WO2024186147A1 - Healthcare system using ketone body information - Google Patents

Abstract

This method for analyzing the state of a user by using ketone body information comprises steps in which an analysis device: acquires ketone body information of the user; calculates state information of the user on the basis of the ketone body information of the user; and visualizes the calculated state information of the user and outputs same. The ketone body information includes information about the concentration of ketone body included in the exhalation of the user measured using a ketone body measurer. The state information of the user includes at least one from among body fat change amount of the user, weight change amount of the user, blood glucose level of the user, and cholesterol content of the user.

Description

Healthcare system using ketone body information

The technology described below is for a healthcare system that uses ketone body information.

The human body uses glucose, protein, and fat as energy sources. The human body primarily uses glucose as an energy source, followed by protein and fat. When the human body uses fat as an energy source, ketone bodies are created as byproducts of fat breakdown. Ketone bodies include acetone, acetoacetate, and D-β hydroxybutyric acid (D-β). Ketone bodies are excreted through exhaled gas and urine. Accordingly, technologies are being developed to measure ketone bodies in the user's exhaled gas.

[Prior art literature]

[Patent Document]

Korean Patent Publication No. 10-1815038

Conventional techniques for measuring ketone bodies in exhaled gas simply stored the measured data on a server, etc. Accordingly, the conventional techniques simply displayed information on the concentration of ketone bodies in exhaled gas stored on a server according to a request from a user, etc., and did not inform the user of various conditions by utilizing the measured ketone body information. The technique described below discloses a method for informing the user of the user's condition by utilizing the user's measured ketone body information.

A method for analyzing a user's status using ketone body information includes a step in which an analysis device acquires the user's ketone body information; a step in which the analysis device calculates the user's status information based on the user's ketone body information; and a step in which the analysis device visualizes and outputs the calculated user's status information. The ketone body information includes information on the concentration of ketone bodies contained in the user's exhaled breath measured using a ketone body measuring device. The user's status information includes at least one of the user's body fat change amount, the user's weight change amount, the user's blood sugar level, and the user's cholesterol level.

Using the technology described below, it is possible to identify various conditions of the user based on the ketone body information in the user's exhaled gas. This allows the user to roughly identify the user's condition using only a ketone body measuring device without visiting a hospital or the like.

Figure 1 shows the overall process by which an analysis device (100) performs a method for analyzing user status information using ketone body information.

Figure 2 is a flowchart (200) of one embodiment of analyzing user status information based on ketone body information.

Figure 3 is an example in which the analysis device determines the user's status information from the ketone body concentration using a pre-calculated relationship.

Figures 4 and 5 are examples of abnormal values.

Fig. 6 is a configuration of one embodiment of an analysis device (300).

The technology described below can have various modifications and various embodiments. Specific embodiments of the technology described below may be described in the drawings of the specification. However, this is for the purpose of explaining the technology described below and is not intended to limit the technology described below to specific embodiments. Therefore, it should be understood that all modifications, equivalents, or substitutes included in the spirit and scope of the technology described below are included in the technology described below.

In the terms used hereinafter, the singular expression should be understood to include the plural expression unless the context clearly dictates otherwise, and the term "comprises" and the like should be understood to mean the presence of a described feature, number, step, operation, component, part, or combination thereof, but not to exclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

Before going into a detailed description of the drawings, it should be made clear that the division of components in this specification is only a division based on the main function of each component. In other words, two or more components to be described below may be combined into one component, or one component may be divided into two or more components with more detailed functions. In addition to its own main function, each component to be described below may additionally perform some or all of the functions of other components, and of course, some of the main functions of each component may be exclusively performed by other components.

In addition, in performing a method or method of operation, each process constituting the method may occur in a different order from the stated order unless the context clearly states a specific order. That is, each process may occur in the same order as the stated order, may be performed substantially simultaneously, or may be performed in the opposite order.

Below, we will look at the overall process by which the analysis device performs a method of analyzing user status information using ketone body information.

Figure 1 shows the overall process by which an analysis device (100) performs a method for analyzing user status information using ketone body information.

The analysis device (100) may be implemented in various physical forms. For example, the analysis device (100) may have the form of a PC, a laptop, a smart device, a server, or a data processing-only chipset. Alternatively, the analysis device (100) may be a part of a ketone body measuring device. In other words, the analysis device (100) may be implemented in the form of an on-device in a ketone body measuring device.

The analysis device (100) may be singular or plural. That is, the user's status analysis method using the aforementioned ketone body information may be performed by at least one analysis device (100).

The analysis device (100) may be a device that performs a method of analyzing user status information using ketone body information. Specifically, the analysis device (100) may be a device that receives user ketone body information and outputs user status information. The analysis device (100) may use a pre-calculated relationship or an analysis model to calculate the user status information.

Below, a method for analyzing user status information using ketone body information is specifically described.

Figure 2 is a flowchart (200) of one embodiment of analyzing user status information based on ketone body information.

The analysis device can obtain the user's ketone body information (210).

The user's ketone body information may include at least one of the user's acetone, acetoacetate, and D-β hydroxybutyric acid (D-β) information. Ketone bodies are generally known as substances produced in the process of a person using fat as an energy source. Accordingly, based on the user's ketone body information, various conditions of the user, including the amount of fat consumed, can be identified.

The user's ketone body information may include information about the concentration of ketone bodies contained in the user's blood, urine, sweat, and breath. Preferably, the user's ketone body information may include information about the concentration of ketone bodies contained in the user's breath.

The user's ketone body information may include information on the concentration of ketone bodies measured using a ketone body measuring device. The ketone body measuring device may be a device that measures the concentration of ketone bodies contained in the user's blood, urine, sweat, and exhaled air. In one embodiment, the user's ketone body information may include information on the concentration of ketone bodies contained in the user's exhaled air measured using a ketone body measuring device. The ketone body measuring device and the analysis device may be connected to each other by wire or wirelessly.

The user's ketone body information may be time-series data. That is, the user's ketone body information may include information about the time at which the user's ketone body information was acquired. For example, the user's ketone body information may include the user's ketone body information on March 15, the user's ketone body information on April 15, and the user's ketone body information on May 15.

The analysis device can calculate the user's status information based on the user's ketone body information (220).

The user's status information may include information about the user's status that can be determined from the user's ketone body information. The user's status information may include at least one of the user's body fat change amount, the user's weight change amount, the user's blood sugar level, and the user's cholesterol level.

The user's body fat change amount may include how much the body fat has changed compared to the baseline. In this case, the user's body fat change amount may be calculated based on ketone body information. For example, the user's body fat change amount may include information that if the user's exhaled ketone body concentration is 2.9 ppm, the user's body fat has decreased by 1.1 kg compared to one month ago.

The user's weight change may include how much the weight has changed compared to a baseline. In this case, the user's weight change may be calculated based on ketone body information. For example, the user's weight change may include information that if the user's exhaled ketone body concentration is 2.9 ppm, the user's weight has decreased by 1.8 kg compared to one month ago.

The user's blood sugar level may include the user's blood sugar level at a reference point. At this time, the user's blood sugar level may be calculated based on ketone body information. For example, the user's blood sugar level may include information that if the user's exhaled ketone body concentration is 2.9 ppm at the current point in time, the user's current blood sugar level is 84.

The user's cholesterol level may include the user's cholesterol level at a reference point in time. At this time, the user's cholesterol level may be calculated based on ketone body information. For example, the user's cholesterol level may include information that if the user's expiratory ketone body concentration at the current point in time is 2.9 ppm, the user's high-density cholesterol level at the current point in time is 73. The cholesterol level may include at least one of total cholesterol, high-density cholesterol (HDL-cholesterol), and low-density cholesterol (LDL-cholesterol).

Furthermore, the user's status information may include the user's liver function test information. The liver function test information may include at least one of the user's AST (aspartate aminotransferase) level, the user's ALT (alanine aminotransferase) level, the user's GGT (gamma-glutamyl transferase) level, the user's ALP (alkaline phosphatase) level, and the user's Bilirubin level.

Furthermore, the user's status information may include the user's level of treatment.

The user's treatment level may include the extent to which the user suffering from a disease, etc. has been cured of the disease. In particular, if the user's ketone body information includes information on the concentration of ketone bodies contained in the user's exhaled gas, there is an advantage in that the user's treatment level can be easily measured using only the user's exhaled gas without having to separately collect the user's blood.

In one embodiment, the user's treatment level may include the treatment level of pediatric epilepsy. Epilepsy patients are recommended to eat a diet that can produce ketone bodies in order to reduce the frequency of epileptic seizures. Accordingly, based on the ketone body information of the epilepsy patient, the level of ketone bodies in the exhaled breath of the epilepsy patient can be identified, and then the degree of treatment of the epilepsy patient can be calculated based on the identified ketone body level. Through this, it is possible to identify to what extent the pediatric epilepsy patient is being treated as the pediatric epilepsy patient eats a ketone body diet.

In one example, the user's treatment level may include the treatment level of a cancer patient. When a cancer patient recovers after receiving radiation treatment, the damaged cells tend to regenerate better if they eat a diet that can produce ketone bodies. Accordingly, based on the cancer patient's ketone body information, the cancer patient's exhaled ketone body level can be identified, and then the cancer patient's cell regeneration level, etc. can be calculated based on the identified ketone body level.

The analysis device can also calculate the user's status information using pre-computed relationships.

The pre-calculated relationship may include information on the correlation between the user's ketone body information and the user's status information. For example, the analysis device may pre-calculate the correlation by analyzing the relationship between the user's ketone body information and the user's status information based on a database in which the user's ketone body information measured by the user using a ketone body meter and the user's status information are recorded. In particular, when the analysis device pre-calculates the relationship between the ketone body information and the status information of a specific user, it may pre-calculate a relationship optimized for each user.

A database in which user status information is recorded can be constructed based on the user's body composition analysis results, the user's health checkup results, etc. For example, a database in which user status information is recorded can be constructed based on the test results (ex. blood test, etc.) conducted when the user undergoes a health checkup or donates blood. To this end, the analysis device can receive data from a server in which information such as the user's health checkup is stored. Alternatively, a database in which user status information is recorded can be constructed based on the user's InBody measurement results. By utilizing data acquired through tests conducted as needed in this way, the previously calculated relationship described above can be calculated without a separate test on the user.

FIG. 3 is an example in which the analysis device uses a pre-calculated relationship to determine the user's status information from the ketone body concentration. As shown in FIG. 3, the analysis device can obtain ketone body information (concentration). The analysis device can calculate the user's weight change, body fat change, blood sugar level, and cholesterol level according to the obtained ketone body concentration. At this time, the analysis device can calculate the user's weight change, body fat change, blood sugar level, and cholesterol level according to the ketone body concentration using the pre-calculated relationship.

The analysis device can also use the analysis model to calculate the user's status information.

The analysis model can be a model that inputs the user's ketone body information and outputs the user's status information.

The analysis model may be a learning model learned based on learning data. The analysis model may be a machine learning (ML)-based model. The machine learning model may be various types of models. As an example, the machine learning model may be a decision tree, a random forest (RF), a K-nearest neighbor (KNN), a Naive Bayes, a support vector machine (SVM), an artificial neural network (ANN), etc. The ANN may be a deep neural network (DNN), which may include a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted boltzmann machine (RBM), a deep belief network (DBN), a generative adversarial network (GAN), a relation network (RL), etc.

The analysis device can visualize and output the calculated user status information (230).

For example, the analysis device can output user status information through a smartphone screen or computer monitor.

Furthermore, the analysis device can obtain more dietary information about the user.

Diet information may include information that may be generated when a user eats a meal. In one embodiment, the diet information may include at least one of the type of food consumed by the user when eating, the amount of food consumed, the date of the meal, and the time of the meal.

Furthermore, the analysis device can analyze customized diet information based on the user's diet information, the user's ketone body information, and the user's condition information.

For example, the analysis device can calculate customized diet information for reducing body fat by determining which foods the user consumed produced the most ketone bodies and which diet resulted in the greatest change in body fat.

Furthermore, the analysis device can obtain more movement information of the user.

Exercise information may include information that may be generated when a user exercises. In one embodiment, exercise information may include at least one of the type of exercise performed by the user, the date of exercise, and the time of exercise.

Furthermore, the analysis device can analyze customized exercise information based on the acquired exercise information and the user's ketone body information.

For example, the analysis device can calculate customized exercise information for reducing body fat by determining which exercise the user did to generate the most ketone bodies and the diet that resulted in the greatest change in body fat. Or, the analysis device can analyze customized exercise cycles by determining which exercise cycle the user did to generate the most ketone bodies and the exercise cycle that resulted in the greatest change in weight.

Furthermore, the analysis device can obtain more information about the user's purpose.

The user's goal information may include the user's status information that the user wants to achieve. In one embodiment, the user's goal information may include at least one of the user's body fat, the user's weight, the user's blood sugar level, and the user's cholesterol level that the user wants to achieve. For example, the user's goal information may include information that the user wants to reduce body fat by 10%. Or, the user's goal information may include information that the user wants to lose 1 kg of weight.

Furthermore, the analysis device can identify the change pattern of the user's ketone body information based on the user's ketone body information. The analysis device can predict future ketone body information based on the identified change pattern of the ketone body information. The analysis device can predict the period required to achieve the user's purpose based on the predicted ketone body information and the user's purpose information.

For example, the analysis device can predict the user's future ketone body concentration based on the user's ketone body concentration, calculate the user's body fat change amount based on the predicted user's ketone body concentration, and then predict the time it will take for the user to reach the target body fat mass based on the calculated body fat change amount.

If the analysis device acquires more dietary information, the analysis device can predict the diet and period required to achieve the user's purpose. For example, the analysis device can identify the user's ketone body information change pattern according to the food eaten by the user, predict future ketone body information based on the identified ketone body information change pattern, and predict the diet and period required to achieve the user's purpose based on the predicted ketone body information and the user's purpose information.

If the analysis device acquires more exercise information, the analysis device can predict the exercise and period required to achieve the user's purpose. For example, the analysis device can identify the user's ketone body information change pattern according to the user's exercise, predict future ketone body information based on the identified ketone body information change pattern, and predict the exercise and period required to achieve the user's purpose based on the predicted ketone body information and the user's purpose information.

The analysis device can analyze the change pattern of the user's ketone body information to determine if there are any abnormal values. If there are any abnormal values, the analysis device can obtain additional user's ketone body information to replace the abnormal values.

Figures 4 and 5 are examples of abnormal values. The abnormal value may be the user's ketone body concentration when the measured ketone body concentration decreases sharply, as in Figure 4. Or, the abnormal value may be the user's ketone body concentration when the measured ketone body concentration increases sharply, as in Figure 5. As can be seen in Figures 4 and 5, when analyzing the change pattern of the ketone body concentration, if a newly measured value is too different from the analyzed change pattern, it can be considered an abnormal value. An abnormal value may occur when a user uses a ketone body measuring device while the user has a residual toothpaste smell after brushing his or her teeth, when a user uses a ketone body measuring device right after eating food, or when a user uses a ketone body measuring device while exercising. When an abnormal value exists, the analysis device may notify the user of the existence of an abnormal value and request additional user's ketone body information. Accordingly, the analysis device may obtain additional user's ketone body information. For example, the user can clean his or her mouth or after a certain period of time, measure ketone body information again using the ketone body measuring device and report the measured ketone body information to the analysis device. If there are abnormal values in the additional ketone body information, the analysis device can notify the user that there is a problem with the ketone body measuring device. In this case, the user can replace the filter of the ketone body measuring device, etc. Or, the user can contact the place of purchase to receive A/S (after service).

The following describes the analysis device.

Fig. 6 is a configuration of one embodiment of an analysis device (300).

The analysis device (300) may correspond to the analysis device (100) described in Fig. 1. That is, the analysis device (300) may be a device that performs a user status analysis method using the aforementioned ketone body information.

The analysis device (300) may include at least one input device (310), a storage device (320), a calculation device (330), an output device (340), an interface device (350), and a communication device (360).

The input device (310) can receive data, information, or models necessary for performing a user status analysis method using the aforementioned ketone body information.

The input device (310) can receive the user's ketone body information, the user's diet information, the user's exercise information, and the user's purpose information. The input device (310) can receive the analysis model.

The input device (310) may include a device (such as a keyboard, mouse, and touch screen, joystick, trackball, touchpad, scanner, webcam, etc.) for inputting a certain command or data. The input device (310) may include a configuration for receiving data through a separate storage device (such as USB, CD, hard disk, etc.). The input device (310) may also receive data through a separate measuring device or a separate database. The input device (310) may also receive data through a communication device (360) in a wired or wireless manner. The input device (310) may also receive a control signal for controlling the analysis device (300).

The storage device (320) can store data, information, or models, etc. required to perform the user's status analysis method using the aforementioned ketone body information. The storage device (320) can store the user's ketone body information, the user's diet information, the user's exercise information, and the user's purpose information. The storage device (320) can store an analysis model. The storage device (320) can also be a device that stores certain data, information, or models, etc. The storage device (320) can store data, information, models, etc. input through the input device (310). The storage device (320) can store commands that cause the operation device (330) to perform operations required for the user's status analysis method using the ketone body information. The storage device (320) can store information generated during the operation of the operation device (330). That is, the storage device (320) can include a memory. For example, storage devices may include hard disk drives (HDDs), solid state drives (SSDs), ROMs, RAMs, and CD-ROM magnetic tapes or floppy disks.

The calculation device (330) can perform the calculation required to perform the user's status analysis method using the aforementioned ketone body information. The calculation device (330) can calculate the user's status information based on the user's ketone information. The calculation device (330) can calculate the user's status information using a pre-calculated relationship. The calculation device (330) can calculate the user's status information using an analysis model. The calculation device (330) can analyze the user's customized diet information based on the user's diet information, the user's ketone information, and the user's status information. The calculation device (330) can analyze the user's customized exercise information based on the user's exercise information, the user's ketone body information, and the user's status information. The calculation device (330) can identify the user's ketone body information change pattern based on the ketone body information. The calculation device (330) can predict future ketone body information based on the ketone body information change pattern. The calculation device (330) can predict the period required for the user to achieve the goal based on the predicted ketone body information and the user's goal information. The calculation device (330) can analyze the change pattern of the user's ketone body information to determine whether there is an abnormal value. If there is an abnormal value, the calculation device (330) can obtain additional user ketone body information to replace the abnormal value.

The calculation unit (330) may be a device such as a processor, an application processor (AP), or a chip embedded with a program that processes data and processes certain operations. For example, the calculation unit (330) may include a central processing unit (CPU), a graphics processing unit (GPU), or a neural processing unit (NPU). The calculation unit (330) may generate a control signal that controls the analysis unit (300). The calculation unit (330) may generate a control signal that controls the input device (310), the storage device (320), the output device (340), the interface device (350), and the communication device (360) included in the analysis unit (300).

The output device (340) may be a device that outputs certain data, information, and models. The output device (340) may be a device that outputs certain data, information, and models to the outside of the analysis device (300). The output device (340) may output interfaces, input data, analysis results, etc. required for the data processing process. The output device (340) may include devices that output data, etc. through tactile, visual, auditory, gustatory, and olfactory methods. The output device (340) may be physically implemented in various forms, such as a display, a speaker, a vibration motor, or a document output device. The output device (340) may output data, information, or models stored in the storage device (320). The output device (340) may output data, information, and models generated in the process of the calculation device (330) performing calculations. The output device (340) may output the results of the calculations performed by the calculation device (330). The output device (340) may output user status information.

The interface device (350) may be a device that receives certain commands and data from the outside. The interface device (350) may receive a control signal for controlling the analysis device (300). The interface device (350) may output the results analyzed by the analysis device (300). The interface device (350) may receive information necessary for performing the user's status analysis method using the aforementioned ketone body information from a physically connected input device or an external storage device.

The communication device (360) can receive information necessary for performing the user's status analysis method using the aforementioned ketone body information. The communication device (360) can receive a model necessary for performing the user's status analysis method using the aforementioned ketone body information. The communication device (360) can transmit and receive the user's ketone body information, the user's diet information, the user's exercise information, and the user's purpose information. The communication device (360) can transmit and receive an analysis model. The communication device (360) can receive a control signal necessary for controlling the analysis device (300). The communication device (360) can transmit the results analyzed by the analysis device (300). The communication device (360) can mean a configuration that receives and transmits certain data, information, models, etc. through a wired or wireless network. The communication device (360) can perform network communication such as Wi-Fi (Wireless Fidelity), Wi-Fi Direct, Bluetooth, UWB (Ultra-Wide Band), NFC (Near Field Communication), USB (Universal Serial Bus), or HDMI (High Definition Multimedia Interface), LAN (Local Area Network), etc.

The method for analyzing the user's status using the aforementioned ketone body information can be implemented as a program (or application) including an executable algorithm that can be run on a computer.

The above program may be provided stored in a non-transitory computer readable medium.

The above-mentioned temporarily readable medium refers to various RAMs such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchronous DRAM (Synclink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).

The above non-transitory readable medium means a medium that semi-permanently stores data and can be read by a device, rather than a medium that stores data for a short moment, such as a register, cache, or memory. Specifically, the various applications or programs described above may be stored and provided in a non-transitory readable medium, such as a CD, DVD, hard disk, Blu-ray disk, USB, memory card, ROM (read-only memory), PROM (programmable read only memory), EPROM (Erasable PROM, EPROM), EEPROM (Electrically EPROM), or flash memory.

The present examples and the drawings attached to the present specification only clearly illustrate a part of the technical idea included in the above-described technology, and it will be obvious that all modified examples and specific embodiments that can be easily inferred by a person skilled in the art within the scope of the technical idea included in the specification and drawings of the above-described technology are included in the scope of the rights of the above-described technology.

Claims (19)

A step in which the analysis device obtains the user's ketone body information; A step in which the above analysis device calculates the user's status information based on the user's ketone body information; and A step in which the above analysis device visualizes and outputs the calculated user status information; including, A method for analyzing a user's status using ketone body information, wherein the user's status information includes at least one of the user's body fat change amount, the user's weight change amount, the user's blood sugar level, and the user's cholesterol level. In the first paragraph, A method for analyzing a user's status using ketone body information, wherein the ketone body information includes at least one of the user's acetone, acetoacetate and D-β hydroxybutyric acid (D-β) information. In the first paragraph, The above user's status information further includes the user's treatment level, A method for analyzing a user's condition using ketone body information, wherein the user's treatment level includes at least one of a treatment level for pediatric epilepsy and a treatment level for a cancer patient. In the first paragraph, Calculating the user's state information includes calculating the user's state information using a pre-calculated relationship, A method for analyzing a user's status using ketone body information, wherein the above-mentioned pre-calculated relationship includes information on the correlation between the ketone body information and the user's status information. In the first paragraph, Calculating the user's status information includes calculating the user's status information using an analysis model, The above analysis model is a machine learning (ML)-based model that is trained to calculate the user's status information from the user's ketone body information based on learning data, a method for analyzing the user's status using ketone body information. In the first paragraph, The step of the above analysis device obtaining the user's dietary information; and A method for analyzing a user's status using ketone body information, further comprising: a step in which the analysis device analyzes user-customized diet information based on the user's diet information, the user's ketone body information, and the user's status information; In the first paragraph, The step of the above analysis device obtaining the user's exercise information; and A method for analyzing a user's status using ketone body information, further comprising: a step in which the analysis device calculates user-customized exercise information based on the user's exercise information, the user's ketone body information, and the user's status information; In the first paragraph, A step in which the above analysis device obtains user purpose information; A step in which the above analysis device identifies a change pattern in the user's ketone body information based on the user's ketone body information; A step in which the above analysis device predicts future ketone body information based on the identified ketone body information change pattern; and A method for analyzing a user's status using ketone body information, further comprising: a step in which the analysis device predicts a period of time required for the user to achieve a purpose based on the predicted ketone body information and the user's purpose information; In the first paragraph, A step in which the above analysis device analyzes the user's ketone body information change pattern to determine whether there are any abnormal values; and A method for analyzing a user's status using ketone body information, further comprising: a step of the analysis device acquiring additional user ketone body information to replace the abnormal value when the analysis result contains an abnormal value; An input device for obtaining user's ketone body information; A computing device that calculates the user's status information based on the user's ketone body information; and An output device that visualizes and outputs the calculated user status information; including: An analysis device, wherein the user's status information includes at least one of the user's body fat change amount, the user's weight change amount, the user's blood sugar level, and the user's cholesterol level. In Article 10, The above ketone body information is an analysis device including at least one of the user's acetone, acetoacetate and D-β hydroxybutyric acid (D-β) information. In Article 10, The above user's status information further includes the user's level of treatment, An analysis device wherein the treatment level of the user includes at least one of a treatment level of pediatric epilepsy and a treatment level of a cancer patient. In Article 10, Calculating the user's state information includes calculating the user's state information using a pre-calculated relationship, An analysis device wherein the above pre-calculated relationship includes information on the correlation between the ketone body information and the user's status information. In Article 10, Calculating the user's status information includes calculating the user's status information using an analysis model, The above analysis model is an analysis device that is a machine learning (ML)-based model that has been trained to calculate the user's status information from the user's ketone body information based on learning data. In Article 10, The above input device obtains the user's dietary information, The above-mentioned computing device is an analysis device that analyzes customized diet information for the user based on the user's diet information, the user's ketone body information, and the user's status information. In Article 10, The above input device obtains the user's movement information, The above calculation device is an analysis device that calculates user-customized exercise information based on the user's exercise information, the user's ketone body information, and the user's status information. In Article 10, The above input device obtains the user's purpose information, The above-mentioned calculation device is an analysis device that identifies a change pattern of the user's ketone body information based on the user's ketone body information, predicts future ketone body information based on the identified change pattern of ketone body information, and predicts a period of time required for the user to achieve the purpose based on the predicted ketone body information and the user's purpose information. In Article 10, The above-mentioned calculation device is an analysis device that analyzes the change pattern of the user's ketone body information to determine whether there is an abnormal value, and if the analysis result indicates an abnormal value, obtains additional user ketone body information to replace the abnormal value. A computer-readable recording medium storing a program for executing a method for analyzing a user's condition using ketone body information described in Article 1.

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