CN112786153B - Diet control method and system for old people - Google Patents
Diet control method and system for old people Download PDFInfo
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- CN112786153B CN112786153B CN202110013050.3A CN202110013050A CN112786153B CN 112786153 B CN112786153 B CN 112786153B CN 202110013050 A CN202110013050 A CN 202110013050A CN 112786153 B CN112786153 B CN 112786153B
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
Abstract
The invention discloses a diet control method and a system for old people, which are used for obtaining basic information of a first old person; obtaining a first food list of the first elderly, wherein the first food list is used as first input information; acquiring information of a first image through the camera device, processing the information of the first image, and taking the processed information of the first image as second input information; inputting the first input information and the second input information into a first training model to obtain a first output result of the first training model, wherein the output result comprises the digestion grade of the first old; according to the first output result, adjusting the first food list to obtain a second food list; applying the second food manifest to the first elderly. The technical problem that diet of the old cannot be accurately and conveniently analyzed and controlled according to actual conditions in the prior art is solved.
Description
Technical Field
The invention relates to the related field of diet control of old people, in particular to a diet control method and system for old people.
Background
With the increasing severity of aging, the elderly population is relatively increased, and with the increasing age, the physiological functions of heart, brain, and other organs of the elderly are reduced, metabolic dysfunction and low immunity are caused, and the elderly need to take sufficient nutrition and form good eating habits, which is the basic guarantee of body health.
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 the diet of the old cannot be accurately and conveniently analyzed and controlled according to the actual condition exists in the prior art.
Disclosure of Invention
The embodiment of the application provides a diet control method and system for the old, solves the technical problem that diet of the old cannot be accurately and conveniently analyzed and controlled according to actual conditions in the prior art, achieves the technical effects that intelligence can dynamically analyze and adjust diet according to physical conditions of the old, and further achieves convenient and accurate control of diet of the old.
In view of the above problems, the present application provides a diet control method and system for the elderly.
In a first aspect, an embodiment of the present application provides a diet control method for an elderly person, where the method is applied to a diet control system for an elderly person, the system includes a camera device, and the method includes: obtaining basic information of a first elderly person; obtaining a first food list of the first old people according to the basic information, and taking the first food list as first input information; obtaining information of a first image by the camera device, the information of the first image including excrement information of the first old person; acquiring a first processing instruction, processing the first image information through a server according to the first processing instruction, and taking the processed information of the first image as second input information; inputting the first input information and the second input information 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 the plurality of groups of training data comprises: the first input information, the second input information, and identification information identifying a digestion level of the first elderly person; obtaining a first output of the first training model, the output comprising a digestion level of the first elderly person; according to the first output result, adjusting the first food list to obtain a second food list; applying the second food manifest to the first elderly.
In another aspect, the present application further provides a diet control system for an elderly person, the system comprising: a first obtaining unit for obtaining basic information of a first elderly person; a second obtaining unit, configured to obtain a first food list of the first elderly person according to the basic information, and use the first food list as first input information; a third obtaining unit configured to obtain information of a first image including excrement information of the first elderly person by an imaging device; a fourth obtaining unit, configured to obtain a first processing instruction, process the first image information through the server according to the first processing instruction, and use information of the processed first image as second input information; a first input unit, configured to input the first input information and the second input information into a first training model, where the first training model is obtained by training multiple sets of training data, and each of the multiple sets of training data includes: the first input information, the second input information, and identification information identifying a digestion level of the first elderly person; a fifth obtaining unit for obtaining a first output result of the first training model, the output result comprising a digestion level of the first elderly; the first adjusting unit is used for adjusting the first food list according to the first output result to obtain a second food list; a first application unit to apply the second food manifest to the first elderly.
In a third aspect, the present invention provides a diet control system for elderly people, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method of the first aspect.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the first food list of the first old person is obtained according to the basic information of the first old person, the first food list is used as first input information, first image information is obtained through a camera device, the first image information is used as second input data, the second input information of the first input information is input into a first training model, more accurate digestion grade of the first old person is obtained according to the characteristic that self-correction adjustment is continuously carried out on the first training model, and then more accurate adjustment is carried out on the matching condition of the first old person and the first food list, so that the technical effect of accurately and conveniently controlling diet of the old person is 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.
Drawings
FIG. 1 is a schematic flow chart illustrating a method for controlling diet of an elderly person according to an embodiment of the present disclosure;
FIG. 2 is a schematic structural diagram of a diet control system for elderly people according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a first input unit 15, a fifth obtaining unit 16, a first adjusting unit 17, a first application unit 18, 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 a diet control method and system for the old, solves the technical problem that diet of the old cannot be accurately and conveniently controlled according to actual conditions in the prior art, achieves the technical effects that diet is dynamically adjusted according to physical conditions of the old, and accordingly diet of the old is convenient and accurate to control. 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
With the increasing severity of aging, the elderly population is relatively increased, and with the increasing age, the physiological functions of heart, brain, and other organs of the elderly are reduced, metabolic dysfunction and low immunity are caused, and the elderly need to take sufficient nutrition and form good eating habits, which is the basic guarantee of body health. However, the prior art has the technical problem that the diet of the old cannot be accurately and conveniently analyzed and controlled according to the actual situation.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides a diet control method for the old, which is applied to a diet control system for the old, the system comprises a camera device, and the method comprises the following steps: obtaining basic information of a first elderly person; obtaining a first food list of the first old person according to the basic information, and taking the first food list as first input information; obtaining information of a first image by the camera device, wherein the information of the first image comprises excrement information of the first old person; acquiring a first processing instruction, processing the first image information through a server according to the first processing instruction, and taking the processed information of the first image as second input information; inputting the first input information and the second input information 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 the plurality of groups of training data comprises: the first input information, the second input information, and identification information identifying a digestion level of the first elderly person; obtaining a first output of the first training model, the output comprising a digestion level of the first elderly; according to the first output result, adjusting the first food list to obtain a second food list; applying the second food manifest to the first elderly.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Practice ofExample one
As shown in fig. 1, an embodiment of the present application provides a diet control method for an elderly person, where the method is applied to a diet control system for an elderly person, the system includes a camera device, and the method includes:
step S100: obtaining basic information of a first elderly person;
specifically, the diet control system is a system for detecting and analyzing diet conditions of the elderly in real time, the camera device is a device capable of taking images, for example, the camera device may be a monitoring camera, the camera device at least includes a first camera and a second camera, the first elderly is the elderly using the diet control system, and basic information of the elderly is obtained under permission of the elderly, and the basic information includes information such as age, physical health conditions, physical examination results, and surgery conditions.
Step S200: obtaining a first food list of the first old people according to the basic information, and taking the first food list as first input information;
specifically, the first food list is a list of food lists at a first time, which may be breakfast time, lunch time, and dinner time, and the list of food at breakfast time, lunch time, and dinner time of the first elderly person is obtained and used as the first input information.
Step S300: obtaining information of a first image by the camera device, wherein the information of the first image comprises excrement information of the first old person;
specifically, the camera device is a camera with an imaging function, first image information is obtained through a first camera of the camera device, the first image is information of an image corresponding to the food list, for example, when the first food list is a dinner list, the image of the excrement of the first old person is acquired by acquiring the image of the excrement 3 hours after dinner of the first old person, and the image information of the excrement of the first old person is obtained.
Step S400: acquiring a first processing instruction, processing the first image information through a server according to the first processing instruction, and taking the processed information of the first image as second input information;
specifically, the first processing instruction is an instruction for performing image processing on an image, the first image obtained by the imaging device may have image problems including image format, image brightness contrast problem, image detail loss, image color imbalance and the like, the obtained first image is subjected to image processing to obtain processed image information, and the processed image information is used as the second input information.
Step S500: inputting the first input information and the second input information 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 the plurality of groups of training data comprises: the first input information, the second input information, and identification information identifying a digestion level of the first elderly person;
step S600: obtaining a first output of the first training model, the output comprising a digestion level of the first elderly person;
specifically, the first training model is a Neural network model in machine learning, and Neural Networks (NN) are complex Neural network systems formed by widely connecting a large number of simple processing units (called neurons), reflect many basic features of human brain functions, and are highly complex nonlinear dynamical learning systems. 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 the human brain system. Briefly, it is a mathematical model. And inputting the first input information and the second input information into a neural network model through training of a large amount of training data, and outputting the digestion grade comprising the first old people.
More specifically, the training process is essentially a supervised learning process, each group of supervised data includes the first input information, the second input information, and identification information identifying the digestion level of the first elderly, the first input information and the second input information are input into a neural network model, the neural network model performs continuous self-correction and adjustment according to the identification information identifying the digestion level of the first elderly, and the group of supervised learning is ended until the obtained output result is consistent with the identification information, and then the next group of data supervised learning is performed; and when the output information of the neural network model reaches the preset accuracy rate/reaches the convergence state, finishing the supervised learning process. Through the supervised learning of the neural network model, the neural network model can process the input information more accurately, so that the more accurate digestion grade of the first old person can be obtained, the digestion condition of the food can be accurately evaluated by the first old person, and a foundation is tamped for obtaining a more suitable and matched food list subsequently.
Step S700: according to the first output result, adjusting the first food list to obtain a second food list;
step S800: applying the second food manifest to the first elderly.
Specifically, a first output result of the first training model is obtained, the first output result includes the digestion condition of the first elderly on the food in the first food list, according to the digestion result, the food which is not digested well in the first food list is replaced or the intake amount is adjusted, according to the adjustment result, a second food list is obtained, and the second food list is sent to the first elderly to recommend the first elderly to use. The accurate and convenient control of the diet of the old is achieved, the food suitable for the old is recommended more accurately, and the healthy diet is guaranteed.
Further, said adjusting the first food list according to the first output result to obtain a second food list, in step S700 of this embodiment of the present application, further includes:
step S710: obtaining a first digestive granularity threshold value according to the basic information of the first old person;
step S720: judging whether a second image which does not meet the first digestion granularity threshold exists in the first image or not;
step S730: when the second image exists, obtaining image quantity ratio information of the second image;
step S740: obtaining a first adjusting instruction;
step S750: and according to the first adjusting instruction, adjusting the first food list through the second image, the image quantity ratio information and the first output result to obtain second food list information.
Specifically, the first digestive granularity threshold obtained according to the basic information of the first elderly is a granularity threshold of a digestive result of food in the first food list at the image acquisition time, which is obtained according to the physical condition information, the surgical information and the gastrointestinal function information of the first elderly, the threshold is a theoretical threshold of the maximum granularity of the first elderly after digestion in the first food list, the first image is analyzed by a processor, whether a second image exists in the first image is judged, the second image is an image with the granularity larger than the first digestive granularity threshold, when the second image exists, the quantity information of the second image is obtained, a first adjusting instruction is obtained, the components of the second image are analyzed according to the first adjusting instruction, one or more kinds of food information in the first food list corresponding to the second image is obtained, and whether the food corresponding to the second image is removed or not is judged according to the quantity of the second image.
Further, step S900 in the embodiment of the present application further includes:
step S910: obtaining information of a third image of the first elderly person through the camera device, the information of the third image including tooth information of the first elderly person;
step S920: obtaining first video information of the first old person through the camera device, wherein the first video information comprises chewing speed information of the first old person;
step S930: constructing a rectangular coordinate system by taking the tooth information as an abscissa and the chewing speed information as an ordinate, and obtaining a logistic regression line through the rectangular coordinate system based on a logistic regression model;
step S940: inputting information of the third image and first video information into the logistic regression model;
step S950: obtaining a second output result based on the logistic regression line, the second output result including a result of whether the tooth information matches a chewing speed;
step S960: when the second output result is a result that the tooth information is not matched with the chewing speed, obtaining a first early warning instruction;
step S970: and carrying out early warning treatment on the first old people according to the first early warning instruction.
Specifically, image information of teeth of the first old person is obtained through a second camera of the camera device, the tooth information includes information such as health conditions of the teeth, the number of the teeth, hardness and the like, namely third image information, first video information of the first old person in the eating process is obtained through the second camera of the camera device, chewing speed information of the first old person in the eating process is obtained according to the first video information, a rectangular coordinate system is constructed by taking the tooth information as an abscissa and the chewing speed information as an ordinate, a logistic regression line is obtained through the rectangular coordinate system based on a logistic regression model, one side of the logistic regression line represents a first result, the first result is a result that the tooth information and the chewing speed information are matched, the other side of the logistic regression line represents a second result, the second result is a result that the tooth information and the chewing speed information are not matched, matching conditions of the tooth information and the chewing speed of the first old person are judged through the logistic regression model, and whether the tooth information and the chewing speed of the first old person are matched or not is judged, and the early warning effect of the first old person is more accurate.
Further, the embodiment of the present application further includes:
step S971: obtaining eye disease information of the first old person according to the basic information;
step S972: obtaining a visibility range of the first elderly according to the eye disease information of the first elderly;
step S973: obtaining a predetermined sharpness threshold;
step S974: determining whether the visibility range satisfies the predetermined sharpness threshold;
step S975: and when the first reminding instruction is not satisfied, obtaining a first reminding instruction.
Specifically speaking, through first old person's basic information obtains first old person's eye information, eye information includes first old person's eye disease information, eyesight condition etc. according to first old person's eye disease condition, first old person's eyesight condition obtains first old person's visibility information, promptly first old person's actual eyesight condition obtains predetermined definition threshold value, the definition threshold value is according to can distinguish the definition threshold value that boils cooked food and formulate, judges whether first old person's eye eyesight condition can satisfy predetermined definition threshold value, works as the visibility scope does not satisfy when predetermined definition threshold value, obtains first warning instruction, according to first warning instruction reminds there is the food that hardness is unusual in the first old person's food.
Further, when the first prompting instruction is not satisfied, the step S975 in this embodiment of the present application further includes:
step S9751: obtaining the category information of the list food according to the second food list;
step S9752: obtaining a first processing result of different kinds of list food, and obtaining first hardness information according to the first processing result;
step S9753: judging whether the tooth information and the first hardness information have a first matching degree;
step S9754: and when the first matching degree is not obtained, a first early warning instruction is obtained, and early warning is carried out on the first old people according to the first early warning instruction.
Specifically, according to the modified food list, namely a second food list, obtaining food information in the second food list, wherein the food information comprises storage time of the food, storage environment information, information such as different cooking time, cooking temperature and cooking method of different foods in the food list, according to the processing condition, obtaining first hardness information, wherein the first hardness information is estimated hardness information of the food according to a processing result of the food and the food, matching is carried out according to the first hardness information and the tooth information of the first old person, whether the tooth information of the first old person can eat the food with the first hardness at a normal chewing speed is judged, namely whether the tooth information of the first old person has the first matching degree or not is judged, and when the tooth information of the first old person is not available, a first early warning instruction is obtained, and when the first old person is about to eat the food with the first hardness, the first old person is warned to pay attention to the chewing speed according to the first early warning instruction.
Further, the diet control system further includes a humidity sensor, the obtaining a first processing result of the different kinds of food list, and obtaining first hardness information according to the first processing result, in step S9752, the method further includes:
step S97521: obtaining first position information of food of the second food list, wherein the first position is a home placement position of the food in the first old person;
step S97522: obtaining first humidity information of the first location by the humidity sensor;
step S97523: obtaining first ventilation information of the first position;
step S97524: and adjusting the first hardness information according to the first humidity information and the first ventilation volume information.
Specifically, according to the second food list, the placing position information of the food in the second food list in the first old people family is obtained, according to the placing position information, the first humidity information of the first position is obtained through a humidity sensor, the humidity sensor is prepared through a humidity sensitive element, a device capable of obtaining air humidity through measuring the change of the resistivity and the resistance value of a water vapor influence element in the air is used for obtaining the first humidity information of the first position, the ventilation condition of the first position is obtained, according to the first humidity and the ventilation condition, the packaging, sealing and self attributes of the food are combined, the first adjusting information is obtained, and the first hardness information is adjusted according to the first adjusting information. And then more accurate pre-estimation results of the hardness of the cooked food can be obtained.
Further, the embodiment of the present application further includes:
step S1010: obtaining first motion amount information of the first elderly through a motion monitoring device worn by the first elderly;
step S1020: obtaining an energy intake pre-estimated value of the first old person according to the first motion amount information and the basic information;
step S1030: adjusting the second food list according to the energy intake estimated value to obtain a third food list;
step S1040: applying the third food manifest to the first elderly.
Specifically speaking, motion monitoring facilities can be motion monitoring's equipment such as motion monitor, motion bracelet, through motion monitoring facilities obtains first old person's amount of exercise information, the amount of exercise is in the statistics of the amount of exercise of old person's after eating to before eating next time, the amount of exercise includes exercise intensity, motion time, and then is right the calorie of first old person's consumption predicts, obtains energy consumption estimation result, according to energy consumption estimation result obtains the energy intake predictive value of first old person's next eating, according to the energy intake estimation value adjusts the second food manifest, obtains the third food manifest, will the third food manifest is applied to first old person.
In summary, the diet control method and system for the elderly provided by the embodiments of the present application have the following technical effects:
1. the first food list of the first old person is obtained according to the basic information of the first old person, the first food list is used as first input information, first image information is obtained through a camera device, the first image information is used as second input data, the second input information of the first input information is input into a first training model, more accurate digestion grade of the first old person is obtained according to the characteristic that self-correction adjustment is continuously carried out on the first training model, and then more accurate adjustment is carried out on the matching condition of the first old person and the first food list, so that the technical effect of accurately and conveniently controlling diet of the old person is achieved.
2. Due to the fact that supervised learning of the neural network model is adopted, the neural network model can process the input information more accurately, and then the more accurate digestion grade of the first old person is obtained, so that the digestion condition of the food is accurately evaluated by the first old person, and a foundation is laid for obtaining a more suitable and matched food list in the follow-up process.
3. Due to the fact that the mode that the matching condition of the tooth information and the chewing speed of the first old person is judged through the logistic regression model is adopted, the judgment on whether the tooth information and the chewing speed of the first old person are matched is more accurate, and the technical effect of accurately early warning the eating of the first old person is achieved.
Example two
Based on the same inventive concept as the old people's diet control method in the previous embodiment, the present invention also provides a diet control system for old people, as shown in fig. 2, the system includes:
a first obtaining unit 11, the first obtaining unit 11 being used for obtaining basic information of a first elderly person;
a second obtaining unit 12, wherein the second obtaining unit 12 is configured to obtain a first food list of the first elderly person according to the basic information, and the first food list is used as first input information;
a third obtaining unit 13, the third obtaining unit 13 being configured to obtain information of a first image by an imaging device, the information of the first image including excrement information of the first elderly;
a fourth obtaining unit 14, where the fourth obtaining unit 14 is configured to obtain a first processing instruction, process the first image information through the server according to the first processing instruction, and use information of the processed first image as second input information;
a first input unit 15, where the first input unit 15 is configured to input the first input information and the second input information into a first training model, the first training model is obtained through training of multiple sets of training data, and each of the multiple sets of training data includes: the first input information, the second input information, and identification information identifying a digestion level of the first elderly person;
a fifth obtaining unit 16, the fifth obtaining unit 16 being configured to obtain a first output of the first training model, the output comprising a digestion level of the first elderly person;
a first adjusting unit 17, wherein the first adjusting unit 17 is configured to adjust the first food list according to the first output result to obtain a second food list;
a first application unit 18, the first application unit 18 being for applying the second food manifest to the first elderly person.
Further, the system further comprises:
a sixth obtaining unit configured to obtain a first digestion granularity threshold according to the basic information of the first elderly person;
a first judging unit configured to judge whether there is a second image that does not satisfy the first digestion granularity threshold in the first image;
a seventh obtaining unit configured to obtain image number information of the second image when present;
an eighth obtaining unit, configured to obtain a first adjustment instruction;
a ninth obtaining unit, configured to adjust the first food list according to the first adjustment instruction and through the second image, the image quantity information, and the first output result, and obtain second food list information.
Further, the system further comprises:
a tenth obtaining unit configured to obtain, by the image pickup device, information of a third image of the first elderly person, the information of the third image including dental information of the first elderly person;
an eleventh obtaining unit configured to obtain first video information of the first elderly person by the image pickup device, the first video information including mastication speed information of the first elderly person;
a twelfth obtaining unit configured to construct a rectangular coordinate system using the tooth information as an abscissa and the chewing speed information as an ordinate, and obtain a logistic regression line through the rectangular coordinate system based on a logistic regression model;
a second input unit for inputting information of the third image and first video information into the logistic regression model;
a thirteenth obtaining unit configured to obtain a second output result including a result of whether the tooth information matches a chewing speed, based on the logistic regression line;
a fourteenth obtaining unit, configured to obtain a first warning instruction when the second output result is a result that the tooth information does not match the chewing speed;
and the first processing unit is used for carrying out early warning processing on the first old people according to the first early warning instruction.
Further, the system further comprises:
a fifteenth obtaining unit configured to obtain eye disease information of the first elderly person from the basic information;
a sixteenth obtaining unit configured to obtain a visibility range of the first elderly person from eye disease information of the first elderly person;
a seventeenth obtaining unit configured to obtain a predetermined sharpness threshold;
a second determination unit configured to determine whether the visibility range satisfies the predetermined sharpness threshold;
an eighteenth obtaining unit, configured to, when not satisfied, obtain the first alert instruction.
Further, the system further comprises:
a nineteenth obtaining unit, configured to obtain category information of list food according to the second food list;
a twentieth obtaining unit configured to obtain a first processing result of the different kinds of the list food, and obtain first hardness information according to the first processing result;
a third determination unit configured to determine whether the tooth information and the first hardness information have a first degree of matching;
a twenty-first obtaining unit, configured to obtain a first early warning instruction when the first matching degree is not met, and perform early warning on the first old person according to the first early warning instruction.
Further, the system further comprises:
a twenty-second obtaining unit configured to obtain first motion amount information of the first elderly through a motion monitoring device worn by the first elderly;
a twenty-third obtaining unit configured to obtain an energy intake estimate value of the first elderly person based on the first motion amount information and the basic information;
a twenty-fourth obtaining unit, configured to adjust the second food list according to the energy intake estimate to obtain a third food list;
a second application unit for applying the third food manifest to the first elderly.
Further, the system further comprises:
a twenty-fifth obtaining unit, configured to obtain first location information of food in the second food list, where the first location is a home location of the food in the first elderly;
a twenty-sixth obtaining unit configured to obtain first humidity information of the first location by the humidity sensor;
a twenty-seventh obtaining unit configured to obtain first ventilation amount information of the first location;
and the second adjusting unit is used for adjusting the first hardness information according to the first humidity information and the first ventilation volume information.
Various modifications and specific examples of the diet control method for the elderly person in the first embodiment of fig. 1 are also applicable to the diet control system for the elderly person in this embodiment, and a person skilled in the art can clearly know the implementation method of the diet control system for the elderly person in this embodiment through the foregoing detailed description of the diet control method for the elderly person, so the detailed description is omitted here for the sake of brevity.
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 a diet control method for an elderly person as in the previous embodiments, the present invention further provides a diet control system for an elderly person, having a computer program stored thereon, which when executed by a processor, implements the steps of any one of the foregoing diet control methods for an elderly person.
Wherein 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 systems over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
The embodiment of the invention provides a diet control method for old people, which is applied to a diet control system for old people, wherein the system comprises a camera device, and the method comprises the following steps: obtaining basic information of a first elderly person; obtaining a first food list of the first old person according to the basic information, and taking the first food list as first input information; obtaining information of a first image by the camera device, wherein the information of the first image comprises excrement information of the first old person; acquiring a first processing instruction, processing the first image information through a server according to the first processing instruction, and taking the processed information of the first image as second input information; inputting the first input information and the second input information 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 the plurality of groups of training data comprises: the first input information, the second input information, and identification information identifying a digestion level of the first elderly person; obtaining a first output of the first training model, the output comprising a digestion level of the first elderly person; according to the first output result, adjusting the first food list to obtain a second food list; applying the second food manifest to the first elderly. The technical problem that in the prior art, diet of old people cannot be accurately and conveniently analyzed and controlled according to actual conditions is solved, the technical effects that intelligence is achieved, diet is dynamically analyzed and adjusted according to physical conditions of the old people, and then diet of the old people is convenient and accurate to control are achieved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. A diet control method for old people, wherein the method is applied to a diet control system for old people, the system comprises a camera device, and the method comprises the following steps:
obtaining basic information of a first elderly person;
obtaining a first food list of the first old person according to the basic information, and taking the first food list as first input information;
obtaining information of a first image by the camera device, the information of the first image including excrement information of the first old person;
acquiring a first processing instruction, processing the first image information through a server according to the first processing instruction, and taking the processed information of the first image as second input information;
inputting the first input information and the second input information 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 the plurality of groups of training data comprises: the first input information, the second input information, and identification information identifying a digestion level of the first elderly person;
obtaining a first output of the first training model, the output comprising a digestion level of the first elderly;
according to the first output result, adjusting the first food list to obtain a second food list;
applying the second food manifest to the first elderly;
obtaining a first digestive granularity threshold value according to the basic information of the first old person;
judging whether a second image which does not meet the first digestion granularity threshold exists in the first image or not;
when present, obtaining image quantity information of the second image;
obtaining a first adjusting instruction;
and according to the first adjusting instruction, adjusting the first food list through the second image, the image quantity information and the first output result to obtain second food list information.
2. The method of claim 1, wherein the method comprises:
obtaining information of a third image of the first elderly person through the camera device, the information of the third image including tooth information of the first elderly person;
obtaining first video information of the first old person through the camera device, wherein the first video information comprises chewing speed information of the first old person;
constructing a rectangular coordinate system by taking the tooth information as an abscissa and the chewing speed information as an ordinate, and obtaining a logistic regression line through the rectangular coordinate system based on a logistic regression model;
inputting information of the third image and first video information into the logistic regression model;
obtaining a second output result based on the logistic regression line, the second output result including a result of whether the tooth information matches the chewing speed;
when the second output result is a result that the tooth information is not matched with the chewing speed, obtaining a first early warning instruction;
and carrying out early warning treatment on the first old people according to the first early warning instruction.
3. The method of claim 2, wherein the method comprises:
obtaining eye disease information of the first old people according to the basic information; obtaining a visibility range of the first elderly according to the eye disease information of the first elderly;
obtaining a predetermined sharpness threshold;
determining whether the visibility range satisfies the predetermined sharpness threshold;
and when the first reminding instruction is not satisfied, obtaining a first reminding instruction.
4. The method of claim 3, wherein the obtaining a first alert instruction when not satisfied comprises:
obtaining the category information of the list food according to the second food list;
obtaining a first processing result of different kinds of list food, and obtaining first hardness information according to the first processing result;
judging whether the tooth information and the first hardness information have a first matching degree;
and when the first matching degree is not obtained, a first early warning instruction is obtained, and early warning is carried out on the first old people according to the first early warning instruction.
5. The method of claim 1, wherein the method further comprises:
obtaining first amount of motion information of the first elderly through a motion monitoring device worn by the first elderly;
obtaining an energy intake pre-estimated value of the first old person according to the first motion amount information and the basic information;
adjusting the second food list according to the energy intake estimated value to obtain a third food list;
applying the third food manifest to the first elderly.
6. The method of claim 4, wherein the diet control system further comprises a moisture sensor, the obtaining a first treatment result of the different categories of the food inventory, obtaining a first firmness information based on the first treatment result, the method further comprising:
obtaining first position information of food of the second food list, wherein the first position is a home placement position of the food in the first old person;
obtaining first humidity information of the first location by the humidity sensor;
obtaining first ventilation information of the first position;
and adjusting the first hardness information according to the first humidity information and the first ventilation volume information.
7. A diet control system for an elderly person, wherein the system comprises:
a first obtaining unit for obtaining basic information of a first elderly person;
a second obtaining unit, configured to obtain a first food list of the first elderly person according to the basic information, and use the first food list as first input information;
a third obtaining unit configured to obtain information of a first image including excrement information of the first elderly person by an imaging device;
a fourth obtaining unit, configured to obtain a first processing instruction, process the first image information through the server according to the first processing instruction, and use information of the processed first image as second input information;
a first input unit, configured to input the first input information and the second input information into a first training model, where the first training model is obtained by training multiple sets of training data, and each of the multiple sets of training data includes:
the first input information, the second input information, and identification information identifying a digestion level of the first elderly person;
a fifth obtaining unit for obtaining a first output result of the first training model, the output result comprising a digestion level of the first elderly;
the first adjusting unit is used for adjusting the first food list according to the first output result to obtain a second food list;
a first application unit to apply the second food manifest to the first elderly.
8. A diet control system for elderly people comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method according to any of claims 1-6.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110298836A (en) * | 2019-07-05 | 2019-10-01 | 张文华 | The methods, devices and systems of INTESTINAL CLEANSING quality are judged by artificial intelligence |
| CN111798943A (en) * | 2020-06-30 | 2020-10-20 | 南方医科大学南方医院 | Method, system, device and storage medium for recording output and input quantities |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109390056A (en) * | 2018-11-05 | 2019-02-26 | 平安科技（深圳）有限公司 | Health forecast method, apparatus, terminal device and computer readable storage medium |
| CN111899861A (en) * | 2020-08-17 | 2020-11-06 | 江苏达实久信数字医疗科技有限公司 | Intelligent nursing method and system for intensive care unit |
| CN112001338A (en) * | 2020-08-27 | 2020-11-27 | 南通市第二人民医院 | Information processing method and system for improving health level of children |
| CN112086166B (en) * | 2020-09-18 | 2022-11-15 | 常州市中医医院 | Orthopedic patient skin traction nursing method and system |
| CN112133405A (en) * | 2020-09-29 | 2020-12-25 | 苏州立楚信息技术有限公司 | Method and system for assessing children nutrition state of smart community |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110298836A (en) * | 2019-07-05 | 2019-10-01 | 张文华 | The methods, devices and systems of INTESTINAL CLEANSING quality are judged by artificial intelligence |
| CN111798943A (en) * | 2020-06-30 | 2020-10-20 | 南方医科大学南方医院 | Method, system, device and storage medium for recording output and input quantities |
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