Information processing device and information processing program

Abstract

An information processing device according to one aspect of the present disclosure is provided with an acquisition unit and a generation unit. The acquisition unit acquires external perspiration amount data, which pertains to the amount of perspiration discharged from the epidermis, generated on the basis of the output of a first sensor unit, and internal perspiration amount data, which pertains to the amount of perspiration inside the epidermis and the dermis, generated on the basis of the output of a second sensor unit. The generation unit generates perspiration amount data on the basis of the external perspiration amount data and the internal perspiration amount data.

Description

[Technical field]

[0001] The present disclosure relates to an information processing device and an information processing program. [Background technology]

[0002] In recent years, various measurement techniques for determining biological information have been considered. For example, conventionally, Galvanic Skin Response (GSR) has been used as one type of biological information. Electrical activity of a user's skin, such as GSR, which can also be used as biological information, is collectively called Electrodermal Activity (EDA). Skin Potential Activity (SPA) is also included in EDA. EDA is widely used, for example, as a method for detecting activity of a user's autonomic nervous system.

[0003] As a method for reducing body movement noise superimposed on a measurement signal obtained by an EDA sensor, for example, the invention described in Patent Document 1 is known. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-10803 A Summary of the Invention

[0005] Incidentally, Patent Document 1 describes the use of a pressure sensor to reduce body movement noise. However, due to structural constraints of the pressure sensor, the effect of reducing body movement noise is limited. Therefore, it is desirable to provide an information processing device and an information processing program that enable more effective reduction of body movement noise.

[0006] The information processing device according to a first aspect of the present disclosure includes an acquisition unit and a generation unit. The acquisition unit acquires external sweat rate data regarding the amount of sweat emerging from the epidermis, which is generated based on the output of the first sensor unit, and internal sweat rate data regarding the amount of sweat in the epidermis and dermis, which is generated based on the output of the second sensor unit. The generation unit generates the sweat rate data based on the external sweat rate data and the internal sweat rate data.

[0007] In the information processing device according to the first aspect of the present disclosure, sweat rate data is generated based on the external sweat rate data and the internal sweat rate data generated based on the output of the first sensor unit and the second sensor unit. This allows, for example, the internal sweat rate data to be reference data for the external sweat rate data, or the external sweat rate data to be reference data for the internal sweat rate data. As a result, it is possible to detect and reduce body movement noise from the external sweat rate data or the internal sweat rate data without using the output of the pressure sensor as reference data.

[0008] The information processing program according to the second aspect of the present disclosure causes a computer to execute the following two steps. (1) Obtaining external sweat rate data regarding the amount of sweat emerging from the epidermis, which is generated based on the output of the first sensor unit, and internal sweat rate data regarding the amount of sweat in the epidermis and dermis, which is generated based on the output of the second sensor unit. (2) generating sweat rate data based on the external sweat rate data and the internal sweat rate data;

[0009] In the information processing program according to the second aspect of the present disclosure, sweat rate data is generated based on the external sweat rate data and the internal sweat rate data generated based on the output of the first sensor unit and the second sensor unit. This allows, for example, the internal sweat rate data to be reference data for the external sweat rate data, or the external sweat rate data to be reference data for the internal sweat rate data. As a result, it is possible to detect and reduce body movement noise from the external sweat rate data or the internal sweat rate data without using the output of the pressure sensor as reference data. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram illustrating an example of a schematic configuration of a biological information processing apparatus according to an embodiment of the present disclosure. [Diagram 2] 2 is a diagram illustrating an example of a cross-sectional configuration of the vicinity of the surface of a living body with which the sensor unit in FIG. 1 comes into contact. [Diagram 3] 2 is a diagram illustrating a configuration example of a part of a sensor unit in FIG. 1. [Figure 4] 2 is a diagram illustrating a configuration example of a part of a sensor unit in FIG. 1. [Diagram 5] 2 is a diagram illustrating a configuration example of a part of a sensor unit in FIG. 1. [Figure 6] 2 is a diagram illustrating an example of a functional block of the basic measurement unit in FIG. 1. [Figure 7] 2 is a diagram illustrating an example of a determination table used in a reliability determination unit in FIG. 1. [Figure 8] 2 is a diagram illustrating an example of a processing procedure in a reliability determination unit in FIG. 1. [Figure 9] 1. FIG. 4 is a diagram illustrating a modified example of the processing procedure in the reliability determination unit in FIG. [Figure 10] 11 is a diagram for explaining changes over time in the amount of internal sweating and the amount of external sweating. FIG. [Figure 11] 1. FIG. 4 is a diagram illustrating a modified example of the processing procedure in the sweat intensity estimation unit in FIG. [Figure 12] FIG. 2 is a diagram illustrating a modified example of the schematic configuration of the bio-information processing device in FIG. [Figure 13] 13 is a diagram illustrating a state in which the biometric information processing device of FIG. 1 and FIG. 12 is built into a wearable device. [Figure 14] 13 is a diagram illustrating a state in which the biometric information processing device of FIG. 1 and FIG. 12 is built into a wearable device. [Figure 15] 15 is a diagram illustrating a state in which the wearable device of FIG. 13 and FIG. 14 are connected to a terminal device via a network. [Figure 16] 2 is a diagram illustrating an example in which a part of the functions of the biometric information processing apparatus in FIG. 1 is provided in a server apparatus. [Figure 17]13 is a diagram illustrating an example in which a part of the functions of the biometric information processing device in FIG. 12 is provided in a server device. [Figure 18] 2 is a diagram illustrating an example in which a part of the functions of the biometric information processing apparatus in FIG. 1 is provided in a server apparatus. [Figure 19] 13 is a diagram illustrating an example in which some of the functions of the information processing device in FIG. 12 are provided in a server device. [Figure 20] 2 is a diagram illustrating an example in which some of the functions of the information processing device in FIG. 1 are provided in a server device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The description will be made in the following order. 1. Embodiment (FIGS. 1 to 11) An example where a sensor is installed to detect external sweating and a sensor to detect internal sweating. 2. Variations An example of implementing the signal processing unit functions through a program (Figure 12) 3. Application Examples Example of a biometric information processing device installed in a wearable device (Figs. 13 to 20)

[0012] <1. Preferred embodiment> Humans have the ability to sweat on the surface of the body as a response of the autonomic nervous system to changes in the environment. There are various types of sweating, including thermogenic sweating to regulate body temperature when in a hot environment or during exercise, psychological sweating when receiving psychological stimuli such as mental tension or emotional changes, and gustatory sweating when eating spicy or pungent foods.

[0013] There is a type of bio-measurement called perspiration measurement that obtains changes due to perspiration on the body surface. Perspiration measurement is performed using a perspiration sensor. In perspiration measurement, the general method is to place at least two electrodes on the body surface, apply a voltage between the electrodes or allow a current to flow between the electrodes, and obtain the impedance change (or conductance change) between the electrodes due to the perspiration on the body surface.

[0014] In sweat measurement, the active sweat glands on the current path and the amount of sweating affect the measurement results. In daily use, the wrist, where a watch is worn, is considered to be a useful measurement site. However, on the wrist, changes in active sweat glands and sweating amount are smaller than on the fingers and palms, and the distribution of active sweat glands varies from person to person, making it difficult to identify their location, making it difficult to measure the skin conductance response, which is the target for detecting psychological sweating.

[0015] One solution to this problem is to increase the detection rate of active sweat glands by expanding the electrode area, thereby increasing the signal strength for detection. However, such a method also increases the area where contact changes occur between the electrode and the skin, so that body movement noise due to contact changes between the electrode and the skin is more likely to occur depending on the state in which the sweat sensor is worn. As a measure to reduce body movement noise, for example, the invention described in the above-mentioned Patent Document 1 is known. However, the method described in Patent Document 1 reduces body movement noise by using a pressure sensor, so the effect of reducing body movement noise is limited due to the structural constraints of the pressure sensor. In this disclosure, a method is proposed to more effectively reduce body movement noise without using a pressure sensor.

[0016] [composition] Fig. 1 illustrates an example of a schematic configuration of a bioinformation processing device 1 according to an embodiment of the present disclosure. The bioinformation processing device 1 is a device that measures mental sweating by an electrical or optical method. The bioinformation processing device 1 includes a sensor unit 10, a signal processing unit 20, a storage unit 30, and a data output unit 40. Fig. 2 illustrates an example of a cross-sectional configuration near the surface (biological surface 110) of a living body 100 with which the sensor unit 10 comes into contact.

[0017] In the living body 100, the living body surface 110 is covered with the epidermis 120, and the dermis 130 is formed below the epidermis 120 via a basement membrane. A large number of sweat glands 140 are formed in the epidermis 120 and the dermis 130. External sweat s2 is exposed from the sweat glands 140 on the living body surface 110, and internal sweat s1 that is not exposed on the living body surface 110 exists within the epidermis 120 and the dermis 130. The external sweat s2 is sweat that is exposed from the epidermis 120. The internal sweat s1 is sweat within the epidermis 120 and the dermis 130.

[0018] The sensor unit 10 has two types of sensor units (a first sensor unit 11 and a second sensor unit 12). The first sensor unit 11 is an electrical sweat sensor that detects the amount of sweat (external sweat amount) emerging from the epidermis 120 and outputs the first sensor data Sig1(t) obtained thereby. The second sensor unit 12 is an optical sweat sensor that detects the amount of sweat (internal sweat amount) in the epidermis 120 and the dermis 130 and outputs the second sensor data Sig2(t) obtained thereby. The first sensor unit 11 and the second sensor unit 12 contact the same part of the biological surface 110 or the same equivalent part. The "same equivalent part" refers to a part where it is possible to perform a measurement that is substantially the same as when the first sensor unit 11 and the second sensor unit 12 are placed at the same part of the biological surface 110.

[0019] The first sensor unit 11 has a detection electrode 11A as shown in Fig. 3, and during measurement, the detection electrode 11A is brought into contact with the biological surface 110 and a predetermined current is passed through the epidermis 120 to detect the amount of external sweating. The detection electrode 11A is, for example, made of a conductive metal layer. The second sensor unit 12 has a light source 12A as shown in Fig. 3, and detects the amount of internal sweating by irradiating the "same corresponding part" of the biological surface 110 with light L of a wavelength band that reaches the dermis 130 from the light source 12A and detecting the reflected light.

[0020] The detection electrode 11A may be provided with a plurality of openings h as shown in Fig. 4, for example. These plurality of openings h are for transmitting light L. In this case, the light source 12A is disposed on the detection electrode 11A, for example, as shown in Fig. 4. The light source 12A disposed on the detection electrode 11A irradiates the "same site" of the biological surface 110 with light L in a wavelength band that reaches the dermis 130 through the plurality of openings h.

[0021] The detection electrode 11A may be made of a conductive material (e.g., ITO) having optical transparency that transmits the light L. In this case, the light L passes through the detection electrode 11A even if the detection electrode 11A does not have a plurality of openings h. Therefore, for example, as shown in FIG. 5, the light source 12A is arranged on the detection electrode 11A, and the light source 12A arranged on the detection electrode 11A irradiates the "same site" of the biological surface 110 with light L in a wavelength band that reaches the dermis 130 through the detection electrode 11A.

[0022] The storage unit 30 is, for example, a volatile memory such as a dynamic random access memory (DRAM) or a non-volatile memory such as an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The storage unit 30 stores sensor data (first sensor data Sig1(t) and second sensor data Sig2(t)) obtained from the sensor unit 10 and data (external sweat rate data C(t), internal sweat rate data Q(t) and sweat intensity S) generated by the signal processing unit 20.

[0023] The signal processing unit 20 includes, for example, a basic measuring unit 21, a reliability determining unit 22, and a sweat intensity estimating unit 23, as shown in FIG.

[0024] 6, the basic measurement unit 21 includes a first sensor data acquisition unit 21a that acquires analog first sensor data Sig1(t) and an external sweat rate calculation unit 21b that generates external sweat rate data C(t) based on the first sensor data Sig1(t). The external sweat rate calculation unit 21b includes, for example, an IV conversion unit that performs IV conversion on the first sensor data Sig1(t), which is a current signal, an amplifier unit that amplifies a voltage signal obtained by the IV conversion, and a filter unit that reduces unnecessary frequency components included in the amplified voltage signal. The external sweat rate calculation unit 21b outputs, for example, the external sweat rate data C(t), which is a voltage signal obtained by processing by the IV conversion unit, the amplifier unit, and the filter unit, to the change rate calculation unit 21c.

[0025] The basic measurement unit 21 further includes a change amount calculation unit 21c, as shown in FIG. 6. The change amount calculation unit 21c calculates first difference data ΔC(t) (=C(t)-C(t-1)) which is a difference between two pieces of external sweat rate data C(t) that are detected at different times. The change amount calculation unit 21c outputs the calculated first difference data ΔC(t) to the reliability determination unit 22.

[0026] The basic measurement unit 21 further includes, for example, a second sensor data acquisition unit 21d that acquires analog second sensor data Sig2(t) and an internal sweat rate calculation unit 21e that generates internal sweat rate data Q(t) based on the second sensor data Sig2(t), as shown in Fig. 6. The internal sweat rate calculation unit 21e includes, for example, an IV conversion unit that performs IV conversion on the second sensor data Sig2(t), which is a current signal, an amplifier unit that amplifies a voltage signal obtained by the IV conversion, and a filter unit that reduces unnecessary frequency components included in the amplified voltage signal. The internal sweat rate calculation unit 21e outputs the internal sweat rate data Q(t), which is a voltage signal obtained by processing by the IV conversion unit, the amplifier unit, and the filter unit, to the change rate calculation unit 21f.

[0027] The basic measurement unit 21 further includes a change amount calculation unit 21f, for example, as shown in Fig. 6. The change amount calculation unit 21f calculates second difference data ΔQ(t) (=Q(t)-Q(t-1)) which is the difference between two pieces of data with different detection times among the internal sweat rate data Q(t). The change amount calculation unit 21f outputs the calculated second difference data ΔQ(t) to the reliability determination unit 22.

[0028] FIG. 7 shows an example of the judgment table 22A used in the reliability judgment unit 22. In the judgment table 22A, the correlation and reliability between the first differential data ΔC(t) and the second differential data ΔQ(t) are specified. For example, when the first differential data ΔC(t) and the second differential data ΔQ(t) are both decreasing (i.e., becoming negative values), the first differential data ΔC(t) and the second differential data ΔQ(t) have a mutual in-phase correlation. At this time, it can be said that the reliability of the first differential data ΔC(t) and the second differential data ΔQ(t) is high. Also, for example, when the first differential data ΔC(t) and the second differential data ΔQ(t) are both constant (i.e., becoming approximately zero), the first differential data ΔC(t) and the second differential data ΔQ(t) have a mutual in-phase correlation. At this time, it can be said that the reliability of the first differential data ΔC(t) and the second differential data ΔQ(t) is high. Furthermore, for example, when the first difference data ΔC(t) and the second difference data ΔQ(t) are both increasing (i.e., becoming positive values), the first difference data ΔC(t) and the second difference data ΔQ(t) have an in-phase correlation with each other. In this case, it can be said that the reliability of the first difference data ΔC(t) and the second difference data ΔQ(t) is high.

[0029] Also, for example, when the first differential data ΔC(t) is constant (i.e., approximately zero value) and the second differential data ΔQ(t) is decreasing (i.e., negative value), there is no correlation between the first differential data ΔC(t) and the second differential data ΔQ(t). In this case, the reliability of the first differential data ΔC(t) and the second differential data ΔQ(t) can be said to be medium. Also, for example, when the first differential data ΔC(t) is decreasing (i.e., negative value) and the second differential data ΔQ(t) is constant (i.e., approximately zero value), there is no correlation between the first differential data ΔC(t) and the second differential data ΔQ(t). In this case, the reliability of the first differential data ΔC(t) and the second differential data ΔQ(t) can be said to be medium.

[0030] Also, for example, when the first differential data ΔC(t) is increasing (i.e., it is a positive value) and the second differential data ΔQ(t) is constant (i.e., it is approximately zero), there is no correlation between the first differential data ΔC(t) and the second differential data ΔQ(t). In this case, the reliability of the first differential data ΔC(t) and the second differential data ΔQ(t) can be said to be medium. Also, for example, when the first differential data ΔC(t) is constant (i.e., it is approximately zero) and the second differential data ΔQ(t) is increasing (i.e., it is a positive value), there is no correlation between the first differential data ΔC(t) and the second differential data ΔQ(t). In this case, the reliability of the first differential data ΔC(t) and the second differential data ΔQ(t) can be said to be medium.

[0031] Also, for example, when the first differential data ΔC(t) is increasing (i.e., a positive value) and the second differential data ΔQ(t) is decreasing (i.e., a negative value), the first differential data ΔC(t) and the second differential data ΔQ(t) are in an inverse phase relationship with each other. At this time, it can be said that the reliability of the first differential data ΔC(t) and the second differential data ΔQ(t) is low. Also, for example, when the first differential data ΔC(t) is decreasing (i.e., a negative value) and the second differential data ΔQ(t) is increasing (i.e., a positive value), the first differential data ΔC(t) and the second differential data ΔQ(t) are in an inverse phase relationship with each other. At this time, it can be said that the reliability of the first differential data ΔC(t) and the second differential data ΔQ(t) is low.

[0032] The reliability determination unit 22 evaluates the reliability of the external sweat rate data C(t) and the internal sweat rate data Q(t) using, for example, a determination table 22A, and based on the evaluation result, records or discards data according to the reliability, for example, in the procedure shown in Figure 8.

[0033] The reliability determination unit 22 determines the reliability of the external sweat rate data C(t) based on, for example, the second difference data ΔQ(t) (step S101). The reliability determination unit 22 determines the reliability of the internal sweat rate data Q(t) based on, for example, the first difference data ΔC(t) (step S101).

[0034] For example, when the first difference data ΔC(t) and the second difference data ΔQ(t) have an anti-phase correlation with each other, the reliability determination unit 22 evaluates the reliability of both the external sweat rate data C(t) and the internal sweat rate data Q(t) that are in an anti-phase correlation with each other as low. For example, when the first difference data ΔC(t) and the second difference data ΔQ(t) have an in-phase correlation with each other, the reliability determination unit 22 evaluates the reliability of both the external sweat rate data C(t) and the internal sweat rate data Q(t) that are in-phase correlation with each other as high. For example, a calculation such as normalized cross-correlation can be used to determine whether they are in-phase or anti-phase.

[0035] The reliability determination unit 22 processes the external sweat rate data C(t) based on, for example, the evaluation result of the reliability of the external sweat rate data C(t), and sets the resulting data as sweat rate data 20A (included in the sweat rate data 20A). The reliability determination unit 22 processes the internal sweat rate data Q(t) based on, for example, the evaluation result of the reliability of the internal sweat rate data Q(t), and sets the resulting data as sweat rate data 20A (included in the sweat rate data 20A). In other words, the reliability determination unit 22 generates the sweat rate data 20A based on the external sweat rate data C(t) and the internal sweat rate data Q(t).

[0036] For example, when the reliability of the first difference data ΔC(t) is low (step S102; Y), the reliability determination unit 22 discards the external sweat rate data C(t) corresponding to the first difference data ΔC(t) or deletes the external sweat rate data C(t) corresponding to the first difference data ΔC(t) from the storage unit 30 (step S103). At this time, the reliability determination unit 22 excludes the external sweat rate data C(t) corresponding to the first difference data ΔC(t) from the sweat rate data 20A.

[0037] Furthermore, for example, when the reliability of the second difference data ΔQ(t) is low (step S102; Y), the reliability determination unit 22 discards the internal sweat rate data Q(t) corresponding to the second difference data ΔQ(t) or deletes the internal sweat rate data Q(t) corresponding to the second difference data ΔQ(t) from the storage unit 30 (step S103). At this time, the reliability determination unit 22 excludes the internal sweat rate data Q(t) corresponding to the second difference data ΔQ(t) from the sweat rate data 20A.

[0038] For example, when the reliability of the first difference data ΔC(t) is not low (step S102; N), that is, when the reliability of the first difference data ΔC(t) is high or medium, the reliability determination unit 22 records the external perspiration rate data C(t) corresponding to the first difference data ΔC(t) in the storage unit 30, or maintains the record of the external perspiration rate data C(t) corresponding to the first difference data ΔC(t) recorded in the storage unit 30 (step S104). At this time, the reliability determination unit 22 sets the external perspiration rate data C(t) corresponding to the first difference data ΔC(t) as the perspiration rate data 20A (includes it in the perspiration rate data 20A).

[0039] For example, when the reliability of the second difference data ΔQ(t) is not low (step S102; N), that is, when the reliability of the second difference data ΔQ(t) is high or medium, the reliability determination unit 22 records the internal sweat rate data Q(t) corresponding to the second difference data ΔQ(t) in the storage unit 30, or maintains the record of the internal sweat rate data Q(t) corresponding to the second difference data ΔQ(t) recorded in the storage unit 30 (step S104). At this time, the reliability determination unit 22 sets the internal sweat rate data Q(t) corresponding to the second difference data ΔQ(t) as the sweat rate data 20A (includes it in the sweat rate data 20A).

[0040] If the reliability determination unit 22 does not want to end the reliability determination (step S105; N), it continues to execute step S101, and otherwise (step S105; Y), it ends the reliability determination.

[0041] The reliability determination unit 22 may, for example, use a determination table 22A to evaluate the reliability of the external sweat rate data C(t) and the internal sweat rate data Q(t), and based on the evaluation result, may record data according to the reliability, for example, in the procedure shown in FIG. 9.

[0042] The reliability determination unit 22 generates first reliability evaluation data Ec(t) for the external sweat rate data C(t) based on, for example, the evaluation result of the reliability of the external sweat rate data C(t) (step S106). The first reliability evaluation data Ec(t) includes, for example, data (t) on the evaluation result of the reliability of the external sweat rate data C(t). At this time, the reliability determination unit 22 sets the external sweat rate data C(t) and the first reliability evaluation data Ec(t) as the sweat rate data 20A (includes them in the sweat rate data 20A).

[0043] The reliability determination unit 22 generates second reliability evaluation data Eq(t) corresponding to the internal sweat rate data Q(t) based on, for example, the evaluation result of the reliability of the internal sweat rate data Q(t) (step S106). The first reliability evaluation data Ec(t) includes, for example, data (t) on the evaluation result of the reliability of the internal sweat rate data Q(t). At this time, the reliability determination unit 22 sets the internal sweat rate data Q(t) and the second reliability evaluation data Eq(t) as sweat rate data 20A (includes them in the sweat rate data 20A).

[0044] Next, a description will be given of the sweat intensity estimation unit 23. When the reliability determination unit 22 determines that the reliability is high and both the first difference data ΔC(t) and the second difference data ΔQ(t) are increasing (i.e., are positive values), the sweat intensity estimation unit 23 performs sweat intensity estimation.

[0045] Fig. 10 shows an example of changes over time in the internal sweat rate data Q(t) and the external sweat rate data C(t). Fig. 11 shows an example of a procedure for estimating the sweat intensity in the sweat intensity estimator 23.

[0046] The sweat intensity estimation unit 23 first derives rise times ta, tb in the highly reliable time domain of the internal sweat rate data Q(t) and the external sweat rate data C(t) (step S201). Here, the rise time ta refers to the rise time in the highly reliable time domain of the internal sweat rate data Q(t). The internal sweat rate data Q(ta) is, for example, the average value of the waveform before the rise in the highly reliable time domain of the internal sweat rate data Q(t) + 3σ. The sweat intensity estimation unit 23 detects the time when the internal sweat rate data Q(t) gradually increases and exceeds the internal sweat rate data Q(ta) as the rise time ta. The rise time tb refers to the rise time in the highly reliable time domain of the external sweat rate data C(t). The external sweat rate data C(tb) is, for example, the average value of the waveform before the rise in the highly reliable time domain of the external sweat rate data C(t) + 3σ. The sweat intensity estimation unit 23 detects the time when the external sweat rate data C(t) gradually increases and exceeds the external sweat rate data C(tb) as the rise time tb. The rise times ta and tb may be derived by a calculation method different from the above.

[0047] Next, the sweat intensity estimation unit 23 derives the difference tdiff (=tb-ta) between the rise times ta and tb, and the internal sweat amount data Q(ta) (step S202). The difference tdiff (=tb-ta) is correlated with the speed at which sweat is discharged from the inside of the sweat gland 140 to the outside (sweating rate). The internal sweat amount data Q(ta) is the amount of sweat (accumulated sweat amount) accumulated inside the sweat gland 140 at the rise time ta. From the graph of FIG. 10, the greater the accumulated sweat amount, the smaller the difference tdiff, and the smaller the accumulated sweat amount, the larger the difference tdiff. Therefore, the sweat intensity S using the difference tdiff and the internal sweat amount data Q(ta) can be a new index in sweat measurement. Therefore, the sweat intensity estimation unit 23 derives the sweat intensity S (step S203). The sweat intensity S is expressed, for example, as 1 / (tdiff×Q(ta)). The sweat intensity S may be expressed by a formula different from the above. The sweat intensity estimating unit 23 sets the derived sweat intensity S as the sweat rate data 20A (includes it in the sweat rate data 20A).

[0048] The sweat intensity estimation unit 23 outputs the sweat amount data 20A generated as described above to the data output unit 40. The data output unit 40 outputs the sweat amount data 20A acquired from the sweat intensity estimation unit 23 to the outside. The sweat intensity estimation unit 23 derives the sweat intensity S, for example, every time the reliability determination unit 22 detects a time region with high reliability in the internal sweat amount data Q(t) and the external sweat amount data C(t) (step S204; N). The sweat intensity estimation unit 23 ends the derivation of the sweat intensity S, for example, when a predetermined condition is satisfied (step S204; Y).

[0049] [effect] Next, the effects of the biometric information processing device 1 will be described.

[0050] In the biometric information processing device 1, sweat rate data 20A to be outputted to the outside is generated based on the external sweat rate data C(t) and the internal sweat rate data Q(t) generated based on the outputs of the first sensor unit 11 and the second sensor unit 12. This allows, for example, the internal sweat rate data Q(t) to be reference data for the external sweat rate data C(t) and the external sweat rate data C(t) to be reference data for the internal sweat rate data Q(t). As a result, it is possible to detect and reduce body movement noise from the external sweat rate data C(t) or the internal sweat rate data Q(t) without using the output of a pressure sensor as reference data. Therefore, body movement noise can be reduced more effectively.

[0051] In the biometric information processing device 1, the reliability of the external sweat rate data C(t) is evaluated based on the second difference data ΔQ(t), which is the difference between two pieces of internal sweat rate data Q(t) detected at different times. Then, based on the evaluation result of the reliability of the external sweat rate data C(t), processing is performed on the external sweat rate data C(t), and the resulting data becomes the sweat rate data 20A. In this way, it is possible to detect and reduce body movement noise from the external sweat rate data C(t) without using the output of a pressure sensor as reference data. Therefore, body movement noise can be reduced more effectively.

[0052] In the biometric information processing device 1, the reliability of the internal sweat rate data Q(t) is evaluated based on the first difference data ΔC(t), which is the difference between two pieces of external sweat rate data C(t) detected at different times. Then, based on the evaluation result of the reliability of the internal sweat rate data Q(t), the internal sweat rate data Q(t) is processed, and the resulting data becomes the sweat rate data 20A. In this way, it is possible to detect and reduce body movement noise from the internal sweat rate data Q(t) without using the output of a pressure sensor as reference data. Therefore, body movement noise can be reduced more effectively.

[0053] In the biometric information processing device 1, when the second difference data ΔQ(t) and the first difference data ΔC(t) have a mutually inverse correlation, the reliability of the parts of the external sweat rate data C(t) and the internal sweat rate data Q(t) that are mutually inversely correlated is evaluated as low. Furthermore, when the second difference data ΔQ(t) and the first difference data ΔC(t) have a mutually in-phase correlation, the reliability of the parts of the external sweat rate data C(t) and the internal sweat rate data Q(t) that are mutually in-phase correlated is evaluated as high. Then, the data of the parts of the external sweat rate data C(t) and the internal sweat rate data Q(t) that are evaluated as having a high reliability becomes the sweat rate data 20A, and the data of the parts of the external sweat rate data C(t) and the internal sweat rate data Q(t) that are evaluated as having a low reliability is excluded from the sweat rate data 20A. In this way, only data evaluated to have a high reliability is output as the sweat rate data 20A, making it possible to provide sweat rate data 20A in which body movement noise has been more effectively reduced.

[0054] In the biometric information processing device 1, the reliability of the external sweat rate data C(t) is evaluated based on the second difference data ΔQ(t), which is the difference between two pieces of data detected at different times among the internal sweat rate data Q(t). Then, based on the evaluation result of the reliability of the external sweat rate data C(t), reliability evaluation data Ex(t) for the external sweat rate data C(t) is generated. This makes it possible to extract data with high reliability from the data included in the sweat rate data 20A by referring to the reliability evaluation data Ex(t) without excluding data evaluated to have low reliability from the sweat rate data 20A outputted to the outside. Therefore, by outputting the reliability evaluation data Ex(t) to the outside together with the external sweat rate data C(t), it is possible to provide sweat rate data 20A in which body movement noise is more effectively reduced.

[0055] In the biometric information processing device 1, the reliability of the internal sweat rate data Q(t) is evaluated based on the first difference data ΔC(t), which is the difference between two pieces of external sweat rate data C(t) detected at different times. Then, based on the evaluation result of the reliability of the internal sweat rate data Q(t), reliability evaluation data Eq(t) for the internal sweat rate data Q(t) is generated. This makes it possible to extract data with high reliability from the data included in the sweat rate data 20A by referring to the reliability evaluation data Eq(t) without excluding data evaluated to have low reliability from the sweat rate data 20A outputted to the outside. Therefore, by outputting the reliability evaluation data Eq(t) to the outside together with the internal sweat rate data Q(t), it becomes possible to provide sweat rate data 20A in which body movement noise is more effectively reduced.

[0056] <2. Modifications> In the above embodiment, for example, as shown in Fig. 12, the processing program 31 may be stored in the storage unit 30. In this case, the processing program 31 may be loaded into the signal processing unit 20, so that the signal processing unit 20 executes the various functions described above. Even in this case, the same effects as those of the above embodiment can be obtained.

[0057] <3. Application Examples> An example in which the biometric information processing device 1 according to the above embodiment and its modified example is applied to a wearable device 200 will be described below.

[0058] FIG. 13 shows a state where the biometric information processing device 1 according to the above embodiment and its modified example is built into a wearable device 200. FIG. 13 shows an example of a state where the biometric information processing device 1 is built into a wristband-type or wristwatch-type wearable device 200. FIG. 14 shows an example of a side configuration of the wearable device 200 of FIG. 13. The wearable device 200 includes, for example, a housing 210 that houses various devices and a belt 220 for fixing the device to the wrist. The housing 210 houses, for example, a signal processing unit 20, a storage unit 30, and a data output unit 40. For example, a sensor unit 10 is provided on the inner surface of the belt 220. For example, a detection electrode 11A and a light source 12A are provided on the sensor unit 10 at a location that contacts the wrist of the living body 100.

[0059] The biometric information processing device 1 built in the wearable device 200 is connected to the terminal device 300 via a network 400, for example, as shown in FIG. 15. At this time, in the biometric information processing device 1 built in the wearable device 200, the data output unit 40 is connected to the terminal device 300 via the network 400, for example, as shown in FIG. 16. In the biometric information processing device 1 built in the wearable device 200, the signal processing unit 20 has a basic measurement unit 21 and a reliability determination unit 22. The sweat intensity estimation unit 23 is omitted from the signal processing unit 20, and a processing program 331 that realizes the function of the sweat intensity estimation unit 23 is stored in the storage unit 330 of the terminal device 300. In other words, the function of the sweat intensity estimation unit 23 is transferred from the biometric information processing device 1 to the terminal device 300. In the bio-information processing device 1 built into the wearable device 200, the memory unit 30 stores sensor data obtained from the sensor unit 10 (first sensor data Sig1(t), second sensor data Sig2(t)) and data generated by the signal processing unit 20 (external sweat rate data C(t), internal sweat rate data Q(t)).

[0060] The terminal device 300 includes, for example, a control unit 310, a communication unit 320, and a storage unit 330. The control unit 310 executes the function of the sweat intensity estimation unit 23 by loading a processing program 331 into the control unit 310. The storage unit 330 is, for example, a volatile memory such as a DRAM, or a non-volatile memory such as an EEPROM or a flash memory. The storage unit 330 stores data (external sweat amount data C(t), internal sweat amount data Q(t)) transmitted from the biometric information processing device 1 built into the wearable device 200, and data (sweat intensity S) obtained by executing the processing program 331 in the control unit 310.

[0061] 17, for example, a processing program 32 may be stored in the storage unit 30. In this case, the processing program 32 may be loaded into the signal processing unit 20, causing the signal processing unit 20 to execute the functions of the basic measuring unit 21 and the reliability determining unit 22. Even in this case, the same effects as those of the above embodiment can be obtained.

[0062] In addition, in the biometric information processing device 1 built in the wearable device 200, the signal processing unit 20 may have a basic measurement unit 21, for example, as shown in FIG. 18. In this case, the reliability determination unit 22 and the sweat intensity estimation unit 23 are omitted from the signal processing unit 20, and a processing program 332 that realizes the functions of the reliability determination unit 22 and the sweat intensity estimation unit 23 is stored in the storage unit 330 of the terminal device 300. In other words, the functions of the reliability determination unit 22 and the sweat intensity estimation unit 23 are transferred from the biometric information processing device 1 to the terminal device 300. In the biometric information processing device 1 built in the wearable device 200, the storage unit 30 stores sensor data obtained from the sensor unit 10 (first sensor data Sig1(t), second sensor data Sig2(t)) and data generated by the signal processing unit 20 (external sweat amount data C(t), internal sweat amount data Q(t)).

[0063] The terminal device 300 includes, for example, a control unit 310, a communication unit 320, and a storage unit 330. A processing program 332 is loaded into the control unit 310, whereby the control unit 310 executes the functions of the reliability determination unit 22 and the sweat intensity estimation unit 23. The storage unit 330 stores data (external sweat rate data C(t), internal sweat rate data Q(t)) transmitted from the biometric information processing device 1 built into the wearable device 200, and data (sweat intensity S) obtained by executing the processing program 332 in the control unit 310.

[0064] 19, for example, a processing program 33 may be stored in the storage unit 30. In this case, the processing program 33 may be loaded into the signal processing unit 20, causing the signal processing unit 20 to execute the function of the basic measuring unit 21. Even in this case, the same effects as those of the above embodiment can be obtained.

[0065] 20, the signal processing unit 20 may include a first sensor data acquisition unit 21a and a second sensor data acquisition unit 21d. In this case, the external sweat amount calculation unit 21b, the change amount calculation unit 21c, the internal sweat amount calculation unit 21e, the change amount calculation unit 21f, the reliability determination unit 22, and the sweat intensity estimation unit 23 are omitted from the signal processing unit 20, and a processing program 333 that realizes the functions of the external sweat amount calculation unit 21b, the change amount calculation unit 21c, the internal sweat amount calculation unit 21e, the change amount calculation unit 21f, the reliability determination unit 22, and the sweat intensity estimation unit 23 is stored in the storage unit 330 of the terminal device 300. That is, the functions of the external sweat rate calculation unit 21b, the change amount calculation unit 21c, the internal sweat rate calculation unit 21e, the change amount calculation unit 21f, the reliability determination unit 22, and the sweat intensity estimation unit 23 are transferred from the biometric information processing device 1 to the terminal device 300. In the biometric information processing device 1 built into the wearable device 200, the storage unit 30 stores sensor data obtained from the sensor unit 10 (first sensor data Sig1(t), second sensor data Sig2(t)).

[0066] The terminal device 300 includes, for example, a control unit 310, a communication unit 320, and a storage unit 330. A processing program 333 is loaded into the control unit 310, whereby the control unit 310 executes the functions of the external sweat rate calculation unit 21b, the change amount calculation unit 21c, the internal sweat rate calculation unit 21e, the change amount calculation unit 21f, the reliability determination unit 22, and the sweat intensity estimation unit 23. The storage unit 330 stores data (external sweat rate data C(t), internal sweat rate data Q(t)) transmitted from the biometric information processing device 1 built into the wearable device 200, and data (sweat intensity S) obtained by executing the processing program 333 in the control unit 310.

[0067] Note that the effects described in this specification are merely examples. The effects of the present disclosure are not limited to the effects described in this specification. The present disclosure may have effects other than the effects described in this specification.

[0068] For example, the above-described series of processes can be executed by software, but can also be executed by hardware.

[0069] In addition, the above-described embodiments and their variations can be applied to applications that require objective cognitive load tolerance, such as games, health care, learning, training for sports competitions, training for human resource development, and driving a moving object such as an automobile.

[0070] Furthermore, for example, the present disclosure can have the following configuration. (1) an acquisition unit that acquires external sweat rate data regarding the amount of sweat emerging from the epidermis, which is generated based on an output from the first sensor unit, and internal sweat rate data regarding the amount of sweat in the epidermis and the dermis, which is generated based on an output from the second sensor unit; a generating unit for generating sweat rate data based on the external sweat rate data and the internal sweat rate data; Equipped with Information processing device. (2) The apparatus further includes an evaluation unit that evaluates the reliability of the external sweat rate data based on internal sweat rate difference data, which is a difference between two pieces of internal sweat rate data detected at different times, The generation unit processes the external sweat rate data based on the evaluation result of the reliability of the external sweat rate data by the evaluation unit, and sets the resultant data as the sweat rate data. An information processing device as described in (1). (3) the evaluation unit evaluates reliability of the internal sweat rate data based on external sweat rate difference data, which is a difference between two pieces of external sweat rate data detected at different times; The generation unit processes the internal sweat rate data based on the evaluation result of the reliability of the internal sweat rate data by the evaluation unit, and sets the resultant data as the sweat rate data. An information processing device according to (2). (4) the evaluation unit evaluates the reliability of both the external sweat rate data and the internal sweat rate data, which are in the in-phase correlation, as low when the internal sweat rate difference data and the external sweat rate difference data have an in-phase correlation with each other, and evaluates the reliability of both the external sweat rate data and the internal sweat rate data, which are in the in-phase correlation with each other, as high when the internal sweat rate difference data and the external sweat rate difference data have an in-phase correlation with each other; The generating unit sets a portion of the external sweat rate data and the internal sweat rate data that is evaluated by the evaluating unit as having a high reliability as the sweat rate data, and excludes a portion of the external sweat rate data and the internal sweat rate data that is evaluated by the evaluating unit as having a low reliability from the sweat rate data. An information processing device according to (3). (5) The device further includes an output unit that outputs the sweat rate data reflecting the evaluation by the evaluation unit to an outside. (4) An information processing device. (6) The apparatus further includes an evaluation unit that evaluates the reliability of the external sweat rate data based on internal sweat rate difference data, which is a difference between two pieces of internal sweat rate data detected at different times, The generating unit generates first reliability evaluation data for the external sweat rate data based on an evaluation result of the reliability of the external sweat rate data by the evaluating unit. An information processing device as described in (1). (7) The apparatus further includes an output unit that outputs the external sweat rate data and the first reliability evaluation data to the outside as the sweat rate data. (6) An information processing device. (8) the evaluation unit evaluates reliability of the internal sweat rate data based on external sweat rate difference data, which is a difference between two pieces of external sweat rate data detected at different times; The generating unit generates second reliability evaluation data for the internal sweat rate data based on an evaluation result of the reliability of the internal sweat rate data by the evaluating unit. (6) An information processing device. (9) The apparatus further includes an output unit that outputs the external sweat rate data, the internal sweat rate data, the first reliability evaluation data, and the second reliability evaluation data to an outside as the sweat rate data. An information processing device according to (8). (10) The first sensor unit detects an amount of external sweating and outputs the data obtained thereby; the second sensor unit detecting the amount of internal sweating and outputting the data obtained thereby; Further equipped An information processing device according to any one of (1) to (9). (11) The first sensor unit is an electrical sensor that detects the amount of external sweating. The second sensor unit detects the amount of internal sweating optically. An information processing device according to (10). (12) Obtaining external sweat rate data generated based on an output of the first sensor unit and internal sweat rate data generated based on an output of the second sensor unit; generating sweat rate data based on the external sweat rate data and the internal sweat rate data; Have your computer run Information processing program.

[0071] According to the information processing device according to the first aspect of the present disclosure, the sweat rate data is generated based on the external sweat rate data and the internal sweat rate data generated based on the output of the first sensor unit and the second sensor unit, so that, for example, the internal sweat rate data can be used as reference data for the external sweat rate data, or the external sweat rate data can be used as reference data for the internal sweat rate data. As a result, it is possible to reduce body movement noise from the external sweat rate data or the internal sweat rate data without using the output of the pressure sensor as reference data. Therefore, body movement noise can be effectively reduced.

[0072] According to the information processing program according to the second aspect of the present disclosure, the sweat rate data is generated based on the external sweat rate data and the internal sweat rate data generated based on the output of the first sensor unit and the second sensor unit, so that, for example, the internal sweat rate data can be used as reference data for the external sweat rate data, or the external sweat rate data can be used as reference data for the internal sweat rate data. As a result, it is possible to reduce body movement noise from the external sweat rate data or the internal sweat rate data without using the output of the pressure sensor as reference data. Therefore, body movement noise can be effectively reduced.

[0073] Furthermore, for example, the present disclosure can have the following configuration. (1) an acquisition unit that acquires first sweat rate data generated based on an output of the electrical sensor unit and second sweat rate data generated based on an output of the optical sensor unit; a generating unit that generates sweat rate data based on the first sweat rate data and the second sweat rate data; Equipped with Information processing device. (2) and an evaluation unit that evaluates reliability of the first sweat rate data based on second sweat rate difference data, the second sweat rate difference data being a difference between two pieces of data detected at different times, The generating unit processes the first sweat rate data based on the evaluation result of the reliability of the first sweat rate data by the evaluating unit, and sets the resultant data as the sweat rate data. An information processing device as described in (1). (3) the evaluation unit evaluates reliability of the second sweat rate data based on first sweat rate difference data, which is a difference between two pieces of data detected at different detection times, among the first sweat rate data; The generation unit processes the second sweat rate data based on the evaluation result of the reliability of the second sweat rate data by the evaluation unit, and sets the resultant data as the sweat rate data. An information processing device according to (2). (4) the evaluation unit evaluates the reliability of both the first sweat rate data and the second sweat rate data, which are in an in-phase correlation, as low when the second sweat rate difference data and the first sweat rate difference data have an in-phase correlation with each other, and evaluates the reliability of both the first sweat rate data and the second sweat rate data, which are in an in-phase correlation with each other, as high when the second sweat rate difference data and the first sweat rate difference data have an in-phase correlation with each other; The generating unit sets a portion of the first sweat rate data and the second sweat rate data that is evaluated by the evaluating unit as having a high reliability as the sweat rate data, and excludes a portion of the first sweat rate data and the second sweat rate data that is evaluated by the evaluating unit as having a low reliability from the sweat rate data. An information processing device according to (3). (5) The device further includes an output unit that outputs the sweat rate data reflecting the evaluation by the evaluation unit to an outside. (4) An information processing device. (6) and an evaluation unit that evaluates reliability of the first sweat rate data based on second sweat rate difference data, the second sweat rate difference data being a difference between two pieces of data detected at different times, The generating unit generates first reliability evaluation data for the first sweat rate data based on an evaluation result of the reliability of the first sweat rate data by the evaluating unit. An information processing device as described in (1). (7) The device further includes an output unit that outputs the first sweat rate data and the first reliability evaluation data to an outside as the sweat rate data. (6) An information processing device. (8) the evaluation unit evaluates reliability of the second sweat rate data based on first sweat rate difference data, which is a difference between two pieces of data detected at different detection times, among the first sweat rate data; The generating unit generates second reliability evaluation data for the second sweat rate data based on an evaluation result of the reliability of the second sweat rate data by the evaluating unit. (6) An information processing device. (9) The device further includes an output unit that outputs the first sweat rate data, the second sweat rate data, the first reliability evaluation data, and the second reliability evaluation data to an outside as the sweat rate data. (8) An information processing device. (10) The electrical sensor unit is an electrical sensor that detects the amount of sweat that is expressed through the epidermis; the optical sensor unit for optically detecting the amount of sweat in the epidermis and the dermis; Further equipped An information processing device according to any one of (1) to (9). (11) Obtaining first sweat rate data generated based on an output of the electrical sensor unit and second sweat rate data generated based on an output of the optical sensor; generating sweat rate data based on the first sweat rate data and the second sweat rate data; Have your computer run Information processing program.

[0074] According to the information processing device according to the first aspect of the present disclosure, the sweat rate data is generated based on the first sweat rate data and the second sweat rate data generated based on the output of the electrical sensor unit and the optical sensor unit. For example, the second sweat rate data can be used as reference data for the first sweat rate data, and the first sweat rate data can be used as reference data for the second sweat rate data. As a result, it is possible to detect and reduce body movement noise from the first sweat rate data or the second sweat rate data without using the output of the pressure sensor as reference data. Therefore, body movement noise can be reduced more effectively.

[0075] According to the information processing program of the second aspect of the present disclosure, the sweat rate data is generated based on the first sweat rate data and the second sweat rate data generated based on the output of the electrical sensor unit and the optical sensor unit, so that, for example, the second sweat rate data can be reference data for the first sweat rate data, or the first sweat rate data can be reference data for the second sweat rate data. As a result, it is possible to detect and reduce body movement noise from the first sweat rate data or the second sweat rate data without using the output of the pressure sensor as reference data. Therefore, body movement noise can be reduced more effectively.

[0076] This application claims priority based on Japanese Patent Application No. 2020-072405, filed on April 14, 2020 in the Japan Patent Office, the entire contents of which are incorporated herein by reference.

[0077] Those skilled in the art will recognize that various modifications, combinations, subcombinations, and variations may occur to those skilled in the art depending on design requirements and other factors, and that such modifications are within the scope of the appended claims and their equivalents.

Claims

1. an acquisition unit that acquires external sweat rate data regarding the amount of sweat emerging from the epidermis, which is generated based on an output from the first sensor unit, and internal sweat rate data regarding the amount of sweat in the epidermis and the dermis, which is generated based on an output from the second sensor unit; a generating unit for generating sweat rate data based on the external sweat rate data and the internal sweat rate data; Equipped with Information processing device.

2. The apparatus further includes an evaluation unit that evaluates the reliability of the external sweat rate data based on internal sweat rate difference data, which is a difference between two pieces of internal sweat rate data detected at different times, The generating unit processes the external sweat rate data based on the evaluation result of the reliability of the external sweat rate data by the evaluating unit, and sets the resultant data as the sweat rate data. The information processing device according to claim 1 .

3. the evaluation unit evaluates reliability of the internal sweat rate data based on external sweat rate difference data, which is a difference between two pieces of external sweat rate data detected at different detection times; The generation unit processes the internal sweat rate data based on the evaluation result of the reliability of the internal sweat rate data by the evaluation unit, and sets the resultant data as the sweat rate data. The information processing device according to claim 2 .

4. the evaluation unit evaluates the reliability of both the external sweat rate data and the internal sweat rate data, which are in the in-phase correlation, as low when the internal sweat rate difference data and the external sweat rate difference data have an in-phase correlation with each other, and evaluates the reliability of both the external sweat rate data and the internal sweat rate data, which are in the in-phase correlation with each other, as high when the internal sweat rate difference data and the external sweat rate difference data have an in-phase correlation with each other; The generating unit sets a portion of the external sweat rate data and the internal sweat rate data that is evaluated by the evaluating unit as having a high reliability as the sweat rate data, and excludes a portion of the external sweat rate data and the internal sweat rate data that is evaluated by the evaluating unit as having a low reliability from the sweat rate data. The information processing device according to claim 3 .

5. The device further includes an output unit that outputs the sweat rate data reflecting the evaluation by the evaluation unit to an outside. The information processing device according to claim 4.

6. and an evaluation unit that evaluates the reliability of the external sweat rate data based on internal sweat rate difference data, which is a difference between two pieces of internal sweat rate data detected at different times. The generating unit generates first reliability evaluation data for the external sweat rate data based on an evaluation result of the reliability of the external sweat rate data by the evaluating unit. The information processing device according to claim 1 .

7. The apparatus further includes an output unit that outputs the external sweat rate data and the first reliability evaluation data to the outside as the sweat rate data. The information processing device according to claim 6.

8. the evaluation unit evaluates reliability of the internal sweat rate data based on external sweat rate difference data, which is a difference between two pieces of external sweat rate data detected at different times; The generating unit generates second reliability evaluation data for the internal sweat rate data based on an evaluation result of the reliability of the internal sweat rate data by the evaluating unit. The information processing device according to claim 6.

9. The apparatus further includes an output unit that outputs the external sweat rate data, the internal sweat rate data, the first reliability evaluation data, and the second reliability evaluation data to an outside as the sweat rate data. The information processing device according to claim 8.

10. The first sensor unit detects an amount of external sweating and outputs the data obtained thereby; the second sensor unit detecting the amount of internal sweating and outputting the data obtained thereby; Further equipped The information processing device according to claim 1 .

11. The first sensor unit is an electrical sensor that detects the amount of external sweating. The second sensor unit detects the amount of internal sweating optically. The information processing device according to claim 10.

12. Obtaining external sweat rate data regarding the amount of sweat emerging from the epidermis, which is generated based on an output from the first sensor unit, and internal sweat rate data regarding the amount of sweat in the epidermis and the dermis, which is generated based on an output from the second sensor unit; generating sweat rate data based on the external sweat rate data and the internal sweat rate data; Have your computer run Information processing program.

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