtain urine conversion rate information of the first user according to the daily total intake water amount information and the daily urination amount information;
a twentieth obtaining unit, configured to obtain a second correction parameter according to the urine conversion rate information;
a second correcting unit for correcting the daily urination information of the first user based on the second correction parameter.
Various modifications and specific examples of the information processing method for improving the urine sample collection efficiency in the first embodiment of fig. 1 are also applicable to the information processing device for improving the urine sample collection efficiency in the present embodiment, and through the foregoing detailed description of the information processing method for improving the urine sample collection efficiency, those skilled in the art can clearly understand that a method for implementing the information processing device for improving the urine sample collection efficiency in the present embodiment is not described in detail here for the sake of brevity of the description.
Exemplary electronic device
An electronic apparatus of an 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 the information processing method for improving the collection efficiency of the urine sample, the invention also provides an information processing device for improving the collection efficiency of the urine sample, wherein the information processing device is stored with a computer program, and the computer program is used for realizing the steps of any one of the information processing methods for improving the collection efficiency of the urine sample when being executed by a processor.
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 306 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 apparatus 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 invention provides an information processing method for improving the collection efficiency of a urine sample, which comprises the following steps: obtaining physical sign characteristic information of a first user; obtaining historical urination rule information of the first user; using the physical sign characteristic information as first input information, and using the historical defecation rule information as second input information to be input into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the physical sign characteristic information, the historical defecation rule information and identification information used for identifying whether the first user needs to urinate; obtaining first output information of the first training model, wherein the first output information comprises a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate; when the first output information is a first output result, obtaining a first reminding instruction; and collecting urine of the first user according to the first reminding instruction. The technical problem that urine examination time is delayed due to the fact that urine samples are difficult to collect in the prior art is solved, and the technical effect of improving the collection efficiency of the urine samples is achieved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, 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 (devices), 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 means 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 instruction means 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 the preferred embodiment and all changes and modifications that 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.

Claims (9)

1. An information processing method for improving urine sample collection efficiency, wherein the method comprises the following steps:
obtaining sign characteristic information of a first user, wherein the sign characteristic information comprises identity information and real-time body state information of the first user;
obtaining historical urination rule information of the first user, wherein the historical urination rule is obtained by monitoring the urination times and urination time information of the first user according to daily life and dietary habits of the first user, the urination time comprises urination time information and urination time length information, the urination amount of the first user is estimated and recorded according to the urination time length information, and the historical urination rule information of the first user is obtained according to the urination times, time and discharge capacity;
using the physical sign characteristic information as first input information, and using the historical urination law information as second input information to input into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the physical sign characteristic information, the historical urination rule information and identification information used for identifying whether the first user needs to urinate;
obtaining first output information of the first training model, wherein the first output information comprises a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate;
when the first output information is a first output result, obtaining a first reminding instruction;
and collecting urine of the first user according to the first reminding instruction.
2. The method of claim 1, wherein the method comprises:
obtaining daily water intake information of the first user;
obtaining daily eating water content information of the first user;
taking the daily drinking water amount information as first input information, and taking the daily eating water content information as second input information to be input into a second training model, wherein the second training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the daily drinking water amount information, the daily eating water content information and identification information for identifying the urine output of the first user;
and obtaining second output information of the second training model, wherein the second output information is daily urination information of the first user.
3. The method of claim 2, wherein the method comprises:
obtaining a first correction parameter according to the sign characteristic information of the first user;
and correcting the daily urination information of the first user according to the first correction parameter.
4. The method of claim 2, wherein the obtaining daily eating water content information of the first user comprises:
obtaining daily eating category information of the first user;
obtaining daily food intake information of the first user;
and obtaining the daily food intake and water content information of the first user according to the daily food intake type information and the daily food intake information of the first user.
5. The method of claim 1, wherein the method comprises:
obtaining absorbent capacity information of the first user's care article;
obtaining a predetermined water absorption threshold value;
judging whether the water absorption reaches the preset water absorption threshold value;
if the water absorption amount reaches the preset water absorption amount threshold value, a second reminding instruction is obtained;
and collecting urine of the first user according to the second reminding instruction.
6. The method of claim 5, wherein said obtaining information on the water absorption capacity of the first user's care product comprises, prior to:
obtaining gender information of a first user;
according to the gender information, first water absorption position information is obtained, and the first water absorption position information is the water absorption position information of the first user care product;
and obtaining the water absorption capacity information of the nursing article of the first user according to the first water absorption position information.
7. The method of claim 2, wherein the method comprises:
obtaining the daily total intake water amount information of the first user according to the daily drinking water amount information and the daily eating water content information of the first user;
acquiring urine conversion rate information of the first user according to the daily total water inflow information and the daily urination information;
acquiring a second correction parameter according to the urine conversion rate information;
and correcting the daily urination information of the first user according to the second correction parameter.
8. An information processing apparatus that improves urine sample collection efficiency, wherein the apparatus comprises:
a first obtaining unit, configured to obtain sign characteristic information of a first user, where the sign characteristic information includes identity information and real-time body state information of the first user;
a second obtaining unit, configured to obtain historical urination rule information of the first user, where the historical urination rule is obtained by monitoring urination times and urination time information of the first user according to daily life and dietary habits of the first user, the urination time includes urination time information and urination duration information, the urination amount of the first user is estimated and recorded according to the urination duration information, and the historical urination rule information of the first user is obtained according to the urination times, time and discharge amount;
a first input unit, configured to use the sign characteristic information as first input information, and use the historical urination law information as second input information to input a first training model, where the first training model is obtained through training multiple sets of training data, and each set of training data in the multiple sets includes: the physical sign characteristic information, the historical urination rule information and identification information used for identifying whether the first user needs to urinate;
a third obtaining unit, configured to obtain first output information of the first training model, where the first output information includes a first output result and a second output result, the first output result is a result that the first user needs to urinate, and the second output result is a result that the first user does not need to urinate;
a fourth obtaining unit, configured to obtain a first prompting instruction when the first output information is a first output result;
the first collection unit is used for collecting urine of the first user according to the first reminding instruction.
9. An information processing apparatus for improving urine sample collection efficiency, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to perform the steps of the method of any one of claims 1-7.
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