Sleep Assist System

Abstract

The sleep assistance system (1A) includes an information processing device (21) and multiple sensors (4). A first sensor (42, 43) measures at least one of body movement data (532) and vital sign data (533). A second sensor (41) measures at least one of temperature data (530) and humidity data (531) inside clothing. A third sensor (44) measures at least one of ambient temperature data (534) and ambient humidity data (535). The information processing device (21) includes: a sleep parameter calculation unit (63) that calculates at least one sleep parameter (536) using at least one of the body movement data (532) and the vital signs data (533); a temperature and humidity factor calculation unit (64) that calculates multiple temperature and humidity factors (537) using at least one of the clothing temperature data (530), the clothing humidity data (531), the ambient temperature data (534), and the ambient humidity data (535); and an analysis unit (65) that determines one or more combinations of sleep parameters (536) and temperature and humidity factors (537) that are correlated.

Description

Technical Field

[0001] This invention relates to sleep aid systems. Background Technology

[0002] For infants and toddlers, quality sleep is closely related to healthy physical and mental development. However, in recent years, more and more infants and toddlers have experienced sleep problems: difficulty falling asleep even when in bed, insufficient sleep, and inability to fall asleep in a relaxed state.

[0003] To achieve quality sleep, it is necessary to understand the current quality of sleep and make improvements as needed.

[0004] Various sensors and applications have been developed as a means of measuring sleep quality. These sensors and applications, for example, are designed to measure the quality of sleep in adults.

[0005] Prior art literature

[0006] Patent documents

[0007] Patent Document 1: Japanese Patent Application Publication No. 2020-16528

[0008] Patent Document 2: Japanese Patent No. 7125223

[0009] Patent Document 3: Japanese Patent Application Publication No. 2016-123436 Summary of the Invention

[0010] -The problem the invention aims to solve-

[0011] Infant sleep differs from adult sleep in terms of quantity, quality, and pattern. Furthermore, infant sleep patterns change as they grow. Therefore, it is necessary to develop new features that can improve the quality of infant sleep.

[0012] Furthermore, the sleep patterns of caregivers with language communication difficulties, similar to those of infants and young children, may differ from those of healthy individuals in terms of quantity, quality, and frequency. Therefore, it is necessary to develop new features to improve the sleep quality of caregivers.

[0013] The present invention provides a sleep aid system that can solve the above-mentioned problems.

[0014] -Methods for solving problems-

[0015] This invention relates to a sleep assistance system comprising an information processing device and multiple sensors. The multiple sensors include at least one of a first sensor, a second sensor, and a third sensor. The first sensor measures at least one of body movement data representing the subject's body movement and vital sign data representing the subject's vital signs. The second sensor measures at least one of clothing temperature data representing the temperature inside the clothing worn by the subject and clothing humidity data representing the humidity inside the clothing. The third sensor measures at least one of the ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment. The information processing device includes a sleep parameter calculation unit, a temperature and humidity factor calculation unit, and an analysis unit. The sleep parameter calculation unit calculates at least one sleep parameter using at least one of the body movement data and the vital sign data. The temperature and humidity factor calculation unit calculates multiple temperature and humidity factors using at least one of the clothing temperature data, the clothing humidity data, the ambient temperature data, and the ambient humidity data. The analysis unit uses the at least one sleep parameter corresponding to a first period of sleep and the multiple temperature and humidity factors corresponding to the first period of sleep to determine one or more combinations of correlated sleep parameters and temperature and humidity factors.

[0016] This invention relates to an information processing device capable of acquiring data from multiple sensors. The multiple sensors include at least one of a first sensor, a second sensor, and a third sensor. The information processing device comprises a receiving unit, a sleep parameter calculation unit, a temperature and humidity factor calculation unit, and an analysis unit. The receiving unit receives, from the first sensor, at least one of body movement data representing the subject's body movement and vital sign data representing the subject's vital signs; from the second sensor, at least one of clothing temperature data representing the temperature inside the clothing worn by the subject and clothing humidity data representing the humidity inside the clothing; and from the third sensor, at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment. The sleep parameter calculation unit uses at least one of the body movement data and the vital sign data to calculate at least one sleep parameter. The temperature and humidity factor calculation unit uses at least any one of the clothing temperature data, the clothing humidity data, the ambient temperature data, and the ambient humidity data to calculate multiple temperature and humidity factors. The analysis unit uses at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period to determine one or more combinations of sleep parameters and temperature and humidity factors that are correlated.

[0017] This invention relates to a sleep-aiding method for controlling an information processing device capable of acquiring data from multiple sensors. The multiple sensors include at least one of a first sensor, a second sensor, and a third sensor. The sleep-aiding method receives, via the receiving unit of the information processing device, at least one of body movement data representing the subject's body movements and vital sign data representing the subject's vital signs from the first sensor. The sleep-aiding method receives, via the receiving unit of the information processing device, at least one of clothing temperature data representing the temperature inside the clothing worn by the subject and clothing humidity data representing the humidity inside the clothing from the second sensor. The sleep-aiding method receives, via the receiving unit of the information processing device, at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment from the third sensor. The sleep-aiding method calculates at least one sleep parameter using at least one of the body movement data and the vital sign data using the sleep parameter calculation unit of the information processing device. The sleep-aiding method calculates multiple temperature and humidity factors using at least one of the clothing temperature data, clothing humidity data, ambient temperature data, and ambient humidity data using the temperature and humidity factor calculation unit of the information processing device. The sleep assistance method, through the analysis unit of the information processing device, uses at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period to determine one or more combinations of related sleep parameters and temperature and humidity factors.

[0018] This invention is a program executed by a computer capable of acquiring data from multiple sensors. The multiple sensors include at least one of a first sensor, a second sensor, and a third sensor. The program causes the computer to perform the following steps: receiving from the first sensor at least one of body movement data representing the subject's body movement and vital sign data representing the subject's vital signs. The program causes the computer to perform the following steps: receiving from the second sensor at least one of clothing temperature data representing the temperature inside the clothing worn by the subject and clothing humidity data representing the humidity inside the clothing. The program causes the computer to perform the following steps: receiving from the third sensor at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment. The program causes the computer to perform the following steps: calculating at least one sleep parameter using at least one of the body movement data and the vital sign data. The program causes the computer to perform the following steps: calculating multiple temperature and humidity factors using at least one of the clothing temperature data, the clothing humidity data, the ambient temperature data, and the ambient humidity data. The program causes the computer to perform the step of determining one or more combinations of related sleep parameters and temperature and humidity factors using at least one sleep parameter corresponding to the first period of sleep and the plurality of temperature and humidity factors corresponding to the first period of sleep.

[0019] -Invention Effects-

[0020] According to the present invention, a sleep aid system that can solve the above-mentioned problems can be provided. Attached Figure Description

[0021] Figure 1 This is a conceptual diagram illustrating a structural example of the sleep aid system according to the first embodiment.

[0022] Figure 2 The sleep aid system according to the first embodiment includes a temperature and humidity sensor inside the clothing. Figure 2 (a) Top view, Figure 2 (b) sectional view and Figure 2 (c) Top view.

[0023] Figure 3 This is a block diagram illustrating an example of the system structure of the information processing device included in the sleep assistance system according to the first embodiment.

[0024] Figure 4 This is a block diagram illustrating an example of the functional structure of the information processing device included in the sleep assistance system according to the first embodiment.

[0025] Figure 5This is a diagram illustrating an example of the sleep parameters used in the sleep assistance system according to the first embodiment.

[0026] Figure 6 This is a diagram showing an example of the reference time for the total sleep time of infants and young children used in the sleep assistance system according to the first embodiment.

[0027] Figure 7 This is a diagram illustrating an example of the temperature and humidity factors used in the sleep aid system according to the first embodiment.

[0028] Figure 8 This is a diagram illustrating examples of sleep parameters and temperature and humidity factors used during a specific period in the sleep assistance system according to the first embodiment.

[0029] Figure 9 This is a diagram illustrating an example of the priority order of sleep parameters in the sleep evaluation system according to the first embodiment.

[0030] Figure 10 This is a graph showing an example of the correlation coefficients between environmental parameters and temperature and humidity factors calculated in the sleep assistance system according to the first embodiment.

[0031] Figure 11A This is a graph representing an example of the comfort range calculated based on the regression line of activity level per unit time and average ambient humidity in the sleep assistance system according to the first embodiment.

[0032] Figure 11B This is a graph illustrating an example of the comfort range calculated by the regression line based on the wake-up time and average temperature inside clothing in the sleep aid system according to the first embodiment.

[0033] Figure 11C This is a graph representing an example of the comfort range calculated based on the regression line of bedtime and average ambient temperature in the sleep assistance system according to the first embodiment.

[0034] Figure 11D This is a graph illustrating an example of the comfort range calculated based on the regression line of wake-up time and average ambient temperature in the sleep assistance system according to the first embodiment.

[0035] Figure 11E This is a graph representing an example of the comfort range calculated based on the regression line of the number of awakenings and the average ambient temperature in the sleep aid system according to the first embodiment.

[0036] Figure 12 This is a diagram illustrating an example of the structure of a comfort range table used in the sleep aid system according to the first embodiment.

[0037] Figure 13A This is a graph representing an example of the comfort range calculated based on the regression curves of bedtime and average ambient temperature in the sleep assistance system according to the first embodiment.

[0038] Figure 13B This is a graph representing an example of the comfort range calculated based on the regression curves of bedtime and average ambient humidity in the sleep assistance system according to the first embodiment.

[0039] Figure 14 This is a diagram illustrating an example of behavioral data used in the sleep evaluation system according to the first embodiment.

[0040] Figure 15 This is a diagram illustrating an example of the judgment results of the sleep quality of infants and young children using behavioral data in the sleep evaluation system according to the first embodiment.

[0041] Figure 16 This is a diagram showing a first example of a comfort judgment table used in the sleep assistance system according to the first embodiment.

[0042] Figure 17 This is a diagram showing a second example of a comfort judgment table used in the sleep aid system according to the first embodiment.

[0043] Figure 18 This is a diagram showing a third example of a comfort judgment table used in the sleep assistance system according to the first embodiment.

[0044] Figure 19A This is a graph representing an example of the comfort range calculated in the sleep aid system according to the first embodiment, based on the regression line of the first infant's activity level per unit time and the average ambient humidity.

[0045] Figure 19B This is a graph representing an example of the comfort range calculated in the sleep assistance system according to the first embodiment, based on the regression line of the second infant's activity level per unit time and the average ambient humidity.

[0046] Figure 20 This is a flowchart illustrating an example of the data processing steps performed in the sleep aid system according to the first embodiment.

[0047] Figure 21 This is a flowchart illustrating an example of the steps involved in the correlation resolution processing performed in the sleep assistance system according to the first embodiment.

[0048] Figure 22This is a flowchart illustrating an example of the decision / notification processing steps performed in the sleep assistance system according to the first embodiment.

[0049] Figure 23 This is a conceptual diagram illustrating a structural example of the sleep aid system according to the second embodiment. Detailed Implementation

[0050] The embodiments will now be described with reference to the accompanying drawings.

[0051] (First Implementation)

[0052] First, refer to Figure 1 The structure of the sleep assistance system according to the first embodiment of the present invention will be described below. The sleep assistance system 1A is a system for assisting a user 31 who is undertaking childcare or caregiving for a subject 30. The sleep assistance system 1A, for example, provides the user 31 with information for improving the quality of the subject 30's sleep.

[0053] Subject 30 was an infant or a person being cared for. The person being cared for was, for example, someone with language communication difficulties requiring care. Subject 30 was wearing underwear or absorbent materials, such as disposable diapers or cloth diapers.

[0054] User 31 is the user who utilizes the sleep assistance system 1A. If subject 30 is an infant or young child, user 31 may be, for example, a family member of subject 30 or a caregiver at the childcare facility where subject 30 is being cared for. If subject 30 is a person being cared for, user 31 may be, for example, a family member of subject 30 or a caregiver at the nursing home where subject 30 resides. Here, the case of one user 31 is illustrated, but there may also be two or more users 31.

[0055] The following is a primary example of a sleep aid system 1A that provides information to the caregiver to improve the quality of the infant's sleep, when the subject 30 is an infant or toddler and the user 31 is a caregiver. The subject 30, who is an infant or toddler, is also referred to as infant 30. The user 31, who is a caregiver, is also referred to as caregiver 31. Furthermore, in the following description, by replacing infant 30 with a person being cared for and caregiver 31 with a caregiver, the same sleep aid system 1A that provides information to the caregiver to improve the quality of the person being cared for can also be implemented.

[0056] The structure of the sleep assistance system 1A will be described. The sleep assistance system 1A includes, for example, an information processing device 21 and multiple sensors 4.

[0057] Information processing device 21 is an information processing device used by childcare worker 31. Information processing device 21 can be implemented, for example, as an embedded system built into a portable information terminal, tablet computer, personal computer, or infant monitoring robot. Portable information terminals can be, for example, smartphones, mobile phones, or personal digital assistants (PDAs).

[0058] The information processing device 21 analyzes data related to the infant 30 and provides information (hereinafter also referred to as sleep aid information) to improve the sleep environment of the infant 30. The information processing device 21 provides the sleep aid information to the caregiver 31, for example, by displaying it on a screen.

[0059] Multiple sensors 4 are sensors used to measure the state of the infant 30. The multiple sensors 4 may include, for example, a communication unit for transmitting data (signals) including the measurement results to an external device. The communication unit transmits the data including the measurement results to the information processing device 21, for example, in real time. Various short-range wireless communication methods such as Bluetooth (registered trademark) or wireless LAN can be used as the communication method for the communication unit. Alternatively, the multiple sensors 4 may also include a storage unit that can be read by the information processing device 21. The storage unit stores data representing the measurement results. The data stored in the storage unit is transmitted via the communication unit, for example, through wireless communication, and read by the information processing device 21.

[0060] Multiple sensors 4, including, for example, a clothing temperature and humidity sensor 41, a body motion sensor 42, a vital signs sensor 43, and an ambient temperature and humidity sensor 44.

[0061] The clothing temperature and humidity sensor 41 is a sensor that measures (monitors) the temperature and humidity inside the clothing worn by the infant 30 at given time intervals. The clothing temperature and humidity sensor 41 can be installed, for example, on either the inside of the clothing worn by the infant 30 or on the outer surface of the absorbent material or underwear worn by the infant 30, allowing for easy removal and replacement. The clothing worn by the infant 30 is also referred to as the infant's clothes. Similarly, the absorbent material worn by the infant 30 is also referred to as the infant's absorbent material. The following primarily illustrates the case where the infant 30 is wearing an absorbent material. When installed on the outer surface of the absorbent material, the clothing temperature and humidity sensor 41 is installed on the absorbent material at the location covered by the clothing. When no clothing is worn over the absorbent material, it is preferably installed on underwear or the like, so that it becomes the inside of the clothing, rather than the outer surface of the absorbent material. "Inside the clothing" (or "the interior of the clothing") refers to the inside of the clothing or the outside of the absorbent material covered by the clothing. The internal temperature of the infant's clothing 30 (i.e., the temperature of the inside of the clothing or the outer surface of the absorbent material where the internal temperature and humidity sensor 41 is installed) is referred to as the internal temperature of the clothing. The internal humidity of the infant's clothing 30 (i.e., the humidity of the inside of the clothing or the outer surface of the absorbent material where the internal temperature and humidity sensor 41 is installed) is referred to as the internal humidity of the clothing.

[0062] The clothing interior temperature and humidity sensor 41 sends data representing a time series of clothing interior temperature and humidity to the information processing device 21. For example, the clothing interior temperature and humidity sensor 41 sends data representing a time series of clothing interior temperature and humidity within a unit period to the information processing device 21. A unit period may be, for example, 1 second, 10 seconds, or 1 minute. Alternatively, the measured data representing at least one of the clothing interior temperature and humidity can be sent to the information processing device 21 in real time, depending on whether the clothing interior temperature and humidity sensor 41 has detected at least one of them. The data representing the clothing interior temperature is also referred to as clothing interior temperature data. The clothing interior temperature data may also include information about the time when the corresponding clothing interior temperature was measured. The data representing the clothing interior humidity is also referred to as clothing interior humidity data. The clothing interior humidity data may also include information about the time when the corresponding clothing interior humidity was measured. For a specific structural example of the clothing interior temperature and humidity sensor 41, please refer to... Figure 2 To be discussed later.

[0063] The motion sensor 42 is a sensor that measures the body movements of the infant 30 at given time intervals. The motion sensor 42 can be a non-contact sensor or a contact sensor. A non-contact motion sensor 42 can be, for example, a millimeter-wave radar. The non-contact motion sensor 42 is, for example, positioned at a location where the infant 30 can be observed. This location could be any of a wall, pillar, ceiling, or furniture. A contact motion sensor 42 can be, for example, implemented using an accelerometer, a gyroscope, or a combination of both. The motion sensor 42 can be, for example, easily attached to the inside of the clothing worn by the infant 30 or the outer surface of absorbent material or underwear worn by the infant 30. The motion sensor 42 can also be a belt-shaped sensor. The belt-shaped motion sensor 42 is wrapped around the arm or leg of the infant 30. Alternatively, the motion sensor 42 can also be a sheet-like pressure sensor. A sheet-like motion sensor 42 is used to capture these movements as patterned changes in pressure applied to the motion sensor 42. The sheet-like motion sensor 42 is positioned under a lying infant 30. The infant 30's movements include waving of hands and feet, rolling over, etc. The infant 30's movements are expressed, for example, as activity level. Furthermore, the infant 30's activity level is expressed, for example, as the amount or intensity of activity based on at least a portion of the infant 30's body, or the cumulative value of the amount and intensity of activity. The amount and intensity of activity are determined, for example, based on accelerations measured in the X-axis, Y-axis, and Z-axis directions, respectively. The X-axis is, for example, the longitudinal direction of the infant 30's body (i.e., the up-down direction when standing). The Y-axis is the lateral direction of the infant 30's body (i.e., the left-right direction when standing). The Z-axis is a direction orthogonal to the aforementioned X-axis and Y-axis (i.e., the forward-backward direction when standing). The amount of activity is a value obtained by accumulating the instantaneous activity intensity over a fixed time period (e.g., 2 minutes).

[0064] The motion sensor 42 includes a communication unit that transmits data representing a time-series of the infant's (e.g., activity level) to the information processing device 21. The motion sensor 42 transmits data representing a time-series of motion within a unit period to the information processing device 21, for example, on a unit-per ...

[0065] The vital signs sensor 43 is a sensor that measures the vital signs of the infant 30 at given intervals. Vital signs include, for example, heart rate (including parameters calculated based on heart rate and heart rate variability), respiratory rate, and skin temperature. Skin temperature is, for example, the temperature of the infant 30's extremities (e.g., hands, feet). The vital signs sensor 43, like the motion sensor 42, is positioned relative to the infant 30. The vital signs sensor 43 can be a non-contact sensor or a contact sensor. A non-contact vital signs sensor 43 is, for example, a millimeter-wave radar. A contact vital signs sensor 43 is, for example, a wearable biosensor that measures heart rate, respiratory rate, and skin temperature.

[0066] The vital signs sensor 43 includes a communication unit that transmits data representing a time series of heart rate, respiratory rate, and skin temperature to the information processing device 21. The vital signs sensor 43 transmits data representing a time series of heart rate, respiratory rate, and skin temperature within a unit period to the information processing device 21, for example, on a unit period basis. Alternatively, it may transmit the measured data representing at least one of heart rate, respiratory rate, and skin temperature to the information processing device 21 in real time, depending on whether the vital signs sensor 43 has detected at least one of these parameters. The data representing heart rate, respiratory rate, and skin temperature is also referred to as vital signs data. The vital signs data may also include information about the time at which at least one of the corresponding heart rate, respiratory rate, and skin temperature was measured.

[0067] Alternatively, it can be implemented as a device that integrates two or more sensors obtained by arbitrarily combining the temperature and humidity sensor 41 inside the clothing, the body motion sensor 42, and the vital signs sensor 43.

[0068] The ambient temperature and humidity sensor 44 is a sensor that measures the temperature and humidity of the living environment in which the infant 30 is located at given times. The ambient temperature and humidity sensor 44 is not installed relative to the infant 30. More specifically, the ambient temperature and humidity sensor 44 is not installed on any of the infant 30's clothing or absorbent materials. The ambient temperature and humidity sensor 44 is, for example, located in the room where the infant 30 is located. The temperature of the living environment in which the infant 30 is located is referred to as the ambient temperature. The humidity of the living environment in which the infant 30 is located is referred to as the ambient humidity.

[0069] The ambient temperature and humidity sensor 44 includes a communication unit that transmits data representing a time series of ambient temperature and humidity to the information processing device 21. For example, the ambient temperature and humidity sensor 44 transmits data representing a time series of ambient temperature and humidity within a unit period to the information processing device 21 on a unit period basis. Alternatively, it may transmit measured data representing at least one of the ambient temperature and humidity to the information processing device 21 in real time, depending on whether the ambient temperature and humidity sensor 44 has measured at least one of them. The data representing the ambient temperature is also referred to as ambient temperature data. The ambient temperature data may also include information about the time when the corresponding ambient temperature was measured. The data representing the ambient humidity is also referred to as ambient humidity data. The ambient humidity data may also include information about the time when the corresponding ambient temperature was measured.

[0070] In addition, the multiple sensors 4 may also include a camera device 45.

[0071] The camera device 45 is a camera that generates dynamic image data of the infant 30. The camera device 45 may be, for example, an RGB camera, a monochrome camera, or a spectral camera. The dynamic image data includes multiple images of the infant 30 captured over a time series. These multiple images may be, for example, images showing the entire body of the infant 30. Alternatively, the multiple images may each be images showing only a part of the infant 30's body. The dynamic image data contains information about the time at which each of the multiple images was generated.

[0072] Camera device 45, for example, is positioned to film the infant 30. Camera device 45, for example, is mounted on any of a wall, pillar, ceiling, or furniture.

[0073] The camera device 45, for example, includes a communication unit for transmitting moving image data to an external device. This communication unit can, for example, communicate with the information processing device 21. The communication unit sends moving image data to the information processing device 21. The communication method used by the communication unit can be, for example, any short-range wireless communication method such as Bluetooth or wireless LAN.

[0074] Alternatively, the camera device 45 may also include a storage unit (i.e., a storage medium) that can be read by the information processing device 21. The storage unit stores moving image data. The moving image data stored in the storage unit is read by the information processing device 21, for example, via wireless communication or wired communication via a cable connecting the information processing device 21 and the camera device 45.

[0075] In addition, the sleep aid system 1A may also include an air conditioning unit 22.

[0076] Air conditioning unit 22 is a device that has the function of adjusting at least one of the temperature and humidity of the room where the infant 30 is located. Air conditioning unit 22 is, for example, an air conditioner, a dehumidifier, and a humidifier.

[0077] The air conditioning unit 22, for example, includes a communication unit that can receive instructions from the information processing device 21. The communication unit, for example, can communicate with the information processing device 21. The communication method used by the communication unit can be any communication method such as wireless LAN, wired LAN, Bluetooth, or infrared communication. The operation of the air conditioning unit 22 can be controlled by the information processing device 21. Specifically, the target temperature and target humidity set by the air conditioning unit 22 are changed according to the instructions sent from the information processing device 21 to the air conditioning unit 22. The air conditioning unit 22 operates so that the temperature and humidity (i.e., ambient temperature and ambient humidity) of the room where the infant 30 is located become the set target temperature and target humidity.

[0078] Figure 2 These are (a) top view, (b) sectional view and (c) bottom view of the temperature and humidity sensor 41 inside the clothing.

[0079] like Figure 2 As shown in (a), the temperature and humidity sensor 41 inside the clothing includes a first cover 411. The first cover 411 is a cover that covers the sensor part, etc. The first cover 411 is, for example, dome-shaped. When viewed from above, the first cover 411 appears, for example, circular.

[0080] Figure 2 (b) is Figure 2 The cross-sectional view along line II shown in (a) shows the temperature and humidity sensor 41 inside the clothing. In addition to the first cover 411, the temperature and humidity sensor 41 also includes, for example, a second cover 412, a temperature sensor unit 413, a humidity sensor unit 414, a communication unit 415, and a fastener 416.

[0081] The first cover 411 is located on the opposite side of the side that can contact the outer surface of the clothing or absorbent material of the infant 30 when the clothing temperature and humidity sensor 41 is installed relative to the infant 30.

[0082] The second cover 412 is a flat plate. When a temperature and humidity sensor 41 is installed inside the clothing relative to the infant 30, the second cover 412 has a side that can contact the outer surface of the infant 30's clothing or absorbent material. In this case, for example, the entire second cover 412 overlaps with the outer surface of the infant 30's clothing or absorbent material. The second cover 412 has an opening 417. By providing the opening 417, the temperature and humidity of the object overlapping with the second cover 412 (i.e., the infant 30) can be measured more accurately, and the influence of temperature and humidity from outside the object (e.g., outdoor air) can be reduced. Furthermore, the second cover 412 is connected to the first cover 411.

[0083] The space enclosed by the connected second cover 412 and the first cover 411 is a receiving space 418. A temperature sensor unit 413, a humidity sensor unit 414, and a communication unit 415 are disposed in the receiving space 418. In other words, the temperature sensor unit 413, the humidity sensor unit 414, and the communication unit 415, except for the portion corresponding to the opening 417, are covered by the connected second cover 412 and the first cover 411.

[0084] Temperature sensor 413 is a sensor unit that measures the ambient temperature. For example, a thermocouple or a thermistor can be used as temperature sensor 413. Temperature sensor 413 measures the temperature inside the clothing of the infant 30 through the opening 417 of the second cover 412.

[0085] The humidity sensor unit 414 is a sensor unit that measures the humidity in the vicinity at given intervals. For example, an electrostatic capacitive humidity sensor can be used as the humidity sensor unit 414. The humidity sensor unit 414 measures the humidity inside the clothing of the infant 30 through the opening 417 of the second cover 412.

[0086] A heat-insulating material may also be provided between the temperature sensor section 413, the humidity sensor section 414, and the first cover 411. Alternatively, a heat-insulating material may be provided between the temperature sensor section 413, the humidity sensor section 414, and the second cover 412 (with the opening 417 removed). Alternatively, the first cover 411 and the second cover 412 may be formed using a heat-insulating material. Examples of heat-insulating materials include plastics, ceramics, silicone resins, and polyurethane-based resins. The thermal conductivity of the heat-insulating material is 20 W / m•K or less, more preferably 1 W / m•K or less. With the heat-insulating material, the temperature measured by the temperature sensor section 413 and the humidity measured by the humidity sensor section 414 become less susceptible to the influence of outdoor air. Therefore, the temperature and humidity related to the infant 30 can be measured with high accuracy. Furthermore, no heat-insulating material is provided at the opening 417.

[0087] The communication unit 415 is configured to perform wired or wireless communication between the temperature and humidity sensor 41 inside the clothing and the outside. The communication unit 415 includes, for example, a transmitting unit and a receiving unit. The communication unit 415, for example, performs communication with the information processing device 21. More specifically, the communication unit 415 sends signals (data) to the information processing device 21 based on the temperature measured by the temperature sensor unit 413 and the humidity measured by the humidity sensor unit 414.

[0088] Fastener 416 is a component that secures the temperature and humidity sensor 41 inside the clothing to the clothing or absorbent material of the infant 30. Fastener 416 can be, for example, an adhesive layer formed by applying an adhesive, or a mechanical hook-and-loop fastener.

[0089] like Figure 2 As shown in (c), the bottom surface of the clothing temperature and humidity sensor 41 is composed of a second cover 412 having an opening 417 and a fastener 416. When the clothing temperature and humidity sensor 41 is installed relative to the infant 30, the bottom surface of the clothing temperature and humidity sensor 41 is the surface in contact with the outer surface of the infant 30's clothing or absorbent material. The bottom surface of the clothing temperature and humidity sensor 41 is fixed relative to the outer surface of the infant 30's clothing or absorbent material by the fastener 416.

[0090] Alternatively, the opening 417 can be located on a different side than the side where the fastener 416 is located. For example, if a clothing temperature and humidity sensor 41 is installed relative to the infant 30, the opening 417 can be located on the first cover 411, so that the first cover 411 is closer to the infant 30's body than the second cover 412, which includes the side where the fastener 416 is located. This is because a closer opening 417 to the infant 30's body allows for more accurate acquisition of the clothing's internal temperature and humidity.

[0091] Furthermore, the method of installing the temperature and humidity sensor 41 inside the clothing of the infant 30 is not limited to the method of using fastener 416. For example, it can also be a method of using tape, elastic mesh, or elastic cylindrical fasteners worn on the torso of the infant 30. The same applies to the method of installing the motion sensor 42 and the vital signs sensor 43 on the infant 30. In addition, at least one of the motion sensor 42 and the vital signs sensor 43 can also be disposed in the housing space 418 together with the temperature sensor unit 413 and the humidity sensor unit 414. In this case, the communication unit 415, for example, sends a signal based on the activity level measured by the motion sensor 42 and a signal based on the vital signs measured by the vital signs sensor 43 to the information processing device 21.

[0092] Figure 3This is a block diagram illustrating an example of the system structure of the information processing device 21. The information processing device 21 includes, for example, a CPU 51, RAM 52, a storage device 53, a touch screen display 54, a first communication unit 55, a second communication unit 56, a vibration unit 57, and a speaker 58.

[0093] CPU51 is a processor that controls the operation of various components within the information processing device 21.

[0094] RAM52 is volatile memory. RAM52 is, for example, DRAM. The storage area of ​​RAM52 is allocated, for example, as a storage area for data used by OS521, applications (e.g., sleep assistant program 522), and processes executed by CPU51.

[0095] Storage device 53 is a storage device equipped with non-volatile memory. Storage device 53 is, for example, a solid-state drive (SSD) or a hard disk drive (HDD). Storage device 53 stores programs (program products) and data used to control the operation of information processing device 21. Storage device 53 may store, for example, data such as temperature inside clothing 530, humidity inside clothing 531, body movement data 532, vital sign data 533, ambient temperature data 534, ambient humidity data 535, sleep parameters 536, temperature and humidity factors 537, comfort range table 538, and comfort judgment table 539. Storage device 53 may also store behavioral data 540.

[0096] The temperature data 530 inside the clothing is obtained by the temperature and humidity sensor 41 inside the clothing, representing the temperature inside the clothing of infants and young children 30.

[0097] The humidity data 531 inside the clothing is data representing the humidity inside the clothing of infants and young children 30, obtained by the temperature and humidity sensor 41 inside the clothing.

[0098] The motion data 532 is data representing the motion (e.g., activity level) of the infant 30, acquired by the motion sensor 42.

[0099] Vital signs data 533 is data representing the vital signs of infants 30 acquired by vital signs sensor 43.

[0100] The ambient temperature data 534 is data representing the temperature of the living environment of the infant 30, which is obtained by the ambient temperature and humidity sensor 44.

[0101] The ambient humidity data 535 is data representing the humidity of the living environment of the infant 30, which is obtained by the ambient temperature and humidity sensor 44.

[0102] Sleep parameter 536 is a parameter used to evaluate the quality of sleep in infants and young children 30. Sleep parameter 536 is calculated, for example, using at least one of body movement data 532 and vital signs data 533.

[0103] Temperature and humidity factor 537 is a factor (indicator) related to the temperature and humidity experienced by infants and young children 30 that may affect sleep parameter 536. Temperature and humidity factor 537 is calculated, for example, using at least one of the following: temperature data inside clothing 530, humidity data inside clothing 531, ambient temperature data 534, and ambient humidity data 535, and includes statistical measures of these values, plus indicators that affect or are derived from temperature and humidity, such as the wetting time of absorbent materials and discomfort index. For specific examples of temperature and humidity factor 537, refer to [reference needed]. Figure 7 To be discussed later.

[0104] Comfort Range Table 538 is a collection of information representing the range of values ​​for temperature and humidity factors 537 suitable for the sleep of infants and young children 30. More specifically, Comfort Range Table 538 stores, for each temperature and humidity factor, the upper limit and lower limit, or both, of the range of temperature and humidity factors 537 that allow for the attainment of preferred sleep parameters 536. The range of values ​​for temperature and humidity factors 537 that allow for the attainment of preferred sleep parameters 536 is also referred to as the comfort range of that temperature and humidity factor 537. For a specific example of Comfort Range Table 538, see [link to relevant documentation]. Figure 12 To be discussed later.

[0105] Comfort Judgment Table 539 is a table outlining the conditions for determining whether the sleep environment is suitable for infant 30 (i.e., the comfort of the sleep environment) and the coping methods for situations where the sleep environment is unsuitable for infant 30. The sleep environment includes not only the environment in which infant 30 is situated (living environment) but also the internal environment of the clothing worn by infant 30 (clothing internal environment). Furthermore, improving the sleep environment means improving at least one of the environment in which infant 30 is situated or the internal environment of the clothing worn by infant 30. For the specific structure of Comfort Judgment Table 539, please refer to [reference needed]. Figure 16 , Figure 17 as well as Figure 18 To be discussed later.

[0106] Behavioral data 540 represents data on the behavior of the infant 30 related to sleep. The sleep-related behaviors of the infant 30 include the infant's actions and states upon waking, during the day, and at night. More specifically, the sleep-related behaviors of the infant 30 include, for example, the infant's state upon waking, mood upon waking, state during the day, mood during the day, state when awake during the night, and mood when awake during the night. These sleep-related behaviors of the infant 30 are used as criteria for judging the quality of the infant's sleep. Behavioral data 540 is generated (input) based on operations performed by the caregiver 31 on the information processing device 21. Operations performed by the caregiver 31 on the information processing device 21 include, for example, operations performed by the caregiver 31 on the touch panel of the graphical user interface (GUI) displayed on the liquid crystal display (LCD) of the touchscreen display 54. For a specific structural example of behavioral data 540, see [link to relevant documentation]. Figure 14 To be discussed later.

[0107] Storage device 53 can also further store dynamic image data. The dynamic image data is generated by camera device 45 and includes data of time-series images of the infant 30 captured.

[0108] The touchscreen display 54 is an input / output device. The touchscreen display 54 may include, for example, an LCD and a touch panel. The touchscreen display 54 may display, for example, an image based on a display signal generated by the CPU 51 on the LCD screen.

[0109] A touch panel is disposed on the upper surface of the LCD. The touch panel is an electrostatic capacitive pointing device used for input on the LCD screen. The touch panel detects the contact position on the screen where a finger touches. The touch panel can send a signal indicating the detected contact position to various parts (e.g., the CPU 51) within the information processing device 21. Based on the time-series changes in the detected contact position, the CPU 51 can, for example, detect the finger movement.

[0110] The touchscreen display 54 shows information notifying the caregiver 31, including images of a GUI prompting the caregiver 31 to input information. The caregiver 31 can input information related to the infant 30's sleep into the information processing device 21, for example, by operating the GUI using a touch panel.

[0111] The first communication unit 55 is a device configured to perform wired or wireless communication between the information processing device 21 and external devices. For example, the first communication unit 55 performs communication with the air conditioning unit 22 and a server device (not shown). The first communication unit 55 includes a transmitting unit and a receiving unit.

[0112] The second communication unit 56 is configured to perform wired or wireless communication between the information processing device 21 and external devices. For example, the second communication unit 56 performs communication with the clothing temperature and humidity sensor 41, the body motion sensor 42, the vital signs sensor 43, and the ambient temperature and humidity sensor 44. The second communication unit 56 may also perform communication with the camera device 45. The second communication unit 56 includes a transmitting unit and a receiving unit.

[0113] The vibration unit 57 is an output device having a vibration mechanism. The vibration mechanism is, for example, implemented as a motor with an eccentric weight mounted on a rotating shaft. The vibration unit 57 causes the information processing device 21 to vibrate, for example, based on a signal generated by the CPU 51. The signal generated by the CPU 51 can be a signal specifying at least one of the vibration magnitude, vibration time, and vibration mode.

[0114] Speaker 58 is an output device. Speaker 58 outputs sound based on sound signals generated by CPU 51, for example.

[0115] Next, the program (program product) executed by CPU51 will be explained.

[0116] CPU 51 executes various programs loaded from storage device 53 into RAM 52. The programs executed by CPU 51 include operating system (OS) 521 and sleep assistant program 522.

[0117] OS521 is a program used to control the basic operations of various components within the information processing device 21. The CPU 51 executes OS521 for tasks such as controlling input / output, file management, memory management, and communication.

[0118] The sleep assistance program 522 is a program designed to improve the quality of sleep for infants and young children 30. More specifically, the sleep assistance program 522 is configured to allow the information processing device 21 to perform the following functions: receiving data related to the infant or young child 30 from multiple sensors 4; and parsing the received data to provide sleep assistance information to the caregiver 31. Alternatively, the sleep assistance program 522 may also be configured to allow the information processing device 21 to perform a function of acquiring feedback data regarding the sleep assistance information.

[0119] Figure 4 This is a block diagram illustrating an example of the functional structure of the CPU 51 that executes the sleep assistance program 522. Please note that the information processing device 21 centered on the CPU 51 configured to execute the sleep assistance program 522 will sometimes be referred to as "CPU 51" in the following text.

[0120] CPU 51, for example, includes a receiving processing unit 61, a storage processing unit 62, a sleep parameter calculation unit 63, a temperature and humidity factor calculation unit 64, an analysis unit 65, a judgment unit 66, a notification processing unit 67, a control unit 68, and a feedback processing unit 69. CPU 51 may also include a generation processing unit 60. The receiving processing unit 61, storage processing unit 62, sleep parameter calculation unit 63, temperature and humidity factor calculation unit 64, analysis unit 65, judgment unit 66, notification processing unit 67, control unit 68, feedback processing unit 69, and generation processing unit 60 are, for example, functional structures possessed by CPU 51 through the execution of sleep assistance program 522.

[0121] The receiving and processing unit 61 receives data from the clothing temperature and humidity sensor 41, the body movement sensor 42, the vital signs sensor 43, and the ambient temperature and humidity sensor 44 via the second communication unit 56. The data to be received is time-series data of clothing temperature 530, clothing humidity 531, body movement data 532, vital signs data 533, ambient temperature data 534, and ambient humidity data 535. The receiving and processing unit 61 sends the received data to the storage and processing unit 62.

[0122] The storage processing unit 62 stores the data sent from the receiving processing unit 61 in the storage device 53. For example, the storage processing unit 62 associates data such as the temperature inside clothing 530, humidity inside clothing 531, body movement data 532, vital signs data 533, ambient temperature data 534, and ambient humidity data 535 with the date and time before storing them in the storage device 53. The date and time used for association are the date and time corresponding to the measurement of each data point, and are sent from each sensor along with the data. However, in the case of real-time transmission, the data can also be appended by the receiving processing unit 61 during data reception.

[0123] The sleep parameter calculation unit 63 calculates sleep parameters 536 for each sleep cycle, for example, during each sleep cycle of the infant 30, using at least one of the body movement data 532 and vital sign data 533 stored in the storage device 53. The sleep parameter calculation unit 63 may also further use information input by the caregiver 31 (e.g., bedtime) to calculate sleep parameters 536. Alternatively, the sleep parameter calculation unit 63 may use dynamic image data generated by the camera device 45 to calculate sleep parameters 536. The calculated sleep parameters 536 are stored in the storage device 53.

[0124] Additionally, a single sleep episode, such as nighttime sleep, is defined more specifically as the longest sleep episode within a 24-hour period including the night (e.g., 24 hours from 12:00 noon on one day to 12:00 noon on the next day). A single sleep episode can span two days. Hereinafter, a single sleep episode is determined based on the date the sleep begins. For example, sleep from 8:00 PM on April 1st to 6:00 AM on April 2nd is defined as sleep on April 1st. In other words, sleep on a given day can extend into the following day.

[0125] The temperature and humidity factor calculation unit 64, for example, calculates the temperature and humidity factor 537 corresponding to a day's sleep using at least one of the following stored in the storage device 53: temperature data 530 inside the clothing, humidity data 531 inside the clothing, ambient temperature data 534, and ambient humidity data 535, during each (once) of an infant's (toddler's) sleep. The calculated temperature and humidity factor 537 is then stored in the storage device 53.

[0126] The analysis unit 65 analyzes, for example, the sleep parameters 536 and temperature and humidity factors 537 corresponding to a specific period of sleep, and obtains combinations of highly correlated (correlated) sleep parameters 536 and temperature and humidity factors 537. Hereinafter, this specific period will also be referred to as the first period. The first period, for example, includes M days (M times) of sleep for an infant or toddler 30. M is an integer greater than or equal to 2, for example, 6. The first period can vary depending on the infant or toddler's age in months (age). Furthermore, if the analysis unit 65 stores sleep parameters 536 and temperature and humidity factors 537 corresponding to more than M days of sleep in the storage device 53, it can also select to obtain sleep parameters 536 and temperature and humidity factors 537 corresponding to M days of sleep with better quality. The analysis unit 65 analyzes the obtained sleep parameters 536 and temperature and humidity factors 537 corresponding to the M days of sleep, and obtains combinations of highly correlated sleep parameters 536 and temperature and humidity factors 537. The sleep parameters 536 corresponding to the first period of sleep will also be simply referred to as the sleep parameters 536 of the first period. The temperature and humidity factor 537 corresponding to the sleep period in the first period is also simply referred to as the temperature and humidity factor 537 of the first period.

[0127] Next, the analysis unit 65 calculates the range (comfort range) of the temperature and humidity factor 537 values ​​for obtaining the preferred value of the sleep parameter 536 based on the combination of the more relevant sleep parameter 536 and the temperature and humidity factor 537. The analysis unit 65 then sets the calculated comfort range in the comfort range table 538 stored in the storage device 53. Thus, a comfort range corresponding to each infant 30 can be set in the comfort range table 538. For a specific example of analyzing the sleep parameter 536 and the temperature and humidity factor 537 and setting the comfort range of the temperature and humidity factor 537 in the comfort range table 538, please refer to... Figures 10-12 To be discussed later.

[0128] The determination unit 66 uses the comfort range table 538 and the comfort determination table 539 to determine, for example, at fixed intervals whether the current sleep environment, as indicated by the temperature and humidity factor 537, is suitable for the infant 30 (comfort of the sleep environment). Alternatively, the determination unit 66 may also determine whether the current sleep environment is suitable for the infant 30 based on the operation of the information processing device 21 by the caregiver 31 (more specifically, the operation requesting a determination of the comfort of the sleep environment).

[0129] Specifically, the determination unit 66 determines whether the current temperature inside the clothing, the humidity inside the clothing, the ambient temperature, and the ambient humidity are all within the comfort range set in the comfort range table 538. The current temperature inside the clothing is, for example, the temperature represented by the most recently acquired (saved) data from the clothing temperature data 530 stored in the storage device 53. The same applies to the current humidity inside the clothing, the ambient temperature, and the ambient humidity. A suitable sleeping environment for the infant 30 is, for example, an environment where the current temperature inside the clothing, the humidity inside the clothing, the ambient temperature, and the ambient humidity are all within the comfort range set in the comfort range table 538. Conversely, an unsuitable sleeping environment for the infant 30 is, for example, an environment where at least one of the current temperature inside the clothing, the humidity inside the clothing, the ambient temperature, and the ambient humidity is outside the comfort range set in the comfort range table 538.

[0130] If the current sleep environment is suitable for the infant 30, the determination unit 66 generates sleep aid information indicating that the current sleep environment is suitable for the infant 30. Furthermore, the determination unit 66 sends the generated sleep aid information to the notification processing unit 67.

[0131] If the current sleep environment is unsuitable for the infant 30, the determination unit 66, based on the determination results of whether the current temperature inside the clothing, humidity inside the clothing, ambient temperature, and ambient humidity are within the comfort range set in the comfort range table 538, obtains a coping method from the comfort determination table 539. The obtained coping method is a method for making the sleep environment suitable for the infant 30. For specific methods of obtaining the coping method from the comfort determination table 539, please refer to... Figures 16-18 As will be described later. The determination unit 66 generates information including at least one of the following: a determination result indicating that the current sleep environment is unsuitable for the infant 30, and a coping method. Furthermore, the determination unit 66 sends the generated sleep assistance information to the notification processing unit 67. Additionally, if the coping method obtained from the comfort determination form 539 includes a coping method based on controlling the air conditioning device 22, the determination unit 66 may also send sleep assistance information to the control unit 68.

[0132] The notification processing unit 67 notifies the caregiver 31 of information related to the infant's (30's) sleep environment. Specifically, the notification processing unit 67 retrieves a comfort range table 538 from the storage device 53. The notification processing unit 67 then notifies the caregiver 31 of the comfort range based on the temperature and humidity factor 537 in the retrieved comfort range table 538. The notification processing unit 67 may also further retrieve data representing the current sleep environment (hereinafter referred to as current sleep environment data). Current sleep environment data includes, for example, recent data on the temperature inside clothing 530, humidity inside clothing 531, ambient temperature 534, and ambient humidity 535. The notification processing unit 67 then notifies the caregiver 31 of the retrieved current sleep environment data and the comfort range based on the temperature and humidity factor 537 in the comfort range table 538. Additionally, the notification processing unit 67 may also receive sleep assistance information sent from the determination unit 66. The notification processing unit 67 notifies the childcare worker 31 of the current sleep environment data obtained, the comfort range of temperature and humidity factors 537 based on the comfort range table 538, and the received sleep aid information. The notification processing unit 67 may also notify the childcare worker 31 of at least one of the current sleep environment data, the comfort range of temperature and humidity factors 537 based on the comfort range table 538, and the sleep aid information. This notification may be made using, for example, at least one of a touchscreen display 54 and a speaker 58.

[0133] When the determination unit 66 sends a message to the notification processing unit 67 indicating that the sleeping environment is unsuitable for the infant 30, in addition to the above notification, the determination unit 66 may also send a signal to the vibration unit 57 to issue a warning to the caregiver 31, thus notifying via vibration.

[0134] For example, the notification processing unit 67 generates a display signal for displaying an image (hereinafter referred to as a notification image) that shows the current sleep environment data, the comfort range of the temperature and humidity factor 537, and sleep aid information. The notification image may include, for example, an image showing at least one of the current sleep environment data plotted within the comfort range of the temperature and humidity factor 537 in two-dimensional coordinates of temperature and humidity, and an image showing the sleep aid information. The notification image may also include a GUI for inputting an evaluation related to the notified sleep aid information. The GUI for inputting an evaluation related to the notified sleep aid information may be, for example, a button for inputting whether the notified sleep aid information is appropriate, or to what extent it is appropriate. The notification processing unit 67 sends the generated display signal to the touchscreen display 54. The touchscreen display 54 displays the notification image on the screen based on the received display signal. By observing the displayed notification image, the caregiver 31 can confirm the current sleep environment data and the comfort range of the temperature and humidity factor 537 related to the infant 30, and can obtain sleep aid information for setting a suitable sleep environment for the infant 30. The caregiver 31 may implement coping methods based on sleep aid information (e.g., removing one layer of clothing from the infant 30, operating the air conditioning unit 22, etc.). As a result, a comfortable sleep environment based on sleep aid information (i.e., the temperature inside the clothing, the humidity inside the clothing, the ambient temperature, and the ambient humidity within a comfortable range) can be provided to the infant 30, thereby improving the quality of the infant 30's sleep.

[0135] Furthermore, the notification processing unit 67 can also send a signal requesting vibration to the vibration unit 57 based on the received sleep aid information. The vibration unit 57 then causes the information processing device 21 to vibrate based on the received signal. By vibrating the information processing device 21, the caregiver 31 can be prompted to check the notification image displayed on the screen. This vibration can also have a specific vibration pattern. The information processing device 21 vibrates with a specific vibration pattern, thereby enabling the caregiver 31 to recognize that sleep aid information has been received.

[0136] Furthermore, the notification processing unit 67 can also send an audio signal based on sleep aid information to the speaker 58. The speaker 58 outputs an audio signal based on the received audio signal. This audio signal can be either a recorded message or an alarm. The caregiver 31 can identify the sleep aid information through the audio signal. Alternatively, the caregiver 31 can be prompted to confirm the notification image displayed on the screen through the audio signal.

[0137] The control unit 68 receives sleep aid information sent from the determination unit 66. Based on the sleep aid information, the control unit 68 generates a request related to at least one of the ambient temperature and ambient humidity. The request may include, for example, information indicating at least one of a set target temperature and target humidity for the air conditioning device 22. Alternatively, the request may also include information indicating at least one of increasing the ambient temperature, decreasing the ambient temperature, increasing the ambient humidity, and decreasing the ambient humidity. The control unit 68 sends the generated request to the air conditioning device 22, for example, via the first communication unit 55. The air conditioning device 22 receives the request sent by the control unit 68 and performs actions based on the request. Thus, a comfortable sleep environment (e.g., ambient temperature and humidity within a comfortable range) based on the sleep aid information can be provided to the infant 30.

[0138] The feedback processing unit 69 processes feedback on information notified to the childcare worker 31. Specifically, the feedback processing unit 69 processes, for example, feedback based on operations performed by the childcare worker 31 on the touchscreen display 54.

[0139] Feedback represents an evaluation related to the sleep aid information being provided. More specifically, feedback may represent, for example, the result of the caregiver 31's judgment on whether the provided information was appropriate. The feedback processing unit 69 may also use the feedback to collaborate with the analysis unit 65 to update the comfort range table 538.

[0140] Additionally, the notification processing unit 67 can further process information related to the behavior of the infant 30 for the caregiver 31 to input. This processing includes, for example, displaying an image (hereinafter, information input image) on the touchscreen display 54 that includes a GUI for inputting information related to the infant 30's behavior. The GUI for inputting information may be, for example, a button for selecting the infant 30's actual behavior from candidates for the infant 30's behavior, or a text area for inputting text representing the infant 30's behavior.

[0141] More specifically, the notification processing unit 67 generates, for example, a display signal for displaying an information input image. The notification processing unit 67 sends the generated display signal to the touchscreen display 54. Based on the received display signal, the touchscreen display 54 displays the information input image on the screen. The displayed information input image is an image that prompts the caregiver 31 to input information related to the infant's / toddler's 30 behavior. The caregiver 31 inputs information related to the infant / toddler's 30 behavior through operations on the displayed information input image via the touch panel.

[0142] In addition, the notification processing unit 67 may further use at least one of the vibration unit 57 and the speaker 58 to input urging information to the childcare worker 31.

[0143] Specifically, the notification processing unit 67 can also send a signal requesting vibration to the vibration unit 57 when displaying the information input image. Based on the received signal, the vibration unit 57 causes the information processing device 21 to vibrate. By vibrating the information processing device 21, the caregiver 31 can be prompted to confirm the information input image displayed on the screen. This vibration can also have a specific vibration pattern. The information processing device 21 vibrates with a specific vibration pattern, thereby allowing the caregiver 31 to recognize that the information input image has been displayed.

[0144] Additionally, the notification processing unit 67 can also send an audio signal associated with the information input image to the speaker 58. The speaker 58 outputs a sound based on the received audio signal. This sound can be a recording of a specific message or an alarm. Through the sound, the caregiver 31 can be prompted to check the information input image displayed on the screen.

[0145] The generation processing unit 60 generates data based on the actions performed by the childcare worker 31. This data includes, for example, behavioral data 540. The generation processing unit 60 generates behavioral data 540, for example, based on the actions of the childcare worker 31 on a touchscreen display 54 showing an information input image. The generation processing unit 60 associates the generated behavioral data 540 with a date (or date and time) and saves it to the storage device 53.

[0146] Here, the sleep parameter 536 calculated by the sleep parameter calculation unit 63 will be explained. Figure 5 An example representing a summary of sleep parameter 536.

[0147] Sleep parameters 536 are used to evaluate the sleep quality of infants and young children 30. Sleep parameters 536 include, for example, average activity level when active, bedtime start, bedtime, sleep onset, wake-up time, total sleep time, awakening time, number of awakenings, activity level per unit time, deep sleep occupancy, rapid eye movement (REM) sleep occupancy, sleep efficiency, heart rate, heart rate variability, respiratory rate per unit time, and extremity skin temperature. Each sleep parameter is sent to the judgment unit 66 to determine whether it is good or bad, and the result is sent to the notification processing unit 67, with notification provided in the same manner as for temperature and humidity factors.

[0148] The average activity level during active periods is the average of the amount of activity sensed during body movements from the time of falling asleep to the time of waking up. In other words, the average activity level during active periods is the average of non-zero activity levels measured during the period from the time of falling asleep to the time of waking up. The average activity level during active periods is calculated by the sleep parameter calculation unit 63, for example, based on body movement data 532 acquired by the body movement sensor 42. The lower the average activity level during active periods, the better; therefore, if it is less than a given value, the determination unit 66 determines that the infant 30's sleep quality is good.

[0149] The bedtime start time is the moment when the caregiver 31 begins putting the infant 30 to bed (e.g., the moment the infant 30 gets into bed). The bedtime start time is also referred to as the lying-down time or the bedtime. The bedtime start time may be input, for example, based on the caregiver 31's operation of the information processing device 21. Alternatively, the bedtime start time may also be obtained, for example, by the CPU 51 parsing dynamic image data acquired by the camera device 45. The earlier the bedtime start time, the better; therefore, if it is earlier than a given time, the determination unit 66 determines that the infant 30's sleep quality is good.

[0150] Bedtime is the time from the start of bedtime to the time of falling asleep. Bedtime is calculated based on, for example, the start of bedtime is input and the time of falling asleep is calculated by the sleep parameter calculation unit 63. The shorter the bedtime, the better; therefore, if it is shorter than a given time, the determination unit 66 determines that the infant 30's sleep quality is good.

[0151] The sleep onset time is the moment when the infant 30 has fallen asleep. The sleep onset time is calculated by the sleep parameter calculation unit 63, for example, based on body movement data 532 acquired by the body movement sensor 42, or on vital sign data 533 acquired by the vital sign sensor 43. The sleep onset time is, for example, the initial moment after the start of bedtime when the infant 30's body movement becomes zero at a fixed time (e.g., 5 minutes). Alternatively, the sleep onset time can also be input based on the operation of the information processing device 21 by the caregiver 31. The earlier the sleep onset time, the better; therefore, if it is earlier than a given time, the determination unit 66 determines that the infant 30's sleep quality is good.

[0152] The wake-up time is the moment when the infant 30 has woken up. The wake-up time can be, for example, the moment when sustained, relatively strong body movement (e.g., body movement exceeding a threshold intensity for more than one hour) begins after the time the infant falls asleep. The wake-up time can be calculated by the sleep parameter calculation unit 63, for example, based on body movement data 532 acquired by the body movement sensor 42, or based on vital sign data 533 acquired by the vital sign sensor 43. Alternatively, the wake-up time can also be input based on the operation of the information processing device 21 by the caregiver 31. The earlier the wake-up time, the better; therefore, if it is earlier than a given time, the determination unit 66 determines that the infant 30's sleep quality is good.

[0153] Total sleep time is the time from the moment of falling asleep to the moment of waking up, excluding any periods of wakefulness. Total sleep time is calculated, for example, based on the moment of falling asleep, the moment of waking up, and the periods of wakefulness calculated by the sleep parameter calculation unit 63. Alternatively, the total sleep time can be input by the caregiver 31 using the information processing device 21. If the total sleep time falls within the range of the baseline time corresponding to the infant's age for each month, the determination unit 66 determines that the infant's sleep quality is good. Furthermore, the closer the total sleep time is to the range of the baseline time corresponding to the infant's age for each month, the more likely the determination unit 66 is to determine that the infant's sleep quality is good.

[0154] Figure 6 An example of a baseline time representing the total sleep time of an infant or toddler over 30 years.

[0155] The awakening time is the duration of sustained physical activity exceeding a certain threshold intensity for a specific period (e.g., 1 hour) from the time of falling asleep to the time of waking up. The awakening time is calculated by the sleep parameter calculation unit 63, for example, based on physical activity data 532 acquired by the physical activity sensor 42, or on vital sign data 533 acquired by the vital sign sensor 43. A shorter awakening time is better; therefore, if it is shorter than a given time, the determination unit 66 determines that the infant 30's sleep quality is good.

[0156] The number of awakenings during sleep is the number of times awakening occurs during the period from the time the child falls asleep to the time the child wakes up. The number of awakenings during sleep is calculated by the sleep parameter calculation unit 63 based on the number of awakenings during the period from the time the child falls asleep to the time the child wakes up. The fewer the number of awakenings during sleep, the better; therefore, if the number is less than a given value, the determination unit 66 determines that the infant 30's sleep quality is good.

[0157] The activity level per unit time is a value obtained by converting the activity level from the time of falling asleep to the time of waking up into a value per unit time. The activity level per unit time is calculated, for example, by the sleep parameter calculation unit 63 based on the body movement data 532 acquired by the body movement sensor 42. The lower the activity level per unit time, the better; therefore, if it is less than a given value, the determination unit 66 determines that the infant 30's sleep quality is good. Conversely, if the activity level per unit time is 0, the determination unit 66 determines that the infant 30's sleep quality is poor. The unit time is, for example, 1 hour.

[0158] The deep sleep occupancy rate is the ratio of deep sleep time to the time from the moment of falling asleep to the moment of waking up. Deep sleep time is calculated, for example, by the sleep parameter calculation unit 63 based on body movement data 532 acquired by the body movement sensor 42. A higher deep sleep occupancy rate is better; therefore, if it exceeds a given value, the determination unit 66 determines that the infant 30's sleep quality is good.

[0159] REM sleep occupancy is the proportion of REM sleep time to the time from the time of falling asleep to the time of waking up. REM sleep time is calculated, for example, by the sleep parameter calculation unit 63 based on body movement data 532 acquired by the body movement sensor 42. A higher REM sleep occupancy is better; therefore, if it exceeds a given value, the determination unit 66 determines that the infant 30's sleep quality is good.

[0160] Sleep efficiency is the ratio of the total sleep time (i.e., the time from the time of falling asleep to the time of waking up, excluding wakefulness) to the total sleep time. Sleep efficiency is calculated, for example, based on the time of falling asleep, the time of waking up, and the total sleep time calculated by the sleep parameter calculation unit 63. If the sleep efficiency value is higher than a given value, the determination unit 66 determines that the infant 30's sleep quality is good.

[0161] The heart rate is the heart rate during deep sleep (e.g., the most frequent heart rate 3 hours after falling asleep). The most frequent heart rate is calculated by the sleep parameter calculation unit 63, for example, based on the data corresponding to the deep sleep time within the vital signs data 533 acquired by the vital signs sensor 43 (more specifically, the heart rate data measured by the heart rate sensor). A lower most frequent heart rate is better; therefore, if it is less than a given value, the determination unit 66 determines that the infant 30's sleep quality is good. Where the most frequent heart rate is below 50, the determination unit 66 determines that the infant 30's sleep quality is poor.

[0162] The respiratory rate per unit time is the respiratory rate per unit time during the period from the time of falling asleep to the time of waking up. The respiratory rate per unit time is calculated by the sleep parameter calculation unit 63, for example, based on the vital sign data 533 (more specifically, the respiratory rate data measured by the respiratory rate sensor) acquired by the vital sign sensor 43, corresponding to the time from the time of falling asleep to the time of waking up. The lower the respiratory rate per unit time, the better. Therefore, if it is less than a given value, the determination unit 66 determines that the infant 30's sleep quality is good.

[0163] Territorial skin temperature is the average skin temperature of the extremities, such as hands or feet, during the period from the time of falling asleep to the time of waking up. Territorial skin temperature is calculated by the sleep parameter calculation unit 63, for example, based on data corresponding to the time from the time of falling asleep to the time of waking up, within the vital sign data 533 acquired by the vital sign sensor 43 (more specifically, skin temperature data measured by the skin temperature sensor). A higher territorial skin temperature during sleep is better; therefore, if it exceeds a given value, the determination unit 66 determines that the infant 30's sleep quality is good.

[0164] Thus, by using sleep parameter 536, the quality of sleep of infant 30 can be evaluated in sleep assistance system 1A. Sleep parameter 536 is not limited to the foregoing example, and various parameters capable of evaluating the quality of sleep of infant 30 can be used.

[0165] In addition, the sleep duration of infants and young children varies with age, as shown in reference 1 below.

[0166] Reference 1: Research Group on Sleep and Use of Information and Communication Devices by Preschool Children, "Sleep Guidelines for Preschool Children", [online], [retrieved March 30, 2023], Internet <URL: <https: / / www.mhlw.go.jp / content / 000375711.pdf>

[0167] Next, the temperature and humidity factor 537 calculated by the temperature and humidity factor calculation unit 64 will be explained. Figure 7 Examples representing the various summaries of multiple temperature and humidity factors 537.

[0168] Temperature and humidity factor 537 refers to temperature and humidity-related elements that may affect sleep parameters 536. Temperature and humidity factor 537 includes, for example, statistical measures of temperature and humidity that vary over time, such as average temperature inside clothing, average humidity inside clothing, average ambient temperature, and average ambient humidity; factors affecting temperature and humidity, such as the wetting time of absorbent materials; and indicators derived from temperature and humidity, such as the discomfort index. Additionally, Figure 7In addition to these temperature and humidity factors 537, the parameters for obtaining the wetting time of absorbent items, which are temperature and humidity factors 537, are further shown, namely, the time of urination and the time of changing absorbent items. Furthermore, in the calculation of temperature and humidity factor 537, as described below, the time of falling asleep and the time of waking up, included in the sleep parameter 536, are sometimes used. In this case, the calculation of temperature and humidity factor 537 can also be configured to be performed after calculating the time of falling asleep and the time of waking up for the corresponding day.

[0169] The average temperature or humidity inside the clothing is the average value of the temperature or humidity inside the clothing from the time of falling asleep to the time of waking up. The average temperature or humidity inside the clothing is calculated by the temperature and humidity factor calculation unit 64, for example, based on data corresponding to the time from the time of falling asleep to the time of waking up, within the clothing temperature data 530 or clothing humidity data 531 obtained by the clothing temperature and humidity sensor 41. Alternatively, other statistical values ​​of clothing temperature or humidity may be used instead of the average temperature or humidity inside the clothing. These statistical values ​​may include various statistical values ​​such as deviation values, median values, maximum values, and minimum values.

[0170] The urination time is the moment when the infant 30 urinates. The urination time can be, for example, the moment when the temperature and humidity inside the clothing begin to rise simultaneously. For example, the temperature and humidity factor calculation unit 64 calculates the urination time based on the clothing temperature data 530 and clothing humidity data 531 obtained by the clothing temperature and humidity sensor 41.

[0171] The absorbent material replacement time is the time when the absorbent material worn by the infant 30 is changed. For example, the time when the humidity inside the clothing drops sharply can be used as the replacement time. For instance, the temperature and humidity factor calculation unit 64 calculates the absorbent material replacement time based on the humidity data 531 inside the clothing obtained by the clothing temperature and humidity sensor 41.

[0172] The absorbent fabric wetting time is the time it takes for an infant's absorbent fabric to become damp during the period from bedtime to wake-up time. In other words, the absorbent fabric wetting time is the time from the moment of urination to the moment the absorbent fabric is changed. If there are multiple urinations (or multiple absorbent fabric changes) during the period from bedtime to wake-up time, the absorbent fabric wetting time is the sum of the time from each urination to the next immediate absorbent fabric change.

[0173] The average ambient temperature or average ambient humidity is the average of the ambient temperature or humidity from the time of falling asleep to the time of waking up. The average ambient temperature or average ambient humidity is calculated by the temperature and humidity factor calculation unit 64, for example, based on data corresponding to the time from the time of falling asleep to the time of waking up, within the ambient temperature data 534 or ambient humidity data 535 acquired by the ambient temperature and humidity sensor 44. Alternatively, other statistical values ​​of ambient temperature or ambient humidity may be used instead of the average ambient temperature or average ambient humidity.

[0174] For example: For example, the average ambient temperature and average ambient humidity mentioned above are used as the ambient temperature and ambient humidity in the following formula (1), and the temperature and humidity factor calculation unit 64 calculates the discomfort index contained in the temperature and humidity factor 537.

[0175]

[0176] The information processing device 21 uses these temperature and humidity factors 537 as candidates to analyze their correlation with the quality of the infant's sleep (e.g., sleep parameter 536), and calculates the relationship between each temperature and humidity factor 537 and the quality of the infant's sleep as a correlation. The temperature and humidity factors 537 are not limited to the examples described above, and various numerical indicators related to temperature and humidity that may affect the quality of the infant's sleep can be used.

[0177] For example, sleep parameters 536 and temperature and humidity factors 537 are obtained for each day of sleep in infants and young children (30 years old) and stored in storage device 53. Furthermore, in analyzing the correlation between sleep parameters 536 and temperature and humidity factors 537, sleep parameters 536 and temperature and humidity factors 537 for a first period are used. Additionally, depending on the type of sleep parameters 536 being analyzed, data for all temperature and humidity factors 537 for the first period may not be used; instead, data for a portion of the first period, such as bedtime, the first 3 hours after falling asleep, the first hour before waking up, or the first hour before waking up, may be used. In this case, a statistical value for the temperature and humidity factors 537 is calculated, for example, based on the data for such a portion of the period.

[0178] Figure 8 Examples of sleep parameters 536 and temperature and humidity factors 537 for the first period stored in storage device 53 are shown. Here, examples of sleep parameters 536 and temperature and humidity factors 537 obtained for different three days of sleep for infant 30 are shown as sleep parameters 536 and temperature and humidity factors 537 for the first period.

[0179] For example, during sleep on Day 1, the activity level per unit of time was 22.4. The total sleep time was 432 minutes. The bedtime (sleep latency) was 38 minutes. The bedtime (time of lying down) was 11:38 PM. The wake-up time was 7:54 AM. There was one awakening during the night. The temperature inside the clothing was 29.3°C. The ambient humidity was 46%. The same pattern was observed during sleep on Days 2 and 3.

[0180] Reference Figures 9-12 This describes an example of the operation of the analysis unit 65, which analyzes sleep parameters 536 and temperature and humidity factors 537 and calculates the comfort range of temperature and humidity factors 537.

[0181] The analysis unit 65 of the information processing device 21 is activated automatically, for example, by the CPU 51 or by an operator's instruction, based on the storage device 53 accumulating sleep parameters 536 and temperature and humidity factors 537 for a first period (M days of sleep). The analysis unit 65 analyzes the correlation between each sleep parameter 536 and each temperature and humidity factor 537, and obtains formulas representing these relationships. Furthermore, the analysis unit 65 can be activated automatically every given period, such as every week, starting from the last activation.

[0182] The analysis unit 65 obtains sleep parameters 536 and temperature and humidity factors 537 for a first period (M days of sleep) from the storage device 53. Furthermore, if the storage device 53 stores sleep parameters 536 and temperature and humidity factors 537 for more than M days, the analysis unit 65 can also obtain sleep parameters 536 and temperature and humidity factors 537 for the M days with better sleep quality. The analysis unit 65 compares the sleep parameters 536 for each day, for example, to determine the days with better sleep quality. A day with better sleep quality refers to, for example, the M days that include more sleep parameters 536 determined to be of good quality. Additionally, if the quality of sleep in a combination of two days cannot be determined, the analysis unit 65 can determine that the sleep quality of the two days is the same. Alternatively, the analysis unit 65 can determine the quality of sleep on two days based on the priority order of the sleep parameters 536.

[0183] Figure 9 An example of the priority order of sleep parameters 536 that determine the quality of sleep. Figure 9 In the example shown, the priority order is from high to low, following the order of sleep efficiency, deep sleep percentage, REM sleep percentage, activity level per unit time, average activity level when active, and so on. Furthermore, the time of bedtime (the moment of lying down) has the lowest priority.

[0184] In analyzing the correlation between the acquired sleep parameter 536 and temperature and humidity factor 537, the analysis unit 65 may use at least one of the following: a regression line, a regression curve, or multiple regression analysis. For example, when using a regression line to analyze the correlation, the analysis unit 65 obtains N combinations of sleep parameters 536 and temperature and humidity factor 537 whose absolute values ​​of the correlation coefficient of the regression line are greater than or equal to a first threshold, in descending order of the absolute values ​​of the correlation coefficients. Alternatively, when using both a regression line and a regression curve to analyze the correlation, the analysis unit 65 may also obtain N combinations of sleep parameters 536 and temperature and humidity factor 537 whose coefficient of determination of the regression line is greater than or equal to a second threshold and the regression curve whose coefficient of determination of the regression line is greater than or equal to a second threshold, in descending order of the coefficient of determination. Furthermore, N is an integer greater than or equal to 1. For example, when using multiple regression analysis to analyze correlations, the analysis unit 65 calculates the coefficients of each of the multiple temperature and humidity factors 537 by performing multiple regression analysis with one of the sleep parameters 536 as the target variable (dependent variable) and multiple temperature and humidity factors 537 as the explanatory variables (independent variables), thereby obtaining the multiple regression equation for the sleep parameter 536. For instance, if the analysis unit 65 obtains multiple multiple regression equations corresponding to each of the multiple sleep parameters 536, it obtains N multiple regression equations in descending order of the largest coefficient contained in each of the multiple multiple regression equations. The obtained N multiple regression equations are equivalent to N combinations of the sleep parameter 536 and the temperature and humidity factors 537 with larger coefficients.

[0185] Figure 10 Examples of correlation coefficients r between each of the sleep parameters 536 and each of the temperature and humidity factors 537 are provided. Here, the analysis of the correlation between sleep parameters 536 and temperature and humidity factors 537 using a regression line is illustrated. For sleep parameters 536, bedtime, sleep onset time, wake-up time, total sleep time, number of awakenings during the night, and activity level per unit time are used. For temperature and humidity factors 537, average ambient temperature, average ambient humidity, average temperature inside clothing, average humidity inside clothing, and the wetting time of absorbent materials are used. In this case, the correlation coefficient r can be calculated for all combinations of bedtime, sleep onset time, wake-up time, total sleep time, number of awakenings during the night, and activity level per unit time, and average ambient temperature, average ambient humidity, average temperature inside clothing, average humidity inside clothing, and the wetting time of absorbent materials. In a given combination of sleep parameters 536 and temperature and humidity factors 537, the higher the correlation between these sleep parameters 536 and temperature and humidity factors 537, the larger the absolute value of the correlation coefficient r.

[0186] Figure 10In the example shown, the correlation coefficient r between bedtime and average ambient temperature is -0.785. The correlation coefficient r between bedtime and average ambient humidity is -0.177. In this case, average ambient temperature is more strongly correlated with bedtime than average ambient humidity.

[0187] Furthermore, the correlation coefficient r between activity level per unit time and average ambient temperature is 0.268. The correlation coefficient r between activity level per unit time and average ambient humidity is -0.846. In this case, the correlation between average ambient humidity and activity level per unit time is higher than that between average ambient temperature and average ambient humidity.

[0188] The analysis unit 65, for example, selects N combinations from the sleep parameter 536 and the temperature and humidity factor 537, where the absolute value of the correlation coefficient r is above a first threshold, in descending order of the absolute value of the correlation coefficient r. Here, the first threshold is set to 0.4, and N is set to 5. Therefore, Figure 10 In the example shown, five combinations of sleep parameter 536 and temperature and humidity factor 537 with an absolute value of correlation coefficient r greater than 0.4 are obtained. That is, the combination of activity level per unit time and average ambient humidity, the combination of wake-up time and average temperature inside clothing, the combination of bedtime and average ambient temperature, the combination of wake-up time and average ambient temperature, and the combination of number of awakenings during the night and average ambient temperature are obtained.

[0189] The analysis unit 65 calculates the range (comfort range) of the temperature and humidity factor 537 that yields the preferred value of the sleep parameter 536 based on the obtained combination of the more relevant sleep parameter 536 and the temperature and humidity factor 537. More specifically, the analysis unit 65 calculates the comfort range of the temperature and humidity factor 537, for example, based on the regression line corresponding to the combination of the more relevant sleep parameter 536 and the temperature and humidity factor 537.

[0190] Based on the obtained regression line, the analysis unit 65 determines a specific range as the comfort range of the temperature and humidity factor 537 as follows: First, the range of the temperature and humidity factor 537 that has been measured in reality during the first period is determined. Next, using the previously obtained regression line (regression formula) between the temperature and humidity factor 537 and the related sleep parameter 536, the value of the temperature and humidity factor 537 corresponding to the value of the sleep parameter 536 that is most suitable for the sleep of the infant 30 within this range is obtained, and this value is set as the front end (i.e., one end) of the comfort range. Furthermore, a specific proportion, such as one-third, of the range within the entire range of the temperature and humidity factor 537 that belongs to the front end of the comfort range is set as the comfort range of the temperature and humidity factor 537.

[0191] Reference Figures 11A to 11E An example of the comfort range calculated based on the regression line is given. Figures 11A to 11ECorresponding to in Figure 10 The examples shown include combinations of activity level per unit time and average ambient humidity, wake-up time and average temperature inside clothing, bedtime and average ambient temperature, wake-up time and average ambient temperature, and number of times one wakes up during the night and average ambient temperature.

[0192] Figure 11A Example of a comfort range representing a regression line based on activity level per unit time and average ambient humidity. Regression line 71 represents the relationship between activity level per unit time and average ambient humidity of infants 30 during the first period (M days of sleep).

[0193] Based on regression line 71, a specific range 71R of average ambient humidity is determined as the comfortable range for average ambient humidity, for example, as follows. As mentioned earlier, the less activity per unit time, the better the quality of sleep for infant 30. Therefore, within the specific range 71R, for example, the average ambient humidity value corresponding to the activity level per unit time most suitable for infant 30's sleep (i.e., the minimum activity level) is set as the front end (i.e., the right end) of the comfortable range, within the entire range of activity level per unit time shown by regression line 71. Here, the minimum activity level is not the actual measured activity level, but the activity level calculated using the formula representing regression line 71 based on the actual measured average ambient humidity. Next, the average ambient humidity value corresponding to the least suitable activity level (i.e., the maximum activity level) is obtained (shown as the left end of regression line 71 in the figure), and the range between this and the front end of the previously determined comfortable range is set as the range of average ambient humidity. Within the entire range of average ambient humidity thus obtained, a specific proportion of the range on the front end of the comfortable range is determined as the comfortable range of average ambient humidity. The specific proportion is, for example, 1 / 3. Figure 11A In the example shown, the average ambient humidity ranges from 45% to 69%. The range 71R, from 61% to 69% at the front end of the comfort range, is determined as the comfortable range of average ambient humidity during sleep. The range 71R from 61% to 69% is the range where 69% is set as the upper third of the entire range of average ambient humidity shown by the regression line 71.

[0194] Figure 11B This is an example of a comfort range represented by a regression line based on wake-up time and average temperature inside clothing. Regression line 72 represents the relationship between wake-up time and average temperature inside clothing for infants 30 during the first period.

[0195] Based on regression line 72, a specific range 72R of average clothing temperature is determined as follows, serving as the comfortable range for average clothing temperature. As mentioned earlier, the earlier the wake-up time, the better the quality of sleep for infant 30. Therefore, the specific range 72R, for example, is a range within the entire range of wake-up times shown by regression line 72, where the average clothing temperature corresponding to the wake-up time most suitable for infant 30's sleep (i.e., the earliest wake-up time) is set as the front end (i.e., one end) of the comfortable range, and the wake-up time calculated using a formula expressed by regression line 72 based on the average clothing temperature measured in reality, rather than the actual measured wake-up time, is set as a specific proportion of the entire range of average clothing temperature at the other end. Figure 11B In the example shown, the range 72R from 32°C to 33°C is calculated as the comfortable range of average in-clothing temperature during sleep. The range 72R from 32°C to 33°C is the range where 33°C is set as the upper third of the entire range of average in-clothing temperature shown by regression line 72.

[0196] Figure 11C This example illustrates the comfort range of the regression line based on bedtime and average ambient temperature. Regression line 73 represents the correlation between bedtime and average ambient temperature for infants 30 during the first period. Furthermore, here, the average ambient temperature used to analyze the correlation with bedtime is the average ambient temperature from the start of bedtime until falling asleep.

[0197] exist Figure 11C In the example shown, the range 73R from 23°C to 23.5°C is calculated as the comfortable range of average ambient temperature during sleep. The range 73R from 23°C to 23.5°C is the range where 23.5°C is set to the upper third of the entire range of average ambient temperature shown by the regression line 73. The method for determining this comfortable range is the same as that used previously in the overview, as for determining average ambient humidity and average temperature inside clothing; therefore, details are omitted.

[0198] Figure 11D This example illustrates the comfort range based on the regression line derived from wake-up time and average ambient temperature. Regression line 74 represents the correlation between wake-up time and average ambient temperature for infants 30 during the first period.

[0199] exist Figure 11DIn the example shown, the range 74 from 22.5°C to 23.0°C is calculated as the comfortable range of average ambient temperature during sleep. The range 74R from 22.5°C to 23.0°C is the range where 23.0°C is the upper third of the entire range of average ambient temperature shown by the regression line 74. The method for determining this comfortable range is the same as that described in the previous summary, and is therefore omitted in detail.

[0200] Figure 11E This example illustrates the comfort range based on the regression line derived from the number of awakenings during intermittent sleep and the average ambient temperature. Regression line 75 represents the correlation between the number of awakenings during intermittent sleep and the average ambient temperature for infants 30 during the first period.

[0201] Figure 11E In the example shown, the range 75R from 21.2°C to 21.9°C is calculated as the comfortable range of average ambient temperature during sleep. The range 75R from 21.2°C to 21.9°C is the range where 21.2°C is the lower third of the entire range of average ambient temperature shown by the regression line 75. The method for determining this comfortable range is the same as that described in the previous summary, and is therefore omitted in detail.

[0202] In addition, the comfortable range of average ambient temperature during sleep also depends on... Figure 11D The comfort range of a temperature and humidity factor 537 is calculated using the regression line 74 shown in the diagram, which represents the wake-up time and average ambient temperature. Where the comfort range of a certain temperature and humidity factor 537 can be calculated based on a combination with at least one sleep parameter 536, for example, a regression line representing a higher relevant combination is used to calculate the comfort range of that temperature and humidity factor 537. For example, in... Figure 11D The correlation ratio of the combination of wake-up time and average ambient temperature shown in the figure Figure 11E In cases where the combination of wake-up frequency and average ambient temperature is higher, the comfort range of average ambient temperature is calculated based on regression line 74 of wake-up time and average ambient temperature. In such cases, for example, the comfort range of average ambient temperature based on regression line 75 of a correspondingly lower number of wake-up frequency and average ambient temperature is not calculated.

[0203] The analysis unit 65 will determine the comfort range, for example, the comfort range table 538 stored in the storage device 53.

[0204] Figure 12Example of the structure of Comfort Range Table 538. Comfort Range Table 538 is used to determine whether the sleep environment is suitable for infants 30 during bedtime and sleep. Furthermore, the comfort ranges set in Comfort Range Table 538 can also be provided to caregivers 31 as information indicating a suitable sleep environment for infants 30.

[0205] Comfort range table 538 may include, for example, the comfort ranges for average ambient temperature, average ambient humidity, average temperature inside clothing, average humidity inside clothing, and the wetting time of absorbent materials, as comfort ranges for sleeping. Furthermore, comfort range table 538 may include the comfort ranges for average ambient temperature, average ambient humidity, average temperature inside clothing, average humidity inside clothing, and the wetting time of absorbent materials, as comfort ranges for sleep.

[0206] Figure 12 In the example shown, the comfort range is set in table 538. Figures 11A to 11D The comfort range calculated in the example shown.

[0207] Regression curves can also be used to analyze the correlation between sleep parameter 536 and temperature and humidity factor 537. When using regression curves, the analysis unit 65 uses a second threshold to select N combinations of sleep parameter 536 and temperature and humidity factor 537 with a large coefficient of determination R2.

[0208] Based on the selected regression curve, the analysis unit 65 determines a specific range as the comfort range of the temperature and humidity factor 537 as follows: First, the range of the temperature and humidity factor 537 actually measured during the first period is determined. Next, using the previously obtained regression curve (regression formula) of the temperature and humidity factor 537 and the related sleep parameter 536, the value of the temperature and humidity factor 537 corresponding to the value of the sleep parameter 536 that is most suitable for the infant 30's sleep within this range is obtained, and this value is set as the center of the comfort range. Furthermore, the range within which the temperature and humidity factor 537 is located, for example, one-sixth of the way to either side, is set as the comfort range of the temperature and humidity factor 537.

[0209] Reference Figure 13A as well as Figure 13B An example of calculating the comfort range based on regression curves is illustrated. Here, N combinations of sleep parameter 536 (with the largest coefficient of determination R2) and temperature and humidity factor 537 are used to obtain combinations of bedtime and average ambient temperature, as well as combinations of bedtime and average ambient humidity.

[0210] Figure 13A Example of a comfort range represented by regression curves based on bedtime and average ambient temperature. Regression curve 76 shows the correlation between bedtime and average ambient temperature for infants 30 during the first period.

[0211] Based on regression curve 76, a specific range 76R of average ambient temperature corresponding to the shortest bedtime is calculated as the comfortable range of average ambient temperature. This specific range 76R, for example, is a range of values ​​centered on the average ambient temperature corresponding to the bedtime most suitable for infant 30's sleep (i.e., the shortest bedtime) within the entire range of bedtimes shown by regression curve 76, and is a specific range of values ​​within the entire range of average ambient temperature shown by regression curve 76. This specific range of values, for example, is a range from -5°C to +5°C. Figure 13A In the example shown, the range 76R from 23.3°C to 24.3°C is calculated as the comfortable range of average ambient temperature during sleep. The range 76R from 23.3°C to 24.3°C is the range from -5°C to +5°C centered on the average ambient temperature of 23.8°C corresponding to the shortest sleep time shown by regression curve 76.

[0212] Figure 13B Examples of comfort ranges represented by regression curves based on bedtime and average ambient humidity. Regression curve 77 shows the correlation between bedtime and average ambient humidity for infants 30 during the first period.

[0213] Based on regression curve 77, a specific range 77R of average ambient humidity corresponding to shorter bedtimes is calculated as the comfortable range of average ambient humidity. This specific range 77R, for example, is a range of values ​​centered on the average ambient humidity corresponding to the bedtime most suitable for infants 30's sleep, within the entire range of bedtimes shown by regression curve 77, and specifically within the entire range of average ambient humidity shown by regression curve 77. This specific range of values, for example, is from -5% to +5%. Figure 13B In the example shown, the range 77R from 41% to 51% is calculated as the comfortable range of average ambient humidity during sleep. The range 77R from 41% to 51% is the range from -5% to +5% centered on the average ambient humidity of 46% corresponding to the shortest bedtime shown by regression curve 77.

[0214] The correlation between sleep parameter 536 and temperature and humidity factor 537 can also be analyzed using multiple regression analysis. In this case, the analysis unit 65 obtains the multiple regression equations for each sleep parameter 536 by calculating the coefficients of each of the multiple temperature and humidity factors 537 through multiple regression analysis with each sleep parameter as the target variable being at least one sleep parameter 536 and the explanatory variables being multiple temperature and humidity factors 537. Hereinafter, the case of obtaining the multiple regression equations for three sleep parameters A, B, and C is illustrated. The multiple regression equations for sleep parameters A, B, and C are set as each of the following equations (2) to (4).

[0215]

[0216]

[0217]

[0218] Here, X, Y, and Z represent temperature and humidity factors 537. a, b, c, e, f, h, and i are the coefficients of temperature and humidity factors 537 in the multiple regression equation. Furthermore, among the coefficients a, b, and c included in equation (2), we assume that the absolute value of coefficient a is the largest. Among the coefficients e and f included in equation (3), we assume that the absolute value of coefficient e is the largest. Among the coefficients h and i included in equation (4), we assume that the absolute value of coefficient h is the largest. The absolute value of coefficient a is greater than the absolute value of coefficient e. Furthermore, the absolute value of coefficient e is greater than the absolute value of coefficient h.

[0219] The analysis unit 65 calculates the comfort range of various temperature and humidity factors 537 suitable for the sleep of infants 30 based on the acquired multiple regression equations of at least one sleep parameter 536. More specifically, the analysis unit 65 obtains N multiple regression equations based on the coefficients with the largest absolute values ​​contained in each multiple regression equation, according to the acquired multiple regression equations of at least one sleep parameter 536. For example, the analysis unit 65 compares the coefficients with the largest absolute values ​​contained in each multiple regression equation and obtains N multiple regression equations in descending order of the absolute values ​​of these coefficients. Moreover, the analysis unit 65 calculates the comfort range of various temperature and humidity factors 537 suitable for the sleep of infants 30 based on the acquired N multiple regression equations. For example, the analysis unit 65 determines the threshold of each temperature and humidity factor 537 that yields the preferred values ​​of the corresponding N sleep parameters 536 based on the N multiple regression equations. Alternatively, the analysis unit 65 may determine the comfort range (threshold) based on the N multiple regression equations by prioritizing the temperature and humidity factors 537 with the largest absolute values ​​of their corresponding coefficients.

[0220] For example, when N is 2, the analysis unit 65 obtains two multiple regression equations based on the absolute values ​​of coefficients a, e, and h (i.e., the coefficients with the largest absolute values ​​in each multiple regression equation) of the three multiple regression equations of sleep parameters A, B, and C. In other words, the analysis unit 65 obtains a multiple regression equation for sleep parameter A (Equation (2)) with the coefficient a having the largest absolute value among the absolute values ​​of coefficients a, e, and h, and a multiple regression equation for sleep parameter B (Equation (3)) with the coefficient e having the second largest absolute value. Moreover, based on the multiple regression equations for sleep parameter A and sleep parameter B, the analysis unit 65 determines the thresholds (or comfort ranges) of temperature and humidity factors X, Y, and Z that allow obtaining preferred values ​​for sleep parameters A and B. Thus, for example, if at least one of the temperature and humidity factors X, Y, and Z becomes below the corresponding threshold (or within the comfort range), then, if preferred values ​​for sleep parameters A and B can be obtained, information on how to change the temperature and humidity factors X, Y, and Z can be provided to the caregiver 31. In other words, caregivers 31 are provided with options to change temperature and humidity factors X, Y, and Z to improve the sleep environment of infants 30. Furthermore, information on how to change each of the temperature and humidity factors X, Y, and Z should be communicated to caregivers 31, prioritizing information with the largest absolute value of the corresponding coefficient.

[0221] When calculating the comfort range of temperature and humidity factor 537 for each of the N combinations of highly correlated sleep parameters 536 and temperature and humidity factors 537, the analysis unit 65 can also calculate the comfort range of each temperature and humidity factor 537 based on the sleep parameters 536 corresponding to more than one day of sleep in which the infant 30 is judged to have good sleep quality (i.e., the infant 30's sleep is comfortable). Furthermore, the determination of the N combinations of highly correlated sleep parameters 536 and temperature and humidity factors 537 can be made, for example, using at least one of the aforementioned regression lines, regression curves, and multiple regression analysis. The determination of whether the infant 30's sleep quality on a particular day is good can be made, for example, using behavioral data 540.

[0222] The analysis unit 65 uses the behavioral data 540 stored in the storage device 53 to determine the quality of the infant 30's sleep each day. Specifically, the analysis unit 65 calculates, for example, the number of criteria items indicating good sleep quality among the multiple criteria items included in the daily behavioral data 540. Furthermore, if the number of criteria items indicating good sleep quality exceeds a threshold, the analysis unit 65 determines that the infant 30's sleep quality for that day is good.

[0223] Figure 14An example representing a summary of each of the multiple items included in the behavioral data 540. The multiple items included in the behavioral data 540 are items used as criteria for judging the quality of the infant 30's sleep (criterion items). Criterion items represent the infant 30's behavior related to sleep. Criterion items include, for example, at least one of the following: items related to spontaneous waking, items related to feeling refreshed after waking, items related to a good mood upon waking, items related to a good mood during the day, items related to daytime wakefulness, and items related to the condition and mood when waking up during the night. The values ​​of each criterion item are set based on the operation of the caregiver 31 on the information processing device 21 (e.g., operation on the touchscreen display 54). The caregiver 31, for example, performs the operation of setting the values ​​of each criterion item after acquiring the infant 30's sleep data for the most recent day. The set values ​​of each criterion item are used to judge the quality of the sleep for that most recent day. More specifically, for example, the assessment of the quality of sleep of infants and young children on April 1st uses criteria including the condition and mood when awake during sleep (night) on April 1st, whether they spontaneously wake up on April 2nd, whether they feel refreshed after waking up, whether they are in a good mood when waking up, whether they are in a good mood during the day, and whether they are awake during the day.

[0224] In the assessment criteria for a given day's sleep, the item related to spontaneous wake-up indicates whether the infant (30) spontaneously woke up on that day. If the infant (30) spontaneously woke up, the item related to spontaneous wake-up is set to "Y". If the infant (30) did not spontaneously wake up, the item related to spontaneous wake-up is set to "N". The infant (30) had better sleep quality when the item related to spontaneous wake-up was set to "Y" compared to when it was set to "N".

[0225] The items related to feeling refreshed after waking up indicate whether the infant felt refreshed after waking up on the corresponding day. If the infant felt refreshed after waking up, the item related to feeling refreshed after waking up is marked "Y". If the infant took a long time to wake up, the item related to feeling refreshed after waking up is marked "N". When the item related to feeling refreshed after waking up is marked "Y", the infant's sleep quality is better compared to when it is marked "N".

[0226] The items related to mood upon waking indicate whether the infant (age 30) was in a good mood upon waking on the corresponding day. If the infant (age 30) was in a good mood upon waking, the item related to mood upon waking was set to "Y". If the infant (age 30) was in a bad mood upon waking, the item related to mood upon waking was set to "N". When the item related to mood upon waking was set to "Y", the infant (age 30) had better sleep quality compared to when it was set to "N".

[0227] The items related to daytime mood indicate whether the infant (age 30) was in a good mood during the day on the corresponding day. If the infant (age 30) was in a good mood during the day, the item related to daytime mood was set to "Y". If the infant (age 30) was in a bad mood during the day, the item related to mood upon waking was set to "N". When the item related to mood upon waking was set to "Y", the infant (age 30) had better sleep quality compared to when it was set to "N".

[0228] The items related to daytime alertness indicate whether the infant (30) was awake during the day on the corresponding day. If the infant (30) was awake during the day, the item related to daytime alertness is set to "Y". If the infant (30) appeared sleepy during the day, the item related to daytime alertness is set to "N". The infant (30) had better sleep quality when the item related to daytime alertness was set to "Y" compared to when it was set to "N".

[0229] The items related to the state and mood during nighttime awakenings indicate the state and mood of infant 30 during nighttime awakenings on the corresponding day. If infant 30 did not awaken during the night, the items related to the state and mood during nighttime awakenings are set to, for example, "A". If infant 30 awakened during the night without crying, the items related to the state and mood during nighttime awakenings are set to, for example, "B". If infant 30 awakened during the night while crying, the items related to the state and mood during nighttime awakenings are set to, for example, "C". When the items related to the state and mood during nighttime awakenings are set to "A", infant 30 has better sleep quality than when set to "B". Furthermore, when the items related to the state and mood during nighttime awakenings are set to "B", infant 30 has better sleep quality than when set to "C".

[0230] The caregiver 31 observes the behavior of the infant 30 and determines the values ​​set for each judgment criterion item of the behavioral data 540. Based on their experience in caring for the infant 30, the caregiver 31 is more likely to determine values ​​for each judgment criterion item that appropriately represent the infant 30's actions, mood, condition, etc. Therefore, the behavioral data 540 is useful as information for judging the quality of the infant 30's sleep. Furthermore, the judgment criterion items are not limited to the aforementioned examples; various behaviors of the infant 30 related to sleep can be used.

[0231] The analysis unit 65 uses N days' worth of behavioral data 540 to determine the quality of sleep for 30 infants and young children each day. N is, for example, an integer greater than or equal to 1.

[0232] Figure 15 This is an example of the assessment results for the sleep quality of infants and toddlers 30 using behavioral data 540. Here, we illustrate the assessment of the sleep quality of infants and toddlers 30 each day using three days' worth of behavioral data 540.

[0233] The analysis unit 65 determines the quality of sleep for 30 infants / toddlers each day based on a first indicator. The first indicator, for example, represents the number of criteria items indicating good sleep quality within all criteria items of the corresponding day's behavioral data 540. The number of criteria items indicating good sleep quality is, for example, the number of items with either "Y" or "A" as a criterion.

[0234] Specifically, if the first indicator exceeds the threshold, the analysis unit 65 determines that the sleep quality for that day is good. If the first indicator is below the threshold, the analysis unit 65 determines that the sleep quality for that day is poor. Furthermore, if the first indicator equals the threshold, the analysis unit 65 determines that the sleep quality for that day is average. The threshold is, for example, half of all the judgment criteria. Additionally, the threshold can be changed according to the infant's age (months). Alternatively, the threshold can be set by the caregiver 31. Figure 15 In the example shown, the threshold is 3 (i.e., 6, which is half of all the judgment benchmark items).

[0235] Of the 540 behavioral data points from Day 1, the following were assigned the following labels: "N" for items related to spontaneously waking up; "Y" for items related to feeling refreshed upon waking; "Y" for items related to mood upon waking; "Y" for items related to mood during the day; "N" for items related to alertness during the day; and "C" for items related to the state and mood when waking up during the night.

[0236] The behavioral data 540 for DAY1 contains 3 instances of "Y" and "A", therefore the analysis unit 65 calculates the first indicator as 3. Furthermore, since the first indicator equals the threshold, the analysis unit 65 determines that the sleep quality for DAY1 is average.

[0237] Of the 540 behavioral data points from Day 2, the following were marked with "N": "N" for items related to spontaneously waking up; "N" for items related to feeling refreshed after waking up; "N" for items related to mood upon waking; "Y" for items related to mood during the day; "N" for items related to alertness during the day; and "C" for items related to the state and mood when waking up during the night.

[0238] The behavioral data 540 for DAY2 contains only one "Y" and one "A", so the analysis unit 65 calculates the first indicator as 1. Moreover, the first indicator is below the threshold, so the analysis unit 65 determines that the sleep quality for DAY2 is poor.

[0239] In the behavioral data of Day 3 (DAY 3), the following items were marked with "Y" for items related to spontaneously waking up, feeling refreshed after waking up, feeling good upon waking up, feeling good during the day, feeling awake during the day, and feeling unwell during the night.

[0240] The behavioral data 540 for DAY3 contains 5 instances of "Y" and "A", therefore the analysis unit 65 calculates the first indicator as 5. Furthermore, since the first indicator exceeds the threshold, the analysis unit 65 determines that the sleep quality for DAY3 is good.

[0241] Thus, the analysis unit 65 uses behavioral data 540 to determine the quality of the infant's (30's) sleep each day. Based on the range of values ​​for multiple sleep parameters 536 corresponding to more than one day of sleep deemed to be of good quality by the infant (30) and N combinations of correlated sleep parameters and temperature / humidity factors, the analysis unit 65 calculates the range (comfort range) of temperature / humidity factors 537 included in each of these N combinations, suitable for the infant (30's) sleep. For example, based on multiple sleep parameters 536 deemed to be of good quality by the caregiver 31 for more than one day, the analysis unit 65 calculates the range of values ​​for each of these multiple sleep parameters 536. Furthermore, based on the calculated ranges of each sleep parameter 536, the analysis unit 65 calculates the range of values ​​corresponding to temperature / humidity factors 537 that are highly correlated with that sleep parameter 536. The calculated ranges of values ​​for each temperature / humidity factor 537 are used as the comfort range.

[0242] More specifically, the analysis unit 65 obtains, for example, a minimum and a maximum value of a certain sleep parameter 536 from which the infant 30 has been judged to have had good sleep quality for more than one day. The analysis unit 65 calculates the range from the obtained minimum to the maximum value as the comfort range of the sleep parameter 536. Next, the analysis unit 65 determines the temperature and humidity factor 537 that is highly correlated with the sleep parameter 536. In determining the temperature and humidity factor 537 that is highly correlated with the sleep parameter 536, at least one of the aforementioned regression lines, regression curves, and multiple regression analysis is used. The analysis unit 65 calculates the range of values ​​of the determined temperature and humidity factor 537 corresponding to the comfort range of the sleep parameter 536 as the comfort range of the temperature and humidity factor 537.

[0243] Alternatively, the analysis unit 65 can, for example, calculate the range of values ​​for each of the multiple temperature and humidity factors 537 based on multiple temperature and humidity factors 537 that the childcare worker 31 has determined to have provided good sleep quality for more than one day. The calculated range of values ​​for each temperature and humidity factor 537 is used as the comfort range. Specifically, the analysis unit 65 obtains, for example, the minimum and maximum values ​​of one or more values ​​of a certain temperature and humidity factor 537 from which the infant 30 has been determined to have provided good sleep quality for more than one day. Furthermore, the analysis unit 65 calculates the comfort range of that temperature and humidity factor 537 from the range obtained from the minimum to the maximum value.

[0244] Next, refer to Figures 16-18 The comfort judgment form 539 used by the judgment unit 66 of the information processing device 21 will be explained. When the sleep environment is not suitable for the infant 30, the judgment unit 66 obtains a coping method from the comfort judgment form 539 and sends it to the notification processing unit 67.

[0245] Figure 16This is the first example of the structure of the comfort judgment form 539. The comfort judgment form 539 includes multiple entries corresponding to various judgment conditions related to a suitable sleep environment for infants and young children 30.

[0246] The multiple criteria are based on data related to the state of the infant 30 at a specific moment. A specific moment is, for example, the most recent moment when data related to the state of the infant 30 was acquired. Data related to the state of the infant 30 at a specific moment includes, for example, at least one of the following: temperature inside clothing, humidity inside clothing, ambient temperature, and ambient humidity at that specific moment. Meeting at least one of the multiple criteria means that the environment is not suitable for the infant 30's sleep. Conversely, if none of the multiple criteria are met, it means that the environment is suitable for the infant 30's sleep.

[0247] The entries include fields such as the temperature inside clothing, ambient temperature, ambient humidity, and coping methods.

[0248] Within the entries corresponding to a certain judgment condition, the "Clothing Temperature" field indicates conditions related to the temperature inside the clothing within that judgment condition. The "Ambient Temperature" field indicates conditions related to the ambient temperature. The "Ambient Humidity" field indicates conditions related to the ambient humidity within the corresponding judgment condition. The "Response Method" field indicates the response method if the corresponding judgment condition is met.

[0249] Conditions related to the temperature inside the clothing, the ambient temperature, and the ambient humidity are indicated by at least one of the following: "High," "Normal," "Low," and "-." "High" indicates a condition where the corresponding temperature inside the clothing, ambient temperature, or ambient humidity is higher than the comfort range. "Normal" indicates a condition where the corresponding temperature inside the clothing, ambient temperature, or ambient humidity is within the comfort range. "Low" indicates a condition where the corresponding temperature inside the clothing, ambient temperature, or ambient humidity is lower than the comfort range. "-" indicates that none of these conditions exist for the corresponding temperature inside the clothing, ambient temperature, or ambient humidity.

[0250] The coping methods are information provided to the caregiver 31. The caregiver 31 can improve the sleep environment of the infant 30 based on the coping methods provided via the notification processing unit 67.

[0251] exist Figure 16 For example, the entry at the front indicates that if the conditions of "high" temperature inside the clothing and "high" ambient temperature have been met, the appropriate response is to use air conditioning to lower the outside temperature (ambient temperature), remove one layer of clothing, or change underwear or wipe away sweat, at least one of these.

[0252] Figure 17This represents the second example from Comfort Judgment Form 539. Figure 16 different, Figure 17 The comfort assessment form 539 shown includes fields for temperature inside clothing, humidity inside clothing, ambient temperature, and coping methods.

[0253] For information on the clothing interior temperature field, ambient temperature field, and coping method field, please refer to... Figure 16 And as mentioned above.

[0254] The "Clothing Inner Humidity" field represents the conditions related to the humidity inside the clothing within the corresponding judgment criteria. Conditions related to the humidity inside the clothing are also... Figure 16 The ambient humidity is also characterized in the same way, for example, "high" means that the humidity inside the clothes is higher than the comfort range, and so on.

[0255] exist Figure 17 For example, the entry at the front also states: if the conditions of "high" temperature inside the clothes, "high" humidity inside the clothes, and "high" ambient temperature have been met, the coping methods are to use air conditioning to lower the outside temperature, remove one layer of clothing, change underwear, wipe away sweat, and change to absorbent materials, at least one of the following:

[0256] Figure 18 This represents the third example in the comfort assessment table 539. Figure 18 The comfort assessment table 539 shown includes fields for humidity inside clothing, ambient humidity, and coping methods.

[0257] For the environmental humidity field and the coping method field, please refer to... Figure 16 As mentioned earlier. Regarding the humidity field inside clothing, please refer to... Figure 17 As mentioned above.

[0258] Figure 18 For example, the first item indicates that if both the conditions of "high" humidity inside clothing and "high" ambient humidity are met, the appropriate action is to change underwear, wipe away sweat, or dehumidify at least one of these. Additionally, the fifth item indicates that if both the conditions of "normal" humidity inside clothing and "normal" ambient humidity are met, no action is required. As with the fifth item, items requiring no action are preferably excluded from the comfort assessment table 539.

[0259] If the current sleep environment meets all the conditions shown in any of the entries in the comfort judgment table 539, the judgment unit 66 obtains a coping method from that entry. The obtained coping method is a coping method for making the sleep environment suitable for the infant 30. The judgment unit 66 sends sleep assistance information including the obtained coping method to the notification processing unit 67.

[0260] The notification processing unit 67 uses the sleep assistance information received from the judgment unit 66 to notify the childcare worker 31 of coping methods. The childcare worker 31 can then implement these coping methods (e.g., removing an item of clothing from the infant 30, operating the air conditioning unit 22, etc.). Therefore, a comfortable sleep environment based on the sleep assistance information can be provided to the infant 30, improving the quality of the infant 30's sleep.

[0261] Here, refer to Figure 19A as well as Figure 19B The significance of calculating the comfort range of infant 30 using data acquired by sensor 4 related to infant 30 will be explained. An example is given here: the comfort range is calculated for the first infant 30 and the second infant 30 based on regression lines of activity level per unit time and ambient humidity, respectively. The second infant 30 is different from the first infant 30. Furthermore, the lower the activity level per unit time, the better the sleep quality of infant 30.

[0262] Figure 19A This example illustrates a comfort range calculated based on a regression line of activity level per unit time and ambient humidity for the first infant 30. The regression line 78 represents the correlation between activity level per unit time and average ambient humidity for the first infant 30 during the first period. Based on the regression line 78, a specific range 78R of average ambient humidity corresponding to lower activity levels per unit time is determined as the comfort range of average ambient humidity for the first infant 30. Figure 19A In the example shown, the range 78R from 40% to 50% is calculated as the comfortable range of average ambient humidity for the first infant 30.

[0263] In contrast, Figure 19B This example illustrates a comfort range calculated based on a regression line of activity level per unit time and ambient humidity for the second infant 30. The regression line 79 represents the correlation between activity level per unit time and average ambient humidity of the second infant 30 obtained during the first period. Based on the regression line 79, a specific range 79R of average ambient humidity corresponding to lower activity levels per unit time is determined as the comfort range of average ambient humidity for the second infant 30. Figure 19B In the example shown, the range 78R from 60% to 70% is calculated as the comfortable range of average ambient humidity for the second infant 30.

[0264] Thus, the average comfortable range of ambient humidity differs for the first infant 30 and the second infant 30. In other words, the comfortable range of temperature and humidity factor 537 will vary for each infant 30. Therefore, the sleep assistance system 1A acquires data for each infant 30 and calculates the comfortable range of temperature and humidity factor 537 for each infant 30. As a result, the caregiver 31 can be informed of the comfortable range of temperature and humidity factor 537 for a particular infant 30, thereby effectively improving the sleep quality of that infant 30.

[0265] Next, refer to Figures 20-22 The flowchart illustrates the steps of the processing performed in the information processing device 21.

[0266] Figure 20 This is a flowchart illustrating an example of the data processing steps performed in the information processing device 21. The data processing involves performing calculations using data measured and acquired by the sensor 4 to obtain sleep parameters 536 and temperature and humidity factors 537. The CPU 51 of the information processing device 21 performs the data processing, for example, whenever data acquired by any sensor 4 is stored in the storage device 53. Alternatively, the CPU 51 may perform the data processing at fixed intervals.

[0267] First, the CPU 51 performs calculations using the body movement data 532 and vital sign data 533 stored in the storage device 53 (step S101), thereby calculating the sleep parameters 536. The calculation method for each sleep parameter 536 is as described above. The CPU 51 determines whether the sleep parameters 536 have been calculated (step S102).

[0268] Upon calculating the sleep parameter 536 (as in step S102), the CPU 51 saves the calculated sleep parameter 536 to the storage device 53 (step S103), and proceeds to step S104. The calculated sleep parameter 536, for example, is associated with a corresponding date and saved to the storage device 53.

[0269] If the sleep parameter 536 is not calculated (No in step S102), the process executed by CPU 51 proceeds to step S104.

[0270] Next, the CPU 51 uses the temperature data 530 inside the clothing, the humidity data 531 inside the clothing, the ambient temperature data 534, and the ambient humidity data 535 stored in the storage device 53 to calculate the temperature and humidity factor 537 (step S104). The calculation method for each temperature and humidity factor 537 is as described above. The CPU 51 determines whether the temperature and humidity factor 537 has been calculated (step S105).

[0271] Upon calculating the temperature and humidity factor 537 (as in step S105), the CPU 51 saves the calculated temperature and humidity factor 537 to the storage device 53 (step S106) and ends. The calculated temperature and humidity factor 537, for example, is associated with the corresponding date and saved to the storage device 53.

[0272] If the temperature and humidity factor 537 is not calculated (No in step S105), the CPU 51 ends the data processing.

[0273] Through the above data processing, the CPU 51 can use the data stored in the storage device 53 to calculate the sleep parameters 536 and the temperature and humidity factors 537.

[0274] Figure 21 This is a flowchart illustrating an example of the steps in the correlation analysis process performed in the information processing device 21. The correlation analysis process is used to determine the range (comfort range) of the temperature and humidity factor 537 for obtaining the preferred sleep parameter 536. The CPU 51 accumulates a first period quantity (M days) of the sleep parameter 536 and the temperature and humidity factor 537, and accordingly performs the correlation analysis process. Here, the case where a regression line is used in the analysis of the correlation between the sleep parameter 536 and the temperature and humidity factor 537 is illustrated. Alternatively, regression curves or multiple regression analysis can also be used in the analysis of the correlation between the sleep parameter 536 and the temperature and humidity factor 537.

[0275] First, CPU 51 generates a regression line for each of at least one sleep parameter 536 and all combinations of each of the plurality of temperature and humidity factors 537 (step S106). Specifically, when generating a regression line for a combination of a certain sleep parameter 536 and a certain temperature and humidity factor 537, CPU 51 generates a regression line based on the value of the M-day quantity of the sleep parameter 536 and the value of the M-day quantity of the temperature and humidity factor 537.

[0276] CPU 51 selects N combinations of sleep parameter 536 and temperature / humidity factor 537 from the generated regression line, in descending order of the absolute value of the correlation coefficient (step S202). Alternatively, if there are fewer than N combinations of sleep parameter 536 and temperature / humidity factor 537 with an absolute value of the correlation coefficient above the first threshold, CPU 51 selects all combinations with an absolute value of the correlation coefficient above the first threshold, in descending order of the absolute value of the correlation coefficient. Hereinafter, it is assumed that CPU 51 selects N combinations of sleep parameter 536 and temperature / humidity factor 537.

[0277] CPU51 sets variable i to 1 (step S203). Variable i is used to determine one of the N combinations obtained.

[0278] Next, CPU51 uses the regression line corresponding to the i-th combination, based on the previously used... Figures 11A to 11D The steps described so far determine the range of values ​​for temperature and humidity factor 537 that yields the preferred sleep parameter 536 as the comfort range (step S204). The CPU 51 sets the determined comfort range for temperature and humidity factor 537 in the comfort range table 538 (step S205).

[0279] CPU51 increments variable i by 1 (step S206). Furthermore, CPU51 determines whether variable i is greater than N (step S207). In other words, CPU51 performs processing to determine the comfort range for all the decisions made on the acquired N combinations.

[0280] If variable i is less than N (No in step S207), CPU51 determines whether the temperature and humidity factor 537 of the i-th combination is consistent with any of the temperature and humidity factors 537 of the combinations up to the (i-1)-th combination (step S208).

[0281] If the temperature and humidity factor 537 of the i-th combination is consistent with any of the temperature and humidity factors 537 of the combinations up to the (i-1)-th combination (as in step S208), CPU 51 returns to step S206. If the temperature and humidity factor 537 of the i-th combination is consistent with any of the temperature and humidity factors 537 of the combinations up to the (i-1)-th combination, the comfort range of that temperature and humidity factor 537 has already been determined based on any of the combinations up to the (i-1)-th combination. Therefore, CPU 51 skips the determination based on the comfort range of the i-th combination.

[0282] If the temperature and humidity factor 537 of the i-th combination is different from any of the temperature and humidity factors 537 of the combinations up to the (i-1)-th combination (no in step S208), CPU 51 returns to step S204. In other words, processing for determining the comfort range is performed based on the i-th combination.

[0283] If variable i is greater than N (as in step S207), the processing for determining the comfort range ends for all N combinations, and therefore CPU 51 ends the correlation parsing process.

[0284] Through the above correlation analysis, the CPU 51 can determine the comfort range of temperature and humidity factor 537 that can obtain the preferred sleep parameter 536 based on the combination of highly correlated sleep parameter 536 and temperature and humidity factor 537.

[0285] Figure 22This is a flowchart illustrating an example of the decision / notification processing steps performed in the information processing device 21. The decision / notification processing is based on whether the current environment is suitable for the infant 30 to sleep, and it notifies the infant of information related to a suitable sleep environment. The CPU 51 performs the decision / notification processing, for example, at fixed intervals. Alternatively, the CPU 51 may also perform the decision / notification processing based on the operation of the information processing device 21 by the caregiver 31.

[0286] First, the CPU 51 determines whether the infant 30 is asleep (step S301). Specifically, the CPU 51 determines, for example, that the infant 30 is asleep based on the infant's movement data 532, since the wake-up time has not yet been calculated after the sleep time has been calculated.

[0287] If the infant 30 is determined to be asleep (step S301), the CPU 51 obtains the comfort range of the temperature and humidity factors 537 during sleep from the comfort range table 538 (step S302).

[0288] If the infant is determined to be not asleep (No in step S301), the CPU 51 obtains the comfort range of temperature and humidity factors 537 during sleep from the comfort range table 538 (step S303).

[0289] Next, the CPU 51 determines whether the current environment of the infant 30 converges within the acquired comfort range (step S304). Specifically, the CPU 51 obtains the most recent clothing temperature, clothing humidity, ambient temperature, and ambient humidity from the clothing temperature data 530, clothing humidity data 531, ambient temperature data 534, and ambient humidity data 535 stored in the storage device 53. Additionally, if the CPU 51 detects that the absorbent material has not been changed after the infant 30 urinated, it can obtain the wetting time of the absorbent material from the temperature and humidity factor 537 stored in the storage device 53. Furthermore, the CPU 51 determines whether the acquired temperature and humidity or temperature and humidity factors, such as clothing temperature, clothing humidity, ambient temperature, ambient humidity, and the wetting time of the absorbent material, each converge within a comfortable range.

[0290] If the current environment converges within a comfortable range (as in step S304), the CPU 51 notifies the caregiver 31 that the current environment is suitable for the sleeping or bedtime infant 30 (step S305), ending the determination / notification process. Alternatively, the CPU 51 may also notify the caregiver 31 of at least one of the current environment and the comfort range.

[0291] If the current environment does not converge to a comfortable range (step S304), CPU 51 uses the comfort judgment table 539 to obtain a coping method (step S306). CPU 51 notifies the caregiver 31 that the current environment is unsuitable for the sleeping or bedtime infant 30 and the obtained coping method (step S307), ending the judgment / notification process. Alternatively, CPU 51 may also notify the caregiver 31 of at least one of the current environment and the comfort range. Furthermore, CPU 51 may control the air conditioning device 22 based on the obtained coping method (step S308). For example, based on the coping method of lowering the ambient temperature, CPU 51 communicates with the first communication unit 55 to control the air conditioning device 22, thereby lowering the set temperature.

[0292] Through the above judgment / notification process, CPU 51 can notify the caregiver 31 whether the current environment is suitable for the sleeping or bedtime infant 30. Furthermore, if the current environment is not suitable for the sleeping or bedtime infant 30, CPU 51 can notify the caregiver 31 of coping methods to create a suitable environment. Thus, the sleep assistance system 1A can assist the caregiver 31 in providing a comfortable sleeping environment for the infant 30, thereby improving the quality of the infant 30's sleep.

[0293] (Second Implementation)

[0294] In the sleep assistance system 1A according to the first embodiment, the information processing device 21 used by the user 31 (e.g., a childcare worker or caregiver) uses data acquired by the sensor 4 to generate sleep assistance information. In contrast, in the sleep assistance system according to the second embodiment, the server device uses data acquired by the sensor 4 to generate sleep assistance information.

[0295] In the sleep assistance system according to the second embodiment, the server device has at least a portion of the functions of the information processing device 21 in the first embodiment. Specifically, the server device in the second embodiment has the function of determining the comfort of the infant's (30's) sleep environment and generating sleep assistance information. Hereinafter, the differences from the first embodiment will be mainly explained.

[0296] Figure 23 This illustrates a structural example of the sleep assistance system 1B according to the second embodiment. The sleep assistance system 1B includes an information processing device 21, multiple sensors 4, a server device 25, and a network 26.

[0297] Multiple sensors 4 can each communicate with server device 25 via network 26. Specifically, each of the multiple sensors 4 sends data (sensor data) acquired by the sensor 4 to server device 25 via network 26. Additionally, the multiple sensors 4 can also send sensor data to information processing device 21, which then forwards the sensor data to server device 25. The sensor data includes data acquired by clothing temperature and humidity sensor 41, body motion sensor 42, vital signs sensor 43, and ambient temperature and humidity sensor 44. The sensor data may also include dynamic image data generated by camera device 45.

[0298] Communication via network 26 can be either wired or wireless. Network 26 may include, for example, wired local area networks (LANs), wireless local area networks (LANs), and wide area networks (WANs). WANs may include, for example, mobile phone networks, fixed-line telephone networks, satellite communication networks, dedicated lines, asynchronous transfer mode (ATM), and Internet Protocol-Virtual Private Networks (IP-VPNs).

[0299] Server device 25 is an information processing device that parses data related to infant 30 and provides information (sleep assistance information) to assist infant 30 in sleep. Server device 25 may be implemented as, for example, a server computer.

[0300] Server device 25 receives sensor data from multiple sensors 4, for example, via network 26. Alternatively, server device 25 may also receive sensor data from multiple sensors 4, respectively, via information processing device 21 and network 26.

[0301] Furthermore, the server device 25 can communicate with the information processing device 21 via a network 26, for example. Specifically, the server device 25 sends sleep assistance information to the information processing device 21, for example, via the network 26. The server device 25, in order to analyze sensor data and provide sleep assistance information, has, for example, a reference... Figure 3 as well as Figure 4 The information processing device 21 of the first embodiment described above has the same structure.

[0302] Information processing device 21 receives sleep aid information from server device 25 via network 26. Information processing device 21 receives sleep aid information from server device 25, for example, via first communication unit 55. Information processing device 21 notifies childcare worker 31 of the received sleep aid information. Information processing device 21 has a structure for receiving sleep aid information and notifying childcare worker 31. The structure for notifying childcare worker 31 of sleep aid information, and is set in reference... Figure 4 The notification processing unit 67 of the information processing device 21 described in the first embodiment is similar. Additionally, the information processing device 21 may also have a structure for controlling the air conditioning unit 22 based on received sleep aid information. The structure for controlling the air conditioning unit 22 based on sleep aid information, and the structure provided at the reference... Figure 4 The same applies to the control unit 68 of the information processing device 21 in the first embodiment described above.

[0303] With the above structure, in the sleep assistance system 1B of the second embodiment, the server device 25 can acquire sensor data from multiple sensors 4 and use the acquired sensor data to provide sleep assistance information to the information processing device 21. Furthermore, it is not limited to the function of providing sleep assistance information; the server device 25 may also have other functions of the information processing device 21 of the first embodiment. For example, the server device 25 may also have the function of processing feedback based on the operations of the caregiver 31 on the information processing device 21. Additionally, for example, the server device 25 may also have the function of controlling the air conditioning unit 22 based on the sleep assistance information.

[0304] When implementing this invention, the above-described implementation method is only one example, and various changes can be made to the specific method to implement it.

[0305] The following notes further disclose the embodiments of the present invention described above.

[0306] <1>

[0307] A sleep aid system includes an information processing device and multiple sensors.

[0308] The plurality of sensors includes at least one of a first sensor, a second sensor, and a third sensor.

[0309] The first sensor measures at least one of body movement data representing the subject's body movements and vital sign data representing the subject's vital signs.

[0310] The second sensor measures at least one of the following: internal temperature data representing the temperature inside the clothing worn by the subject, and internal humidity data representing the humidity inside the clothing.

[0311] The third sensor measures at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment.

[0312] The information processing device includes:

[0313] The sleep parameter calculation unit calculates at least one sleep parameter using at least one of the body movement data and the vital signs data.

[0314] The temperature and humidity factor calculation unit calculates multiple temperature and humidity factors using at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data; and

[0315] The analysis unit uses at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period to determine one or more combinations of sleep parameters and temperature and humidity factors that are correlated.

[0316] <2>

[0317] According to the sleep assistance system described in <1>,

[0318] The at least one sleep parameter includes at least one of the subject's sleep latency, sleep onset time, wake-up time, total sleep time, awakening time, number of awakenings, activity level per unit time, deep sleep occupancy, REM sleep occupancy, and sleep efficiency.

[0319] <3>

[0320] According to the sleep assistance system described in <2>,

[0321] The at least one sleep parameter also includes at least one of heart rate, heart rate variability, respiratory rate per unit time, and extremity skin temperature.

[0322] <4>

[0323] According to any one of <1> to <3>, a sleep assistance system

[0324] The plurality of temperature and humidity factors include at least one of the following: the statistical values ​​of ambient temperature, ambient humidity, temperature inside clothing, humidity inside clothing, the time it takes for the absorbent material worn by the subject to become wet, and the discomfort index during the period from the time the subject falls asleep to the time he wakes up.

[0325] <5>

[0326] According to any one of <1> to <4>, a sleep assistance system

[0327] The analysis unit calculates, based on one or more combinations of sleep parameters and temperature and humidity factors that are correlated with the determination, a range of suitable sleep values ​​for the subject for each of the more than one combinations of temperature and humidity factors.

[0328] The information processing device further includes: a notification processing unit that notifies the user of the information processing device of information representing the calculated range.

[0329] <6>

[0330] According to the sleep assistance system described in <5>,

[0331] The notification processing unit further notifies the user of the information processing device of information representing at least one of the latest temperature data inside the clothing, humidity data inside the clothing, ambient temperature data, and ambient humidity data.

[0332] <7>

[0333] According to the sleep assistance system described in <6>,

[0334] The notification processing unit notifies the user of the information processing device that an image of at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data has been plotted within the calculated range, expressed in two-dimensional coordinates of temperature and humidity.

[0335] <8>

[0336] According to the sleep assistance system described in <5>,

[0337] The analytical unit

[0338] The correlation between each of the at least one sleep parameter corresponding to sleep during the first period and each of the plurality of temperature and humidity factors corresponding to sleep during the first period is calculated using a regression line.

[0339] Based on the combination of a first sleep parameter and a first temperature and humidity factor whose absolute value of the correlation coefficient of the calculated regression line is above a first threshold, the range of values ​​of the first temperature and humidity factor suitable for the sleep of the subject is calculated.

[0340] <9>

[0341] According to the sleep assistance system described in <8>,

[0342] The notification processing unit notifies the user of the information processing device of information indicating the range of the calculated values ​​of the first temperature and humidity factor.

[0343] <10>

[0344] According to the sleep assistance system described in <5>,

[0345] The analytical unit

[0346] The correlation between each of the at least one sleep parameter corresponding to sleep during the first period and each of the plurality of temperature and humidity factors corresponding to sleep during the first period was calculated using regression lines and regression curves.

[0347] Based on the combination of the first sleep parameter and the first temperature and humidity factor, where the coefficient of determination of the calculated regression line is above the second threshold, the range of values ​​for the first temperature and humidity factor suitable for the sleep of the subject is calculated.

[0348] Based on the calculated regression curve, the combination of the second sleep parameter and the second temperature and humidity factor above the second threshold is used to calculate the range of values ​​of the second temperature and humidity factor suitable for the sleep of the subject.

[0349] <11>

[0350] According to the sleep assistance system described in <10>,

[0351] The notification processing unit notifies the user of the information processing device of information indicating the range of the calculated first temperature and humidity factor values ​​and information indicating the range of the calculated second temperature and humidity factor values.

[0352] <12>

[0353] According to the sleep assistance system described in <5>,

[0354] The analytical unit

[0355] By using a multiple regression analysis with the target variable being a first sleep parameter (one of the at least one sleep parameter corresponding to sleep during the first period) and the explanatory variables being the multiple temperature and humidity factors corresponding to sleep during the first period, a multiple regression equation for the first sleep parameter, in which the coefficients of each of the multiple temperature and humidity factors are calculated, is obtained.

[0356] Based on the multiple regression equation, the range of values ​​for each of the multiple temperature and humidity factors suitable for the sleep of the subject is calculated.

[0357] <13>

[0358] According to the sleep assistance system described in <12>,

[0359] The notification processing unit notifies the user of the information processing device of information representing the range of values ​​for the calculated multiple temperature and humidity factors.

[0360] <14>

[0361] According to the sleep assistance system described in <5>,

[0362] The analytical unit

[0363] By performing multiple regression analysis with each of the at least one sleep parameter corresponding to sleep during the first period as the target variable and the multiple temperature and humidity factors corresponding to sleep during the first period as the explanatory variables, at least one multiple regression equation is obtained, which calculates the coefficients of each of the multiple temperature and humidity factors and corresponds to the at least one sleep parameter.

[0364] Based on the largest coefficient contained in each of the at least one multiple regression equations, N multiple regression equations are obtained from the at least one multiple regression equation.

[0365] Based on the N multiple regression equations, calculate the range of values ​​for each of the multiple temperature and humidity factors suitable for the sleep of the subject.

[0366] N is an integer greater than or equal to 1.

[0367] <15>

[0368] According to the sleep assistance system described in <5>,

[0369] The analysis unit calculates the range of values ​​of at least one sleep parameter corresponding to more than one day of sleep deemed to be of good quality by the subject, and the range of values ​​of the temperature and humidity factors included in each of the more than one combinations of sleep parameters with correlation to the determination, which are suitable for the subject's sleep.

[0370] <16>

[0371] According to the sleep assistance system described in <5>,

[0372] The analytical unit

[0373] The correlation between each of the at least one sleep parameter corresponding to sleep during the first period and each of the plurality of temperature and humidity factors corresponding to sleep during the first period is calculated using a regression line.

[0374] Based on the combination of a first sleep parameter and a first temperature and humidity factor whose absolute value of the correlation coefficient of the calculated regression line is above a first threshold, the range of values ​​of the first temperature and humidity factor suitable for the sleep of the subject is calculated using the first temperature and humidity factor corresponding to the sleep during the second period in which the sleep quality of the subject is determined to be good. Alternatively, based on the combination of a second sleep parameter and a second temperature and humidity factor whose determination coefficient of the calculated regression line is above a second threshold, the range of values ​​of the second temperature and humidity factor suitable for the sleep of the subject is calculated using the second temperature and humidity factor corresponding to the sleep during the second period.

[0375] <17>

[0376] According to the sleep assistance system described in <5>,

[0377] The analytical unit

[0378] The correlation between each of the at least one sleep parameter corresponding to sleep during the first period and each of the plurality of temperature and humidity factors corresponding to sleep during the first period was calculated using regression curves.

[0379] Based on the combination of the first sleep parameter and the first temperature and humidity factor, which is a factor of determination of the calculated regression curve above a first threshold, the range of values ​​of the first temperature and humidity factor suitable for the sleep of the subject is calculated using the first temperature and humidity factor corresponding to the sleep during the second period in which the subject's sleep quality is determined to be good.

[0380] <18>

[0381] According to the sleep assistance system described in <5>,

[0382] The analytical unit

[0383] By performing multiple regression analysis with each of the at least one sleep parameter corresponding to sleep during the first period as the target variable and the multiple temperature and humidity factors corresponding to sleep during the first period as the explanatory variables, at least one multiple regression equation is obtained, which calculates the coefficients of each of the multiple temperature and humidity factors and corresponds to the at least one sleep parameter.

[0384] Based on the largest coefficient contained in each of the at least one multiple regression equations, N multiple regression equations are obtained from the at least one multiple regression equation.

[0385] Based on the N multiple regression equations, the range of values ​​for each of the multiple temperature and humidity factors suitable for the subject's sleep is calculated using the multiple temperature and humidity factors corresponding to the sleep during the second period when the subject's sleep quality was determined to be good.

[0386] N is an integer greater than or equal to 1.

[0387] <19>

[0388] According to the sleep assistance system described in <5>,

[0389] The information processing device further includes a determination unit that uses at least one of the calculated range and the most recent measured temperature data inside the clothing, humidity data inside the clothing, ambient temperature data, and ambient humidity data to determine whether the current environment is suitable for the subject's sleep, and decides on a coping method if the current environment is not suitable for the subject's sleep.

[0390] The notification processing unit notifies the user of at least one of the determination results indicating whether the current environment is suitable for the subject's sleep and the corresponding coping method.

[0391] <20>

[0392] According to the sleep assistance system described in <19>,

[0393] The information processing device further includes a control unit that, based on the response method, controls the settings of an air conditioning device installed in the environment.

[0394] <21>

[0395] According to any one of <1> to <20>, a sleep assistance system

[0396] In cases where the subject is an infant, the first period varies depending on the subject's age in months.

[0397] <22>

[0398] According to any one of <1> to <21>, a sleep assistance system

[0399] The first sensor is installed either on the inside of the clothing worn by the subject or on the outer surface of the absorbent material or underwear worn by the subject.

[0400] At least one of the body movement data and the vital signs data is measured on either the inside of the garment on which the first sensor is installed or on the outer surface of the absorbent material or the underwear.

[0401] <23>

[0402] According to any one of <1> to <21>, a sleep assistance system

[0403] The first sensor is a belt-shaped sensor that is installed on the subject's arm or leg.

[0404] The first sensor, which is installed on the subject's arm or leg, measures at least one of the body movement data and the vital signs data.

[0405] <24>

[0406] According to any one of <1> to <23>, a sleep aid system

[0407] The physical activity data includes the intensity and amount of activity of the subject.

[0408] The vital signs data include the subject's heart rate, heart rate variability, respiratory rate, and skin temperature.

[0409] The sleep parameter calculation unit uses at least one of the activity intensity, activity level, skin temperature, heart rate, heart rate variability, and respiratory rate to calculate the at least one sleep parameter.

[0410] <25>

[0411] The sleep aid system according to any one of <1> to <24>

[0412] The second sensor is installed either on the inside of the clothing worn by the subject or on the outer surface of the absorbent material or underwear worn by the subject.

[0413] At least one of the temperature data inside the garment and the humidity data inside the garment is measured, either on the inside of the garment where the second sensor is installed or on the outer surface of the absorbent material or the underwear.

[0414] <26>

[0415] According to any one of <1> to <25>, a sleep aid system

[0416] The third sensor was not installed on any of the clothing, the absorbent material worn by the subject, or the underwear worn by the subject.

[0417] <27>

[0418] According to the sleep assistance system described in <1>,

[0419] The analysis unit calculates, based on one or more combinations of sleep parameters and temperature and humidity factors that are correlated with the determination, a range of values ​​of temperature and humidity factors suitable for the subject's sleep included in each of the more than one combinations.

[0420] <28>

[0421] According to the sleep assistance system described in <27>,

[0422] The information processing device further includes a determination unit that uses at least one of the calculated range and the most recent time-measured temperature data inside the clothing, humidity data inside the clothing, ambient temperature data, and ambient humidity data to determine whether the current environment is suitable for the subject's sleep, and if the current environment is not suitable for the subject's sleep, determines a coping method.

[0423] <29>

[0424] According to the sleep assistance system described in <28>,

[0425] The information processing device further comprises: a notification processing unit that notifies the user of the information processing device of at least one of the most recently measured data of the temperature inside the clothing, the humidity inside the clothing, the ambient temperature data, and the ambient humidity data, and at least one of the information indicating the calculated range.

[0426] <30>

[0427] According to the sleep assistance system described in <29>,

[0428] The notification processing unit notifies the user of at least one of the determination results indicating whether the current environment is suitable for the subject's sleep and the corresponding coping method.

[0429] <31>

[0430] An information processing device that can acquire data from multiple sensors.

[0431] The plurality of sensors includes at least one of a first sensor, a second sensor, and a third sensor.

[0432] The information processing device includes:

[0433] The receiving unit receives, from the first sensor, at least one of body movement data representing the subject's body movement and vital sign data representing the subject's vital signs; from the second sensor, at least one of clothing temperature data representing the temperature inside the clothing worn by the subject and clothing humidity data representing the humidity inside the clothing; and from the third sensor, at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment.

[0434] The sleep parameter calculation unit calculates at least one sleep parameter using at least one of the body movement data and the vital signs data.

[0435] The temperature and humidity factor calculation unit calculates multiple temperature and humidity factors using at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data; and

[0436] The analysis unit uses at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period to determine one or more combinations of sleep parameters and temperature and humidity factors that are correlated.

[0437] <32>

[0438] A sleep-aid method involves controlling an information processing device that acquires data from multiple sensors.

[0439] Multiple sensors include at least one of a first sensor, a second sensor, and a third sensor.

[0440] In the aforementioned sleep-aiding method,

[0441] The receiving unit of the information processing device receives at least one of the following from the first sensor: body movement data representing the subject's body movements and vital sign data representing the subject's vital signs.

[0442] The receiving unit of the information processing device receives, from the second sensor at least one of data representing the temperature inside the clothing worn by the subject (indicating the temperature inside the clothing) and data representing the humidity inside the clothing (indicating the humidity inside the clothing).

[0443] The receiving unit of the information processing device receives, from the third sensor at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment.

[0444] The sleep parameter calculation unit of the information processing device calculates at least one sleep parameter using at least one of the body movement data and the vital sign data.

[0445] The temperature and humidity factor calculation unit of the information processing device calculates multiple temperature and humidity factors using at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data.

[0446] The analysis unit of the information processing device uses at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period to determine one or more combinations of sleep parameters and temperature and humidity factors that are related.

[0447] <33>

[0448] A program executed by a computer that can acquire data from multiple sensors.

[0449] The plurality of sensors includes at least one of a first sensor, a second sensor, and a third sensor.

[0450] The program causes the computer to perform the following steps:

[0451] Receive at least one of body movement data representing the subject's body movements and vital sign data representing the subject's vital signs from the first sensor;

[0452] The second sensor receives at least one of the following: internal temperature data representing the temperature inside the clothing worn by the subject and internal humidity data representing the humidity inside the clothing.

[0453] The third sensor receives at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment.

[0454] At least one sleep parameter is calculated using at least one of the body movement data and the vital signs data;

[0455] Using at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data, calculate multiple temperature and humidity factors; and

[0456] Using at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period, determine one or more combinations of sleep parameters and temperature and humidity factors that are correlated.

[0457] -Symbol Explanation-

[0458] 1A Sleep Assist System

[0459] 21 Information processing device

[0460] 22 Air conditioning equipment

[0461] 30 Infants and toddlers

[0462] 31 Childcare Workers

[0463] 4 sensors

[0464] 41. Temperature and humidity sensor inside clothing

[0465] 42 Body motion sensors

[0466] 43 Vital Signs Sensors

[0467] 44 Ambient temperature and humidity sensor

[0468] 45. Camera device

[0469] 411 First Cover

[0470] 412 Second Cover

[0471] 413 Temperature Sensor Section

[0472] 414 Humidity Sensor Section

[0473] 415 Ministry of Communications

[0474] 416 Fasteners

[0475] 417 Opening

[0476] 51 CPU

[0477] 52 RAM

[0478] 53 Storage devices

[0479] 54 Touchscreen Displays

[0480] 55 First Ministry of Communications

[0481] 56 Second Ministry of Communications

[0482] 57 Vibrating section

[0483] 58 speakers

[0484] 521 OS

[0485] 522 Sleep Assistance Program

[0486] 530 Temperature data inside clothing

[0487] 531 Humidity data inside clothing

[0488] 532 body movement data

[0489] 533 Vital Signs Data

[0490] 534 Ambient Temperature Data

[0491] 535 Ambient humidity data

[0492] 536 Sleep Parameters

[0493] 537 Temperature and humidity factors

[0494] 538 Comfort Range Table

[0495] 539 Comfort Assessment Form

[0496] 540 Behavioral Data

[0497] 61 Receiving and Processing Department

[0498] 62 Storage and Processing Department

[0499] 63 Sleep Parameter Calculation Department

[0500] 64 Temperature and Humidity Factor Calculation Department

[0501] 65. Analysis Section

[0502] 66 Judgment Department

[0503] 67 Notification Processing Department

[0504] 68 Control Department

[0505] 69 Feedback Processing Department

[0506] 60 Generation Processing Department

[0507] 1B Sleep Assist System

[0508] 25 server devices

[0509] 26. Network.

Claims

1. A sleep assistance system, comprising an information processing device and multiple sensors, The plurality of sensors includes at least one of a first sensor, a second sensor, and a third sensor. The first sensor measures at least one of body movement data representing the subject's body movements and vital sign data representing the subject's vital signs. The second sensor measures at least one of the following: internal temperature data representing the temperature inside the clothing worn by the subject, and internal humidity data representing the humidity inside the clothing. The third sensor measures at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment. The information processing device includes: The sleep parameter calculation unit calculates at least one sleep parameter using at least one of the body movement data and the vital signs data. The temperature and humidity factor calculation unit calculates multiple temperature and humidity factors using at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data. as well as The analysis unit uses at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period to determine one or more combinations of sleep parameters and temperature and humidity factors that are correlated.

2. The sleep assistance system according to claim 1, wherein, The at least one sleep parameter includes at least one of the subject's sleep latency, sleep onset time, wake-up time, total sleep time, awakening time, number of awakenings, activity level per unit time, deep sleep occupancy, REM sleep occupancy, and sleep efficiency.

3. The sleep assistance system according to claim 2, wherein, The at least one sleep parameter also includes at least one of heart rate, heart rate variability, respiratory rate per unit time, and extremity skin temperature.

4. The sleep assistance system according to any one of claims 1 to 3, wherein, The plurality of temperature and humidity factors include at least one of the following: the statistical values ​​of ambient temperature, ambient humidity, temperature inside clothing, humidity inside clothing, the time it takes for the absorbent material worn by the subject to become wet, and the discomfort index during the period from the time the subject falls asleep to the time he wakes up.

5. The sleep assistance system according to any one of claims 1 to 4, wherein, The analysis unit calculates, based on one or more combinations of sleep parameters and temperature and humidity factors that are correlated with the determination, a range of suitable sleep values ​​for the subject for each of the more than one combinations of temperature and humidity factors. The information processing device further includes: a notification processing unit that notifies the user of the information processing device of information representing the calculated range.

6. The sleep assistance system according to claim 5, wherein, The notification processing unit further notifies the user of the information processing device of information representing at least one of the latest temperature data inside the clothing, humidity data inside the clothing, ambient temperature data, and ambient humidity data.

7. The sleep assistance system according to claim 6, wherein, The notification processing unit notifies the user of the information processing device that an image of at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data has been plotted within the calculated range, expressed in two-dimensional coordinates of temperature and humidity.

8. The sleep assistance system according to claim 5, wherein, The analytical unit The correlation between each of the at least one sleep parameter corresponding to sleep during the first period and each of the plurality of temperature and humidity factors corresponding to sleep during the first period is calculated using a regression line. Based on the combination of a first sleep parameter and a first temperature and humidity factor whose absolute value of the correlation coefficient of the calculated regression line is above a first threshold, the range of values ​​of the first temperature and humidity factor suitable for the sleep of the subject is calculated.

9. The sleep assistance system according to claim 8, wherein, The notification processing unit notifies the user of the information processing device of information indicating the range of the calculated values ​​of the first temperature and humidity factor.

10. The sleep assistance system according to claim 5, wherein, The analytical unit The correlation between each of the at least one sleep parameter corresponding to sleep during the first period and each of the plurality of temperature and humidity factors corresponding to sleep during the first period was calculated using regression lines and regression curves. Based on the combination of the first sleep parameter and the first temperature and humidity factor, where the coefficient of determination of the calculated regression line is above the second threshold, the range of values ​​for the first temperature and humidity factor suitable for the sleep of the subject is calculated. Based on the calculated regression curve, the combination of the second sleep parameter and the second temperature and humidity factor above the second threshold is used to calculate the range of values ​​of the second temperature and humidity factor suitable for the sleep of the subject.

11. The sleep assistance system according to claim 10, wherein, The notification processing unit notifies the user of the information processing device of information indicating the range of the calculated first temperature and humidity factor values ​​and information indicating the range of the calculated second temperature and humidity factor values.

12. The sleep assistance system according to claim 5, wherein, The analytical unit By performing a multiple regression analysis with the target variable being a first sleep parameter (one of the at least one sleep parameter corresponding to sleep during the first period) and the explanatory variables being the multiple temperature and humidity factors corresponding to sleep during the first period, a multiple regression equation for the first sleep parameter, in which the coefficients of each of the multiple temperature and humidity factors are calculated, is obtained. Based on the multiple regression equation, the range of values ​​for each of the multiple temperature and humidity factors suitable for the sleep of the subject is calculated.

13. The sleep assistance system according to claim 12, wherein, The notification processing unit notifies the user of the information processing device of information representing the range of values ​​for the calculated multiple temperature and humidity factors.

14. The sleep assistance system according to claim 5, wherein, The analytical unit By performing multiple regression analysis with each of the at least one sleep parameter corresponding to sleep during the first period as the target variable and the multiple temperature and humidity factors corresponding to sleep during the first period as the explanatory variables, at least one multiple regression equation is obtained, which calculates the coefficients of each of the multiple temperature and humidity factors and corresponds to the at least one sleep parameter. Based on the largest coefficient contained in each of the at least one multiple regression equations, N multiple regression equations are obtained from the at least one multiple regression equation. Based on the N multiple regression equations, calculate the range of values ​​for each of the multiple temperature and humidity factors suitable for the sleep of the subject. N is an integer greater than or equal to 1.

15. The sleep assistance system according to claim 5, wherein, The analysis unit calculates the range of values ​​of at least one sleep parameter corresponding to more than one day of sleep deemed to be of good quality by the subject, and the range of values ​​of the temperature and humidity factors included in each of the more than one combinations of sleep parameters with correlation to the determination, which are suitable for the subject's sleep.

16. The sleep assistance system according to claim 5, wherein, The analytical unit The correlation between each of the at least one sleep parameter corresponding to sleep during the first period and each of the plurality of temperature and humidity factors corresponding to sleep during the first period is calculated using a regression line. Based on the combination of a first sleep parameter and a first temperature and humidity factor whose absolute value of the correlation coefficient of the calculated regression line is above a first threshold, the range of values ​​of the first temperature and humidity factor suitable for the sleep of the subject is calculated using the first temperature and humidity factor corresponding to the sleep during the second period in which the sleep quality of the subject is determined to be good. Alternatively, based on the combination of a second sleep parameter and a second temperature and humidity factor whose determination coefficient of the calculated regression line is above a second threshold, the range of values ​​of the second temperature and humidity factor suitable for the sleep of the subject is calculated using the second temperature and humidity factor corresponding to the sleep during the second period.

17. The sleep assistance system according to claim 5, wherein, The analytical unit The correlation between each of the at least one sleep parameter corresponding to sleep during the first period and each of the plurality of temperature and humidity factors corresponding to sleep during the first period was calculated using regression curves. Based on the combination of the first sleep parameter and the first temperature and humidity factor, which is a factor of determination of the calculated regression curve above a first threshold, the range of values ​​of the first temperature and humidity factor suitable for the sleep of the subject is calculated using the first temperature and humidity factor corresponding to the sleep during the second period in which the subject's sleep quality is determined to be good.

18. The sleep assistance system according to claim 5, wherein, The analytical unit By performing multiple regression analysis with each of the at least one sleep parameter corresponding to sleep during the first period as the target variable and the multiple temperature and humidity factors corresponding to sleep during the first period as the explanatory variables, at least one multiple regression equation is obtained, which calculates the coefficients of each of the multiple temperature and humidity factors and corresponds to the at least one sleep parameter. Based on the largest coefficient contained in each of the at least one multiple regression equations, N multiple regression equations are obtained from the at least one multiple regression equation. Based on the N multiple regression equations, the range of values ​​for each of the multiple temperature and humidity factors suitable for the subject's sleep is calculated using the multiple temperature and humidity factors corresponding to the sleep during the second period when the subject's sleep quality was determined to be good. N is an integer greater than or equal to 1.

19. The sleep assistance system according to claim 5, wherein, The information processing device further includes a determination unit that uses at least one of the calculated range and the most recent measured temperature data inside the clothing, humidity data inside the clothing, ambient temperature data, and ambient humidity data to determine whether the current environment is suitable for the subject's sleep, and decides on a coping method if the current environment is not suitable for the subject's sleep. The notification processing unit notifies the user of at least one of the determination results indicating whether the current environment is suitable for the subject's sleep and the corresponding coping method.

20. The sleep assistance system according to claim 19, wherein, The information processing device further includes a control unit that controls the settings of an air conditioning device set in the environment based on the response method.

21. The sleep assistance system according to any one of claims 1 to 20, wherein, In cases where the subject is an infant, the first period varies depending on the subject's age in months.

22. The sleep assistance system according to any one of claims 1 to 21, wherein, The first sensor is installed either on the inside of the clothing worn by the subject or on the outer surface of the absorbent material or underwear worn by the subject. At least one of the body movement data and the vital signs data is measured on either the inside of the garment on which the first sensor is installed or on the outer surface of the absorbent material or the underwear.

23. The sleep assistance system according to any one of claims 1 to 21, wherein, The first sensor is a belt-shaped sensor that is installed on the subject's arm or leg. The first sensor, which is installed on the subject's arm or leg, measures at least one of the body movement data and the vital signs data.

24. The sleep assistance system according to any one of claims 1 to 23, wherein, The physical activity data includes the intensity and amount of activity of the subject. The vital signs data include the subject's heart rate, heart rate variability, respiratory rate, and skin temperature. The sleep parameter calculation unit uses at least one of the activity intensity, activity level, skin temperature, heart rate, heart rate variability, and respiratory rate to calculate the at least one sleep parameter.

25. The sleep assistance system according to any one of claims 1 to 24, wherein, The second sensor is installed either on the inside of the clothing worn by the subject or on the outer surface of the absorbent material or underwear worn by the subject. At least one of the temperature data inside the garment and the humidity data inside the garment is measured, either on the inside of the garment where the second sensor is installed or on the outer surface of the absorbent material or the underwear.

26. The sleep assistance system according to any one of claims 1 to 25, wherein, The third sensor was not installed on any of the clothing, the absorbent material worn by the subject, or the underwear worn by the subject.

27. The sleep assistance system according to claim 1, wherein, The analysis unit calculates, based on one or more combinations of sleep parameters and temperature and humidity factors that are correlated with the determination, a range of values ​​of temperature and humidity factors suitable for the subject's sleep included in each of the more than one combinations.

28. The sleep assistance system according to claim 27, wherein, The information processing device further includes a determination unit that uses at least one of the calculated range and the most recent time-measured temperature data inside the clothing, humidity data inside the clothing, ambient temperature data, and ambient humidity data to determine whether the current environment is suitable for the subject's sleep, and if the current environment is not suitable for the subject's sleep, determines a coping method.

29. The sleep assistance system according to claim 28, wherein, The information processing device further comprises: a notification processing unit that notifies the user of the information processing device of at least one of the most recently measured data of the temperature inside the clothing, the humidity inside the clothing, the ambient temperature data, and the ambient humidity data, and at least one of the information indicating the calculated range.

30. The sleep assistance system according to claim 29, wherein, The notification processing unit notifies the user of at least one of the determination results indicating whether the current environment is suitable for the subject's sleep and the corresponding coping method.

31. An information processing device capable of acquiring data from multiple sensors, The plurality of sensors includes at least one of a first sensor, a second sensor, and a third sensor. The information processing device includes: The receiving unit receives, from the first sensor, at least one of body movement data representing the subject's body movement and vital sign data representing the subject's vital signs; from the second sensor, at least one of clothing temperature data representing the temperature inside the clothing worn by the subject and clothing humidity data representing the humidity inside the clothing; and from the third sensor, at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment. The sleep parameter calculation unit calculates at least one sleep parameter using at least one of the body movement data and the vital signs data. The temperature and humidity factor calculation unit calculates multiple temperature and humidity factors using at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data. as well as The analysis unit uses at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period to determine one or more combinations of sleep parameters and temperature and humidity factors that are correlated.

32. A sleep-aiding method for controlling an information processing device that acquires data from multiple sensors. Multiple sensors include at least one of a first sensor, a second sensor, and a third sensor. In the aforementioned sleep-aiding method, The receiving unit of the information processing device receives at least one of the following from the first sensor: body movement data representing the subject's body movements and vital sign data representing the subject's vital signs. The receiving unit of the information processing device receives, from the second sensor at least one of data representing the temperature inside the clothing worn by the subject (indicating the temperature inside the clothing) and data representing the humidity inside the clothing (indicating the humidity inside the clothing). The receiving unit of the information processing device receives, from the third sensor at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment. The sleep parameter calculation unit of the information processing device calculates at least one sleep parameter using at least one of the body movement data and the vital sign data. The temperature and humidity factor calculation unit of the information processing device calculates multiple temperature and humidity factors using at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data. The analysis unit of the information processing device uses at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period to determine one or more combinations of sleep parameters and temperature and humidity factors that are related.

33. A program executed by a computer capable of acquiring data from multiple sensors. The plurality of sensors includes at least one of a first sensor, a second sensor, and a third sensor. The program causes the computer to perform the following steps: Receive at least one of body movement data representing the subject's body movements and vital sign data representing the subject's vital signs from the first sensor; The second sensor receives at least one of the following: internal temperature data representing the temperature inside the clothing worn by the subject and internal humidity data representing the humidity inside the clothing. The third sensor receives at least one of ambient temperature data representing the ambient temperature of the environment in which the subject is located and ambient humidity data representing the ambient humidity of the environment. At least one sleep parameter is calculated using at least one of the body movement data and the vital signs data; Calculate multiple temperature and humidity factors using at least one of the temperature data inside the clothing, the humidity data inside the clothing, the ambient temperature data, and the ambient humidity data; as well as Using the at least one sleep parameter corresponding to the sleep during the first period and the plurality of temperature and humidity factors corresponding to the sleep during the first period, determine one or more combinations of sleep parameters and temperature and humidity factors that are correlated.

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