CN115414543A - Autonomous learning-based breast pump mode adjusting method and device, breast pump and medium - Google Patents

Autonomous learning-based breast pump mode adjusting method and device, breast pump and medium Download PDF

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Publication number
CN115414543A
CN115414543A CN202211099458.8A CN202211099458A CN115414543A CN 115414543 A CN115414543 A CN 115414543A CN 202211099458 A CN202211099458 A CN 202211099458A CN 115414543 A CN115414543 A CN 115414543A
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China
Prior art keywords
milk
user
determining
mode
sucking
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CN202211099458.8A
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Chinese (zh)
Inventor
王耀
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Shenzhen Lute Jiacheng Supply Chain Management Co Ltd
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Shenzhen Lute Jiacheng Supply Chain Management Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
    • A61M1/06—Milking pumps
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
    • A61M1/06—Milking pumps
    • A61M1/062—Pump accessories
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
    • A61M1/06—Milking pumps
    • A61M1/069—Means for improving milking yield
    • A61M1/0693—Means for improving milking yield with programmable or pre-programmed sucking patterns
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
    • A61M1/06—Milking pumps
    • A61M1/069—Means for improving milking yield
    • A61M1/0697—Means for improving milking yield having means for massaging the breast
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M2205/00—General characteristics of the apparatus
    • A61M2205/33—Controlling, regulating or measuring
    • A61M2205/3306—Optical measuring means
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M2205/00—General characteristics of the apparatus
    • A61M2205/33—Controlling, regulating or measuring
    • A61M2205/3331—Pressure; Flow
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M2205/00—General characteristics of the apparatus
    • A61M2205/33—Controlling, regulating or measuring
    • A61M2205/3379—Masses, volumes, levels of fluids in reservoirs, flow rates

Abstract

The invention discloses a breast pump mode adjusting method and device based on autonomous learning, a breast pump and a medium, wherein the method comprises the following steps: recording the milk sucking mode and the milk sucking amount of the user every day in a first preset time period; determining a milk sucking quantity expected value; respectively comparing the milk sucking amount with the expected value of the milk sucking amount, and counting comparison results; and according to the comparison result, determining that the milk sucking mode of the user is met in different time periods. In the application, the milk sucking mode and the milk sucking amount of the user are counted, the optimal milk sucking mode in different time periods is calculated through an AI artificial intelligence algorithm, the milk sucking mode of the user is intelligently prompted or switched, the problem that the user self judges that the milk sucking mode is inaccurate in the existing mode can be effectively solved, the milk sucking mode which is most suitable for the user is provided in different time periods, the user experience can be improved, and the damage to the body of the user is avoided.

Description

Autonomous learning-based breast pump mode adjusting method and device, breast pump and medium
Technical Field
The invention relates to the technical field of mother and infant articles, in particular to a breast pump and a medium, and a breast pump mode adjusting method and device based on autonomous learning.
Background
The breast pump is an auxiliary tool for helping a newborn mother to squeeze milk out of a breast and collect the milk, and the breast pump is used by more and more professional women on the premise of working to meet the requirement of breast feeding.
However, the current breast pumps only rely on the user to adjust the milk suction mode, the milk secreted by the user in different milk suction modes in different periods and different time points is different, the user cannot know the proper milk suction mode, the self-judgment of the accurate milk suction mode is caused, the user repeatedly adopts the uniform milk suction mode to perform the milk suction operation according to factors such as habits, and the milk suction mode is not used accurately, so that the milk suction effect is poor, the too large milk suction amount or the too small milk suction amount is easy to occur, the body health of the user is influenced, and the user experience is poor.
Disclosure of Invention
Therefore, it is necessary to provide a milk pumping mode adjustment method, device, breast pump and medium based on autonomous learning to solve the problems of inaccurate milk pumping mode and poor milk pumping effect, which cannot be self-judged by a user in the prior art.
In a first aspect, a milk elicitation mode adjustment method based on autonomous learning is provided, including:
recording the milk sucking mode and the milk sucking amount of the user every day in a first preset time period;
determining a milk sucking quantity expected value;
respectively comparing the milk sucking amount with the expected value of the milk sucking amount, and counting comparison results;
and according to the comparison result, determining that the milk sucking modes of the user are met in different time periods.
In an embodiment, the recording of the milk elicitation pattern and the milk elicitation amount of the user each day within the preset time period includes:
determining an average of the user's daily milk intake;
determining the physical health state of the user according to the average value;
and pushing corresponding milk sucking suggestions and health promotion suggestions to the user according to the physical health state of the user.
In an embodiment, the determining, according to the comparison result, that the milk sucking mode of the user is met in different time periods includes:
determining the priority sequence of different milk sucking modes in different time periods according to the comparison result;
and determining the optimal milk suction modes in different time periods according to the priority sequence to serve as the milk suction modes which accord with the user in the different time periods.
In an embodiment, the recording the milk suction mode and the milk suction amount of the user each time every day within the first preset time period comprises:
when a user is in a special period, determining the milk sucking mode and the milk sucking amount of the user every day in the special period;
determining a milk absorption reference value in a special period;
and pushing the milk sucking modes corresponding to different time periods in the special period to the user according to the milk sucking reference value and the milk sucking amount of the user every day in the special period.
In an embodiment, after determining that the user's milk elicitation pattern is met for the different time period, the method includes:
determining time information of daily milk absorption of the user;
determining the working time and the rest time of the user according to the time information;
and adjusting the milk suction time which accords with the milk suction mode of the user in different time periods according to the working time and the rest time of the user.
In an embodiment, after determining that the milk sucking mode of the user is met in different time periods according to the comparison result, the method includes:
when different milk suction time periods are reached, sending milk suction prompt information to the user, and pushing a corresponding milk suction mode to the user; or
And when different milk suction time periods are reached, automatically converting the current milk suction mode into the milk suction mode corresponding to the milk suction time period.
In a second aspect, there is provided a milk elicitation pattern adjustment device based on autonomous learning, the device comprising:
the recording unit is used for recording the milk sucking mode and the milk sucking amount of the user every day in a first preset time period;
a milk intake expected value determining unit for determining a milk intake expected value;
the comparison unit is used for comparing the milk sucking amount with the expected value of the milk sucking amount respectively and counting comparison results;
and the milk suction mode determining unit is used for determining the milk suction modes which accord with the user in different time periods according to the comparison result.
In an embodiment, the apparatus further comprises a pushing unit for:
determining an average of the user's daily milk intake;
determining the physical health state of the user according to the average value;
and pushing corresponding milk sucking suggestions and health promotion suggestions to the user according to the physical health state of the user.
In a third aspect, a breast pump is provided, comprising a memory, a processor and computer readable instructions stored in the memory and executable on the processor, the processor implementing the steps of the autonomous learning based milk elicitation pattern adjustment method as described above when executing the computer readable instructions.
In a fourth aspect, a readable storage medium is provided, which stores computer readable instructions, which when executed by a processor, implement the steps of the autonomic learning based milk elicitation pattern adjustment method as described above.
The milk suction mode adjusting method and device based on the autonomous learning, the breast pump and the medium have the following implementation methods: recording the milk sucking mode and the milk sucking amount of the user every day in a first preset time period; determining a milk sucking quantity expected value; respectively comparing the milk sucking amount with the expected value of the milk sucking amount, and counting comparison results; and according to the comparison result, determining that the milk sucking mode of the user is met in different time periods. In this application, through making statistics of user's the mode of suckling and the volume of suckling, AI artificial intelligence algorithm calculates the optimal mode of suckling of different time quantums to intelligence suggestion or switching user's the mode of suckling, can effectively solve the inaccurate problem of user's self-judgement mode of suckling of current mode, provide the most suitable user's mode of suckling in the time quantums of difference, improve the effect of suckling, thereby can improve user experience, avoid causing the damage to user's health.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive labor.
FIG. 1 is a flow chart of a method for adjusting a milk elicitation mode based on autonomic learning according to an embodiment of the present invention;
FIG. 2 is a graph illustrating the variation of milk intake in a simulated infant sucking mode according to an embodiment of the present invention;
FIG. 3 is a graph illustrating the variation of milk intake in a simulated infant sucking mode according to an embodiment of the present invention;
FIG. 4 is a graph illustrating the variation of the milk intake in a simulated baby suckback mode according to an embodiment of the present invention;
FIG. 5 is a graph showing the variation of the milk sucking amount from the small suction to the large suction in the milk sucking mode with 2 suction cycles as a group according to an embodiment of the present invention;
FIG. 6 is a graph showing the variation of the first large suction and the second small suction in the milk sucking mode with 2 suction cycles as a set according to an embodiment of the present invention;
FIG. 7 is a schematic structural diagram of an apparatus for adjusting a milk elicitation mode based on autonomic learning according to an embodiment of the present invention;
fig. 8 is a schematic view of a breast pump in accordance with an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In one embodiment, as shown in fig. 1, there is provided a milk elicitation pattern adjustment method based on autonomous learning, including the steps of:
in step S110, recording a milk sucking mode and a milk sucking amount of a user every day in a first preset time period;
in this embodiment of the present application, the first preset time period may be a specific time range, for example, 60 days, 180 days, and the like, and may be specifically set according to an actual situation, which is not limited herein.
In the embodiment of the present application, according to the milk sucking rule of the user, every other same milk sucking time may be taken as the same sequence of milk sucking times in each day, the statistics may be performed according to the sequence of the milk sucking times in each day and the milk sucking amount, and the expected value a is selected, for example, the milk sucking may be performed at time intervals of 9 am, 2 pm and 6 pm in the sequence of the milk sucking times, which may be E, F, G, and the recording may be performed every day according to the sequence of the milk sucking times, and the milk sucking amount of each time in each day may be respectively counted according to the sequence of the milk sucking times.
In the embodiment of the application, the milk suction mode can comprise massage before milk suction, massage while milk suction, milk suction modes with different milk suction time and massage mode frequency, and the like. Referring to fig. 2-6, several different modes of milk elicitation are shown, and graphs showing the variation of milk elicitation over time and with the intensity of milk elicitation can be seen for the different modes of milk elicitation. By means of the variation graph, the milk suction effect of the milk suction amount in different milk suction modes can be determined.
In this application embodiment, can set up the monitoring devices of the volume of suckling on the storage milk container of breast pump, when carrying out the operation of suckling through this volume of suckling monitoring devices, monitor the milk volume in the storage milk container to transmit for the main control board, it has the AI to independently learn the chip to integrate on this main control board, can independently take notes and operate.
Wherein, this suckling volume monitoring devices can include pressure sensor, acceleration sensor, gravity sensor, inclination sensor, infrared sensor etc..
In the embodiment of the application, the breast pump and the terminal equipment can be associated and synchronously transmitted to the terminal equipment for storage and operation due to excessive data such as the milk sucking amount and the milk sucking mode which need to be recorded.
Wherein, this terminal equipment can include equipment such as cell-phone, panel computer, can install corresponding APP procedure in advance in this equipment to carry out relevance and data transmission with the breast pump.
In the embodiment of the application, the milk sucking mode and the milk sucking amount of the user every day can be collected and recorded in real time, so that the AI artificial intelligence algorithm can be adjusted, and the calculation accuracy is improved.
In an embodiment of the present application, the recording the milk suction mode and the milk suction amount of the user every day after the preset period of time includes:
determining an average of the user's daily milk intake;
determining the physical health state of the user according to the average value;
and pushing corresponding milk sucking suggestions and health promotion suggestions to the user according to the physical health state of the user.
Specifically, the average value of the daily milk intake of the user can be determined according to the recorded daily milk intake mode and the daily milk intake of the user, the physical health state of the user can be determined according to the average value, and when the physical health state of the user is poor or better, corresponding health promotion suggestions can be pushed to the user, for example, when the milk secretion is excessive, the energy intake can be reduced, so that the user can adjust the diet and the living habits, and the user experience can be improved.
In the embodiment of the application, taking n days as an example, the daily milk sucking amount of a user for n days is recordedIs L 1 、L 2 ……L n Calculating the average value e = (L) of the milk absorption amount of n days 1 +L 2 +……+L n )/n；
Calculating the milk absorption quantity L in the n +1 th day n+1 ；
If L is n-1 < e 80% and L n+2 If the health status is less than e, 80%, the current health status of the user is indirectly poor or the pressure is very high, which can be recorded as A, and at the moment, health promotion suggestions can be recommended in a strong intelligent manner, for example, health promotion suggestions are continuously sent to the associated user terminal for multiple times;
if e is 80% or less L n+1 < e 90%, and L n+2 If the current physical health state of the user is general or the pressure is large, the state can be recorded as B, and the health promotion suggestion can be intelligently recommended at the moment, for example, the health promotion suggestion is sent to the associated user terminal;
if e is more than or equal to 90 percent and L is less than or equal to 90 percent n-1 If < e, 110%, indirectly indicating that the physical health state of the user is still clear, and omitting the recommendation;
if e is 110% or less L n+1 < e 120% and L n+2 If the energy intake is larger than e and 110%, indirectly indicating that the current energy intake of the user is larger or the lactation amount is too large, recording the result as C, and pushing health promotion suggestions for reducing lactation or energy intake to the user;
if e is more than or equal to 120 percent and L is less than or equal to n+1 And L is n+2 > e 120%, this indirectly indicates that the precious mother may be too energy intake or very large in lactation, which may be recorded as D, when it is necessary to reduce lactation urgently or to reduce energy intake by a large amount.
In an embodiment of the present application, the recording the milk suction mode and the milk suction amount of the user each time every day within the first preset time period includes:
when a user is in a special period, determining a milk sucking mode and a milk sucking amount of the user every day in the special period;
determining a milk absorption reference value in a special period;
and pushing the milk sucking modes corresponding to different time periods in the special period to the user according to the milk sucking reference value and the milk sucking amount of the user every day in the special period.
Specifically, when the user handles a physiological period or other special periods, the milk suction mode and the milk suction amount of the user every day during the word period can be determined, and according to the milk suction reference value in the special period under normal conditions, the milk suction modes corresponding to different time periods in the special period can be pushed to the user according to the milk suction reference value and the milk suction amount of the user every day during the special period, so that the phenomenon that the milk suction amount of the user is too large during the special period and the body health is affected can be avoided.
Wherein the reference value of milk elicitation for the specific period can be determined by counting the milk elicitation of a plurality of users during the period.
In step S120, a desired milk elicitation amount is determined;
in the embodiment of the application, the expected value of the milk suction amount can be obtained by collecting the milk suction amounts of preset users and calculating an average value to be used as the expected value of the milk suction amount.
In this embodiment, the expected value of the milk suction amount may be obtained by collecting the milk suction amount of the user within a preset time, and calculating an average value as the expected value of the milk suction amount.
In this embodiment, the expected value may include a plurality of values, and a corresponding expected value may be assigned to each sequence of the number of times of milk sucking, for example, an average value of the amount of milk sucked by the user in each sequence of the number of times of milk sucking per day may be respectively counted as the expected value of the sequence of the number of times of milk sucking.
In step S130, comparing the milk intake with the expected value of the milk intake, and counting the comparison result;
in the embodiment of the application, the milk suction amount of each time every day can be respectively compared with the milk suction amount, and the comparison records and stores the result.
In step S140, according to the comparison result, it is determined that the milk sucking mode of the user is met in different time periods.
In an embodiment of the present application, determining, according to the comparison result, that the milk sucking mode of the user is met in different time periods includes:
determining the priority sequence of different milk suction modes in different time periods according to the comparison result;
and determining the optimal milk suction modes in different time periods according to the priority sequence to serve as the milk suction modes which accord with the user in the different time periods.
Specifically, the expected value is a, the milk volume in a certain sequence of milk withdrawal times on a certain day is a, the statistic is 1 when a > a, the statistic is 2 when 80% a < a, and the statistic is N when 60% a < 80% a, the statistic is 3,a. Wherein, should 1 be better suckling mode, 2 be the suboptimum suckling mode, 3 and N can be ignored, confirm 1 the time corresponding suckling mode that appears, can confirm that the time quantum that corresponds at present suckling number of times order accords with user's suckling mode.
Further, when the corresponding milk suction modes are different when 1 occurs, the number of different milk suction modes can be counted, and the milk suction mode with the largest number is taken as the optimal milk suction mode.
In an embodiment of the present application, after determining that the milk suction mode of the user is met in different time periods, the method includes:
determining time information of daily milk absorption of the user;
determining the working time and the rest time of the user according to the time information;
and adjusting the milk suction time which accords with the milk suction mode of the user in different time periods according to the working time and the rest time of the user.
Specifically, the time information corresponding to each time of milk suction of the user every day can be counted, and the working time and the rest time of the user are determined according to the time information, for example, when the user performs the milk suction operation at 7 am, 1 am and 6 pm every day, the working time can be considered to be fixed, so that the milk suction time of each milk suction mode can be adjusted, and the problems of milk blockage or mastitis and the like caused by untimely milk suction are avoided.
In an embodiment, after determining that the milk sucking mode of the user is met in different time periods according to the comparison result, the method includes:
when different milk suction time periods are reached, sending milk suction prompt information to the user, and pushing a corresponding milk suction mode to the user; or
And when different milk sucking time periods are reached, automatically converting the current milk sucking mode into a milk sucking mode corresponding to the milk sucking time period.
Specifically, after determining that the different time periods accord with the milk suction modes of the user, whether the user performs the milk suction operation currently can be detected when the corresponding time periods are reached, if not, the user is prompted to perform the milk suction operation currently, and the milk suction mode corresponding to the current time period of the user is provided. If so, determining whether the current milk suction mode is consistent with the milk suction mode corresponding to the current time period, and if not, automatically converting the current milk suction mode into the milk suction mode corresponding to the milk suction time period, so that a user can adopt the optimal milk suction mode at different time periods, and the user experience is improved.
The embodiment of the application provides a milk elicitation mode adjustment method based on autonomous learning, which comprises the following steps: recording the milk sucking mode and the milk sucking amount of the user every day in a first preset time period; determining a milk sucking quantity expected value; respectively comparing the milk intake with the expected value of the milk intake, and counting comparison results; and according to the comparison result, determining that the milk sucking mode of the user is met in different time periods. In the application, through making statistics of the milk sucking mode and the milk sucking amount of the user, the AI artificial intelligence algorithm calculates the optimal milk sucking mode in different time periods, so that the intelligent prompt or the switching of the milk sucking mode of the user can effectively solve the problem that the user self judges that the milk sucking mode is inaccurate in the existing mode, the milk sucking mode which is most suitable for the user is provided in different time periods, the user experience can be improved, and the damage to the body of the user is avoided.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In one embodiment, a milk elicitation pattern adjustment device based on autonomous learning is provided, and the milk elicitation pattern adjustment device based on autonomous learning corresponds to the milk elicitation pattern adjustment method based on autonomous learning in the above-described embodiments one to one. As shown in fig. 7, the self-learning based milk elicitation mode adjustment device includes a recording unit 10, a milk elicitation amount expected value determination unit 20, a comparison unit 30, and a milk elicitation mode determination unit 40. The functional modules are explained in detail as follows:
the recording unit 10 is used for recording the milk sucking mode and the milk sucking amount of the user every day in a first preset time period;
a milk intake desired value determining unit 20 for determining a milk intake desired value;
a comparison unit 30, configured to compare the milk intake with the expected milk intake value, and count comparison results;
and the milk sucking mode determining unit 40 is used for determining the milk sucking modes which accord with the user in different time periods according to the comparison result.
In an embodiment, the apparatus further comprises a pushing unit for:
determining an average of the user's daily milk intake;
determining the physical health state of the user according to the average value;
and pushing corresponding milk sucking suggestions and health promotion suggestions to the user according to the physical health state of the user.
In an embodiment, the milk elicitation mode determination unit 40 is further configured to:
determining the priority sequence of different milk suction modes in different time periods according to the comparison result;
and determining the optimal milk suction modes in different time periods according to the priority sequence to serve as the milk suction modes which accord with the user in the different time periods.
In an embodiment, the apparatus further comprises a special-period milk elicitation mode adjustment unit for:
when a user is in a special period, determining a milk sucking mode and a milk sucking amount of the user every day in the special period;
determining a milk sucking reference value in a special period;
and pushing the milk sucking modes corresponding to different time periods in the special period to the user according to the milk sucking reference value and the milk sucking amount of the user every day in the special period.
In an embodiment, the apparatus further comprises a milk elicitation time adjustment unit for:
determining time information of daily milk absorption of the user;
determining the working time and the rest time of the user according to the time information;
and adjusting the milk suction time which accords with the milk suction mode of the user in different time periods according to the working time and the rest time of the user.
In an embodiment, the apparatus further comprises a milk elicitation mode switching unit for:
when different milk suction time periods are reached, sending milk suction prompt information to the user, and pushing a corresponding milk suction mode to the user; or
And when different milk suction time periods are reached, automatically converting the current milk suction mode into the milk suction mode corresponding to the milk suction time period.
In the embodiment of the application, the optimal milk sucking modes in different time periods are calculated by the AI artificial intelligence algorithm through counting the milk sucking modes and the milk sucking amount of the user, so that the milk sucking modes of the user are intelligently prompted or switched, the problem that the user self judges that the milk sucking modes are inaccurate in the existing mode can be effectively solved, the milk sucking modes most suitable for the user are provided in different time periods, the user experience can be improved, and the damage to the body of the user is avoided.
For the specific definition of the autonomous learning based milk elicitation pattern adjustment device, reference may be made to the above definition of the autonomous learning based milk elicitation pattern adjustment method, which is not described in detail herein. The modules in the above autonomous learning-based milk elicitation mode adjustment device can be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a breast pump is provided, the internal structure of which may be as shown in fig. 8. The system comprises a processor, a memory and a network interface. Wherein the processor is configured to provide computing and control capabilities. The memory includes a readable storage medium. The readable storage medium may be used to store milk volume and milk elicitation patterns and computer control instructions. The network interface may be used to communicate with an external terminal over a network connection. The computer readable instructions, when executed by a processor, implement a method for autonomous learning based breast pattern adjustment.
A breast pump comprising a memory, a processor and computer readable instructions stored in the memory and executable on the processor, the processor when executing the computer readable instructions implementing the steps of the autonomous learning based breast pumping pattern adjusting method as described above.
A readable storage medium storing computer readable instructions which, when executed by a processor, implement the steps of the autonomous learning based milk elicitation pattern adjustment method as described above.
It will be understood by those of ordinary skill in the art that all or part of the processes of the methods of the above embodiments may be implemented by hardware related to computer readable instructions, which may be stored in a non-volatile readable storage medium or a volatile readable storage medium, and when executed, the computer readable instructions may include processes of the above embodiments of the methods. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims (10)

1. A milk elicitation pattern adjustment method based on autonomous learning, characterized in that the method comprises:
recording the milk sucking mode and the milk sucking amount of the user every day in a first preset time period;
determining a milk sucking quantity expected value;
respectively comparing the milk intake with the expected value of the milk intake, and counting comparison results;
and according to the comparison result, determining that the milk sucking mode of the user is met in different time periods.
2. The method for adjusting a milk elicitation pattern based on autonomous learning according to claim 1, wherein said recording of the milk elicitation pattern and the milk elicitation quantity of the user each day over a preset period of time comprises:
determining an average of the user's daily milk intake;
determining the physical health state of the user according to the average value;
and pushing corresponding milk sucking suggestions and health promotion suggestions to the user according to the physical health state of the user.
3. The method for adjusting a milk elicitation pattern based on autonomous learning according to claim 1, wherein the determining, according to the comparison result, a milk elicitation pattern that corresponds to the user in different time periods includes:
determining the priority sequence of different milk suction modes in different time periods according to the comparison result;
and determining the optimal milk suction modes in different time periods according to the priority sequence to serve as the milk suction modes which accord with the user in the different time periods.
4. The method for adjusting a milk elicitation pattern based on autonomous learning according to claim 1, wherein said recording of the milk elicitation pattern and the milk elicitation quantity of the user each day during a first preset period of time comprises:
when a user is in a special period, determining a milk sucking mode and a milk sucking amount of the user every day in the special period;
determining a milk sucking reference value in a special period;
and pushing the milk sucking modes corresponding to different time periods in the special period to the user according to the milk sucking reference value and the milk sucking amount of the user every day in the special period.
5. The autonomic learning based milk elicitation pattern adjustment method according to claim 1, wherein after determining that the user's milk elicitation pattern is met for a different period of time, comprising:
determining time information of daily milk absorption of the user;
determining the working time and the rest time of the user according to the time information;
and adjusting the milk suction time which accords with the milk suction mode of the user in different time periods according to the working time and the rest time of the user.
6. The method for adjusting a milk elicitation pattern based on autonomous learning according to any one of claims 1 to 5, wherein after determining, according to the comparison result, that the milk elicitation pattern of the user is met in different time periods, the method comprises:
when different milk suction time periods are reached, sending milk suction prompt information to the user, and pushing a corresponding milk suction mode to the user; or alternatively
And when different milk suction time periods are reached, automatically converting the current milk suction mode into the milk suction mode corresponding to the milk suction time period.
7. An apparatus for adjusting a milk elicitation pattern based on autonomous learning, the apparatus comprising:
the recording unit is used for recording the milk sucking mode and the milk sucking amount of the user every day in a first preset time period;
a milk intake expected value determining unit for determining a milk intake expected value;
the comparison unit is used for comparing the milk sucking amount with the expected value of the milk sucking amount respectively and counting comparison results;
and the milk suction mode determining unit is used for determining the milk suction modes which accord with the user in different time periods according to the comparison result.
8. The autonomous learning based milk elicitation mode adjustment device according to claim 7, characterised in that it further comprises a pushing unit for:
determining an average of the user's daily milk intake;
determining the physical health state of the user according to the average value;
and pushing corresponding milk sucking suggestions and health promotion suggestions to the user according to the physical health state of the user.
9. A breast pump comprising a memory, a processor and computer readable instructions stored in the memory and executable on the processor, wherein the processor when executing the computer readable instructions carries out the steps of the method of adjusting a pumping pattern based on autonomous learning according to any of claims 1 to 6.
10. A readable storage medium storing computer readable instructions, wherein the computer readable instructions, when executed by a processor, implement the steps of the autonomic learning-based milk elicitation pattern adjustment method according to any one of claims 1 to 6.
CN202211099458.8A 2022-09-08 2022-09-08 Autonomous learning-based breast pump mode adjusting method and device, breast pump and medium Withdrawn CN115414543A (en)

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CN202211099458.8A CN115414543A (en) 2022-09-08 2022-09-08 Autonomous learning-based breast pump mode adjusting method and device, breast pump and medium

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Application Number Priority Date Filing Date Title
CN202211099458.8A CN115414543A (en) 2022-09-08 2022-09-08 Autonomous learning-based breast pump mode adjusting method and device, breast pump and medium

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CN115414543A true CN115414543A (en) 2022-12-02

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Application publication date: 20221202