Deep part body temperature estimation device

Abstract

To provide a deep part body temperature estimation device capable of accurately estimating a deep part body temperature of a bather taking a bath.SOLUTION: A deep part body temperature estimation device 1 includes: a control unit 41 for executing deep part body temperature estimation processing for estimating a deep part body temperature of a bather P1; and detection means 50 and 60 for detecting bathing information on the bather P1. The detection means 50 and 60 includes at least one of biological information detection means 50 for detecting biological information at least including a vital state of the bather P1 as bathing information, and bathing condition information detection means 60 for detecting bathing condition information on a condition during bathing of the bather P1 as bathing information. The control unit 41 can acquire exercise habit information digitized on the basis of a past exercise performance of the bather P1. The control unit 41 executes deep part body temperature estimation processing with the bathing information and the exercise habit information as parameters.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention relates to a deep body temperature estimation device.

Background Art

[0002] Patent Document 1 discloses an example of a conventional deep body temperature estimation device. This deep body temperature estimation device includes an estimation unit that estimates the deep body temperature of a subject.

[0003] The estimation unit uses, as input information, information on the exercise load, information on age, information on weight and height, information on skin surface temperature, and information on heart rate of a plurality of subjects, and uses the measured values of the rectal temperature of the plurality of subjects as output information to perform machine learning to obtain a learned model.

[0004] Then, the estimation unit receives, as parameters, information on the exercise load, information on age, information on weight and height, information on skin surface temperature, and information on heart rate of the subject to be measured, and inputs the information into the learned model to estimate the deep body temperature of the subject to be measured.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] By the way, for example, in order to infer the health condition of a bather, infer the health promotion effect of bathing, or propose bathing conditions for improving the quality of sleep after bathing, it is required to accurately estimate the deep body temperature of the bather in the bathtub during bathing.

[0007] In this regard, Patent Document 1 has no description or suggestion regarding the use of the above-described conventional deep body temperature estimation device for estimating the deep body temperature of a bather in a bathtub during bathing.

[0008] Also, the exercise load of a bather during bathing is not high. According to the MET table that quantifies the intensity of physical activity and exercise, the exercise intensity (MET) of bathing is 1.5, which is the same level as eating or office work (sitting).

[0009] Therefore, even if this deep body temperature estimation device is applied to a bather during bathing, the information regarding the exercise load of the bather will only be information with little variation, and it is considered difficult to use the exercise load of the bather as a parameter for estimating the deep body temperature. That is, this deep body temperature estimation device needs to be improved in order to accurately estimate the deep body temperature of a bather during bathing.

[0010] The present invention has been made in view of the above-described conventional circumstances, and an object to be solved is to provide a deep body temperature estimation device capable of accurately estimating the deep body temperature of a bather during bathing.

Means for Solving the Problem

[0011] The deep body temperature estimation device of the present invention includes a control unit that executes a deep body temperature estimation process for estimating the deep body temperature of a bather in a bathtub during bathing, detection means for detecting bath information regarding the bather during bathing, the bath information being the quantified bath information, and is a deep body temperature estimation device provided with wherein the detection means has at least one of biological information detection means for detecting biological information including at least the vital state of the bather as the bath information, and bath condition information detection means for detecting bath condition information regarding the conditions of the bather during bathing as the bath information, and the control unit is capable of acquiring quantified exercise habit information based on the past exercise achievements of the bather, ​The control unit is characterized by executing the deep body temperature estimation process using the bathing information and the exercise habit information as parameters.

[0012] In the deep body temperature estimation device of the present invention, the detection means has at least one of a biological information detection means and a bathing condition information detection means.

[0013] The biological information of the bather detected by the biological information detection means as bathing information includes at least the vital state of the bather. The vital state is, for example, the bather's heart rate, blood flow volume, sweating amount, etc.

[0014] The bathing condition information detected by the bathing condition information detection means as bathing information is, for example, the temperature of the hot water stored in the bathtub, the elapsed time since the bather started bathing, the temperature of the bathroom where the bathtub is installed, etc.

[0015] The exercise habit information acquired by the control unit is, for example, the frequency of exercise, the required time for exercise, the intensity of exercise, etc.

[0016] The control unit executes the deep body temperature estimation process using such bathing information and exercise habit information as parameters.

[0017] Here, people with a daily exercise habit tend to have a higher vasodilation function and a greater tendency for increased blood flow volume compared to those without an exercise habit in order to dissipate the heat of the body increased by exercise or the like. Therefore, people with a daily exercise habit tend to have a greater tendency for increased blood flow volume in a hot environment.

[0018] Since the hot water stored in the bathtub and in which the bather is immersed during bathing has a temperature higher than the bather's body temperature, it is considered that when a person with an exercise habit takes a bath, the blood flow volume of that bather tends to increase. And since the hot water stored in the bathtub has a larger heat capacity than air, the heat exchange between the body surface of the bather and the hot water is promoted, and the heat transmitted from the hot water to the blood in the body via the body surface easily moves to the deep part of the body by blood circulation. As a result, it is considered that the deep body temperature tends to rise.

[0019] Thus, since there is considered to be a correlation between the deep body temperature during bathing and exercise habits, exercise habit information is suitable as a parameter for estimating the deep body temperature during bathing.

[0020] Therefore, the deep body temperature estimation device of the present invention can accurately estimate the deep body temperature of a bather during bathing.

[0021] The exercise habit information is preferably information based on the number of days on which exercise of a predetermined amount or more has been performed for a predetermined time or more in a past predetermined period.

[0022] By using such specific exercise habit information, the deep body temperature of a bather during bathing can be estimated more accurately.

[0023] The deep body temperature estimation device of the present invention is a portable information terminal that is routinely carried by a bather, and includes a portable information terminal that stores the exercise record of the bather and calculates exercise habit information, and an external server that acquires exercise habit information from the portable information terminal by network communication. It is desirable to further include a communication unit capable of communicating with at least one of them. And it is desirable that the control unit acquires exercise habit information via the communication unit.

[0024] In this case, the control unit can use the exercise habit information of the bather updated by the portable information terminal as a parameter for deep body temperature estimation processing. Thereby, even if the bather does not perform a special operation for causing the control unit to acquire exercise habit information, such as an input operation of exercise record, etc., on the deep body temperature estimation device, the control unit can execute deep body temperature estimation processing, so that improvement in convenience can be realized.

[0025] The detection means preferably includes at least biological information detection means. And the biological information detection means preferably includes at least one of a heart rate detection means for detecting the heart rate of the bather as a vital state, a blood flow detection means for detecting the blood flow of the bather as a vital state, and a sweating amount detection means for detecting the sweating amount of the bather as a vital state.

[0026] In this case, since the biological information used as a parameter for the control unit to estimate the core body temperature includes at least one of the heart rate, blood flow rate, and sweating amount of the bather, the core body temperature of the bather during bathing can be estimated with higher accuracy.

[0027] The detection means preferably has bathing condition information detection means. And the bathing condition information detection means preferably has at least one of a hot water temperature detection means for detecting the temperature of the hot water stored in the bathtub, a bathing elapsed time detection means for detecting the elapsed time since the bather started bathing, and a bathroom temperature detection means for detecting the temperature of the bathroom where the bathtub is installed.

[0028] In this case, since the bathing condition information used as a parameter for the control unit to estimate the core body temperature includes at least one of the temperature of the hot water stored in the bathtub, the bathing elapsed time, and the temperature of the bathroom, the core body temperature of the bather during bathing can be estimated with higher accuracy.

[0029] The control unit preferably can acquire sleep time information quantified based on the bather's past sleep record. And it is desirable for the control unit to execute core body temperature estimation processing using the bathing information, exercise habit information, and sleep time information as parameters.

[0030] The sleep time information obtained by the control unit is, for example, the average value or median value of the sleep time in a past predetermined period, the number of days with a sleep time of a predetermined time or more in a past predetermined period, and the like. When comparing the case where the daily sleep time tends to be long and the case where it tends to be short, it is considered that the autonomic nerves (the balance between the sympathetic nerves and the parasympathetic nerves) are more easily adjusted in the case where the sleep time tends to be long, and the adjustment of blood flow can be smoothly performed. For this reason, a bather whose daily sleep time tends to be long has a tendency for the blood flow to easily increase in a hot environment. In addition, since the hot water in which the bather soaking during bathing is stored in the bathtub has a temperature higher than the body temperature of the bather, when a person with a long daily sleep time takes a bath, it is considered that the blood flow of the bather easily increases. And, since the hot water stored in the bathtub has a larger heat capacity than air, the heat exchange between the body surface of the bather and the hot water is promoted, and the heat transmitted from the hot water to the blood in the body via the body surface easily moves to the deep part of the body by blood circulation. As a result, it is considered that the deep body temperature easily rises. Thus, since it is considered that there is a correlation between the deep body temperature during bathing and the sleep time, the sleep time information is suitable as a parameter for estimating the deep body temperature during bathing. Therefore, this deep body temperature estimation device can more accurately estimate the deep body temperature of the bather during bathing.

[0031] It is desirable that the deep body temperature estimation device of the present invention further includes a communication unit capable of communicating with at least one of a sleep time information terminal that stores the bathing person's sleep record and calculates sleep time information, and an external server that acquires sleep time information from the sleep time information terminal by network communication. And it is desirable that the control unit acquires the sleep time information via the communication unit.

[0032] In this case, the control unit can use the sleep time information of the bather updated by the sleep time information terminal as a parameter for the deep body temperature estimation process. Thereby, even if the bather does not perform a special operation for causing the control unit to acquire the sleep time information, for example, an input operation of the sleep record, etc. on the deep body temperature estimation device, the control unit can execute the deep body temperature estimation process, so that an improvement in convenience can be realized.

Effect of the Invention

[0033] According to the deep body temperature estimation device of the present invention, the deep body temperature of a bather can be estimated with high accuracy. [Brief description of the drawings]

[0034] [Figure 1] FIG. 1 is a schematic diagram of a house to which the deep body temperature estimation device of the embodiment is applied. [Figure 2] FIG. 2 is a block diagram of a house to which the deep body temperature estimation device of the embodiment is applied. [Figure 3] FIG. 3 is a flowchart of a deep body temperature estimation program for the deep body temperature estimation device of the embodiment. [Figure 4] FIG. 4 is a flowchart of a deep body temperature estimation program for the deep body temperature estimation device of the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0035] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, specific embodiments of the present invention will be described with reference to the drawings.

[0036] (Example) As shown in Figure 1, the core body temperature estimation device 1 of the embodiment is an example of a specific aspect of the core body temperature estimation device of the present invention, and is applied to a house H1. The house H1 has multiple rooms such as a living room and bedrooms, as well as a bathroom R1 and a kitchen R2. A hot water supply device 90 is also installed in the house H1.

[0037] The bathroom R1 is equipped with a bathtub 3, a mixer tap 5, a shower 5A, and a bathroom remote control 10. The kitchen R2 is equipped with a kitchen remote control 20.

[0038] Bather P1, who bathes in bathtub 3 of bathroom R1, is a resident of house H1 and lives his / her daily life by moving between rooms in house H1 and going out from house H1. Bather P1 when not bathing is referred to as subject P1A (bather P1).

[0039] Subject P1A (bather P1) wears the smartwatch 30 on the wrist and carries it around daily. The smartwatch 30 is an example of the "portable information terminal" and "sleep time information terminal" of the present invention.

[0040] <Water heater> The water heater 90 has a well-known configuration, so the description will be simplified. It has a gas burner, a heat exchanger, a circulation pump, etc. (not shown). The gas burner burns fuel gas such as city gas to generate high-temperature combustion gas. The water heater 90 circulates the water supplied from a water supply such as a water pipe in the heat exchanger, and heats the water by performing heat exchange with the combustion gas generated by the gas burner, and discharges hot water.

[0041] The water heater 90 supplies hot and cold water to the mixing faucet 5 and the shower 5A via the pipe P5. Also, the water heater 90 supplies hot and cold water to the bathtub 3 via the bathtub supply pipe P3A. The water heater 90 can execute an automatic filling operation for automatically filling the bathtub 3, a supplementary hot water operation for adding hot water to the bathtub 3, and a supplementary water operation for adding water to the bathtub 3.

[0042] Furthermore, the water heater 90 can execute a reheating operation in which hot and cold water is circulated between the bathtub 3, the bathtub return pipe P3B, the heat exchanger, and the bathtub supply pipe P3A by a circulation pump (not shown) and heated by the gas burner.

[0043] As shown in FIGS. 1 and 2, the water heater 90 has a hot water supply control unit 91. The hot water supply control unit 91 is an electronic circuit unit including a CPU (not shown), a storage unit 91M composed of storage elements such as a ROM and a RAM, an interface circuit, etc. The hot water supply control unit 91 executes control processing related to the operations of the gas burner, heat exchanger, circulation pump, etc. of the water heater 90.

[0044] The storage unit 91M stores various programs and setting information for operating the water heater 90, etc. Also, the storage unit 91M appropriately stores various information acquired by the hot water supply control unit 91 during the operation of the water heater 90, etc.

[0045] The water heater 90 has a water temperature sensor 92 and a water level sensor 93 .

[0046] Hot water temperature sensor 92 measures at least one of the temperature of the hot water sent from water heater 90 to bathtub 3 and the temperature of the hot water returned from bathtub 3 to water heater 90, and detects the temperature of the hot water stored in bathtub 3. Hot water supply control unit 91 uses the detection result of water temperature sensor 92 to control reheating operation, etc.

[0047] The deep body temperature estimation device 1 in the embodiment does not use a water temperature sensor 92 to detect the temperature of the water stored in the bathtub 3, but in the modified example described below, the deep body temperature estimation device may use a water temperature sensor 92.

[0048] The water level sensor 93 includes a pressure sensor that measures the pressure inside the internal pipes connected to the bathtub 3 via the bathtub supply pipe P3A and the bathtub return pipe P3B. The water level sensor 93 detects the water level of the bathtub 3 based on the hydrostatic pressure measured by the pressure sensor when the water surface in the bathtub 3 is calm. The hot water supply control unit 91 uses the detection results of the water level sensor 93 to control the automatic bath filling operation, etc.

[0049] The water level when bather P1 is in bathtub 3 is significantly higher than the water level when bather P1 is not in bathtub 3. Based on such changes in the water level, water level sensor 93 detects whether bather P1 is in bathtub 3 or not.

[0050] The deep body temperature estimation device 1 in the embodiment does not use a water level sensor 93 to detect whether the bather P1 is in the bathtub 3, but in the modified example described below, the deep body temperature estimation device may use a water level sensor 93.

[0051] <Bathroom remote control> The bathroom remote control 10 is connected via wired communication to the hot water supply control unit 91 of the hot water supply device 90 and the remote control control unit 21 (described later) of the kitchen remote control 20. As shown in Figure 2, the bathroom remote control 10 has an input unit 12B, a display unit 12D, a remote control communication unit 19, and a remote control control unit 11.

[0052] Bathroom remote control 10 transmits operations performed by bather P1 on input unit 12B to water heating device 90 to remotely control water heating device 90. Bathroom remote control 10 also displays various information transmitted from water heating device 90, such as operating status and setting information, on display unit 12D.

[0053] Furthermore, bathroom remote control 10 can also accept input operations made by bather P1 to core body temperature estimation device 1 via input unit 12B, and display various information about core body temperature estimation device 1 via display unit 12D.

[0054] The remote control communication unit 19 performs wireless communication with a wireless router 7 installed in the house H1 via Wi-Fi (registered trademark) or the like. The remote control control unit 11 connects to an external network NW1 via the remote control communication unit 19 and the wireless router 7, and is capable of performing network communication with an information processing terminal such as an external server 9 connected to the network NW1. The external server 9 is a support server for the core body temperature estimation device 1.

[0055] Furthermore, the remote control communication unit 19 can also use Bluetooth (registered trademark) to directly perform wireless communication with a communication unit 49 (described later) of the core body temperature estimation device 1. Note that the bathroom remote control 10 can be modified so as not to have the remote control communication unit 19, and the remote control control unit 11 can perform wireless communication with the communication unit 49 of the core body temperature estimation device 1 via the remote control unit 21 of the kitchen remote control 20 and the wireless router 7, or perform network communication with an external server 9 or the like.

[0056] The remote control control unit 11 is an electronic circuit unit including a CPU (not shown), a storage unit 11M including storage elements such as a ROM and a RAM, an interface circuit, and the like.

[0057] Remote control unit 11 controls the operation of input unit 12B and display unit 12D of bathroom remote control 10. Remote control unit 11 also controls wired communication between bathroom remote control 10 and hot water supply control unit 91 of hot water supply device 90.

[0058] Furthermore, the remote control control unit 11 receives input operations performed by the bather P1 on the deep body temperature estimation device 1 via the input unit 12B, transmits the input operations to the deep body temperature estimation device 1 via the remote control communication unit 19, receives various information about the deep body temperature estimation device 1 via the remote control communication unit 19, and controls the display unit 12D to display the various information.

[0059] The memory unit 11M stores various programs and setting information for operating the bathroom remote control 10. The memory unit 11M also stores various information acquired by the remote control control unit 11 during operation of the bathroom remote control 10 as appropriate.

[0060] <Kitchen remote control> Kitchen remote control 20 is connected via wired communication to hot water supply control unit 91 of hot water supply device 90 and remote control control unit 11 of bathroom remote control 10. Kitchen remote control 20 has input unit 22B, display unit 22D, remote control communication unit 29, and remote control control unit 21.

[0061] Kitchen remote control 20 transmits operations performed on input unit 22B by a resident in kitchen R2 to water heating apparatus 90, thereby remotely controlling water heating apparatus 90. Kitchen remote control 20 also displays various information transmitted from water heating apparatus 90, such as the operating status and setting information, on display unit 22D.

[0062] The remote control communication unit 29 performs wireless communication with the wireless router 7. The remote control unit 21 can connect to an external network NW1 via the remote control communication unit 29 and the wireless router 7, and perform network communication with an information processing terminal such as an external server 9 connected to the network NW1.

[0063] The remote control unit 21 is an electronic circuit unit including a CPU (not shown), a storage unit 21M composed of storage elements such as a ROM and a RAM, and an interface circuit or the like.

[0064] The remote control unit 21 controls the operations of the input unit 22B and the display unit 22D of the kitchen remote control 20. Also, the remote control unit 21 controls the wired communication between the kitchen remote control 20 and the hot water supply control unit 91 of the hot water supply device 90.

[0065] The storage unit 21M stores various programs and setting information for operating the kitchen remote control 20. Also, the storage unit 21M appropriately stores various information acquired by the remote control unit 21 during the operation of the kitchen remote control 20.

[0066] <Smartwatch> As shown in FIG. 1, the smartwatch 30 is a wristwatch-type portable information terminal, having wireless communication functions such as a telephone and network communication, a music playback function, a life log function, and the like. The life log function is a function for recording the number of steps, moving distance, amount of exercise, calorie consumption (basal metabolism + exercise consumption), sleep data (sleep time, depth of sleep, respiratory rate and body movement during sleep), etc. in a day.

[0067] As shown in FIG. 2, the smartwatch 30 has a terminal control unit 31, a touch panel 32, and a terminal communication unit 39.

[0068] The terminal control unit 31 is an electronic circuit unit including a CPU (not shown), a storage unit 31M composed of storage elements such as a ROM and a RAM, and an interface circuit or the like. The terminal control unit 31 executes control processing related to the operation of the smartwatch 30.

[0069] The storage unit 31M stores various programs and setting information for operating the smartwatch 30. Also, the storage unit 31M appropriately stores various information acquired by the terminal control unit 31. The various information stored by the storage unit 31M includes the life log of the person P1A (bather P1) who routinely carries the smartwatch 30. The terminal control unit 31 updates the life log of the person P1A (bather P1) stored in the storage unit 31M at a predetermined interval (for example, daily).

[0070] The touch panel 32 displays various information such as characters and images by a display unit such as a liquid crystal panel, and receives various inputs by an operation in which the user touches the display unit covering the display unit with a fingertip in a state where the various information displayed on the display unit is visible to the user.

[0071] The terminal communication unit 39 is capable of executing a call using the frequency band of a mobile phone. Also, the terminal communication unit 39 incorporates an electronic circuit that executes wireless communication such as Bluetooth (registered trademark) and Wi-Fi (registered trademark). The terminal communication unit 39 directly executes wireless communication with the deep body temperature estimation device 1 via Bluetooth (registered trademark). Also, the terminal communication unit 39 executes wireless communication with the deep body temperature estimation device 1 via the wireless router 7 or executes wireless communication with the remote control communication unit 19 of the bathroom remote control 10 via Wi-Fi (registered trademark) or the like.

[0072] The terminal control unit 31 can execute network communication with the external server 9 via the terminal communication unit 39 and upload the life log of the person P1A (bather P1) to the external server 9 so that the amount of information of the life log of the person P1A (bather P1) does not exceed the storage capacity of the storage unit 31M.

[0073] Also, the terminal control unit 31 can execute network communication with the external server 9, download an information collection application program for supporting the deep body temperature estimation device 1, and store it in the storage unit 31M.

[0074] By executing the information collection application program, the terminal control unit 31 functions in part as an exercise habit information calculation unit 31A and in part as a sleep time information calculation unit 31B.

[0075] <Exercise habit information calculation unit> Based on the life log of the subject P1A (bather P1) stored in the storage unit 31M, the exercise habit information calculation unit 31A calculates quantified exercise habit information based on the past exercise performance of the subject P1A (bather P1).

[0076] As the exercise habit information, for example, the frequency of exercise, the required time for exercise, the intensity of exercise, etc. can be appropriately selected. In this embodiment, the exercise habit information is information based on the number of days in which exercise of a predetermined amount or more has been performed for a predetermined time or more in the past predetermined period.

[0077] The "past predetermined period" is preferably a long period such as in years or months because it relates to habits. In this embodiment, it is the past six months. The "predetermined amount or more of exercise" preferably has a numerically clear difference from daily activities without exercise. In this embodiment, it is exercise intensity (strength of exercise) of 4.0 METs or more. The "predetermined time or more" preferably has a numerically clear difference from daily activities without exercise. In this embodiment, it is 30 minutes or more. Note that for the "predetermined amount or more of exercise", it may be defined as "exercise that causes sweating" without using exercise intensity.

[0078] The website of the Public Interest Foundation for Aging and Longevity states, "Exercise intensity (strength of exercise) is measured by the amount of oxygen taken in by the body per kilogram of body weight. However, because this amount is difficult to determine, the unit of metabolic equivalent (MET) is used. METs are a unit of exercise intensity that indicates how many times the energy consumed by exercise, assuming a resting oxygen intake of 3.5 ml / kg / min is 1.0 MET. For example, sitting down to watch TV or riding in a car is 1.0 MET; sitting down to talk, eat, or do desk work is 1.5 METs; cooking, doing laundry, changing clothes, washing your face, taking a shower, or walking around the house is 2.0 METs; walking or cleaning is 3.0 METs; table tennis and Radio Calisthenics No. 1 are 4.0 METs; badminton and golf are 4.3 METs; baseball and softball are 5.0 METs; weight training, swimming, and basketball are 6.0 METs..."

[0079] It is thought that when exercising for 30 minutes or more at an intensity of 4.0 METs or more, vital signs such as heart rate, blood flow, and sweat rate tend to increase compared to vital signs during everyday activities without exercise.

[0080] When the subject P1A (bather P1) operates the touch panel 32 and routinely inputs records of the exercise time and type of exercise performed on a specific date and time, the terminal control unit 31 associates the amount of exercise performed at each time with the calories burned (basal metabolic rate + exercise consumption) and stores the information in the memory unit 31M as part of the life log.

[0081] The exercise habit information calculation unit 31A refers to the time and type of exercise history entered by the subject P1A (bather P1), if any, and extracts exercise history in which exercise of a predetermined amount or more of exercise (exercise intensity of 4.0 METs or more) was performed for a predetermined time or more (30 minutes or more) from the life log for a predetermined period of time (past six months) stored in the memory unit 31M, and calculates the number of days on which such exercise history occurred, thereby calculating the exercise habit information of the subject P1A (bather P1).

[0082] The exercise habit information calculated by the exercise habit information calculation unit 31A is stored in the storage unit 31M. The terminal control unit 31 updates the exercise habit information of the subject P1A (bather P1) stored in the storage unit 31M at a predetermined interval (for example, every day).

[0083] <Sleep time information calculation unit> The sleep time information calculation unit 31B calculates quantified sleep time information based on the past sleep records of the subject P1A (bather P1) stored in the storage unit 31M.

[0084] As the sleep time information, for example, the average value or median of the sleep time in a past predetermined period, the number of days with a sleep time of a predetermined time or more in a past predetermined period, etc. can be appropriately selected. In this embodiment, the sleep time information is the average value of the sleep time in a past predetermined period. The "past predetermined period" is preferably a long period such as in years or months because it relates to habits. In this embodiment, it is the past six months.

[0085] It is considered that the more the average value of the sleep time in a past predetermined period becomes longer, the easier it is for the autonomic nerves (the balance between the sympathetic nerves and the parasympathetic nerves) to be adjusted.

[0086] The sleep time information calculation unit 31B extracts the sleep time from the life log of a past predetermined period (the past six months) stored in the storage unit 31M, and calculates the average value of the sleep time as the sleep time information of the subject P1A (bather P1).

[0087] The sleep time information calculated by the sleep time information calculation unit 31B is stored in the storage unit 31M. The terminal control unit 31 updates the sleep time information of the subject P1A (bather P1) stored in the storage unit 31M at a predetermined interval (for example, every day).

[0088] <Deep body temperature estimation device> As shown in FIG. 1, the deep body temperature estimation device 1 is installed in the bathroom R1. The main body 40 of the deep body temperature estimation device 1 is attached to the side wall of the bathroom R1 so as to be exposed in the bathroom R1. Note that the main body 40 of the deep body temperature estimation device 1 may be installed on the ceiling back or the back side of the side wall of the bathroom R1 so as not to be exposed in the bathroom R1.

[0089] As shown in FIGS. 1 and 2, the deep body temperature estimation device 1 includes a control unit 41, a biological information detection means 50, and a bathing condition information detection means 60. The biological information detection means 50 and the bathing condition information detection means 60 are examples of the "detection means" of the present invention.

[0090] The control unit 41 is housed in the main body 40 of the deep body temperature estimation device 1. The control unit 41 is an electronic circuit unit including a CPU (not shown), a storage unit 41M constituted by storage elements such as a ROM and a RAM, and an interface circuit or the like. The control unit 41 executes control processing related to the operation of the deep body temperature estimation device 1.

[0091] The storage unit 41M stores various programs and setting information for operating the deep body temperature estimation device 1. Further, the storage unit 41M appropriately stores various information acquired by the control unit 41. The various information stored in the storage unit 41M includes the deep body temperature estimation program shown in FIGS. 3 and 4.

[0092] As will be described later, the control unit 41 executes a deep body temperature estimation process for estimating the deep body temperature of the bather P1 in the bathtub 3 during bathing by executing the deep body temperature estimation program shown in FIGS. 3 and 4.

[0093] Here, the deep body temperature is the temperature inside the main organs in the body, such as the brain and internal organs. Therefore, in experiments and the like, in order to accurately measure the deep body temperature, a sensor is inserted into the esophagus or rectum to invasively measure the deep body temperature. However, in daily life, the deep body temperature is estimated based on the measured values obtained by non-invasive methods.

[0094] As shown in FIG. 1, the biological information detection means 50 and the bathing condition information detection means 60 are each provided outside the main body 40 of the deep body temperature estimation device 1 and are connected to the control unit 41 by a wired connection. The biological information detection means 50 and the bathing condition information detection means 60 detect bath information regarding the bather P1 during bathing, and detect the digitized bath information.

[0095] Note that the biological information detection means 50 and the bathing condition information detection means 60 may be wirelessly connected to the control unit 41 by performing wireless communication such as Bluetooth (registered trademark) between the biological information detection means 50 and the bathing condition information detection means 60 and the communication unit 49.

[0096] The biological information detection means 50 is a wristband type detection device that is worn on the wrist of the bather P1 when the bather P1 takes a bath in the bathtub 3. The biological information detection means 50 detects biological information including at least the vital state of the bather P1 as bath information. The vital state is, for example, the heart rate, blood flow volume, sweating amount, respiratory rate, blood pressure, etc. of the bather P1.

[0097] As shown in FIG. 2, the biological information detection means 50 includes a heart rate detection means 50A, a blood flow volume detection means 50B, and a sweating amount detection means 50C.

[0098] The heart rate detection means 50A detects the heart rate of the bather P1 as a vital state. Examples of the detection method of the heart rate detection means 50A include a method of measuring the expansion and contraction of the blood vessels in the wrist according to the heartbeat by a pressure sensor or an optical sensor and detecting the heart rate based on the cycle of the expansion and contraction.

[0099] The blood flow volume detection means 50B detects the blood flow volume of the bather P1 as a vital state. Examples of the detection method of the blood flow volume detection means 50B include a method of irradiating light on the skin of the wrist using an LED and measuring the change in the intensity of the reflected light caused by the blood flow with a photodiode.

[0100] The sweating amount detection means 50C detects the sweating amount of the bather P1 as a vital condition. As a detection method of the sweating amount detection means 50C, for example, there is a method of measuring the air humidity before passing through the skin of the wrist and the air humidity after passing through the skin (including the evaporated moisture of sweat) with two humidity sensors, and detecting the sweating amount from the difference therebetween.

[0101] The detection results of the heart rate detection means 50A, the blood flow rate detection means 50B, and the sweating amount detection means 50C are transmitted to the control unit 41.

[0102] As shown in FIG. 1, the bathing condition information detection means 60 detects bathing condition information regarding the conditions during the bath of the bather P1 as bathing information. The bathing condition information is, for example, the temperature and water level of the hot water stored in the bathtub 3, the elapsed time since the bather P1 started bathing, the temperature and humidity of the bathroom R1 in which the bathtub 3 is installed, and the like.

[0103] As shown in FIGS. 1 and 2, the bathing condition information detection means 60 includes a hot water temperature detection means 60A, a bathing elapsed time detection means 60B, and a bathroom temperature detection means 60C.

[0104] The hot water temperature detection means 60A has a hot water temperature sensor installed on the side wall surface of the bathtub 3. The hot water temperature detection means 60A directly detects the temperature of the hot water stored in the bathtub 3.

[0105] The bathing elapsed time detection means 60B has a pressure sensor and a timing means installed on the side wall surface of the bathtub 3. The pressure sensor detects whether or not the bather P1 has started bathing based on the pressure difference between the water level when the bather P1 is in the bathtub 3 and the water level when the bather P1 is not in the bathtub 3. The timing means starts timing when the pressure sensor detects the start of bathing by the bather P1. Thus, the bathing elapsed time detection means 60B detects the elapsed time since the bather P1 started bathing.

[0106] The bathroom temperature detection means 60C is a temperature sensor installed in the vicinity of the bathtub 3 on the side wall surface of the bathroom R1. The bathroom temperature detection means 60C detects the temperature of the bathroom R1.

[0107] The detection results of the hot water temperature detection means 60A, the bathing elapsed time detection means 60B, and the bathroom temperature detection means 60C are transmitted to the control unit 41.

[0108] As shown in FIG. 2, the deep body temperature estimation device 1 further includes a communication unit 49. The communication unit 49 incorporates an electronic circuit that performs wireless communication using Bluetooth (registered trademark), Wi-Fi (registered trademark), etc. The communication unit 49 directly performs wireless communication with the terminal communication unit 39 of the smartwatch 30 via Bluetooth (registered trademark). Also, the communication unit 49 performs wireless communication with the terminal communication unit 39 of the smartwatch 30 via the wireless router 7 using Wi-Fi (registered trademark), etc., or performs wireless communication with the remote control communication unit 19 of the bathroom remote control 10.

[0109] When the control unit 41 executes the deep body temperature estimation process described later, it performs wireless communication with the terminal control unit 31 of the smartwatch 30 via the terminal communication unit 39 and the communication unit 49. And the control unit 41 acquires the exercise habit information and sleep time information stored in the storage unit 31M via the terminal communication unit 39 and the communication unit 49.

[0110] <Deep body temperature estimation process> When the subject P1A (bather P1) starts preparations for bathing, the input unit 12B of the bathroom remote control 10 is operated in the bathroom R1, or the input unit 22B of the kitchen remote control 20 is operated in the kitchen R2 to cause the hot water supply device 90 to perform a hot water filling operation or a supplementary hot water operation, making the hot water stored in the bathtub 3 available for bathing.

[0111] At this time, the control unit 41 of the deep body temperature estimation device 1 executes the deep body temperature estimation program shown in FIGS. 3 and 4, for example, to estimate the health condition of the bather P1, estimate the health promotion effect of bathing, or propose bathing conditions that improve the quality of sleep after bathing.

[0112] First, in step S101 shown in FIG. 3, the control unit 41 acquires the exercise habit information and sleep time information of the subject P1A (bather P1) stored in the memory unit 31M of the smart watch 30. If the exercise habit information and sleep time information of the subject P1A (bather P1) has been uploaded from the smart watch 30 to the external server 9, the exercise habit information and sleep time information of the subject P1A (bather P1) can also be acquired from the external server 9. If multiple residents live in the residence H1, multiple subjects P1A (bather P1) may also be registered in this program. If there is multiple subject P1A (bather P1), the exercise habit information and sleep time information of all of the subjects P1A (bather P1) is acquired. Then, the control unit 41 updates the exercise habit information and sleep time information of the subject P1A (bather P1) stored in the memory unit 41.

[0113] Next, the control unit 41 proceeds to step S102 and determines whether the biological information detection means 50 is attached to the arm of the bather P1. As long as the heart rate detection means 50A, blood flow detection means 50B, and sweat rate detection means 50C do not transmit detection results to the control unit 41, the result is "No," and the control unit 41 repeats step S102. Then, when the heart rate detection means 50A, blood flow detection means 50B, and sweat rate detection means 50C transmit detection results to the control unit 41, the result is "Yes," and the control unit 41 determines that the biological information detection means 50 is attached and proceeds to step S103.

[0114] When the control unit 41 proceeds to step S103, it issues a notification on the display unit 12D of the bathroom remote controller 10 to prompt the user to select a subject for the core body temperature estimation process. In response to the notification, the bather P1 wearing the biological information detection means 50 will perform an input operation on the input unit 12B of the bathroom remote controller 10.

[0115] Next, the control unit 41 proceeds to step S104 and determines whether an input for selecting a target person has been made. The control unit 41 repeats step S104 while the result is "No." Then, when the result is "Yes" in step S104, the control unit 41 proceeds to step S105.

[0116] When the control unit 41 shifts to step S105, it selects the bather P1 who is the subject of the current deep body temperature estimation process from among the registered subjects P1A (bathers P1) based on the input for selecting the subject.

[0117] Next, the control unit 41 shifts to step S106, reads out the exercise habit information and sleep time information of the bather P1 who is the subject of processing stored in the storage unit 41, and sets them as parameters of the estimation formula used in step S116 described later.

[0118] Here, the estimation formula for the deep body temperature used in this embodiment is a formula having eight parameters, [Estimated value Y of deep body temperature]=β0 + β1x1 + β2x2 + β3x3 + β4x4 + β5x5 + β6x6 + β7x7 + β8x8 where:

[0119] β0 is the intercept. β1 to β8 are regression coefficients. x1 to x8 are parameters. In step S106, the exercise habit information is set as the parameter x1, and the sleep time information is set as the parameter x2.

[0120] The estimation formula is constructed every time step S116 is executed based on a deep body temperature estimation algorithm obtained by previously conducting bathing tests on a plurality of subjects, using the exercise habit information and sleep time information of each subject, and the biological information (heart rate, blood flow rate, sweating amount) and bathing condition information (hot water temperature, bathing elapsed time, bathroom temperature) of each subject during bathing as input information, and using the deep body temperature (measured value of rectal temperature) as output information.

[0121] Note that the estimation formula for the deep body temperature is an example, and the number of parameters is not limited to eight. Although not listed as parameters in this embodiment, the height, weight, age, and gender of the bather P1 can also be used as parameters.

[0122] Next, the control unit 41 proceeds to step S107 and determines whether or not the bather P1 is in the bathtub 3. In this embodiment, the control unit 41 makes this determination based on the pressure sensor of the bathing elapsed time detection means 60B. The control unit 41 repeats step S107 as long as the determination is "No." Then, when the determination is "Yes" in step S107, the control unit 41 proceeds to step S108.

[0123] When the control unit 41 proceeds to step S108, it starts the core body temperature estimation process.

[0124] Next, the control unit 41 proceeds to step S111 shown in Fig. 4. Then, the control unit 41 controls the biological information detection means 50, and continuously detects biological information (heart rate, blood flow rate, and sweat rate) as bathing information using the heart rate detection means 50A, blood flow rate detection means 50B, and sweat rate detection means 50C.

[0125] Next, the control unit 41 proceeds to step S112. Then, the control unit 41 controls the bathing condition information detection means 60, and the bathing condition information (bath water temperature, elapsed bathing time, bathroom temperature) is continuously detected as bathing information by the water temperature detection means 60A, the elapsed bathing time detection means 60B, and the bathroom temperature detection means 60C.

[0126] Next, the control unit 41 proceeds to step S113 and waits for a predetermined waiting time. The predetermined waiting time refers to the time interval for the deep body temperature estimation process in step S116. The predetermined waiting time is preferably short enough to adequately follow changes in the physical condition of the bather P1 due to bathing, and is preferably one minute or less. Furthermore, if the predetermined waiting time is too short, the calculation load will become excessive, so it is preferably several seconds or more. In this embodiment, the predetermined waiting time is 20 seconds.

[0127] Next, the control unit 41 proceeds to step S114 and determines whether the bather P1 is in the bathtub 3. If the determination in step S114 is "Yes," the control unit 41 proceeds to step S115. On the other hand, if the determination in step S114 is "No," the control unit 41 determines that the bather P1 has left the bath and proceeds to step S121. The processing from step S121 onwards will be described later.

[0128] When the control unit 41 proceeds from step S114 to step S115, it sets the bathing information (biological information and bathing condition information) of the bather P1 detected in real time as the parameters of the estimation formula described above.

[0129] In step S115, for the biological information, the heart rate is set as parameter x3, the blood flow rate is set as parameter x4, and the sweat rate is set as parameter x5. For the bathing condition information, the water temperature is set as parameter x6, the elapsed bathing time is set as parameter x7, and the bathroom temperature is set as parameter x8.

[0130] Next, the control unit 41 proceeds to step S116. Then, the control unit 41 constructs the above-mentioned estimation formula using the bathing information (biological information and bathing condition information), exercise habit information, and sleeping time information as parameters, and calculates the [estimated value Y of core body temperature].

[0131] Next, the control unit 41 proceeds to step S117 and stores the estimated core body temperature, [estimated core body temperature value Y], in the memory unit 41M. The memory unit 41M stores the [estimated core body temperature value Y] as time-series data at predetermined standby time (20 second) intervals.

[0132] In addition, the control unit 41 can perform network communication with the external server 9 via the communication unit 49 and upload the [estimated core body temperature value Y] of the subject P1A (bather P1) to the external server 9 so that the amount of information on the [estimated core body temperature value Y] of the subject P1A (bather P1) does not exceed the storage capacity of the memory unit 41M.

[0133] In addition, the control unit 41 can also upload the bathing information (biological information and bathing condition information) of the bather P1 to the external server 9. Further, the control unit 41 can have a part of the processing with a large calculation load in the deep body temperature estimation process executed by the external server 9.

[0134] Next, the control unit 41 proceeds to step S118 and displays the estimated deep body temperature and the like on the display unit 12D of the bathroom remote controller 10. At this time, the control unit 41, according to the user's wishes, displays the detection results of the heart rate detection means 50A, the blood flow rate detection means 50B, and the sweating amount detection means 50C, and the information obtained by analyzing them, on the display unit 12D of the bathroom remote controller 10 according to the user's wishes.

[0135] After that, the control unit 41 returns to step S113 and repeats steps S113 to S118.

[0136] When shifting from step S114 to step S121, after the control unit 41 finishes the detection operations of the biological information detection means 50 and the bathing condition information detection means 60, it ends this program.

[0137] <Operational Effects> As shown in FIGS. 1 and 2, the deep body temperature estimation device 1 of the embodiment includes the biological information detection means 50 and the bathing condition information detection means 60 as detection means.

[0138] The biological information of the bather P1 detected by the biological information detection means 50 as bathing information is the vital state of the bather P1, that is, the heart rate, blood flow rate, and sweating amount of the bather P1.

[0139] The bathing condition information detected by the bathing condition information detection means 60 as bathing information is the temperature of the hot water stored in the bathtub 3, the elapsed time since the bather P1 started bathing, and the temperature of the bathroom R1 where the bathtub 3 is installed.

[0140] The exercise habit information acquired by the control unit 41 is the information calculated by the exercise habit information calculation unit 31A of the smart watch 30. The exercise habit information calculation unit 31A extracts, from the life log of the past predetermined period (the past six months) stored in the storage unit 31M, the exercise achievements in which exercise of a predetermined amount or more (exercise intensity of 4.0 mets or more) has been performed for a predetermined time or more (30 minutes or more), and calculates the exercise habit information of the subject P1A (bather P1) by obtaining the number of days on which such exercise achievements have been made.

[0141] The control unit 41 executes the deep body temperature estimation program shown in FIGS. 3 and 4, and in step S116, constructs the above-described estimation formula using such bathing information and exercise habit information as parameters, and calculates [the estimated value Y of the deep body temperature]. Do.

[0142] Here, people with a daily exercise habit tend to have a higher vasodilation function and a larger blood flow volume compared to those without an exercise habit in order to dissipate the heat of the body increased by exercise or the like. Therefore, people with a daily exercise habit tend to have a larger blood flow volume in a hot environment.

[0143] Since the hot water in which the bather P1 immersed during bathing stored in the bathtub 3 has a temperature higher than the body temperature of the bather P1, when a person with an exercise habit takes a bath, it is considered that the blood flow volume of the bather P1 tends to increase. And, since the hot water stored in the bathtub 3 has a larger heat capacity than air, the heat exchange between the body surface of the bather P1 and the hot water is promoted, and the heat transmitted from the hot water to the blood in the body via the body surface easily moves to the deep part of the body by blood circulation. As a result, it is considered that the deep body temperature is likely to rise.

[0144] Thus, since it is considered that there is a correlation between the deep body temperature during bathing and the exercise habit, the exercise habit information is suitable as a parameter for estimating the deep body temperature during bathing.

[0145] Therefore, the deep body temperature estimation device 1 of the embodiment can accurately estimate the deep body temperature of the bather P1 during bathing.

[0146] In addition, in this deep body temperature estimation device 1, the exercise habit information is information based on the number of days on which exercise of a predetermined amount or more (exercise intensity of 4.0 mets or more) was performed for a predetermined time or more (30 minutes or more) in a past predetermined period (the past six months). By using such specific exercise habit information, the deep body temperature of the bather P1 during bathing can be estimated with higher accuracy.

[0147] Furthermore, in this deep body temperature estimation device 1, the smartwatch 30 stores the exercise achievements of the subject P1A (bather P1) and calculates exercise habit information. Then, in step S101 shown in FIG. 3, the control unit 41 acquires the exercise habit information of the subject P1A (bather P1) stored in the storage unit 31M of the smartwatch 30 from the smartwatch 30 via the communication unit 49, or acquires the exercise habit information uploaded to the external server 9 from the external server 9 via the communication unit 49. With this configuration, the control unit 41 can use the exercise habit information of the subject P1A (bather P1) updated by the smartwatch 30 as a parameter for the deep body temperature estimation process. As a result, the control unit 41 can execute the deep body temperature estimation process without the subject P1A (bather P1) performing a special operation for the deep body temperature estimation device 1 to acquire the exercise habit information, such as an input operation of exercise achievements, etc., thus realizing an improvement in convenience.

[0148] Also, in this deep body temperature estimation device 1, as shown in FIG. 2, the biological information detection means 50 includes a heart rate detection means 50A, a blood flow detection means 50B, and a sweating amount detection means 50C. With this configuration, since the biological information used as a parameter for the control unit 41 to estimate the deep body temperature includes the heart rate, blood flow, and sweating amount of the bather P1, the deep body temperature of the bather P1 during bathing can be estimated with higher accuracy.

[0149] Furthermore, in this deep body temperature estimation device 1, as shown in FIGS. 1 and 2, the bathing condition information detection means 60 includes a hot water temperature detection means 60A, a bathing elapsed time detection means 60B, and a bathroom temperature detection means 60C. With this configuration, the bathing condition information, which is a parameter for the control unit 41 to estimate the deep body temperature, includes the temperature of the hot water stored in the bathtub 3, the bathing elapsed time, and the temperature of the bathroom R1. Therefore, the deep body temperature of the bather P1 during bathing can be estimated with higher accuracy.

[0150] Also, in this deep body temperature estimation device 1, the control unit 41 can acquire sleep time information quantified based on the past sleep records of the subject P1A (bather P1). Then, in step S116 shown in FIG. 4, the control unit 41 executes a deep body temperature estimation process using the bathing information, exercise habit information, and sleep time information as parameters. Comparing the cases where the daily sleep time tends to be long and short, it is considered that when the tendency is long, the autonomic nervous system (the balance between the sympathetic and parasympathetic nerves) is more likely to be adjusted, and the adjustment of blood flow can be performed smoothly. For this reason, a bather P1 with a tendency for a long daily sleep time tends to have a larger blood flow in a hot environment. Also, since the hot water stored in the bathtub 3 and in which the bather P1 is immersed during bathing has a temperature higher than the body temperature of the bather P1, when a person with a tendency for a long daily sleep time takes a bath, it is considered that the blood flow of the bather P1 is likely to increase. And since the hot water stored in the bathtub 3 has a larger heat capacity than air, the heat exchange between the body surface of the bather P1 and the hot water is promoted, and the heat transmitted from the hot water to the blood in the body via the body surface is likely to move to the deep part of the body by blood circulation. As a result, it is considered that the deep body temperature is likely to rise. Thus, since there is considered to be a correlation between the deep body temperature and the sleep time during bathing, the sleep time information is suitable as a parameter for estimating the deep body temperature during bathing. Therefore, this deep body temperature estimation device 1 can estimate the deep body temperature of the bather P1 during bathing with higher accuracy.

[0151] Furthermore, in this deep body temperature estimation device 1, the smartwatch 30 stores the sleep history of the subject P1A (bather P1) and calculates sleep time information. Then, in step S101 shown in FIG. 3, the control unit 41 acquires the sleep time information of the subject P1A (bather P1) stored in the memory unit 31M of the smartwatch 30 from the smartwatch 30 via the communication unit 49, or acquires the sleep time information uploaded to the external server 9 from the external server 9 via the communication unit 49. With this configuration, the control unit 41 can use the sleep time information of the subject P1A (bather P1) updated by the smartwatch 30 as a parameter for the deep body temperature estimation process. This allows the control unit 41 to execute the deep body temperature estimation process without the subject P1A (bather P1) having to perform a special operation to have the control unit 41 acquire the sleep time information, such as inputting the sleep history, on the deep body temperature estimation device 1, thereby improving convenience.

[0152] Although the present invention has been described above with reference to the examples, it goes without saying that the present invention is not limited to the above examples and can be modified and applied as appropriate within the scope of the invention.

[0153] In the embodiment, the control unit 41 acquires the sleeping time information of the subject P1A (bathing person P1) and executes the deep body temperature estimation process using the bathing information, exercise habit information, and sleeping time information as parameters, but the present invention is not limited to this configuration. For example, the present invention also includes a configuration in which the control unit 41 does not acquire the sleeping time information of the subject P1A (bathing person P1) and executes the deep body temperature estimation process using the bathing information and exercise habit information as parameters.

[0154] In the embodiment, the deep body temperature estimation device 1 includes the biological information detection means 50 and the bath condition information detection means 60 as detection means, but the present invention is not limited to this configuration. For example, a configuration in which the bath condition information detection means 60 is eliminated from the embodiment, that is, a configuration in which the bath temperature, the bath elapsed time, and the bathroom temperature, which are bath condition information, are excluded as parameters in the deep body temperature estimation formula, is also included in the present invention. Further, a configuration in which the biological information detection means 50 is eliminated from the embodiment, that is, a configuration in which the heart rate, blood flow rate, and sweating amount, which are biological information, are excluded as parameters in the deep body temperature estimation formula, is also included in the present invention.

[0155] In the embodiment, the biological information detection means 50 includes the heart rate detection means 50A, the blood flow rate detection means 50B, and the sweating amount detection means 50C, but the present invention is not limited to this configuration. For example, a configuration in which any one or two of the heart rate detection means 50A, the blood flow rate detection means 50B, and the sweating amount detection means 50C are eliminated from the biological information detection means 50 according to the embodiment, that is, a configuration in which any one or two of the heart rate, blood flow rate, and sweating amount are excluded as parameters in the deep body temperature estimation formula, is also included in the present invention.

[0156] In the embodiment, the bath condition information detection means 60 includes the bath temperature detection means 60A, the bath elapsed time detection means 60B, and the bathroom temperature detection means 60C, but the present invention is not limited to this configuration. For example, a configuration in which any one or two of the bath temperature detection means 60A, the bath elapsed time detection means 60B, and the bathroom temperature detection means 60C are eliminated from the bath condition information detection means 60 according to the embodiment, that is, a configuration in which any one or two of the bath temperature, bath elapsed time, and bathroom temperature are excluded as parameters in the deep body temperature estimation formula, is also included in the present invention.

[0157] In the embodiment, the input unit 12B and the display unit 12D of the bathroom remote controller 10 also serve as the input unit and the display unit of the deep body temperature estimation device 1, but the present invention is not limited to this configuration. For example, a configuration in which the deep body temperature estimation device 1 includes a dedicated input unit and a display unit and executes deep body temperature estimation processing independently of the bathroom remote controller 10 and the water supply device 90 is also included in the present invention. In the deep body temperature estimation device 1 in this case, the control unit 41 acquires the exercise habit information and the sleep time information by inputting (manual input or data transfer via a communication cable) the exercise habit information and the sleep time information to the dedicated input unit, so that the deep body temperature estimation processing can be executed without cooperating with the smart watch 30.

[0158] Eliminating the main body of the deep body temperature estimation device 1 in the embodiment, the control unit 91 of the water supply device 90 has the same configuration as the control unit 41 of the deep body temperature estimation device 1, the storage unit 91M stores the deep body temperature estimation programs shown in FIGS. 3 and 4, the detection results of the biological information detection means 50 and the bathing condition information detection means 60 are transmitted to the control unit 91 via the bathroom remote controller 10, and the control unit 91 executes the deep body temperature estimation program, that is, a configuration in which the control unit 91 of the water supply device 90 also serves as the deep body temperature estimation device is also included in the present invention.

[0159] Eliminating the main body of the deep body temperature estimation device 1 in the embodiment, the control unit 11 of the bathroom remote controller 10 has the same configuration as the control unit 41 of the deep body temperature estimation device 1, the storage unit 11M stores the deep body temperature estimation programs shown in FIGS. 3 and 4, the detection results of the biological information detection means 50 and the bathing condition information detection means 60 are transmitted to the control unit 11, and the control unit 11 executes the deep body temperature estimation program, that is, a configuration in which the control unit 11 of the bathroom remote controller 10 also serves as the deep body temperature estimation device is also included in the present invention.

[0160] In the embodiment, the portable information terminal is the smart watch 30, but the present invention is not limited to this configuration. For example, the portable information terminal may be a smart phone, a tablet, a sensor with a strap that wraps around the chest, or the like.

[0161] In the embodiment, the biometric information detection means 50 is a wristband-type detection device, but the present invention is not limited to this configuration. For example, the biometric information detection means may capture an image including the face of the bather P1 using a camera and detect the breathing rate or other biometric information based on changes in the shape of the mouth and nose. Alternatively, the biometric information detection means may be a smart watch 30 with improved waterproof and heat resistance, which may be worn on the wrist of the bather P1 in the bathroom R1 instead of the biometric information detection means 50.

[0162] In the embodiment, the water temperature detection means 60A has a water temperature sensor installed on the side wall surface of the bathtub 3, but the present invention is not limited to this configuration. For example, the present invention also includes a configuration in which the water temperature detection means 60A is eliminated from the embodiment and the water temperature sensor 92 of the water heater 90 is used as the water temperature detection means.

[0163] In the embodiment, bathing elapsed time detection means 60B has a pressure sensor and a timing means installed on the side wall surface of bathtub 3, but the present invention is not limited to this configuration. For example, the present invention also includes a configuration in which bathing elapsed time detection means 60B is eliminated from the embodiment and the water level sensor 93 and internal clock of water heater 90 are used as bathing elapsed time detection means.

[0164] In the embodiment, the control unit 41 receives an input to select a subject for the core body temperature estimation process in step S104 shown in Fig. 3, but the present invention is not limited to this configuration. For example, the control unit 41 may identify the bather P1 who is the subject of the current core body temperature estimation process from among the registered subjects P1A (bathers P1) by photographing the bather P1 with a camera installed in the bathroom R1 and performing image analysis.

[0165] In the embodiment, the sleep time information terminal is a smart watch 30, but the present invention is not limited to this configuration. For example, the sleep time information terminal may be a sleep monitor installed in the bedroom of the subject P1A (bathing person P1). In this case, the sleep monitor may be placed on the mattress of the bed, wrapped around the head or arm, placed next to the head, or the like. [Industrial Applicability]

[0166] The present invention can be used, for example, in a house or a facility where a bathroom is installed.

Description of Reference Numerals

[0167] 1…Deep body temperature estimation device 3…Bathtub P1…Bather 41…Control unit 50, 60…Detection means (50…Biological information detection means, 60…Bathing condition information detection means) 30…Portable information terminal (smartwatch) 9…External server 49…Communication unit 50A…Heart rate detection means 50B…Blood flow detection means 50C…Sweating amount detection means 60A…Hot water temperature detection means 60B…Bathing elapsed time detection means 60C…Bathroom temperature detection means R1…Bathroom 30…Sleep time information terminal (smartwatch)

Claims

1. A control unit that executes a deep body temperature estimation process for estimating the deep body temperature of a bather taking a bath in a bathtub, Detection means for detecting the bathing information regarding the bather taking a bath, which is digitized bathing information, A deep body temperature estimation device comprising: The detection means includes: Biological information detection means for detecting biological information including at least the vital state of the bather as the bathing information, Bathing condition information detection means for detecting bathing condition information regarding the conditions during the bather's bath as the bathing information, having at least one of The control unit can acquire digitized exercise habit information based on the bather's past exercise performance, The control unit executes the deep body temperature estimation process using the bathing information and the exercise habit information as parameters. A deep body temperature estimation device characterized by this.

2. The deep body temperature estimation device according to claim 1, wherein the exercise habit information is information based on the number of days on which exercise of a predetermined amount or more has been performed for a predetermined time or more in a past predetermined period.

3. A portable information terminal that is routinely carried by the bather, the portable information terminal that stores the bather's exercise performance and calculates the exercise habit information, and a communication unit capable of communicating with at least one of an external server that acquires the exercise habit information from the portable information terminal via network communication, The deep body temperature estimation device according to claim 1, wherein the control unit acquires the exercise habit information via the communication unit.

4. The detection means has at least the biological information detection means, The biological information detection means includes: Heart rate detection means for detecting the heart rate of the bather as the vital state, Blood flow rate detection means for detecting the blood flow rate of the bather as the vital state, Sweating amount detection means for detecting the sweating amount of the bather as the vital state, The deep body temperature estimation device according to any one of claims 1 to 3, having at least one of

5. The detection means has at least the bathing condition information detection means, The bathing condition information detection means includes: Hot water temperature detection means for detecting the temperature of the hot water stored in the bathtub, Bathing elapsed time detection means for detecting the elapsed time since the bather started bathing, Bathroom temperature detection means for detecting the temperature of the bathroom where the bathtub is installed, The deep body temperature estimation device according to any one of claims 1 to 3, having at least one of

6. The control unit is capable of acquiring quantified sleep time information based on the bather's past sleep performance, The deep body temperature estimation device according to claim 1 , wherein the control unit executes the deep body temperature estimation process using the bathing information, the exercise habit information, and the sleeping time information as parameters.

7. The bather further includes a communication unit capable of communicating with at least one of a sleep time information terminal that stores the bather's sleep history and calculates the sleep time information, and an external server that acquires the sleep time information from the sleep time information terminal via network communication. The deep body temperature estimation device according to claim 6 , wherein the control unit acquires the sleeping time information via the communication unit.

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