CN112037879A - Personal intelligent diet monitoring module and method - Google Patents
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- 235000005911 diet Nutrition 0.000 title claims abstract description 40
- 230000037213 diet Effects 0.000 title claims abstract description 36
- 238000012544 monitoring process Methods 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 title claims abstract description 17
- 230000015654 memory Effects 0.000 claims abstract description 49
- 235000015097 nutrients Nutrition 0.000 claims abstract description 44
- 235000016709 nutrition Nutrition 0.000 claims abstract description 15
- 230000035764 nutrition Effects 0.000 claims abstract description 14
- 230000006870 function Effects 0.000 claims description 10
- 239000003086 colorant Substances 0.000 claims description 6
- 235000012054 meals Nutrition 0.000 description 23
- 235000013305 food Nutrition 0.000 description 19
- 230000036541 health Effects 0.000 description 8
- 230000005540 biological transmission Effects 0.000 description 5
- 235000013311 vegetables Nutrition 0.000 description 5
- 230000007423 decrease Effects 0.000 description 4
- 230000000378 dietary effect Effects 0.000 description 4
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- 230000000386 athletic effect Effects 0.000 description 2
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- 229920002678 cellulose Polymers 0.000 description 2
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- 238000004891 communication Methods 0.000 description 2
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- 241000287828 Gallus gallus Species 0.000 description 1
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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
- G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
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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
- G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
-
- 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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- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Nutrition Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biophysics (AREA)
- Physical Education & Sports Medicine (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention relates to a personal intelligent diet monitoring module and a method thereof, comprising the steps of obtaining data from a first memory; acquiring a user medical record from an auxiliary memory; analyzing the nutrients of the user when eating in coordination with the user's medical history; the obtained nutrition amount of the current day is summarized by matching with the medical history of the user to obtain a nutrition suggestion analysis report of the second day.
Description
Technical Field
The invention relates to a personal intelligent diet monitoring module and a method thereof, in particular to a personal intelligent diet monitoring module which can provide a balanced and healthy diet content aiming at individual exercise difference.
Background
From the data in the following Table 1, it can be concluded that the overall constitution of the teenager will be in a downward trend due to the abnormality of three meals; as can be seen from table 1 below, there are only two-year young years with a fixed three-meal habit; while those who are not normal for three meals are up to eight-fold.
TABLE 1 factors affecting the health of college students in the New era
The data source is a survey of the diet conditions of college students in 6 colleges and universities in Gansu province, and the survey shows that the students with good habits of three fixed meals only account for 22%, and the rest of most students do not pay attention to the diet conditions of the students, especially the nutrition of the three meals. The three major keys of human health lie in regular work and rest, reasonable diet structure and proper amount of exercise, so the diet condition is also one of the important factors causing the bad physical condition of students in schools.
On the other hand, as mentioned in the report of "the history of monitoring and developing the biological quality of Chinese schools" from the institute of sports science, national institute of sports institute 2017, the constitution of college students in China still tends to decline, but the rate of decline tends to slow down. At the same time, the body morphology is also changing, and especially the rate of obesity continues to rise, increasing 2% to 3% every 5 years. In addition, the national physical monitoring report in 2015 shows that the decline of the physical state of students from 7 to 19 years is the most serious, so we must pay attention to the decline trend.
Many wearable exercise devices (such as a millet bracelet) only record the exercise duration and type of the user singly, and provide the recorded data to the user for reference whenever the user needs; that is, current athletic wearable devices only passively provide some referential data to the user and do not have any directly constructive reference to the user's own health. Some wearable exercise devices also record physical and physiological activity data, and calculate calories in food by passively inputting daily dietary status by the user, helping to remind the consumer not to increase the weight too quickly, and maintain a healthier weight. The wearable sports device is matched with a food database built in corresponding software, so that after a consumer inputs food materials, the software can calculate nutrients, fat, protein and the like, but the requirement of the user to actively input the content and the type of various foods often causes inconvenience to the user, and the accuracy is not high because the user actively inputs various data, so that the user is often not in front.
TABLE 2 importance of people to healthy life
As can be seen from the results of the online survey data in table 2, the consumption concept of the public gradually upgrades with the improvement of the living standard, and the public focuses on the nutrition of the diet and pursues a healthier dietary structure, and the individual needs of people are reflected by the different attention to various nutrients.
On the other hand, the demand for take-out platforms such as hungry and American groups to select salad and healthy meals has increased year by year, and Chinese consumers have become more concerned about the food materials they eat. Recent studies by Mintel show that food labels and signs such as organic certification and "all natural" are more attractive to Chinese consumers in terms of food material selection. 55% of Chinese men are concerned about additives/preservatives, 49% consider transgenic components as important factors to consider in food selection, and 43% of visited women are concerned about fat content and 41% about sugar, so that eating nutrition and health is a trend that consumers pay more attention year by year.
From the above data, the correlation between diet and health is more and more important for the people in China. However, in the current intelligent era, if all managers who still rely on their own idea to do their own health do not seem to be in accordance with the two words of [ intelligent ], therefore, if a set of modules can be provided to "actively" provide a recommended meal content provided by an authenticated specialist to balance the nutrients required by the user or the lost nutrients according to the difference of the meal content of each meal, the difference of the amount of the lessons, the difference of the types of sports and the intensity of sports, etc. of the user, the user is believed to manage his own health more effectively.
Disclosure of Invention
The invention aims to solve the technical problem that a complete and active diet monitoring module is not provided in the prior art; the method can actively provide a piece of suggestive content for the user to refer to according to the daily life practice of the user, even the sports type, the intensity and the color of the dish selected by three meals, so as to achieve the aim of maintaining the health of the user.
In order to achieve the technical effects, the invention discloses a personal intelligent diet monitoring module, which comprises:
a calculator;
a plurality of sensors connected with the calculator and having transmitting/transmitting function; and
a plurality of memories.
The calculator provided by the invention can be a desktop computer, a smart phone, a Personal Data Assistant (PDA), a tablet computer and the like.
Moreover, the sensor provided by the invention has the functions of recording, sensing and sending, and is a sensor capable of having Radio Frequency Identification (RFID) function, an NFC (Near Field Communication) smart phone, which can sense the physiological index (including important data such as heartbeat, blood pressure, respiration frequency and the like) and the pace number of a user; meanwhile, an auxiliary memory is also arranged in the sensor to store the personal electronic medical record of the user.
The memory included in the present invention includes a first memory in which the colors of dishes within a predetermined period and the nutrients included in each color of dishes are described: including calories and various vitamins and cellulose content; an auxiliary memory, which is selectively disposed in the sensor, can be independent of the sensor, and records the type, intensity and duration of the user's exercise.
The invention also discloses a personal intelligent diet monitoring method, which comprises the following steps:
acquiring data from a first memory;
acquiring a user medical record from an auxiliary memory;
analyzing the nutrients of the user when eating in coordination with the user's medical history;
and (4) combining with the medical history of the user to summarize the nutrient acquisition amount on the current day so as to obtain a nutrient recommendation analysis report on the second day.
The method for monitoring the personal intelligent diet further comprises the step of reading the exercise data of the user from the auxiliary memory before analyzing the nutrition of the user when eating.
The method for monitoring the personal intelligent diet further comprises the step of obtaining the nutrient acquisition amount of the current meal by combining with the analysis of the nutrients after reading the data of the user.
The method for monitoring the personal intelligent diet further comprises the step of summarizing the nutrition acquisition amount on the day and the exercise amount on the day so as to obtain a nutrition suggestion and an exercise suggestion analysis report on the second day.
Drawings
FIG. 1 is a schematic diagram of an exemplary implementation of the personal intelligent diet monitoring module of the present invention.
Fig. 2 is a description mode of nutrition contained in each color of dish when the personal intelligent diet monitoring module is implemented.
Fig. 3 is a flowchart of a first embodiment of the method for monitoring personal intelligent diet of the present invention.
Fig. 4 is a flowchart of a second embodiment of the method for monitoring personal intelligent diet of the present invention.
Fig. 5 is a flowchart of a third embodiment of the method for monitoring the personal intelligent diet of the present invention.
Detailed Description
The invention is further described with reference to the following figures and specific examples.
As shown in fig. 1 to fig. 2, the personal intelligent diet monitoring module of the present invention is implemented by a professional with notary ability to analyze the color of the dish produced by a meal unit in a predetermined time (for example, a month) according to the heat and various nutrients contained therein; then numbering the various vegetable colors; such as 01 for ants, 02 for white-cut chickens, etc., to form a dish card 10 (as shown in fig. 2) and stored in the first memory 20 shown in fig. 1, and the actually prepared dishes are displayed in the display case for selection by people as required at the day. The analysis of the nutrients mainly comprises the steps of classifying meat foods and vegetable foods according to two categories, and then analyzing the percentages of vitamins contained in various foods; of course, such analysis also includes analysis of calories (calories) therein.
After the card 10 is made, the card 10 is also stored in the first memory 20 in the form of data. The first memory 20 may exist alone, but may also exist in the cloud 30 of a platform.
When a user takes a certain color of dish stored in the display cabinet, the user needs to hold a Radio Frequency Identification (RFID) card or an NFC (Near Field Communication) smart phone 40 with transmission and induction functions to automatically induce corresponding to a sensor of the selected color of dish arranged in the display cabinet, or a service person directly inputs the number of the selected color of dish into a terminal or a server in a manual way; no matter the dish color number selected by the user is manually operated or the user utilizes a sensor to sense, the number corresponding to the dish color, the corresponding heat and the corresponding nutrients can automatically generate a report in the terminal or the server; after a series of programs for selecting the colors of dishes, when a user wants to pay, the user uses the Radio Frequency Identification (RFID) card 40 with the transmission and induction functions to pay for the payment, because the radio frequency identification card or the NFC smart phone 40 is internally provided with the auxiliary memory 41 and the electronic medical record data of the user is recorded in the auxiliary memory 41, when the user swipes the card through the radio frequency identification card 40 to pay, the electronic medical record in the auxiliary memory 41 is in interactive linkage with the report generated in the terminal machine; that is, for example, the user's medical record shows that the user is likely to have cramps, and if the nutrients contained in the color of the dish selected by the user are not enough to form enough nutrients to alleviate or even remove the problem of cramping, the report generated by the terminal shows that the user should supplement the nutrients in the aspect at the next meal; at the same time, nutrients contained in the various selected colors are also generated in the report. Moreover, the electronic medical record can simply describe the nutrient deficiency of the user, and can also be a complete piece of medical record data; regardless of the format of the medical record, there is finally a summary note of the user's lack of nutrients or the resolution of the user's condition for the terminal to interpret.
As mentioned above, when the user uses a Radio Frequency Identification (RFID) card or an NFC smart phone 40 with transmission and sensing functions to pay for payment, the corresponding sensor is a POS (point of sale) device 50, and the POS device 50 can be connected to the cloud 30, and similarly, the cloud 30 can also be connected to the first memory 20; therefore, the data in the dish card 10 may exist in the cloud 30 in addition to the first memory 20, and thus, after the electronic medical record data of the user existing in the auxiliary memory 41 and the dish color nutrient data selected by the user are integrated, a nutrient analysis suggestion is formed to exist in the first memory 20 and the cloud 30; in this way, the cloud 30 may periodically (or aperiodically) present a long-term nutritional analysis tracking report for reference. Of course, in order to obtain the nutrient analysis suggestion, or even the long-term nutrient analysis tracking report is more complete and comprehensive, the reference exercise data can be re-generated before the nutrient analysis suggestion, or even the long-term nutrient analysis tracking report begins to be evaluated. The athletic data may be obtained by the wearable device 60 (e.g., a bracelet or the like).
When the motion data is added for analysis, the above-mentioned overall analysis flow is changed to that when the user holds a Radio Frequency Identification (RFID) card or an NFC smart phone 40 with transmission and induction functions to pay for the payment, since the total nutrients of the vegetable colors selected from the vegetable card 10 are automatically added by the first memory 20 when each vegetable color is selected, and when a wireless Radio Frequency Identification (RFID) card 40 is used to sense the swipe of the card by the POS machine 50, the exercise data (e.g., type, intensity, duration, etc.) recorded by the wearable device 60 may also be transferred to the first memory 20 in a manner known in the art (e.g., bluetooth), and as nutrients are added, considering the nutrition and heat lost by the user due to exercise, and modifying the nutrient analysis suggestion; since the nutrient analysis recommendations are considered by the exercise data when the recommendations are made, the follow-up nutrient analysis tracking report is also different from the tracking report when no exercise data is considered.
Please refer to the flow chart of the first embodiment shown in fig. 3. It can be seen that at the beginning of the first meal of a day, the user selects the individually favorite foods from the food display cabinet, and at the same time, the selected foods can be inputted into the user's identification card 40 by the display cabinet attendant according to the code recorded on the menu card 10, and the code is synchronously transmitted to the first memory 20. It should be noted that the food code may be input into the first memory 20 by auto-scanning (e.g., the POS device 50). When the user finishes the food selecting action and prepares to settle the payment, the user settles the payment by using a Radio Frequency Identification (RFID) card 40 having a transmitting and sensing function. At the same time when the user's RFID card or NFC smart phone 40 senses the POS machine 50, the electronic medical record data stored in the auxiliary memory 41 of the RFID card or NFC smart phone 40 is automatically transmitted to the first memory 20, and is compared with the nutrients of various foods selected by the user; therefore, when the nutrient analysis report of the food selected by the meal shows how much calories, cellulose and nutrients the user has consumed for the meal. In addition to the analysis report, the corresponding nutrient analysis is also performed on various types of existing or possibly-occurring diseases in the electronic medical record of the user, for the food absopting, short or short, the demand and the like, so that the analysis report of the current meal is obtained from the first memory 20 and/or the cloud 30. When a user eats along the flow from breakfast, the analysis report of the meal can be obtained, and similarly, corresponding reports are available for lunch and dinner; therefore, when the user has consumed three meals or has not consumed a meal after a predetermined time interval, a meal analysis report of the current day is obtained from the first memory 20 and/or the cloud 30, and a nutrient analysis suggestion is provided.
Referring to fig. 4 again, it can be seen that when the user adds the motion data for analysis, the above-mentioned overall analysis process is changed to that when the user holds a Radio Frequency Identification (RFID) card or an NFC smartphone 40 with transmission and sensing functions to pay for payment, since the total nutrients of the dish color selected from the dish card 10 are automatically added by the first memory 20 or the cloud 30 when each dish color is selected, and when the POS machine 50 is sensed by swiping the card through the Radio Frequency Identification (RFID) card or the NFC smartphone 40, the motion data (such as the type, intensity, and length of time of the motion) recorded by the wearable device 60 is also transmitted to the first memory 20 or the cloud 30 in a currently known feasible manner (such as bluetooth), and as the nutrients are added, considering the nutrition and heat lost by the user due to exercise, and modifying the nutrient analysis suggestion accordingly; since the nutrient analysis recommendations are considered with the motion data already at the time of making the recommendations, the follow-up nutrient analysis tracking report is also different from the tracking report without the motion data. When a user takes a meal according to the flow from breakfast, an analysis report of the variation factor of the motion when the meal is added can be obtained, and similarly, corresponding reports can be obtained for lunch and dinner.
Please refer to fig. 5, which mainly takes the exercise data into account and further finds the meal analysis report, the day analysis report, and the final nutrition analysis suggestion and exercise analysis suggestion. The only difference between the process shown in fig. 5 and the process shown in fig. 3 is whether the exercise data is taken into account, and finally a nutrient analysis proposal and an exercise analysis proposal are respectively obtained according to the dietary options, the physical health status and the exercise status of the user, so that the user can refer to various considerations of the dietary status and the intensity, the kind and the time length of the exercise on the second day.
Based on the above description, it can be seen that the purpose of the embodiments is to provide a balanced and healthy diet and/or exercise analysis proposal for individual differences in study, diet habits and preferences, so as to make people in China healthier.
While the present invention has been described in detail and with reference to the embodiments thereof as illustrated in the accompanying drawings, it will be apparent to one skilled in the art that various changes and modifications can be made therein. Therefore, certain details of the embodiments are not to be interpreted as limiting, and the scope of the invention is to be determined by the appended claims.
Claims (13)
1. A personal intelligent diet monitoring module, characterized by, included:
the plurality of memories at least comprise a first memory and an auxiliary memory, wherein the first memory records the color of the dish and the nutrients contained in each color of the dish within a certain time, and the auxiliary memory records the personal data of the user;
a calculator, linked to the memory, for receiving data from the first memory and/or the auxiliary memory or for transmitting data to the first memory and/or the auxiliary memory; and
at least one sensor linked with the calculator and having recording, sensing, sending/transmitting functions to transmit the sensed data to the calculator.
2. The personal intelligent diet monitoring module according to claim 1, wherein said auxiliary memory is selectively disposed within said at least one sensor.
3. The personal intelligent diet monitoring module according to claim 1 or 2, wherein the at least one sensor comprises a rfid sensor, a NFC smart phone capable of sensing the physiological index and the number of steps of the user.
4. The personal intelligent diet monitoring module of claim 1, wherein said calculator comprises a desktop computer, a smart phone, a personal data assistant or a tablet computer.
5. The personal intelligent diet monitoring module according to claim 3, wherein the personal data in the auxiliary memory is an electronic medical record of the individual.
6. The personal intelligent diet monitoring module according to claim 4, wherein the first memory is contained in a computer or a cloud.
7. A personal intelligent diet monitoring method is characterized by comprising the following steps:
the calculator acquires data selected from the colors in a certain time and nutrients contained in each color from a first memory;
the calculator acquires an electronic medical record of a person from the auxiliary memory;
analyzing the nutrients of the user when eating aiming at the electronic medical record of the individual;
the obtained nutrition amount of the current day is summarized by matching with the medical history of the user to obtain a nutrition suggestion analysis report of the second day.
8. The method of claim 7, wherein the computer first memory comprises a desktop computer, a smart phone, a personal data assistant, or a tablet computer.
9. The personal intelligent diet monitoring module according to claim 3, wherein the personal data in the auxiliary memory is an electronic medical record of the individual.
10. The personal intelligent diet monitoring module according to claim 4, wherein the first memory is contained in a computer or a cloud.
11. The personal intelligent diet monitoring module according to claim 7 or 8, wherein the at least one sensor comprises a rfid sensor, a NFC smart phone that can sense the physiological index and the number of steps of the user.
12. The personal intelligent diet monitoring module according to claim 10, further comprising obtaining the exercise data of the person from the auxiliary memory.
13. The personal intelligent diet monitoring module of claim 12, further comprising deriving a second day exercise advice analysis report since the exercise data was obtained.
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