Health support device and menu providing method

Abstract

To propose a technique for providing a menu suitable for the user's health condition.SOLUTION: A basal metabolic rate estimation unit 40 estimates a user's daily basal metabolic rate. An exercise metabolic rate estimation unit 50 estimates the user's daily exercise metabolic rate. A consumption amount estimation unit 60 estimates the user's daily consumption amount based on the estimated basal metabolic rate and the estimated exercise metabolic rate. A menu determination unit 62 determines a menu for the user based on the estimated consumption amount.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to a technology for supporting a user's health, and in particular to a technology for providing a user with information about menus. [Background technology]

[0002] Lifestyle-related diseases are diseases that develop due to lifestyle habits, and include metabolic syndrome, high blood pressure, dyslipidemia, and diabetes. Regarding the prevention and treatment of diabetes, it is said that it is important to improve one's constitution through exercise so that blood sugar levels are less likely to rise, and to improve one's diet so that blood sugar levels do not rise. It is also said that improving exercise and dietary habits is important for the prevention and treatment of other lifestyle-related diseases.

[0003] Frailty is a condition between a healthy state and a state requiring nursing care, characterized by a decline in physical and cognitive function. When muscle strength and muscle mass decrease due to aging or other factors, activity levels decrease and energy consumption declines. In this state, appetite is lost, leading to a decrease in food intake and a state of malnutrition due to inadequate nutritional intake. If malnutrition continues, muscle strength and muscle mass will decrease, creating a vicious cycle known as the frailty cycle. It is said that frailty can be restored to a healthy state by continuing to exercise moderately and eat a balanced diet.

[0004] To bring subjects closer to a healthy state, it is necessary to at least improve their eating habits, but the current situation is that it is unclear what the appropriate amount of food intake is for preventing and treating lifestyle-related diseases, frailty, etc. In some cases, subjects visit a registered dietitian to receive face-to-face guidance over several months in order to improve their eating habits, but this places a heavy burden on the subjects and the guidance tends to be one-sided.

[0005] In order to reduce the burden of face-to-face instruction, attempts have been made to provide instruction to improve eating habits to subjects via the Internet. In this attempt, the subject sends a questionnaire, the contents of their daily meals, and their weight measurement results to a registered dietitian, who then sends them a video message, recommended menus, a dietary balance guide, and dietary diagnostic advice (see Non-Patent Document 1). This attempt has been carried out on multiple subjects, and a certain degree of effectiveness has been confirmed in the instruction to improve eating habits. [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] Michiko Hashimoto et al., "An Attempt to Provide Nutritional Guidance at the Same Level as Face-to-Face Guidance Using the Internet - Second Report," Journal of the Japan Mibyou System Association, Japan Mibyou System Association, 2007, 13(1), pp.122-124 Summary of the Invention [Problem to be solved by the invention]

[0007] Previously, attempts have been made to provide lifestyle-related disease prevention guidance by sending meal plans to people at risk of developing lifestyle-related diseases. Conventional preventive guidance is based on the subject's BMI (Body Mass Index) and actual food intake (calorie intake), but it cannot be said to be sufficiently effective. Therefore, the present inventor has come up with a method for generating meal plans based on new indicators to promote the subject's health and prevent and treat lifestyle-related diseases and frailty.

[0008] The present disclosure has been made in light of these circumstances, and one of its objectives is to propose a technology for providing a menu suited to the health condition of a user. [Means for solving the problem]

[0009] One aspect of the present disclosure is a health support device that provides a menu to a user, and includes a basal metabolic rate estimation unit that estimates the user's daily basal metabolic rate, an exercise metabolic rate estimation unit that estimates the user's daily exercise metabolic rate, an energy consumption estimation unit that estimates the user's daily energy consumption from the estimated basal metabolic rate and the estimated exercise metabolic rate, and a menu determination unit that determines a menu for the user based on the estimated energy consumption.

[0010] Another aspect of the present disclosure is a menu provision method for providing a menu to a user, comprising the steps of estimating the user's daily basal metabolic rate, estimating the user's daily exercise metabolic rate, estimating the user's daily consumption from the estimated basal metabolic rate and the estimated exercise metabolic rate, determining the user's menu based on the estimated consumption, and providing the user with information regarding the determined menu.

[0011] Any combination of the above components, and conversion of the present disclosure into a method, device, system, recording medium, computer program, etc., are also valid aspects of the present disclosure. [Effects of the Invention]

[0012] According to the present disclosure, a technology can be provided that supports the user's health by providing a menu that is suitable for the user's health condition. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a diagram showing an overview of a health support system according to an embodiment of the present invention; [Figure 2] This figure shows examples of physical activity of 3 METs or more published by the Ministry of Health, Labour and Welfare of Japan. [Figure 3] FIG. 2 is a diagram illustrating functional blocks of the health support device. [Figure 4] FIG. 10 is a diagram showing a body fat percentage determination table. [Figure 5] FIG. 10 is a diagram showing an example of a flowchart for determining the calories of a daily menu. [Figure 6]FIG. 10 is a diagram for explaining a process for estimating a daily consumption of a user A. [Figure 7] FIG. 10 is a diagram for explaining the process of estimating the daily consumption of user B. [Figure 8] FIG. 10 is a diagram for explaining the process of estimating the daily consumption of user C. [Figure 9] FIG. 10 is a diagram showing an example of a menu displayed on the screen of a communication terminal device. DETAILED DESCRIPTION OF THE INVENTION

[0014] Figure 1 shows an overview of a health support system 1 according to an embodiment. The health support system 1 provides a menu suited to the health condition of a subject (hereinafter also referred to as a "user") participating in the system, with the aim of improving the eating habits of the user. Although only one user is shown in Figure 1, in reality, many users may participate in the system.

[0015] In the health support system 1, the health support device 2 functions as a server device, and the user's communication terminal device 8 functions as a client device. The health support device 2 and communication terminal device 8 are connected via a network 3 such as the Internet. The health support device 2 may be configured as a cloud computing system. The menu DB 4 stores a wide variety of daily menus for each daily calorie intake. When the health support device 2 is notified of the user's daily calorie intake, it provides the health support device 2 with menus for one or more days that correspond to that calorie intake. The communication terminal device 8 may be a device with communication and image display functions, such as a smartphone or tablet. The communication terminal device 8 is preferably portable and can be carried by the user, but it may also be a stationary device installed in the home.

[0016] In the health support system 1, the user wears a portable activity meter 7 and transmits data measured by the activity meter 7 (hereinafter referred to as "activity data") to the health support device 2 via a communication terminal device 8. The activity meter 7 measures activity data including information on the user's heart rate and activity level at a predetermined sampling period. The activity meter 7 may be of a type attached to a belt or the like, but a wristband type worn on the arm is preferred so that the user can wear it at all times without difficulty.

[0017] The activity meter 7 is equipped with a triaxial acceleration sensor and has the function of measuring the amount of activity of the user. One of the indicators of physical activity is a unit called exercise (Ex). The amount of exercise indicates how intense the exercise was and for how long, and is calculated by multiplying the intensity of the physical activity (hereinafter referred to as "exercise intensity") by the activity time. In the method of calculating the amount of exercise, the unit of exercise intensity is "METs," and 1 MET corresponds to sitting and resting. Therefore, activity of N METs corresponds to N times the exercise at rest. The activity meter 7 of this embodiment measures exercise intensity (METs) per unit time (e.g., 1 minute) based on the detection value of the triaxial acceleration sensor.

[0018] Figure 2 shows an example of physical activity of 3 METs or more published by the Ministry of Health, Labor and Welfare of Japan. The table shown in Figure 2 is an excerpt from the "2006 Exercise Guidelines for Health Promotion." For example, if you perform 20 minutes of physical activity that requires 3 METs, the amount of exercise is calculated as "3 METs x 1 / 3 hour = 1 exercise." The greater the amount of exercise, the more calories you have burned through the exercise. The activity meter 7 derives exercise intensity (METs) from the values ​​detected by the 3-axis acceleration sensor.

[0019] The activity meter 7 of the embodiment has a function of deriving activity data such as heart rate, number of steps, and exercise intensity (METs) at a sampling period of, for example, one minute, and temporarily storing the data in memory together with time information indicating the timing of the derivation. The activity meter 7 periodically transmits the temporarily stored activity data together with the time information to the health support device 2 via the communication terminal device 8. After transmitting the activity data via the communication terminal device 8, the activity meter 7 deletes the transmitted activity data from memory and temporarily stores the activity data derived every minute again in memory. The activity meter 7 may transmit the activity data to the health support device 2, for example, once a week. The activity meter 7 may also be equipped with a wireless communication function and periodically transmit the activity data to the health support device 2.

[0020] The user measures their weight using the scale 5 and their blood pressure using the sphygmomanometer 6 at set times throughout the day. The user transmits the measured weight data and blood pressure data to the health support device 2 via the communication terminal device 8. If the scale 5 also has a function for measuring body fat percentage, the user transmits weight data including their weight and body fat percentage to the health support device 2 via the communication terminal device 8. The user may transmit the weight data and blood pressure data to the health support device 2 each time they measure their weight, or may transmit the weight data and blood pressure data together with their activity data.

[0021] Health support device 2 has a function of receiving data measured by scale 5, blood pressure monitor 6, and activity meter 7, and then performing various analyses to digitize the user's health condition and exercise status and provide the data to communication terminal device 8, thereby supporting the user's health. Health support device 2 of the embodiment has a function of determining a menu with calorie calculations based on at least weight data and activity data, as part of health support.

[0022] A user can receive health support services from the health support device 2 by starting a predetermined application on the communication terminal device 8 and logging in to the health support device 2. Information about a day's worth of menu items may be transmitted from the health support device 2 to the communication terminal device 8 every day, or information about menu items for a predetermined period (for example, one to two weeks) may be transmitted all at once. The health support device 2 may create a personal page for each user that compiles data about their health condition and exercise status, and allow the user to view detailed information about the number of steps taken each day, and information about changes in weight and blood pressure.

[0023] 3 shows functional blocks of the health support device 2. The health support device 2 includes a data acquisition unit 10, a measurement data storage unit 20, a user data storage unit 22, and a processing unit 30. The data acquisition unit 10 includes a weight data acquisition unit 12, a blood pressure data acquisition unit 14, and an activity data acquisition unit 16. The processing unit 30 includes a basal metabolic rate estimation unit 40, an exercise-related metabolic rate estimation unit 50, an energy consumption estimation unit 60, a menu determination unit 62, and a menu provision unit 64. The basal metabolic rate estimation unit 40 includes a first derivation unit 42, a second derivation unit 44, and a determination unit 46, and the exercise-related metabolic rate estimation unit 50 includes a first derivation unit 52, a second derivation unit 54, and a determination unit 56.

[0024] 3, each element described as a functional block that performs various processes can be configured in hardware by a circuit block, memory, or other LSI, and in software by a program loaded into memory, etc. Therefore, it will be understood by those skilled in the art that these functional blocks can be realized in various forms by hardware alone, software alone, or a combination thereof, and are not limited to any one of them.

[0025] The user data storage unit 22 stores user attribute data linked to information identifying the user (user ID). Here, the attribute data includes gender, age (date of birth), and height. Height may be measured periodically by the user and transmitted to the health support device 2 together with weight data, for example.

[0026] The data acquisition unit 10 acquires measurement data transmitted from the user's communication terminal device 8 and stores it in the measurement data storage unit 20. The weight data acquisition unit 12 acquires weight data including the user's weight and body fat percentage. If the scale 5 used by the user cannot measure the body fat percentage, the weight data acquisition unit 12 acquires weight data including the user's weight. The blood pressure data acquisition unit 14 acquires the user's blood pressure data. The activity data acquisition unit 16 acquires the user's activity data. The activity data includes the heart rate, number of steps, and exercise intensity (METs) associated with time information indicating the timing of measurement. The weight data, blood pressure data, and activity data are linked to information identifying the user (user ID) and stored in the measurement data storage unit 20.

[0027] <Calculating Basal Metabolic Rate> The basal metabolic rate estimation unit 40 has a function of estimating the user's daily basal metabolic rate based on weight data. In the basal metabolic rate estimation unit 40, a first derivation unit 42 calculates the user's basal metabolic rate using lean body mass, which is obtained by subtracting fat mass from body mass. The lean body mass is calculated from body mass and body fat percentage (%) using the following formula: (Lean body mass) = Body weight x (100-Body fat percentage) / 100 In the embodiment, the first derivation unit 42 calculates the basal metabolic rate of the user using the Cunningham equation, which uses the lean body mass. Specifically, the first derivation unit 42 calculates the basal metabolic rate of the user using the following equation (A1). <Cunningham's Law> (basal metabolic rate)=370+21.6×(lean body mass)...Formula (A1) In this way, the first derivation unit 42 calculates the basal metabolic rate using the lean body mass without using the gender and age of the user. Because the basal metabolic rate varies depending on the muscle mass and skeletal mass of the body, it is believed that the Cunningham formula can most accurately calculate the basal metabolic rate of the user.

[0028] The second derivation unit 44 calculates the basal metabolic rate of the user without using the lean body mass. For example, the second derivation unit 44 may calculate the basal metabolic rate of the user using formula (A2) of the Ministry of Health, Labor and Welfare. <Ministry of Health, Labour and Welfare Ceremony> (Basal metabolic rate) = Basal metabolic rate standard value × weight (Equation (A2)) The basal metabolic rate reference value is determined according to the user's gender and age in accordance with Table 1 below. [Table 1] This table is an excerpt from the "Dietary Reference Intakes for Japanese (2020 Edition)" by the Ministry of Health, Labour and Welfare. In this way, the second derivation unit 44 calculates the basal metabolic rate using the user's gender, age, and weight, without using the lean body mass. Formula (A2) can be used when the health support device 2 is able to know the user's gender, age, and weight.

[0029] The second derivation unit 44 may calculate the basal metabolic rate of the user using a calculation formula other than Formula 2. For example, the second derivation unit 44 may calculate the basal metabolic rate of the user using Formula (A3) of the National Institute of Health and Nutrition. <National Institute of Health and Nutrition formula> (Basal metabolic rate (male)) = (0.0481 × weight + 0.0234 × height - 0.0138 × age - 0.4235) × 1,000 / 4.186 (Basal metabolic rate (female)) = (0.0481 × weight + 0.0234 × height - 0.0138 × age - 0.9708) × 1,000 / 4.186 ...Formula (A3) Equation (A3) can be used when the health support device 2 knows the sex, age, weight, and height of the user.

[0030] If the height, sex, and so on of the user are unknown, the second derivation unit 44 can calculate the basal metabolic rate of the user using the following formula (A4). <Formula for calculating 1 MET from exercise intensity> (Basal metabolic rate) = 1 [METs] × 0.0175 × body weight × 60 [minutes] × 24 [hours] Formula (A4) Here, we assume that the oxygen intake at rest is 3.5 [ml / kg min] and the energy expenditure per liter of oxygen consumed is 5 [kcal / l]. (3.5 [ml / kg min] x 5 [kcal / l] = 0.0175 [kcal / kg min]) Formula (A4) can be used when the health support device 2 is able to grasp the weight of the user. When formula (A2) or formula (A3) can be used, the second derivation unit 44 does not need to calculate the basal metabolic rate using formula (A4).

[0031] The determination unit 46 determines, based on a predetermined criterion, either the basal metabolic rate calculated by the first derivation unit 42 or the basal metabolic rate calculated by the second derivation unit 44 as the estimated value of the user's basal metabolic rate. The determination unit 46 may determine the larger of the basal metabolic rate calculated by the first derivation unit 42 or the basal metabolic rate calculated by the second derivation unit 44 as the estimated value of the user's basal metabolic rate.

[0032] FIG. 4(a) shows a body fat percentage determination table for men, and FIG. 4(b) shows a body fat percentage determination table for women. Referring to Figure 4(a), males up to 14 years old are judged to be mildly obese or obese if their body fat percentage is 25% or more, males aged 15 to 17 years old are judged to be mildly obese or obese if their body fat percentage is 24% or more, males aged 18 to 39 years old are judged to be mildly obese or obese if their body fat percentage is 22% or more, males aged 40 to 59 years old are judged to be mildly obese or obese if their body fat percentage is 23% or more, and males aged 60 years old or older are judged to be mildly obese or obese if their body fat percentage is 25% or more. Also, referring to Figure 4(b), females up to 14 years old are judged to be mildly obese or obese if their body fat percentage is 34% or higher, females aged 15 to 17 years old are judged to be mildly obese or obese if their body fat percentage is 36% or higher, females aged 18 to 39 years old are judged to be mildly obese or obese if their body fat percentage is 35% or higher, females aged 40 to 59 years old are judged to be mildly obese or obese if their body fat percentage is 36% or higher, and females aged 60 years old or older are judged to be mildly obese or obese if their body fat percentage is 37% or higher.

[0033] When the user's body fat percentage is higher than the standard body fat percentage derived from the user's gender and age, the determination unit 46 may determine the basal metabolic rate calculated by the second derivation unit 44 as the estimated value of the user's basal metabolic rate, rather than determining the basal metabolic rate calculated by the first derivation unit 42 as the estimated value of the user's basal metabolic rate. In other words, when the user's body fat percentage is a body fat percentage that is determined to be mild obesity or obesity, the determination unit 46 may determine the basal metabolic rate calculated by the second derivation unit 44 as the estimated value of the user's basal metabolic rate.

[0034] <Calculation of exercise metabolic rate> The exercise metabolic rate estimation unit 50 has a function of estimating the user's daily exercise metabolic rate based on the activity data. In the exercise metabolic rate estimation unit 50, the first derivation unit 52 calculates the user's exercise metabolic rate using the heart rate included in the activity data. The heart rate increases as the intensity of exercise increases, so it is a highly reliable indicator of exercise intensity. (1) First, the first derivation unit 52 calculates the maximum heart rate as follows. (Maximum heart rate) = 220 - age (2) The first derivation unit 52 calculates the exercise intensity [%] based on the heart rate as follows. Exercise intensity [%] = (average heart rate during exercise - resting heart rate) / (maximum heart rate - resting heart rate) (3) The first lead-out section 52 calculates the maximum amount of oxygen (VO2max) taken into the body during exercise as follows. VO2max [ml / kg min] = 15 x (maximum heart rate / resting heart rate) (4) The first outlet 52 calculates the oxygen consumption amount as follows. Oxygen consumption [ml] = exercise intensity [%] x VO2max x body weight x exercise time (5) From the above, the first derivation unit 52 calculates the exercise-induced calorie expenditure (exercise metabolic rate) using the following formula (B1). <Formula for calculating heart rate> (Exercise metabolic rate) = oxygen consumption [ml] × 5 [kcal / l] Formula (B1) As described above, 5 kcal / l corresponds to the amount of energy consumed when consuming 1 liter of oxygen. The first derivation section 52 may calculate the exercise metabolic rate for each predetermined time period (for example, 1 minute).

[0035] The second derivation unit 54 calculates the user's exercise metabolic rate using the exercise intensity (METs) included in the activity data. For example, the second derivation unit 44 calculates the exercise metabolic rate from the exercise intensity expressed in METs using the following formula (B2). (Exercise metabolic rate) = (exercise intensity [METs] - 1) x 0.0175 x body weight x duration [min] Here, we assume that the oxygen intake at an exercise intensity of 1 MET is 3.5 ml / kg / min, and the energy expenditure when consuming 1 liter of oxygen is 5 kcal / l (3.5 ml / kg min x 5 kcal / l = 0.0175 kcal / kg min). The second derivation section 54 may calculate the exercise metabolic rate for each predetermined time period (for example, one minute).

[0036] The determination unit 56 determines, based on a predetermined criterion, either the exercise metabolic rate calculated by the first derivation unit 52 or the exercise metabolic rate calculated by the second derivation unit 54 as the estimated value of the user's exercise metabolic rate. When both the first derivation unit 52 and the second derivation unit 54 calculate the exercise metabolic rate every minute, the determination unit 56 determines, for every minute, either the exercise metabolic rate calculated by the first derivation unit 52 or the exercise metabolic rate calculated by the second derivation unit 54 as the estimated value of the user's exercise metabolic rate. The determination unit 56 may determine the larger of the exercise metabolic rate calculated by the first derivation unit 52 or the exercise metabolic rate calculated by the second derivation unit 54 as the estimated value of the user's exercise metabolic rate.

[0037] As described above, heart rate correlates with exercise intensity, making it a highly reliable indicator of exercise intensity. The activity meter 7 of this embodiment is worn on the user's wrist and measures exercise intensity in units of METs based on the detection values ​​of a triaxial acceleration sensor. For example, when a user is pedaling a bicycle at full power, the heart rate increases in accordance with the exercise intensity. However, because the user is holding the handlebars of the bicycle, the user's arms do not move vigorously, and the detection values ​​of the triaxial acceleration sensor are unlikely to increase. Therefore, the exercise intensity (METs) derived from the detection values ​​of the triaxial acceleration sensor tends to be lower than the actual exercise intensity. Therefore, the exercise metabolic rate calculated from the heart rate is usually greater than the exercise metabolic rate calculated from the detection values ​​of the triaxial acceleration sensor, and the determination unit 56 determines the exercise metabolic rate calculated by the first derivation unit 52 as the estimated value of the user's exercise metabolic rate.

[0038] On the other hand, it is known that the measurement accuracy of a heart rate monitor gradually deteriorates as the heart rate increases, and as the heart rate increases, the heart rate monitor tends to measure a lower heart rate than the actual heart rate. Therefore, when the exercise metabolic rate calculated by the first derivation unit 52 is lower than the exercise metabolic rate calculated by the second derivation unit 54, the determination unit 56 may determine the exercise metabolic rate calculated by the second derivation unit 54 as an estimated value of the user's exercise metabolic rate.

[0039] The consumption estimation unit 60 estimates the user's daily consumption (calories consumed) from the basal metabolic rate estimated by the basal metabolic rate estimation unit 40 and the exercise metabolic rate estimated by the exercise metabolic rate estimation unit 50. Specifically, the consumption estimation unit 60 estimates the user's daily consumption from the estimated value of the basal metabolic rate determined by the determination unit 46 and the estimated value of the exercise metabolic rate determined by the determination unit 56. The consumption estimation unit 60 calculates the consumption using the following formula (C1). (Amount consumed) = Basal metabolic rate + Exercise metabolic rate...Formula (C1)

[0040] The menu determination unit 62 determines a menu for the user based on the estimated consumption. Specifically, the menu determination unit 62 determines a menu for the user by regarding the estimated daily consumption (calories consumed) as the daily food intake (calories ingested). The menu DB4 records various seasonal meal menus for each calorie intake, and the menu determination unit 62 obtains from the menu DB4 a menu with an intake calorie level that approximately matches the user's daily consumption. Note that if the daily consumption is P [kcal], the menu determination unit 62 preferably determines a menu that results in a daily intake calorie of P [kcal]. However, since it is difficult to exactly match the daily intake calorie to P [kcal], for example, the menu may be determined so that the total intake calorie of the menu for one week is 7P [kcal]. The menu providing unit 64 provides information about the determined menu to the user's communication terminal device 8.

[0041] 5 shows an example of a flowchart for determining the calories of a daily menu. If the user's weight data includes a body fat percentage and the lean body mass can be calculated from the weight and body fat percentage (Y in S10), the first derivation unit 42 calculates the basal metabolic rate using formula (A1) (S12). If the user's body fat percentage is equal to or lower than the standard body fat percentage derived from the user's gender and age (N in S14), the determination unit 46 determines the basal metabolic rate calculated using formula (A1) as the estimated value of the user's basal metabolic rate (S20). On the other hand, if the user's body fat percentage is higher than the standard body fat percentage and the user is determined to be mildly obese or obese (Y in S14), the second derivation unit 44 calculates the basal metabolic rate using formula (A2) (S16), and the determination unit 46 determines the basal metabolic rate calculated using formula (A2) as the estimated value of the user's basal metabolic rate (S20).

[0042] If the lean body mass cannot be calculated (N in S10), the second derivation unit 44 calculates the basal metabolic rate using formula (A3) (S18). Since height data is required to use formula (A3), if there is no height data, the second derivation unit 44 calculates the basal metabolic rate using formula (A4) (S18). The determination unit 46 determines the basal metabolic rate calculated using formula (A3) or formula (A4) as the estimated value of the user's basal metabolic rate (S20).

[0043] Next, the exercise-related metabolic rate estimation unit 50 calculates the exercise-related metabolic rate based on the activity data. Specifically, the first derivation unit 52 calculates the exercise-related metabolic rate using formula (B1), and the second derivation unit 54 calculates the exercise-related metabolic rate using formula (B2) (S22). If the exercise-related metabolic rate calculated using formula (B1) is equal to or greater than the exercise-related metabolic rate calculated using formula (B2) (Y in S24), the determination unit 56 determines the exercise-related metabolic rate calculated using formula (B1) as the estimated value of the user's exercise-related metabolic rate (S26). On the other hand, if the exercise-related metabolic rate calculated using formula (B1) is less than the exercise-related metabolic rate calculated using formula (B2) (N in S24), the determination unit 56 determines the exercise-related metabolic rate calculated using formula (B2) as the estimated value of the user's exercise-related metabolic rate (S28).

[0044] Once the estimated basal metabolic rate and the estimated activity-based metabolic rate are determined as described above, the consumption estimation unit 60 adds the estimated basal metabolic rate and the estimated activity-based metabolic rate (equation (C1)) to estimate the user's daily consumption (S30). The menu determination unit 62 determines the user's daily menu based on the estimated daily consumption (S32).

[0045] Below, a method for estimating the daily consumption (calories consumed) of various users will be described using specific examples. (For User A) FIG. 6(a) shows information about user A, an athlete. User A's BMI is 25.06. Generally, health assessments based on BMI indicate that a BMI of 25 or higher is outside the appropriate range, and so conventional dietary advice would advise user A to reduce his calorie intake. However, user A's body fat percentage is 12%, meaning he is neither slightly obese nor obese, so reducing his calorie intake is not recommended.

[0046] 6(b) shows the weekly exercise metabolic rate (calories burned during exercise) of user A. The average of this exercise metabolic rate is 1984 kcal / day. 6(c) shows an example of the basal metabolic rate calculated using formula (A1) and formula (A2). In this example, since user A's body fat percentage is 12%, formula (A1), which uses lean body mass, calculates a higher basal metabolic rate than formula (A2).

[0047] In this example of user A, the consumption estimation unit 60 adds the basal metabolic rate (1796 [kcal]), which is the larger calculation result, to the exercise metabolic rate (1984 [kcal]), and estimates user A's daily consumption to be 3780 [kcal]. Based on this estimation result, the menu determination unit 62 determines a daily menu for user A so that the daily calorie intake will be approximately 3780 [kcal]. In this way, according to the method of the embodiment, it is possible to set the daily calorie intake regardless of BMI.

[0048] (User B) FIG. 7(a) shows information about User B, who is frail. User B's BMI is 17.78, indicating that he or she is underweight. Generally, if the BMI is less than 18.5, the user is determined to be underweight, and dietary advice is given to User B to advise him or her to increase his or her calorie intake. However, there are currently no effective standards for determining how much an increase in calorie intake is appropriate.

[0049] 7(b) shows the weekly exercise metabolic rate (calories burned during exercise) of user B. The average of this exercise metabolic rate is 43 kcal / day. 7(c) shows an example of the basal metabolic rate calculated using formula (A1) and formula (A2). In this example, since user B's body fat percentage is 12%, formula (A1), which uses lean body mass, calculates a higher basal metabolic rate than formula (A2).

[0050] In this example of user B, the consumption estimation unit 60 adds the basal metabolic rate (1130 [kcal]), which is the larger calculation result, to the activity metabolic rate (43 [kcal]), and estimates user B's daily consumption to be 1174 [kcal]. Based on this estimation result, the menu determination unit 62 determines a daily menu for user B so that the daily calorie intake will be approximately 1174 [kcal]. It is estimated that user B, who is in such a frail state, currently has a daily calorie intake of around 800 [kcal], and this is probably why user B has not been able to escape from the frail state. Therefore, by determining a menu so that user B's daily calorie intake will be 1174 [kcal], it is possible to support user B in returning to a healthy state.

[0051] (User C) Figure 8(a) shows information about user C, who is metabolically obese. User C's body fat percentage is 28.9, indicating that he is obese (see Figure 4(a)). Therefore, user C needs to reduce his daily calorie intake, but there is currently no effective standard for determining how much of a calorie intake reduction is appropriate.

[0052] 8(b) shows the weekly exercise metabolic rate (calories burned through exercise) of user C. The average of this exercise metabolic rate is 744 kcal / day. 8(c) shows an example of the basal metabolic rate calculated using formula (A1) and formula (A2). In this example, since user B is obese, formula (A1), which uses lean body mass, calculates a lower basal metabolic rate than formula (A2).

[0053] In this example of user C, the consumption estimation unit 60 adds the basal metabolic rate (1612 [kcal]), which is the larger calculation result, to the activity metabolic rate (744 [kcal]), and estimates user C's daily consumption to be 2356 [kcal]. Based on this estimation result, the menu determination unit 62 determines a daily menu for user C so that the daily calorie intake will be approximately 2356 [kcal]. It is estimated that the current daily calorie intake of such metabolically obese user C is probably 2500 [kcal] or more, and therefore it is thought that the obesity state has not been resolved. Therefore, by determining a menu so that user C's daily calorie intake will be 2356 [kcal], it is possible to support user C in returning to a healthy state.

[0054] If the basal metabolic rate (1522 [kcal]) calculated using formula (A1) is added to the activity metabolic rate (744 [kcal]), the estimated daily calorie intake for user C is 2266 [kcal]. If a menu is determined for user C so that the daily calorie intake is 2266 [kcal] and user C can live each day with that menu, user C can quickly return to a healthy state, but it is often difficult for obese people to suppress their appetite. Therefore, in this embodiment, the larger calculated basal metabolic rate (1612 [kcal]) is used to determine the user's daily calorie intake, thereby supporting user C to return to a healthy state without strain.

[0055] 9 shows an example of a menu displayed on the screen of communication terminal device 8. The menu screen displays icons related to other health support services provided by health support device 2, in this case, dietary balance checks and quizzes. When menu providing unit 64 transmits information related to the menu to communication terminal device 8, the user can view a menu with calorie calculations tailored to the user.

[0056] The present disclosure has been described above based on examples. These examples are merely illustrative, and it will be understood by those skilled in the art that various modifications are possible in the combination of the components and processing steps, and that such modifications are also within the scope of the present disclosure.

[0057] An overview of an aspect of the present disclosure is as follows: A health support device of an aspect of the present disclosure includes a basal metabolic rate estimation unit that estimates a user's daily basal metabolic rate, an exercise-induced metabolic rate estimation unit that estimates the user's daily exercise-induced metabolic rate, an energy consumption estimation unit that estimates the user's daily energy consumption from the estimated basal metabolic rate and the estimated exercise-induced metabolic rate, and a menu determination unit that determines a menu for the user based on the estimated energy consumption.

[0058] According to this embodiment, by determining a menu for a user based on the amount of food consumed (calories consumed) by the user in one day, it is possible to appropriately set the calorie intake of the user in one day.

[0059] The health support device may further include an activity data acquisition unit that acquires activity data of the user, and the exercise metabolic rate estimation unit may include a first derivation unit that calculates the user's exercise metabolic rate using a heart rate included in the activity data, a second derivation unit that calculates the user's exercise metabolic rate using an exercise intensity included in the activity data, and a determination unit that determines, based on a predetermined criterion, either the exercise metabolic rate calculated by the first derivation unit or the exercise metabolic rate calculated by the second derivation unit as an estimated value of the user's exercise metabolic rate. By determining, as an estimated value of the user's exercise metabolic rate, either the exercise metabolic rate calculated using the heart rate included in the activity data or the exercise metabolic rate calculated using the exercise intensity included in the activity data, it is possible to properly estimate the exercise metabolic rate.

[0060] The determination unit may determine the larger of the exercise metabolic rate calculated by the first derivation unit or the exercise metabolic rate calculated by the second derivation unit as the estimated value of the exercise metabolic rate of the user.

[0061] The basal metabolic rate estimation unit may include a first derivation unit that calculates the user's basal metabolic rate using lean body mass, which is body weight minus fat mass, a second derivation unit that calculates the user's basal metabolic rate without using lean body mass, and a determination unit that determines either the basal metabolic rate calculated by the first derivation unit or the basal metabolic rate calculated by the second derivation unit as an estimated value of the user's basal metabolic rate based on a predetermined standard. By determining either the basal metabolic rate calculated using lean body mass or the basal metabolic rate calculated without using lean body mass as the estimated value of the user's basal metabolic rate, it is possible to properly estimate the basal metabolic rate.

[0062] The first derivation unit may calculate the basal metabolic rate without using the user's gender and age, and the second derivation unit may calculate the basal metabolic rate using the user's gender and age. The determination unit may determine the larger of the basal metabolic rate calculated by the first derivation unit or the basal metabolic rate calculated by the second derivation unit as the estimated value of the user's basal metabolic rate.

[0063] The basal metabolic rate estimation unit may further include a weight data acquisition unit that acquires the user's body fat percentage, and the determination unit may determine the basal metabolic rate calculated by the second derivation unit as an estimated value of the user's basal metabolic rate when the user's body fat percentage is higher than a standard body fat percentage derived from the user's gender and age.

[0064] A menu provision method according to one aspect of the present disclosure includes the steps of estimating a user's daily basal metabolic rate, estimating the user's daily exercise metabolic rate, estimating the user's daily consumption from the estimated basal metabolic rate and the estimated exercise metabolic rate, determining a menu for the user based on the estimated consumption, and providing the user with information about the determined menu.

[0065] According to this embodiment, by determining a menu for a user based on the amount of food consumed (calories consumed) by the user in one day, it is possible to appropriately set the calorie intake of the user in one day.

[0066] A program according to one aspect of the present disclosure enables a computer to perform the following functions: estimate a user's daily basal metabolic rate; estimate a user's daily exercise metabolic rate; estimate the user's daily consumption amount from the estimated basal metabolic rate and the estimated exercise metabolic rate; determine a menu for the user based on the estimated consumption amount; and provide the user with information about the determined menu.

[0067] According to this embodiment, by determining a menu for a user based on the amount of food consumed (calories consumed) by the user in one day, it is possible to appropriately set the calorie intake of the user in one day. [Explanation of symbols]

[0068] 1 Health support system, 2 Health support device, 3 Network, 4 Menu database, 5 Weight scale, 6 Blood pressure monitor, 7 Activity meter, 8 Communication terminal device, 10 Data acquisition unit, 12 Weight data acquisition unit, 14 Blood pressure data acquisition unit, 16 Activity data acquisition unit, 20 Measurement data storage unit, 22 User data storage unit, 30 Processing unit, 40 Basal metabolic rate estimation unit, 42 First derivation unit, 44 Second derivation unit, 46 Determination unit, 50 Exercise metabolic rate estimation unit, 52 First derivation unit, 54 Second derivation unit, 56 Determination unit, 60 Energy consumption estimation unit, 62 Menu determination unit, 64 Menu provision unit.

Claims

1. A health support device that provides a menu to a user, a basal metabolic rate estimation unit that estimates a daily basal metabolic rate of the user; an exercise metabolic rate estimation unit that estimates the user's daily exercise metabolic rate; a consumption estimation unit that estimates the user's daily consumption based on the estimated basal metabolic rate and the estimated exercise metabolic rate; a menu determination unit that determines a menu for the user based on the estimated consumption amount; A health support device comprising:

2. further comprising an activity data acquisition unit that acquires activity data of the user; The exercise metabolic rate estimation unit a first derivation unit that calculates the user's exercise metabolic rate using the heart rate included in the activity data; a second derivation unit that calculates the user's exercise metabolic rate using the exercise intensity included in the activity data; a determination unit that determines, based on a predetermined criterion, either the exercise metabolic rate calculated by the first derivation unit or the exercise metabolic rate calculated by the second derivation unit as an estimated value of the exercise metabolic rate of the user; 2. The health support device according to claim 1, further comprising:

3. The determination unit determines the larger of the exercise metabolic rate calculated by the first derivation unit and the exercise metabolic rate calculated by the second derivation unit as the estimated value of the exercise metabolic rate of the user.

3. The health support device according to claim 2.

4. The basal metabolic rate estimation unit a first derivation unit that calculates the basal metabolic rate of the user using a lean body mass obtained by subtracting fat mass from body weight; a second derivation unit that calculates the basal metabolic rate of the user without using the lean body mass; a determination unit that determines either the basal metabolic rate calculated by the first derivation unit or the basal metabolic rate calculated by the second derivation unit as an estimated value of the user's basal metabolic rate based on a predetermined criterion; 2. The health support device according to claim 1, further comprising:

5. the first derivation unit calculates the basal metabolic rate without using the gender and age of the user; the second derivation unit calculates the basal metabolic rate using the user's gender, age, and weight; 5. The health support device according to claim 4.

6. the determination unit determines the larger of the basal metabolic rate calculated by the first derivation unit and the basal metabolic rate calculated by the second derivation unit as the estimated value of the user's basal metabolic rate; 5. The health support device according to claim 4.

7. The basal metabolic rate estimation unit a weight data acquisition unit that acquires the user's body fat percentage; the determination unit determines the basal metabolic rate calculated by the second derivation unit as the estimated value of the basal metabolic rate of the user when the user's body fat percentage is higher than a standard body fat percentage derived from the user's gender and age.

5. The health support device according to claim 4.

8. A menu provision method for providing a menu to a user, estimating a user's daily basal metabolic rate; estimating a user's daily exercise metabolic rate; estimating the user's daily energy consumption from the estimated basal metabolic rate and the estimated exercise metabolic rate; determining a menu for the user based on the estimated consumption; providing information about the determined menu to a user; A menu providing method characterized by having the following.

9. On the computer, A function to estimate the user's daily basal metabolic rate, A function to estimate the user's daily exercise metabolic rate, A function to estimate the user's daily energy consumption from the estimated basal metabolic rate and the estimated exercise metabolic rate; A function to determine a menu for the user based on the estimated consumption amount; A function to provide the user with information about the determined menu; A program to achieve this.

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