JP7432204B2 - Whole body sweat estimation system and heatstroke prevention system - Google Patents

Description

Article 30, Paragraph 2 of the Patent Act applies “Development of a helmet-type wearable device capable of measuring perspiration during various activities”, ICEP20 19 Proceedings 2019, pp138-143, ICEP2019 Publication date April 8, 2019

The present invention relates to a whole body sweat amount estimation system and a heatstroke prevention system.

At construction sites, workers may be engaged in work in high-temperature environments. In high-temperature environments, it is necessary to prevent workers from getting heatstroke. For example, Patent Document 1 describes an example of a heat stroke prevention system. In the heat stroke prevention system of Patent Document 1, it is determined whether there is a possibility of heat stroke based on the amount of sweat of the head measured by a head-mounted device.

International Publication No. 2019/078308

Incidentally, the amount of whole body sweat is sometimes used to improve the accuracy of predicting the occurrence of heat stroke. Patent Document 1 also describes that the amount of sweat of the whole body can be estimated from the amount of sweat of the head. However, there is a need to further improve the accuracy of estimating the amount of whole body sweat.

The present invention solves the above-mentioned problems, and aims to provide a whole body sweat amount estimation system and a heat stroke prevention system that can improve the estimation accuracy of the whole body sweat amount.

A whole-body sweat amount estimation system for achieving the above purpose includes a sweat amount measurement unit that measures the amount of sweat per person's head, an exercise time measurement unit that measures the exercise time of the person, and an exercise time measurement unit that measures the amount of sweat of the person's head. Based on an environmental measurement device that measures temperature, sweat amount data acquired from the sweat amount measurement section, exercise time data acquired from the exercise time measurement section, and environmental data acquired from the environment measurement device, A whole body sweat amount calculation unit that calculates the whole body sweat amount.

A desirable aspect of the whole body sweat amount estimation system of the present disclosure includes a unique data storage unit that stores unique data including age, height, weight, head circumference, hair amount, and exercise habits of the person, and the environment measuring device , the relative humidity of the place where the person is present is measured, and the whole body sweat amount calculation unit calculates the whole body sweat amount based on the sweat amount data, the exercise time data, the environmental data, and the unique data. .

As a desirable aspect of the whole-body sweat amount estimation system of the present disclosure, the whole-body sweat amount calculation unit is configured to calculate the whole-body sweat amount as P, the head sweat amount as Q, the age as Y, the weight as W, and the height as He. , where the head circumference is C, the hair amount is Ha, the exercise habit is Mc, the exercise time is Mt, the temperature is T, and the relative humidity is Hu, the whole body sweat amount is calculated by the following formula (8). do.

P=α ₁ ×Q+α ₂ ×Y+α ₃ ×W+α ₄ ×He+α ₅ ×C+α ₆ ×Ha+α ₇ ×Mc+α ₈ ×Mt+α ₉ ×T+α ₁₀ ×Hu+α ₁₁ ...(8)

As a desirable aspect of the whole body sweat amount estimation system of the present disclosure, the whole body sweat amount calculation unit calculates the estimated value of the whole body sweat amount (g) as P, the head sweat amount (g) as Q, the age (years) as Y, and the body weight. (kg) is W, height (cm) is He, head circumference (cm) is C, hair volume (g) is Ha, exercise habit (times/week) is Mc, exercise time (minutes) is Mt, temperature (℃) ) is T and the relative humidity (%) is Hu, the whole body sweat amount is calculated by the following formula (11).

P=9.54×Q-0.2×Y+0.76×W+0.17×He+2.56×C+13.2×Ha-0.1×Mc+4.89×Mt+27.1×T+0.87×Hu-1900 ・...(11)

A heat stroke prevention system for achieving the above purpose includes a sweat amount measurement unit that measures the amount of sweat per person's head, an exercise time measurement unit that measures the exercise time of the person, and an air temperature at the place where the person is. an environmental measuring device that measures the person's whole body based on sweat amount data acquired from the sweat amount measuring section, exercise time data acquired from the exercise time measuring section, and environmental data acquired from the environment measuring device. The apparatus includes a whole body sweat amount calculation section that calculates the amount of sweat perspiration, and a heat stroke prediction section that predicts the possibility that the person will suffer from heat stroke based on the whole body sweat amount.

A desirable aspect of the heatstroke prevention system of the present disclosure includes a unique data storage unit that stores unique data including age, height, weight, head circumference, hair amount, and exercise habits of the person, and the environment measuring device includes: The relative humidity of the place where the person is present is measured, and the whole body sweat amount calculation unit calculates the whole body sweat amount based on the sweat amount data, the exercise time data, the environmental data, and the unique data.

A desirable aspect of the heat stroke prevention system of the present disclosure includes a vital sensor that measures at least one of the person's skin temperature, core body temperature, heart rate, heart rate interval, and respiration rate, and the whole body sweat amount calculation unit: The whole body sweat amount is calculated based on the sweat amount data and vital data acquired from the vital sensor.

As a desirable aspect of the heat stroke prevention system of the present disclosure, the unique data includes a heat stroke history of the person.

As a desirable aspect of the heat stroke prevention system of the present disclosure, the heat stroke prediction unit predicts the possibility that the person will suffer from heat stroke using artificial intelligence.

According to the system for estimating the amount of whole body sweat and the heat stroke prevention system of the present disclosure, it is possible to improve the accuracy of estimating the amount of whole body sweat.

FIG. 1 is a schematic diagram of a heatstroke prevention system according to an embodiment. FIG. 2 is a schematic diagram of the heat stroke prevention system of the embodiment. FIG. 3 is a sectional view of the head mounted device of the embodiment. FIG. 4 is a graph showing the relationship between head sweat amount and whole body sweat amount. FIG. 5 is a graph showing the relationship between head sweat amount and whole body sweat amount. FIG. 6 is a graph showing the relationship between the estimated whole body sweat amount and the whole body sweat amount.

Hereinafter, the present invention will be explained in detail with reference to the drawings. Note that the present invention is not limited to the modes for carrying out the present invention (hereinafter referred to as embodiments). Furthermore, the constituent elements in the embodiments below include those that can be easily imagined by those skilled in the art, those that are substantially the same, and those that are within the so-called equivalent range. Furthermore, the components disclosed in the embodiments below can be combined as appropriate.

(Embodiment)
FIG. 1 is a schematic diagram of a heatstroke prevention system according to an embodiment. FIG. 2 is a schematic diagram of the heat stroke prevention system of the embodiment. FIG. 3 is a sectional view of the head mounted device of the embodiment.

The heat stroke prevention system 100 of this embodiment is a system for suppressing the onset of heat stroke in workers. The heatstroke prevention system 100 is applied to workers at construction sites, for example. The heat stroke prevention system 100 is also a whole body sweat amount estimation system 500 that estimates a person's whole body sweat amount. As shown in FIG. 1, the heat stroke prevention system 100 includes a head mounted device 10, an environment measuring device 59, a management device 91, an alarm device 95, a unique data storage unit 103, and a heat stroke prediction device 200. ,including.

The head mounted device 10 is mounted on the head of a worker, for example. In the following description, a person who wears the head-mounted device 10 will be referred to as a wearer. For example, the head mounted device 10 of this embodiment is a helmet. As shown in FIGS. 1 to 3, the head mounted device 10 includes an inner shell 30, an outer shell 20, a spacer 40, a fan 60, a battery 11, a first flow path 41, and a second flow path. 42, a first humidity sensor 51, a second humidity sensor 52, a vital sensor 56, an acceleration sensor 57, and a communication device 58.

As shown in FIG. 3, the inner shell 30 is a member facing the wearer's head. The inner shell 30 is made of, for example, synthetic resin or cloth. The inner shell 30 has a plurality of gaps and covers a portion of the wearer's head. Sweat generated on the wearer's head turns into water vapor and passes through the inner shell 30 without being blocked by the inner shell 30.

As shown in FIG. 3, the outer shell 20 is a member that covers the inner shell 30 and has a hemispherical shape. The outer shell 20 includes a main body 21 and a cushioning material 25. The main body 21 is made of, for example, synthetic resin. Cushioning material 25 is attached to the inner surface of main body 21 . The inner surface of the cushioning material 25 faces the inner shell 30. The buffer material 25 has a cavity inside. In the following description, the area outside the substantially hemispherical area surrounded by the outer shell 20 will be referred to as the outside E.

As shown in FIG. 3, the spacer 40 is disposed between the inner shell 30 and the outer shell 20. More specifically, the spacer 40 is sandwiched between the inner shell 30 and the cushioning material 25. Therefore, there is a gap between the inner shell 30 and the cushioning material 25.

As shown in FIG. 3, a fan 60 is provided in the outer shell 20. The air volume of the fan 60 can be adjusted manually or by a control circuit included in the management device 91. The fan 60 is adjusted to blow air at an air volume that makes the temperature of the exhaust air coming out of the second flow path 42 equal to or higher than the dew point temperature of the exhaust air. That is, the fan 60 is adjusted to blow air at an air volume that does not cause dew condensation on surrounding objects of the discharged air. The minimum air volume of the fan 60 is preferably such that the exhaust air has a dew point temperature or higher. This is because humidity sensors generally cannot measure the humidity of air whose relative humidity is higher than 100% (humidity of air whose temperature is below the dew point temperature). In order to make the relative humidity of the discharged air 100% or less, the management device 91 should increase the air volume of the fan 60 so that the temperature measured by a second humidity sensor 52 (described later) becomes equal to or higher than the dew point temperature. When used in a general work environment where the relative humidity of the exhaust air does not reach 100% (an environment where dew does not form on objects around the exhaust air), Even if the air volume of the fan 60 is simply and manually set to a desired air volume depending on the tolerance and amount of perspiration, the exhaust air will be at or above the dew point. Therefore, the second humidity sensor 52, which will be described later, can accurately measure absolute humidity. The minimum air volume of the fan 60 is preferably 0.01 l/min or more so that the air on the surface of the second humidity sensor 52 is replaced. The air volume of the fan 60 is more preferably 0.01 l/min or more and 500 l/min or less.

The battery 11 supplies power to the fan 60 , the first humidity sensor 51 , the second humidity sensor 52 , the vital sensor 56 , the acceleration sensor 57 , and the communication device 58 . Battery 11 is attached to outer shell 20.

As shown in FIG. 3, the first flow path 41 is a gap between the wearer's head and the cushioning material 25. A lower end portion of the first flow path 41 is connected to the outside E. The upper end of the first flow path 41 is connected to a hole provided in the buffer material 25. A fan 60 is arranged in the hole provided in the buffer material 25. The fan 60 is located at the upper end of the first flow path 41 . That is, the fan 60 is located at the downstream end of the first flow path 41.

As shown in FIG. 3, the second flow path 42 is a flow path provided in the outer shell 20. The second flow path 42 is a cavity provided in the buffer material 25. The second flow path 42 is connected to the first flow path 41. A lower end portion of the second flow path 42 is connected to the outside E.

The fan 60 sends air from the first flow path 41 toward the second flow path 42 . Air enters the first flow path 41 from the outside E and is discharged to the outside E from the second flow path 42. When the wearer sweats, water vapor is supplied to the first flow path 41. Air in the first flow path 41 containing water vapor due to sweat is discharged to the outside E via the second flow path 42.

The first humidity sensor 51 is a sensor for measuring the absolute humidity of intake air entering the first flow path 41 (hereinafter referred to as "first absolute humidity"). Absolute humidity is the amount of water vapor contained in air per unit volume. As shown in FIG. 3, the first humidity sensor 51 is located outside E. For example, the first humidity sensor 51 is attached to the outer shell 20. The first humidity sensor 51 measures the temperature and relative humidity of the outside E air.

The second humidity sensor 52 is a sensor for measuring the absolute humidity of the exhaust air exiting from the second flow path 42 (hereinafter referred to as second absolute humidity). As shown in FIG. 3, the second humidity sensor 52 is arranged in the second flow path 42. The second humidity sensor 52 measures the temperature and relative humidity of the air in the second flow path 42 .

The vital sensor 56 is a sensor that measures at least one of the wearer's skin temperature, core body temperature, heart rate, heartbeat interval, and respiration rate. The vital sensor 56 is attached to the inner surface of the inner shell 30, as shown in FIG. The vital sensor 56 is in contact with the wearer.

The acceleration sensor 57 is a sensor for measuring the exercise state of the wearer. Acceleration sensor 57 detects acceleration caused by movement of the wearer. Acceleration sensor 57 is attached to outer shell 20.

The communication device 58 is a device for transmitting information detected by the first humidity sensor 51, the second humidity sensor 52, the vital sensor 56, and the acceleration sensor 57 to the management device 91. Communication device 58 is attached to outer shell 20 as shown in FIG.

The environment measuring device 59 measures the environment where the wearer is. More specifically, the environment measuring device 59 measures wet bulb temperature, dry bulb temperature, black bulb temperature, and solar radiation. The environment measuring device 59 is placed at a work site where a wearer is present. The environment measuring device 59 calculates a wet bulb globe temperature (WBGT) and relative humidity based on the measured values of the wet bulb temperature, dry bulb temperature, and black bulb temperature. The environment measuring device 59 transmits the measured information to the management device 91 via, for example, a communication device.

The management device 91 is a computer, and includes, for example, a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), an input interface, an output interface, and the like. The management device 91 receives the measured values of the first humidity sensor 51 , the second humidity sensor 52 , the vital sensor 56 , the acceleration sensor 57 , and the environment measurement device 59 . The management device 91 receives measurement values from a plurality of wearers at one work site. The management device 91 also receives measurement values from multiple work sites.

As shown in FIG. 1, the management device 91 includes a sweat amount measuring section 911 and an exercise time measuring section 913. The sweat amount measurement unit 911 calculates the amount of sweat on the wearer's head. The exercise time measuring unit 913 calculates the exercise time of the wearer.

The sweat amount measurement unit 911 calculates the first absolute humidity based on the temperature and relative humidity of the intake air received from the first humidity sensor 51. There are various approximate formulas for estimating ^absolute humidity from relative humidity, but here we will use the Tetens formula, which is relatively commonly used. When the temperature of is t _A (K), the relative humidity of the intake air is RH _A (%), and the saturated water vapor pressure of the intake air is e _A (hPa), the sweat amount measurement unit 911 calculates the following equation (1) and Obtain X from equation (2).

The sweat amount measurement unit 911 calculates the mass of moisture that enters the first flow path 41 per unit time based on the first absolute humidity (X) and the air volume of the fan 60. When the mass of moisture that enters the first flow path 41 per unit time is A (g/min) and the air volume of the fan 60 is V (m ³ /min), the sweat amount measurement unit 911 calculates the amount of sweat according to the following formula (3). Get A from.

The sweat amount measurement unit 911 calculates the second absolute humidity based on the temperature and relative humidity of the discharged air received from the second humidity sensor 52. The second absolute humidity is Y (g/m ³ ), the temperature of the exhaust air is t _B (K), the relative humidity of the exhaust air is RH _B (%), and the saturated water vapor pressure of the exhaust air is e _B (hPa). In this case, the sweat amount measurement unit 911 obtains Y from the following equations (4) and (5).

The sweat amount measurement unit 911 calculates the mass of moisture coming out of the second flow path 42 per unit time based on the second absolute humidity (Y) and the air volume of the fan 60. If the mass of this moisture is B (g/min), the sweat amount measurement unit 911 obtains B from the following equation (6).

When the mass of moisture evaporated from the wearer's head per unit time is C (g/min), the sweat amount measurement unit 911 obtains C from the following equation (7). In the following description, the mass (C) of moisture evaporated from the wearer's head per unit time is described as the amount of head perspiration. The sweat amount measurement unit 911 calculates and stores the head sweat amount at predetermined intervals.

The exercise time measuring unit 913 calculates the exercise time of the wearer. For example, the exercise time measurement unit 913 calculates the wearer's exercise time based on information acquired from the acceleration sensor 57. The exercise time measurement unit 913 calculates the wearer's exercise time by integrating the time during which the acceleration detected by the acceleration sensor 57 exceeds a predetermined threshold. The exercise time measurement unit 913 resets the exercise time when the acceleration detected by the acceleration sensor 57 remains below a predetermined threshold for a certain period of time. Note that the exercise time measurement unit 913 may calculate the exercise time using other methods. For example, the exercise time measurement unit 913 may calculate the exercise time based on information acquired from the airflow sensor of the fan 60. The exercise time measurement unit 913 calculates the wearer's exercise time by integrating the time during which the air volume of the fan 60 exceeds a predetermined threshold.

The alarm device 95 is a device for making the wearer aware that he or she may suffer from heatstroke. The alarm device 95 is, for example, a smartphone. The alarm device 95 issues an alarm based on the information received from the heat stroke prediction device 200. The type of alarm is not particularly limited. Examples of alarms include sound, light or vibration.

The unique data storage unit 103 is a device that stores unique data of the wearer. The unique data storage unit 103 is a computer, and includes, for example, a CPU, a ROM, a RAM, an input interface, an output interface, and the like. The unique data includes the wearer's age, gender, height, weight, head circumference, amount of hair, exercise habits, and history of heatstroke. For example, the results of regularly performed physical measurements are stored in the unique data storage unit 103 as unique data. Exercise habits are the frequency of exercising at a certain intensity or higher in a certain period of time. The unique data storage unit 103 calculates and stores the wearer's head surface area and whole body surface area based on, for example, height, weight, and head circumference. Note that the unique data storage unit 103 may store directly measured head surface area and whole body surface area of the wearer. The heatstroke history is the number of times the wearer has suffered from heatstroke. Note that the heat stroke history may be the frequency of heat stroke in a certain period of time. Further, the unique data storage unit 103 stores sweat amount data, vital data, environmental data, etc. at the time of heat stroke, for wearers whose heat stroke history is not zero.

The heat stroke prediction device 200 is a device that predicts the possibility that the wearer will suffer from heat stroke. Heat stroke prediction device 200 is part of cloud 300. Cloud 300 is also called cloud computing. For example, the heat stroke prediction device 200 is included in a server of the cloud 300.

The heat stroke prediction device 200 receives sweat amount data, vital data, and environmental data from the management device 91 via the Internet. The sweat amount data is, for example, a real-time value of the head sweat amount calculated by the sweat amount measurement unit 911. Vital data is a real-time value of skin temperature, core body temperature, heart rate, heartbeat interval, or respiration rate measured by a vital sensor. The environmental data are real-time values of air temperature (dry bulb temperature), relative humidity, and heat index (WBGT) measured by the environmental measuring device 59. Note that the sweat amount data may be an average value of the head sweat amount calculated by the sweat amount measurement unit 911 for each fixed period of time. Note that the vital data may be an average value of the amount of sweat per certain period of time measured by the vital sensor. The environmental data may be the average value of the air temperature (dry bulb temperature), relative humidity, heat index (WBGT) measured by the environment measuring device 59 at regular intervals, and the like.

As shown in FIG. 1, the heat stroke prediction device 200 includes a whole body sweat amount calculation section 201 and a heat stroke prediction section 203. The whole body sweat amount calculation unit 201 calculates the whole body sweat amount of the wearer. The whole body sweat amount calculation unit 201 calculates the wearer's whole body sweat amount based on sweat amount data, exercise time data, and environmental data. For example, the whole body sweat amount calculation unit 201 calculates the whole body sweat amount based on the wearer's age, weight, height, head circumference, hair amount, exercise habits, exercise time, environmental temperature, and relative humidity. Specifically, the whole body sweat amount (g) is P, the head sweat amount (g) is Q, the age (years) is Y, the weight (kg) is W, the height (cm) is He, and the head circumference (cm). If C is the amount of hair (g), Ha is the amount of hair (g), Mc is the exercise habit (times/week), Mt is the exercise time (minutes), T is the temperature (°C), and Hu is the relative humidity (%), calculate the amount of whole body sweat. The unit 201 calculates the whole body sweat amount using the following formula (8).

P=α ₁ ×Q+α ₂ ×Y+α ₃ ×W+α ₄ ×He+α ₅ ×C+α ₆ ×Ha+α ₇ ×Mc+α ₈ ×Mt+α ₉ ×T+α ₁₀ ×Hu+α ₁₁ ...(8)

In equation (8), α ₂ , α ₇ , and α ₁₁ are preferably negative values, and the other coefficients are preferably positive values. For example, α ₁ is 9.54, α ₂ × is −0.2, α ₃ is 0.76, α ₄ is 0.17, α ₅ is 2.56, and α ₆ × is 13.2, α ₇ × is −0.1, α ₈ × is 4.89, α ₉ × is 27.1, α ₁₀ is 0.87, and α ₁₁ is -1900.

The heat stroke prediction unit 203 predicts the possibility that the wearer will suffer from heat stroke based on the amount of whole body sweat. The heat stroke prediction unit 203 calculates an index related to the possibility that the wearer will suffer from heat stroke. For example, the heat stroke prediction unit 203 calculates an index based on the ratio of the amount of whole body sweat to the weight of the wearer. The index is a numerical value that is 0 when the ratio of whole body sweat amount to body weight is 0%, and is 100 when the ratio is 1.5%. For example, if the ratio of whole body sweat to body weight is 0.3%, the index is 20. Note that the above-mentioned index is an example and is not particularly limited. The heatstroke prediction unit 203 may calculate the index using other unique data and environmental data. Furthermore, the heat stroke prediction unit 203 calculates the amount of water that the wearer should replenish based on the amount of whole body sweat.

Note that the heat stroke prediction unit 203 may have artificial intelligence (AI). The heat stroke prediction unit 203 can improve the accuracy of predicting the possibility that the wearer will suffer from heat stroke by having artificial intelligence learn the accumulated information.

The heat stroke prediction unit 203 transmits the calculated index and the amount of water to be replenished to the management device 91. The management device 91 transmits a command to the alarm device 95 to issue an alarm when the index calculated by the heat stroke prediction unit 203 is greater than or equal to a predetermined threshold. The alarm device 95 receives a command from the management device 91 and issues an alarm to make the wearer aware that there is a high possibility of suffering from heatstroke.

FIGS. 4 and 5 are graphs showing the relationship between the amount of perspiration of the head and the amount of perspiration of the whole body. FIG. 6 is a graph showing the relationship between the estimated whole body sweat amount and the whole body sweat amount.

A first experiment and a second experiment were conducted regarding the relationship between head sweat amount and whole body sweat amount. The first experiment is an experiment regarding the relationship between the amount of head sweat and the amount of whole body sweat when the subject is at rest. The second experiment was an experiment regarding the relationship between the amount of head sweat and the amount of whole body sweat while the subject was exercising.

In the first experiment, the test subject wore an experimental helmet capable of measuring the amount of sweat on the head, similar to the head-mounted device 10 described above. The subjects wore cotton experimental shirts and experimental pants to reduce the effects of ineffective sweating on the body surface. Measurement of body weight and head sweat amount was started 30 minutes after the subjects entered the laboratory at 30°C ± 0.5°C and maintained a sitting position. Body weight and head sweat were measured over 30 minutes. In the first experiment, subjects held a sitting position for 30 minutes. That is, the subjects were in a resting state in the first experiment. Laboratory temperature was maintained at 30°C. Body weight was measured every 6 minutes using a precision electronic bench scale. Body weight was measured after the subjects took off their experimental shirts and experimental pants and wiped the sweat from their body surfaces. The difference between the weight before the start of the experiment and the current weight (weight loss) corresponds to the amount of whole body sweat. Head sweat amount was calculated every minute based on the above-mentioned equations (1) to (7). There were a total of 18 subjects in the first experiment.

FIG. 4 is a graph showing the relationship between head sweat amount and whole body sweat amount in the first experiment. Regression analysis was performed on all data from a total of 18 people. The straight line in the graph of FIG. 4 is a regression equation obtained by regression analysis. When the whole body sweat amount is P (g) and the head sweat amount is Q (g), the following formula (9) was derived from the results of the first experiment. The correlation coefficient is 0.75. Therefore, the whole body sweat amount can be calculated with high accuracy based on the head sweat amount using the following formula (9).

P=20.4×Q...(9)

In the second experiment, the test subject wore an experimental helmet capable of measuring the amount of sweat on the head, similar to the head-mounted device 10 described above. Measurement of the subject's weight and head sweat amount was started while the subject was wearing work clothes. Body weight and head sweat were measured over 30 minutes. The temperature at the experimental site was maintained at 30°C or higher and 34°C or lower. The thickness index (WBGT) of the experimental field was maintained at 26.9°C or higher and 28.9°C or lower. Body weight was measured every 10 minutes using a precision electronic bench scale. Subjects walked in the experimental area for 10 minutes before their weight was measured. Walking speed was constant, 1.43±0.1 (m/s). The difference between the weight before the start of the experiment and the current weight (weight loss) corresponds to the amount of whole body sweat. Head sweat amount was calculated every minute based on the above-mentioned equations (1) to (7). There were a total of 15 subjects in the second experiment.

FIG. 5 is a graph showing the relationship between head sweat amount and whole body sweat amount in the second experiment. Regression analysis was performed on all data from a total of 15 people. The straight line in the graph of FIG. 5 is a regression equation obtained by regression analysis. When the whole body sweat amount is P (g) and the head sweat amount is Q (g), the following formula (10) was derived from the results of the second experiment. The correlation coefficient is 0.87. Therefore, the whole body sweat amount can be calculated with high accuracy based on the head sweat amount using the following formula (10).

P=23.1×Q...(10)

Using all the data from the second experiment, the subject's age, weight, height, head circumference, hair volume, exercise habits, exercise time (time elapsed from the start of the experiment), temperature and relative humidity of the experiment site. Multiple regression analysis was performed. Estimated whole body sweat amount (g) is P, head sweat amount (g) is Q, age is Y, weight (kg) is W, height (cm) is He, head circumference (cm) is C, hair amount ( g) is Ha, exercise habit is Mc, exercise time (minutes) is Mt, temperature (℃) is T, and relative humidity (%) is Hu, the estimated whole body sweat amount is expressed by the following formula (11). Ru. The straight line in the graph of FIG. 6 is a regression equation obtained by regression analysis of the measured whole body sweat amount and the estimated whole body sweat amount calculated by equation (11). The correlation coefficient is 0.97. Therefore, the whole body sweat amount can be calculated with high accuracy using the following equation (11).

P=9.54×Q-0.2×Y+0.76×W+0.17×He+2.56×C+13.2×Ha-0.1×Mc+4.89×Mt+27.1×T+0.87×Hu-1900 ・...(11)

As explained above, the heat stroke prevention system 100 includes a sweat amount measurement unit 911 that measures the amount of sweat per person's head, a unique data storage unit 103 that stores unique data including the person's height or weight, and A whole body sweat amount calculation section 201 that calculates the amount of sweat per person's whole body based on the sweat amount data and unique data acquired from the amount measuring section 911, and predicts the possibility that a person will suffer from heat stroke based on the amount of whole body sweat. A heat stroke prediction unit 203 is provided.

This makes it possible to predict with high accuracy the likelihood of a person suffering from heatstroke by using unique data in addition to the amount of whole body sweat, which is closely related to the likelihood of heatstroke. Therefore, the heat stroke prevention system 100 of this embodiment can improve the accuracy of predicting the possibility of heat stroke.

The heat stroke prevention system 100 includes an environment measuring device 59 that measures the environment of a place where a person is present. The whole body sweat amount calculation unit 201 calculates the whole body sweat amount based on the sweat amount data, the unique data, and the environmental data acquired from the environment measuring device 59. This improves the accuracy of the calculated whole body sweat amount. The heat stroke prevention system 100 of this embodiment can further improve the accuracy of predicting the possibility of heat stroke.

The heatstroke prevention system 100 includes a vital sensor 56 that measures at least one of a person's skin temperature, core body temperature, heart rate, heartbeat interval, and respiration rate. The whole body sweat amount calculation unit 201 calculates the whole body sweat amount based on the sweat amount data, the unique data, and the vital data acquired from the vital sensor 56. This improves the accuracy of the calculated whole body sweat amount. The heat stroke prevention system 100 of this embodiment can further improve the accuracy of predicting the possibility of heat stroke.

In the heat stroke prevention system 100, the unique data includes a person's heat stroke history. People who have had heatstroke in the past are more likely to get heatstroke than people who have never had heatstroke. Therefore, the heat stroke prevention system 100 of this embodiment can further improve the accuracy of predicting the possibility of heat stroke.

In the heatstroke prevention system 100, the heatstroke prediction unit 203 uses artificial intelligence to predict the possibility that a person will suffer from heatstroke. Thereby, the heat stroke prevention system 100 of this embodiment can further improve the accuracy of predicting the possibility of heat stroke.

The whole body sweat amount estimation system 500 (heat stroke prevention system 100) of the present embodiment includes a sweat amount measurement section 911 that measures the amount of sweat per person's head, an exercise time measurement section 913 that measures the amount of exercise time of the person, and a person. Based on the environmental measuring device 59 that measures the temperature of the place where the person is, sweat amount data acquired from the sweat amount measuring section 911, exercise time data acquired from the exercise time measuring section 913, and environmental data acquired from the environmental measuring device 59. and a whole body sweat amount calculation unit 201 that calculates a person's whole body sweat amount.

Thereby, the whole body sweat amount estimation system 500 can calculate the whole body sweat amount with high accuracy by using the person's exercise time and the temperature of the place where the person is. Therefore, the whole body sweat amount estimation system 500 can improve the estimation accuracy of the whole body sweat amount.

The whole body sweat amount estimation system 500 includes a unique data storage unit 103 that stores unique data including a person's age, height, weight, head circumference, hair amount, and exercise habits. The environment measuring device 59 measures the relative humidity of a place where people are present. The whole body sweat amount calculation unit 201 calculates the whole body sweat amount based on sweat amount data, exercise time data, environmental data, and unique data. The relationship between the amount of head sweat and the amount of whole body sweat is closely related to a person's age, height, weight, head circumference, amount of hair, exercise habits, exercise time, temperature of the place where the person is, and relative humidity. The whole body sweat amount estimation system 500 can reflect the above-mentioned information in the whole body sweat amount estimated value. Therefore, the whole body sweat amount estimation system 500 can further improve the estimation accuracy of the whole body sweat amount.

In the whole body sweat amount estimation system 500, the whole body sweat amount calculation unit 201 calculates the whole body sweat amount as P, the head sweat amount as Q, the age as Y, the weight as W, the height as He, the head circumference as C, and the amount of hair as Ha. , where Mc is the exercise habit, Mt is the exercise time, T is the temperature, and Hu is the relative humidity, the amount of whole body sweat is calculated using the following formula (8). Thereby, the whole body sweat amount estimation system 500 can further improve the estimation accuracy of the whole body sweat amount.

P=α ₁ ×Q+α ₂ ×Y+α ₃ ×W+α ₄ ×He+α ₅ ×C+α ₆ ×Ha+α ₇ ×Mc+α ₈ ×Mt+α ₉ ×T+α ₁₀ ×Hu+α ₁₁ ...(8)

In the whole body sweat amount estimation system 500, the whole body sweat amount calculation unit 201 calculates the estimated whole body sweat amount (g) as P, the head sweat amount (g) as Q, the age as Y, the body weight (kg) as W, and the height ( cm) is He, head circumference (cm) is C, hair volume (g) is Ha, exercise habit is Mc, exercise time (minutes) is Mt, temperature (℃) is T, and relative humidity (%) is Hu. , the whole body sweat amount is calculated using the following formula (11). Thereby, the whole body sweat amount estimation system 500 can further improve the estimation accuracy of the whole body sweat amount.

P=9.54×Q-0.2×Y+0.76×W+0.17×He+2.56×C+13.2×Ha-0.1×Mc+4.89×Mt+27.1×T+0.87×Hu-1900 ・...(11)

10 Head mounted device 11 Battery 20 Outer shell 21 Main body 25 Cushioning material 30 Inner shell 40 Spacer 51 First humidity sensor 52 Second humidity sensor 56 Vital sensor 57 Acceleration sensor 58 Communication device 59 Environment measuring device 60 Fan 91 Management device 95 Alarm Device 100 Heat stroke prevention system 103 Unique data storage unit 200 Heat stroke prediction device 201 Whole body sweat amount calculation unit 203 Heat stroke prediction unit 300 Cloud 500 Whole body sweat amount estimation system 911 Sweat amount measurement unit 913 Exercise time measurement unit E External

Claims (6)

a sweat amount measurement unit that measures the amount of sweat per person's head;
an exercise time measurement unit that measures exercise time of the person;
an environmental measuring device that measures the temperature and relative humidity of the place where the person is;
a unique data storage unit that stores unique data including age, height, weight, head circumference, hair amount, and exercise habits of the person;
The amount of whole body sweat of the person is determined based on the sweat amount data acquired from the sweat amount measuring section, the exercise time data acquired from the exercise time measuring section , the environmental data acquired from the environment measuring device , and the unique data . A whole-body sweat amount calculation unit that calculates,
Equipped with
The whole body sweat amount calculation unit calculates the whole body sweat amount as P, the head sweat amount as Q, the age as Y, the weight as W, the height as He, the head circumference as C, and the amount of hair as Ha. The whole body sweat amount estimation system calculates the whole body sweat amount by the following formula (1), where the exercise habit is Mc, the exercise time is Mt, the temperature is T, and the relative humidity is Hu .
P=α ₁ ×Q+α ₂ ×Y+α ₃ ×W+α ₄ ×He+α ₅ ×C+α ₆ ×Ha+α ₇ ×Mc+α ₈ ×Mt+α ₉ ×T+α ₁₀ ×Hu+α ₁₁ ...(1) a sweat amount measurement unit that measures the amount of sweat per person's head;
an exercise time measurement unit that measures exercise time of the person;
an environmental measuring device that measures the temperature and relative humidity of the place where the person is;
a unique data storage unit that stores unique data including age, height, weight, head circumference, hair amount, and exercise habits of the person;
Calculate the amount of whole body sweat of the person based on the sweat amount data acquired from the sweat amount measuring section, the exercise time data acquired from the exercise time measuring section, the environmental data acquired from the environment measuring device, and the unique data. A whole body sweat amount calculation unit,
Equipped with
The whole body sweat amount calculation unit calculates the estimated whole body sweat amount (g) as P, the head sweat amount (g) as Q, the age (years) as Y, the weight (kg) as W, and the height (cm) as He. If head circumference (cm) is C, hair volume (g) is Ha, exercise habit (times/week) is Mc, exercise time (minutes) is Mt, temperature (℃) is T, and relative humidity (%) is Hu. , a whole body sweat amount estimation system that calculates the whole body sweat amount using the following formula (2).
P=9.54×Q-0.2×Y+0.76×W+0.17×He+2.56×C+13.2×Ha-0.1×Mc+4.89×Mt+27.1×T+0.87×Hu-1900 ・...(2) a sweat amount measurement unit that measures the amount of sweat per person's head;
an exercise time measurement unit that measures exercise time of the person;
an environmental measuring device that measures the temperature and relative humidity of the place where the person is;
a unique data storage unit that stores unique data including age, height, weight, head circumference, hair amount, and exercise habits of the person;
The amount of whole body sweat of the person is determined based on the sweat amount data acquired from the sweat amount measuring section, the exercise time data acquired from the exercise time measuring section , the environmental data acquired from the environment measuring device , and the unique data . P, the sweat amount of the head is Q, the age is Y, the weight is W, the height is He, the head circumference is C, the hair amount is Ha, the exercise habit is Mc, the exercise time is Mt, the a whole body sweat amount calculation unit that calculates the whole body sweat amount of the person according to the following formula (1), where the temperature is T and the relative humidity is Hu ;
a heatstroke prediction unit that predicts the possibility that the person will suffer from heatstroke based on the amount of whole body sweat;
A heat stroke prevention system.
P=α ₁ ×Q+α ₂ ×Y+α ₃ ×W+α ₄ ×He+α ₅ ×C+α ₆ ×Ha+α ₇ ×Mc+α ₈ ×Mt+α ₉ ×T+α ₁₀ ×Hu+α ₁₁ ...(1) a sweat amount measurement unit that measures the amount of sweat per person's head;
an exercise time measurement unit that measures exercise time of the person;
an environmental measuring device that measures the temperature and relative humidity of the place where the person is;
a unique data storage unit that stores unique data including age, height, weight, head circumference, hair amount, and exercise habits of the person;
An estimated whole body sweat amount (g ) is P, head sweat amount (g) is Q, age (years) is Y, weight (kg) is W, height (cm) is He, head circumference (cm) is C, hair amount (g) is Ha , where Mc is the exercise habit (times/week), Mt is the exercise time (minutes), T is the temperature (°C), and Hu is the relative humidity (%), calculate the amount of whole body sweat of the person using the following formula (2). A whole body sweat amount calculation unit,
a heatstroke prediction unit that predicts the possibility that the person will suffer from heatstroke based on the amount of whole body sweat;
A heat stroke prevention system.
P=9.54×Q-0.2×Y+0.76×W+0.17×He+2.56×C+13.2×Ha-0.1×Mc+4.89×Mt+27.1×T+0.87×Hu-1900 ・...(2) The heat stroke prevention system according to claim 3 or 4 , wherein the unique data includes a heat stroke history of the person. The heatstroke prevention system according to any one of claims 3 to 5 , wherein the heatstroke prediction unit predicts the possibility that the person will suffer from heatstroke using artificial intelligence.

Images