JP2022123075A - Method of controlling body condition estimation device and control device of body condition estimation device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method of estimating a body condition, the method enables estimation of a body condition of a person without requiring prior calibration.

SOLUTION: Provided is a method of estimating a body condition executed by a computer, the method including: a blood flow measurement step (S11) of measuring by the computer blood flow rates at at least two portions among portions of a person; and a body condition estimation step (S12) of estimating by the computer a body condition of the person on the basis of the blood flow rates at at least two portions that have been measured in the blood flow measurement step (S11).

SELECTED DRAWING: Figure 6

COPYRIGHT: (C)2022,JPO&INPIT

Description

The present invention relates to a physical condition estimation method, a physical condition estimation device, and a program.

Patent Literature 1 discloses a technique for determining a person's physical condition such as stress, fatigue, drowsiness, and wakefulness based on a pulse wave signal obtained by measuring a pulse wave generated by blood circulation.

Japanese Patent Application Laid-Open No. 2002-272708

However, there are individual differences in pulse pressure. Therefore, the technique disclosed in Patent Literature 1 has a problem that calibration (adjustment) such as setting the pulse pressure of the individual to be determined is necessary in advance, that is, before the physical condition is determined.

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide a physical condition estimation method and the like capable of estimating a person's physical condition without requiring prior calibration.

A control method according to one aspect of the present invention is a device control method, in which information about a person's body surface temperature detected by a thermo camera is acquired, and based on the information about the body surface temperature, a deep body temperature of the person is calculated. estimating, detecting the state of the person based on the estimated core body temperature, and controlling the operation of the device according to the detected state of the person;

For example, a control method according to one aspect of the present invention is a control method for a physical condition estimation device, in which information about a body surface temperature of a person detected by a thermo camera is acquired, and based on the information about the body surface temperature, the person estimating the deep body temperature of the person, detecting the state of the person based on the estimated deep body temperature, controlling the operation of the physical condition estimation device according to the detected state of the person, and is installed in an area where the person can wake up, and the physical condition estimation device estimates the deep body temperature of the person based on the body surface temperature of the person acquired by the thermo camera, and the body temperature of the person based on the estimated deep body temperature A state is detected, and equipment used by the person is controlled according to the detected state of the person.

In addition, these generic or specific aspects may be realized by a system, method, integrated circuit, computer program, or a recording medium such as a computer-readable CD-ROM. Any combination of programs and recording media may be used.

The physical condition estimation method of the present invention can estimate a person's physical condition without requiring prior calibration.

FIG. 1 is a block diagram showing a configuration of a physical condition estimation device according to Embodiment 1. FIG. FIG. 2 is a block diagram showing an example of a detailed configuration of a blood flow measurement unit in FIG. 1. As shown in FIG. FIG. 3 is a block diagram showing an example of a detailed configuration of a physical condition estimation unit in FIG. 1; FIG. 4 is a diagram showing an example of the Russell annulus model. FIG. 5 is a diagram showing an example of output control of the physical condition estimation device in FIG. FIG. 6 is a flow chart showing an outline of the operation of the physical condition estimation device shown in FIG. FIG. 7 is a diagram illustrating an example of output control of the physical condition estimation device according to the first embodiment. FIG. 8 is a flow chart showing an example of an output control method of the physical condition estimation device according to the first embodiment. FIG. 9 is a diagram illustrating an example of output control of the physical condition estimation device according to the second embodiment. FIG. 10 is a flowchart illustrating an example of an output control method of the physical condition estimation device according to the second embodiment. FIG. 11 is a flowchart illustrating an example of an output control method of the physical condition estimation device according to the third embodiment. 12 is a block diagram showing a configuration of a physical condition estimation device according to Embodiment 2. FIG. FIG. 13 is a block diagram showing an example of the detailed configuration of the emotion estimating unit in FIG. 12; 14A is a diagram showing an example of usage of the Russell annulus model used by the emotion estimation unit in FIG. 12. FIG. FIG. 14B is a diagram showing an example of the Schlossberg cone model used by the emotion estimation unit 24 of FIG. 15 is a block diagram showing an example of the detailed configuration of the physical condition estimation unit of FIG. 12. FIG. 16 is a flow chart showing an outline of the operation of the physical condition estimation device shown in FIG. 12. FIG. 17 is a diagram showing an example of output control of the physical condition estimation device in the example of the second embodiment. FIG. 18 is a diagram illustrating an example of output control of the physical condition estimation device according to Modification 1 of Embodiment 2. FIG. 19 is a diagram illustrating an example of output control of a physical condition estimation device according to Modification 2 of Embodiment 2. FIG. FIG. 20 is a flow chart showing an example of an epileptic seizure estimation and output control method. FIG. 21 is a diagram for explaining one mode of output control depending on the detection result of core body temperature. FIG. 22 is a flow chart showing an example of an output control method dependent on the detection result of core body temperature.

A physical condition estimation method according to an aspect of the present invention is a physical condition estimation method executed by a computer, wherein the computer simultaneously measures blood flow in at least two parts of a human body; and a physical condition estimation step in which the computer estimates the physical condition of the person based on the blood flow rates of the at least two sites measured in the blood flow measurement step.

According to the above aspect, even when the computer estimates the physical condition of a person by measuring the blood flow volume, which varies from person to person, the physical condition of the person can be estimated without prior calibration.

Further, for example, in the blood flow measurement step, as the blood flow at the at least two sites, the blood flow at a first site that does not change with the person's physical condition and at a second site that varies with the person's physical condition is measured. may be

Here, for example, the first portion may be the person's forehead, and the second portion may be at least one of the person's lower eyes, nose, lips, limbs, and neck. good too.

Further, for example, in the blood flow measurement step, blood flow in the forehead of the person and blood flow in the lower part of the eye of the person are measured as the blood flow in the at least two parts, and in the physical condition estimation step, the As the physical condition of the person, the sleep time of the person may be estimated.

Also, for example, in the blood flow measurement step, the blood flow in the person's forehead and the blood flow in one of the person's nose, lips, and limbs are measured as the blood flow in the at least two parts. Further, in the physical condition estimation step, the physical condition of the person may be a degree of heat and cold that the person feels.

Further, for example, in the blood flow measurement step, blood flow in the forehead of the person and blood flow in the neck of the person are measured as the blood flow in the at least two parts, and in the physical condition estimation step, the blood flow in the person's neck is measured. As the physical condition of the person, the presence or absence of stiff shoulders of the person may be estimated.

Further, for example, an emotion estimation step of estimating the emotion of the person based on the physiological quantity of the person, and an emotion estimated in the physical condition estimation step based on the emotion estimated in the emotion estimation step. and a correction step of correcting the physical condition of the person.

Here, for example, the physiological quantity of the person may be blood flow in one of the at least two regions.

Further, for example, the physiological quantity of the person may be a blood flow volume of a part of the person that is different from the at least two parts.

Further, for example, the physiological quantity of the person is the color of the face, heart rate, heart rate variability, LF/HF (Low Frequency/High Frequency) of heart rate variability, RR interval, pulse wave, pulse variability, electroencephalogram, Respiratory rate, respiratory volume, blood flow, blood flow variability, blood pressure, blood pressure variability, oxygen saturation, movement of body parts, movement of body muscles, movement of facial muscles, body temperature, skin temperature, skin conductance, skin resistance , amount of sweat and/or rate of sweat.

Further, for example, in the blood flow measurement step, by irradiating each of the at least two locations with light of a predetermined wavelength and receiving light of different wavelengths, blood flow at the at least two locations may be measured in a non-contact manner. good too.

Here, for example, in the blood flow measurement step, the blood flow at the at least two locations may be measured using a camera.

In addition, a physical condition estimation device according to an aspect of the present invention includes a blood flow measuring unit that simultaneously measures blood flow in at least two parts of a human body, and the at least two blood flow measuring parts measured by the blood flow measuring unit. a physical condition estimating unit for estimating the physical condition of the person based on the blood flow volume of the site;

In addition, these general or specific aspects may be realized by a system, method, integrated circuit, computer program, or a recording medium such as a computer-readable CD-ROM. Or it may be realized by any combination of recording media.

Hereinafter, a physical condition estimation method and the like according to one aspect of the present invention will be specifically described with reference to the drawings. It should be noted that each of the embodiments described below is a specific example of the present invention. Numerical values, shapes, materials, constituent elements, arrangement positions of constituent elements, and the like shown in the following embodiments are examples, and are not intended to limit the present invention. In addition, among the constituent elements in the following embodiments, constituent elements that are not described in independent claims representing the highest concept will be described as arbitrary constituent elements.

(Embodiment 1)
[Configuration of physical condition estimation device]
FIG. 1 is a block diagram showing the configuration of a physical condition estimation device 10 according to Embodiment 1. As shown in FIG.

The physical condition estimation device 10 includes a blood flow measurement unit 11, a physical condition estimation unit 12, and an output control unit 13, as shown in FIG. The physical condition estimation device 10 is realized by a computer or the like.

<Blood flow measurement unit 11>
FIG. 2 is a block diagram showing an example of the detailed configuration of the blood flow measurement unit 11 in FIG. 1. As shown in FIG.

As shown in FIG. 2, the blood flow measurement unit 11 includes a camera unit 111 and a blood flow measurement processing unit 112, and simultaneously measures blood flow in at least two parts of the human body. Here, the blood flow volume of at least two parts is a first part which does not fluctuate with the physical condition of the person and a second part which fluctuates with the physical condition of the person. For example, the first portion is a person's forehead, and the second portion is at least one of the person's lower eye, nose, lips, limbs, and neck.

More specifically, the camera unit 111 is, for example, a laser speckle camera, a laser Doppler blood flow meter, or the like, and irradiates light of a predetermined wavelength to each of the at least two locations and receives light of different wavelengths. The blood flow measurement processing unit 112 measures the blood flow at the at least two locations in a non-contact manner based on the lights of different wavelengths received by the camera unit 111 .

Note that the camera unit 111 may be composed of one camera as long as it can measure blood flow at at least two locations at the same time, or may be composed of a device different from a camera such as a millimeter wave sensor or a pulse oximeter. may be

<Physical condition estimation unit 12>
FIG. 3 is a block diagram showing an example of the detailed configuration of the physical condition estimation unit 12 in FIG. FIG. 4 is a diagram showing an example of the Russell annulus model.

As shown in FIG. 3, the physical condition estimating unit 12 includes a blood flow acquisition unit 121 and a physical condition estimation processing unit 122. Based on the blood flow in at least two parts measured by the blood flow measuring unit 11, the physical condition estimating unit 12 to estimate the physical condition of

More specifically, the blood flow acquisition unit 121 acquires blood flow at at least two sites measured by the blood flow measurement unit 11 . The physical condition estimation processing unit 122 estimates the physical condition of the person based on the blood flow volumes of at least two parts acquired by the blood flow acquisition unit 121 .

Here, as blood flow volumes in at least two parts, it is preferable to measure blood flow volumes in a first part that does not fluctuate with a person's physical condition and a second part that fluctuates with a person's physical condition. Also, as described above, for example, the first part is the person's forehead, and the second part is at least one of the person's lower eye, nose, lips, limbs, and neck. Thereby, the physical condition estimating unit 12 can estimate the physical condition of the person from the blood flow rate of the second region based on the blood flow rate of the first region without requiring prior calibration.

In the present embodiment, the physical condition of a person means a state of mind and body other than emotions, which is a state of mind of a person defined by the Russell annulus model, which is a two-dimensional model shown in FIG. Therefore, a person's physical condition includes, for example, sleep time, degree of heat and cold such as hot or cold, stiff shoulders, facial spots, dry skin, and the like.

For example, when the blood flow measuring unit 11 measures the blood flow in at least two parts, the blood flow in the person's forehead and the blood flow in the lower part of the eye of the person, the physical condition estimating unit 12 measures the physical condition of the person. , may estimate a person's sleep time. When a person sleeps for a short time, dark circles appear and the blood flow in the lower part of the eye decreases. Therefore, the sleep time of the person on the previous day (or the day) can be estimated from the blood flow.

Further, for example, when the blood flow measurement unit 11 measures the blood flow in at least two parts, the blood flow in the person's forehead and the blood flow in one of the person's nose, lips, and limbs, The physical condition estimating unit 12 may estimate the degree of heat and cold felt by the person as the physical condition of the person. When it is hot, the temperature of the nose is relatively higher than that of the forehead, and when it is cold, the temperature is reversed.

Further, for example, when the blood flow measuring unit 11 measures the blood flow in the forehead of a person and the blood flow in the neck of the person as the blood flow in at least two parts, the physical condition estimating unit 12 measures the physical condition of the person. As such, the presence or absence of stiff shoulders of the person may be estimated. With respect to the blood flow in the forehead and neck, if the blood flow in the neck is relatively low, stiff neck occurs (or may occur). . Here, instead of stiff shoulders, headache may be estimated as the physical condition of the person. With respect to the blood flow between the forehead and the neck, when the blood flow in the neck is relatively low, headaches are more likely to occur in addition to stiff shoulders.

Although the forehead is exemplified as the first part here, it is not limited to the forehead. Any other site may be used as long as the blood flow rate is relatively small under fluctuations in physical condition, such as the oral cavity or the eyeball.

Also, the blood flow measurement unit 11 may measure the blood flow of the entire face of the same person every day. In this case, the physical condition estimating unit 12 determines that the physical condition of the person is based on the fluctuation amount of the blood flow measured daily, and the blood flow is locally reduced and the person's face is starting to develop spots. It can be estimated that

<Output control unit 13>
The output control unit 13 performs output control according to the physical condition of the person estimated by the physical condition estimation unit 12 .

FIG. 5 is a diagram showing an example of output control of the physical condition estimation device 10 in FIG. FIG. 5 shows an example in which the previous day's sleep time estimated from the blood flow in the forehead and under the eyes of the person 50 is output to the display surface 61 of the mobile terminal 60 such as a smart phone of the person 50. there is

Note that the output control of the physical condition estimation device 10 (output control unit 13) is not limited to the example shown in FIG.

(time of sleeping)
For example, the output control unit 13 may predict what time the person is likely to be sleepy today based on the sleep time estimated as the person's physical condition by the physical condition estimation unit 12 . Then, when the physical condition estimation device 10 is mounted in a car, the output control unit 13 may send a notification prompting a break to the car navigation screen or the mobile terminal of the user when the time approaches. Also, if the physical condition estimation device 10 is installed in the space where the person is present, the output control unit 13 may brighten the lighting to encourage awakening when the time approaches.

Further, when the output control unit 13 determines that the cumulative sleep time estimated by the physical condition estimation unit 12 is short, the output control unit 13 may notify the company where the person works to encourage rest.

In addition, the output control unit 13 expresses the sleep time estimated by the physical condition estimation unit 12 as the person's today's concentration level and productivity, and notifies the person via a mobile terminal such as a smartphone. good too.

Note that the output control unit 13 may determine not only the sleeping hours of the previous day estimated by the physical condition estimating unit 12 but also the sleeping hours of a plurality of days including the previous day as the sleeping hours.

Further, the output control unit 13 may set the person's insurance premium based on the sleeping hours for a plurality of days estimated by the physical condition estimation unit 12 and notify the person. Here, the insurance premium refers to the insurance premium for life insurance, automobile insurance, or the like. If sleep time is shorter than the specified time, the possibility of drowsy driving increases and the risk of lifestyle-related diseases increases. may be notified to

(Degree of heat and cold, presence or absence of stiff shoulders, etc.)
In addition, the output control unit 13 controls the air volume, air temperature, wind direction, etc. of the air conditioner in the space where the person is in accordance with the degree of coldness such as hot cold or cold estimated as the physical condition of the person by the physical condition estimation unit 12. You may

When the physical condition estimating unit 12 estimates that the person has stiff shoulders as a physical condition of the person, the output control unit 13 is configured to prevent stiff shoulders and reduce stiff shoulders when the physical condition estimating device 10 is mounted in a vehicle. Alternatively, the seat heater of the vehicle may be controlled to heat the shoulder area.

In addition, the output control unit 13 expresses the degree of stiff shoulders estimated by the physical condition estimation unit 12 as the person's degree of concentration and productivity today, and notifies the person via a mobile terminal such as a smartphone. may Furthermore, when the output control unit 13 confirms that the degree of stiff shoulders estimated by the physical condition estimation unit 12 is severe or that stiff shoulders occur frequently, the output control unit 13 sends a message to a smartphone or the like that a massage or a clinic should be performed. A proposal may be made to the person via a portable terminal such as a mobile terminal, a method of relieving it may be proposed, or a means of relieving the stiff shoulder may be proposed by other means.

When the physical condition estimating unit 12 estimates that the physical condition of the person is that the person has blemishes on the face, the output control unit 13 notifies the user via a portable terminal such as a smart phone that the person should receive a massage or the like. A proposal may be made to the person himself/herself, a method for reducing the blemish may be proposed, or a means for alleviating the blemish may be proposed.

[Operation of physical condition estimation device 10]
Next, the operation of the physical condition estimation device 10 described above will be described with reference to FIG. FIG. 6 is a flow chart showing an outline of the operation of the physical condition estimation device 10 shown in FIG. The operation of the physical condition estimation device 10 is executed by a computer provided in the physical condition estimation device 10 .

First, the physical condition estimation device 10 simultaneously measures blood flow in at least two parts of a person (S11). Next, the physical condition estimation device 10 estimates the physical condition of the person based on the measured blood flow volumes of at least two sites (S12). Then, the physical condition estimation device 10 performs output control according to the estimated physical condition (S13).

[Effects, etc.]
As described above, according to the physical condition estimation method and the like in the present embodiment, even when the computer estimates the physical condition by measuring the blood flow volume that varies among individuals, the physical condition of the person can be estimated without prior calibration. physical condition can be estimated.

More specifically, the physical condition estimating method and physical condition estimating device according to the present embodiment measure blood flow in at least two parts of a human body, such as a part that does not fluctuate with the human physical condition and a part that fluctuates with the human physical condition. are measured at the same time. Accordingly, the physical condition of a person can be estimated based on the measured blood flow volumes of at least two sites without requiring prior calibration.

In the above embodiment, the physical condition of a person is described as including, for example, sleep time, degree of coldness such as hot or cold, stiff shoulders, spots on the face, dryness of the skin, etc. However, examples of physical conditions of a person are described. is not limited to these. As a person's physical condition, it includes the level of wanting to go to the toilet, the level of motion sickness, the risk of heat shock, the risk of increased blood pressure during defecation, the level of drunkenness, the driving skill, the level of hunger, the level of fatigue, the level of depression, etc. good too. These examples will be described as Examples 1 to 9 below.

(Example 1)
In the first embodiment, a case of estimating the level of desire to go to the toilet as a person's physical condition will be described.

FIG. 7 is a diagram illustrating an example of output control of the physical condition estimation device 10 according to the first embodiment. FIG. 8 is a flowchart showing an example of an output control method of the physical condition estimation device 10 according to the first embodiment.

In this embodiment, for example, the physical condition estimation apparatus 10 measures the blood flow in the forehead of the person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and The level of the person's desire to go to the toilet is estimated as the physical condition of the person based on the amount of blood flow under the eyes of the person. When a person becomes tense due to wanting to go to the toilet, etc., the blood flow between the forehead and the lower part of the eye relatively decreases, so it is possible to estimate the level of the person's desire to go to the toilet.

Assuming that the physical condition estimation device 10 according to the present embodiment is mounted in a vehicle, the physical condition estimation device 10 according to the present embodiment estimates that the person's level of wanting to go to the bathroom is equal to or higher than the threshold, As shown in FIG. 7, a public toilet 71 may be displayed on the car navigation screen 70 to guide the route there.

In addition, as shown in FIG. 8, the physical condition estimation device 10 estimates the person's level of wanting to go to the bathroom (S121), and if the estimated level of wanting to go to the toilet of the person is lower than the threshold (S131 No), if it is within a predetermined distance, it may be guided to a clean toilet even if it is a little far away (S132). On the other hand, if the estimated level of the person's desire to go to the toilet is higher than the threshold (Yes in S131), the user may be guided to an empty and nearby toilet regardless of how clean the toilet is (S133).

In this way, the physical condition estimation device 10 may change the guidance method according to the estimated level of the person's desire to go to the bathroom.

It should be noted that the method of estimating the person's level of wanting to go to the toilet as a person's physical condition is not limited to the one based on the blood flow of two or more sites as described above. The level of desire to go to the toilet may be estimated from the heart rate fluctuation, blood pressure fluctuation, and facial expression of the person. When a person wants to go to the bathroom, their heart rate increases, their blood pressure increases, and their facial expression becomes a restrained expression (e.g., clenching their teeth). can be estimated. Here, heart rate, blood pressure, and facial expression may all be used to estimate a person's level of wanting to go to the bathroom. You can estimate the level you want to go to.

(Example 2)
In a second embodiment, a case of estimating a motion sickness level as a person's physical condition will be described.

FIG. 9 is a diagram illustrating an example of output control of the physical condition estimation device 10 according to the second embodiment. FIG. 10 is a flow chart showing an example of an output control method of the physical condition estimation device 10 according to the second embodiment.

In this embodiment, for example, the physical condition estimation apparatus 10 measures the blood flow in the forehead of the person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and The motion sickness level of the person is estimated as the physical condition of the person based on the amount of blood flow under the eyes of the person. When a person becomes tense due to motion sickness, etc., the physical condition estimating device 10 can estimate the motion sickness level of the person because the blood flow between the forehead and the lower part of the eye relatively decreases. .

Assuming that the physical condition estimating device 10 is mounted in a car, when the physical condition estimating device 10 estimates that the person's motion sickness level is equal to or higher than the threshold, the car navigation screen 70 displays A parking area 72 for resting may be displayed, and the route to that area may be guided. Of course, the method of informing the driver of the person's situation is not limited to this. For example, the situation of the person is communicated to the driver by displaying the information on the car navigation screen 70 or the instrument panel, or by using the driver's portable terminal or the in-vehicle speaker to convey the information by voice. Any method is acceptable.

For example, as shown in FIG. 10, the physical condition estimation device 10 estimates the person's motion sickness level (S121A). and estimate the person's motion sickness level after a certain period of time. On the other hand, if the person's estimated motion sickness level is higher than the threshold (Yes in S131A), a device control signal for controlling devices such as the brake, accelerator, and active suspension of the vehicle may be output (S133A).

As a result, it is possible to reduce the sensitivity of the accelerator and brakes to reduce sudden starts and accelerations so that the person does not get sick any more, or to soften the active suspension to reduce vibrations applied to the body. In addition, by controlling the device in this way, even if the person is a child and cannot say that he or she has motion sickness, it is possible to prevent the person from vomiting in the car or prevent the person from getting motion sickness from rising. can. Furthermore, if the car is a taxi, it is possible to prevent the inconvenience caused by the taxi by letting the customer get off before the customer vomits or by refusing to board the customer. can.

Note that the method for estimating the motion sickness level of the person as the physical condition of the person is not limited to the one based on the blood flow volume of two or more parts as described above. The motion sickness level may be estimated from the person's facial expression, heart rate and blood pressure information. When people get motion sickness, their facial expressions turn pale and they look sick, and the time-series correlation (ρmax) between heart rate fluctuations and blood pressure fluctuations decreases. A person's motion sickness level can be estimated. here,
A person's motion sickness level may be estimated using both ρmax and facial expression, or any one of them may be used to estimate a person's motion sickness level.

(Example 3)
In a third embodiment, a case of estimating the risk of heat shock as a physical condition of a person will be described. Here, heat shock refers to vascular disorders such as fainting, myocardial infarction, and cerebral infarction that occur with sudden changes in blood pressure. There are many cases of heat shock due to a sudden rise in blood pressure when undressing in a cold dressing room before bathing, or a sudden rise in blood pressure when entering hot water.

In this embodiment, the physical condition estimating apparatus 10 measures, for example, the blood flow in the forehead of a person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and the Based on the amount of blood flow under the eyes of the person and the physical condition of the person, the degree of risk of heat shock of the person is estimated. When a person is cold, the blood flow in the lower part of the eye is relatively low, and when it is hot, the blood flow in the lower part of the eye is relatively high. can estimate the degree of danger to

FIG. 11 is a flowchart showing an example of an output control method of the physical condition estimation device 10 according to the third embodiment.

For example, as shown in FIG. 11, the physical condition estimation device 10 estimates the risk of heat shock of the person (S121C), and if the estimated risk of heat shock of the person is lower than the threshold (S131C No), the process may return to S11 and estimate the person's risk of heat shock after a certain period of time. On the other hand, if the estimated risk of heat shock for the person is higher than the threshold (Yes in S131C), a device control signal including an instruction to turn on the heating is output in order to raise the ambient temperature of the person. (S133C).

As a result, sudden changes in blood pressure of the person can be prevented, and heat shock can be prevented.

Note that the output control method of the physical condition estimation device 10 when the estimated risk of heat shock for the person is higher than the threshold is not limited to the method described above. For example, if the person is in the dressing room or the restroom, the person may be notified to that effect and be encouraged to turn on the heating. Further, for example, the physical condition estimation device 10 includes an instruction such as adding water to the hot water when the person is bathing in the bathroom and the estimated risk of heat shock for the person is higher than a threshold. A control signal may be output. As a result, by lowering the temperature of the hot water in which the person is bathing, sudden blood pressure fluctuations can be prevented.

It should be noted that the method of estimating the degree of risk of heat shock of the person as the physical condition of the person is not limited to the method based on the blood flow rate of two or more sites as described above. The risk of heat shock may be estimated from the person's blood pressure information. If the blood pressure can be constantly measured, it can be estimated that the risk of heat shock is increasing, for example, when the blood pressure reaches a predetermined value or higher.

Here, instead of the predetermined value, a plurality of thresholds may be provided to estimate the degree of risk of heat shock in stages. The blood pressure threshold for judging that the risk of heat shock is increasing can be adjusted based on the degree of arteriosclerosis. The degree of arteriosclerosis can be estimated from pulse pressure (maximal blood pressure and minimum blood pressure) or from pulse wave transit time, and the method is not limited.

Further, the blood pressure threshold is not limited to being adjusted based on arteriosclerosis, and may be adjusted based on age or the amount of water in the body. This is because when the amount of water in the body is reduced, the blood pressure fluctuates rapidly, and heat shock is likely to occur. As long as it can be determined that the risk of heat shock is increasing, other methods may be used for adjustment.

Note that the degree of arteriosclerosis may be manually input based on the results of a physical examination, etc., instead of being detected in a non-contact manner, and similarly, the age may also be manually input.

In addition, if it is possible to constantly measure blood pressure, warnings and notifications such as warnings may be issued according to the degree of arteriosclerosis and water content, and changes in the person's blood pressure may be seen within sight of the person. It does not matter if it is displayed.

(Example 4)
In a fourth embodiment, a case of estimating the degree of risk due to an increase in blood pressure during defecation as a physical condition of a person will be described. During defecation, a person strains to promote excretion, but this straining increases blood pressure, which may cause fainting, myocardial infarction, cerebral infarction, and other vascular disorders.

In this embodiment, the physical condition estimating apparatus 10 measures, for example, the blood flow in the forehead of a person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and the Based on the amount of blood flow under the eyes of the person and the physical condition of the person, the degree of risk due to an increase in blood pressure during defecation of the person is estimated. When a person has a bowel movement, the blood flow in the forehead and the lower part of the eye relatively increases due to straining.

Then, when the physical condition estimation apparatus 10 according to the present embodiment estimates that the degree of risk due to an increase in blood pressure during defecation of the person is equal to or greater than a predetermined value, the physical condition estimation apparatus 10 notifies the user to that effect and encourages the user to reduce strain. Alternatively, a warm-water washing toilet seat may be controlled by a device, and water may be sprayed near the anus by a shower to reduce straining and encourage defecation.

As a result, sudden changes in blood pressure of the person can be prevented, and vascular disorders can be prevented.

It should be noted that the method of estimating the degree of risk due to an increase in blood pressure during defecation of a person as a physical condition of the person is not limited to the method based on the blood flow at two or more sites as described above. From the blood pressure information of the person, the degree of risk due to an increase in blood pressure during defecation may be estimated. If the blood pressure can be constantly measured, for example, when the blood pressure reaches a predetermined value or higher, it can be estimated that the risk of increased blood pressure during defecation is increasing.

Here, instead of the predetermined value, a plurality of threshold values may be provided to estimate the degree of risk due to an increase in blood pressure during defecation in stages. The blood pressure threshold for judging that the risk of increased blood pressure during defecation is increasing can be adjusted based on the degree of arteriosclerosis. The degree of arteriosclerosis can be estimated from pulse pressure (maximal blood pressure and minimum blood pressure) or from pulse wave transit time, but any means is acceptable.

Further, the blood pressure threshold is not limited to being adjusted based on arteriosclerosis, and may be adjusted based on age or the amount of water in the body. This is because when the amount of water in the body is reduced, the blood pressure fluctuates rapidly, and heat shock is likely to occur. As long as it can be determined that the risk of heat shock is increasing, other methods may be used for adjustment.

Note that the degree of arteriosclerosis may be manually input based on the results of a physical examination, etc., instead of being detected in a non-contact manner, and similarly, the age may also be manually input.

In addition, if it is possible to constantly measure blood pressure, warnings and notifications such as warnings may be issued according to the degree of arteriosclerosis and water content, and changes in the person's blood pressure may be seen within sight of the person. It does not matter if it is displayed.

(Example 5)
In the fifth embodiment, a case of estimating a drunkenness level as a person's physical condition will be described.

In this embodiment, the physical condition estimating apparatus 10 measures, for example, the blood flow in the forehead of a person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and the The drunkenness level of the person is estimated as the physical condition of the person based on the amount of blood flow under the eyes of the person. As for blood flow between the forehead and the lower part of the eye, when a person gets drunk, the blood flow in the lower part of the eye increases relatively, and when a person feels sick due to drinking, the blood flow in the lower part of the eye increases relatively. , the person's drunkenness level can be estimated.

When the physical condition estimating device 10 according to the present embodiment estimates that the drunkenness level of the person is equal to or higher than a predetermined value, that is, the person is in a drunken state, the physical condition estimating device 10 according to the present embodiment may be controlled (equipment control) so that the engine of the automobile cannot be started. This can prevent the person from driving a car while intoxicated.

In addition, when the physical condition estimation apparatus 10 according to the present embodiment estimates that the person's drunkenness level is equal to or higher than a predetermined value, that is, that the person is overdrinking, the physical condition estimation apparatus 10 notifies the user of the fact or informs the user of the drunkenness level of the person. may be displayed. As a result, the person can be made aware of his/her own overdrinking level, and the person can be prevented from overdrinking.

It should be noted that the method of estimating the drunkenness level of the person as the physical condition of the person is not limited to the one based on the blood flow of two or more parts as described above. The person's drunkenness level may be estimated from the person's facial expression, heart rate, blood pressure information, blood flow, and breath information. When a person becomes intoxicated, the gaze becomes unsteady, the blood circulation improves and the heart rate increases, the complexion turns red, the blood pressure drops due to being relaxed after being drunk, and the alcohol in the breath. The drunkenness level of the person can be estimated from the increase in concentration. All of these pieces of information may be used to estimate the drunkenness level of the person, or any one of them may be used, or a combination of a plurality of pieces of information may be used for estimation.

(Example 6)
In a sixth embodiment, a case of estimating driving skill as a person's physical condition will be described.

In this embodiment, the physical condition estimating apparatus 10 measures, for example, the blood flow in the forehead of a person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and the The driving skill of the person is estimated as the physical condition of the person based on the amount of blood flow under the eyes of the person. In terms of the blood flow between the forehead and the lower part of the eye, people do not get nervous when their driving skills are high and they are comfortable driving. Since the blood flow in the lower part of the eye is relatively decreased due to tension, it is possible to estimate the driving skill of the person.

When the physical condition estimating apparatus 10 according to the present embodiment estimates that the person's driving skill is lower than a predetermined value, that is, that the person is in a state of not being able to afford to drive, the physical condition estimation apparatus 10 performs device control to increase the sensitivity of the brake to increase the inter-vehicle distance. The speed may be kept moderate, or the device may be controlled to reduce the sensitivity of the accelerator. As a result, even when the driving skill of the person is low and there is no leeway, it is possible to guide the person to drive with a lot of leeway.

It should be noted that the method of estimating the driving skill of the person as the physical condition of the person is not limited to the one based on the blood flow of two or more parts as described above. The person's driving skill may be estimated from the person's facial expression and heart rate fluctuations. It is possible to estimate the amount of leeway in driving from a person's facial expression. A person's driving skill can be estimated. All of these pieces of information may be used to estimate the driving skill of the person, any one of them, or a combination of a plurality of pieces of information may be used for estimation.

When the physical condition estimating apparatus 10 according to the present embodiment is mounted in a vehicle and the physical condition of the person is estimated based on the facial expression of the person, fear may be estimated as the physical condition of the person. For example, the physical condition estimation device 10 according to the present embodiment estimates whether or not there is fear from the facial expression of the passenger of the vehicle when the vehicle is automatically driven. Then, if it is estimated that the person has fear, that is, that the person has no leeway (unreliable autonomous driving), the vehicle equipment may be controlled to set the distance between vehicles to be large and the speed to be low. . This makes it possible to give a sense of security to the person riding in the vehicle.

Furthermore, when the physical condition estimation device 10 according to the present embodiment recognizes that the passenger is looking at the car window during automatic driving based on the person's facial expression, the vehicle speed is reduced. device may be controlled. By doing so, the person can slowly look at the car window.

(Example 7)
In a seventh embodiment, a case of estimating a hunger level as a person's physical condition will be described.

In this embodiment, the physical condition estimating apparatus 10 measures, for example, the blood flow in the forehead of a person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and the The hunger level of the person is estimated as the physical condition of the person based on the amount of blood flow under the eyes of the person. When a person's hunger level increases, the blood flow in the forehead and the lower part of the eye is stressed, and the blood flow in the lower part of the eye relatively decreases. Therefore, the hunger level of the person can be estimated.

Assuming that the physical condition estimating apparatus 10 according to the present embodiment is installed in an office, the physical condition estimating apparatus 10 according to the present embodiment estimates that the person's hunger level is equal to or higher than a predetermined value, that is, the person's hunger. In this case, the illumination may be controlled (equipment control) so as to increase the blue component contained in the illumination. This is because viewing blue light has the effect of reducing hunger.

Also, if the physical condition estimation device 10 according to this embodiment is installed in a car, the physical condition estimation device 10 according to this embodiment estimates that the person's hunger level is equal to or higher than a predetermined value, that is, the person's hunger. In this case, the car navigation screen may display nearby restaurants from the current location and guide the route there.

It should be noted that the method of estimating the hunger level of the person as the physical condition of the person is not limited to the one based on the blood flow volume of two or more parts as described above. The person's hunger level may be estimated from the person's blood sugar level, breath information, and abdominal sounds. When a person becomes hungry, the blood sugar level decreases, the amount of acetone contained in exhaled air increases, and the abdominal sound increases due to increased gastrointestinal activity. be able to. Then, the hunger level of the person may be estimated using all of these pieces of information, any one of them, or a combination of a plurality of them.

(Example 8)
In an eighth embodiment, a case of estimating a fatigue level as a person's physical condition will be described.

In this embodiment, the physical condition estimating apparatus 10 measures, for example, the blood flow in the forehead of a person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and the The fatigue level of the person is estimated as the physical condition of the person based on the amount of blood flow under the eyes of the person. When a person's fatigue level increases, the person is stressed, and the blood flow between the forehead and the lower part of the eye relatively decreases, so the fatigue level of the person can be estimated.

Assuming that the physical condition estimating device 10 according to the present embodiment is mounted in a vehicle, the physical condition estimating device 10 according to the present embodiment estimates that the fatigue level of the person is equal to or higher than a predetermined value. device may be controlled to audibly encourage a break, or control may be performed to switch to automatic driving so that the fatigue of the driver, who is the person in question, does not increase any further.

It should be noted that the method of estimating the fatigue level of the person as the physical condition of the person is not limited to the one based on the blood flow of two or more sites as described above. The fatigue level of the person may be estimated from the person's facial expression, oxygen saturation in the bloodstream, and lactic acid concentration. When a person gets tired, the oxygen saturation level in the blood decreases, the lactic acid concentration increases, and a feeling of fatigue appears in the facial expression, so the fatigue level of the person can be estimated. All of these pieces of information may be used to estimate the fatigue level of the person, or any one of them may be used, or a combination of a plurality of pieces of information may be used for estimation.

(Example 9)
In the ninth embodiment, a case of estimating a depression level as a person's physical condition will be described.

In this embodiment, the physical condition estimating apparatus 10 measures, for example, the blood flow in the forehead of a person and the blood flow in the lower part of the eye of the person as the blood flow in at least two parts, and measures the blood flow in the forehead and the The depression level of the person is estimated as the physical condition of the person based on the amount of blood flow under the eyes of the person. A person is stressed when the depression level is high, and the blood flow between the forehead and the lower part of the eye is relatively low, so the depression level of the person can be estimated.

Then, the physical condition estimation device 10 according to the present embodiment may control the lighting of the room when it is estimated that the person's depression level is equal to or higher than a predetermined value, that is, the person is in a depressed state. Controlling the lighting in a room, for example making it brighter in the morning and darker at night, can regulate the person's circadian rhythm and alleviate depression. When the physical condition estimation apparatus 10 according to the present embodiment estimates that the depression level of the person is equal to or higher than a predetermined value, i.e., that the person is in a depressed state, the physical condition estimation apparatus 10 plays uplifting music in the morning and relaxing music in the evening. A music device may be controlled to play.

It should be noted that the method of estimating the depression level of the person as the physical condition of the person is not limited to the one based on the blood flow of two or more sites as described above. The person's depression level may be estimated from the person's facial expression and heartbeat interval. It is known that when a person is depressed, the proportion of time during which the parasympathetic nervous system is activated is reduced in relation to fluctuations in the autonomic nervous system during the day. The depression level of the person can be estimated from the ability to examine the rate of parasympathetic activation. In addition, it is known that when a person is in a depressed state, he/she can see facial expressions peculiar to the depressed state (for example, expressionlessness that does not match the viewpoint). Depressed state can be estimated from the change in facial expression when the image is shown. All of these pieces of information may be used to estimate the depression level of the person, any one of them, or a combination of a plurality of pieces of information may be used for estimation.

(Embodiment 2)
In Embodiment 1, a case has been described in which a person's physical condition is estimated based on a person's physiological quantity such as blood flow in at least two parts of the person's parts, but the present invention is not limited to this. The physical condition of the person may be estimated by estimating the physical condition of the person based on the physiological quantity and further correcting the physical condition based on the emotion of the person when the physiological quantity is acquired. This case will be described below as a second embodiment.

[Configuration of physical condition estimation device]
FIG. 12 is a block diagram showing the configuration of the physical condition estimation device 20 according to Embodiment 2. As shown in FIG. Elements similar to those in FIG. 1 and the like are denoted by the same reference numerals, and detailed description thereof will be omitted.

The physical condition estimation device 20 includes a blood flow measurement unit 11, a physical condition estimation unit 22, an output control unit 13, and an emotion estimation unit 24, as shown in FIG. This physical condition estimation device 20 is realized by a computer or the like. Physical condition estimating apparatus 20 shown in FIG. 12 differs from physical condition estimating apparatus 10 according to Embodiment 1 in that emotion estimating section 24 is added and physical condition estimating section 22 is configured differently.

<Emotion estimation unit 24>
The emotion estimation unit 24 estimates the emotion of the person based on the person's physiological quantity. More specifically, the emotion estimation unit 24 estimates the person's emotion using the Russell annulus model shown in FIG. 4 based on the person's physiological quantity. Here, the physiological quantity is data related to the function of the living body, and includes, for example, facial color, heart rate, heart rate variability, LF/HF (Low Frequency/High Frequency) of heart rate variability, RR interval, pulse wave , pulse variability, brain waves, respiratory rate, respiratory volume, blood flow, blood flow variability, blood pressure, blood pressure variability, oxygen saturation ₍ SpO2), body part movement, body muscle movement, facial muscle movement, At least one of body temperature, skin temperature, skin conductance, skin resistance, skin roughness, skin shine, perspiration amount and perspiration rate is included. Here, examples of movements of body parts include the frequency and speed of blinking.

Therefore, the emotion estimating unit 24 estimates the emotion of the person, such as the arousal level of the person, based on the blood flow at one of at least two sites measured by the blood flow measuring unit 11 as the physiological amount of the person. You may The emotion estimating unit 24 also determines, as the physiological quantity of the person, the blood flow in at least two parts of the person different from the parts measured by the blood flow measuring unit 11, for example, the arousal level of the person. A person's emotions may be inferred. In addition, the emotion estimating unit 24, as a physiological quantity of a person, can also estimate the person's Emotions may be inferred.

The emotion estimating unit 24 uses the Russell annulus model shown in FIG. From this, the axis of wakefulness/drowsiness may be determined to estimate a person's emotion. This will be explained below.

FIG. 13 is a block diagram showing an example of the detailed configuration of the emotion estimation section 24 of FIG. 12. As shown in FIG. FIG. 14A is a diagram showing an example of usage of the Russell annulus model used by the emotion estimation unit 24 of FIG. FIG. 14B is a diagram showing an example of the Schlossberg cone model used by the emotion estimation unit 24 of FIG.

The emotion estimation unit 24 includes a camera unit 241, a facial expression estimation unit 242, an emotion estimation processing unit 243, and a storage unit 244, as shown in FIG.

People have various emotions such as joy or surprise. The Russell annulus model shown in FIG. 4 is obtained by arranging various emotions that a person has on a plane consisting of an axis of pleasure and displeasure and an axis of arousal and drowsiness. The Russell annulus model shows that various human emotions can be arranged in an annulus on the plane shown in FIG. The arousal/sleepiness axis can be calculated based on the physiological quantity described above, such as a person's heart rate, although it may be difficult to appear in a person's facial expression. On the other hand, the pleasant/unpleasant axis may be calculated from a person's facial expression or the like. By doing so, it is possible to more accurately estimate a person's emotions than by estimating emotions from only facial expressions or physiological quantities.

The storage unit 244 stores data corresponding to the Russell annulus model as shown in FIG. 14, for example.

The camera unit 241 photographs the entire face of the person. The facial expression estimation unit 242 estimates the facial expression of the person based on the person's face captured by the camera unit 241 .

The emotion estimation processing unit 243 refers to data stored in the storage unit 244 and corresponding to the Russell annulus model shown in FIG. 14, for example. The emotion estimation processing unit 243 determines the position on the axis of pleasure and discomfort based on the facial expression of the person estimated by the facial expression estimation unit 242, and from the blood flow of the part of the person measured by the blood flow measurement unit 11, By determining the position on the wake/drowsiness axis, the person's emotion may be estimated. Further, as described above, the emotion estimation processing unit 243 may determine the position on the axis of wakefulness and drowsiness from physiological data such as heartbeat, respiration, pulse wave, and blood pressure. For example, the emotion estimation processing unit 243 may estimate the person's heart rate based on slight changes in the person's facial color estimated by the facial expression estimation unit 242, and determine the position on the axis of wakefulness and drowsiness. Needless to say, such a method of obtaining an emotion is not limited to the case of correcting the estimated physical condition, and can be applied to the case of obtaining only the emotion.

Although the case of estimating emotions using the Russell annulus model has been described here, other models may be used. For example, in the Schlossberg cone model shown in FIG. - Rejection axis may also be calculated based on physiological quantity. By doing so, it becomes possible to estimate emotions more accurately.

<Physical condition estimation unit 22>
FIG. 15 is a block diagram showing an example of the detailed configuration of the physical condition estimation unit 22 of FIG. 12. As shown in FIG. Elements similar to those in FIG. 3 are denoted by the same reference numerals, and detailed description thereof will be omitted.

As shown in FIG. 15, the physical condition estimation unit 22 includes a blood flow acquisition unit 121, a physical condition estimation processing unit 122, an estimated emotion acquisition unit 223, and a correction unit 224. A person's physical condition is estimated based on blood flow volumes at two sites. Physical condition estimating section 22 shown in FIG. 15 has an additional configuration of estimated emotion acquiring section 223 and correcting section 224, compared to physical condition estimating section 12 shown in FIG.

More specifically, the estimated emotion acquiring section 223 acquires the person's emotion estimated by the emotion estimating section 24 . The correction unit 224 corrects the physical condition of the person estimated by the physical condition estimation processing unit 122 based on the person's emotion estimated by the emotion estimation unit 24 .

Here, for example, the case where the physical condition estimation processing unit 122 estimates “stiff shoulder” as the physical condition of the person at a predetermined level and the emotion estimation unit 24 estimates “excited” as the person's emotion will be described as an example. do. Since "excitement" contributes to reducing stiff shoulders by increasing the blood flow of the person, the correction unit 224 can correct the physical condition of the person to "stiff shoulders" at a level lower than the predetermined level. . In this way, the physical condition estimating unit 22 can obtain an estimation result that corrects the physical condition of the person based on the person's emotions.

[Operation of physical condition estimation device 20]
Next, the operation of the physical condition estimation device 20 described above will be described with reference to FIG. FIG. 16 is a flow chart showing an overview of the operation of the physical condition estimation device 20 shown in FIG. The operation of the physical condition estimation device 20 is executed by a computer provided in the physical condition estimation device 20 .

First, the physical condition estimation device 20 simultaneously measures blood flow in at least two parts of the human body (S21). Next, the physical condition estimation device 20 estimates the physical condition of the person based on the measured blood flow volumes of at least two sites (S22). Next, the physical condition estimation device 20 estimates the person's emotion based on the blood flow rate of at least one part (S23). Here, the blood flow rate of one site for estimating a person's emotion may be the site measured for estimating physical condition, or may be another site. Next, the physical condition estimation device 20 corrects the physical condition of the person estimated in S22 based on the emotion of the person estimated in S23 (S24). Then, the physical condition estimation device 20 performs output control according to the corrected physical condition (S25).

[Effects, etc.]
As described above, according to the physical condition estimation method and the like in the present embodiment, even when the computer estimates the physical condition by measuring the blood flow volume that varies between individuals, the physical condition of the person can be estimated without prior calibration. Physical condition can be estimated. Furthermore, according to the physical condition estimation method and the like of the present embodiment, the estimated physical condition can be corrected based on the person's emotion, so the person's physical condition can be estimated in consideration of the person's emotion.

Here, as an example, a case where the estimated physical condition is the level of stiff shoulders and the estimated emotion is the degree of excitement will be described.

(Example)
FIG. 17 is a diagram showing an example of output control of the physical condition estimation device 20A in the example of the second embodiment.

In this embodiment, for example, the blood flow measuring unit 11A measures the blood flow in at least two parts, the blood flow A in the forehead A of the person 50, the blood flow B in the neck B of the person 50, and the nose C of the person 50. Measure the blood flow C of The emotion estimation unit 24A estimates the degree of excitement of the person 50 as the emotion of the person 50 based on the measured blood flow C of the nose C.

The physical condition estimation unit 22 first estimates the stiff shoulder level of the person 50 as the physical condition of the person 50 based on the measured blood flow A of the forehead A and blood flow B of the neck B. Next, the physical condition estimation unit 22 corrects the estimated stiff shoulder level of the person 50 based on the degree of excitement of the person 50 estimated by the emotion estimation unit 24A.

Then, the output control unit 13A outputs and displays the corrected stiff shoulder level on the display surface 62 of the mobile terminal 60 such as a smart phone of the person 50 as output control according to the estimated physical condition of the person.

In addition, although the said embodiment and Example demonstrated correct|amending the estimated physical condition based on a person's emotion, it is not restricted to it. Based on the estimated physical condition of the person, the estimated emotion of the person may be corrected. Modifications 1 and 2 will be described below.

(Modification 1)
Hereinafter, as Modified Example 1, a case where the estimated physical condition is the sleep hours of the previous day and the estimated emotion is the level of drowsiness will be described.

FIG. 18 is a diagram showing an example of output control of physical condition estimation device 20B according to Modification 1 of Embodiment 2. In FIG.

In this modification, for example, the blood flow measuring unit 11B measures blood flow at at least two sites, blood flow A at the forehead A of the person 50, blood flow B at the lower part of the eye B of the person 50, and nose B of the person 50. The blood flow C of C is measured. The physical condition estimating unit 22 first estimates the sleep time of the person 50 the previous day as the physical condition of the person 50 based on the measured blood flow A of the forehead A and the blood flow B of the lower part of the eye B.

The emotion estimation unit 24B, based on the previous day's sleep time of the person 50 estimated by the physical condition estimation unit 22 and the blood flow C of the nose C measured by the blood flow measurement unit 11B, determines the emotion of the person 50 as the emotion of the person 50. Estimate sleepiness level. More specifically, when the nose skin temperature rises, the emotion estimation unit 24B first estimates the drowsiness level (awakening degree) from the blood flow C measured by the blood flow measurement unit 11B. be able to. Next, when the sleep duration of the previous day of the person 50 estimated by the physical condition estimation unit 22 is short (for example, when it is shorter than the average sleep duration of the person 50), the emotion estimation unit 24B calculates the drowsiness level estimated from the blood flow C. It may be corrected to a deeper drowsiness level.

Then, as output control, the output control unit 13B may output and display the corrected sleepiness level on the display surface 63 of the mobile terminal 60 such as a smart phone of the person 50 .

In this manner, the physical condition estimation device 20B may correct the estimated emotion based on the estimated physical condition.

Note that the estimated physical condition is not limited to the number of hours of sleep on the previous day, and may be the degree of heat or cold. For example, when it is estimated that the person 50 feels cold as the physical condition, the drowsiness level estimated as the emotion of the person 50 may be corrected to be lower. Also, the estimated physical condition may be the presence or absence of “stiff shoulders” and the estimated emotion may be the pleasant emotion of the person 50 . For example, when it is estimated that the person 50 has stiff shoulders as a physical condition, the pleasant feeling estimated as the emotion of the person 50 may be corrected to be lower than normal.

(Modification 2)
In Modification 1, the case of estimating the emotion of the person 50 from the blood flow in the nose of the person 50 has been described, but the present invention is not limited to this. As described above, the emotion of the person 50 may be estimated based on the face of the person 50 captured by the camera unit 241 . Hereinafter, this case will be described as Modified Example 2. FIG. In this modified example, it is assumed that the estimated physical condition is the degree of coldness and heat, and the estimated emotion is the drowsiness level.

FIG. 19 is a diagram showing an example of output control of a physical condition estimation device 20C according to Modification 2 of Embodiment 2. In FIG.

In this modified example, for example, the blood flow measurement unit 11 measures the blood flow A of the person 50's forehead A and the blood flow B of the person's 50 lower eye B as the blood flow of at least two sites. The physical condition estimating unit 22 first estimates the degree of coldness and heat of the person 50 as the physical condition of the person 50 based on the measured blood flow A of the forehead A and blood flow B of the lower part of the eye B.

The emotion estimating unit 24 determines sleepiness of the person 50 as the emotion of the person 50 based on the degree of heat and cold of the person 50 estimated by the physical condition estimating unit 22 and the image of the entire face of the person 50 captured by the emotion estimating unit 24. Estimate the level.

More specifically, first, the emotion estimator 24 photographs the entire face of the person 50 . Next, the emotion estimating unit 24 estimates the heart rate of the person 50 from the slight variations in the complexion of the person 50, and determines the position on the axis of wakefulness and drowsiness as shown in FIG. Also, the emotion estimation unit 24 determines the position on the pleasure/displeasure axis from the facial expression estimated from the photographed face of the person 50 . Thereby, the emotion estimating section 24 can estimate the drowsiness level as a person's emotion from the photographed image of the whole face of the person 50 . Then, the emotion estimation unit 24 corrects the drowsiness level estimated from the image of the entire face of the person 50 based on the degree of hot or cold of the person 50 estimated by the physical condition estimation unit 22 . For example, when the physical condition estimating unit 22 estimates that the person 50 feels cold as the physical condition, the emotion estimating unit 24 may perform correction to lower the drowsiness level estimated as the emotion of the person 50. .

Then, as output control, the output control unit 13C may output and display the corrected drowsiness level on the display surface 63C of the mobile terminal 60 such as a smart phone of the person 50. FIG.

Thus, the physical condition estimation device 20C may correct the estimated emotion based on the estimated physical condition.

Although the processing of the present invention has been described in the first and second embodiments, there are no particular restrictions on the subject or device that performs each processing.

For example, as described above, the physical condition estimating device may include a blood flow measuring unit, a physical condition estimating unit, an output control unit, etc., or may include only a physical condition estimating unit or only a physical condition estimating unit and an output controlling unit. good. Also, the physical condition estimation unit and the output control unit may be processed by a cloud server or the like arranged at a location different from the local device. For example, heavy processing and control may be performed on the cloud server side, and light processing and control may be performed on the local device, and processing and control may be distributed between the cloud server device and the local device. Note that the cloud server device and the local device may be collectively called a physical condition estimation device.

It may also be processed by a processor or the like (discussed below) embedded within a particular locally located device.

(1) The physical condition estimation apparatus is specifically a computer system comprising a microprocessor, ROM, RAM, hard disk unit, display unit, keyboard, mouse, and the like. A computer program is stored in the RAM or hard disk unit. The physical condition estimation device achieves its functions by the microprocessor operating according to the computer program. Here, the computer program is constructed by combining a plurality of instruction codes indicating instructions to the computer in order to achieve a predetermined function.

(2) A part or all of the components constituting the physical condition estimation device may be configured from one system LSI (Large Scale Integration).
A system LSI is an ultra-multifunctional LSI manufactured by integrating multiple components on a single chip. Specifically, it is a computer system that includes a microprocessor, ROM, RAM, etc. . A computer program is stored in the RAM. The system LSI achieves its functions by the microprocessor operating according to the computer program.

(3) A part or all of the components constituting the physical condition estimation device may be composed of a detachable IC card or a single module. The IC card or module is a computer system composed of a microprocessor, ROM, RAM and the like. The IC card or the module may include the super multifunctional LSI. The IC card or the module achieves its function by the microprocessor operating according to the computer program. This IC card or this module may be tamper resistant.

(4) The present invention may be the method shown above. Moreover, it may be a computer program for realizing these methods by a computer, or it may be a digital signal composed of the computer program.

(5) The present invention also provides a computer-readable recording medium for the computer program or the digital signal, such as a flexible disk, hard disk, CD-ROM, MO, DVD, DVD-ROM, DVD-RAM, BD ( Blu-ray (registered trademark) Disc), semiconductor memory, or the like. Moreover, it may be the digital signal recorded on these recording media.

Further, according to the present invention, the computer program or the digital signal may be transmitted via an electric communication line, a wireless or wired communication line, a network represented by the Internet, data broadcasting, or the like.

The present invention may also be a computer system comprising a microprocessor and memory, the memory storing the computer program, and the microprocessor operating according to the computer program.

Also, by recording the program or the digital signal on the recording medium and transferring it, or by transferring the program or the digital signal via the network or the like, it can be implemented by another independent computer system. You can do it.

(6) The above embodiments and modifications may be combined.

(7) Also, the physical condition of a person may be other than those described in the first and second embodiments. For example, it may be epileptic seizure, Meniere's disease, dizziness, or the like. In this case, in order to estimate the physical condition of the person, the physiological quantity such as the blood flow of the person may or may not be used. Methods for estimating a person's physical condition other than those exemplified in the first and second embodiments will be described below.

(epileptic seizure)
A method for estimating an epileptic seizure as a person's physical condition and the output when an epileptic seizure is estimated will be described.

Occurrence of an epileptic seizure can be estimated (detected) from a person's gaze, breathing, and pupil diameter. This is because epileptic seizures are known to cause stiffening of the gaze, disturbed breathing, and loss of pupillary light reflex. Therefore, by measuring a person's line of sight, breathing, and pupil diameter, it is possible to estimate (detect) an epileptic seizure as a person's physical condition.

FIG. 20 is a flow chart showing an example of an epileptic seizure estimation and output control method.

As shown in FIG. 20, first, for example, a person's line of sight is detected (S31), and based on the detected person's line of sight, it is estimated whether the person has an epileptic seizure (S32). Here, it is possible to estimate the occurrence of a human epileptic seizure by using all information of a person's line of sight, breathing, and pupils, and even if one of them is used, epileptic seizures can be estimated using a combination of a plurality of them. It is permissible to presume the occurrence of a seizure.

Next, when it is estimated that an epileptic seizure has not occurred (No in S32), the process returns to S31. On the other hand, when it is estimated that an epileptic seizure has occurred in the person (Yes in S32), if the person is in a car, a device that controls the brake, accelerator, active suspension, etc. of the car. A control signal is output (S33).

Furthermore, if the person is in an automatically driven automobile, the person is automatically parked in a safe place or made to go directly to the nearest hospital by automatic operation (S34). In S34, the nearest ambulance or security center may be called.

(Meniere's disease and dizziness)
Next, a method for estimating Meniere's disease or dizziness as a physical condition of a person and an output when Meniere's disease or dizziness is estimated will be described.

By detecting a person's line of sight, Meniere's disease or dizziness of the person can be estimated (detected). This is because it is known that people's eyes are spinning when they have dizziness or Meniere's disease.

Then, when estimating (detecting) a person's Meniere's disease or dizziness, if the person is in a self-driving car, the car's brake, accelerator, and active system will automatically park the car in a safe place. You can control or direct equipment such as suspension. Of course, the nearest ambulance or security center can be immediately called, or control can be performed to automatically drive the car directly to the nearest hospital.

(various diseases)
In addition, the following diseases may be estimated (detected) as a person's physical condition from the following components and secretions contained in exhaled breath.

For example, when a large amount of ammonia contained in exhaled breath is secreted, it is possible to detect a decrease in renal or hepatic function, deterioration of the intestinal environment, or gout of the person. Further, for example, when a large amount of NO is secreted in exhaled breath, it is possible to detect bronchial asthma or drowsiness of the person. Further, for example, when a large amount of hydrogen sulfide contained in breath is secreted, gastrointestinal disease of the person can be detected. Also, for example, when a large amount of 3-methyl-3-sulfanylhexan-1-ol is secreted in exhaled breath, it can be estimated that the person is under mental stress.

Then, for example, a sensor capable of detecting each of the chemical substances described above may be placed on the desk, mouse, or the like of the person's office, and when the person's physical condition is detected, the person or the medical department may be notified. As a result, prevention against various diseases of the person can be promoted.

(core body temperature)
Also, as a physical condition of a person, a deep body temperature may be estimated.

By detecting the body surface temperature of the person, the core body temperature can be estimated. For example, the forehead temperature is considered to be close to the core body temperature, and the core body temperature can be estimated by detecting the forehead temperature or the like with a thermo camera. In addition, by measuring the room temperature at the same time and correcting the body surface temperature, the core body temperature can be estimated with higher accuracy. Note that the core body temperature may be estimated with higher accuracy by estimating the core body temperature including the temperature of other parts such as the eyeballs.

An example of output control when estimating (detecting) core body temperature will be described below.

FIG. 21 is a diagram for explaining one mode of output control depending on the detection result of core body temperature. FIG. 22 is a flow chart showing an example of an output control method dependent on the detection result of core body temperature.

As shown in FIG. 21, by detecting the forehead temperature and the like of the patient 51 with the thermo camera 40, the deep body temperature of the patient 51 visiting the hospital can be measured without contact. Therefore, for example, by detecting the deep body temperature of the patient 51 before entering the hospital, the fever state of the patient 51 can be detected, so the entrance to the hospital (waiting room) may be automatically opened according to the fever state.

That is, as shown in FIG. 22, first, the core body temperature of the patient 51 is detected by the thermo camera 40 (S41), and the core body temperature of the patient 51 is 38° C. or higher, 37° C. to 38° C., or 37° C. or lower. It is determined whether there is (S42).

In S42, if the core body temperature of the patient 51 is, for example, 38° C. or higher, control is performed to automatically open the door A of the waiting room A (S43). door B is automatically opened (S44). If the deep body temperature of the patient 51 is 37° C. or lower, control is performed to automatically open the door C of the waiting room C (S45).

As a result, the patient 51 who has a high fever does not have to wait in the same room as the patient 51 who has a normal fever, so the patient who has a normal fever can be prevented from being infected by the patient who has a high fever.

21 and 22 may be other values, and may be adjusted according to age. This is because it is known that young people have a higher body temperature. The age may be registered in, for example, a patient registration card.

Note that this estimation method may be installed in a taxi. As a result, it is possible to refuse the boarding of a patient with fever as necessary, so that secondary infection to the driver can be prevented. In addition, when boarding public transportation such as a train, it is possible to separate vehicles for people with high body temperature and people with normal body temperature. This is because it is possible to reduce the spread of diseases in public transportation such as trains.

Further, examples of the method of estimating the core body temperature and the output control thereof are not limited to these.

For example, it is possible to measure (estimate) the deep body temperature every day when waking up, and estimate the menstrual cycle of a woman. Then, in the period during the estimated menstrual cycle when the skin tends to be dry, the settings of the humidifier, the air conditioner, etc. may be automatically adjusted to prevent the skin from drying out. If it is a time when the user is easily irritated, control may be performed to select relaxing music on a stereo or the like.

Note that the timing for measuring the core body temperature daily is not limited to the time of waking up, as long as it can be measured under the same conditions every day, such as when washing the face in the morning.

Also, for example, the core body temperature may be measured when going to work at an office or the like. For example, by measuring the core body temperature at the moment a card reader is held up when entering a building, it is possible to link the core body temperature of a person and identify an employee with a fever. In addition, for example, a boss who receives fever information from a subordinate can adjust the work balance or encourage the employee to go home, thereby maintaining the employee's health and preventing the infection from spreading to other employees.

(dry skin)
In addition, the dryness level of the skin may be estimated as the physical condition of the person.

This is because the dryness level of the skin can be estimated by measuring the moisture content of the skin of the person. Then, when the dryness level is a predetermined level, that is, when the moisture content of the skin is reduced to a predetermined value or less, the humidifier in the room where the person is present may be operated to adjust the humidity of the room. Thereby, the person's beauty effect can be promoted.

(metabolic rate)
Also, as a physical condition of a person, a metabolic rate may be estimated.

By measuring the temperature of the clavicle portion of the person with a thermo camera, radiation thermometer, or the like, it is possible to estimate the metabolic rate of the person. The presence of brown fat is known to increase metabolic rate, and brown fat is localized in the clavicle region and brown fat produces heat. Therefore, the metabolic rate can be estimated by measuring the temperature of the clavicle portion of the person.

Then, for example, the metabolic rate may be estimated, and if the calorie intake is higher than the estimated metabolic rate, a warning may be given to the person. Thereby, obesity etc. of the said person can be prevented.

(others)
Also, as the physical condition of a person, the way of sitting on a chair may be estimated (detected).

By arranging a sensor that measures the pressure distribution on the seated portion of the chair, it is possible to detect how the person sits on the chair. Then, it is also possible to estimate a part of the person who is likely to have low back pain from the detected sitting style of the person, and to prevent back pain by warming the part with a heater.

Shortness of breath may also be estimated (detected) as a physical condition of a person.

Shortness of breath can be detected from the person's breathing rate and oxygen saturation. When shortness of breath is detected, the rhythm of breathing may be notified by voice or the like. As a result, the person's breathing rhythm can be adjusted. As for the breathing rhythm, it is possible to regulate the person's breathing by indicating a slightly slower rhythm than the current breathing rate of the detected person, and further slowing down the indicated rhythm gradually.

As a physical condition of a person, palpitations due to tension or the like may be estimated (detected) by measuring the heart rate.

Then, when it is detected that the person is having palpitations due to tension or the like, the person may hear the sound of a rhythm that is slightly slower than the measured current heart rate. This can lower the person's heart rate and relieve tension. If a certain amount of tension is required, such as before a sports match, the sound of a rhythm that gradually increases from the resting heart rate may be heard. This can lead to an ideal tension state.

Note that premiums for life insurance or medical insurance may be adjusted according to the type, degree, and time of the detected physical condition. As a result, the premiums for those in good physical condition can be reduced and the premiums for those in poor physical condition can be increased, thereby increasing the satisfaction of the insured.

Also, when a person who is in poor physical condition is detected in a movie theater or the like, the person in charge may be notified, for example, so that the person in charge who receives the notification calls out to the person and urges them to leave. As a result, it is possible to prevent interruption of the screening by a person who is in poor physical condition.

As described above, methods for estimating a person's physical condition other than those exemplified in Embodiments 1 and 2 have been described, but the present invention is not limited to this. Similarly, human emotions may be estimated by methods other than those described in the second embodiment. Examples will be described below.

(frustration level)
For example, a frustration level may be estimated (detected) as a person's emotion.

The frustration level can be estimated from the person's facial expression and blood flow. This is because it is known that when a person is irritated, it appears in their facial expressions. In addition, it is known that when a person is irritated, the sympathetic nerves are activated and the peripheral blood flow decreases, resulting in a decrease in the peripheral blood flow. Here, a person's irritation level may be estimated using all of the facial expression and blood flow information, or any one of them may be used, or a plurality of information may be used to estimate the irritation level. I do not care.

Then, when the frustration level of the person is estimated, if the person is driving, control may be performed so that the engine sound of the car is taken more into the vehicle, thereby amplifying the sense of speed more than the actual speed. This prevents the person from overspeeding. Of course, when estimating a person's frustration, control may be performed to reduce the sensitivity of the accelerator of the vehicle to prevent the vehicle from suddenly starting, or control to reduce the sensitivity of the brake may be performed to prevent the vehicle from suddenly stopping.

(drowsiness level)
Also, for example, a drowsiness level may be estimated (detected) as a person's emotion.

This is because it is known that when people feel drowsiness, it appears in their facial expressions. In addition, when a person feels drowsy, the parasympathetic nerves are activated and the variation in heartbeat intervals increases, the blood flow in the peripheral area increases, and the skin temperature in the peripheral area increases accordingly. This is because dilation is known to lower blood pressure. In addition, it is known that when the breathing interval becomes short, the oxygen concentration decreases and the person feels drowsy.

Thus, a person's sleepiness level may be estimated from the person's facial expression, heartbeat interval, respiration, blood pressure, blood flow, or skin temperature.

Here, the human drowsiness level may be estimated using all of the information on the person's facial expression, heartbeat interval, respiration, blood pressure, blood flow, and skin temperature. may be used to estimate the drowsiness level.

Further, it is also possible to learn a combination of these pieces of information that provides the highest estimation accuracy, and change the combination for each person.

For example, it is known that some people tend to show drowsiness on their faces, while others find it difficult to do so. For a person whose face is prone to drowsiness, facial expressions can be used for estimation, and of course, by detecting facial expressions in combination with other physiological quantities, highly accurate drowsiness level estimation can be achieved. Similarly, the combination may be changed for each drowsiness level to be detected. Also, for example, some people have a marked drop in blood pressure when drowsiness occurs early, while others do not. Therefore, when detecting early drowsiness, if the blood pressure of a person whose blood pressure drops significantly when drowsiness occurs early, drowsiness should be estimated including the blood pressure.

Note that these are only examples, and sleepiness may be estimated by including other physiological indices as necessary. As a result, highly accurate drowsiness estimation can be realized. In other words, the same applies not only to the estimation of early onset of drowsiness, but also to the estimation of deep drowsiness, and any physiological index may be selected. As a result, it is possible to estimate the sleepiness level with high accuracy by selecting the optimal physiological index through learning according to the person and the depth of sleepiness to be detected.

When drowsiness is detected (estimated) and the person is driving, the car may be controlled to ventilate the car to increase the oxygen concentration in the car or take in outside air. By doing so, the drowsiness of the person can be reduced. It should be noted that, for example, by opening a partition between the engine room and the vehicle interior so that the engine sound of the vehicle is taken into the interior of the vehicle, the sense of speed may be amplified and the awakening level may be increased. Furthermore, by controlling the hardness of the suspension of the car and transmitting vibration, the alertness may be increased.

(Method for detecting each physiological quantity)
Methods for detecting each physiological quantity are exemplified below.

(Heart rate)
The heart rate can be detected by detecting subtle color variations in the flesh-colored part of the face captured by the camera. This is because mainly the green component of the color of the flesh-colored portion of the face fluctuates in synchronism with the heartbeat.

Alternatively, the heart rate may be detected by detecting temperature fluctuations in a temperature range corresponding to facial skin photographed by a thermo camera. This is because the temperature of the face photographed by the thermo camera fluctuates in synchronization with the heartbeat cycle, so the heart rate can be determined by detecting the temperature fluctuation in the temperature range corresponding to the skin.

Alternatively, the earlobe, finger, or the like may be irradiated with infrared rays, and the heart rate may be detected from the amount of variation in the reflected infrared rays. Furthermore, a sheet sensor or the like may be used to detect vibrations generated by heartbeats, obtain heartbeat waveforms, and detect the heartbeat rate.

(blood pressure)
Blood pressure can be obtained from the pulse wave transit time. Pulse wave transit time is the time it takes for blood flow out of the heart to reach a given extremity.

The pulse wave transit time tends to increase as the blood pressure decreases, and the pulse wave transit time tends to increase as the blood pressure increases. The pulse wave propagation time can be obtained from the amount of time difference between the pulse wave peak obtained from the facial image taken by the camera and the pulse wave peak obtained from images other than the face (neck, hands, etc.). . For example, the pulse wave propagation time may be obtained from the difference between the pulse wave peak times at two different points in the face (for example, the chin and the forehead).

In addition, the heart vibration is obtained with a millimeter wave sensor, etc., and the pulse wave of the face is detected from subtle color changes in the facial image taken by the camera, and the amount of time lag between the peak of the heart vibration and the pulse wave peak of the face is measured. As the propagation time, the blood pressure may be obtained by estimating the blood pressure fluctuation.

(skin moisture)
Skin moisture can be measured by irradiating the skin with a near-infrared water absorption wavelength (960 nm) and detecting the amount of light that returns. This is because when a person has a lot of skin moisture, the irradiated near-infrared light is absorbed and the amount of returning near-infrared light is reduced.

Alternatively, the amount of water (skin moisture) may be estimated from the hardness of the skin by irradiating ultrasonic waves or air and detecting the amount of variation at that time with millimeter waves or the like. This is because it is known that a person's skin becomes hard when the moisture content of the skin decreases.

(Blood glucose level)
The blood sugar level can be obtained by detecting the returning component of the infrared light irradiated to the eyeball. This is because, in the spectrum of the eyeball (aqueous humor), there is absorption at the sugar absorption wavelength (around 1650 nm), so the proportion of returning infrared light decreases as the blood sugar level increases.

Also, the blood sugar level may be estimated from the optical rotation of the eyeball portion (aqueous humor). This is because the higher the blood sugar level, the greater the optical rotation. Of course, the method of estimating the blood sugar level may be another method, and the method is not limited.

(exhalation component)
The exhalation component can be detected from the absorption amount of the component to be detected among the components contained in the exhalation at the absorption wavelength (for example, around 225 nm for NO).

For example, exhalation components can be detected by irradiating the exhalation with light of the component to be detected and detecting the amount of transmitted light. Of course, the spectrum may be detected by chromatography or the like, and the technique is not limited.

(breathing)
Breathing can be detected by irradiating a person whose respiration is to be measured with, for example, a rectangular pattern using infrared rays or the like in a camera image, and detecting a respiration waveform from variations in the pattern.

Note that respiration may be detected using visible light instead of infrared light, and the irradiation pattern may not be a rectangular pattern. Alternatively, a millimeter wave may be irradiated and detected from the Doppler shift amount of the reflected wave, or a TOF sensor may be used for detection.

In addition, it is known that the temperature of the lower nostrils changes due to respiration, for example, the temperature of the lower nostrils decreases when inhaling and the temperature of the lower nostrils rises when exhaling. Therefore, a thermal image may be used to detect a respiratory waveform from temperature fluctuations in the nostrils.

INDUSTRIAL APPLICABILITY The present invention can be used for a physical condition estimation method, a physical condition estimation device, and a program for estimating a person's physical condition. It can be used for an estimation method, a physical condition estimation device, and a program.

10, 20, 20A, 20B, 20C physical condition estimating device 11, 11A, 11B blood flow measurement unit 12, 22 physical condition estimating unit 13, 13A, 13B, 13C output control unit 24, 24A, 24B emotion estimating unit 40 thermo camera 50 people 51 patient 60 mobile terminal 61, 62, 63, 63C display surface 70 car navigation screen 71 public toilet 72 parking area 111, 241 camera unit 112 blood flow measurement processing unit 121 blood flow acquisition unit 122 physical condition estimation processing unit 223 estimated emotion acquisition unit 224 Correction unit 242 Facial expression estimation unit 243 Emotion estimation processing unit 244 Storage unit

Claims (7)

A control method for a physical condition estimation device,
Acquire information about the body surface temperature of a person detected by a thermo camera,
estimating the core body temperature of the person based on the information about the body surface temperature;
detecting the state of the person based on the estimated core body temperature;
controlling the operation of the physical condition estimation device according to the detected state of the person;
The thermo camera is installed in an area where the person can wake up,
In the physical condition estimation device,
estimating the deep body temperature of the person based on the body surface temperature of the person acquired by the thermo camera, and detecting the state of the person based on the estimated deep body temperature;
controlling a device used by the person according to the detected state of the person;
control method. The information on the body surface temperature of the person is measured when the person wakes up,
The control method according to claim 1. said person is a woman,
the person's condition is the person's menstrual cycle;
In the physical condition estimation device,
detecting the person's menstrual cycle based on the estimated core body temperature when the person wakes up, and controlling the device according to the menstrual cycle;
The control method according to claim 2. A control method for a physical condition estimation device,
Acquire information about the body surface temperature of a person detected by a thermo camera,
estimating the core body temperature of the person based on the information about the body surface temperature;
detecting the state of the person based on the estimated core body temperature;
controlling the operation of the physical condition estimation device according to the detected state of the person;
The thermo camera is installed in an area where the person can wash their face,
In the physical condition estimation device,
estimating the deep body temperature of the person based on the body surface temperature of the person acquired by the thermo camera, and detecting the state of the person based on the estimated deep body temperature;
controlling a device used by the person according to the detected state of the person;
control method. The information about the body surface temperature of the person is measured when the person washes the face,
The control method according to claim 4. A control device for a physical condition estimation device,
an acquisition unit that acquires information about a person's body surface temperature detected by a thermo camera;
using the estimating unit of the physical condition estimating device to estimate the core body temperature of the person based on the information on the body surface temperature;
using the detection unit of the physical condition estimation device to detect the state of the person based on the estimated core body temperature;
A control unit that controls the operation of the physical condition estimation device according to the detected state of the person,
The thermo camera is installed in an area where the person can wake up,
The control unit causes the physical condition estimation device to
estimating the deep body temperature of the person based on the body surface temperature of the person acquired by the thermo camera, and detecting the state of the person based on the estimated deep body temperature;
controlling a device used by the person according to the detected state of the person;
Control device. A control device for a physical condition estimation device,
an acquisition unit that acquires information about a person's body surface temperature detected by a thermo camera;
using the estimating unit of the physical condition estimating device to estimate the core body temperature of the person based on the information on the body surface temperature;
using the detection unit of the physical condition estimation device to detect the state of the person based on the estimated core body temperature;
A control unit that controls the operation of the physical condition estimation device according to the detected state of the person,
The thermo camera is installed in an area where the person can wash their face,
The control unit causes the physical condition estimation device to
estimating the deep body temperature of the person based on the body surface temperature of the person acquired by the thermo camera, and detecting the state of the person based on the estimated deep body temperature;
controlling a device used by the person according to the detected state of the person;
Control device.

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