JP2021053261A - Analysis method, analyzer, and program - Google Patents

Abstract

To provide a method for performing appropriate analysis excluding an individual difference on the number of sweat glands and the like in the case of analyzing a mental state of stress and the like on the basis of a measurement result of a subject's sweat rate.SOLUTION: An analysis method to be performed by an analyzer 300 includes: depending on a result obtained by measuring sweat rates of psychogenic perspiration using a perspiration meter 200, calculating a degree of variation of the sweat rates with respect to a lapse of time; and calculating a score on the basis of the calculated degree of variation. A standard deviation is used as the degree of variation and the score is calculated on the basis of the degree of variation and a predetermined threshold.SELECTED DRAWING: Figure 1

Description

The present invention relates to an analysis method, an analysis device, and a program.

A sweat meter that measures the amount of sweating may be used to measure the amount of mental sweating that responds to stress regardless of body temperature regulation.

Patent Document 1 is, for example, an example of a technique using the above measurement results. Patent Document 1 describes, for example, that it is determined that a subject has responded to a lie when the amount of continuous sweating suddenly increases during a question and response.

Patent No. 2512695 Patent No. 3559993 Patent No. 3711521

In the technique described in Patent Document 1, a process of detecting whether or not it is a lie is executed based on the amount of sweating. Mental sweating represents the activity of the cutaneous sympathetic nerve, and when there is an activity of brain functions such as the amygdala, hippocampus, and prefrontal cortex, that is, when there is an emotional reaction (when a person feels comfortable or uncomfortable, becomes nervous or upset) Since it occurs instantaneously, it is possible to evaluate the stress state and stress event by analyzing this. However, the amount of sweating varies from person to person depending on the number of sweat glands and the like. Therefore, there has been a problem that it may be difficult to perform an appropriate analysis when performing an analysis based on the measurement result of the perspiration meter.

Therefore, an object of the present invention is to provide an analysis method, an analysis device, and a program for solving the problem that it may be difficult to perform an appropriate analysis when performing an analysis based on the measurement result of a sweat meter. is there.

The analysis method, which is one embodiment of the present invention, in order to achieve such an object
The analyzer is
According to the result of measuring the amount of sweating of mental sweating, the degree of variation in the amount of sweating with respect to the passage of time was calculated.
The score is calculated based on the calculated degree of variation.

In addition, the analyzer, which is another embodiment of the present invention, is
A variation degree calculation unit that calculates the variation degree of the sweating amount with the passage of time according to the result of measuring the sweating amount of mental sweating.
A score calculation unit that calculates a score based on the variation degree calculated by the variation degree calculation unit, and a score calculation unit.
It has a structure of having.

In addition, the program which is another form of the present invention
For the analyzer
A variation degree calculation unit that calculates the variation degree of the sweating amount with the passage of time according to the result of measuring the sweating amount of mental sweating.
A score calculation unit that calculates a score based on the variation degree calculated by the variation degree calculation unit, and a score calculation unit.
It is a program to realize.

According to the present invention, an analysis method, an analysis device, and an analysis device for solving the problem that it may be difficult to perform an appropriate analysis when performing an analysis based on the measurement result of a sweat meter by being configured as described above. It becomes possible to provide a program.

It is a figure which shows an example of the whole structure of the processing system in 1st Embodiment of this invention. It is a block diagram which shows an example of the structure of the processing apparatus shown in FIG. It is a figure for demonstrating an example of the process of calculating the degree of variation. It is a figure for demonstrating an example of the period for calculating the degree of variation. It is a figure for demonstrating an example of a score calculation process. It is a figure which shows an example of the processing information used when determining the processing. It is a flowchart which shows an example of the operation of the processing apparatus in 1st Embodiment of this invention. It is a flowchart which shows an example of the end determination shown in FIG. 7 in more detail. It is a block diagram which shows an example of the structure of the processing apparatus in the 2nd Embodiment of this invention.

[First Embodiment]
The first embodiment of the present invention will be described with reference to FIGS. 1 to 8. FIG. 1 is a diagram showing an example of the overall configuration of the processing system 100. FIG. 2 is a block diagram showing an example of the configuration of the processing device 300. FIG. 3 is a diagram for explaining an example of processing for calculating the degree of variation. FIG. 4 is a diagram for explaining an example of a period for calculating the degree of variation. FIG. 5 is a diagram for explaining an example of the score calculation process. FIG. 6 is a diagram showing an example of processing information used when determining the processing to be executed. FIG. 7 is a flowchart showing an example of the operation of the processing device 300. FIG. 8 is a flowchart showing an example of the end determination shown in FIG. 7 in more detail.

In the first embodiment of the present invention, the processing system 100 including the processing device 300 that performs analysis based on the measurement result by the sweat meter 200 and determines the processing to be executed will be described. As will be described later, the processing device 300 calculates the degree of variation in the amount of sweating with the passage of time based on the information indicating the amount of sweating acquired from the sweating meter 200. Further, the processing device 300 calculates the score based on the calculated degree of variation. Then, the processing device 300 determines the processing to be executed based on the calculated result.

FIG. 1 is a diagram showing an example of the overall configuration of the processing system 100. Referring to FIG. 1, the processing system 100 includes, for example, a sweat meter 200 and a processing device 300. As shown in FIG. 1, the sweat meter 200 and the processing device 300 are connected so as to be able to communicate with each other by, for example, by wire. The sweat meter 200 and the processing device 300 may be connected so as to be able to communicate with each other by wireless communication such as Wi-Fi (registered trademark) or Bluetooth (registered trademark).

The sweat meter 200 is attached to the palm of the user and measures the amount of perspiration. For example, the sweat meter 200 continuously and at regular intervals measures the amount of mental sweating that responds to the stress of the user. Then, the sweat meter 200 transmits information indicating the amount of perspiration, which is the measurement result, to the processing device 300.

The sweat meter 200 is, for example, a ventilation capsule type sweat meter. Here, the ventilation capsule type sweat meter measures the amount of perspiration based on the humidity of the air measured before supplying the capsule and the humidity measured after mixing the supplied air and sweat in the capsule. It refers to a device. The amount of sweating on the palms and soles of the feet, which is called mental sweating, increases rapidly in response to the stress response. By using a ventilation capsule type sweating meter as the sweating meter 200, the situation is continuously and high. In response, the amount of sweating can be measured accurately. A configuration example of the ventilation capsule type sweat meter is disclosed in, for example, Patent Document 2 and Patent Document 3.

The sweat meter 200 may be attached to a place other than the palm of the user. For example, the sweat meter 200 can be attached to the sole of the user's foot or the like.

Further, the sweat meter 200 may be provided at a position where it comes into contact with the palm of the user, in addition to being attached to the palm of the user. For example, the sweat meter 200 may be provided at a position where it comes into contact with a measuring portion such as a pointing device such as a mouse, a steering wheel of an automobile, a controller of a game machine, or the like.

The processing device 300 is an information processing device that performs analysis based on the measurement result of the sweat meter 200 and determines the processing to be executed. FIG. 2 shows an example of the configuration of the processing device 300. Referring to FIG. 2, the processing apparatus 300 has a storage unit 310 and an arithmetic processing unit 320 as main components.

The storage unit 310 is a storage device such as a hard disk or a memory. The storage unit 310 stores processing information and a program 316 required for various processes in the arithmetic processing unit 320. The program 316 realizes various processing units by being read and executed by the arithmetic processing unit 320. The program 316 is read in advance from an external device or a recording medium via a data input / output function of the processing device 300, and is stored in the storage unit 310. The main information stored in the storage unit 310 includes, for example, sweating data 311 and variation degree information 312, threshold information 313, score information 314, and processing information 315.

Further, the arithmetic processing unit 320 has a microprocessor such as an MPU and its peripheral circuits. The arithmetic processing unit 320 reads the program 316 from the storage unit 310 and executes it, thereby realizing various processing units in cooperation with the hardware and the program 316. The main processing units realized by the calculation processing unit 320 include, for example, an acquisition unit 321, a variation degree calculation unit 322, an end determination unit 323, a score calculation unit 324, and a processing determination unit 325.

Hereinafter, each of the above-described configurations will be described in more detail.

The acquisition unit 321 acquires information indicating the amount of perspiration, which is the measurement result of the perspiration meter 200, from the perspiration meter 200. Then, the acquisition unit 321 stores the acquired measurement result as sweating data 311 in the storage unit 310.

The variation degree calculation unit 322 calculates the variation degree of the sweating amount with respect to the passage of time based on the sweating data 311. For example, the variation degree calculation unit 322 calculates the standard deviation of the amount of sweating within a predetermined time as the variation degree. Then, the variation degree calculation unit 322 stores the calculated variation degree as the variation degree information 312 in the storage unit 310.

FIG. 3 is a diagram showing an example of a process in which the variation degree calculation unit 322 calculates the standard deviation which is the variation degree. As shown in FIG. 3, for example, the variation degree calculation unit 322 calculates the standard deviation from the measurement result of the amount of sweating in one second. Further, the variation degree calculation unit 322 performs the above calculation process at predetermined time intervals. For example, the variation degree calculation unit 322 performs the above calculation process in 0.5 second increments.

Specifically, for example, as shown in FIG. 3, the variation degree calculation unit 322 is based on the data of the amount of sweating in the most recent 1 second, 1 second after the occurrence of the sweating reaction analysis event that starts the variation degree calculation process. To calculate the first standard deviation. Subsequently, the variation degree calculation unit 322 calculates the second standard deviation based on the sweating amount data in the most recent 1 second, 1.5 seconds after the occurrence of the sweating reaction analysis event that starts the variation degree calculation process. To do. Similarly, the variation degree calculation unit 322 calculates the third standard deviation based on the sweating amount data in the most recent 1 second, 2.0 seconds after the occurrence of the sweating reaction analysis event that starts the variation degree calculation process. To do. For example, as described above, the variation degree calculation unit 322 performs a process of calculating the standard deviation from the information indicating the amount of sweating per second every 0.5 seconds. In other words, the variation degree calculation unit 322 calculates a plurality of standard deviations based on the sweating data 311.

The variation degree calculation unit 322 can acquire information indicating that the sweating reaction analysis event has occurred by any means. For example, the processing device 300 can be configured to detect that a sweating reaction analysis event has occurred based on voice information, image information, or the like. The variation degree calculation unit 322 can acquire information indicating that a sweating reaction analysis event has occurred, depending on the result of detection by the processing device 300. Further, the variation degree calculation unit 322 may be configured to acquire, for example, information indicating that a sweating reaction analysis event has occurred from an external device or the like. For example, the variation degree calculation unit 322 can be configured to detect that a sweating reaction analysis event has occurred by detecting a predetermined action of the user such as a mouse click. Further, the variation degree calculation unit 322 may be configured to acquire information indicating that a sweating reaction analysis event has occurred, for example, in response to the acquisition unit 321 starting to acquire information indicating the amount of sweating. I do not care.

Further, the above-mentioned calculation process of the degree of variation by the degree of variation calculation unit 322 is continued until the end determination is made by the end determination unit 323 described later. Details of the processing by the end determination unit 323 will be described later.

For example, as described above, the variation degree calculation unit 322 calculates the variation degree of the sweating amount based on the sweating data 311. Further, the variation degree calculation unit 322 performs the variation degree calculation process from the occurrence of the sweating reaction analysis event to the end determination by the end determination unit 323, for example.

The target period and frequency for calculating the standard deviation by the variation degree calculation unit 322 are not limited to the above-exemplified cases. For example, the variation degree calculation unit 322 may be configured to perform a process of calculating the standard deviation from the information indicating the amount of sweating for 1.5 seconds every 0.8 seconds. As described above, the target period and frequency for calculating the standard deviation may be other than those illustrated above.

The end determination unit 323 performs an end determination for determining the end of the variation degree calculation process based on the sweating data 311 and the like. In other words, the end determination unit 323 determines the measurement range for measuring the amount of perspiration and calculating the degree of variation (or calculating the score described later) by performing an end determination for determining the end of the variation degree calculation process. To do. Then, the end determination unit 323 notifies the variation degree calculation unit 322 and the score calculation unit 324 that the determination to end has been performed.

For example, the end determination unit 323 waits for the elapse of the first time (for example, 6 seconds) after the occurrence of the sweating reaction analysis event. Then, the end determination unit 323 determines the end to indicate that the calculation of the degree of variation is completed when the predetermined condition is satisfied after the lapse of the first time.

Specifically, after the first time elapses, the end determination unit 323 continues for a preset period of no sweating reaction (the amount of perspiration of mental sweating is 0, or less than or equal to a predetermined value). Then, the end is determined. Alternatively, the end determination unit 323 determines the end as a timeout when the preset second time elapses after the first time elapses. In this way, the end determination unit 323 determines the end after the lapse of the first time, when no sweating reaction continues for a preset second, or when the second time elapses.

The first time, the value of the amount of sweating determined to have no sweating reaction, the number of continuous seconds without sweating reaction, and the second time may be set to arbitrary values. Further, the conditions for the end determination unit 323 to determine the end may be other than those illustrated above, or may be a part of those exemplified above.

The above can be summarized in FIG. FIG. 4 is a diagram showing an example of a period for calculating the degree of variation. As shown in FIG. 4, after the first time elapses, the degree of variation is calculated until the second time elapses or no sweating reaction continues for a preset second. That is, the degree of variation is calculated in advance for the first analysis section until the first time elapses after the occurrence of the sweating reaction analysis event and the second time elapses or no sweating reaction after the elapse of the first analysis section. It is performed over two analysis sections, a second analysis section until it continues for a set second. Further, as will be described later, the score is calculated based on the calculation results of the first analysis section and the second analysis section. That is, the score calculation process is performed based on the calculation result of the degree of variation from the occurrence of the sweating reaction analysis event to the end of the second analysis section. In other words, the first analysis section and the second analysis section are measurement ranges for measuring the amount of sweating, calculating the degree of variation, and calculating the score.

The score calculation unit 324 calculates a score to be used when evaluating the degree of sweating based on the degree of variation indicated by the degree of variation information 312. Then, the score calculation unit 324 stores the calculated score as score information 314 in the storage unit 310.

For example, when the score calculation unit 324 receives a notification from the end determination unit 323 indicating that the end has been determined, the score calculation unit 324 refers to the variation degree information 312 and refers to the first analysis section and the second analysis section to be score calculated. Get the information that shows the standard deviation in. Further, the score calculation unit 324 refers to the threshold value information 313 and acquires information indicating the threshold value. Then, the score calculation unit 324 calculates the score based on the acquired information indicating the standard deviation and the information indicating the threshold value. For example, the score calculation unit 324 calculates the score by measuring the number of times of the standard deviation exceeding the threshold value among the standard deviations in the first analysis section and the second analysis section.

For example, FIG. 5 is a diagram for explaining an example of the score calculation process. In FIG. 5, a line graph of the curve shows the amount of sweating, and a bar graph shows the value of the standard deviation calculated based on the amount of sweating. For example, in the case shown in FIG. 5, it is assumed that the threshold value is 0.008. In this case, in FIG. 5, the number of standard deviations exceeding the threshold value “0.008” is four. Therefore, in the case of the example shown in FIG. 5, the score calculation unit 324 calculates "4" as the score.

For example, as described above, the score calculation unit 324 calculates the score according to the number of standard deviations exceeding the threshold value based on the variation degree information 312 and the threshold value information 313. Then, the score calculation unit 324 stores the calculated score as score information 314 in the storage unit 310.

As described above, the score calculation unit 324 calculates the score based on the number of standard deviations exceeding the threshold value. Therefore, it can be said that the score calculated by the score calculation unit 324 is a score whose value increases as the period in which the degree of variation is larger than the predetermined value becomes longer. Further, the score calculated by the score calculation unit 324 indicates that the larger the value, the greater the degree of change in the amount of perspiration measured by the perspiration meter 200. In other words, it can be said that the score calculated by the score calculation unit 324 is a value for evaluating the degree of change in the amount of sweating (or evaluating the degree of sweating).

Further, it is assumed that the threshold value information 313 is stored in the storage unit 310 in advance, for example. The threshold value indicated by the threshold value information 313 may be any value. Further, the threshold value indicated by the threshold value information 313 may be configured to be dynamically correctable.

The process determination unit 325 determines the process to be executed based on the score indicated by the score information 314. For example, the processing determination unit 325 determines the processing to be executed based on the score indicated by the score information 314 and the processing information 315 previously stored in the storage unit 310.

FIG. 6 shows an example of processing information 315. As shown in FIG. 6, in the processing information 315, for example, the score value and the processing content are associated with each other. The processing determination unit 325 determines the processing to be executed by referring to the processing information 315 and specifying the processing content corresponding to the score indicated by the score information 314. For example, in the case shown in FIG. 6, when the score is 3, the processing determination unit 325 determines that the processing C is executed.

The processing content in the processing information 315 can be configured to change stepwise according to the value of the score. For example, by configuring the processing content in the processing information 315 to change stepwise according to the score value, the processing determination unit 325 may determine to perform the stepwise processing according to the score value. You can.

Further, the result of the determination by the processing determination unit 325 can be configured to be transmitted to an external device or the like. The processing apparatus 300 may be configured to execute processing according to the result of determination by the processing determination unit 325.

The above is an example of the configuration of the processing device 300.

Subsequently, the operation of the processing device 300 will be described with reference to FIGS. 7 and 8. First, an example of the overall operation of the processing device 300 will be described with reference to FIG. 7.

With reference to FIG. 7, the acquisition unit 321 acquires information indicating the amount of perspiration, which is the measurement result of the perspiration meter 200, from the perspiration meter 200 (step S101). Then, the acquisition unit 321 stores the acquired measurement result as sweating data 311 in the storage unit 310.

The variation degree calculation unit 322 calculates the variation degree of the sweating amount based on the sweating data 311 (step S102). For example, the variation degree calculation unit 322 calculates the standard deviation of the amount of sweating in a predetermined period as the variation degree. Then, the variation degree calculation unit 322 stores the calculated variation degree as the variation degree information 312 in the storage unit 310.

The end determination unit 323 performs an end determination for determining the end of the variation degree calculation process based on the sweating data 311 or the like (step S103). Then, the end determination unit 323 notifies the variation degree calculation unit 322 and the score calculation unit 324 that the determination to end has been performed. The details of the processing by the end determination unit 323 will be described later.

Upon receiving the above notification, the variation degree calculation unit 322 ends the variation degree calculation process.

The score calculation unit 324 calculates the score based on the variation degree information 312 (step S104). Then, the score calculation unit 324 stores the calculated score as score information 314 in the storage unit 310.

The process determination unit 325 determines the process to be executed based on the score indicated by the score information 314. For example, the processing determination unit 325 determines the processing to be executed based on the score indicated by the score information 314 and the processing information 315 previously stored in the storage unit 310 (step S105).

The above is an example of the operation of the processing device 300.

Subsequently, with reference to FIG. 8, the details of the processing by the end determination unit 323 shown in step S103 will be described.

Referring to FIG. 8, the end determination unit 323 waits for the elapse of the first time after the occurrence of the sweating reaction analysis event (step S201).

After the lapse of the first time (step S201, Yes), the end determination unit 323 determines the end when the no sweating reaction continues for a preset second (step S202, Yes) (step S203). Further, even if no sweating reaction continues for a preset second (step S202, No), the end determination unit 323 times out when the preset second time elapses (step S204, Yes). (Step S203). As described above, after the lapse of the first time, the end determination unit 323 continues for a preset second (step S202, Yes) that there is no sweating reaction, or the second time elapses (step S204, Yes). , The end is determined (step S203).

The above is a detailed example of the end determination.

As described above, the processing device 300 has a variation degree calculation unit 322, a score calculation unit 324, and a processing determination unit 325. With such a configuration, the score calculation unit 324 can calculate the score based on the degree of variation calculated by the degree of variation calculation unit 322. Further, the processing determination unit 325 can determine the processing based on the score calculated by the score calculation unit 324. This makes it possible to determine the process to be executed while suppressing the influence of individual differences in the amount of sweating. As a result, when performing analysis or processing based on the measurement result of the sweat meter 200, it is possible to perform appropriate analysis or processing.

Further, according to the above configuration, the processing determination unit 325 can determine the processing according to the score. For example, the processing determination unit 325 can determine the processing step by step according to the score. This makes it possible to determine more accurate and appropriate processing.

In this embodiment, a case where the amount of perspiration of mental sweating is measured by using a perspiration meter 200 such as a ventilation capsule type perspiration meter has been illustrated. However, instead of the ventilation capsule type sweat meter, a Galvanic Skin Response (GSR) that electrically evaluates mental sweating can also be used. GSR has an energization method that measures skin impedance and a potential method that measures the potential difference between the hairless part (palm / sole) and the hairy part (other than the one on the left), and the value suddenly increases in response to the appearance of mental sweating. Changes to. In this way, GSR may be used to measure the amount of perspiration of mental sweating.

Further, in the present embodiment, a case where each processing unit is realized by reading the program 316 stored in the storage unit 310 by the arithmetic processing unit 320 has been illustrated. However, each processing unit may be realized by hardware such as a logic circuit.

Further, in the present embodiment, a case where the function as the processing device 300 is realized by one information processing device has been illustrated. However, the function as the processing device 300 may be realized by a plurality of information processing devices. For example, the processing device 300 includes an analysis device that executes processing of the acquisition unit 321, the variation degree calculation unit 322, the end determination unit 323, and the score calculation unit 324, a processing execution device that executes the processing of the processing determination unit 325, and the processing execution device. It may be composed of. The processing device 300 may be realized from a plurality of information processing devices other than those illustrated above.

The processing system 100 described in the present embodiment can be applied to situations where various processes are determined. For example, the processing system 100 can be applied to a stress evaluation system that identifies a factor of stress from a sweating reaction to a question. When the processing system 100 is applied to the stress evaluation system, the processing determination unit 325 can determine how to narrow down the processing for narrowing the range of the next question to be performed according to the size of the score. For example, the processing determination unit 325 can be configured to make a determination to narrow down the range of the next question to the range to which the question having the larger score belongs as the score is larger. Further, the processing system 100 measures the amount of perspiration from a sweat meter 200 incorporated in a controller of a game machine or the like, evaluates the content, and for example, a system that gradually branches the progress of the game content according to emotional changes, a mouse, or the like. It can be applied to, for example, a system in which the amount of perspiration is measured from a perspiration meter 200 incorporated in a handle or the like to detect drowsiness and evaluate concentration. The treatment system 100 may be applied to a system other than the above-exemplified system in which the treatment is branched according to the amount of perspiration.

[Second Embodiment]
Next, a second embodiment of the present invention will be described with reference to FIG. In the second embodiment, the outline of the configuration of the analysis device 40 will be described.

FIG. 9 shows an example of the configuration of the analysis device 40. Referring to FIG. 9, the analysis device 40 includes, for example, a variation degree calculation unit 41 and a score calculation unit 42.

The above-mentioned processing unit can be realized by hardware such as a logic circuit, for example. The above-mentioned processing unit may be realized, for example, by executing a program stored in the storage device by an arithmetic unit such as a CPU (Central Processing Unit).

The variation degree calculation unit 41 calculates the variation degree of the sweating amount with the passage of time according to the result of measuring the sweating amount of mental sweating.

The score calculation unit 42 calculates the score based on the degree of variation calculated by the degree of variation calculation unit 41.

As described above, the analysis device 40 has a variation degree calculation unit 41 and a score calculation unit 42. With such a configuration, the score calculation unit 42 can calculate the score based on the degree of variation calculated by the degree of variation calculation unit 41. By calculating the score in this way, it is possible to analyze regardless of the amount of sweating. That is, according to the above configuration, when performing an analysis based on the measurement result of the sweat meter 200, it is possible to perform an appropriate analysis.

Further, the above-mentioned analysis device 40 can be realized by incorporating a predetermined program into the analysis device 40. Specifically, the program according to another embodiment of the present invention is a variation degree calculation unit that calculates the variation degree of the sweating amount with the passage of time according to the result of measuring the sweating amount of mental sweating on the analysis device 40. This is a program for realizing 41 and a score calculation unit 42 that calculates a score based on the variation degree calculated by the variation degree calculation unit 41.

Further, in the analysis method executed by the analysis device 40 described above, the analysis device 40 calculates the degree of variation in the amount of sweating with the passage of time according to the result of measuring the amount of sweating in mental sweating, and the calculated variation. The method is to calculate the score based on the degree.

Even the invention of the program or the analysis method having the above-mentioned configuration can achieve the above-mentioned object of the present invention because it has the same operation and effect as the above-mentioned analysis device 40.

<Additional notes>
Part or all of the above embodiments may also be described as in the appendix below. Hereinafter, the outline of the analysis method and the like in the present invention will be described. However, the present invention is not limited to the following configurations.

(Appendix 1)
The analyzer is
According to the result of measuring the amount of sweating of mental sweating, the degree of variation in the amount of sweating with respect to the passage of time was calculated.
An analysis method for calculating a score based on the calculated degree of variation.
(Appendix 2)
The analysis method described in Appendix 1
An analysis method for calculating the standard deviation of the amount of sweating within a predetermined time as the degree of variation.
(Appendix 3)
The analysis method according to Appendix 1 or Appendix 2.
An analysis method for calculating the score based on the degree of variation calculated at predetermined time intervals and a predetermined threshold value within the measurement range for measuring the amount of sweating.
(Appendix 4)
The analysis method described in Appendix 3
An analysis method in which the number of times the threshold value is exceeded among the degree of variation within the measurement range is measured, and the score is calculated based on the measurement result.
(Appendix 5)
The analysis method according to Appendix 3 or Appendix 4.
An analysis method for determining the measurement range based on the measurement result of the amount of sweating.
(Appendix 6)
The analysis method described in Appendix 5
An analysis method for determining the measurement range according to the time when the value of the amount of sweating becomes equal to or less than a predetermined value.
(Appendix 7)
The analysis method according to Appendix 5 or Appendix 6, wherein the analysis method is used.
An analysis method for determining the measurement range according to the time during which the value of the amount of sweating becomes equal to or less than a predetermined value after the elapse of a predetermined time.
(Appendix 8)
The analysis method according to any one of Supplementary note 1 to Supplementary note 7.
An analysis method that determines the processing to be executed based on the score.
(Appendix 9)
A variation degree calculation unit that calculates the variation degree of the sweating amount with the passage of time according to the result of measuring the sweating amount of mental sweating.
A score calculation unit that calculates a score based on the variation degree calculated by the variation degree calculation unit, and a score calculation unit.
Analytical device with.
(Appendix 10)
For the analyzer
A variation degree calculation unit that calculates the variation degree of the sweating amount with the passage of time according to the result of measuring the sweating amount of mental sweating.
A score calculation unit that calculates a score based on the variation degree calculated by the variation degree calculation unit, and a score calculation unit.
A program to realize.

The programs described in each of the above embodiments and appendices may be stored in a storage device or recorded in a computer-readable recording medium. For example, the recording medium is a portable medium such as a flexible disk, an optical disk, a magneto-optical disk, and a semiconductor memory.

Although the present invention has been described above with reference to each of the above embodiments, the present invention is not limited to the above-described embodiments. Various changes that can be understood by those skilled in the art can be made to the structure and details of the present invention within the scope of the present invention.

100 Processing system 200 Sweating meter 300 Processing device 310 Storage unit 311 Sweating data 312 Variation degree information 313 Threshold information 314 Score information 315 Processing information 316 Program 320 Calculation processing unit 321 Acquisition unit 322 Variation degree calculation unit 323 End judgment unit 324 Score calculation unit 325 Processing judgment unit 40 Analysis device 41 Variation degree calculation unit 42 Score calculation unit

Claims (10)

The analyzer is
According to the result of measuring the amount of sweating of mental sweating, the degree of variation in the amount of sweating with respect to the passage of time was calculated.
An analysis method for calculating a score based on the calculated degree of variation. The analysis method according to claim 1.
An analysis method for calculating the standard deviation of the amount of sweating within a predetermined time as the degree of variation. The analysis method according to claim 1 or 2.
An analysis method for calculating the score based on the degree of variation calculated at predetermined time intervals and a predetermined threshold value within the measurement range for measuring the amount of sweating. The analysis method according to claim 3.
An analysis method in which the number of times the threshold value is exceeded among the degree of variation within the measurement range is measured, and the score is calculated based on the measurement result. The analysis method according to claim 3 or 4.
An analysis method for determining the measurement range based on the measurement result of the amount of sweating. The analysis method according to claim 5.
An analysis method for determining the measurement range according to the time during which the value of the amount of sweating becomes equal to or less than a predetermined value. The analysis method according to claim 5 or 6.
An analysis method for determining the measurement range according to the time during which the value of the amount of sweating becomes equal to or less than a predetermined value after the elapse of a predetermined time. The analysis method according to any one of claims 1 to 7.
An analysis method that determines the processing to be executed based on the score. A variation degree calculation unit that calculates the variation degree of the sweating amount with the passage of time according to the result of measuring the sweating amount of mental sweating.
A score calculation unit that calculates a score based on the variation degree calculated by the variation degree calculation unit, and a score calculation unit.
Analytical device with. For the analyzer
A variation degree calculation unit that calculates the variation degree of the sweating amount with the passage of time according to the result of measuring the sweating amount of mental sweating.
A score calculation unit that calculates a score based on the variation degree calculated by the variation degree calculation unit, and a score calculation unit.
A program to realize.

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