JP7262002B2 - Arousal induction system - Google Patents

Description

The present disclosure relates to wakefulness induction systems.

BACKGROUND ART Conventionally, there has been proposed an awakening induction control device that induces awakening of a person in such a way as to awaken a person from drowsiness. For example, Patent Literature 1 discloses a device that stimulates a person with heat and induces awakening of the person by controlling air conditioning. Further, for example, Patent Literature 2 and Patent Literature 3 disclose a device that stimulates a person with sound and induces awakening of the person by controlling the sound. Further, Patent Literature 4 discloses a device that stimulates a person with the scent and induces awakening of the person by controlling a device that emits the scent.

JP 2005-186657 A JP-A-2009-31905 JP-A-11-109985 JP-A-11-310053

However, a conventional device for inducing arousal of a person detects drowsiness of the person and then induces the awakening of the person. In other words, since wakefulness is induced after a person is once drowsy, it actually takes time until the degree of wakefulness increases.

Therefore, an object of the present disclosure is to increase a person's arousal level by enabling wakefulness induction by various devices before a person becomes drowsy.

In order to solve the above problems, an awakening guidance system according to an aspect of the present disclosure includes an estimation unit that estimates the degree of drowsiness of a person for each individual based on information about the physiological conditions of a plurality of people; a control device that controls equipment for changing the surrounding environment of the person based on the degree of drowsiness susceptibility estimated by the estimation unit, wherein the control device controls the drowsiness susceptibility of the plurality of people. The device is controlled so that the degree of stiffness satisfies a predetermined condition.

Advantageous Effects of Invention According to the present disclosure, it is possible to induce wakefulness using various devices before a person becomes drowsy, thereby increasing the degree of wakefulness of the person.

1 is a block diagram showing a functional configuration of a drowsiness susceptibility estimation device according to Embodiment 1. FIG. FIG. 2 is a schematic diagram showing an example of an installation state of the thermal image sensor according to the embodiment. 3 is a schematic diagram showing an example of a thermal image of a person acquired by the thermal image sensor of FIG. 2; FIG. FIG. 4 is a schematic diagram showing another example of thermal image capturing by the thermal image sensor according to the embodiment. FIG. 5 is a schematic diagram showing an example of a thermal image of a person acquired by the thermal image sensor 21 of FIG. FIG. 6 is a graph showing the relationship between the degree of drowsiness and the amount of heat released. FIG. 7 is a graph showing the relationship between the degree of drowsiness and environmental temperature (air temperature). FIG. 8 is a flowchart showing a procedure for estimating the degree of drowsiness of a person by the device for estimating the susceptibility to drowsiness according to Embodiment 1; FIG. 9 is a flowchart showing a procedure for estimating the degree of drowsiness of a person according to the second embodiment. FIG. 10 is a flowchart showing a procedure for estimating the degree of drowsiness of a person according to the third embodiment. FIG. 11 is a block diagram showing a functional configuration of a drowsiness tendency estimation device according to Embodiment 4. FIG. FIG. 12 is a schematic diagram illustrating an example of an installation state of the illuminance sensor according to the embodiment; FIG. 13 is a graph showing the relationship between the degree of drowsiness and illuminance. 14 is a block diagram showing a functional configuration of a drowsiness tendency estimation device according to Embodiment 5. FIG. 15 is a block diagram showing a functional configuration of a drowsiness tendency estimation device according to Embodiment 6. FIG. FIG. 16 is a graph showing the amount of change in drowsiness level after a predetermined period of time when the amount of heat released by a person is 33 W/m ² . FIG. 17 is a graph showing the amount of change in drowsiness level after a predetermined period of time when the amount of heat released by a person is 50 W/m ² . FIG. 18 is a block diagram showing a functional configuration of a wakefulness induction system according to Embodiment 7. As shown in FIG. FIG. 19 is a graph showing the relationship between human comfort level and heat release amount. FIG. 20 is a block diagram showing a functional configuration of a wakefulness induction system according to Embodiment 9. As shown in FIG.

(Summary of this disclosure)
In order to solve the above problems, an apparatus for estimating drowsiness according to one aspect of the present disclosure includes a sensor that detects at least one of information about a person's heat and the surrounding environment of the person, and based on the detection result of the sensor, and an estimation unit for estimating the degree of drowsiness of a person for each individual.

According to this, the estimating unit estimates the degree of drowsiness of a person for each individual based on at least one of the information about the person's heat and the surrounding environment of the person detected by the sensor. In other words, even for a person who is not drowsy, the degree of drowsiness at that point in time can be estimated for each individual based on the person's heat-related information or the surrounding environment. Therefore, if such a drowsiness estimating apparatus is employed in an awakening induction system, it will be possible to induce awakening using various devices before a person becomes drowsy. Thereby, a person's alertness can be raised.

Also, the sensor may include a thermal image sensor that acquires a thermal image of a person as information about heat of the person.

Here, with a thermal image sensor, it is possible to easily acquire a thermal image for each individual. Therefore, the degree of drowsiness of each individual can be easily estimated based on the thermal image of the person acquired by the thermal image sensor.

In addition, the estimating unit may calculate the amount of heat radiation or the thermal sensation of a person from the thermal image acquired by the thermal image sensor, and estimate the degree of drowsiness of each individual based on the amount of heat radiation or the thermal sensation. good.

Here, it is known that the amount of human heat release or thermal sensation tends to show a tendency toward the degree of drowsiness. That is, the estimating unit estimates the degree of drowsiness of the person based on the person's heat release amount or thermal sensation, so it is possible to accurately estimate the drowsiness degree of the person.

Also, the sensor may include an illuminance sensor that detects the illuminance around the person as the surrounding environment of the person.

According to this, by detecting the illuminance around the person, it is possible to estimate the degree of drowsiness of the person.

The sensor may also include a gas sensor that detects the concentration of gaseous components around the person as the environment around the person.

According to this, it is possible to estimate the degree of drowsiness of the person by detecting the gas component around the person.

Further, a notification unit for notifying the degree of drowsiness may be provided.

According to this, since the notification unit notifies the degree of drowsiness, the person can be notified of the estimated degree of drowsiness. This notification enables a person to grasp the degree of drowsiness, which the person is unaware of, and can be reflected in future drowsiness measures.

In addition, the wakefulness guidance system controls a device for changing the surrounding environment of the person based on the drowsiness estimating device and the drowsiness easiness degree estimated by the drowsiness estimating device. and a controller that induces wakefulness.

According to this, the control device can drive the device for inducing the awakening of the person in a mode according to the degree of drowsiness. Therefore, it is possible to induce wakefulness by the device before a person becomes drowsy. Thereby, a person's alertness can be raised.

Further, a comfort level detection device that detects a person's comfort level may be provided, and the control device may control the device based on the comfort level detected by the comfort level detection device and the degree of drowsiness.

According to this, the control device controls the equipment based on the degree of comfort detected by the comfort level detection device and the degree of drowsiness, so that it is possible to induce wakefulness while reproducing an environment in which the person feels comfortable. is possible.

The device may also include a lighting device.

According to this, it is possible to induce awakening of a person by controlling the lighting device.

Further, the illumination device may irradiate pulsed light with a frequency of 0.1 Hz or more and 1 Hz or less and a duty ratio of 0.00001 or more and 0.1 or less during wakefulness induction.

According to this, at the time of wakefulness induction, pulsed light with a duty ratio of 0.00001 or more and 0.1 or less is emitted from the lighting device at a frequency of 0.1 Hz or more and 1 Hz or less. It can be carried out.

The device may also include an audio device.

According to this, it is possible to induce awakening of a person by controlling the acoustic device.

In addition, the acoustic device can output sounds with different frequencies on the left and right sides of a person, and during wakefulness induction, the left and right sounds may differ in frequency within a range of 30 Hz or less.

According to this, during wakefulness induction, since the difference in sound frequency between the left and right sound devices is 30 Hz or less, wakefulness induction can be performed efficiently.

The device may also include a vibrating device that vibrates the person.

According to this, it is possible to induce awakening of a person by controlling the vibrating device.

Further, the vibration device may generate vibration in a frequency band that stimulates the muscle spindles of a person during wakefulness induction.

According to this, at the time of induction of wakefulness, since the vibrating device generates vibration in a frequency band that stimulates human muscle spindles, induction of wakefulness can be efficiently performed.

The equipment may also include an air conditioner.

According to this, the awakening of the person can be induced by controlling the air conditioner.

Embodiments of the present disclosure will be described below with reference to the drawings. It should be noted that all of the embodiments described below represent comprehensive or specific examples of the present disclosure. Therefore, numerical values, components, arrangement positions and connection forms of components, steps, order of steps, and the like shown in the following embodiments are examples and are not intended to limit the present disclosure. Therefore, among the constituent elements in the following embodiments, constituent elements that are not described in independent claims representing the highest concept of the present disclosure will be described as optional constituent elements.

Each figure is a schematic diagram and is not necessarily strictly illustrated. Therefore, scales and the like are not always the same in each drawing. In each figure, the same reference numerals are assigned to substantially the same configurations, and duplicate descriptions are omitted or simplified.

(Embodiment 1)
[Device for estimating drowsiness]
<Configuration>
First, a drowsiness estimating apparatus according to Embodiment 1 will be described. 1 is a block diagram showing a functional configuration of a drowsiness susceptibility estimation device according to Embodiment 1. FIG.

The drowsiness estimating device 1 detects at least one of information about a person's heat and the surrounding environment of the person, and estimates the degree of drowsiness of the person for each individual based on the detection result. is. Here, the “drowsiness susceptibility degree” is an index that indicates the degree to which a person to be detected becomes drowsy after a state in which he or she is not drowsy. In other words, it can be said that a person estimated to have a low degree of drowsiness is less susceptible to drowsiness at this time. "Drowsiness is not easily attacked" includes a long time before feeling drowsiness, a slow progression of drowsiness within a predetermined time period, and being attacked by light sleepiness. On the other hand, it can be said that a person estimated to have a high degree of drowsiness is likely to be attacked by drowsiness at this time. The term "easily attacked by drowsiness" includes short time to feel drowsiness, rapid progress of drowsiness in a predetermined time, and being attacked by deep drowsiness.

Details of the drowsiness estimating apparatus 1 will be described below.

As shown in FIG. 1 , the drowsiness estimating device 1 includes a sensor 2 , an estimating section 3 , and a reporting section 4 .

The sensor 2 is a sensor that detects information about human heat. In this embodiment, the sensor 2 includes a thermal image sensor 21 that acquires a thermal image of the person as information on heat of the person. Specifically, the thermal image sensor 21 is a thermo camera that measures infrared rays emitted by a person by acquiring a thermal image by imaging with infrared rays.

FIG. 2 is a schematic diagram showing an example of an installation state of the thermal image sensor 21 according to the embodiment. FIG. 3 is a schematic diagram showing an example of a thermal image G1 of a person acquired by the thermal image sensor 21 of FIG. As shown in FIG. 2 , the thermal image sensor 21 is installed on a desk 150 . When one person P1 exists in the imaging range R of the thermal image sensor 21, the thermal image sensor 21 acquires a thermal image G1 as shown in FIG.

FIG. 4 is a schematic diagram showing another example of thermal image capturing by the thermal image sensor 21 according to the embodiment. FIG. 5 is a schematic diagram showing an example of thermal images G2 and G3 of a person acquired by the thermal image sensor 21 of FIG. As shown in FIG. 4, when two people P2 and P3 are present in the imaging range R of the thermal image sensor 21, as shown in FIG. G2 and G3 will be included. In other words, it is possible to acquire the thermal images G2 and G3 of a plurality of persons by one-time imaging.

Based on the thermal images G1, G2, and G3 acquired by the sensor 2, the estimation unit 3 estimates the degree of drowsiness of the person. Specifically, the estimation unit 3 is electrically connected to the sensor 2 and acquires the thermal images G1, G2, and G3 from the sensor 2. FIG. The estimating unit 3 calculates a person's heat release amount from the thermal images G1, G2, and G3, and estimates the sleepiness degree for each individual based on this heat release amount. When one image includes a thermal image G1 of one person, the estimating unit 3 calculates the heat release amount of one person from the thermal image G1. Further, when there are thermal images G2 and G3 of a plurality of persons in one image, the estimating section 3 calculates heat radiation amounts of the plurality of persons from the thermal images G2 and G3. A well-known calculation method can be used to calculate the heat release amount.

FIG. 6 is a graph showing the relationship between the degree of drowsiness and the amount of heat released. This graph summarizes the results of evaluating the degree of drowsiness by changing the amount of clothing worn by the subject and the environmental temperature (thermal condition) to determine the amount of heat released by the subject under each thermal condition. Specifically, subjects were evaluated for the degree of drowsiness under five thermal conditions. Thermal condition 1 is heavy clothing and the ambient temperature is 22°C. Thermal condition 2 is light clothing and the environmental temperature is 22°C. Thermal condition 3 is innerwear (clothing amount between thick and light clothing), and the environmental temperature is 22°C. The thermal condition 4 is underwear and the environmental temperature is 28°C. The thermal condition 5 is underwear and the environmental temperature is 16°C. For example, the amount of clothes in the case of thick clothes is 1.5 clos, the amount of clothes in the case of inner clothes is 1.0 clos, and the amount of clothes in the case of light clothes is 0.5 clos.

Then, the subject's facial expression is photographed under each thermal condition, and the drowsiness level after a predetermined time under each thermal condition is obtained from the characteristics of the facial expression after a predetermined time has passed under each thermal condition. It was evaluated as the degree of ease of becoming. In addition, under each thermal condition, a thermal image G1 of the subject was acquired by the thermal image sensor 21, and the heat release amount was calculated based on the thermal image G1. The evaluation results and the amount of heat release under each thermal condition are summarized in the graph of FIG. 6, and an approximate curve L thereof is obtained. Based on this approximate curve L, it is possible to estimate the degree of drowsiness from the amount of heat released.

It should be noted that it is also possible to evaluate the degree of drowsiness easily, for example, based on other physical characteristics that indicate signs of future drowsiness. In addition, it is also possible to evaluate the degree of drowsiness based on the test subject's report.

FIG. 7 is a graph showing the relationship between the degree of drowsiness and environmental temperature (air temperature). This graph summarizes the results of evaluating the environmental temperature under each thermal condition and the degree of drowsiness of the subject by changing the amount of clothes worn by the subject and the environmental temperature. Each condition and the method of evaluating the degree of drowsiness are the same as in the case of FIG. As shown in FIG. 7, under thermal conditions 1 to 3, the degrees of drowsiness are different even if the ambient temperature is the same. This indicates that the degree of drowsiness varies depending on the amount of clothing even if the environmental temperature is constant. Therefore, it can be seen that the drowsiness tendency cannot be determined on a one-to-one basis using the ambient temperature as a standard.

On the other hand, in the case of FIG. 6 described above, the amount of clothing does not affect the relationship between the amount of heat dissipation and the degree of drowsiness. can be estimated. Therefore, even if the amount of clothing varies from person to person, it is possible to estimate the degree of drowsiness of the person by obtaining the amount of heat release for each person.

The estimation unit 3 is implemented by, for example, a CPU (Central Processing Unit) and a control program stored in a storage unit communicable with the CPU. Examples of the storage unit include ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), SSD (Solid State Drive), and the like.

The notifying unit 4 notifies the degree of drowsiness estimated by the estimating unit 3 . Specifically, the reporting unit 4 is electrically connected to the estimating unit 3 and acquires the sleepiness degree from the estimating unit 3 . The notification unit 4 is, for example, a display device such as a display, and displays the degree of drowsiness in characters, pictures, symbols, etc. to notify the surroundings. Note that the notification unit 4 may be an audio device such as a speaker that performs auditory notification, or may be other devices, and its means is not limited to a display, an audio device, or the like.

<Action>
Next, the operation of the drowsiness estimating apparatus 1 according to the embodiment will be described with reference to FIG.

FIG. 8 is a flowchart showing a procedure for estimating the degree of drowsiness of a person by the device 1 for estimating the susceptibility to drowsiness according to the first embodiment.

First, the thermal image sensor 21 acquires a human thermal image G1 (step S1). The estimation unit 3 calculates the amount of heat released by the person based on the thermal image G1 acquired by the thermal image sensor 21 (step S2). Next, the estimating unit 3 estimates the degree of drowsiness of a person from the amount of heat dissipation based on the approximate curve L (step S3). Note that when the thermal images G2 and G3 of a plurality of people have been acquired in step S1, the estimating unit 3 repeats steps S2 and S3 by the number of people to estimate the sleepiness degree for each individual.

Thereafter, the notification unit 4 notifies the surroundings of the degree of drowsiness of each individual estimated by the estimation unit 3 (step S4). At the time of this notification, the degree of drowsiness of each individual may be individually notified. In addition, notification may be made only when the average value of the degree of drowsiness of multiple people exceeds a certain reference value. Notification may be made only when there is a degree of drowsiness.

<effect>
As described above, according to the present embodiment, the estimating unit 3 estimates the degree of drowsiness of a person for each individual based on the information about the person's heat detected by the sensor 2 . That is, even for a person who is not drowsy, the degree of drowsiness at that time can be estimated for each individual based on the person's heat information. Therefore, if such a drowsiness estimating apparatus 1 is employed in an awakening induction system, it becomes possible to induce awakening for each individual using various devices before a person becomes drowsy. Thereby, a person's awakening degree can be raised for every individual.

Here, the thermal image sensor 21 can easily acquire thermal images G1, G2, and G3 for each individual. Therefore, based on the thermal images G1, G2, and G3 of the person acquired by the thermal image sensor 21, it is possible to easily estimate the degree of drowsiness of each individual.

In addition, as described above, it was found that there is a correlation between the degree of drowsiness and the amount of heat released by a person. As a result, the estimating unit 3 estimates the degree of drowsiness of the person based on the amount of heat released by the person, so that it is possible to accurately estimate the degree of drowsiness of the person.

In addition, since the notification unit 4 can notify the degree of drowsiness for each individual, the estimated degree of drowsiness can be reported for each individual. This notification enables a person to grasp the degree of drowsiness, which the person is unaware of, and can be reflected in future drowsiness measures.

(Embodiment 2)
In the above first embodiment, the case of estimating the degree of drowsiness for each individual from the amount of heat released by a person has been exemplified. In this second embodiment, a case will be described in which the degree of drowsiness is estimated for each individual based on a person's thermal sensation (hot/cold sensation). It should be noted that, in the following description, portions equivalent to those of the first embodiment are denoted by the same reference numerals, and descriptions thereof may be omitted.

FIG. 9 is a flowchart showing a procedure for estimating the degree of drowsiness of a person according to the second embodiment.

First, the thermal image sensor 21 acquires a thermal image G1 of a person (step S11). The estimation unit 3 estimates the thermal sensation of a person based on the thermal image G1 acquired by the thermal image sensor 21 . Specifically, based on the thermal image G1 acquired by the thermal image sensor 21, the estimating unit 3 estimates the thermal sensation by detecting the skin temperature of the part exposed from the clothes (step S12). It is known that depending on the part of the human body, the skin temperature of that part has a high correlation with the thermal sensation. An example of a site that is highly correlated with thermal sensation is the nose. The value obtained by subtracting the skin temperature of the nose from the skin temperature of the forehead also shows a high correlation with the thermal sensation. The estimating unit 3 obtains the skin temperature of the site necessary for estimating the thermal sensation from the thermal image G1, and estimates the thermal sensation from the result. Note that other well-known methods can be used for estimating the thermal sensation, and the method is not limited to the method described above.

Next, the estimation unit 3 estimates the degree of drowsiness based on the thermal sensation (step S13). Here, a case is exemplified in which the degree of drowsiness is estimated from the amount of heat dissipation from which the thermal sensation is converted into the amount of heat dissipation. It is known that there is a predetermined relationship between the thermal sensation and the amount of heat released. The predetermined relationship is detailed in, for example, Non-Patent Document 1 (Non-Patent Document 1: Hideyoshi Ishigaki, 2 others, “Influence of temperature and humidity on heat balance and psychological reaction of the human body (Part 3)”, [online ], 1999, Nissei Ki (S46), [Searched May 31, 2017], Internet <URL: https://www.jstage.jst.go.jp/article/seikisho1966/36/3/36_3_S46 /_pdf>) is described. The estimating unit 3 converts the thermal sensation into a heat release amount based on a predetermined relationship. After that, the estimating unit 3 estimates the degree of drowsiness of the person based on the approximate curve L from the amount of heat released.

After that, the notification unit 4 notifies the surroundings of the degree of drowsiness of each individual estimated by the estimation unit 3 (step S14).

According to the present embodiment, the estimating unit 3 estimates the degree of drowsiness of the person based on the person's thermal sensation, so it is possible to accurately estimate the degree of drowsiness.

In this example, the amount of heat released is calculated in order to estimate the degree of drowsiness from the thermal sensation, but there is a certain correlation between the thermal sensation and the degree of drowsiness. It is shown that. That is, it is naturally possible to obtain the relationship between the degree of drowsiness directly from the thermal sensation without going through the amount of heat release, and the degree of drowsiness may be calculated directly from the thermal sensation from that relationship. Any other index may be used, and the method is not limited as long as the degree of drowsiness is calculated based on the thermal sensation.

Here, the thermal sensation of the person P1 is obtained from the thermal image G1 to calculate the degree of drowsiness. It is possible to individually estimate the degree of drowsiness of each person based on the thermal sensations of a plurality of persons.

(Embodiment 3)
In the second embodiment, the case of estimating the degree of drowsiness from the estimated thermal sensation has been described. In this third embodiment, a case will be described in which the thermal sensation is estimated based on the amount of heat released, and the degree of drowsiness is estimated from the thermal sensation. That is, in the third embodiment, the estimation unit 3 stores in advance the relationship between the thermal sensation and the degree of drowsiness. It is assumed that the relationship between the thermal sensation and the degree of drowsiness is appropriately set based on various experiments, simulations, empirical rules, and the like. For example, when the relationship between the thermal sensation and the degree of drowsiness is more accurate than the relationship between the amount of heat release and the degree of drowsiness, it is desirable to adopt this method.

FIG. 10 is a flowchart showing a procedure for estimating the degree of drowsiness of a person according to the third embodiment. It should be noted that, in the following description, portions equivalent to those of the first embodiment are denoted by the same reference numerals, and descriptions thereof may be omitted.

First, the thermal image sensor 21 acquires a human thermal image G1 (step S21). The estimation unit 3 calculates the amount of heat released by the person based on the thermal image G1 acquired by the thermal image sensor 21 (step S22). Next, the estimation unit 3 estimates the person's thermal sensation based on the amount of heat released by the person (step S23). Specifically, the estimation unit 3 estimates the thermal sensation from the amount of heat dissipation based on the predetermined relationship illustrated in the third embodiment.

Then, the estimation unit 3 estimates the degree of drowsiness of the person from the thermal sensation based on the relationship between the thermal sensation and the degree of drowsiness (step S24). After that, the notification unit 4 notifies the surroundings of the degree of drowsiness of each individual estimated by the estimation unit 3 (step S25).

According to the present embodiment, the estimating unit 3 estimates the degree of drowsiness of the person based on the thermal sensation calculated from the amount of heat released by the person. is possible.

Also, here, the degree of drowsiness of the person P1 is calculated by obtaining the heat radiation amount of the corresponding person P1 from the thermal image G1. can individually estimate the degree of drowsiness of each person based on the amount of heat released by a plurality of persons.

(Embodiment 4)
In the first embodiment, the case of estimating the degree of drowsiness from the information about the person's heat acquired by the sensor 2 has been exemplified and explained. In this fourth embodiment, a case will be described in which the degree of drowsiness is estimated from the surrounding environment of the person acquired by the sensor 2a. It should be noted that, in the following description, portions equivalent to those of the first embodiment are denoted by the same reference numerals, and descriptions thereof may be omitted.

FIG. 11 is a block diagram showing a functional configuration of a drowsiness tendency estimation device 1A according to Embodiment 4. As shown in FIG. Specifically, FIG. 11 is a diagram corresponding to FIG.

As shown in FIG. 11, the sensor 2a of the drowsiness estimation device 1A is a sensor that detects a person's surrounding environment. In this embodiment, the sensor 2a includes an illuminance sensor 22 that detects the illuminance around the person as the surrounding environment of the person.

FIG. 12 is a schematic diagram showing an example of an installation state of the illuminance sensor 22 according to the embodiment. Specifically, FIG. 12 is a diagram corresponding to FIG. As shown in FIG. 12, a plurality of persons P4 and P5 exist in another space partitioned by walls W. As shown in FIG. Each space need not be completely compartmentalized. Each space is illuminated by external light from a window (not shown) and illumination light from a lighting device (not shown). The illuminance sensor 22 is installed on the desk 150 in each space. Thereby, each illuminance sensor 22 detects the illuminance in each space. That is, each illuminance sensor 22 can detect the illuminance around each of the persons P4 and P5.

FIG. 13 is a graph showing the relationship between the degree of drowsiness and illuminance. As shown in FIG. 13, when the illuminance is lower than about 40 lux, the degree of drowsiness is stable at a high level. On the other hand, when the illuminance is higher than about 200 lux, the drowsiness tendency is low and stable. When the illuminance increases from about 40 lux to about 200 lux, the degree of drowsiness is sharply decreased as the illuminance increases.

The estimation unit 3 estimates the degree of drowsiness from the surrounding illuminance obtained by the sensor 2a, based on the relationship between the degree of drowsiness and the illuminance shown in FIG.

According to this embodiment, by detecting the illuminance around the persons P4 and P5, it is possible to estimate the degree of drowsiness of the persons P4 and P5 for each individual.

(Embodiment 5)
In the above-described Embodiment 4, the case of estimating the degree of drowsiness on the basis of the illuminance, which is one of the surrounding environments of a person, has been exemplified and explained. In this fifth embodiment, a case will be described in which the degree of drowsiness is estimated based on the concentration of the gaseous component around the person, which is one of the surrounding environments of the person. It should be noted that, in the following description, portions equivalent to those of the first embodiment are denoted by the same reference numerals, and descriptions thereof may be omitted.

FIG. 14 is a block diagram showing a functional configuration of a drowsiness tendency estimation device 1B according to Embodiment 5. As shown in FIG. Specifically, FIG. 14 is a diagram corresponding to FIG.

As shown in FIG. 14, the sensor 2b of the drowsiness estimating apparatus 1B is a sensor that detects a person's surrounding environment. In the present embodiment, the sensor 2b includes a gas sensor 23 that detects the concentration of gaseous components around the person as the surrounding environment of the person. The gas sensor 23 is, for example, a gas sensor that detects the concentration of at least one of carbon dioxide and oxygen. Note that the gas sensor 23 may be installed so as to be able to individually detect the concentration of the gas component in each compartmentalized space. Note that each space does not have to be completely compartmentalized.

Here, in the surrounding environment of a person, when the concentration of carbon dioxide increases, the degree of drowsiness tends to increase. Similarly, the lower the concentration of oxygen, the higher the drowsiness tends to be. Based on this relationship, the estimation unit 3 estimates the degree of drowsiness from the concentrations of the surrounding gas components obtained by the sensor 2b.

According to this embodiment, it is possible to estimate the degree of drowsiness of the person for each individual by detecting the concentration of the gas component around the person.

The gas sensor 23 may be a gas sensor capable of detecting the concentration of a plurality of gaseous components, or may be a sensor capable of detecting the concentration of a specific gaseous component such as an oxygen sensor or a carbon dioxide sensor. .

(Embodiment 6)
In the first embodiment, the case where the drowsiness estimating device 1 estimates only the degree of drowsiness has been exemplified. In this sixth embodiment, a case will be described where the drowsiness tendency estimation device 1C estimates the degree of drowsiness tendency and drowsiness. It should be noted that, in the following description, portions equivalent to those of the first embodiment are denoted by the same reference numerals, and descriptions thereof may be omitted.

FIG. 15 is a block diagram showing a functional configuration of a drowsiness tendency estimation device 1C according to Embodiment 6. As shown in FIG. As shown in FIG. 15, a drowsiness estimating device 1C has a configuration obtained by adding an imaging unit 30, a drowsiness estimating unit 40, and a drowsiness predicting unit 50 to the drowsiness estimating device 1 of the first embodiment. ing.

The imaging unit 30 is a camera for imaging the face of the person P1. Examples of the imaging unit 30 include a camera using a CMOS (Complementary Metal Oxide Semiconductor) image sensor, a camera using a CCD (Charge Coupled Device) image sensor, and the like.

The sleepiness estimation unit 40 detects a sleepiness level indicating the degree of sleepiness of the person P1. For example, the drowsiness estimation unit 40 has an interface for acquiring a moving image including the person P1 captured by the imaging unit 30 connected to the drowsiness estimation unit 40, and detects the drowsiness level of the person P1 from the moving image. . The sleepiness estimation unit 40 outputs the sleepiness level of the person P<b>1 to the sleepiness prediction unit 50 . A method for detecting the drowsiness level of the person P1 is not particularly limited. For example, the drowsiness level can be detected from moving image information of the face of the person P1. Specifically, the drowsiness level is estimated from the movement of blinks included in the moving image information of the face of the person P1. It can be estimated that the drowsiness level is low when the blinking period of the person P1 is stable, and the drowsiness level is high when the blinking period of the person P1 is slow and the blinking period is short and frequent.

The sleepiness prediction unit 50 predicts the future sleepiness level of the person P1 based on the sleepiness degree estimated by the estimation unit 3 and the sleepiness level estimated by the sleepiness estimation unit 40 . For example, if the degree of drowsiness of the person P1 is high, the drowsiness prediction unit 50 predicts the future drowsiness level by increasing the current drowsiness level of the person P1 to a relatively high level. On the other hand, when the degree of drowsiness of the person P1 is low, the drowsiness prediction unit 50 predicts that the person P1's current drowsiness level is lowered or the current drowsiness level is slightly raised, and is used in the future. Predict as sleepiness level. The sleepiness prediction unit 50 outputs the predicted sleepiness level to the notification unit 4 . As a result, the notification unit 4 notifies the predicted future sleepiness level of the person P1.

Here, another example of sleepiness prediction method will be described. Based on the thermal image G<b>1 acquired by the thermal image sensor 21 , the estimation unit 3 calculates the amount of heat released by the photographed person. The estimating unit 3 stores in advance the drowsiness level fluctuation amount after a predetermined time corresponding to the heat release amount. For example, FIG. 16 shows the drowsiness level fluctuation amount after a predetermined time when the amount of heat released by a person is 33 W/m ² . In addition to the relationship illustrated in FIG. 16, the estimating unit 3 stores in advance the drowsiness level fluctuation amount after a predetermined time according to each heat release amount.

Then, assuming that the amount of heat released by the person calculated by the estimation unit 3 is 33 W/m ² , the estimation unit 3 predicts the amount of change in the drowsiness level after a predetermined time based on the graph shown in FIG. 16 . That is, the estimation unit 3 estimates that the sleepiness level will increase by about 1.5 after about 5 minutes, and will increase by about 2.3 after about 10 minutes. Here, the drowsiness level is represented by five levels, and the higher the value, the stronger the drowsiness. By doing so, it is possible to predict how the subsequent sleepiness level will fluctuate depending on the heat release amount.

Here, the case where the amount of heat dissipation is 33 W/m ² has been described, but if the sleepiness level fluctuation amount after a predetermined time for other heat dissipation is also stored in the estimation unit 3, it will drowsiness level fluctuation amount can be estimated. For example, in a colder environment, that is ^, when the amount of heat released by a person increases (for example, the amount of heat released is 50 W/m ² ), as shown in FIG. The amount of change in sleepiness level is small. From this, it is estimated that the amount of change in sleepiness level is relatively small over time. For example, when driving a car, it is possible to display how sleepy you will be at which point on the route to the destination set on the car navigation system, etc., based on the estimated arrival time on each route. It is possible. The driver can refer to this display and consider where to take a break. Of course, based on this information, the car navigation system may notify the driver to take a break or the like.

Also, here, it has been described that the amount of change in drowsiness after a predetermined period of time is estimated based on the amount of heat release, but of course the amount of heat release may not be used, and the ambient temperature, for example, may be used. People are more likely to feel sleepy in a slightly warm environment with an ambient temperature of about 25°C than in a low temperature environment with an ambient temperature of 15°C or less. Therefore, by measuring in advance the amount of change in drowsiness after a predetermined time at each temperature, it is possible to estimate the drowsiness after a predetermined time according to the outside temperature. Of course, if there are factors other than the ambient temperature that affect a person's drowsiness, by measuring the amount of change in drowsiness after a predetermined time under each condition in advance based on that, a predetermined amount of sleepiness can be determined according to each condition. Drowsiness after hours can be estimated.

In addition, when heat radiation is used as a factor that affects human drowsiness, it is known that the heat radiation has a correlation that does not depend on the human thermal sensation and the amount of clothing. It has the advantage of being able to estimate drowsiness after a predetermined period of time regardless of light clothing.

In addition, although it has been explained here that drowsiness is predicted based on the amount of heat released from the thermal image, the estimating unit 3 can also use an illuminance sensor or a gas sensor to calculate the amount of change in the drowsiness level after a predetermined time. may be stored in advance, and the amount of change in sleepiness level after a predetermined time period may be estimated based on the illuminance and gas concentration. For example, in the case of illuminance, it is difficult for people to become sleepy when the surroundings are bright, and relatively easy for people to become sleepy when the surroundings are dark. Especially when driving an automobile, it has the advantage of being able to accurately predict the transition of a person's drowsiness based on the illuminance at that time.

On the other hand, if the gas is carbon dioxide, for example, it is because when the concentration of carbon dioxide is high, people tend to become sleepy, and when the concentration is low, people do not easily become sleepy. This has the advantage of being able to accurately predict the drowsiness of a person from the transition of the carbon dioxide concentration when the carbon dioxide gas rises due to internal air circulation during automobile driving.

It should be noted that the drowsiness prediction unit 50 can also predict drowsiness using the amount of drowsiness level fluctuation after a predetermined time according to the amount of heat released.

The drowsiness estimation unit 40 and the drowsiness prediction unit 50 are realized by, for example, a CPU and a control program stored in a storage unit communicable with the CPU, like the estimation unit 3 .

As described above, according to the present embodiment, the drowsiness estimating apparatus 1C predicts the future drowsiness level based on the current drowsiness level of the person P1 and the degree of drowsiness. , this future sleepiness level can be reflected in future sleepiness measures.

In this embodiment, the case of estimating the current drowsiness level from a moving image including the person P1 has been exemplified. However, any method may be used to estimate the sleepiness level. For example, the drowsiness level can be estimated using the heart rate, skin conductance, skin temperature, electroencephalogram, etc. of the person P1.

In the method using the heartbeat, for example, the sympathetic nerve/parasympathetic nerve (LF/HF) may be obtained from the interval between the R waves of the heartbeat (RR interval) to estimate the drowsiness level. LF/HF tends to be lower when a person is sleepy.

In the method using the skin conductance, for example, the drowsiness level may be estimated by obtaining the amount of mental perspiration from the skin conductance. Mental perspiration tends to decrease when a person becomes sleepy.

In the method using the skin temperature, the drowsiness level can be estimated from the peripheral skin temperature such as fingertips. Peripheral skin temperature tends to rise when a person is sleepy.

In the method using electroencephalograms, for example, the drowsiness level may be estimated from the alpha wave amplitude or the alpha wave ratio. The alpha wave amplitude and alpha wave ratio tend to increase when a person becomes sleepy.

(Embodiment 7)
[Awakening induction system]
In this seventh embodiment, a description will be given of a case in which a device for estimating the tendency to become drowsy is employed in a wakefulness induction system. Here, a case where the drowsiness estimating apparatus 1 according to Embodiment 1 is adopted in the awakening guidance system will be described, but the drowsiness estimating apparatus of other embodiments may be adopted in the awakening guidance system. may Arousal induction systems are installed, for example, in vehicles such as automobiles and indoors such as offices.

FIG. 18 is a block diagram showing a functional configuration of wakefulness induction system 100 according to Embodiment 7. As shown in FIG. As shown in FIG. 18, the awakening guidance system 100 includes a drowsiness estimating device 1 and a device 200 for changing the surrounding environment of a person P1.

Control device 110 controls equipment 200 based on the degree of drowsiness estimated by drowsiness estimating device 1 to induce awakening of persons P1, P2, and P3. Specifically, control device 110 is communicably connected to drowsiness estimation device 1 and device 200 . The control device 110 includes a CPU, a RAM, and a ROM. The CPU develops a control program stored in the ROM into the RAM and executes it, thereby controlling the device 200 based on the degree of drowsiness. do. For example, the control device 110 controls the device 200 in the normal mode when the degree of drowsiness is less than or equal to a predetermined value, and controls the device 200 in the normal mode when the degree of drowsiness exceeds the predetermined value. Control the device 200 in guidance mode. Here, the predetermined value is a threshold value for operating the device 200 in the awakening induction mode, and may be arbitrarily changed by the user.

The device 200 includes, for example, a lighting device 210, a sound device 220, a vibration device 230, and an air conditioner 240.

The illumination device 210 can be dimmed under the control of the control device 110 . Lighting device 210 performs illumination with a higher wakefulness-inducing effect in the wakefulness-inducing mode than in the normal mode. Specifically, in the awakening induction mode, lighting device 210 can induce awakening of person P1 by emitting brighter light than in the normal mode. In addition, in the awakening induction mode, the first method of inducing the awakening of the person P1 by increasing the amount of blue light contained in the light compared to the normal mode, or the pulse light with a duty ratio lower than that in the normal mode is used to induce the awakening of the person P1. It is also possible to employ a second method of guidance.

Specifically, in the first method, lighting device 210 may irradiate person P1 with light having a peak wavelength in the range of 400 nm to 500 nm. Thereby, the awakening of the person P1 can be efficiently induced.

In addition, in the second method, since the awakening of the person P1 is induced by pulsed light with a duty ratio lower than that in the normal mode, for example, when the awakening guidance system 100 is provided in a vehicle, the person P1 can be awakened while driving even at night. Arousal can be induced while preventing P1's face from shining and conspicuous. In particular, in the second method, lighting device 210 may emit pulsed light with a duty ratio of 0.00001 or more and 0.1 or less at a frequency of 0.1 Hz or more and 1 Hz or less (first condition). By irradiating the person P1 with such light, wakefulness can be induced more efficiently. Also in this second method, lighting device 210 may irradiate person P1 with light having a peak wavelength in the range of 400 nm or more and 500 nm or less.

The audio device 220 can adjust the output sound based on the control of the control device 110 . The sound device 220 outputs a sound having a higher wakefulness-inducing effect in the wakefulness-inducing mode than in the normal mode. Sounds with a high wakefulness-inducing effect include making the volume higher than in the normal mode and playing music with a high wakefulness-inducing effect.

In addition, when the acoustic device 220 is capable of outputting sounds with different frequencies on the left and right sides of the person P1, the acoustic device 220 makes a difference in the frequencies of the sounds on the left and right within a range of 30 Hz or less in the awakening induction mode. (second condition). If there is a difference in frequency between the left and right sounds in this way, it is possible to induce awakening of the person P1 efficiently.

Vibration device 230 applies vibration to person P1 under the control of control device 110 . Vibration device 230 includes a vibration actuator, a vibration damper, and the like. Vibration device 230 is non-vibrating in the normal mode and vibrates in the wake-inducing mode. Specifically, the vibration device 230 preferably generates vibration in a frequency band that stimulates the muscle spindles of the person P1 in the wakefulness induction mode (third condition). When muscle spindles are stimulated by vibration, the brainstem reticular activation system in the brain is activated. Since the brainstem reticular activation system is involved in arousal of a person, activation of the brainstem reticular activation system induces awakening of the person P1.

Further, examples of places where the vibrating device 230 is installed in the vehicle include a seat and a steering wheel. Further, examples of places in the room where the vibrating device 230 is installed include a chair, a writing instrument, an operating device (a mouse, a keyboard, etc.), and the like.

The air conditioner 240 performs air conditioning under the control of the control device 110 . The air conditioner 240 performs air conditioning with a higher wakefulness-inducing effect in the wakefulness-inducing mode than in the normal mode. Specifically, in the awakening induction mode, the air conditioner 240 can induce the awakening of the person P1 by making the temperature lower than in the normal mode. In the awakening induction mode, the air conditioner 240 may induce the awakening of the person P1 by blowing air on the person P1 to lower the sensible temperature. Furthermore, the air conditioner 240 may not only lower the temperature, but also raise and lower the temperature at predetermined time intervals to induce awakening of the person P1. In this case, the time interval should be 5 minutes or more and 60 minutes or less, and the range of temperature increase/decrease should be 2° C. or more and 15° C. or less.

As described above, according to the present embodiment, control device 110 controls lighting device 210 to induce awakening of person P1.

In addition, at the time of wakefulness induction, pulsed light with a duty ratio of 0.00001 or more and 0.1 or less is emitted from the lighting device 210 at a frequency of 0.1 Hz or more and 1 Hz or less, so that wakefulness can be induced efficiently. can be done.

In addition, the controller 110 controls the acoustic device 220 to induce wakefulness of the person.

In addition, during wakefulness induction, since the difference in sound frequency between the left and right sound devices 220 is 30 Hz or less, wakefulness induction can be performed efficiently.

In addition, by controlling the vibration device 230 by the control device 110, it is possible to induce awakening of the person.

In addition, at the time of wakefulness induction, since the vibrating device 230 generates vibration in a frequency band that stimulates the muscle spindles of the person P1, wakefulness can be induced efficiently.

In addition, by controlling the air conditioner 240 by the control device 110, it is possible to induce awakening of the person.

Note that in the present embodiment, the device 200 (the lighting device 210, the sound device 220, the vibrating device 230, and the air conditioner 240) is switched to the awakening induction mode according to the degree of drowsiness estimated by the drowsiness ease estimation device 1. The case where it operates with is illustrated. However, the device 200 may operate in the alertness induction mode without interlocking with the drowsiness tendency estimation device 1 . For example, the device 200 may operate in the awakening induction mode by being operated individually by a person. No matter what kind of situation the person existing around the device 200 is in (no drowsiness, drowsiness, high drowsiness, low drowsiness, etc.),
It is possible to forcibly induce wakefulness. In particular, the first condition, the second condition, and the third condition described above are preferable because wakefulness induction can be performed efficiently. In this way, in the wakefulness guidance system that induces wakefulness without considering the degree of drowsiness, the drowsiness estimating device 1 may be omitted.

Further, when the drowsiness estimating apparatus 1C according to Embodiment 6 is employed in a wakefulness induction system, the operation of the device 200 may be controlled based on the predicted future drowsiness level.

(Embodiment 8)
In the above-described seventh embodiment, the case where control device 110 controls device 200 based on the degree of drowsiness has been exemplified. In this seventh embodiment, a case will be described in which control device 110 controls device 200 based on the degree of drowsiness and the degree of comfort of person P1. It should be noted that, in the following description, portions equivalent to those of the eighth embodiment may be given the same reference numerals and descriptions thereof may be omitted.

In the eighth embodiment, the estimation unit 3 also estimates the degree of comfort of the person P1 from the thermal image G1 acquired by the thermal image sensor 21 .

FIG. 19 is a graph showing the relationship between the degree of comfort of the person P1 and the heat release amount. This graph summarizes the results of evaluating the degree of comfort while determining the amount of heat released by the subject under each thermal condition by changing the amount of clothing worn by the subject and the environmental temperature. Specifically, subjects were evaluated for the degree of drowsiness under five thermal conditions. Thermal conditions 1 to 5 are the same as in the first embodiment. Subjects evaluated the degree of comfort in each thermal condition on a 5-point scale. When the degree of comfort is 0, it is a state in which neither comfort nor discomfort can be determined. When the degree of comfort is positive, it indicates that the degree of comfort increases as the level increases. When the degree of comfort is negative, it indicates that the lower the level, the more uncomfortable. An average value of the evaluation results for a plurality of persons was obtained, and the average value and the amount of heat release were summarized in the graph of FIG. 19 to obtain an approximate curve L1. Based on this approximated curve L1, the estimator 3 can estimate the comfort level from the amount of heat released.

When controlling the device 200 in the awakening induction mode, the control device 110 also uses the comfort level estimated by the estimation unit 3 to control the operation of the device 200 . Specifically, control device 110 monitors the comfort level estimated by estimation unit 3, and controls air conditioner 240 so that the comfort level is greater than a predetermined value.

As described above, according to the present embodiment, control device 110 controls device 200 based on the degree of comfort and the degree of drowsiness detected by device 1 for estimating the susceptibility to drowsiness. It is possible to induce awakening while reproducing the environment that feels like.

(Embodiment 9)
In the eighth embodiment described above, when the estimation unit 3 estimates the degree of drowsiness and the degree of comfort based on the amount of heat released, The case where it functions also as a degree detection apparatus was illustrated. In this ninth embodiment, a description will be given of a case in which the awakening guidance system has a dedicated comfort level estimation unit that detects the comfort level of person P1. It should be noted that, in the following description, parts equivalent to those of the sixth and seventh embodiments are denoted by the same reference numerals, and descriptions thereof may be omitted.

FIG. 20 is a block diagram showing the functional configuration of a wakefulness induction system 100D according to the ninth embodiment. As shown in FIG. 20, the wakefulness guidance system 100D includes a sleepiness estimation device 1C, a device 200 for changing the surrounding environment of the person P1, and a comfort level estimation unit 300 for estimating the comfort level of the person P1. I have. In the wakefulness induction system 100D, the comfort estimation unit 300 calculates the amount of heat radiation from the person P1 based on the thermal image G1 including the person P1 measured by the thermal image sensor 21, and calculates the comfort level of the person P1 based on the graph of FIG. Calculate degrees. Furthermore, from the future drowsiness level predicted by the drowsiness estimating device 1C in FIG. Levels can be lowered as much as possible. For example, the air conditioner 240 may be controlled so that the comfort level is greater than zero. In this case, by controlling the amount of heat dissipation to be as large as possible within a range that does not exceed 46 W/m ² , it is possible to realize an environment in which it is difficult to become drowsy while maintaining comfort. Of course, the predetermined value of the comfort level may not be 0, and may be set by the user. For example, if the comfort level is set to be greater than -1, the arousal level can be increased even if the comfort level decreases slightly, and if the comfort level is set to be greater than 0, the comfort level Arousal can be increased as much as possible while maintaining

In addition, although the device 200 is controlled by the control device 110 based on the future sleepiness and comfort level here, the current sleepiness estimated by the sleepiness estimation unit 40 and the comfort level estimated by the comfort level estimation unit 300 are The device 200 may also be controlled based on this. By doing so, it is possible to control the present sleepiness to be as low as possible while maintaining the comfort level.

(Other embodiments)
As described above, the sleepiness estimation device and the awakening induction system according to the present disclosure have been described based on the above embodiments, but the present disclosure is not limited to the above embodiments. For example, it is realized by arbitrarily combining the components and functions of each embodiment without departing from the scope of the present disclosure, or by applying various modifications that a person skilled in the art can think of for each embodiment. Forms are also included in this disclosure.

For example, in Embodiments 1 to 5 above, the thermal image sensor 21, the illuminance sensor 22 and the gas sensor 23 are individually provided in the sensors 2, 2a and 2b, but the thermal image sensor, the illuminance sensor and the gas sensor may be provided in the sensor. This makes it possible to estimate the degree of drowsiness in a composite manner using the detection results of each sensor.

In Embodiments 6 and 7 above, the awakening induction system 100 includes a plurality of devices (the lighting device 210, the sound device 220, the vibration device 230, and the air conditioner 240) for changing the surrounding environment of the person. Although the case has been exemplified, the wakefulness induction system only needs to have at least one device for changing the surrounding environment of a person. In addition, the device for changing the surrounding environment of a person may be other than the lighting device 210, the sound device 220, the vibration device 230, and the air conditioner 240, as long as it can induce the awakening of the person by changing the surrounding environment. It is also possible to use instruments.

Further, for example, the present disclosure can be implemented not only as a drowsiness estimating device or an alertness-inducing system, but also a program including, as steps, processes performed by each component of the drowsiness-easiness estimating device or the alertness-inducing system, and its It can also be realized as a computer-readable recording medium recording the program. The program may be pre-recorded on a recording medium, or may be supplied to the recording medium via a wide area network including the Internet.

That is, the general or specific aspects described above may be implemented in a system, device, integrated circuit, computer program or computer readable recording medium, and any of the system, device, integrated circuit, computer program and recording medium may be implemented. may be implemented in any combination.

INDUSTRIAL APPLICABILITY The present disclosure is used for a system or the like that operates a device or the like that induces human awakening according to the current state of the person.

1, 1A, 1B, 1C estimating devices 2, 2a, 2b sensor 3 estimating unit 4 reporting unit 21 thermal image sensor 22 illuminance sensor 23 gas sensor 30 imaging unit 40 drowsiness estimating unit 50 drowsiness predicting unit 100 awakening induction system 110 control device 150 desk 200 Equipment 210 Lighting device 220 Acoustic device 230 Vibration device 240 Air conditioner 300 Comfort level estimation units G1, G2, G3 Thermal images L, L1 Approximate curves P1, P2, P3, P4, P5 Person R Imaging range

Claims (13)

an estimating unit for estimating, for each individual, the degree of sleepiness of a specific person out of the plurality of people , based on information about the physiological conditions of the plurality of people;
a control device that controls a device for changing the surrounding environment of the specific person based on the degree of drowsiness estimated by the estimation unit;
A comfort level detection device that detects the comfort level of the specific person,
The control device controls the equipment so that the specific person's degree of comfort based on temperature and the degree of drowsiness of the person satisfy predetermined conditions.
awakening system. wherein the physiological state includes the heartbeat of the specific person;
Arousal induction system according to claim 1. The degree of drowsiness is estimated by obtaining the sympathetic/parasympathetic nerves from the interval between the R waves of the heartbeat of the specific person,
Arousal induction system according to claim 2. The physiological state includes the amount of perspiration of the specific person,
A wakefulness induction system according to any one of claims 1 to 3. The degree of drowsiness is estimated by obtaining the amount of mental perspiration from the skin conductance of the specific person,
A wakefulness induction system according to claim 4. the physiological state includes skin temperature of the specific person;
A wakefulness induction system according to any one of claims 1 to 5. The degree of drowsiness is estimated by obtaining the skin temperature of the peripheral part of the specific person,
Arousal induction system according to claim 6. the device comprises a lighting device;
A wakefulness induction system according to any one of claims 1 to 7. The illumination device emits pulsed light with a frequency of 0.1 Hz or more and 1 Hz or less and a duty ratio of 0.00001 or more and 0.1 or less during awakening induction.
Arousal induction system according to claim 8. the device comprises an acoustic device;
Arousal induction system according to any one of claims 1 to 9. The acoustic device can output sounds with different frequencies on the left and right sides of the specific person, and during wakefulness induction, the sound frequencies on the left and right sides are different within a range of 30 Hz or less.
Arousal induction system according to claim 10. the equipment comprises an air conditioner;
Arousal induction system according to any one of claims 1 to 11. The air conditioner sets the temperature lower than normal during wakefulness induction, and raises and lowers the temperature within a range of 2° C. or higher and 15° C. or lower at intervals of 5 minutes or more and 60 minutes or less.
Arousal induction system according to claim 12.

Images