JP6650212B2 - Information processing apparatus, program, information processing method, and information processing system - Google Patents

Description

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

  A method of evaluating the degree of fatigue of a subject using the amount of human herpes virus contained in body fluids such as saliva as an index is disclosed (Patent Document 1).

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

JP 2007-330263 A JP 2013-165828 A

  However, in the evaluation method of Patent Document 1, it is necessary to measure the amount of human herpes virus contained in a body fluid. In order to measure the amount of human herpes virus, the amount of human herpes virus DNA (DeoxyRibonucleic Acid) is measured using, for example, a technique such as PCR (Polymerase Chain Reaction). It requires special measuring equipment and reagents, and takes time. Therefore, it is not suitable for the purpose of easily evaluating the change in the degree of fatigue before and after sleep in daily life, that is, the degree of recovery from fatigue caused by sleep.

  Patent Document 2 does not disclose or suggest the evaluation of the degree of recovery from fatigue before and after sleep.

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

In one aspect, the information processing apparatus of the present invention associates an acquisition unit that acquires sleep data including a time-series change in sleep depth and a time-series change in heart rate during sleep of the subject with the sleep data and the degree of recovery. reference to the storage unit, extracts the sleep data indicating a time series change similar to the time series changes in sleep data acquired by the acquiring unit, the extracted extraction unit for extracting the associated degree of recovery sleep data And an output unit for outputting information on the degree of recovery extracted by the extraction unit.

  In one embodiment, an information processing device or the like that easily evaluates the degree of recovery from fatigue before and after sleep can be provided.

FIG. 2 is an explanatory diagram illustrating a configuration of an information processing system. FIG. 4 is an explanatory diagram showing a record layout of a 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. FIG. 9 is an explanatory diagram illustrating a record layout of a comparison DB. FIG. 4 is an explanatory diagram illustrating a method for calculating a similarity. FIG. 4 is an explanatory diagram illustrating a screen displayed on the portable information device. 5 is a flowchart illustrating a flow of processing of a program. It is a flowchart which shows the flow of a process of the subroutine of calculating similarity. FIG. 14 is an explanatory diagram illustrating a record layout of a recovery degree DB according to the second embodiment. FIG. 13 is an explanatory diagram illustrating a configuration of an information processing system according to a third embodiment. FIG. 14 is an explanatory diagram illustrating a record layout of a result DB according to the third embodiment. FIG. 14 is an explanatory diagram showing a screen displayed on the portable information device according to the third embodiment. 13 is a flowchart illustrating a flow of processing of a program according to the third embodiment. FIG. 14 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 the 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 multi-function mobile phone, and a tablet. Further, as the portable information device 35, a portable or wall-mounted information device dedicated to the information processing system 10 may be used.

  The client 20 is a control device that controls a sensor installed in a 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 control device of a home energy management system (HEMS) connected to sensors and solar cells installed inside and outside the house. Further, as the client 20, an information device such as a general-purpose personal computer, tablet, or smartphone may be used.

  The client CPU 21 is an arithmetic and control unit that controls the client 20. One or a plurality of CPUs or a multi-core CPU is used as the client CPU 21. The client CPU 21 is connected to each unit of hardware constituting the client 20 via a bus.

  The main storage device 22 is a storage device such as an SRAM (Static RAM), a DRAM (Dynamic RAM), a flash memory, or a semiconductor memory disk. The main storage device 22 temporarily stores information required during 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 an SRAM, a DRAM, a flash memory, a semiconductor memory disk, or a 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 performs communication 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, for example, a sheet-shaped sensor and is installed between the bed mattress and the sheet. The sleep sensor 25 detects a pulse, respiration, body motion, body temperature, and the like of the person lying on the bed. Note that the sleep sensor 25 and the client 20 may be integrated.

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

  Sleep sensor 25 outputs the detected information to 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 may not analyze the 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 installed in a data center, a general-purpose personal computer, and a tablet.

  The server CPU 41 is an arithmetic and control unit that executes a program according to the present invention. As the server CPU 41, one or a plurality of CPUs or a multi-core CPU is used. The server CPU 41 is connected to various hardware components of the server 40 via a bus.

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

  The auxiliary storage device 43 is a storage device such as an SRAM, a DRAM, a flash memory, a semiconductor memory disk, or a 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 performs communication 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 personal attributes, the degree of recovery due to sleep, and sleep data. The 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. Note that the time during which the user is awake for sleeping but is awake includes the time during 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 recovery degree DB 51 is a DB in which sleep data and a result of evaluating changes in the degree of fatigue before and after sleep are recorded in advance by a medical institution equipped with facilities.

  A number unique to the record is recorded in the number field. The personal data field includes an age field and a gender field. The age field records the age of the individual. The gender field records the gender of the individual.

  The recovery degree data field includes a pre-bedtime fatigue degree field, a wakeup fatigue degree field, and a recovery degree field. The fatigue level before going to bed is recorded in the pre-bedtime fatigue field. The wakeup fatigue field records the degree of wakeup fatigue. In the recovery degree field, a difference between the fatigue level before bedtime and the fatigue level at wake-up is recorded.

  Here, the degree of fatigue will be described. Various methods for quantitatively evaluating the degree of 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 herpes virus in saliva. Once infected, the human herpes virus is a virus that is retained in salivary glands and the like in a latently infected state for a lifetime. Most adults carry the human herpes virus. When immunity is reduced due to accumulation of fatigue, latently infected human herpes virus is reactivated. Therefore, the degree of fatigue can be evaluated from the amount of human herpes virus in saliva. The degree of fatigue before going to bed is evaluated using the amount of human herpes virus in saliva collected just before going to bed. The wake-up fatigue level is evaluated using the amount of human herpes virus in saliva collected immediately after wake-up. The degree of recovery from sleep can be evaluated based on the difference between the fatigue level before bedtime and the fatigue level at wakeup.

  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 indicates the elapsed time from when the person enters the bed to when he or she wakes up. The unit of the horizontal axis is time. The vertical axis indicates the sleep depth. The sleep depth is indicated by six stages of awakening, REM sleep, stage 1, stage 2, stage 3 and stage 4. Awakening is a state of waking up. REM sleep is a state of light sleep where the body is asleep but the brain is active. Steps 1 to 4 are called non-REM sleep. The larger the number, the deeper the sleep gradually. Among them, sleep stage 3 and sleep stage 4 indicate a state of deep sleep. FIG. 3 shows a state in which the subject sleeps deeply in about 30 minutes after entering the bed, then repeats REM sleep and non-REM sleep, and wakes up during non-REM sleep.

  FIG. 4 is an example of data recorded in the heart rate change field. The horizontal axis indicates the elapsed time from when the person enters the bed to when he or she wakes up. The unit of the horizontal axis is time. The vertical axis indicates the heart rate. FIG. 4 shows a state in which the heart rate changes during sleep.

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

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

  The comparison DB 52 is a DB that associates the number of each record extracted from the recovery degree DB 51 with the result of comparison between 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 a total score field. The comparison DB 52 has one record for each compared record in the recovery degree DB 51. The comparison DB 52 is a DB that is newly created each time a user wakes up.

  Extraction of records from the recovery degree DB 51 will be described. The record whose attribute recorded in the personal data field of the recovery degree DB 51 matches the attribute of the user is extracted. In the present embodiment, a case will be described as an example where a record of a man in his twenties is extracted from each record shown in FIG.

  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 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 and scoring the degree of similarity is recorded. Have been. In the heart rate coefficient field, a value obtained by comparing the heart rate change data recorded in the recovery degree DB 51 with the heart rate change data acquired from the sleep sensor 25 and scoring the degree of similarity is recorded. Have been. In the total point field, a value obtained as a result of comprehensively evaluating 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 of scoring the degree of similarity. The horizontal axis in FIGS. 6A to 6D is common, and indicates 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 in FIG. 6A indicates sleep depth. FIG. 6A shows data acquired from the sleep sensor 25. The vertical axis in FIG. 6B also indicates the sleep depth. FIG. 6B shows data recorded in the sleep depth change field of the recovery degree DB 51. In the subsequent processing, awakening is scored as zero, REM sleep as minus 1, stage 1 as minus 2, stage 2 as minus 3, stage 3 as minus 4, and stage 4 as minus 5, respectively.

  The vertical axis of FIG. 6C indicates a difference obtained by subtracting the value of FIG. 6A from the value of 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. The average value of the values on the vertical axis at each time in FIG. 6D is a score indicating the degree of similarity. 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 will be zero. When the difference between the graph of FIG. 6A and the graph of FIG. 6A is large, the score increases. A score indicating the degree to which the heart rates are similar is calculated in the same manner.

  FIG. 7 is an explanatory diagram illustrating 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. The recovery degree column 61 describes a recovery degree estimated from sleep data acquired from the sleep sensor 25 during sleep. The recovery level uses the value of the recovery level field of the record extracted from the recovery level DB 51 using the number recorded in the number field of the record with the lowest score in the total score field in FIG. 5 as a key. Here, when a plurality of records are extracted, the average value of the values in the recovery degree field of each record is used.

  The sleep time column 62 displays the total time of REM sleep and non-REM sleep. 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 indicating a temporal change of the sleep depth acquired by the sleep sensor 25 is displayed. The horizontal axis indicates the elapsed time from when the person enters the bed to when he or she wakes 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 the processing of the program. The flow of processing of the program according to the present 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 the sleep data (step S502). The client CPU 21 transmits the user information to the server 40 via the communication unit 26 and the network 31 (Step S503). The user information is data indicating attributes of the user such as age and gender.

  The server CPU 41 receives the 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 record of a person having an attribute similar to the user information (step S602). An example in which records of men in their twenties are extracted will be described.

  The client CPU 21 transmits sleep data to the server 40 via the communication unit 26 and the network 31 (Step S504). The client CPU 21 thereafter ends the processing.

  The server CPU 41 receives the sleep data via the network 31 and the communication unit 46 (Step S603). The server CPU 41 activates a subroutine for calculating the 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 a similarity, that is, a score indicating the degree of similarity. This is a subroutine for creating the comparison DB 52. The flow of the process of the subroutine for calculating the similarity will be described later.

  The server CPU 41 extracts, from the comparison DB 52, records having a higher similarity, that is, records having a lower total score. The server CPU 41 searches the recovery degree DB 51 using the number field of the record 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 degree of similarity with the sleep data acquired by the sleep sensor 25. (Step S605).

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

  The server CPU 41 transmits the degree of recovery or the like to the portable information device 35 via the communication unit 46 and the network 31 (step S607). The server CPU 41 thereafter ends the processing. The portable information device 35 receives the degree of recovery or 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. Thereafter, the portable information device 35 ends the process.

  FIG. 9 is a flowchart illustrating the flow of a subroutine for calculating the 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 a 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 acquires the 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 obtained from the sleep depth change field and the sleep depth data obtained from the sleep sensor 25 for each elapsed time (step S623). FIG. 6C described above is an example of the result obtained in step S623.

  The server CPU 41 squares the value of the difference 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 an average value of the values obtained in step S624. Thereafter, this average value is used as the 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 obtained from the heart rate field and the heart rate data obtained from the sleep sensor 25 for each elapsed time (step S627).

  The server CPU 41 squares the value of the difference 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 used as a 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 of the comparison DB 52.

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

  The server CPU 41 determines whether or not to end the processing (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 processing is to be ended (YES in step S631), server CPU 41 ends the processing. If it is determined that the processing is not to be ended (NO in step S631), server CPU 41 adds 1 to 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 or the like that easily 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 in accordance with the operation of the portable information device 35 by the user. Daily data may be stored in the auxiliary storage device 43, and data on an arbitrary date may be displayed on the display unit of the portable information device 35 based on a user's instruction. By doing so, the user can view the degree of recovery at a convenient time, such as during commuting, and use it for health management.

  When a general-purpose personal computer or the like is used as the client 20, the screen of FIG. 7 may be displayed on the display device of the client 20. Alternatively, 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. Further, when the client 20 and the sleep sensor 25 are integrated, the information processing system 10 according to the present embodiment can be used more easily.

  In the recovery degree data field of the recovery degree DB 51, any data indicating a change in the state of the person before and after sleep can be used. For example, a subjective change in the degree of fatigue obtained by a method such as a questionnaire may be used. Further, a value indicating a change in mental abilities such as processing ability obtained by the Kraepelin test before and after sleep may be used.

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

  In step S602, a similar record may be extracted using attributes such as a history, obesity, blood pressure, and occupation. In this case, information on these attributes is recorded in the personal data field of the recovery degree DB 51 in advance.

  In step S606, the degree of recovery may be calculated using only one of the change in sleep depth and the change in heart rate. Further, data such as a change in body temperature during sleep, body movement such as turning over, and a respiratory rate may be used as the 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 each of 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 a representative value is recorded in each field of the sleep data field of the recovery degree DB 51 instead of the 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 in place of the recovery degree DB 51 described in FIG. An information processing system 10 according to the second embodiment will be described with reference to FIG. The description of the parts common to the first embodiment is omitted.

  The recovery degree DB 51 is a DB that associates personal attributes, the degree of recovery 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 sleep duration field and an average body temperature field. In the deep sleep time field, the total value of the times of sleep depth 3 and sleep depth 4 is recorded. In the average body temperature field, data indicating the average body temperature during sleep is recorded.

  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 in FIG. Calculate the degree. However, steps S625 and S629 for obtaining a time-series average value are omitted.

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

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

[Embodiment 3]
The third embodiment relates to an information processing system 10 that records the results of the degree of recovery and proposes a sleep environment in which a high degree of recovery can be obtained. FIG. 11 is an explanatory diagram illustrating the 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. The description of the parts 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 in the bedroom. The humidity sensor 29 is a sensor that measures the humidity in 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 an achievement DB 53.

  FIG. 12 is an explanatory diagram illustrating a record layout of the result DB 53 according to the third embodiment. The performance DB 53 is a DB that records the sleepiness index of a specific individual and the environmental data of the bedroom in association with each other. Here, the good sleep index is an index indicating sleep comfort, and a larger sleep index indicates that comfortable sleep was obtained. For the good sleep index, for example, the above-described degree of recovery before and after sleep can be used. As the good sleep index, a numerical value indicating the activity at the time of waking up, such as the reciprocal of the time from waking to getting out of bed, may be used. The ratio of the time the user slept deeply to the time the user went to bed may be used. The user who wakes up may set a subjective sleepiness index.

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

  In the number field, a number unique to each record recorded in the achievement DB 53 is recorded. The date when the user got up is recorded in the date field. The above-mentioned good sleep index is recorded in the good sleep index field. In the average temperature field, an average value of the indoor temperature while the user is sleeping is recorded. In the average humidity field, an average value of the 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 results DB 53, and records the number, date, 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. The recommended temperature column 65 describes a recommended temperature obtained from a record on the day when the high sleepiness index is recorded. The recommended humidity column 66 describes the recommended humidity obtained from the record on the day when the high sleep index was recorded.

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

  When the user operates the portable information device 35 to instruct to display the recommended sleep environment, 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 performance DB 53 and extracts a record in which a numerical value equal to or greater than the predetermined first threshold value is recorded in the sleep-sleep 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. As the representative value, for example, an average value of each field is used.

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

  The server CPU 41 calculates a bad environment coefficient from the extracted record (step S655). Here, the bad 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. As the representative value, for example, an average value of each field is used.

  The server CPU 41 determines whether 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), server CPU 41 transmits the recommended sleep environment to portable information device 35 via communication unit 46 and network 31 (step S657). The server CPU 41 thereafter ends the processing.

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

  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). Here, when it is determined in step S656 that there is a significant difference (YES in step S656), for example, a 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 that “the recommended sleep environment could not be calculated” is displayed. Thereafter, the portable information device 35 ends the process.

  According to the present embodiment, it is possible to realize the information processing system 10 that accumulates the data of the daily good sleep index and the sleep environment and proposes an environment in which 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 environment data, the information processing system 10 that can propose a more comfortable sleeping environment can be realized. Further, data indicating a chronological change may be used in the environment data field. By doing so, it is possible to provide the information processing system 10 that proposes an environment in which a comfortable sleep can be obtained from the time of falling asleep to the time of awakening.

  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, the recommended sleep environment may be calculated once a week, for example, without waiting for the reception of the request from the portable information device in step S651. By doing so, it is possible to provide the information processing system 10 that automatically sets the environment of the bedroom in accordance with a change in the season and a change in the physical condition of the user.

[Embodiment 4]
Embodiment 4 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 the configuration of the information processing system 10 according to the fourth embodiment. The configuration of the present embodiment will be described with reference to FIG. The description of the parts 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 is 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 the program 71 in the auxiliary storage device 43. Further, the server CPU 41 may read out the 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 the program 71 in the auxiliary storage device 43.

  The 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. The part of the program 71 that is 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 is stored in the auxiliary storage device of the portable information device 35. The client 20 and the portable information device 35 may each 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 the program 71 from another server computer (not shown) via the communication unit 46. The program 71 is installed as a control program of 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 above-described information processing system 10 as a whole.

The technical features (components) described in each embodiment can be combined with each other, and a new technical feature can be formed by combining the features.
The embodiment disclosed this time is an example in all points and should be considered as not being restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

10 Information Processing System 20 Client 21 Client CPU
22 main storage device 23 auxiliary storage device 24 sensor I / F
Reference Signs List 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 that acquires sleep data including a time-series change in sleep depth and a time-series change in heart rate during sleep of the subject,
By referring to the storage unit which associates the degree of recovery sleep data, it extracts the sleep data indicating a time series change similar to the time series changes in sleep data acquired by the acquiring unit, associated with the extracted sleep data An extraction unit for extracting the degree of recovery,
An output unit configured to output information related to the degree of recovery extracted by the extraction unit. The information processing device according to claim 1, wherein the recovery degree associated with the sleep data is determined based on a change in biological data before and after sleep. The information processing device according to claim 2, wherein the biological data is a concentration of a predetermined component in a body fluid. A sleep data acquisition unit that acquires sleep data including a time series change in sleep depth and a time series change in heart rate during sleep of the subject ,
With reference to the storage unit that associates the sleep data and the degree of recovery, sleep data indicating a time series change similar to the time series change of the sleep data acquired by the sleep data acquisition unit is extracted, and the extracted sleep data. A first acquisition unit for acquiring an associated recovery degree ;
A determining unit configured to determine a good sleep index related to sleep comfort of the subject based on the recovery degree acquired by the first acquiring unit ;
A second acquisition unit configured to acquire environmental data of a sleeping place of the subject ;
A recording unit that records the sleepiness index and the environmental data in association with each other,
When receiving an instruction to display a recommended sleep environment, an extraction unit that extracts environment data associated with a good sleep index in a predetermined range from the recording unit,
An information processing apparatus and an output unit for front Ki抽 detection section outputs a representative value of the extracted environment data. The information processing apparatus according to claim 4, wherein the recovery degree is determined based on a change in biological data before and after sleep . The information processing apparatus according to claim 4, wherein the degree of recovery is determined based on a change in the amount of human herpes virus in body fluid before and after sleep . Obtain sleep data including a time-series change in sleep depth and a time-series change in heart rate during sleep of the subject,
By referring to the storage unit which associates the degree of recovery sleep data, it extracts the sleep data indicating a time series change similar to the time series change of the sleep data Nemu acquired, associated with the extracted sleep data recovery Extract the degree,
A program that causes a computer to output the extracted information about the degree of recovery. When receiving an instruction to display a recommended sleep environment, a recovery degree determined based on sleep data including a time-series change in sleep depth and a time-series change in heart rate during sleep of the subject; From the information recorded in association with the environmental data of the sleeping place where the data was obtained, the degree of recovery that satisfies the predetermined condition is extracted,
A program that causes a computer to execute processing to output information about environmental data associated with the extracted degree of recovery . Obtain sleep data including time-series changes in sleep depth and heart rate during sleep of the subject,
By referring to the storage unit which associates the degree of recovery sleep data, it extracts the sleep data indicating a time series change similar to the time series change of the sleep data Nemu acquired, associated with the extracted sleep data recovery Extract the degree,
An information processing method for causing a computer to execute a process of outputting the information on the degree of recovery. When receiving an instruction to display a recommended sleep environment, a recovery degree determined based on sleep data including a time-series change in sleep depth and a time-series change in heart rate during sleep of the subject; From the information recorded in association with the environmental data of the sleeping place where the data was obtained, the degree of recovery that satisfies the predetermined condition is extracted,
An information processing method for causing a computer to execute a process of outputting information relating to environmental data associated with the extracted recovery degree . 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 a state including a sleep depth and a heart rate of the subject,
A first output unit that outputs sleep data including a time series change in sleep depth and a time series change in heart rate, generated based on the information detected by the state detection unit,
The information processing device is
A sleep data acquisition unit that acquires sleep data output from the first output unit;
From information associating the degree of recovery and sleep data, recovery the sleep data acquisition unit extracts the sleep data indicating a time series change similar to the time series change of the obtained sleep data, associated with the extracted sleep data An extraction unit for extracting a degree,
A second output unit that outputs information about 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 environment sensor, an information processing device, and a display device,
The sleep sensor,
A first detection unit that detects a state including a sleep depth and a heart rate of the subject;
A first output unit that outputs sleep data including a time-series change in sleep depth and a time-series change in heart rate, generated based on the information detected by the first detection unit,
The environment sensor includes:
A second detection unit that detects an environment around the subject during sleep ;
A second output unit that outputs environment data generated based on the environment detected by the second detection unit,
The information processing device,
A sleep data acquisition unit that acquires sleep data output by the first output unit ;
With reference to the storage unit that associates the sleep data and the degree of recovery, sleep data indicating a time series change similar to the time series change of the sleep data acquired by the sleep data acquisition unit is extracted, and the extracted sleep data. A first acquisition unit for acquiring an associated recovery degree ;
A determination unit configured to determine a good sleep index related to the sleep comfort of the subject based on the degree of recovery acquired by the first acquisition unit;
A second acquisition unit that acquires environment data output by the second output unit;
A recording unit that records the sleepiness index determined by the determination unit in association with the environmental data acquired by the second acquisition unit ,
An extracting unit configured to extract a good sleep index that satisfies a predetermined condition from the recording unit;
An output unit that outputs information about environmental data associated with the sleepiness index extracted by the extraction unit,
The display device,
An information processing system including a display unit that displays information output by the output unit.

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