JP2016218563A - Information processing device, program, information processing method, and information processing system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing device or the like for simply evaluating a fatigue recovery degree before and after sleep.SOLUTION: The information processing device includes an acquisition unit for acquiring sleep data of an object person, an extraction unit for extracting a recovery degree associated with sleep data similar to the sleep data acquired from a storage unit which associates sleep data with recovery degrees by the acquisition unit, and an output unit for outputting information on the recovery degree extracted by the extraction unit.SELECTED DRAWING: Figure 7

Description

  The present invention relates to an information processing apparatus, a program, an information processing method, and an information processing system.

  A fatigue evaluation method for evaluating the fatigue level of a subject using the amount of human herpesvirus contained in body fluid such as saliva as an index is disclosed (Patent Document 1).

  A sleep evaluation device that detects biological information during sleep of a subject, calculates a sleep evaluation score for each item such as sleep depth and sleep rhythm, and determines the sleep type of the subject is disclosed (Patent Document) 2).

JP 2007-330263 A JP2013-165828A

  However, in the evaluation method of Patent Document 1, it is necessary to measure the amount of human herpesvirus contained in the body fluid. In order to measure the amount of human herpesvirus, the amount of human herpesvirus DNA (DeoxyRibonucleic Acid) is measured using a technique such as PCR (Polymerase Chain Reaction). Special measuring devices and reagents are required and time is required. Therefore, it is not suitable for the purpose of simply evaluating the change in the degree of fatigue before and after sleep in daily life, that is, the degree of recovery from fatigue due to sleep.

  Moreover, in patent document 2, it is neither indicated nor suggested about evaluation of the fatigue recovery degree before and after sleep.

  In one aspect, an object of the present invention is to provide an information processing apparatus and the like that easily evaluates the degree of fatigue recovery before and after sleep.

  In one aspect, the information processing apparatus of the present invention is similar to sleep data acquired by the acquisition unit with reference to an acquisition unit that acquires sleep data of the subject and a storage unit that associates sleep data with the degree of recovery. An extraction unit that extracts a degree of recovery associated with sleep data and an output unit that outputs information on the degree of recovery extracted by the extraction unit.

  In one aspect, it is possible to provide an information processing apparatus or the like that simply evaluates the degree of fatigue recovery before and after sleep.

It is explanatory drawing which shows the structure of an information processing system. It is explanatory drawing which shows the record layout of recovery degree DB. It is explanatory drawing which shows the example of a sleep depth change graph. It is explanatory drawing which shows the example of a heart rate change graph. It is explanatory drawing which shows the record layout of comparison DB. It is explanatory drawing which shows the calculation method of similarity. It is explanatory drawing which shows the screen displayed on a portable information device. It is a flowchart which shows the flow of a process of a program. It is a flowchart which shows the flow of a process of the subroutine of similarity calculation. It is explanatory drawing which shows the record layout of recovery degree DB of Embodiment 2. FIG. FIG. 10 is an explanatory diagram illustrating a configuration of an information processing system according to a third embodiment. It is explanatory drawing which shows the record layout of performance DB of Embodiment 3. FIG. 10 is an explanatory diagram illustrating a screen displayed on the portable information device of Embodiment 3. FIG. 12 is a flowchart illustrating a processing flow of a program according to the third embodiment. FIG. 10 is an explanatory diagram illustrating a configuration of an information processing system according to a fourth embodiment.

[Embodiment 1]
FIG. 1 is an explanatory diagram illustrating a configuration of the information processing system 10. The information processing system 10 includes a portable information device 35, a client 20, and a server 40 connected via a network 31. Note that a plurality of clients 20 and portable information devices 35 may be connected to the network 31.

  The portable information device 35 is a small information device including a display unit and a wireless communication unit. The portable information device 35 is a general-purpose portable information device such as a smartphone, a multifunctional mobile phone, or a tablet. Further, a portable or wall-mounted information device dedicated to the information processing system 10 may be used for the portable information device 35.

  The client 20 is a control device that controls a sensor installed in the user's bedroom. The client 20 includes a client CPU (Central Processing Unit) 21, a main storage device 22, an auxiliary storage device 23, a sensor I / F (InterFace) 24, a communication unit 26, and a bus. The client 20 may use a home energy management system (HEMS) control device connected to a sensor, a solar cell, or the like attached inside or outside the house. Moreover, you may use information apparatuses, such as a general purpose personal computer, a tablet, and a smart phone, for the client 20. FIG.

  The client CPU 21 is an arithmetic control device that controls the client 20. As the client CPU 21, one or a plurality of CPUs, a multi-core CPU, or the like is used. The client CPU 21 is connected to each hardware unit constituting the client 20 via a bus.

  The main storage device 22 is a storage device such as SRAM (Static RAM), DRAM (Dynamic RAM), flash memory, or semiconductor memory disk. The main storage device 22 temporarily stores information necessary during the processing performed by the client CPU 21 and a program being executed by the client CPU 21.

  The auxiliary storage device 23 is a storage device such as SRAM, DRAM, flash memory, semiconductor memory disk, or hard disk. The auxiliary storage device 23 stores a program to be executed by the client CPU 21 and various information necessary for executing the program.

  The sensor I / F 24 is an interface that receives signals from various sensors connected to the client 20. The communication unit 26 communicates with the network 31. The communication unit 26 is used for exchanging information with the portable information device 35 and the server 40.

  A sleep sensor 25 is connected to the client 20 via a sensor I / F 24. The sleep sensor 25 is a sheet-like sensor, for example, and is installed between the bed mattress and the sheet. The sleep sensor 25 detects the pulse, respiration, body movement, body temperature, and the like of a person lying on the bed. The sleep sensor 25 and the client 20 may be integrated.

  The sleep sensor 25 may be a sensor that is installed on the bed bed or the wall of the room and detects the pulse, respiration, body movement, body temperature, etc. of the person lying on the bed by microwaves or infrared rays.

  The sleep sensor 25 outputs the detected information to the sensor I / F 24. The sleep sensor 25 analyzes the detected information and outputs a sleep state such as REM sleep to the sensor I / F 24. Note that the sleep sensor 25 does not analyze information, and the client CPU 21 or a server CPU 41 described later may analyze the information.

  The server 40 includes a server CPU 41, a main storage device 42, an auxiliary storage device 43, a communication unit 46, and a bus. The server 40 is an information processing device such as a large computer or a general-purpose personal computer or tablet installed in the data center.

  The server CPU 41 is an arithmetic control device that executes a program according to the present invention. As the server CPU 41, one or a plurality of CPUs, a multi-core CPU, or the like is used. The server CPU 41 is connected to each hardware part constituting the server 40 via a bus.

  The main storage device 42 is a storage device such as SRAM (Static RAM), DRAM (Dynamic RAM), flash memory, or semiconductor memory disk. The main storage device 42 temporarily stores information necessary during the processing performed by the server CPU 41 and a program being executed by the server CPU 41.

  The auxiliary storage device 43 is a storage device such as SRAM, DRAM, flash memory, semiconductor memory disk, or hard disk. The auxiliary storage device 43 stores a program to be executed by the server CPU 41, a recovery degree DB (DataBase) 51, and a comparison DB 52.

  The communication unit 46 communicates with the network 31. The communication unit 46 is used for exchanging information with the client 20 and the portable information device 35 and updating various DBs stored in the auxiliary storage device 43.

  FIG. 2 is an explanatory diagram showing a record layout of the recovery degree DB 51. FIG. 3 is an explanatory diagram illustrating an example of a sleep depth change graph. FIG. 4 is an explanatory diagram illustrating an example of a heart rate change graph. The recovery degree DB 51 will be described with reference to FIGS.

  The recovery degree DB 51 is a DB that associates individual attributes, the recovery degree due to sleep, and sleep data. Sleep data is data indicating the state of a sleeping person, such as sleep depth, pulse, body temperature, body movement, and the like. The sleep data includes data obtained from one type of sensor and data obtained by processing data obtained from a plurality of sensors. It should be noted that the time when the person is in bed for sleep but is awake is included in the sleep.

  The recovery degree DB 51 has a number field, a personal data field, a recovery degree data field, and a sleep data field. The recovery degree DB 51 has one record for one person's overnight sleep. The degree of recovery DB 51 is a DB in which results of evaluating sleep data and changes in fatigue level before and after sleep in advance at a well-equipped medical institution or the like are recorded.

  In the number field, a record-specific number is recorded. The personal data field includes an age field and a gender field. In the age field, the age of the individual is recorded. In the gender field, the individual gender is recorded.

  The recovery degree data field includes a pre-sleeping fatigue degree field, a wake-up fatigue degree field, and a recovery degree field. The fatigue level before going to bed is recorded in the fatigue level before going to bed. In the wake-up fatigue level field, the wake-up fatigue level is recorded. In the recovery level field, the difference between the fatigue level before going to bed and the fatigue level when waking up is recorded.

  Here, the fatigue level will be described. Various methods for quantitatively evaluating human fatigue have been proposed. For example, as shown in Patent Document 1, the degree of fatigue can be evaluated from the amount of human herpesvirus in saliva. A human herpesvirus is a virus that is retained in the salivary gland and the like in a latently infected state once infected. Most adults carry human herpesvirus. When immunity decreases with the accumulation of fatigue, the latently infected human herpesvirus is reactivated. Therefore, the degree of fatigue can be evaluated from the amount of human herpesvirus in saliva. The degree of fatigue before going to bed is evaluated using the amount of human herpesvirus in saliva collected just before going to bed. The degree of fatigue when waking up is evaluated using the amount of human herpesvirus in saliva collected immediately after waking up. The degree of recovery by sleep can be evaluated from the difference between the degree of fatigue before sleep and the degree of fatigue when waking up.

  The sleep data field includes a sleep depth change field and a heart rate change field. In the sleep depth change field, data indicating a change in sleep depth during sleep is recorded. In the heart rate change field, data indicating a change in heart rate during sleep is recorded.

  FIG. 3 is an example of data recorded in the sleep data field. The horizontal axis shows the elapsed time from when a person enters the bed until he gets up. The unit of the horizontal axis is time. The vertical axis indicates the sleep depth. The depth of sleep is shown in 6 stages of wakefulness, REM sleep, stage 1, stage 2, stage 3 and stage 4. Awakening is a state of awakening. REM sleep is a shallow sleep state in which the body is sleeping but the brain is active. Stages 1 to 4 are called non-REM sleep. The larger the number, the deeper the sleep. Of these, sleep stage 3 and sleep stage 4 indicate a state of deep sleep. FIG. 3 shows a state in which the user wakes up during the non-REM sleep by repeating the REM sleep and the non-REM sleep after a good sleep about 30 minutes after entering the bed.

  FIG. 4 is an example of data recorded in the heart rate change field. The horizontal axis shows the elapsed time from when a person enters the bed until he gets up. The unit of the horizontal axis is time. The vertical axis represents the heart rate. FIG. 4 shows a state where the heart rate is changing during sleep.

  The information processing system 10 according to the present embodiment uses the recovery degree DB 51 described above and sleep data acquired from the sleep sensor 25 installed in the user's bedroom to estimate the degree of recovery of the user due to the night's sleep. And display.

  FIG. 5 is an explanatory diagram showing a record layout of the comparison DB 52. FIG. 6 is an explanatory diagram showing a method of calculating the similarity. A method for estimating the degree of recovery will be described with reference to FIGS. 5 and 6.

  The comparison DB 52 is a DB that associates the result of comparing the number of each record extracted from the recovery degree DB 51 with the sleep data recorded in the recovery degree DB 51 and the sleep data acquired from the sleep sensor 25. The comparison DB 52 includes a number field, a sleep depth coefficient field, a heart rate coefficient field, and an overall point field. The comparison DB 52 has one record for each record compared in the recovery degree DB 51. The comparison DB 52 is a DB that is newly created every time the user gets up.

  The extraction of records from the recovery degree DB 51 will be described. A record in which the attribute recorded in the personal data field of the recovery degree DB 51 matches the user's attribute is extracted. In the present embodiment, a case where a record of a male in his 20s is extracted from each record shown in FIG. 2 will be described as an example.

  In the number field, the number of the record recorded in the recovery degree DB 51 is recorded. In the sleep depth coefficient field, a value obtained by scoring the degree of similarity is recorded by comparing the sleep depth change data recorded in the recovery degree DB 51 with the sleep depth change data acquired from the sleep sensor 25. Has been. In the heart rate coefficient field, the heart rate change data recorded in the recovery degree DB 51 and the heart rate change data acquired from the sleep sensor 25 are compared, and a value obtained by scoring the degree of similarity is recorded. Has been. In the comprehensive point field, a value obtained as a result of comprehensive evaluation of the value of the sleep depth coefficient field and the value of the heart rate coefficient is recorded.

  6A to 6D are diagrams illustrating an example of a method for scoring the degree of similarity. The horizontal axis of FIGS. 6A to 6D is common, and shows the elapsed time from when a person enters the bed to when he / she wakes up. The unit of the horizontal axis is time. The vertical axis | shaft of FIG. 6A shows sleep depth. FIG. 6A shows data acquired from the sleep sensor 25. The vertical axis in FIG. 6B also shows the sleep depth. FIG. 6B shows data recorded in the sleep depth change field of the recovery degree DB 51. In the subsequent processing, wakefulness is scored as zero, REM sleep is minus 1, stage 1 is minus 2, stage 2 is minus 3, stage 3 is minus 4, and stage 4 is minus 5.

  The vertical axis in FIG. 6C indicates the difference obtained by subtracting the value in FIG. 6A from the value in FIG. 6B for each time. The vertical axis in FIG. 6D indicates a value obtained by squaring the value in FIG. 6C for each time. Let the average value of the value of the vertical axis | shaft about each time of FIG. 6D be a score which shows the degree to which it is similar. In the example of FIG. 6D, the score is 3.4. If the graph of FIG. 6B matches the graph of FIG. 6A, the score is zero. When the difference between the graph of FIG. 6A and the graph of FIG. 6A is large, the score is large. The score indicating the degree of similarity of the heart rate is also calculated by the same method.

  FIG. 7 is an explanatory diagram showing a screen displayed on the portable information device 35. The portable information device 35 displays the screen of FIG. 7 after the user wakes up. On the screen, a recovery degree column 61, a sleep time column 62, a deep sleep time column 63, and a sleep depth column 64 are displayed. In the recovery degree column 61, the degree of recovery estimated from the sleep data acquired from the sleep sensor 25 during sleep is described. The recovery degree uses the value of the recovery degree field of the record extracted from the recovery degree DB 51 using the number recorded in the number field of the record having the lowest score in the total point field of FIG. 5 as a key. Here, when a plurality of records are extracted, the average value of the recovery field of each record is used.

  In the sleep time column 62, the total time of REM sleep and non-REM sleep is displayed. In the deep sleep time column 63, the total time of the sleep depth 3 and the sleep depth 4 is displayed. In the sleep depth column 64, a graph showing a temporal change in the sleep depth acquired by the sleep sensor 25 is displayed. The horizontal axis shows the elapsed time from when a person enters the bed until he gets up. The unit of the horizontal axis is time. The vertical axis indicates the sleep depth.

  FIG. 8 is a flowchart showing the flow of processing of the program. The process flow of the program according to this embodiment will be described with reference to FIG.

  The client CPU 21 acquires sleep data from the sleep sensor 25 via the sensor I / F 24 (step S501). The sleep data is continuously acquired after the user gets on the floor and stored in the auxiliary storage device 23.

  The client CPU 21 detects that the user has woken up from the change in sleep data (step S502). The client CPU 21 transmits user information to the server 40 via the communication unit 26 and the network 31 (step S503). The user information is data indicating attributes such as the user's age and sex.

  The server CPU 41 receives user information via the network 31 and the communication unit 46 (step S601). The server CPU 41 searches the recovery degree DB 51 and extracts a person record having an attribute similar to the user information (step S602). A case where a record of a male in his 20s is extracted will be described as an example.

  The client CPU 21 transmits sleep data to the server 40 via the communication unit 26 and the network 31 (step S504). Thereafter, the client CPU 21 ends the process.

  The server CPU 41 receives sleep data via the network 31 and the communication unit 46 (step S603). The server CPU 41 activates a subroutine for calculating similarity (step S604). The similarity calculation subroutine compares the sleep data acquired from the sleep sensor 25 with the sleep data recorded in the record extracted in step S602 to calculate the similarity, that is, a score indicating the degree of similarity. This is a subroutine for creating the comparison DB 52. The flow of processing of the similarity calculation subroutine will be described later.

  The server CPU 41 extracts a record having a higher similarity from the comparison DB 52, that is, a record having a low overall score. The server CPU 41 searches the recovery degree DB 51 using the record number field extracted from the comparison DB 52 as a key, and extracts a matching record. As described above, the server CPU 41 extracts a record having a higher similarity with the sleep data acquired by the sleep sensor 25. (Step S605).

  The server CPU 41 calculates a user recovery level from the value recorded in the recovery level field of the extracted record (step S606). If there is one record extracted in step S605, the value recorded in the recovery degree record of that record is used as the user's recovery degree. If there are a plurality of records extracted in step S605, the average value of the values recorded in the recovery degree records of those records is used as the user's recovery degree.

  The server CPU 41 transmits the degree of recovery and the like to the portable information device 35 via the communication unit 46 and the network 31 (step S607). The server CPU 41 then ends the process. The portable information device 35 receives the degree of recovery and the like via the network 31 (step S701). The portable information device 35 displays the degree of recovery or the like on the display unit (step S702). The screen displayed here is, for example, the screen described in FIG. The portable information device 35 thereafter ends the process.

  FIG. 9 is a flowchart showing the flow of processing of a subroutine for calculating similarity. The similarity calculation subroutine compares the sleep data acquired from the sleep sensor 25 with the sleep data recorded in the record extracted in step S602 to calculate the similarity, that is, a score indicating the degree of similarity. This is a subroutine for creating the comparison DB 52.

  The server CPU 41 sets the counter I to the initial value 1 (step S621). The server CPU 41 extracts the I-th record from the records extracted in step S602. The server CPU 41 records the value recorded in the number field of the extracted record in the number field of the I-th record in the comparison DB 52. The server CPU 41 obtains sleep depth data recorded in the sleep depth change field of the extracted record (step S622).

  The server CPU 41 obtains a difference between the sleep depth data acquired from the sleep depth change field for each elapsed time and the sleep depth data acquired from the sleep sensor 25 (step S623). FIG. 6C described above is an example of the result obtained in step S623.

  The server CPU 41 squares the difference value obtained in step S623 for each elapsed time (step S624). FIG. 6D described above is an example of the result obtained in step S624. The server CPU 41 calculates the average value of the values obtained in step S624. Thereafter, this average value is set as a sleep depth coefficient (step S625). The server CPU 41 records the sleep depth coefficient in the sleep depth coefficient field of the I-th record in the comparison DB 52.

  The server CPU 41 acquires the heart rate data recorded in the heart rate change field of the I-th record among the records extracted in step S602 (step S626). The server CPU 41 obtains a difference between the heart rate data acquired from the heart rate field for each elapsed time and the heart rate data acquired from the sleep sensor 25 (step S627).

  The server CPU 41 squares the difference value obtained in step S627 for each elapsed time (step S628). The server CPU 41 calculates an average value of the values obtained in step S628. Thereafter, this average value is set as the heart rate coefficient (step S629). The server CPU 41 records the heart rate coefficient in the heart rate coefficient field of the I-th record in the comparison DB 52.

  Server CPU41 calculates | requires the average value of a sleep depth coefficient and a heart rate coefficient. Hereinafter, this average value is set as a total score (step S630). The server CPU 41 records the total score in the total score field of the I-th record in the comparison DB 52.

  The server CPU 41 determines whether or not to end the process (step S631). The case where the processing is ended is a case where the processing of all the records extracted in step S602 is ended. If it is determined that the process is to be ended (YES in step S631), the server CPU 41 ends the process. If it is determined not to end the process (NO in step S631), the server CPU 41 adds 1 to the counter I (step S632). The server CPU 41 returns to step S622.

  According to the present embodiment, it is possible to provide an information processing apparatus that simply evaluates the degree of fatigue recovery before and after sleep.

  The screen of FIG. 7 may be displayed on the display unit of the portable information device 35 according to the operation of the portable information device 35 by the user. Daily data may be stored in the auxiliary storage device 43 and data of an arbitrary date may be displayed on the display unit of the portable information device 35 based on a user instruction. By doing so, the user can view the degree of recovery at a convenient time such as during commuting and can use it for health care.

  When a general-purpose personal computer or the like is used for the client 20, the screen of FIG. 7 may be displayed on the display device of the client 20. Further, the degree of recovery or the like may be output by voice without using the screen.

  Instead of using the server 40 and the portable information device 35, the client CPU 21 may perform a process of calculating the degree of recovery, and display the result on the display unit of the client 20. By doing so, the degree of recovery can be calculated by a stand-alone device that is not connected to the network, so that the information processing system 10 of the present embodiment can be easily installed and used. Furthermore, when the client 20 and the sleep sensor 25 are integrated, the information processing system 10 of the present embodiment can be used more easily.

  In the recovery degree data field of the recovery degree DB 51, arbitrary data indicating changes in the state of the person before and after sleeping can be used. For example, a subjective change in fatigue obtained by a method such as a questionnaire may be used. Moreover, you may use the value which shows the change before and after sleep of mental ability, such as processing ability obtained by the Kraepelin test | inspection.

  The similarity calculation method described with reference to FIGS. 6 and 9 is an example. An arbitrary method such as pattern matching may be used to evaluate the degree of similarity between the two data.

  In step S602, similar records may be extracted using attributes such as pre-existing disease, obesity level, blood pressure, and occupation. In this case, information regarding these attributes is recorded in advance in the personal data field of the recovery degree DB 51.

  In step S606, the degree of recovery may be calculated using only one of sleep depth change and heart rate change. Further, for example, data such as body temperature change during sleep, body movement such as turning over, and respiratory rate may be used as sleep data. By using many types of data, the degree of recovery can be calculated more accurately.

  In step S630, the total score may be calculated by weighting the similarity of the change in sleep depth and the similarity of the change in heart rate.

[Embodiment 2]
The second embodiment relates to the information processing system 10 in which representative values are recorded in each field of the sleep data field of the recovery degree DB 51 instead of time-series data.

  FIG. 10 is an explanatory diagram illustrating a record layout of the recovery degree DB 51 according to the second embodiment. The recovery degree DB 51 in FIG. 10 is a DB used instead of the recovery degree DB 51 described in FIG. The information processing system 10 according to the second embodiment will be described with reference to FIG. Note that description of portions common to the first embodiment is omitted.

  The recovery degree DB 51 is a DB that associates individual attributes, the recovery degree due to sleep, and sleep data. The recovery degree DB 51 has a number field, a personal data field, a recovery degree data field, and a sleep data field. The recovery degree DB 51 has one record for one person's overnight sleep. The number field, personal data field, and recovery degree data field are the same as in the first embodiment.

  The sleep data field includes a deep sleep time field and an average body temperature field. In the deep sleep time field, the total value of the sleep depth 3 and the sleep depth 4 is recorded. Data indicating the average body temperature during sleep is recorded in the average body temperature field.

  Data corresponding to the information in the sleep data field of the recovery degree DB 51 in FIG. 10 is extracted from the sleep data acquired from the sleep sensor 25, and similar to the first embodiment using the similarity calculation subroutine of FIG. Calculate the degree. However, step S625 and step S629 for obtaining a time-series average value are omitted.

  According to the present embodiment, a constant is recorded in each data of the sleep data field, so that the capacity of the recovery degree DB 51 can be reduced. Also, the calculation amount of the subroutine for calculating the similarity can be reduced.

  The sleep data field may include both time-series data such as changes in sleep depth and representative values such as average body temperature.

[Embodiment 3]
The third embodiment relates to an information processing system 10 that records a recovery record and proposes a sleep environment in which a high recovery degree is obtained. FIG. 11 is an explanatory diagram illustrating a configuration of the information processing system 10 according to the third embodiment. The configuration of the information processing system 10 according to the third embodiment will be described with reference to FIG. Note that description of portions common to the first embodiment is omitted.

  The information processing system 10 includes a portable information device 35, a client 20, and a server 40 connected via a network 31.

  A sleep sensor 25, a room temperature sensor 28, and a humidity sensor 29 are connected to the client 20 via a sensor I / F 24. The room temperature sensor 28 is a sensor that measures the room temperature of the bedroom. The humidity sensor 29 is a sensor that measures the humidity of the bedroom.

  The auxiliary storage device 43 stores a program to be executed by the server CPU 41, a recovery degree DB 51, a comparison DB 52, and a performance DB 53.

  FIG. 12 is an explanatory diagram illustrating a record layout of the performance DB 53 according to the third embodiment. The record DB 53 is a DB that records a specific individual's sleep index and bedroom environmental data in association with each other. Here, the pleasant sleep index is an index indicating the comfort of sleep, and the larger one indicates that a comfortable sleep is obtained. For the sleep index, for example, the degree of recovery before and after sleep can be used. For the sleep index, a numerical value indicating the activity of awakening action such as the reciprocal of the time from waking up to getting out of bed may be used. You may use the ratio of the time when the user slept with respect to the time when the user went into bed. In addition, the user who gets up may determine a subjective sleep index.

  The performance DB 53 includes a number field, a personal data field, and an environment data field. The personal data field has a date field and a sleep index field. The environmental data field has an average temperature field and an average humidity field. The record DB 53 has one record for each sleep.

  In the number field, a number unique to each record recorded in the record DB 53 is recorded. In the date field, the date when the user got up is recorded. The aforementioned sleep index is recorded in the sleep index field. In the average temperature field, the average value of the room temperature while the user is sleeping is recorded. In the average humidity field, an average value of indoor humidity while the user is sleeping is recorded.

  Each time the user wakes up, the server CPU 41 creates a new record in the performance DB 53, and records the number, date, pleasant sleep index, average temperature, and average humidity in each field.

  FIG. 13 is an explanatory diagram illustrating a screen displayed on the portable information device 35 according to the third embodiment. The portable information device 35 displays the screen of FIG. 13 when the user instructs to display the recommended sleep environment. A recommended temperature column 65 and a recommended humidity column 66 are displayed on the screen. In the recommended temperature column 65, the recommended temperature obtained from the record of the day when the high sleep index is recorded is described. In the recommended humidity column 66, the recommended humidity obtained from the record on the day when the high sleep index is recorded.

  FIG. 14 is a flowchart showing a flow of processing of the program according to the third embodiment. The process flow of the program according to the third embodiment will be described with reference to FIG.

  When the user instructs to display the recommended sleep environment by operating the portable information device 35, the portable information device 35 transmits a request via the network 31 (step S721). The server CPU 41 receives the request via the network 31 and the communication unit 46 (step S651). The server CPU 41 searches the record DB 53 and extracts a record in which a numerical value equal to or greater than a predetermined first threshold is recorded in the sleepiness index field (step S652).

  The server CPU 41 calculates a good environment coefficient from the extracted record (step S653). Here, the good environment coefficient is a representative value of each of the average temperature field and the average humidity field of the record extracted in step S652. For example, the average value of each field is used as the representative value.

  The server CPU 41 searches the record DB 53 and extracts a record in which a numerical value less than a predetermined second threshold value is recorded in the pleasant sleep index field (step S654). Here, the second threshold is a numerical value equal to or smaller than the first threshold. Note that the same value may be used for the first threshold and the second threshold.

  The server CPU 41 calculates a defective environment coefficient from the extracted record (step S655). Here, the defective environment coefficient is a representative value of each of the average temperature field and the average humidity field of the record extracted in step S654. For example, the average value of each field is used as the representative value.

  The server CPU 41 determines whether or not there is a significant difference between the good environment coefficient calculated in step S653 and the bad environment index calculated in step S655 (step S656). The presence or absence of a significant difference is determined by, for example, a statistical test.

  If it is determined that there is a significant difference (YES in step S656), the server CPU 41 transmits the recommended sleep environment to the portable information device 35 via the communication unit 46 and the network 31 (step S657). The server CPU 41 then ends the process.

  If it is determined that there is no significant difference (NO in step S656), the server CPU 41 transmits a message indicating that the recommended sleep environment cannot be calculated to the portable information device 35 via the communication unit 46 and the network 31 (step S658). The server CPU 41 then ends the process.

  The portable information device 35 receives the information transmitted in step S657 or step S658 (step S723). The portable information device 35 displays the received information on the display unit (step S724). If it is determined in step S656 that there is a significant difference (YES in step S656), for example, the screen shown in FIG. 13 is displayed. If it is determined in step S656 that there is no significant difference (NO in step S656), for example, a message “Recommended sleep environment could not be calculated” is displayed. The portable information device 35 thereafter ends the process.

  According to the present embodiment, it is possible to realize the information processing system 10 that accumulates the daily sleep sleep index and sleep environment data and proposes an environment in which a more comfortable sleep can be obtained.

  For example, noise, oxygen concentration, carbon dioxide concentration, and the like may be recorded in the environmental data field. By using a lot of environmental data, the information processing system 10 that can propose a more comfortable sleep environment can be realized. Further, data indicating a time-series change may be used in the environment data field. By doing in this way, the information processing system 10 which proposes the environment which can obtain comfortable sleep from the time of sleep to the time of awakening can be provided.

  In step S657, the recommended sleep environment may be transmitted to the air conditioner in the bedroom. By doing so, it is possible to provide the information processing system 10 that automatically sets the bedroom to an environment where a comfortable sleep can be obtained. In this case, for example, the recommended sleep environment may be calculated once a week without waiting for the reception of the request from the portable information device in step S651. By doing in this way, the information processing system 10 which sets a bedroom environment automatically according to a change of a season and a user's physical condition can be provided.

[Embodiment 4]
The fourth embodiment relates to a mode in which the portable information device 35, the client 20, the server 40, and the program 71 are operated in combination.

  FIG. 15 is an explanatory diagram illustrating a configuration of the information processing system 10 according to the fourth embodiment. The configuration of this embodiment will be described with reference to FIG. Note that description of portions common to the first embodiment is omitted.

  The information processing system 10 includes a portable information device 35, a client 20, and a server 40 connected via a network 31. The portable information device 35 is a small information device including a display unit and a wireless communication unit. The client 20 includes a client CPU 21, a main storage device 22, an auxiliary storage device 23, a sensor I / F 24, a communication unit 26, and a bus. A sleep sensor 25, a room temperature sensor 28, and a humidity sensor 29 are connected to the client 20 via a sensor I / F 24.

  The server 40 includes a server CPU 41, a main storage device 42, an auxiliary storage device 43, a communication unit 46, a reading unit 47, and a bus. The reading unit 47 is a device that reads the portable recording medium 72, and specifically, for example, a micro SD (Secure Digital) card slot, a disk drive, or the like.

  The program 71 is recorded on a portable recording medium 72. The server CPU 41 reads the program 71 via the reading unit 47 and stores it in the auxiliary storage device 43. The server CPU 41 may read a program 71 stored in a semiconductor memory 73 such as a flash memory mounted in the server 40. Further, the server CPU 41 may download the program 71 from another server computer (not shown) connected via the communication unit 46 and store it in the auxiliary storage device 43.

  A portion of the program 71 executed by the client 20 is transmitted to the client 20 via the communication unit 46 and the network 31 and stored in the auxiliary storage device 23. A portion of the program 71 executed by the portable information device 35 is transmitted to the portable information device 35 via the communication unit 46 and the network 31 and stored in the auxiliary storage device of the portable information device 35. Note that each of the client 20 and the portable information device 35 may download the program via the network 31.

  The server CPU 41 reads the program 71 for executing the above-described various software processes from the portable recording medium 72 or the semiconductor memory 73 or downloads it from another server computer (not shown) via the communication unit 46. The program 71 is installed as a control program for the server 40, loaded into the main storage device 42, and executed by the server CPU 41.

  The client CPU 21 reads the transmitted program 71 from the auxiliary storage device 23. The program 71 is installed as a control program for the client 20, loaded into the main storage device 22, and executed by the client CPU 21. Similarly, the program 71 is installed as a control program for the portable information device 35, loaded into the main storage device of the portable information device 35, and executed by the CPU of the portable information device 35. As described above, the information processing system functions as the information processing system 10 described above as a whole.

The technical features (components) described in each embodiment can be combined with each other, and new technical features can be formed by combining them.
The embodiments disclosed herein are illustrative in all respects and should not be considered as restrictive. The scope of the present invention is defined not by the above-described meaning but by the scope of the claims, and is intended to include all modifications within the meaning and scope equivalent to the scope of the claims.

10 Information processing system 20 Client 21 Client CPU
22 Main storage device 23 Auxiliary storage device 24 Sensor I / F
25 Sleep Sensor 26 Communication Unit 28 Room Temperature Sensor 29 Humidity Sensor 31 Network 35 Portable Information Device 40 Server 41 Server CPU
42 Main storage device 43 Auxiliary storage device 46 Communication unit 47 Reading unit 51 Recovery degree DB
52 Comparison DB
53 Results DB
61 Recovery degree column 62 Sleep time column 63 Deep sleep time column 64 Sleep depth column 65 Recommended temperature column 66 Recommended humidity column 71 Program 72 Portable recording medium 73 Semiconductor memory

Claims (12)

An acquisition unit for acquiring sleep data of the target person;
An extraction unit that extracts a recovery level associated with sleep data similar to the sleep data acquired by the acquisition unit with reference to a storage unit that associates sleep data with a recovery level;
An information processing apparatus comprising: an output unit that outputs information on the degree of recovery extracted by the extraction unit. The information processing apparatus according to claim 1, wherein the degree of recovery associated with the sleep data is determined based on a change in biological data before and after sleep. The information processing apparatus according to claim 2, wherein the biological data is a concentration of a predetermined component in the body fluid. A first acquisition unit that acquires sleep data of the subject;
A second acquisition unit for acquiring environmental data of a sleeping place;
A recording unit for recording the sleep index determined based on the sleep data in association with the environmental data;
An extraction unit for extracting a sleep index satisfying a predetermined condition from the recording unit;
An information processing apparatus comprising: an output unit that outputs information related to environmental data associated with the sleep index extracted by the index extraction unit. The information processing apparatus according to claim 4, wherein the sleep index is a value indicating time of a predetermined sleep depth. The information processing apparatus according to claim 4, wherein the sleep index is a value indicating a change in biological data before and after sleep. With reference to the storage unit that associates the sleep data with the degree of recovery, the degree of recovery associated with the sleep data similar to the acquired sleep data of the subject is extracted,
A program for causing a computer to execute processing for outputting information on the degree of recovery. From the information recorded by associating the sleep index determined based on the acquired sleep data of the subject and the acquired environmental data of the sleeping place, a sleep index satisfying a predetermined condition is extracted,
A program that causes a computer to execute a process of outputting information related to environmental data associated with the extracted sleep index. With reference to the storage unit that associates the sleep data with the degree of recovery, the degree of recovery associated with the sleep data similar to the acquired sleep data of the subject is extracted,
An information processing method for causing a computer to execute a process of outputting information on the degree of recovery. From the information recorded by associating the sleep index determined based on the acquired sleep data of the subject and the acquired environmental data of the sleeping place, a sleep index satisfying a predetermined condition is extracted,
An information processing method for causing a computer to execute a process of outputting information on environmental data associated with the extracted sleep index. In an information processing system including a sleep sensor, an information processing device, and a display device,
The sleep sensor
A state detection unit that detects the state of the target person;
A first output unit that outputs sleep data generated based on the information detected by the state detection unit;
The information processing apparatus includes:
An acquisition unit for acquiring sleep data output from the first output unit;
An extraction unit that extracts the degree of recovery associated with sleep data similar to the sleep data acquired by the acquisition unit from information that associates sleep data with the degree of recovery;
A second output unit that outputs information on the degree of recovery extracted by the extraction unit;
The display device
An information processing system comprising: a display unit that displays information output by the second output unit. In an information processing system including a sleep sensor, an environmental sensor, an information processing device, and a display device,
The sleep sensor
A first detection unit for detecting the state of the subject person;
A first output unit that outputs sleep data generated based on the state detected by the first detection unit;
The environmental sensor is
A second detection unit that detects an environment around the subject person;
A second output unit that outputs environmental data generated based on the environment detected by the second detection unit;
The information processing apparatus includes:
A first acquisition unit for acquiring sleep data output by the first output unit;
A second acquisition unit for acquiring environmental data output by the second output unit;
A recording unit that records the sleep index calculated based on the sleep data in association with the environmental data;
An extraction unit for extracting a sleep index satisfying a predetermined condition from the recording unit;
An output unit that outputs information about the environment associated with the sleep index extracted by the extraction unit;
The display device
An information processing system comprising: a display unit that displays information output by the output unit.

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