Sleep Care Device

Abstract

The present invention relates to a sleep care device which is connected with a user terminal of a user via a network to propose improvement of the quality of sleep of the user, the sleep care device comprising: an acquiring unit for acquiring user data including at least one of biometric data of the user acquired by the user terminal, or life data relating to life indicated by the user; a recommending unit which, on the basis of the user data, outputs at least one of a recommended improving agent or a recommended action for improving the quality of sleep of the user; a transmitting unit for transmitting the recommended improving agent and the recommended action to the user terminal; a shipping instruction unit for providing an instruction for shipping the recommended improving agent to the user; and a storage unit for storing at least the user data, the recommended improving agent, and the recommended action for each user.

Description

[Technical Field]

[0001] The present invention relates to a sleep care device, a sleep care system, a user terminal, a sleep care program, and a sleep care method. [Background technology]

[0002] It is said that more than 20% of people in Japan are dissatisfied with their sleep. It has been pointed out that such sleep disorders are closely related to lifestyle-related diseases, and methods for achieving comfortable sleep are extremely important for maintaining good health. In response to this, many solutions to sleep issues have been proposed, including supplements and behavioral recommendations. For example, Patent Document 1 discloses a system in which a consultant diagnoses inquiry information entered by a user into a user terminal and determines custom-made products (cosmetics, health foods, etc.) based on that diagnosis. Furthermore, Patent Document 2 discloses a system that suggests supplements that a user is lacking based on answers to questions about the user's diet and exercise habits, as well as nutritional information for each supplement. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2008-176382 [Patent Document 2] Patent No. 6586499 Summary of the Invention [Problem to be solved by the invention]

[0004] However, there is room for improvement in the above solutions, and a need exists for a system that can propose sleep quality improvements that are more suited to each user. The present invention has been made to solve this problem, and aims to provide a sleep care device, sleep care system, user terminal, sleep care program, and sleep care method that can propose sleep quality improvements that are more suited to each user. [Means for solving the problem]

[0005] The sleep care device of the present invention is a sleep care device that is connected to a user's user terminal via a network and suggests improvements to the user's sleep quality.It is equipped with an acquisition unit that acquires user data including at least one of the user's biometric data acquired by the user terminal and life data related to the user's life, a recommendation unit that outputs at least one of a recommended improvement agent and a recommended action to improve the user's sleep quality based on the user data, a transmission unit that transmits the recommended improvement agent and the recommended action to the user terminal, a shipping instruction unit that issues instructions to ship the recommended improvement agent to the user, and a memory unit that stores at least the user data, the recommended improvement agent, and the recommended action for each user.

[0006] In the above-mentioned sleep care device, the memory unit stores multiple pieces of teacher data including at least a first parameter having data regarding the test user's life, a second parameter having recommended improvement agents and recommended actions proposed to the test user based on the first parameter, and a third parameter having the degree of improvement in the test user's sleep quality obtained as a result of the recommended improvement agents and recommended actions for the second parameter, and the recommendation unit can be configured to output the recommended improvement agents and recommended actions for the second parameter included in the teacher data from the teacher data having a first parameter that is highly similar to the user data.

[0007] In the above-mentioned sleep care device, after the recommended improvement agent and the recommended action proposed by the recommendation unit are sent to the user terminal, if it is determined from the user data acquired by the acquisition unit after a predetermined period that the user's sleep quality does not exceed the improvement degree of the third parameter, the recommendation unit can be configured to output a recommended improvement agent and a recommended action for improving the user's sleep quality based on the user data acquired by the acquisition unit after the predetermined period.

[0008] The sleep care device may further include a generation unit that generates content to be displayed on the user terminal based on the recommended improvement agent and the recommended behavior output by the recommendation unit, and the content may be configured to be transmitted to the user terminal by the transmission unit.

[0009] In the sleep care device, after the recommended improvement agent is output by the recommendation unit, the user data input to the recommendation unit can include the output recommended improvement agent.

[0010] In the above-mentioned sleep care device, the recommendation unit can be configured to, as an initial process, output the recommended improvement agent and the recommended action based on the user data including the lifestyle data, and to, as a normal process after the initial process, output the recommended improvement agent and the recommended action based on the user data including the biometric data and the lifestyle data.

[0011] In the sleep care device, the recommendation unit may be configured to set a plurality of types of the recommended improving agents for each effect on sleep, and to output a combination of the plurality of recommended improving agents.

[0012] A sleep care system according to the present invention includes any of the sleep care devices described above and at least one of the user terminals.

[0013] The user terminal of the present invention is a user terminal connected via a network to a sleep care device that suggests improvements to sleep, and includes: a biometric data acquisition unit that acquires biometric data of the user; and an input unit that inputs lifestyle data related to the user's lifestyle. The sleep care device includes a transmitting unit that transmits at least one of the biometric data and the lifestyle data to the sleep care device as user data, a receiving unit that receives at least one of the recommended improvement agents and the recommended actions output based on the user data in the sleep care device, and a display unit that displays the received recommended improvement agents and the recommended actions.

[0014] The sleep care program of the present invention is a sleep care program that suggests improvements to a user's sleep in a sleep care device connected to the user's user terminal via a network, and causes the computer of the sleep care device to execute the following steps: acquiring user data including at least one of the user's biometric data acquired by the user's user terminal and lifestyle data related to the user's lifestyle; outputting at least one of a recommended improvement agent and a recommended action to improve the user's sleep quality based on the user data; transmitting the recommended improvement agent and the recommended action to the user terminal; issuing instructions to ship the recommended improvement agent to the user; and storing at least the user data, the recommended improvement agent, and the recommended action.

[0015] The sleep care method of the present invention includes the steps of transmitting user data, including at least one of the user's biometric data acquired by the user's user terminal and lifestyle data related to the user's lifestyle, to a sleep care device; outputting at least one of a recommended improvement agent and a recommended action to improve the user's sleep quality based on the user data, transmitting the recommended improvement agent and the recommended action to the user terminal, and shipping the recommended improvement agent to the user.

[0016] In the sleep care method, the user data can be periodically transmitted to the sleep care device, and the recommended improvement agent and the recommended behavior can be periodically transmitted to the user terminal. [Effects of the Invention]

[0017] According to the present invention, it is possible to propose improvements to the quality of sleep that are more suitable for each user. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a schematic diagram illustrating the configuration of a sleep care system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram showing an example of a hardware configuration of a mobile terminal. [Figure 3] FIG. 2 is a block diagram illustrating an example of a hardware configuration of a sensor terminal. [Figure 4] FIG. 2 is a block diagram showing an example of a software configuration of the mobile terminal. [Figure 5] FIG. 2 is a block diagram illustrating an example of a hardware configuration of a server. [Figure 6] 10 is a table showing an example of training data. [Figure 7] FIG. 2 is a block diagram showing an example of a software configuration of a server. [Figure 8] 10 is a flowchart showing a process performed by a recommendation unit. [Figure 9] 10 is an example of an initial diagnosis notification. [Figure 10] 1 is an example of a daily report. [Figure 11] This is an example of a weekly report. [Figure 12] 1 is an example of a notification about a recommended action. [Figure 13] 10 is a flowchart showing an initial process in the sleep care system. [Figure 14] 10 is an example of a registration screen. [Figure 15] This is an example of an initial questionnaire. [Figure 16]FIG. 10 is a block diagram showing another example of an input method for the recommendation unit. DETAILED DESCRIPTION OF THE INVENTION

[0019] <1. Overview of the Sleep Care System> An embodiment of a sleep care system according to the present invention will be described below with reference to the drawings. The sleep care system according to this embodiment is a system for improving the quality of sleep of a user. Sleep quality can be defined as follows: High quality sleep can be defined as a state in which there are no or few sleep challenges, mainly represented by the following four sleep patterns: (1) Difficulty falling asleep (sleep onset disorder) (2) "Midnight awakening" - shallow sleep and frequent awakenings during the night (3) "Early morning awakening" (4) "Deep sleep disorder" - not feeling satisfied (rested) even after a certain amount of sleep The quality of sleep is calculated based on at least one of biometric data acquired by a sensor terminal (described later) and lifestyle data provided by the user. In this embodiment, the sleepiness index (described later) is used as an index of sleep quality. However, the present invention is not limited to this, and other indices can also be used as an index of sleep quality.

[0020] As shown in Figure 1, this sleep care system includes at least one user terminal 100 and a server (sleep care device) 200, which are connected via a network 700 such as the Internet. Server 500 can also transmit and receive information via network 700 to and from a shipping center 600, which is a facility for shipping recommended sleep-improving agents, such as supplements (described below), to users. The configuration of this system will be described in detail below.

[0021] <2. User Device> <2-1. User Device Overview> 1, a user terminal 100 according to this embodiment includes a mobile terminal 1 and a sensor terminal 2 connected to the mobile terminal 1 wirelessly or via a wire, and various biological data measured by the sensor terminal 2 is transmitted to the mobile terminal 1. The mobile terminal 1 and the sensor terminal 2 will be described in detail below.

[0022] <2-2.Mobile devices> Fig. 2 is a block diagram showing an example of the hardware configuration of a mobile terminal. As shown in Fig. 2, the mobile terminal 1 is a computer to which a control unit 11, a storage unit 12, a communication interface 13, a touch panel display 14, a speaker 15, and a microphone 16 are electrically connected. In Fig. 2, the communication interface is referred to as a "communication I / F." This also applies to Fig. 5, which will be described later.

[0023] The control unit 11 includes a hardware processor such as a CPU (Central Processing Unit), RAM (Random Access Memory), and ROM (Read Only Memory), and controls each component in accordance with information processing. The storage unit 12 is configured with, for example, a hard disk drive, a solid state drive, an optical disk, a magnetic disk, a flash memory, a memory card, and the like, and stores various data such as a terminal program 121, biometric data 122 transmitted from the sensor terminal 2, content data 123 transmitted from the server 500, and lifestyle data 124 input by the user.

[0024] The terminal program 121 is software for collecting biometric data 122 and the like from the sensor terminal 2, managing various data including the collected biometric data 122, and communicating with the server 500. Details will be described later. The biometric data 122 is collected by running the terminal program 121 after establishing communication between the mobile terminal 1 and the sensor terminal 2. The content data 123 is data related to notifications sent to the user from the server, such as diagnostic results and reports (described later). The life data 124 is data related to the user's life, such as the contents of a questionnaire entered by the user, such as wake-up time, bedtime, and level of awakening, as described later. In addition, some of the biometric data obtainable by the sensor terminal 2 (described later) can be used as life data to be input by the user himself / herself. For example, if the number of steps, distance traveled, heart rate upon waking, respiratory rate, blood pressure, blood sugar level, and the like are acquired using a device other than the sensor terminal, the user may input these data into the mobile terminal 1 and thus consider them as life data.

[0025] The communication interface 13 is, for example, a wired LAN (Local Area Network) module, a wireless LAN module, or the like, and is an interface for performing wired or wireless communication via a network. The type of communication interface 13 may be configured appropriately depending on the object to be connected and the type of communication standard. In this embodiment, the mobile terminal 1 is connected to the sensor terminal 2 and the server 500 via the communication interface 13. For example, Bluetooth (registered trademark) can be used for communication between the mobile terminal 1 and the sensor terminal 2. Alternatively, the mobile terminal 1 and the sensor terminal 2 can be connected by wire.

[0026] Touch panel display 14 (hereinafter sometimes simply referred to as display) may be a known type and is used for touch operations for selection, input of characters, etc., and display of images, etc. A user can operate mobile terminal 1 via touch panel display 14. Therefore, this touch panel display 14 corresponds to the display unit and input unit of the user terminal according to the present invention. Speaker 15 and microphone 16 may be known types and are used for outputting and inputting voice, respectively.

[0027] It should be noted that, with regard to the specific hardware configuration of the mobile terminal 1, components can be omitted, replaced, or added as appropriate depending on the embodiment. For example, the control unit 11 may include multiple hardware processors. The hardware processor may be configured with a microprocessor, an FPGA (field-programmable gate array), or the like. Furthermore, the mobile terminal 1 may be an information processing device designed specifically for the service provided, as well as a mobile terminal such as a tablet PC or a smartphone.

[0028] The mobile terminal 1 may also be connected to a drive device or the like for reading data stored in a storage medium. In this case, the terminal program 121 can be provided via the storage medium. When a drive device is connected to the mobile terminal 1, the terminal program 121 can be stored in the storage medium. A storage medium is a medium that stores information such as a program by electrical, magnetic, optical, mechanical, or chemical action so that a computer or other device, machine, or the like can read the information. Examples of the storage medium include a CD (Compact Disk), a DVD (Digital Versatile Disk), and a flash memory.

[0029] <2-3. Sensor terminal> Fig. 3 is a block diagram showing an example of the hardware configuration of a sensor terminal. As shown in Fig. 3, the sensor terminal 2 is attached to the user's body so as to be in direct or indirect contact with the body, and is used to acquire biometric data. Specifically, the sensor terminal 2 is a computer including a controller 21, and a display unit 22, an operation unit 23, a RAM 24, a storage unit 25, a communication unit 26, and a measurement unit 27, which are all connected to the controller 21.

[0030] The controller 21 is configured to control the operation of each unit using, for example, a microcomputer, an FPGA (field-programmable gate array), etc. The display unit 22 is configured to be able to display various information using, for example, a liquid crystal display, an organic EL display, etc. The operation unit 23 is appropriately configured to be able to accept user operations using, for example, a button, a touch panel, etc. The operation unit 23 may be configured as a button physically provided on the sensor terminal 2. Furthermore, when a touch panel display is used as the display unit 22, the operation unit 23 may be configured as a virtual button displayed on the display unit 22.

[0031] The RAM 24 may be a DRAM, an SRAM, or the like, and temporarily stores data and is used as a working storage area for the controller 21. The storage unit 25 is configured, for example, with a hard disk drive, a solid state drive, an optical disk, a magnetic disk, a flash memory, a memory card, or the like, and stores biological data obtained by measurement (for example, various measurement values, index values ​​calculated from the measurement values, etc.).

[0032] The communication unit is similar to the communication interface 13, and is, for example, a wired LAN module, a wireless LAN module, etc. The sensor terminal 2 is connected to the mobile terminal 1 via the communication unit .

[0033] The measurement unit 27 may be configured appropriately depending on the measurement target. For example, the measurement unit 27 may be configured with at least one measurement device such as a microphone, vibration sensor, pressure sensor, piezoelectric sensor, acceleration sensor, brain wave sensor, camera, or infrared sensor. The microphone and vibration sensor detect human movement, voice, snoring, etc., and the sleep state is determined based on this. In addition, various measurement devices acquire data such as the number of steps, distance traveled, travel speed, blood pressure, heart rate, electrocardiogram, body movement, body temperature, weight, blood glucose level, temperature, humidity, and ambient brightness. Hereinafter, these data will be collectively referred to as biometric data. Furthermore, the calories and ingredients of a meal may be analyzed by photographing the meal with a camera and analyzing the acquired image.

[0034] The biological data acquired by the measurement unit 27 is digitized by A / D conversion and stored in the storage unit 25 by the controller 21. The biological data stored in the storage unit 25 is transmitted to the mobile terminal 1 via the communication unit 26. At this time, the biological data is transmitted to the mobile terminal 1 periodically or continuously depending on the type of the biological data.

[0035] As with the mobile terminal 1, the specific hardware configuration of the sensor terminal 2 can be appropriately omitted, replaced, or added depending on the embodiment. In the sensor terminal 2 according to this embodiment, the measurement unit 27 and the units that perform various information processing (controller 21, RAM 24, storage unit 25, and communication unit 26) are integrated, but these may also be separated.

[0036] The form of the sensor terminal 2 is not particularly limited, and various forms are possible, such as a type attached to the wrist or other part of the body. Furthermore, when measuring vibrations such as body movement, a thin form may be used that can be placed under bedding, such as a futon or a mat. Multiple measurement units 27 of different forms may also be provided. Furthermore, the sensor terminal 2 may be configured to automatically start measuring biometric data without the user having to operate the operation unit 23. For example, the sensor terminal 2 may start measuring immediately after being worn, or the sensor may detect the ambient brightness and start measuring after the lights have dimmed. Alternatively, in the case of the thin form described above, the sensor may start measuring automatically after the user gets on the bedding.

[0037] <2-4. Software configuration of mobile terminal> Fig. 4 is a block diagram showing an example of the software configuration of a mobile terminal. The control unit 11 of the mobile terminal 1 loads the terminal program 121 stored in the storage unit 12 into the RAM. The control unit 11 then interprets and executes the terminal program 121 loaded into the RAM using the CPU to control each component. As a result, as shown in Fig. 4, the mobile terminal 1 is configured as a computer including, as software modules, a biometric data acquisition unit 111, a communication control unit 112, a display control unit 113, an input control unit 114, and a user data generation unit 115. These functional configurations will be described below.

[0038] The biometric data acquisition unit 111 communicates with the sensor terminal 2 to periodically or continuously collect biometric data and the like from the sensor terminal 2. The collected biometric data is then stored in the storage unit 12. The communication control unit 112 has a function to periodically or continuously transmit the biometric data 122, life data 124, and the like stored in the storage unit 12 to the server 500, and to receive various data such as content data 123 from the server 500. The communication control unit 112 also has a function to store various data received from the server 500 in the storage unit 12.

[0039] The display control unit 113 has a function to display various data stored in the memory unit 12 on the touch panel display 14. For example, when the terminal program 121 is started, the display control unit 113 has a function to display a screen for user registration, and to display various data received from the server 500 in a predetermined format. The input control unit 114 has a function to input the user's actions and questionnaire responses as life data from the touch panel display 14 and store this in the memory unit 12. The life data includes personal information such as the user's name, address, age, sex, weight, and occupation.

[0040] The user data generation unit 115 generates user data including at least one of the biometric data 122 acquired by the biometric data acquisition unit 111 and the life data acquired by the input control unit 114, and stores the generated user data in the storage unit 12. The biometric data is included in the user data, and details of the biometric data will be described later. The user data is then transmitted to the server by the communication control unit 112.

[0041] <3. Server> <3-1. Server hardware configuration> Next, the server 500 will be described. Fig. 5 is a block diagram showing an example of the hardware configuration of the server. As shown in Fig. 5, the server 500 is a computer in which a control unit 51, a storage unit 52, and a communication interface 53 are electrically connected.

[0042] The control unit 51 includes a hardware processor such as a central processing unit (CPU), a random access memory (RAM), and a read-only memory (ROM), and controls each component in accordance with information processing. The storage unit 52 stores various data such as a sleep care program 521, user data 522 for each user, training data 523 for outputting recommended improvement agents and recommended actions (described later) based on the user data 522, product data 524, action data 525, and content data 526.

[0043] <3-1-1. Sleep Care Program> The sleep care program 521 is a program for outputting recommended medicines and recommended actions based on the biological data and lifestyle data, and for carrying out various processes for sleep care. Specific processes will be described later.

[0044] <3-1-2. User Data> The user data 522 is as described above, and includes at least biometric data and lifestyle data, and is data related to each user that is stored for each user. This user data 522 includes the biometric data 122 and lifestyle data 124 described above, as well as data related to recommended improvement agents and recommended behaviors. Therefore, these data are stored in chronological order so that new data is added sequentially, and past history can be referenced.

[0045] <3-1-3. Training data> The training data 523 is data collected in advance from a plurality of subjects (test users) in order to output recommended improvement agents and recommended actions, which will be described later, and has a table such as that shown in FIG. 6. As shown in the figure, each training data 523 has first to third parameters. The first parameter includes the user's attributes, the lifestyle status answered by the user, the recommended improvement agent, the recommended action, etc.

[0046] Specifically, as shown in FIG. 6, the first parameters include bedtime, wake-up time, sleep pattern, daytime activity level, recommended sleep aids, recommended behaviors, questionnaire results, alcohol consumption, age, gender, and the like collected from the subject. The second parameters include recommended sleep aids and behaviors recommended to the subject based on the first parameters. That is, the second parameters include recommended sleep aids and behaviors actually recommended to the subject having the first parameters to improve their sleep quality. The third parameters include the degree of improvement in sleep quality achieved when the subject lives their life based on the recommended sleep aids and behaviors of the second parameters. The degree of improvement is a relative result compared to the previous sleep quality (e.g., sleepiness) and is expressed, for example, as a numerical value of 1% or more.

[0047] Such teacher data 523 is collected in advance from a large number of subjects (including overlapping subjects) and stored in the storage unit 52. Furthermore, when the quality of sleep of a user of this system improves when living a life based on the recommended improvement agent and recommended behavior, the data is additionally stored as teacher data 523. On the other hand, when the quality of sleep of the user does not improve, the data is not stored as teacher data, but can be stored separately.

[0048] <3-1-4. Product Data> Product data 524 is data related to recommended sleep improvers. Recommended sleep improvers are not limited to foods, beverages, or supplements that can improve sleep quality. As an example, a recommended sleep improver can be a functional food. Functional food products contain, for example, the functional ingredients listed in Table 1 below. These ingredients include amino acids, proteins, pigments, polyphenols, and lactic acid bacteria. Furthermore, multiple functional foods with specified types and amounts of these functional ingredients can be included in the product data as recommended sleep improvers. However, these functional ingredients are merely examples and are not particularly limited. Functional foods include not only so-called foods such as cookies, chocolate, and pasta, but also beverages and supplements. Furthermore, recommended sleep improvers can be modified by changing the type of food or the seasoning (e.g., sweeter or stronger) to suit individual circumstances and preferences, in addition to the amount of functional ingredients. Furthermore, recommended sleep improvers can be generated ex post based on the desired function.

[0049] [Table 1]

[0050] In addition to the recommended improving agent, the product data 524 also includes information such as its efficacy, dosage, and origin. In the example shown in Table 1, functional ingredients are set for each effect on sleep. Therefore, the recommendation unit 513, which will be described later, outputs recommended improving agents containing functional ingredients according to the user's sleep quality, etc. Furthermore, depending on the user's sleep quality, multiple functional ingredients may be necessary, and in such cases, multiple recommended improving agents can be output in combination. It should be noted that the effects on sleep described above include hypotheses and are merely examples. The same applies to the recommended actions, which will be described later.

[0051] If necessary, pharmaceuticals can be provided as recommended improving agents, such as melatonin receptor agonists, orexin receptor antagonists, 5-HT1A receptor agonists, benzodiazepine receptor agonists, and antihistamines.

[0052] <3-1-5. Behavioral Data> The behavioral data 525 is data related to recommended behaviors for improving sleep quality. Recommended behaviors include, for example, dietary content, bath time, exercise, yoga, meditation, sleep time, and lifestyle habits. Each recommended behavior is stored along with explanatory and advice text, audio, photos, and videos. Along with each recommended behavior, the device used to perform the recommended behavior, such as training equipment, aromatherapy equipment, bath additives, and supplements, can also be stored.

[0053] As shown in Table 2 below, recommended actions can also be set for each effect on sleep. The recommendation unit 513, which will be described later, outputs recommended actions according to the user's quality of sleep, but can also output a combination of multiple recommended actions.

[0054] [Table 2]

[0055] <3-1-6. Content Data> The content data 526 includes data for generating screens to be displayed on the mobile terminal 1. As will be described later, the mobile terminal 1 of this embodiment displays content related to an initial diagnosis notification, a periodic report, and a recommended action notification. The content data 526 is material data for generating these contents, and includes, for example, fixed phrases such as findings based on the history of user data that is periodically transmitted, findings related to the progress of recommended improvement agents and recommended actions, and the like.

[0056] <3-1-7.Other> The hardware such as the communication interface 53 has almost the same configuration as the mobile terminal 1, and therefore a description thereof will be omitted. Note that, like the mobile terminal 1, a display, a speaker, a microphone, and the like may also be provided, if necessary.

[0057] <3-2. Server software configuration> Fig. 7 is a block diagram showing an example of the software configuration of the server. The control unit 51 of the server 500 loads the sleep care program 521 stored in the memory unit 52 into the RAM. The control unit 51 then interprets and executes the sleep care program 521 loaded into the RAM using the CPU to control each component. As a result, as shown in Fig. 7, the server 500 is configured as a computer including, as software modules, a user data acquisition unit 511, a communication control unit 512, a recommendation unit 513, a content generation unit 514, and a shipping instruction unit 515. The functional configuration of these units will be described below.

[0058] <3-2-1. User data acquisition section> The user data acquisition unit 511 communicates with the mobile terminal 1 to collect personal information, biometric data 122, lifestyle data 124, etc. transmitted from the mobile terminal 1. The collected various data are then stored in the storage unit 52 as user data 522 in chronological order for each user.

[0059] <3-2-2. Communication control section> The communication control unit 512 has a function of controlling communication with the mobile terminal 1. Specifically, the communication control unit 512 has a function of transmitting data such as a report, which will be described later, to the mobile terminal 1, or receiving the various data described above from the mobile terminal 1, based on predetermined conditions.

[0060] <3-2-3. Recommendations> The recommendation unit 513 has a function of outputting a recommended improvement agent and a recommended action based on the user data 522. Specifically, the process shown in FIG. 8 is performed. First, at a predetermined timing when the user data 522 is accumulated, data corresponding to the first parameter of the teacher data 523 is extracted from the user data 522 as input parameters (step S11). Note that each piece of data of the first parameter may not be included in the input parameters. For example, when this system is used for the first time, a recommended improvement agent or a recommended action has not been set, and therefore input parameters not including these data are extracted.

[0061] Next, as shown in FIG. 6, the similarity between the first parameters of the plurality of training data 523 and the input parameters is calculated (step S12). There are various methods for calculating the similarity, but for example, these parameters can be represented in vector form, and the similarity can be calculated based on the distance and likelihood between the vectors. When calculating the distance and likelihood between the vectors, the value of each element of the vector may be normalized in advance so that the value is, for example, 0 to 1, and then the distance and likelihood are calculated. Alternatively, the vector may be normalized first, and then the distance and likelihood may be calculated. Note that, as described above, if the input parameters do not include recommended improvement agents or recommended actions, these data are deleted from the first parameters before the similarity is calculated.

[0062] Next, the top three teacher data having the first parameter with the highest similarity to the input parameter are selected (step S13). Following this, one teacher data is selected based on a random number (step S14). The reason for using this method is as follows: when the similarity described above is used, there is a possibility that the teacher data with the highest similarity will always be selected. Therefore, by selecting the top three teacher data and then selecting one teacher data from there based on a random number, it is possible to distribute recommendations to users.

[0063] Next, the second parameter and the third parameter included in the selected teacher data 523 are extracted and stored in the storage unit 52 as user data 522 (step S15). Therefore, the extracted second parameter becomes the recommended improvement agent and recommended action to be recommended to the user.

[0064] The above process is an example, and other methods can be used to output the recommended improvement agent and recommended action. For example, the recommended improvement agent and recommended action can be output by machine learning or deep learning using input parameters as input, but this is not limited to this. For example, classification trees, support vector machines, ensemble learning, etc. can be used as machine learning.

[0065] <3-2-4. Content Generation Unit> The content generation unit 514 generates content to be displayed on the mobile terminal 1 based on the user data 522, the product data 524, the behavioral data 525, the selected recommended improvement agent, the recommended behavior, etc. There are various types of content, and in this embodiment, for example, content related to an initial diagnosis notification, various reports, various questionnaires, recommended improvement agents, and recommended behaviors is generated.

[0066] FIG. 9 shows an example of an initial diagnosis notification, which is content sent to the mobile terminal 1 after user registration, as described below. This initial diagnosis notification includes the type of insomnia, a display of recommended improvement agents, and a display of recommended actions. Since types of insomnia are primarily classified into the four types described above—difficulty falling asleep (sleep onset), waking up during the night, waking up early, and lack of a sense of deep sleep—one of these is displayed in the initial diagnosis notification along with its explanation. The content generation unit 514 determines the type of insomnia based on the questionnaire submitted at the time of user registration. In the example of FIG. 9, L-theanine is displayed as the recommended improvement agent and meditation as the recommended action, along with an explanation by an expert. The recommended improvement agent and recommended action are output by the recommendation unit 513 based on the initial questionnaire. The accompanying explanation is extracted from the product data 524 and the behavioral data 525.

[0067] FIG. 10 is an example of a daily report sent every day, and FIG. 11 is an example of a weekly report sent every other week. The daily report shown in FIG. 10 includes the time of bedtime, time of wake-up, number of awakenings, feeling of waking up, number of steps, whether or not drinking alcohol was used, whether or not meditation was used, recommended sleep aids, heart rate, sleep level, and sleep assessment. These are extracted from items stored in the user data 522. Note that feeling of waking up, whether or not drinking alcohol was used, and meditation were entered by the user as responses to a questionnaire on the mobile terminal 1, as will be described later, but the other items are based on measurements automatically made by the measurement unit 27 of the sensor terminal 2.

[0068] Sleepiness can be calculated, for example, as follows: First, a five-minute moving average of each of body movement, breathing, and heart rate is calculated, and then the body movement, breathing, and heart rate are multiplied by their respective multipliers to obtain the section sleep intensity (smaller numbers indicate deeper sleep). In deep sleep, the three parameters are low, resulting in a small overall section sleep intensity. Conversely, for example, if a person wakes up midway through sleep, the body movement, breathing, and heart rate will all be large, resulting in a larger sleep intensity. By calculating these every five to ten minutes, for an eight-hour sleep, a section sleep intensity of 48 to 96 points can be obtained. This is then averaged over the entire sleep interval to obtain the sleep intensity for that sleep interval. Sleep assessment is then performed based on this sleep intensity.

[0069] Sleep assessment can be expressed quantitatively, such as from 0 to 10 (10 being the best), or qualitatively, such as A, B, C, and D. The example in Figure 10 shows sleep assessment qualitatively. The correspondence between quantitative and qualitative assessments can be, for example, A for 0 to less than 2.5, B for 2.5 to less than 5, C for 5 to less than 7.5, and D for 7.5 to less than 10. The evaluation method for quantitative assessments is as follows: First, the maximum and minimum values ​​of the quantitative assessment are determined. Here, they are 10 and 0. Next, sleep assessment items are determined, and a "maximum minus minimum value" (10 in this example) is allocated to each assessment item in advance. For example, if there are five assessment items, and the allocation is evenly distributed, 2.5 points are allocated to each. Examples of assessment items include "deep sleep in the first half of sleep" and "not waking up in the middle of the night." By examining the sleep level of each sleep segment, the degree to which each item is satisfied can be determined, and the allocated points can be used as the maximum score to convert the score. Finally, the constants for each assessment item are summed to obtain a quantitative sleep assessment.

[0070] However, since there are users who feel comfortable even with a short sleep time, for example, a coefficient is set such that 6 hours of sleep is 100 for a user who feels comfortable with 6 hours of sleep, and 8 hours of sleep is 100 for a user who needs 8 hours of sleep, and the sleep level is calculated by multiplying this coefficient by the sleep level. The displayed graphs of heart rate and sleep level are generated by the content generation unit 514 processing time-series data.

[0071] In this way, the content generation unit 514 generates a screen to be shown to the user based on the user data 522, the product data 524, the behavior data 525, and the content data 526.

[0072] The daily report shown in FIG. 10 is an example, and other items can also be displayed. For example, in addition to the user's data, data on other users can also be displayed. In this case, for example, average data for people with the same sleep pattern, or numerical values ​​and graphs for individuals with the same sleep pattern, can be displayed. In this way, showing competitors can increase motivation to improve sleep. In addition, points can be set to be accumulated based on changes in sleep level or behavior, and when a certain number of points are accumulated, they can be exchanged for products, etc.

[0073] The weekly report shown in FIG. 11 is a summary report for one week that shows the average of the daily reports for one week, changes in recommended improvement agents and recommended behaviors over the week, findings, etc. Specifically, the report shows the average bedtime, average wake-up time, average sleep duration, average number of awakenings, average sleep assessment, average number of steps, average number of meditations, recommended improvement agents, and findings, and is generated by the content generation unit 514 based on one week's worth of user data 522. The findings include not only findings on the user data but also advice for the user, and findings suitable for the displayed data are extracted from the content data 526 described above. Note that the daily report shown in FIG. 9 does not include findings, but they can also be included.

[0074] FIG. 12 shows an example of a notification regarding a recommended behavior. Notifications are sent to the user periodically at appropriate times, and recommended behaviors are displayed according to the user's situation. In the example of FIG. 12, meditation is the recommended behavior, and buttons for two-minute meditation and five-minute meditation are displayed. When the user touches either button, instructions for two-minute or five-minute meditation are displayed using text, illustrations, or video. These texts, etc. are extracted from behavioral data 525.

[0075] The content relating to such recommended actions is generated by the content generation unit 514 based on the recommended actions determined by the recommendation unit 513 and the explanations and the like stored together with the recommended actions. Although not shown in the figures, content can also be created for the recommended improvement agent in a similar manner and transmitted to the mobile terminal 1.

[0076] The various reports described above include user data for each predetermined period, i.e., the results of the user's behavior and evaluation of their sleep, and advice for the user, but these may be separated. That is, a report on the results and evaluation of the user's behavior and the corresponding advice can be sent separately. For example, reports and advice with transmission timings set as follows can be created.

[0077] [Table 3]

[0078] However, if a large number of notifications are sent to a mobile device, the user may not be able to view them all, so it is preferable to reduce the number of transmissions by sending a combination of several reports and advice.

[0079] <3-2-5. Shipping Instructions> Next, the shipping instruction unit 515 will be described. Once the recommended improvement agent is determined by the recommendation unit 513, the shipping instruction unit transmits the user's personal information and the recommended improvement agent to the shipping center 600. As a result, the shipping center 600 delivers the recommended improvement agent to the user.

[0080] <4. Processing in the sleep care system> Next, the processing in the sleep care system configured as above will be described with reference to Fig. 13. Fig. 13 is a flowchart showing the initial processing in the sleep care system.

[0081] First, the initial processing will be described. First, the user registers as a user (step S21). For example, when the user accesses the homepage or registration page of this sleep care system, a registration screen such as that shown in FIG. 14 is displayed on the touch panel display 14 of the mobile terminal 1. On this registration screen, an email address, password, name, address, and gender are entered. After these entries are completed and a send button (not shown) is touched, an initial questionnaire screen such as that shown in FIG. 15 is displayed (step S22). On this initial questionnaire screen, the bedtime, wake-up time, and the time from going to bed to falling asleep are entered. Two types of bedtime and wake-up times are entered: one for a normal day and one for a day before a holiday. In addition, although not shown, questions such as those from the Athens Insomnia Scale or the Pittsburgh Sleep Quality Index can also be displayed, but the content of the questionnaire is not particularly limited.

[0082] Then, when an input is made on the initial questionnaire screen, the content is transmitted to the server 500 (step S23). In the server 500, the content of the questionnaire is stored in the user data 522. Next, in the server 500, the content generation unit 514 generates the above-mentioned initial diagnosis notice based on the output result of the recommendation unit 513, and transmits it to the mobile terminal 1 (step S24). Furthermore, each item displayed in the initial diagnosis notice is stored in the storage unit 52 as the user data 522. Furthermore, the recommended improvement agent displayed in the initial diagnosis notice is transmitted to the dispatch center by the above-mentioned shipping instruction unit 515, and is delivered from the dispatch center to the user (step S25). At this time, the sensor terminal 2 is also delivered to the user, if necessary.

[0083] Next, the normal processing of sleep care begins. That is, the user takes the recommended improvement agent and performs the recommended behavior based on the initial diagnosis notification. Regarding the recommended behavior, in addition to the recommended behavior shown in the initial diagnosis notification, notifications such as those shown in FIG. 12 are periodically sent. Furthermore, if the recommended behavior is taking a bath or sleeping with socks on, a notification is sent at the time when the recommended behavior is to be performed, encouraging the user to perform the recommended behavior. Furthermore, notifications encouraging the user to take the recommended improvement agent can also be sent sequentially. For example, a notification can be sent to the mobile device 2 before the time to take the recommended improvement agent.

[0084] On the other hand, the biometric data 122 of the user is transmitted from the sensor terminal 2 to the mobile terminal 1. The biometric data 122 may be transmitted continuously from the mobile terminal 1 to the server 500, or may be transmitted every time data is accumulated for a predetermined period of time.

[0085] Furthermore, the user periodically answers questionnaires about his / her physical condition and behavioral patterns, and transmits the answers from the mobile terminal 1 to the server 500. The questionnaire is not particularly limited, but for example, a daily questionnaire conducted every day and a monthly questionnaire conducted once a month can be prepared. For example, the daily questionnaire is a questionnaire transmitted upon waking up, and as shown in FIG. 15, the user inputs the time he / she went to bed yesterday, the time he / she woke up today, and the state of his / her bed. This is because, for example, even if the biometric data 122 is the same, the level of satisfaction with sleep may vary. Such a questionnaire can be correlated with the biometric data measured by the sensor terminal 2, leading to improved accuracy of recommended behaviors and recommended improvement agents. In addition to the questionnaire conducted upon waking up, a questionnaire can be transmitted every day four hours after waking up. For example, this questionnaire prompts the user to input daytime sleepiness and measures whether this has improved daytime work performance or other performance.

[0086] The monthly questionnaire, for example, asks the user to enter information about their sleep quality on a monthly basis, as well as questions about their eating habits, exercise habits, stress, etc., and is conducted in conjunction with the biometric data 122 to understand their long-term condition. Responses to such questionnaires are processed as lifestyle data. The content of the questionnaire is not particularly limited, and various questions can be included. The frequency of the questionnaire is also not particularly limited, and in addition to the above, a questionnaire can be sent weekly.

[0087] 12, if the user touches a button or the like shown in the notification, for example, a button related to an illustration or video, the recommended action is determined to have been performed and can be included as part of the life data. That is, when a button or the like is touched, it is transmitted to the server 500 as life data.

[0088] In this way, the user continues to take the recommended improving agent while continuing to send the biometric data 122 and answer the questionnaire, i.e., continue to send lifestyle data. Based on this, the various reports and advice described above are periodically sent to the mobile terminal 1. These data are stored in the user data 522 in the server 500. Furthermore, the server 500 can calculate the transition of sleep quality, for example, sleepiness, based on the sent biometric data 122 and lifestyle data 124. This makes it possible to calculate the degree of improvement in sleep quality due to the recommended improving agent and recommended behavior.

[0089] Based on the transmitted biometric data 122 and the lifestyle data 124 provided in the questionnaire, the recommendation unit 513 periodically outputs recommended actions and recommended improvement agents and transmits them to the mobile device 1. At the same time, the shipping instruction unit 515 notifies the shipping center 600 of the shipment of the recommended improvement agent. The timing for outputting the recommended improvement agent and recommended actions is not particularly limited, and various settings are possible, such as when the recommended improvement agent is used up, at predetermined intervals such as once a month, or when the sleep state (e.g., sleep level) is significantly improved or not. For example, if, after living a life based on the recommended improvement agent and recommended actions for a predetermined period of time, the degree of improvement described above does not exceed the degree of improvement specified by the extracted third parameter for the predetermined period of time, the recommendation unit 513 can output the recommended improvement agent and recommended actions. Furthermore, if the recommended actions change, the content of the notification regarding the recommended actions shown in FIG. 12 also changes.

[0090] As described above, normal processing is repeated, and the sleep state improves.

[0091] <5. Features> As described above, according to this embodiment, the system is configured to recommend not only recommended sleep-improving agents but also recommended actions based on the user's biometric data and lifestyle data, thereby enabling sleep improvement suggestions tailored to the individual. For example, the functional components contained in the recommended sleep-improving agents have different mechanisms of action, so it is expected that different individuals will benefit from these agents. Therefore, by presenting not only recommended sleep-improving agents but also recommended actions based on the user's biometric data and lifestyle data, improvement in sleep quality is expected.

[0092] <6. Variations> Although one embodiment of the present invention has been described above, the present invention is not limited to this and various modifications are possible. The following modifications can be combined as appropriate.

[0093] (1) In the above embodiment, the mobile terminal 1 and the sensor terminal 2 are provided as separate devices. However, depending on the type of biometric data to be acquired, these can be integrated and used as a user terminal. Furthermore, instead of transmitting the biometric data 122 from the mobile terminal 1 to the server 500, the biometric data can be transmitted from the sensor terminal 2 to the server 500 without going through the mobile terminal 1. In this case, a server dedicated to collecting biometric data can be prepared, and the biometric data can be provided from this server to the server 500 as described above, and a sleep care service can be provided from this server 500.

[0094] Alternatively, after the sensor terminal 2 transmits the biometric data to the mobile terminal 2, the mobile terminal 2 can transmit the biometric data to an intermediate server for data processing, and the intermediate server can then transmit the processed biometric data to the server 500. The intermediate server can, for example, convert the biometric data transmitted from the mobile terminal 2 into data in a format compatible with input from the recommendation unit 513 and transmit this to the server 500. Furthermore, if the index of sleep quality is, for example, a sleepiness level based on the biometric data, the intermediate server can calculate the sleepiness level and transmit it to the server 500. When the sleep care system takes such a form, the combination of the intermediate server and the server corresponds to the sleep care device of the present invention.

[0095] (2) The items of biometric data and life data can be changed as appropriate depending on the performance and functions of the sensor terminal 2. For example, if wake-up time and bedtime can be measured by the sensor terminal 2, they can be processed as biometric data. However, if the sensor terminal 2 does not have the function to measure these times, the user can include them in the life data as their answers to a questionnaire. Therefore, data other than data that can be measured by the sensor terminal 2 can be manually entered by the user as life data as appropriate.

[0096] (3) The method of transmitting user data from the mobile terminal 1 to the recommendation unit 513 is not particularly limited, and can be, for example, as shown in FIG. 16 . As shown in the figure, in this example, user data is input to the recommendation unit 513 monthly, and a recommended improvement agent and a recommended behavior are output. First, the sleepiness level is calculated every five minutes from biological data such as body movement, heart rate, and breathing. Then, a daily sleep pattern and daily sleepiness level are calculated from the five-minute sleepiness level. The results of the above-mentioned questionnaire are also stored daily. In this way, the sleep pattern and sleepiness level are calculated daily, and once one month's worth of data has been accumulated, the monthly sleep pattern and sleepiness level are calculated. The daily questionnaire results are also taken into consideration when calculating the monthly sleepiness level. Then, in addition to these monthly sleep patterns and sleepiness levels, personal information such as gender and age, responses to the monthly questionnaire, recommended improvement agents being taken, and recommended behaviors are input to the recommendation unit 513. Based on this input, the recommendation unit 513 outputs a recommended improvement agent and a recommended behavior and notifies the user. The past database shown in FIG. 16 stores teacher data and the like for use in inference by the recommendation unit 513.

[0097] (4) In the above embodiment, the recommendation unit 513 outputs both the recommended improvement agent and the recommended behavior, but either one may be output. For example, a member who only proposes the recommended behavior can be provided. In this case, among a predetermined number of users with similar user data, the sleep levels of users who only perform the recommended behavior (hereinafter referred to as "simple users") and users who both perform the recommended behavior and take the recommended improvement agent (hereinafter referred to as "normal users") are compared. For example, if the normal users' sleep levels are improved, the effectiveness of the recommended improvement agent is recognized. In this case, the inference method (e.g., training data) of the recommendation unit 513 can be modified so that the recommended improvement agent is more likely to be recommended. On the other hand, if the normal users' sleep levels do not improve or are poor, the effectiveness of the recommended improvement agent is considered to be low, and the inference method of the recommendation unit 513 can be modified so that the recommended improvement agent is not recommended as often. Furthermore, a member who only presents the recommended improvement agent can be provided. In this case, the effectiveness of the recommended behavior can be verified and the training data can be modified in the same manner as above.

[0098] (5) The storage unit 52 included in the server 500 can be divided into multiple units according to the type of data. Also, multiple servers can be provided depending on the functions (for example, functional configurations 511 to 515) required of the server 500. Furthermore, the recommendation unit 513 can be divided into two units: a recommendation unit that outputs recommended improvement agents, and a recommendation unit that outputs recommended actions.

[0099] (6) Advice from an expert can also be sought. For example, if a user wishes to consult with an expert, the mobile terminal 1 can notify the server 500 of a consultation request. Upon receiving the notification of the consultation request, the server 500 selects an expert who can respond to the consultation and notifies an external server that can contact the expert of the consultation content. In response, the external server can transmit a response to the consultation content to the mobile terminal 1.

[0100] (7) The terminal program 121 implemented on the mobile terminal 1 of the above embodiment can be executed by executing a dedicated application, or by accessing a website provided by the server, on which the user can input lifestyle data and display various reports, etc., on the mobile terminal.

[0101] (8) The recommendation unit 513 can also make recommendations as follows. First, biometric data is collected from multiple subjects over a predetermined period of time, and the state at the time the biometric data was measured is classified into REM sleep, deep sleep, light sleep, wakefulness, etc. based on the collected data. Next, the biometric data of multiple subjects over multiple days is clustered for each day. Typical clustering methods include the K-means algorithm and self-organization, but any type is acceptable. Using such a method, the daily biometric data is classified into N classes. The class to which each subject belongs most frequently among the multiple days of data classification is then designated as the subject's class. Next, one of M improvement agents (or actions) is recommended for each subject's classification, and the subject is asked to take (or take) the recommended agent (or action). In this way, M recommended improvement agents and actions are set for the N classes, and the sleep effect of each class is assessed using, for example, quantitative sleep assessment. The best recommended improvement agents and actions for each class are determined, and training data is created. In other words, the training data in this case includes the class, the recommended improvement agents, and the recommended actions. Furthermore, clustering can be performed based not only on the biometric data but also on the results of the initial questionnaire, or on the biometric data and the results of the initial questionnaire, to determine recommended improvement materials and recommended actions.

[0102] Alternatively, classes can be set as follows. First, one of M1 recommended improvement agents (or recommended actions) is recommended to L1 subjects, and each subject is asked to take (or take) the action. This is done for all recommended improvement agents, and the one that improves sleep level the most is designated as the optimal improvement agent for that subject. If subjects with the same optimal recommended improvement agent are placed in the same class, a maximum of M1 classes can be created. By performing the same process for L2 different subjects with M2 different improvement agents, or by repeating this process, the number of recommended improvement agents that can be supported can be increased. Training data can be created based on the classes set in this way.

[0103] Next, an initial questionnaire is conducted. The initial questionnaire can be conducted, for example, on a website provided by the server 500. Next, based on the results of the initial questionnaire, the user's sleep disorder pattern is estimated from the four types described above. The estimated results are then assigned to the classes described above. For example, if the training data is created based on the questionnaire results, the relationship between the questionnaire results and the classes can be established by comparing the training data with each person's class. Furthermore, if biometric data acquisition has been completed, the sleep class can be estimated by calculating the similarity with representative data for the class.

[0104] Once the user's sleep class is estimated, recommended medications and recommended actions are output for each class. The recommended medications and recommended actions may be output simultaneously, or separately at regular intervals. For example, a four-week period of recommended medications may be sent, with additional recommended actions being notified from the third week onwards. Biometric data and behavioral pattern data are then collected as appropriate, and based on this, class selection and the output of recommended medications and recommended actions are performed periodically.

[0105] (9) To encourage users to take recommended medications or take other actions, points can be awarded each time they take these actions, and these points can be used to purchase products. By providing users with a dedicated community, social networking site, message board, etc., it is also possible to exchange information and increase motivation. [Explanation of symbols]

[0106] 100 user terminals 500 Servers (Sleep Care Devices)

Claims

1. A sleep care device that is connected to a user terminal of a user via a network and suggests improvements to the user's sleep quality, an acquisition unit that acquires user data including at least one of biometric data of the user acquired by the user terminal and life data related to the life of the user; a recommendation unit that outputs at least a recommended improving agent to improve the quality of sleep of the user based on the user data; a transmitting unit that transmits at least the recommended improvement agent to the user terminal; a shipping instruction unit that issues an instruction to ship the recommended improving agent to the user; a storage unit that stores at least the user data and the recommended improvement agent for each user; Equipped with The acquisition of user data by the acquisition unit and the output of the recommended improvement agent by the recommendation unit are repeated multiple times, a sleep care device, wherein after the recommended improvement agent is output by the recommendation unit, the user data input to the recommendation unit includes the output recommended improvement agent.

2. A sleep care device that is connected to a user terminal of a user via a network and suggests improvements to the user's sleep quality, an acquisition unit that acquires user data including at least one of biometric data of the user acquired by the user terminal and life data related to the life of the user; a recommendation unit that outputs at least a recommended improving agent to improve the quality of sleep of the user based on the user data; a transmitting unit that transmits at least the recommended improvement agent to the user terminal; a shipping instruction unit that issues an instruction to ship the recommended improving agent to the user; a storage unit that stores at least the user data and the recommended improvement agent for each user; Equipped with The storage unit includes: A plurality of teacher data are stored, each of which includes at least a first parameter having data on the life of a test user, a second parameter having a recommended improvement agent and a recommended action proposed to the test user based on the first parameter, and a third parameter having a degree of improvement in the quality of sleep of the test user obtained as a result of the recommended improvement agent and the recommended action of the second parameter, The recommendation unit A sleep care device configured to output the recommended improvement agent and the recommended action for the second parameter contained in teacher data from teacher data having a first parameter that is highly similar to the user data.

3. If it is determined that the sleep quality of the user does not exceed the improvement degree of the third parameter from the user data acquired by the acquisition unit after a predetermined period of time has elapsed since at least the recommended improving agent proposed by the recommendation unit was sent to the user terminal, 3. The sleep care device according to claim 2, wherein the recommendation unit is configured to output at least a recommended improving agent to improve the quality of sleep of the user based on the user data acquired by the acquisition unit after a predetermined period of time.

4. a generation unit that generates content to be displayed on the user terminal based on at least the recommended improvement agent output by the recommendation unit; The sleep care device according to claim 1 , wherein the content is transmitted to the user terminal by the transmitting unit.

5. 5. The sleep care device according to claim 2, wherein after the recommended improvement agent is output by the recommendation unit, the user data input to the recommendation unit includes the output recommended improvement agent.

6. The recommendation unit As an initial process, output at least the recommended improvement agent based on the user data including the lifestyle data; 6. The sleep care device according to claim 1, wherein, as a normal process after the initial process, the device is configured to output at least the recommended improvement agent based on the user data including the biometric data and the lifestyle data.

7. 7. The sleep care device according to claim 1, wherein the recommendation unit is configured to set a plurality of types of the recommended improving agents for each effect on sleep, and to output a combination of the plurality of recommended improving agents.

8. A sleep care device according to any one of claims 1 to 7; at least one of the user terminals; A sleep care system that includes:

9. 8. A sleep care program for suggesting improvements to a user's sleep in a sleep care device according to claim 1, which is connected to a user terminal of a user via a network, comprising: The computer of the sleep care device acquiring user data including at least one of biometric data of the user acquired by a user terminal of the user and life data relating to the life of the user; outputting at least a recommended improving agent for improving the quality of sleep of the user based on the user data; transmitting at least the recommended remedy to the user terminal; issuing an instruction to ship the recommended improvement agent to the user; storing at least the user data and the recommended improvement agent; A sleep care program that helps you achieve this.

10. transmitting user data, including at least one of biometric data of the user acquired by a user terminal of the user and lifestyle data related to the user's lifestyle, from the user terminal to the sleep care device according to any one of claims 1 to 7; In the sleep care device, outputting at least a recommended improving agent for improving the quality of sleep of the user based on the user data; transmitting at least the recommended improvement agent to the user terminal by the sleep care device; a step of instructing the sleep care device to ship the recommended improvement agent to the user; A sleep care method that includes:

11. periodically transmitting the user data to the sleep care device; The sleep care method according to claim 10 , wherein the recommended improvement agent is periodically transmitted to the user terminal.

12. transmitting user data, including at least one of biometric data of the user acquired by a user terminal of the user and lifestyle data related to the user's lifestyle, from the user terminal to the sleep care device of claim 2; In the sleep care device, outputting at least a recommended improving agent for improving the quality of sleep of the user based on the user data; transmitting at least the recommended improvement agent to the user terminal by the sleep care device; a step of instructing the sleep care device to ship the recommended improvement agent to the user; A sleep care method that includes:

13. periodically transmitting the user data to the sleep care device; The sleep care method according to claim 12 , wherein the recommended improvement agent and the recommended behavior are periodically transmitted to the user terminal.

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