KR20210028765A - System for providing health care information based on microbiome and method thereof - Google Patents

Abstract

The present invention relates to a microbiome-based health information providing system and a method thereof, capable of predicting and preventing diseases. The microbiome-based health information providing method according to an embodiment of the present invention includes the following steps: collecting life pattern information on eating habits, exercise, and sleep; analyzing intestinal microbes of a user through a fecal sample collection kit in which the collected feces of the user is inserted; and recommending eating habits, exercise, and sleep information according to the correlation between the intestinal microbes and the eating habits, the amount of exercise and the sleep based on analysis results.

Description

System for providing health care information based on microbiome and method thereof

The present invention relates to a microbiome-based health information providing system and method thereof.

The population of microorganisms living in various places in the human body is called an indigenous microbiota, and their entire genetic information is called a microbiome. Microbiome is being studied very actively as it has recently been discovered that it is correlated with various life phenomena or diseases in the human body.

Although such microbiome is mainly focused on research related to food, since it is affected by overall lifestyle patterns such as sleep or exercise, various analyzes and suggestions for improvement based on this are required.

KR 2019-0025180 A

In order to solve the problems of the prior art as described above, an embodiment of the present invention is to promote health by analyzing big data such as intestinal microbial analysis data, exercise amount, ingested food and sleep, and to predict and prevent diseases. We intend to provide a biome-based health information provision system and method.

However, the problem to be solved by the present invention is not limited to the problems mentioned above, and other problems that are not mentioned will be clearly understood by those skilled in the art from the following description.

According to an aspect of the present invention for solving the above problems, there is provided a method for providing health information based on microbiome performed by an analysis/recommendation service server, comprising: collecting life pattern information on eating habits, exercise, and sleep; Analyzing the microorganisms held in the intestines of the user through the collection kit into which the collected user's feces are put; And recommending eating habits, exercise, and sleep information for improving the possessed microorganisms according to the association between the possessing microorganisms and eating habits, exercise amount, and sleep based on the analysis result. .

In one embodiment, the microbiome-based health information providing method comprises the steps of registering a member through a mobile app installed in a user terminal; And writing a questionnaire on health conditions and lifestyle habits; may further include.

In one embodiment, the microbiome-based health information providing method further comprises generating visualization information on the analyzed result and guiding it to a user terminal, wherein the visualization information includes an intestinal bacteria ratio, an obesity/normal bacteria ratio, and Diagnosis, changes in intestinal microflora, amount of exercise/sleep/nutrients intake, relationship between intestinal bacteria and health factors, and absolute number of bacteria, and the health factors include anticancer power, immunity, antioxidant power, hormone (serotonin), stress and DNA methylation. Can include.

In an embodiment, the collecting may collect exercise information, sleep information, blood sugar information, and blood pressure information through a healthcare device.

In one embodiment, the collecting may register a meal type or take a picture and upload it through a user terminal.

In one embodiment, the recommending step recommends exercise information, sleep information, and diet for improving the retained microorganism, derives a direction of increasing beneficial bacteria for improvement of the retained microorganism, and based on the user's preferred food. I can recommend the above diet.

In one embodiment, the step of analyzing is to derive the association between the microorganism and the disease or disease, and reflect the diet, sleep information, and exercise information in a 5:3:2 ratio to improve diet, sleep, and exercise adjustment. You can derive possible numbers.

In one embodiment, the analyzing step may diagnose the possessed microorganism by searching a microorganism database based on the microorganism information extracted from the collection kit.

In one embodiment, the step of analyzing may identify a constituent ingredient from the uploaded photo, and calculate the calorie, nutritional composition, and nutritional composition of the food based on the identified constituent ingredient.

According to another aspect of the present invention, a retained microorganism that collects lifestyle pattern information on eating habits, exercise, and sleep from a healthcare device or a user terminal, and analyzes a user's intestinal microorganisms through a collection kit into which the collected user's feces are put. Analysis unit; A condition diagnosis unit that generates visualization information on the analyzed result and guides it to the user terminal, and derives a correlation between the possessed microorganism and a disease or disease; And a microbiome-based health information providing system comprising a; and a recommendation unit for recommending eating habits, exercise, and sleep information for improving the possessed microorganisms according to the association between the possessed microorganisms and the eating habits, exercise amount, and sleep based on the analysis result. do. Here, the visualization information includes intestinal bacteria ratio, obesity/normal bacteria ratio and diagnosis, intestinal microbial changes, exercise/sleep quantity/nutrient intake, relationship between intestinal bacteria and health factors, and absolute number of bacteria, and the health factors include anticancer power, Includes immunity, antioxidant power, hormones (serotonin), stress and DNA methylation.

The microbiome-based health information providing system and method according to an embodiment of the present invention analyzes big data such as intestinal microbial analysis data, exercise amount, ingested food and sleep to improve not only diet but also overall life patterns such as sleep and exercise. By recommending that you do, you can promote health and predict and prevent diseases.

In addition, the present invention provides visualization data on the analyzed data through the user terminal, so that the user can easily understand the analysis result related to the microorganisms possessed in his or her intestine, and the health status and improvement direction according to it can be easily recognized. .

In addition, the present invention provides diet, exercise, and sleep information for the improvement of microorganisms in the intestine, thereby helping the user to independently make efforts to improve individual matters among the lifestyle patterns, thereby enhancing the user's target awareness. can do.

1 is a block diagram showing a microbiome-based health information providing system according to an embodiment of the present invention,
2 is a block diagram showing the analysis/recommendation service server of FIG. 1,
Figure 3 is a block diagram of the server database of Figure 1,
4 is a diagram showing a first example of visualization data,
5 is a diagram showing a second example of visualization data,
6 is a diagram showing a third example of visualization data,
7 is a diagram showing a fourth example of visualization data,
8 is a diagram showing a fifth example of visualization data,
9 is a flowchart of a method for providing health information based on a microbiome according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art may easily implement the present invention. The present invention may be implemented in various different forms and is not limited to the embodiments described herein. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and the same reference numerals are assigned to the same or similar components throughout the specification.

The embodiments of the present invention are provided to more fully describe the present invention to those of ordinary skill in the art, and the embodiments described below may be modified in various other forms, and The scope is not limited to the following examples. Rather, these examples are provided to make the present invention more faithful and complete, and to fully convey the spirit of the present invention to those skilled in the art.

The terms used in this specification are used to describe specific embodiments, and are not intended to limit the present invention. As used herein, the singular form may include a plural form unless the context clearly indicates a different case. Also, as used herein, “comprise” and/or “comprising” specify the presence of the mentioned shapes, numbers, steps, actions, members, elements and/or groups thereof. And does not exclude the presence or addition of one or more other shapes, numbers, actions, members, elements and/or groups. As used herein, the term “and/or” includes any and all combinations of one or more of the corresponding listed items.

In the present specification, terms such as first and second are used to describe various members, regions, and/or parts, but it is obvious that these members, parts, regions, layers and/or parts are not limited by these terms. . These terms do not imply any particular order, top or bottom, or superiority, and are only used to distinguish one member, region, or region from another member, region, or region. Accordingly, the first member, region, or region to be described below may refer to the second member, region, or region without departing from the teachings of the present invention.

In the present specification, terms such as "or" and "at least one" may represent one of words listed together, or a combination of two or more. For example, "A or B" and "at least one of A and B" may include only one of A or B, and may include both A and B.

Hereinafter, embodiments of the present invention will be described with reference to the drawings schematically showing embodiments of the present invention. In the drawings, for example, depending on manufacturing techniques and/or tolerances, variations of the illustrated shape can be expected. Accordingly, the embodiments of the present invention should not be construed as being limited to the specific shape of the region shown in the present specification, but should include, for example, a change in shape caused by manufacturing.

1 is a block diagram showing a microbiome-based health information providing system according to an embodiment of the present invention, FIG. 2 is a block diagram showing the analysis/recommendation service server of FIG. 1, and FIG. 3 is a server database of FIG. It is a block diagram of.

Referring to FIG. 1, a microbiome-based health information providing system 10 according to an embodiment of the present invention includes an analysis/recommendation service server 100, a healthcare device 200, a collection kit 300, and a user terminal. Includes 400.

The microbiome-based health information providing system 10 aims to promote human health through big data analysis of the intestinal microbial analysis of the human body, exercise amount, and information on ingested food, and further predict and prevent diseases.

At this time, the microbiome-based health information providing system 10 may perform member management, service management, and billing service based on a block chain.

In addition, the microbiome-based health information providing system 10 may operate de-identified microbial analysis big data. Alternatively, the microbiome-based health information providing system 10 can be identified when referring to personal information of a blockchain-based UMA (User Managed Accessed).

The analysis/recommendation service server 100 collects lifestyle pattern information on eating habits, exercise, and sleep from the healthcare device 200 and the user terminal 400, and based on the intestinal microbial information extracted from the collection kit 300. It is possible to diagnose the microorganisms possessed in the intestines of the user.

In addition, the analysis/recommendation service server 100 may analyze the association between the possessed microorganism and the eating habit, exercise amount, and sleep, and recommend eating habits, exercise, and sleep information for improving the possessed microorganism based on the analysis result. For example, the association between the retained microorganism and diet, exercise and sleep can be derived through comparison with a standard group.

To this end, the analysis/recommendation service server 100 may search the microorganism database 102 and the server database 150. Here, the microbial database 102 may be a database collected by microbial-related medical institutions and research institutes. In addition, the analysis/recommendation service server 100 may update user data collected in connection with the service to the server database 150.

In addition, the analysis/recommendation service server 100 may include a server database 150. Here, the server database 150 may store user information collected by the analysis/recommendation service server 100 and various types of information according thereto.

The healthcare device 200 may be an IoT device. The healthcare device 200 may collect exercise information, sleep information, blood sugar and blood pressure information. Here, the exercise information may include step count, heart rate, running speed, exercise time, exercise trend, and calorie consumption.

In addition, the healthcare device 200 may transmit the collected information to the analysis/recommendation service server 100. In this case, the healthcare device 200 may transmit information collected through its own communication function or through the user terminal 400 to the analysis/recommendation service server 100. For example, the healthcare device 200 may be a wearable device such as a wristband type device, a smart phone type device, and a blood pressure monitor.

The collection kit 300 may analyze microorganisms in the user's body by inserting the collected feces. Here, the collection kit 300 may be provided at a base medical facility designated by an operator or an operator of the analysis/recommendation service server 100. At this time, the user can deliver the collected feces to the base medical facility offline.

Alternatively, the debt kit 300 may be configured as an IoT device. To this end, the debt kit 300 may be distributed to users in advance. In this case, the user may directly put the collected feces into the collection kit 300. The collection kit 300 may transmit the analyzed information to the analysis/recommendation service server 100.

The user terminal 400 may access the analysis/recommendation service server 100 to perform membership registration. In this case, the user terminal 400 may proceed with the subscription procedure through the mobile app. For example, the user terminal 400 may proceed with subscription after receiving authentication with a phone number. Also, the user terminal 400 may check the validity of the email address. Optionally, the user terminal 400 may sign up in connection with an account of an Internet portal site such as SNS.

In addition, the user terminal 400 may input a questionnaire on health conditions and lifestyle habits. Here, the interview may include a family history and medical history.

In addition, the user terminal 400 may transmit the food information consumed to the analysis/recommendation service server 100. That is, the user may register meal information in the analysis/recommendation service server 100 through the user terminal 400.

Alternatively, the user terminal 400 may take a picture of food before eating and upload a picture of the food to the analysis/recommendation service server 100.

Referring to FIG. 2, the analysis/recommendation service server 100 may include a member management unit 110, a microbial analysis unit 120, a condition diagnosis unit 130, and a recommendation unit 140.

The member management unit 110 may perform membership registration through a mobile app installed on the user terminal 400. Here, the member management unit 110 may perform member management, service management, and billing service accordingly. In this case, in particular, for the protection and security of personal information in accordance with the increasing collection of personal data, the member management unit 110 may perform a block chain-based operation.

In addition, the member management unit 110 may provide the user terminal 400 with a questionnaire on health status and lifestyle during the membership registration process. In this case, the user may upload the paperweight to the analysis/recommendation service server 100 using the user terminal 400. Here, the questionnaire includes a health status and lifestyle, and the health status may include a family history and medical history.

The possessed microorganism analysis unit 120 may collect exercise information, sleep information, blood sugar information, and blood pressure information through the healthcare device 200. Here, the exercise information may include step count, heart rate, running speed, exercise time, exercise trend, and calorie consumption. In addition, the sleep information may include a sleep amount and a time zone.

In addition, the retained microorganism analysis unit 120 may register the type of meal through the user terminal 400. Here, the user may upload the type of food consumed at each meal through the user terminal 400.

Alternatively, the possessed microbial analysis unit 120 may identify food ingredients constituting the food from the photos uploaded by the user terminal 400. As an example, the possessed microbial analysis unit 120 may recognize food in a photo and search for information on the recognized food in the server database 150 to identify the corresponding food ingredient. At this time, the retained microbial analysis unit 120 may calculate calories, nutritional components, and nutritional composition of the food based on the identified food materials.

In addition, the possessed microorganism analysis unit 120 may analyze the user's intestinal microorganisms through the collection kit 300. At this time, the possessed microbial analysis unit 120 may search the microbial database 102 based on the intestinal microbial information extracted through the collection kit 300 to diagnose the intestinal microbe of the user. Here, the retained microbial analysis unit 120 may diagnose harmful bacteria and beneficial bacteria by classifying them.

The condition diagnosis unit 130 may generate visualization information on the analyzed result of the microbial analysis unit 120 and guide the generated information to the user terminal 400. Here, the visualization information guided to the user terminal 400 is various graph information, including intestinal bacteria ratio, obesity/normal bacteria ratio and diagnosis, changes in intestinal microorganisms, exercise/sleep quantity/nutrients intake, relationship between intestinal bacteria and health factors, and absolute bacteria. May contain numbers.

Thereby, the user can easily understand the analysis results related to the microorganisms possessed in his or her intestines. In addition, it is possible to easily recognize the direction of improvement of one's own health condition and the intestinal-bearing microorganisms different from the analysis result.

In addition, the condition diagnosis unit 130 may derive a correlation between the possessed microorganism analyzed by the possessed microorganism analysis unit 120 and the disease or disease. Here, the condition diagnosis unit 130 may derive an expected disease or disease that may occur by searching for a disease related to a possessed microorganism in the microorganism database 102.

In addition, the condition diagnosis unit 130 may propose a preventive measure for a corresponding disease or disease. The preventive measures may include improvement of the possessed microorganism or a lifestyle to prevent the disease or disease.

At this time, the condition diagnosis unit 130 may derive an improvement possible value for the possessed microorganism. For example, the condition diagnosis unit 130 may derive an improvement possible value according to diet, sleep, and exercise adjustment by reflecting the eating habit, sleep information, and exercise information at a ratio of 5:3:2. Here, the condition diagnosis unit 130 may search through the microorganism database 102 or the server database 150 for correlations between the possessed microorganisms and eating habits, sleep information, and exercise.

The recommendation unit 140 may recommend eating habits, exercise, and sleep information for improving the holding microorganisms based on the analysis result of the holding microorganism analysis unit 120 and the improvement possible value of the condition diagnosis unit 130. Here, the recommendation unit 140 may recommend the corresponding information according to the association between the retained microorganism and eating habits, exercise amount, and sleep. In this case, the recommendation unit 140 may search the association between the retained microorganism and the eating habit, exercise amount, and sleep through the microorganism database 102 or the server database 150.

In addition, the recommendation unit 140 may recommend exercise information, sleep information, and diet for improving the possessed microorganisms. For example, the recommendation unit 140 may derive a direction of increasing beneficial bacteria for improvement of the holding microorganism. At this time, the recommendation unit 140 may recommend exercise, sleep, and diet so that beneficial bacteria increase.

In addition, the recommendation unit 140 may recommend a diet based on food that the user prefers. Here, the food that the user prefers may be food that the user usually consumes.

As a result, it is possible to help the user to independently make efforts to improve individual items among the lifestyle patterns. Therefore, it is possible to increase the user's target awareness for each individual item.

Referring to FIG. 3, the server database 150 may include user information 151, healthcare information 152, microbial information 153, food intake information 154, and food photo information 155. .

The user information 151 may be member management information. Here, the user information 151 may include service management and billing information.

The healthcare information 152 may be information collected by the analysis/recommendation service server 100 through the healthcare device 200. Here, the healthcare information 152 may include exercise information, blood sugar and blood pressure information.

The retained microorganism information 153 may be information extracted through the collection kit 300 and information about the user's own microorganisms analyzed by the retained microorganism analysis unit 120. Here, the retained microorganism information 153 may include harmful bacteria, beneficial bacteria, and obese bacteria. Optionally, the retained microbial information 153 may include related diseases or diseases.

The food intake information 154 may be meal information registered in the analysis/recommendation service server 100 through the user terminal 400. In addition, the food intake information 154 may be food information analyzed based on a photo uploaded by the user terminal 400.

The food photo information 155 may be a photo uploaded to the analysis/recommendation service server 100 through the user terminal 400.

Visualization data will be described in more detail with reference to FIGS. 4 to 8. Here, the visualization material describes a state displayed on the user terminal 400.

4 is a diagram showing a first example of visualization data, FIG. 5 is a diagram showing a second example of visualization data, FIG. 6 is a diagram showing a third example of visualization data, and FIG. 7 is a fourth example of visualization data. It is a diagram showing an example, and FIG. 8 is a diagram showing a fifth example of visualization data.

Referring to FIG. 4, a first example of the visualization data is the ratio of intestinal bacteria, and may include the ratio of beneficial bacteria (Bifidobacterium, Lactobacillus), intermediate bacteria (Bacteroides), and harmful bacteria (Clostridium). . In this case, in the first example of the visualization data, the average ratio of the standard group may be displayed together with the intestinal ratio of the user. For example, the percentage of bacteria in the intestine may be represented by a circular band graph.

In addition, in the first example of the visualization data, a total score calculated for the ratio of intestinal bacteria may be displayed together with a numerical value of the ratio of intestinal bacteria. For example, the overall score for the ratio of intestinal bacteria may be calculated based on the average ratio of the standard group.

Referring to FIG. 5, a second example of the visualization data is the ratio of obesity/normal bacteria, and may include the ratio of obesity-inducing bacteria (permyguetes) and normal bacteria (bacterioidetes). In this case, in the second example of the visualization data, the average ratio of the standard group may be displayed together with the obesity/normal bacteria ratio of the user. For example, the ratio of obesity/normal bacteria may be displayed as a bar graph.

The second example of the visualization data is the diagnosis of obesity bacteria, and a composite score calculated for the ratio of obesity inducing bacteria and normal bacteria can be displayed. For example, the overall score for the diagnosis of obesity bacteria may be calculated based on the average ratio of the standard group. At this time, the ratio of obesity-inducing bacteria and normal bacteria may be displayed together in a circular band graph.

Referring to FIG. 6, a third example of the visualization data is an intestinal bacteria/exercise/sleep/eating habit monitoring chart, which may include changes in intestinal microorganisms, changes in body and amount of exercise/sleep/nutrient intake. Here, the intestinal microbial change may be displayed as a bar graph showing the rate of change of beneficial bacteria, intermediate bacteria and harmful bacteria.

Body changes can be indicated by changes in body weight, skeletal muscle mass, body fat percentage, and cell and water ratio.

The amount of exercise/sleep amount/nutrient intake may indicate the amount of walking and running exercise (time), nutrients intake and their ratio, and sleep amount (or sleep time). Here, an impact balance score may be displayed for ingested nutrients.

Referring to FIG. 7, the fourth example of the visualization data is an additional analysis of the ratio of intestinal bacteria, and the ratio of beneficial bacteria (Bifidobacterium, Lactobacillus), and harmful bacteria (Clostridium) is displayed as a bar graph and a radial graph. I can. In this case, in the fourth example of the visualization data, the standard ratio of the standard group may be displayed together.

Here, in the fourth example of the visualization data, the relationship between intestinal bacteria and health factors may be further displayed. For each health factor, the average size of the beneficial bacteria, harmful bacteria and standard groups can be displayed as a bar graph. At this time, the health factors may include anti-cancer power, immunity, antioxidant power, hormone (serotonin), stress, and DNA methylation.

Referring to FIG. 8, in a fifth example of the visualization data, the absolute number of cells of beneficial bacteria (Bifidobacterium, Lactobacillus), and harmful bacteria (Clostridium) may be displayed. Here, the absolute cell number may be displayed in CFU (Colony-Forming Unit) units. At this time, the absolute cell number may be displayed to be divided into a bar graph, a numerical value, and an aptitude range.

With this configuration, the microbiome-based health information providing system 10 according to an embodiment of the present invention can promote health, predict and prevent diseases, and allow the user to analyze the results related to the microorganisms in his intestine. It is easy to understand, and the health status and direction of improvement accordingly can be easily recognized, and it can help users to independently make efforts for improvement for individual items in their life patterns, thus raising the user's awareness of the goal. have.

Hereinafter, a method of providing health information based on microbiome of the present invention will be described with reference to FIG. 9.

9 is a flowchart of a method for providing health information based on a microbiome according to an embodiment of the present invention.

The microbiome-based health information provision method 500 includes the steps of signing up for a member (S510 and S520), collecting food/exercise/sleep information (S530), analyzing the possessed microorganism (S540), and guiding and recommending analysis results. It includes steps S550 and S560.

In more detail, as shown in FIG. 9, first, the analysis/recommendation service server 100 performs membership registration through a mobile app installed in the user terminal 400 (step S510). In this case, the analysis/recommendation service server 100 may check the validity of the input email address and perform subscription processing in connection with the account of the portal site.

Next, the analysis/recommendation service server 100 creates a questionnaire on health status and lifestyle using the user terminal 400 (step S520). In this case, the user may upload the paperweight to the analysis/recommendation service server 100 using the user terminal 400. Here, the questionnaire includes a health status and lifestyle, and the health status may include a family history and medical history.

Next, the analysis/recommendation service server 100 collects lifestyle pattern information for eating habits, exercise, and sleep (step S530). In this case, the analysis/recommendation service server 100 may collect exercise information, sleep information, blood sugar information, and blood pressure information through the healthcare device 200. Here, the exercise information may include step count, heart rate, running speed, exercise time, exercise trend, and calorie consumption. In addition, the sleep information may include a sleep amount and a time zone.

In addition, the analysis/recommendation service server 100 may register a meal type through the user terminal 400. That is, the user may upload the type of food consumed at each meal to the analysis/recommendation service server 100 through the user terminal 400.

Alternatively, the analysis/recommendation service server 100 may collect food information from a photo uploaded by the user terminal 400. That is, the user may use the user terminal 400 to take a picture of food before eating and upload a picture of the food to the analysis/recommendation service server 100.

Next, the analysis/recommendation service server 100 analyzes the possessed microorganism (step S540). At this time, the analysis/recommendation service server 100 may analyze the microorganisms possessed in the intestine of the user by using the collection kit 300 into which the collected user's feces are put. Here, the analysis/recommendation service server 100 may search the microorganism database 102 based on the intestinal microorganism information extracted through the collection kit 300 to diagnose the intestinal microorganisms of the user. In addition, the analysis/recommendation service server 100 may classify and diagnose harmful bacteria and beneficial bacteria.

In addition, the analysis/recommendation service server 100 may identify ingredients constituting food from the photos uploaded by the user terminal 400. As an example, the analysis/recommendation service server 100 may recognize food in a picture and search for information on the recognized food in the server database 150 to identify a corresponding food ingredient. In this case, the analysis/recommendation service server 100 may calculate calories, nutritional components, and nutritional composition of the food based on the identified food ingredients.

In addition, the analysis/recommendation service server 100 may derive a correlation between the analyzed possessed microorganism and a disease or disease. Here, the analysis/recommendation service server 100 may derive a possible disease or disease by searching for a disease related to a microorganism in the microorganism database 102.

In this case, the analysis/recommendation service server 100 may suggest a preventive measure for a corresponding disease or disease. Here, the preventive measures may include improvement of the possessed microorganism or a lifestyle for preventing the corresponding disease or disease.

In addition, the analysis/recommendation service server 100 may derive an improvement possible value for the possessed microorganism. For example, the analysis/recommendation service server 100 may derive an improvement possible value according to diet, sleep, and exercise adjustment by reflecting eating habits, sleep information, and exercise information in a ratio of 5:3:2. Here, the analysis/recommendation service server 100 may search through the microorganism database 102 or the server database 150 for correlations between the possessed microorganisms and eating habits, sleep information, and exercise.

Next, the analysis/recommendation service server 100 generates visualization information on the analyzed result and guides it to the user terminal 400 (step S550). At this time, the analysis/recommended service server 100 provides visualization information including the intestinal bacteria ratio, obesity/normal bacteria ratio and diagnosis, changes in intestinal microorganisms, exercise/sleep quantity/nutrients intake, the relationship between intestinal bacteria and health factors, and the absolute number of bacteria. It can be guided to the user terminal 400.

Here, the visualization information may include intestinal bacteria ratio, obesity/normal bacteria ratio and diagnosis, changes in intestinal microorganisms, exercise/sleep quantity/nutrients intake, relationship between intestinal bacteria and health factors, and absolute number of bacteria. At this time, the health factors may include anti-cancer power, immunity, antioxidant power, hormone (serotonin), stress, and DNA methylation.

Next, the analysis/recommendation service server 100 recommends eating habits, exercise, and sleep information for improving the possessed microorganisms based on the analysis result (step S560). In this case, the analysis/recommendation service server 100 may recommend the information according to the association between the possessed microorganism and the eating habit, exercise amount, and sleep. Here, the analysis/recommendation service server 100 may search through the microorganism database 102 or the server database 150 for correlations between the possessed microorganisms and eating habits, exercise amount, and sleep.

In addition, the analysis/recommendation service server 100 may recommend exercise information, sleep information, and diet for improving the possessed microorganisms. As an example, the analysis/recommendation service server 100 may derive an increase direction of beneficial bacteria for improvement of the possessed microorganism. In this case, the analysis/recommendation service server 100 may recommend exercise, sleep, and diet so that beneficial bacteria increase.

In addition, the analysis/recommendation service server 100 may recommend a diet based on the food preferred by the user. Here, the food that the user prefers may be food that the user usually consumes.

By such a method, the present invention can promote health, predict and prevent diseases, and allow the user to easily understand the analysis results related to the microorganisms possessed in his or her intestines, and to easily recognize the health status and improvement direction accordingly. In addition, since it is possible to help the user to independently make efforts to improve individual items among the life patterns, the user's awareness of the goal can be improved.

The above methods may be implemented by the analysis/recommended service server 100 as shown in FIG. 1, and in particular, may be implemented as a software program that performs these steps, and in this case, these programs are computer-readable. It may be stored on a possible recording medium or transmitted by a computer data signal combined with a carrier wave in a transmission medium or a communication network. In this case, the computer-readable recording medium may include all types of recording devices in which data readable by a computer system is stored.

Although an embodiment of the present invention has been described above, the spirit of the present invention is not limited to the embodiments presented in the present specification, and those skilled in the art who understand the spirit of the present invention can add components within the scope of the same idea. It will be possible to easily propose other embodiments by changing, deleting, adding, etc., but it will be said that this is also within the spirit scope of the present invention.

10: Microbiome-based health information provision system
100: analysis/recommended service server 102: microbial database
110: member management unit 120: possessed microorganism analysis unit
130: condition diagnosis unit 140: recommendation unit
150: server database 151: user information
152: healthcare information 153: possessed microbial information
154: Ingested food information 155: Food photo information
200: healthcare device 300: collection kit
400: user terminal

Claims (10)

In the microbiome-based health information provision method performed by the analysis/recommended service server,
Collecting lifestyle pattern information on eating habits, exercise and sleep;
Analyzing the microorganisms held in the intestine of the user through the collection kit into which the collected user's feces are put; And
Recommending eating habits, exercise, and sleep information for improving the possessed microorganisms according to the association between the possessing microorganisms and eating habits, exercise amount, and sleep based on the analysis result;
Microbiome-based health information providing method comprising a. The method of claim 1,
Signing up as a member through a mobile app installed on the user terminal; And
The method of providing health information based on microbiome further comprising; writing a questionnaire on health conditions and lifestyle habits. The method of claim 1,
Generating as visualization information on the analyzed result, further comprising the step of guiding the user terminal,
The visualization information includes intestinal bacteria ratio, obesity/normal bacteria ratio and diagnosis, changes in intestinal microbes, exercise/sleep quantity/nutrients intake, relationship between intestinal bacteria and health factors, and absolute number of bacteria,
The health factor is a microbiome-based health information providing method including anticancer power, immunity, antioxidant power, hormone (serotonin), stress and DNA methylation. The method of claim 1,
The collecting step is a microbiome-based health information providing method for collecting exercise information, sleep information, blood sugar information, and blood pressure information through a healthcare device. The method of claim 1,
The collecting step is a microbiome-based health information providing method of registering a meal type or taking a picture and uploading it through a user terminal. The method of claim 1,
The recommending step recommends exercise information and diet for improving the retained microorganisms,
Derive the direction of increasing beneficial bacteria for the improvement of the retained microorganisms,
A microbiome-based health information providing method that recommends the diet based on the user's favorite food. The method of claim 1,
The analyzing step derives a correlation between the possessing microorganism and a disease or disease,
A method of providing health information based on microbiome that reflects the eating habits, sleep information, and exercise information in a 5:3:2 ratio to derive values that can be improved according to diet, sleep and exercise adjustment. The method of claim 1,
The analyzing step is a microbiome-based health information providing method for diagnosing a possessed microorganism by searching a microorganism database based on the microorganism information extracted from the collection kit. The method of claim 5,
The analyzing step identifies the constituent ingredients from the uploaded photo,
Microbiome-based health information providing method for calculating calories, nutritional components, and nutritional composition of the food based on the identified ingredients. A retention microbial analysis unit that collects life pattern information on eating habits, exercise, and sleep from a health care device or from a user terminal, and analyzes a user's intestinal microbes through a collection kit into which the collected user's feces are put;
A condition diagnosis unit that generates visualization information on the analyzed result, guides it to the user terminal, and derives a correlation between the possessed microorganism and a disease or disease; And
Including; a recommendation unit for recommending information on eating habits, exercise, and sleep for improving the holding microorganisms according to the association between the holding microorganism and the eating habit, exercise amount, and sleep based on the analysis result; and
The visualization information includes intestinal bacteria ratio, obesity/normal bacteria ratio and diagnosis, changes in intestinal microbes, exercise/sleep quantity/nutrients intake, relationship between intestinal bacteria and health factors, and absolute number of bacteria,
The health factor is a microbiome-based health information providing system including anticancer power, immunity, antioxidant power, hormone (serotonin), stress and DNA methylation.

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