CN116196497A - Mode adjustment method, system, equipment and medium based on electric breast pump - Google Patents
Mode adjustment method, system, equipment and medium based on electric breast pump Download PDFInfo
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- CN116196497A CN116196497A CN202310060408.7A CN202310060408A CN116196497A CN 116196497 A CN116196497 A CN 116196497A CN 202310060408 A CN202310060408 A CN 202310060408A CN 116196497 A CN116196497 A CN 116196497A
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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
- A61M1/069—Means for improving milking yield
- A61M1/0693—Means for improving milking yield with programmable or pre-programmed sucking patterns
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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
- A61M2205/00—General characteristics of the apparatus
- A61M2205/33—Controlling, regulating or measuring
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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
- A61M2205/00—General characteristics of the apparatus
- A61M2205/50—General characteristics of the apparatus with microprocessors or computers
Abstract
The application discloses a mode adjustment method, a system, equipment and a medium based on an electric breast pump, wherein the mode adjustment method based on the electric breast pump comprises the following steps: acquiring user physiological information and infant real-time physiological information; based on the real-time physiological information of the infant and the physiological information of the user, monitoring real-time milk quantity data corresponding to each working state of the breast pump; establishing a deep learning model through real-time milk quantity data, and adjusting the working mode of the breast pump through an equipment module carried by the breast pump based on the deep learning model; according to the method, real-time milk quantity data corresponding to each working state of the breast pump is counted through the acquired real-time physiological information of the infant and physiological information of the user by adopting a deep learning model, then a control strategy is formulated, and the working mode of the breast pump is adjusted through a device module carried by the breast pump, so that timeliness, convenience and accuracy of the control of the working mode of the breast pump are improved.
Description
Technical Field
The application relates to the field of mother and infant articles and appliance control, in particular to a mode adjustment method, a mode adjustment system, mode adjustment equipment and mode adjustment media based on an electric breast pump.
Background
Women in the later and lactation period have a strong prolactin secretion to promote mammary gland development and lactation, during which the women can use a breast pump to express breast milk accumulated in the breast, and breast-fed women use a breast pump to extract breast milk, so that the breast milk can be used later to feed infants. The breast pump has a manual type and an electric type, wherein the manual type is divided into a simple rubber ball suction mode, a needle cylinder type and a pressing type, the electric type is divided into a stimulable milk array and a non-stimulable milk array, and the manual type is also divided into a single pump, a double pump and a wearable type. Among these, electric breastpumps typically have different settings or modes of operation, with a stimulation phase and an expression phase (during which breast milk is expressed).
However, most of electric breast pumps on the market at present are sucking force and time adjusted by users, and the breast pump is difficult to adjust to the breast pumping operation suitable for the conditions of the users, so that the breast pumping effect is poor, and the body health of the users is easily affected.
Therefore, the above technical problems are to be solved.
Disclosure of Invention
The embodiment of the application provides a mode adjustment method, a system, equipment and a medium based on an electric breast pump, which are used for solving or partially solving the problems that most of breast pumps in the current market are sucking force and time adjusted by users, and the breast pump is difficult to adjust to breast pumping operation suitable for self conditions by the users, so that the breast pumping effect is poor and the physical health of the users is easily affected.
A method of mode adjustment based on an electric breast pump, comprising:
acquiring user physiological information and infant real-time physiological information;
based on the real-time physiological information of the infant and the physiological information of the user, monitoring real-time milk quantity data corresponding to each working state of the breast pump;
and establishing a deep learning model through real-time milk quantity data, and adjusting the working mode of the breast pump through an equipment module carried by the breast pump based on the deep learning model.
The present application may be further configured in a preferred example to: monitoring real-time milk volume data corresponding to each working state of the breast pump, comprising:
and recording first real-time milk volume data and first time corresponding to the current working state, and recording second real-time milk volume data and second time corresponding to the next adjacent working state, wherein the first real-time milk volume data and the second time are used for calculating average milk velocity.
The present application may be further configured in a preferred example to: establishing a deep learning model through real-time milk volume data, adjusting the working mode of the breast pump through an equipment module carried by the breast pump based on the deep learning model, and comprising the following steps:
and analyzing the average milk output speed by adopting a time sequence to obtain a milk quantity prediction result, and formulating and updating a control strategy according to the milk quantity prediction result to establish a deep learning model and adjusting the working mode of the breast pump according to the deep learning model.
The present application may be further configured in a preferred example to: the control strategy includes a target operating frequency of the breast pump;
adjusting an operating mode of the breast pump by an equipment module carried by the breast pump, comprising:
based on real-time physiological information of the infant, acquiring the current working frequency of the breast pump;
and adjusting the current working frequency according to the target working frequency so as to keep the current working frequency consistent with the target working frequency.
The present application may be further configured in a preferred example to: adjusting an operating mode of the breast pump by an equipment module carried by the breast pump, comprising:
acquiring a target breast pumping force of the breast pump based on the physiological information of the user;
based on the target pumping force, the current pumping force of the breast pump is adjusted so that the current pumping force is consistent with the target pumping force.
The present application may be further configured in a preferred example to: the user physiological information comprises a current breast picture of the user;
after acquiring the physiological information of the user, the method comprises the following steps:
comparing the current breast picture of the user with the physiological information of the user to obtain the current breast state of the user;
based on the current breast state of the user, the operational state of the breast pump is determined.
The present application may be further configured in a preferred example to: the user's current breast state includes a swelling parameter and/or a hardness parameter;
after obtaining the current breast state of the user, comprising:
if the swelling parameter is greater than or equal to a preset swelling parameter threshold value, and/or if the hardness parameter is greater than or equal to a preset hardness parameter threshold value, suspending the breast pumping mode of the breast pump, and controlling the equipment module to perform hot compress and massage on the breast of the user;
if the swelling parameter is smaller than a preset swelling parameter threshold value and the real-time milk quantity data is smaller than an extrusion stage threshold value, the control equipment module massages the breast of the user.
The second object of the present application is to provide a mode adjustment system based on an electric breast pump.
The second object of the present application is achieved by the following technical solutions:
a motor-driven breast pump-based mode adjustment system, comprising:
the information acquisition module is used for acquiring the physiological information of the user and the real-time physiological information of the infant;
the real-time milk quantity data acquisition module is used for monitoring real-time milk quantity data corresponding to each working state of the breast pump based on real-time physiological information of infants and physiological information of users;
and the deep learning model is established and the working mode adjusting module is used for establishing a deep learning model through real-time milk quantity data, and adjusting the working mode of the breast pump through the equipment module carried by the breast pump based on the deep learning model.
The third object of the present application is to provide an electronic device.
The third object of the present application is achieved by the following technical solutions:
an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the above-described mode adjustment method based on an electric breast pump when executing the computer program.
A computer readable storage medium storing a computer program which when executed by a processor implements the above-described mode adjustment method based on an electric breast pump.
In summary, the present application includes the following beneficial technical effects:
according to the mode adjustment method based on the electric breast pump, the real-time physiological information of the infant and the physiological information of the user are acquired through the system input or the third party equipment, then the real-time milk quantity data corresponding to each working state of the breast pump is acquired through the storage equipment carried by the breast pump according to the real-time physiological information of the infant and the physiological information of the user, further the real-time milk quantity data corresponding to each working state of the breast pump is counted, a deep learning model is built, the working mode of the breast pump is adjusted through the equipment module carried by the breast pump in combination with the deep learning model, and timeliness, convenience and accuracy of mode adjustment corresponding to each working state of the breast pump are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments of the present application will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a flow chart of a mode adjustment method based on an electric breast pump according to an embodiment of the present application;
FIG. 2 is a flow chart showing a method for adjusting a mode based on an electric breast pump according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a mode adjustment system based on an electric breast pump according to an embodiment of the present application;
fig. 4 is a schematic diagram of an electronic device according to an embodiment of the application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
Embodiments of the present application are described in further detail below with reference to the drawings attached hereto.
The embodiment of the application provides a mode adjustment method based on an electric breast pump, and the main flow of the method is described as follows:
referring to fig. 1, S10, user physiological information and infant real-time physiological information are acquired.
Specifically, in this embodiment, real-time physiological information of the infant and physiological information of the user are obtained through data such as a hospital diagnosis list or the like input into the system or pictures taken by the third party device.
The real-time physiological information of the infant may include information such as gender, age, weight, physical state, etc. of the infant, and the physiological information of the user may include information such as height, weight, diet, breast size, breast position, breast information, areola, etc.
The step S10 has the effect of improving the accuracy and the comprehensiveness of acquiring the physiological information of the user and the real-time physiological information of the infant.
S20, monitoring real-time milk quantity data corresponding to each working state of the breast pump based on real-time physiological information of the infant and physiological information of the user.
Specifically, according to the real-time physiological information of the infant and the physiological information of the user, the embodiment monitors real-time milk quantity data corresponding to each working state of the breast pump through scales on milk storage equipment carried on the breast pump.
The step S20 is used for monitoring milk quantity obtaining conditions under different working states, and improving accuracy and reliability of adjustment of the mode of the electric breast pump.
S30, establishing a deep learning model through real-time milk quantity data, and adjusting the working mode of the breast pump through an equipment module carried by the breast pump based on the deep learning model.
Specifically, the embodiment performs statistics on the monitored real-time milk volume data, establishes a deep learning model according to the statistics result, and then adjusts the working mode of the breast pump by using the deep learning model and combining with the equipment module carried on the breast pump.
The function of step S30 is to adjust the working mode of the breast pump by using the deep learning model, so as to improve the timeliness, intelligence and reliability of the mode adjustment of the electric breast pump.
According to the mode adjustment method based on the electric breast pump, the real-time physiological information of the infant and the physiological information of the user are acquired through the system input or the third party equipment, then the real-time milk quantity data corresponding to each working state of the breast pump is monitored through the storage equipment carried by the breast pump according to the real-time physiological information of the infant and the physiological information of the user, further the real-time milk quantity data corresponding to each working state of the breast pump is counted, a deep learning model is built, the working mode of the breast pump is adjusted through the equipment module carried by the breast pump in combination with the deep learning model, and timeliness, convenience and accuracy of mode adjustment corresponding to each working state of the breast pump are improved.
In some possible embodiments, the user physiological information comprises a current breast picture of the user.
After step S10, i.e. after acquiring the physiological information of the user, it comprises:
s11, comparing the current breast picture of the user with physiological information of the user to obtain the current breast state of the user.
S12, determining the working state of the breast pump based on the current breast state of the user.
Specifically, the present embodiment obtains a current breast picture of a user through a third party device, analyzes information such as a breast size, a areola size, a nipple size and the like according to the current breast picture of the user, obtains a current breast state of the user, adjusts the working state of the breast pump to continue the breast pumping operation if the current breast state of the user is good, adjusts the working state of the breast pump to suspend the breast pumping operation if the current breast state of the user is abnormal, and further determines the working mode of the breast pump according to current breast parameters obtained by analyzing the current breast picture of the user, wherein the working mode can include a breast pumping mode, a hot compress mode, a massage mode and the like. It should be appreciated that in this embodiment, the user may also set and adjust the operation mode of each breast pump according to the current breast parameters.
The step S11 and the step S12 have the function of determining the working state of the breast pump according to the current breast state of the user, so that the accuracy and the reliability of adjusting the working state of the breast pump are improved.
In some possible embodiments, step S20, that is, monitoring real-time milk volume data corresponding to each operation state of the breast pump, includes:
s201, recording first real-time milk volume data and first time corresponding to the current working state, and recording second real-time milk volume data and second time corresponding to the next adjacent working state, wherein the first real-time milk volume data and the second time are used for calculating average milk output speed.
Specifically, in this embodiment, a time acquisition interval is set in advance in the system, first real-time milk volume data and a first time corresponding to a current working state are obtained according to milk storage equipment carried by the breast pump, then second real-time milk volume data and a second time corresponding to a next adjacent working state are recorded according to the time acquisition interval, and so on, the (n-1) th real-time milk volume data and the (n-1) th time are obtained, the n-th real-time milk volume data and the n-th time are obtained, and then an average milk output speed is obtained by using an average milk output speed calculation formula.
Wherein the average milk yield rate calculation formula is average milk yield rate =
If the calculated average milk output speed is a positive value, the average milk output of the breast pumps corresponding to the (n-1) th time to the n-th time is increased; if the calculated average milk output rate is a negative value, it is explained that the average milk output of the breast pumps corresponding to the (n-1) th to the n-th times is reduced. />
The function of step S201 is to further adjust the operation mode of the breast pump by calculating the average milk output speed, thereby improving the accuracy and reliability of the adjustment of the breast pump mode.
In some possible embodiments, the user's current breast state includes a swelling parameter and/or a hardness parameter.
After step S20, i.e. after obtaining the current breast state of the user, comprises:
s21, if the swelling parameter is greater than or equal to a preset swelling parameter threshold value, and/or if the hardness parameter is greater than or equal to a preset hardness parameter threshold value, suspending the breast pumping mode of the breast pump, and controlling the equipment module to perform hot compress and massage on the breasts of the user.
And S22, if the swelling parameter is smaller than a preset swelling parameter threshold value and the real-time milk quantity data is smaller than an extrusion stage threshold value, the control equipment module massages the breast of the user.
Specifically, in this embodiment, the current breast picture of the user obtained by the third party is compared with a breast information database stored in the system in advance to obtain abnormal breast information, and the current breast picture of the user is analyzed to obtain swelling parameters and/or hardness parameters. And comparing the swelling parameter and/or the hardness parameter with a swelling parameter threshold and/or a hardness parameter threshold preset in the system. If the swelling parameter is greater than or equal to a preset swelling parameter threshold value, and/or if the hardness parameter is greater than or equal to a preset hardness parameter threshold value, suspending the breast pumping mode of the breast pump, controlling a heating module in the equipment module to perform hot compress on the breast of the user, and controlling a massage module in the equipment module to massage the breast of the user. And if the swelling parameter is smaller than a preset swelling parameter threshold value and the real-time milk quantity data is smaller than an extrusion stage threshold value, controlling a massage module in the equipment module to massage the breast of the user.
The function of step S21 and step S22 is that the control device module functionally adjusts the state of the user 'S breast according to the swelling parameter and/or the hardness parameter, thereby improving the milk yield rate of the user' S breast.
In some possible embodiments, step S30, i.e. establishing a deep learning model by real-time milk volume data, adjusts the operation mode of the breast pump by the device module carried by the breast pump based on the deep learning model, includes:
s301, analyzing the average milk output speed by adopting a time sequence to obtain a milk quantity prediction result, and formulating and updating a control strategy according to the milk quantity prediction result to establish a deep learning model and adjusting the working mode of the breast pump according to the deep learning model.
The time sequence is a sequence formed by arranging numerical values of a certain statistical index of a certain phenomenon at different times in time sequence.
Specifically, in this embodiment, the values of the average milk output speed in different time periods are arranged according to the time sequence by adopting a time sequence, so as to form an average milk output speed sequence chart, a milk quantity prediction result is obtained according to the average milk output speed sequence chart, then a corresponding infant feeding schedule is obtained according to the milk quantity prediction result, a control strategy is formulated, the control strategy is updated into a system database, a deep learning model is further established, and then the working mode of the breast pump is adjusted according to the deep learning model.
Wherein the infant feeding schedule includes feeding periods, frequency, milk volume, and the like.
The function of step S301 is to improve the timeliness, predictability, intelligence and reliability of the adjustment of the electric breast pump mode.
In some possible embodiments, the control strategy includes a target operating frequency of the breast pump;
step S30, namely adjusting the operation mode of the breast pump by the device module carried by the breast pump, includes:
s302, acquiring the current working frequency of the breast pump based on real-time physiological information of the infant.
S303, adjusting the current working frequency according to the target working frequency so as to keep the current working frequency consistent with the target working frequency.
Specifically, the present embodiment obtains the current operating frequency of the breast pump according to the information such as the breast pumping frequency, the suction period, the breast pumping force, the breast pumping amount of the infant and the like in the real-time physiological information of the infant, and then controls the current operating frequency of the breast pump according to the target operating frequency until the current operating frequency is consistent with the target operating frequency.
The function of step S302 and step S303 is to improve the accuracy and reliability of the adjustment of the operating frequency of the breast pump.
In some possible embodiments, step S30, i.e. adjusting the operation mode of the breast pump by means of the equipment module carried by the breast pump, comprises:
s304, acquiring the target breast pumping force of the breast pump based on the physiological information of the user.
S305, adjusting the current breast pumping force of the breast pump based on the target breast pumping force so as to keep the current breast pumping force consistent with the target breast pumping force.
Specifically, the embodiment obtains the target breast pumping force of the breast pump according to the information such as the swelling parameter, the hardness parameter, the areola size, the breast size and the like in the physiological information of the user, and then controls the current breast pumping force of the breast pump according to the target breast pumping force until the current breast pumping force is consistent with the target breast pumping force.
The function of step S304 and step S305 is to improve the accuracy and timeliness of the current adjustment of the pumping force of the breast pump.
According to the mode adjustment method based on the electric breast pump, as shown in fig. 2, the working state of the breast pump is determined according to the current breast state of a user, so that the accuracy and reliability of the adjustment of the working state of the breast pump are improved; the working mode of the breast pump is further adjusted by calculating the average milk outlet speed, so that the accuracy and the reliability of the mode adjustment of the breast pump are improved; according to the swelling parameter and/or the hardness parameter, the control equipment module functionally adjusts the state of the breast of the user, so that the breast output speed of the breast of the user is improved.
In another embodiment of the present application, a mode adjustment system based on an electric breast pump is disclosed.
Referring to fig. 3, the mode adjustment system based on the electric breast pump includes:
the acquisition information module 10 is used for acquiring the physiological information of the user and the real-time physiological information of the infant.
The real-time milk quantity data acquisition module 20 is used for acquiring real-time milk quantity data corresponding to each working state of the breast pump based on real-time physiological information of the infant and physiological information of a user.
The deep learning model is built and the working mode is adjusted module 30 is used for building the deep learning model through real-time milk volume data, and based on the deep learning model, the working mode of the breast pump is adjusted through the equipment module carried by the breast pump.
The mode adjustment system based on the electric breast pump provided in this embodiment can achieve the same technical effects as the foregoing embodiments due to the functions of each module and the logic connection between each module, and the principle analysis can see the relevant description of the steps of the mode adjustment method based on the electric breast pump, which is not repeated here.
For specific limitations regarding the electric breast pump based mode adjustment system, reference may be made to the above limitations regarding the electric breast pump based mode adjustment method, which are not described in detail herein. The various modules in the above-described electric breast pump-based mode adjustment system may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or independent of a processor in the device, or may be stored in software in a memory in the device, so that the processor may call and execute operations corresponding to the above modules.
In an embodiment, an electronic device is provided, which may be a monitoring terminal, and an internal structure diagram thereof may be as shown in fig. 4. The electronic device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the electronic device is configured to provide computing and control capabilities. The memory of the electronic device includes a non-volatile medium, an internal memory. The non-volatile medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile media. The database of the electronic equipment is used for storing data to be saved in the mode adjustment method based on the electric breast pump. The network interface of the electronic device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method of mode adjustment based on an electric breast pump.
In an embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the mode adjustment method based on the electric breast pump according to the above embodiment, for example, step S10 to step S30 shown in fig. 1. Alternatively, the processor, when executing the computer program, implements the functions of the modules/units of the electric breast pump based mode adjustment system of the above embodiment, such as the functions of the modules 10 to 30 shown in fig. 3. To avoid repetition, no further description is provided here.
In an embodiment, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the mode adjustment method based on the electric breast pump of the above embodiment, or which when executed by a processor implements the functions of each module/unit in the mode adjustment system based on the electric breast pump of the above system embodiment. To avoid repetition, no further description is provided here.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable medium that when executed comprises the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile 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), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the system is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. A method for adjusting a mode based on an electric breast pump, comprising:
acquiring user physiological information and infant real-time physiological information;
based on the real-time physiological information of the infant and the physiological information of the user, monitoring real-time milk quantity data corresponding to each working state of the breast pump;
and establishing a deep learning model through the real-time milk quantity data, and adjusting the working mode of the breast pump through an equipment module carried by the breast pump based on the deep learning model.
2. The method for adjusting a mode based on an electric breast pump according to claim 1, wherein the monitoring real-time milk volume data corresponding to each working state of the breast pump comprises:
and recording first real-time milk volume data and first time corresponding to the current working state, and recording second real-time milk volume data and second time corresponding to the next adjacent working state, wherein the first real-time milk volume data and the second time are used for calculating average milk velocity.
3. The method for adjusting a mode based on an electric breast pump according to claim 1, wherein the establishing a deep learning model by the real-time milk volume data, adjusting the operation mode of the breast pump by an equipment module carried by the breast pump based on the deep learning model, comprises:
and analyzing the average milk output speed by adopting a time sequence to obtain a milk quantity prediction result, and formulating and updating a control strategy according to the milk quantity prediction result, wherein the control strategy is used for establishing the deep learning model and adjusting the working mode of the breast pump according to the deep learning model.
4. A method of adjusting a mode based on an electric breast pump according to claim 3, wherein said control strategy comprises a target operating frequency of said breast pump;
the adjusting the working mode of the breast pump by the equipment module carried by the breast pump comprises the following steps:
acquiring the current working frequency of the breast pump based on the real-time physiological information of the infant;
and adjusting the current working frequency according to the target working frequency so as to keep the current working frequency consistent with the target working frequency.
5. The method for adjusting a mode based on an electric breast pump according to claim 1, wherein the adjusting the operation mode of the breast pump by the equipment module carried by the breast pump comprises:
acquiring a target breast pumping force of the breast pump based on the physiological information of the user;
and adjusting the current breast pumping force of the breast pump based on the target breast pumping force so as to enable the current breast pumping force to be consistent with the target breast pumping force.
6. The method of claim 1, wherein the user physiological information comprises a current breast picture of the user;
after the acquisition of the physiological information of the user, the method comprises the following steps:
comparing the current breast picture of the user with the physiological information of the user to obtain the current breast state of the user;
based on the current breast state of the user, an operational state of the breast pump is determined.
7. The method of claim 6, wherein the user's current breast state includes a swelling parameter and/or a hardness parameter;
after said obtaining the current breast state of the user, comprising:
if the swelling parameter is greater than or equal to a preset swelling parameter threshold value, and/or if the hardness parameter is greater than or equal to a preset hardness parameter threshold value, suspending a breast pumping mode of the breast pump, and controlling the equipment module to perform hot compress and massage on the breasts of the user;
and if the swelling parameter is smaller than a preset swelling parameter threshold and the real-time milk quantity data is smaller than the extrusion stage threshold, the control equipment module massages the breast of the user.
8. A mode adjustment system based on an electric breast pump, comprising:
the information acquisition module is used for acquiring the physiological information of the user and the real-time physiological information of the infant;
the real-time milk quantity data acquisition module is used for monitoring real-time milk quantity data corresponding to each working state of the breast pump based on the real-time physiological information of the infant and the physiological information of the user;
and the deep learning model is established and the working mode adjusting module is used for establishing a deep learning model through the real-time milk quantity data, and adjusting the working mode of the breast pump through the equipment module carried by the breast pump based on the deep learning model.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the electric breast pump based mode adjustment method according to any one of claims 1 to 7 when executing the computer program.
10. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the electric breast pump based mode adjustment method according to any one of claims 1 to 7.
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| CN202310060408.7A CN116196497A (en) | 2023-01-16 | 2023-01-16 | Mode adjustment method, system, equipment and medium based on electric breast pump |
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| CN202310060408.7A CN116196497A (en) | 2023-01-16 | 2023-01-16 | Mode adjustment method, system, equipment and medium based on electric breast pump |
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| CN202310060408.7A Pending CN116196497A (en) | 2023-01-16 | 2023-01-16 | Mode adjustment method, system, equipment and medium based on electric breast pump |
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| Country | Link |
|---|---|
| CN (1) | CN116196497A (en) |
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2023
- 2023-01-16 CN CN202310060408.7A patent/CN116196497A/en active Pending
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