Information processing method, information processing device, and information processing system

Abstract

This information processing method executed by a computer includes comprises acquiring a plurality of pieces of sleep data obtained by a plurality of detection methods each for detecting sleep of the same user, generating a plurality of sleep diary candidates corresponding to the plurality of detection methods on the basis of the plurality of pieces of sleep data, and presenting the plurality of sleep diary candidates to the user in a selectable manner.

Description

Information processing method, information processing device, and information processing system

[0001] The present disclosure relates to an information processing method, an information processing device, and an information processing system.

[0002] Various techniques for sleep detection have been proposed (see, for example, Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2020-177479

[0004] It is possible to automatically generate (and fill in) a sleep diary using sleep detection technology. Since various detection methods using wearable devices, smartphones, etc. can coexist, the question arises as to which detection method should be used to generate the sleep diary.

[0005] One aspect of the present disclosure makes it possible to select a detection method suitable for generating a sleep diary from among a plurality of detection methods.

[0006] An information processing method according to one aspect of the present disclosure is an information processing method executed by a computer, and includes acquiring a plurality of sleep data obtained by a plurality of detection methods, each of which detects the sleep of the same user; generating a plurality of sleep diary candidates corresponding to the plurality of detection methods based on the plurality of sleep data; and presenting the plurality of sleep diary candidates to the user in a selectable manner.

[0007] An information processing device according to one aspect of the present disclosure includes an acquisition unit that acquires a plurality of sleep data obtained by a plurality of detection methods, each of which detects the sleep of the same user, and a generation unit that generates a plurality of sleep diary candidates corresponding to the plurality of detection methods based on the plurality of sleep data.

[0008] An information processing system according to one aspect of the present disclosure includes a plurality of detection devices that each detect the sleep of the same user, an information processing device that generates a plurality of sleep diary candidates corresponding to the plurality of detection devices based on a plurality of sleep data obtained by the plurality of detection devices, and a terminal device that presents the plurality of sleep diary candidates to the user in a selectable manner.

[0009] 1 is a diagram illustrating an example of a schematic configuration of an information processing system 100 according to a first embodiment. FIG. 1 is a diagram illustrating an example of sleep data 301. FIG. 2 is a diagram illustrating an example of sleep diary candidates. FIG. 3 is a diagram illustrating an example of presentation of sleep diary candidates. FIG. 4 is a diagram illustrating an example of a priority table 302. FIG. 5 is a diagram illustrating an example of a sleep diary 303. FIG. 6 is a flowchart illustrating an example of processing (information processing method) executed in the information processing system 100. FIG. 7 is a flowchart illustrating an example of processing (information processing method) executed in the information processing system 100. FIG. 8 is a diagram illustrating an example of processing (information processing method) executed in the information processing system 100. FIG. 9 is a diagram illustrating an example of processing (information processing method) executed in the information processing system 100. FIG. 10 is a diagram illustrating an example of a schematic configuration of an information processing system 100 according to a second embodiment. FIG. 11 is a diagram illustrating an example of a sleep DB 304. FIG. 12 is a diagram illustrating an example of presentation of statistical information. FIG. 13 is a diagram illustrating an example of processing (information processing method) executed in the information processing system 100. FIG. 14 is a diagram illustrating an example of a hardware configuration of an apparatus. FIG. 15 is a diagram illustrating an example of functional blocks of an information processing system 100 according to an application example.

[0010] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the following embodiments, the same elements are designated by the same reference numerals, and redundant description will be omitted.

[0011] The present disclosure will be described in the following order: 0. Introduction 1. First embodiment 2. Second embodiment 3. Example of hardware configuration 4. Application example 5. Conclusion

[0012] 0. Introduction Many people have sleep problems, and many turn to sleeping pills. Sleep disorders not only affect productivity, but also directly affect mental health and lead to economic losses for society as a whole.

[0013] CBT-i (Cognitive Behavior Therapy for Insomnia) is said to be as effective as or more effective than sleeping pills. This therapy involves short, intensive therapy sessions that are said to be effective for a variety of illnesses and symptoms. Between sessions, homework is assigned that is agreed upon by the therapist and patient. This is a labor-intensive treatment that is carried out face-to-face between the therapist and patient.

[0014] One of the core components of CBT-i is the sleep diary. Traditionally, patients manually filled out the sleep diary based on their own cognitive results. However, in recent years, technology that automatically detects sleep has become widespread. It is conceivable that the sleep diary could be automatically generated (filled in) using the detection results.

[0015] One example of a specific form of detection technology is a wearable device, but sleep detection is also becoming possible using terminal devices such as smartphones. Sleep detection is also possible using sensors installed in various places such as bedrooms, beds, and pillows.

[0016] Multiple detection methods can coexist for the same user. Moreover, each detection method may have a different method (principle, algorithm, etc.), so the sleep diaries generated from the detection data of different detection methods may not match. It is necessary to select a detection method to use for generating the sleep diary from among the multiple detection methods.

[0017] According to the disclosed technology, a user can select the detection method used to generate a sleep diary, which allows the generation of a sleep diary that is appropriate for the user, for example, a sleep diary that is close to the user's cognitive results.

[0018] 1. First Embodiment Fig. 1 is a diagram showing an example of the schematic configuration of an information processing system 100 according to a first embodiment. A user of the information processing system 100 is referred to as user 4 and illustrated in the figure. The information processing system 100 processes data related to the sleep of user 4 and generates a sleep diary for user 4. Such an information processing system 100 can also be called a support system for supporting the health care of user 4.

[0019] The information processing system 100 includes a wearable device 1, a terminal device 2, and an information processing device 3. The information processing system 100 also includes a plurality of detection devices. In the example shown in FIG. 1 , the wearable device 1 and the terminal device 2 each correspond to a detection device (first and second detection devices). When there is no particular distinction between the wearable device 1 and the terminal device 2, they are also simply referred to as detection devices. Note that the term "device" may be interpreted to include the term "device," and these terms may be interpreted as appropriate.

[0020] The wearable device 1, the terminal device 2 and the information processing device 3 are configured to be able to communicate with each other so that at least the sleep data (described later) acquired by each of the wearable device 1 and the terminal device 2 can be used by the information processing device 3, and so that the information generated by the information processing device 3 can be used by the terminal device 2.

[0021] The detection device detects the vital signs of the user 4. Various known vital sign detection technologies, including contactless detection technologies, may be used. Detection may be interpreted to mean measurement, calculation, etc. In this embodiment, vital signs include sleep. The wearable device 1 and the terminal device 2 each detect the sleep of the same user 4.

[0022] Note that the detection device is not limited to the wearable device 1 and the terminal device 2, and any device capable of detecting sleep of the user 4 may be used. For example, a sleep detection sensor installed in various locations such as the bedroom, bed, or pillow of the user 4 may serve as the detection device. There may also be a detection device that detects sleep from the voice of the user 4 or from acceleration. Three or more detection devices may be included in the information processing system 100.

[0023] A method for detecting sleep of the user 4 using a detection device (by a detection device) is also referred to as a detection method. In this sense, the terms detection device and detection method may be interpreted interchangeably as appropriate. The information processing system 100 can also be said to be a system in which multiple detection methods are available.

[0024] Data indicating the detection results of user 4's sleep by the detection device is referred to as sleep data 301. Note that "data" may be interpreted as "information," and these terms may be interpreted appropriately as long as there is no contradiction. Sleep data 301 obtained by wearable device 1 is referred to as sleep data 301-1. Sleep data 301 obtained by terminal device 2 is referred to as sleep data 301-2. When there is no particular distinction between these, they are simply referred to as sleep data 301.

[0025] The sleep data 301 indicates the sleep state of the user 4, and more specifically, indicates whether the user 4 is asleep or not. If the user 4 is asleep, the sleep phase may also be identified, although this is not required. Examples of sleep phases include REM sleep phases, deep sleep phases, and core sleep phases. However, the sleep phases are not limited to these three types. There may be only two types of sleep phases, or four or more types of sleep phases. There may be multiple sleep phases that the detection device can distinguish and detect.

[0026] The wearable device 1 is a device used by a user 4. An example of the wearable device 1 is a wristband-type device (also called a smart watch, etc.), but is not limited to this. The wearable device 1 holds sleep data 301-1. The sleep data 301-1 held by the wearable device 1 may include all data up to the present time, or may include only data from the most recent time up to a certain period in the past.

[0027] The sleep data 301-1 is transmitted from the wearable device 1 to the information processing device 3. The timing of transmission may be determined arbitrarily. For example, the sleep data 301-1 may be transmitted in response to a request from the information processing device 3 or at a predetermined time. The sleep data 301-1 may also be transmitted via the terminal device 2.

[0028] The terminal device 2 is a device used by a user 4 and may also be called a user terminal. An example of the terminal device 2 is a mobile terminal device such as a smartphone, but is not limited to this. Fig. 1 also shows functional blocks of the terminal device 2. The terminal device 2 includes a storage unit 20, a UI unit 21, and a processing unit 22.

[0029] The storage unit 20 stores information used by the terminal device 2. An example of the information stored in the storage unit 20 is a program 200. The program 200 is a program (software) for causing a computer to function as the terminal device 2, and more specifically, is an application program (application software) for causing the processing unit 22 to execute various processes. For example, a memory or the like of the terminal device 2 corresponds to the storage unit 20.

[0030] The UI unit 21 is a user interface unit that accepts operations (user operations) of the terminal device 2 by the user 4 and presents information to the user 4. The presentation may include display, sound output, etc. For example, the operation panel, display, speaker, etc. of the terminal device 2 correspond to the UI unit 21.

[0031] The processing unit 22 executes various processes necessary for the operation of the terminal device 2. The processing unit 22 can also be called a control unit that controls the entire terminal device 2 by controlling other elements within the terminal device 2. For example, a processor or the like of the terminal device 2 corresponds to the processing unit 22.

[0032] The terminal device 2 holds sleep data 301-2. The sleep data 301-2 held by the terminal device 2 may include all data up to the present time, or may include only data from the most recent time up to a certain period in the past.

[0033] The sleep data 301-2 is transmitted from the terminal device 2 to the information processing device 3. The timing of transmission may be determined arbitrarily. For example, the sleep data 301-2 may be transmitted in response to a request from the information processing device 3 or at a predetermined time.

[0034] The format of the sleep data 301-1 transmitted from the wearable device 1 to the information processing device 3 and the format of the sleep data 301-2 transmitted from the terminal device 2 to the information processing device 3 may be the same as or different from each other. Even if the formats are different, the difference can be absorbed by the information processing device 3 (described later).

[0035] The information processing device 3 processes multiple pieces of sleep data 301 obtained by multiple detection methods (in this example, sleep data 301-1 obtained by the wearable device 1 and sleep data 301-2 obtained by the terminal device 2), and generates information to present to the user 4. An example of the information processing device 3 is a server device, but is not limited to this. FIG. 1 also shows functional blocks of the information processing device 3. The information processing device 3 includes a storage unit 30, an acquisition unit 31, a candidate generation unit 32, and a generation unit 33.

[0036] The storage unit 30 stores information used by the information processing device 3. Examples of information stored in the storage unit 30 include a program 300, sleep data 301, a priority table 302, and a sleep diary 303. The program 300 is a program (software) for causing a computer to function as the information processing device 3, and more specifically, is an application program (application software) for causing the acquisition unit 31, the candidate generation unit 32, and the generation unit 33 to execute processes. The sleep data 301, the priority table 302, and the sleep diary 303 will be described later.

[0037] The acquisition unit 31 acquires a plurality of pieces of sleep data 301 obtained by a plurality of detection methods, in this example, sleep data 301-1 obtained by the wearable device 1 and sleep data 301-2 obtained by the terminal device 2. The sleep data 301 acquired by the acquisition unit 31 is stored (held, accumulated) in the storage unit 30. Note that the sleep data 301 stored in the storage unit 30 may be accumulated data of sleep data 301 previously acquired by the acquisition unit 31. The sleep data 301 will be described with reference to FIG. 2 as well.

[0038] FIG. 2 is a diagram showing an example of sleep data 301. The sleep data 301 describes a date and time in association with a state. In the figure, a numerical value indicating the date and time is shown schematically as xxxx, etc. The state indicates the state of the user 4. A state in which the user 4 is awake is described as "awakening." A temporary awakening that occurs during sleep can also be called "awakening mid-sleep." In this example, the state in which the user 4 is asleep is described as a sleep phase. Three types of sleep phases are shown schematically as sleep phase f1, sleep phase f2, and sleep phase f3.

[0039] Note that the above is merely an example of the sleep data 301. Various data related to the sleep of the user 4 may be used as the sleep data 301. For example, as described above, the sleep data 301 does not need to specify the sleep phase. In such a case, the state of the user 4 may be described as, for example, two types: asleep and awake. The sleep data 301 may also include the time when the user 4 went to bed, which makes it possible to calculate the time from when the user went to bed to when the user started to sleep (see FIG. 12 , described below).

[0040] Returning to Fig. 1 , for example, sleep data 301 having the above-described data structure is stored in the storage unit 30. Note that if sleep data 301 already exists when the sleep data 301 is acquired, that data may be overwritten (updated).

[0041] The candidate generator 32 generates multiple sleep diary candidates based on the sleep data 301. The multiple sleep diary candidates generated here target the same time period for the same user 4. Each sleep diary candidate is generated based on the sleep data 301 obtained by a corresponding detection method. Specifically, in this example, a sleep diary based on the sleep data 301-1 and a sleep diary based on the sleep data 301-2 are generated as the multiple sleep diary candidates. The sleep diary candidates will be described with reference to FIG. 3 as well.

[0042] 3 is a diagram showing an example of a sleep diary candidate. In this example, the sleep diary candidate describes a date and a sleep pattern in association with each other. The sleep pattern indicates the state of the user 4 at each time. The sleep pattern can also be called a sleep rhythm or the like.

[0043] The state of the user 4 includes wakefulness and sleep. Unless otherwise specified, wakefulness in a sleep pattern refers to waking up during the night. In relation to the sleep data 301 in FIG. 2 described above, waking up during the night in the sleep data 301 corresponds to wakefulness in a sleep pattern. Anything other than wakefulness (and waking up during the night) in the sleep data 301 corresponds to sleep in a sleep pattern.

[0044] 3 can also be called binary data that describes the sleep of the user 4 in two types, awake and asleep. By providing a simple description that is easy for the user 4 to understand, it is possible to generate a sleep diary candidate that is suitable for presentation to the user 4. Note that sleep may be further categorized and described by distinguishing sleep phases.

[0045] Returning to FIG. 1 , for example, a sleep diary candidate having the above-described data structure is generated by the candidate generation unit 32. As previously mentioned, if the formats of the sleep data 301-1 and the sleep data 301-2 differ, the data is converted to accommodate the differences. That is, the candidate generation unit 32 converts the sleep data 301-1 and the sleep data 301-2 as necessary to describe the sleep patterns in the sleep diary candidate before generating the sleep diary candidate. For example, if the sleep data 301-1 is data describing wakefulness and multiple sleep phases and the sleep diary candidate is binary data describing wakefulness and sleep, the candidate generation unit 32 converts the sleep data 301-1 into binary data. This data conversion allows the use of various detection methods with different data formats.

[0046] The plurality of sleep diary candidates generated by the candidate generator 32 are transmitted from the information processing device 3 to the terminal device 2. Although not shown in FIG. 1 , the plurality of sleep diary candidates generated by the candidate generator 32 may be stored in the storage unit 30.

[0047] The terminal device 2 presents a plurality of sleep diary candidates to the user 4 in a selectable manner. Description will be made with reference to FIG.

[0048] 4 is a diagram showing an example of sleep diary candidate presentation. The UI unit 21 of the terminal device 2 presents (displays) multiple sleep diary candidates side by side. Two of the multiple sleep diary candidates are referred to as sleep diary candidate c1 and sleep diary candidate c2. Sleep diary candidate c1 is a sleep diary candidate generated based on sleep data 301-1 obtained by the wearable device 1. Sleep diary candidate c2 is a sleep diary candidate generated based on sleep data 301-2 obtained by the terminal device 2.

[0049] In response to the presentation of sleep diary candidates c1, c2, etc., user 4 performs a selection operation. User 4 compares the presented sleep diary candidates and selects the sleep diary candidate that is closest to his / her own cognitive results (closest to his / her intuition) based on his / her own subjective opinion. Note that "select" may be interpreted as meaning "designate" or "specify," etc., and these may be interpreted appropriately within a consistent range.

[0050] An example of selection is the selection of a detection method. One detection method is selected from multiple detection methods. Specifically, by selecting one sleep diary candidate from multiple presented sleep diary candidates, the detection method by the corresponding detection device is selected. For example, when sleep diary candidate c1 is selected, the detection method by the wearable device 1 is selected. When sleep diary candidate c2 is selected, the detection method by the terminal device 2 is selected.

[0051] Another example of selection is priority selection. The priority of at least one of the plurality of detection methods is selected. Specifically, one or more sleep diary candidates are selected from the plurality of presented sleep diary candidates, and their priorities are designated (input, etc.). For example, the priorities are designated so that the priority of sleep diary candidate c2 is higher than the priority of sleep diary candidate c1.

[0052] The timing of selecting the priority is not limited to when the sleep diary candidates are presented as described above. The priority may be selected at any timing depending on a user operation or the like. The priority may also be selected by selecting a detection method. For example, the priority of one selected detection method may be set higher than the priorities of the other detection methods.

[0053] Returning to FIG. 1, for example, information indicating the result of the selection as described above is transmitted from the terminal device 2 to the information processing device 3 as the selection result.

[0054] In addition to the selection result, a sleep score may also be transmitted from the terminal device 2 to the information processing device 3. The sleep score indicates a subjective evaluation value of the user 4's sleep for a given day, for example, for a day indicated by a presented sleep diary candidate. Examples of sleep scores include deep sleep and sleepiness, and the sleep score is selected from a plurality of options. For example, like a Likert scale, there are 10 scores from which the user 4 selects. The sleep score may be input when selecting the sleep diary candidate described above, or may be input at any time.

[0055] The generation unit 33 of the information processing device 3 generates a sleep diary based on the selection result and the sleep score. The following description will be divided into a case where the previous selection is a selection of a detection method and a case where the previous selection is a selection of a priority.

[0056] If the previous selection is a detection method, the generator 33 generates a sleep diary based on the sleep data 301 obtained by the selected detection method. For example, if the sleep diary candidate c2 is selected from the sleep diary candidates c1 and c2 in FIG. 4 described above, the generator 33 generates a sleep diary based on the sleep data 301-2 obtained by the terminal device 2. Note that if a sleep diary candidate has already been generated based on the sleep data 301, the sleep diary may be generated using that sleep diary candidate. In other words, generating a sleep diary based on the sleep data 301 may be interpreted to include generating a sleep diary using a sleep diary candidate that has already been generated.

[0057] If the previous selection is a priority selection, the generation unit 33 generates the priority table 302 based on the selection result. The following description will be made with reference to FIG.

[0058] 5 is a diagram showing an example of the priority table 302. The priority table 302 describes the priority and the detection method in association with each other. In this example, the higher the priority, the smaller the value. The highest priority is priority = 1. The detection method is specified by the corresponding detection device.

[0059] 1 , for example, a priority table 302 having the above-described data structure is generated by the generation unit 33 and stored in the storage unit 30. If the priority table 302 already exists, it may be overwritten (updated). In other words, the priority table 302 is updated as appropriate based on the latest selection results.

[0060] The generator 33 refers to the priority table 302 and generates a sleep diary based on the sleep data 301 obtained by the detection method with the highest priority. For example, if the terminal device 2 has the highest priority, the generator 33 generates a sleep diary based on the sleep data 301-2 obtained by the terminal device 2.

[0061] However, since the multiple detection methods coexisting in the information processing system 100 each operate using different algorithms, etc., and the techniques are still being improved, complete sleep data 301 may not be obtained. For example, data loss may occur, such as the absence of data for a certain time period. From such sleep data 301, it may be impossible to properly generate a sleep diary that includes the missing time period.

[0062] Sleep data 301 that cannot (or is difficult to) use to generate an appropriate sleep diary for the target time period due to missing data or the like as described above is also referred to as ineffective data. Conversely, sleep data 301 that is free (or has almost no missing data) and can be used to generate an appropriate sleep diary for the target time period is also referred to as effective data.

[0063] In one embodiment, the generator 33 generates the sleep diary based on detection data obtained by a detection method that is valid and has a high priority. For example, if the terminal device 2 has the highest priority but the sleep data 301-2 obtained by the terminal device 2 is invalid, the generator 33 does not use the sleep data 301-2 to generate the sleep diary. If the sleep data 301-1 obtained by the wearable device 1, which has the next highest priority, is valid, the generator 33 generates the sleep diary based on the sleep data 301-1. By using the priority table 302 in this way, it is possible to automate the selection of the detection method.

[0064] A sleep diary is generated based on the above selection results, i.e., the selection results of the detection method and the selection results of the priority. The sleep diary will be described with reference to FIG.

[0065] FIG. 6 is a diagram showing an example of a sleep diary 303. The sleep diary 303 describes dates, sleep patterns, and sleep scores in association with each other. In this example, the sleep score is expressed on a scale of 1 to 10. The sleep diary 303 is generated based on the sleep data 301 obtained by the detection method specified by the selection result of user 4, and therefore shows the content intended by user 4 (close to the cognitive results of user 4).

[0066] 1 , for example, a sleep diary 303 having the above-described data structure is generated by the generator 33 and stored in the storage unit 30. If the sleep diary 303 already exists at the time of generation, the data may be overwritten (updated).

[0067] The sleep diary 303 is transmitted from the information processing device 3 to the terminal device 2 and presented by the UI unit 21. The timing of transmission and presentation of the sleep diary 303 is not particularly limited, and may be, for example, in response to a user operation of the terminal device 2.

[0068] 7 to 9 are flowcharts showing examples of processes (information processing methods) executed in the information processing system 100. Descriptions of content that overlap with those described above will be omitted where appropriate.

[0069] FIG. 7 shows a process flow for acquiring and storing the sleep data 301.

[0070] In step S1, the acquisition unit 31 of the information processing device 3 acquires sleep data 301. A plurality of pieces of sleep data obtained by a plurality of detection devices, for example, sleep data 301-1 obtained by the wearable device 1 and sleep data 301-2 obtained by the terminal device 2, are acquired.

[0071] In step S2, the acquisition unit 31 of the information processing device 3 determines whether new data is available. For example, if the sleep data 301 acquired in the previous step S1 includes data that has not been acquired before, in other words, data that has not been stored in the storage unit 30, it is determined that new data is available. If new data is available (step S2: Yes), the process proceeds to step S3. If not (step S2: No), the process of the flowchart ends.

[0072] In step S3, the acquisition unit 31 of the information processing device 3 stores new data from the sleep data 301 acquired in the previous step S1 in the storage unit 30. Specifically, the acquired new data, sleep data 301-1 and sleep data 301-2, are added to the sleep data 301-1 and sleep data 301-2 in the storage unit 30. Then, the processing of the flowchart ends.

[0073] 8 shows a process flow for presenting multiple sleep diary candidates. The process of this flowchart is started, for example, in response to a request from the terminal device 2 or when a preset time (e.g., 8:00 a.m.) arrives.

[0074] In step S11, the candidate generator 32 of the information processing device 3 generates multiple sleep diary candidates. For example, a sleep diary candidate based on the sleep data 301-1 and a sleep diary candidate based on the sleep data 301-2 are generated. As described above, if the formats of the sleep data 301-1 and 301-2 are different from each other, the data is converted so that the sleep patterns in the sleep diary candidate can be described (to absorb the differences), and then the sleep diary candidate is generated. The generated multiple sleep diary candidates are transmitted from the information processing device 3 to the terminal device 2.

[0075] In step S12, the UI unit 21 of the terminal device 2 presents a plurality of sleep diary candidates. For example, as described above with reference to FIG. 4, sleep diary candidates c1 and c2 are presented in a selectable manner. Then, the process of the flowchart ends.

[0076] As described above, the user 4 performs a selection operation in response to the presentation of multiple sleep diary candidates. For example, a detection method or a priority is selected. The selection result is transmitted from the terminal device 2 to the information processing device 3. Based on the selection result, the information processing device 3 generates (or updates) the priority table 302 or generates a sleep diary. Note that a timely sleep score is also input into the terminal device 2 and transmitted from the terminal device 2 to the information processing device 3.

[0077] 9 shows a processing flow for generating a sleep diary using the priority table 302. It is assumed that the priority table 302 has been generated based on the selection results so far and stored in the storage unit 30.

[0078] In step S21, the generation unit 33 of the information processing device 3 sets the target priority to the highest priority. If the highest priority is 1 as in FIG. 5 described above, the target priority is set to 1.

[0079] In step S22, the generation unit 33 of the information processing device 3 determines whether the sleep data 301 of the target priority is valid data. As described above, valid data is sleep data that can be used to generate a sleep diary. If the sleep data 301 of the target priority is valid data (step S22: Yes), the process proceeds to step S24. If not (step S22: No), the process proceeds to step S23.

[0080] In step S23, the generation unit 33 of the information processing device 3 sets the target priority to the next priority. The next priority is a priority that is one level lower than the target priority that has been set up until then. Then, the process returns to step S22.

[0081] By repeatedly executing the processes of steps S22 and S23, the sleep data 301 that is valid data and has a high priority (has the highest priority among the valid data) is identified.

[0082] In step S24, the generation unit 33 of the information processing device 3 generates the sleep diary 303 based on the sleep data 301 of the target priority and stores it in the storage unit 30. Thereafter, the processing of the flowchart ends.

[0083] <Modification of First Embodiment> In one embodiment, each time a sleep diary is generated, the user 4 may select a detection method to be used for the generation of the sleep diary. The sleep diary 303 is generated based on the sleep data 301 obtained by the selected detection method. If no selection is made, the sleep diary 303 may be generated based on detection data obtained by a detection method specified based on the priority, as described above. An example of a processing flow will be described with reference to FIG. 10 .

[0084] FIG. 10 is a diagram showing an example of a process (information processing method) executed in the information processing system 100. As shown in FIG.

[0085] In step S31, the generation unit 33 of the information processing device 3 determines whether a detection method has been selected. For example, if the selection result transmitted from the terminal device 2 to the information processing device 3 indicates the selection result of a detection method, it is determined that a detection method has been selected. If a detection method has been selected (step S31: Yes), the process proceeds to step S32. If not (step S31: No), the process proceeds to step S21 in FIG. 9 described above.

[0086] In step S32, the generation unit 33 of the information processing device 3 generates a sleep diary 303 based on the sleep data 301 obtained by the selected detection method, and stores the sleep diary 303 in the storage unit 30. Thereafter, the processing of the flowchart ends.

[0087] According to the first embodiment described above, a plurality of sleep diary candidates corresponding to a plurality of detection methods are presented to the user 4. The user 4 selects a sleep diary candidate that he or she thinks is best, for example, a sleep diary candidate that is close to his or her own cognitive results (close to his or her senses). The selection of a sleep diary candidate is also a selection of a detection method. Based on the selection result, the sleep diary 303 of the user 4 is generated and stored. A sleep diary that is in line with the user 4's subjective opinion can be automatically generated.

[0088] Furthermore, when the priority table 302 is used, it is also possible to generate a sleep diary based on the sleep data 301 with the highest priority among the valid sleep data 301. This makes it possible to strike a balance between the user's needs and the generation of an appropriate sleep diary.

[0089] Furthermore, in one embodiment, some or all of the functions of the information processing device 3 may be incorporated into the terminal device 2. The processing unit 22 of the terminal device 2 may function as some or all of the acquisition unit 31, candidate generation unit 32, and generation unit 33 of the information processing device 3. The storage unit 20 of the terminal device 2 may function as some or all of the storage unit 30 of the information processing device 3. Some of the functions may be incorporated into a device other than the terminal device 2 and the information processing device 3, and used as a component of the information processing system 100.

[0090] The subject of the various processes executed in the information processing system 100 may be appropriately interpreted as a computer, a processor, etc. This is because the wearable device 1, the terminal device 2, and the information processing device 3 are all configured to include a computer, and the processes in each can be said to be executed by a computer. The various processes can also be called information processing methods executed by a computer, a processor, etc., or can also be called operation methods of various devices (or equipment), such as the wearable device 1, the terminal device 2, and the information processing device 3.

[0091] 2. Second Embodiment In the second embodiment, information related to the sleep of multiple users 4 is compiled and statistical information is presented. For example, statistical information on the sleep scores (such as the degree of deep sleep) of multiple users 4 who have similar sleep patterns to the user 4 is presented. The presentation of such statistical information can provide hints for the user 4 to input (describe) a sleep score. This technology may be used in combination with the first embodiment or its variants described above.

[0092] Fig. 11 is a diagram showing an example of the schematic configuration of an information processing system 100 according to the second embodiment. There are multiple users 4, and Fig. 11 shows users 4-1, 4-2, and 4-3, each designated by a reference symbol. When no particular distinction is made between the users, they may simply be referred to as users 4. Naturally, there may be more than three users 4, for example, tens, hundreds, thousands, or even more users 4.

[0093] The information processing system 100 includes a plurality of wearable devices 1 and a plurality of terminal devices 2 corresponding to a plurality of users 4. The wearable device 1 and terminal device 2 used by user 4-1 are illustrated and called wearable device 1-1 and terminal device 2-1. The wearable device 1 and terminal device 2 used by user 4-2 are illustrated and called wearable device 1-2 and terminal device 2-2. The wearable device 1 and terminal device 2 used by user 4-3 are illustrated and called wearable device 1-3 and terminal device 2-3. When there is no particular need to distinguish between these devices, they may simply be called wearable device 1 and terminal device 2.

[0094] As in the first embodiment described above, the information processing device 3 processes, for each user 4, sleep data 301-1 obtained by the wearable device 1 and sleep data 301-2 obtained by the terminal device 2 used by that user 4, and generates information to present to that user 4. The storage unit 30 stores sleep data 301, a priority table 302, and a sleep diary 303 for each user 4.

[0095] Furthermore, in this embodiment, a sleep DB 304 is generated and stored in the storage unit 30. The sleep DB 304 is a database that stores information related to the sleep of multiple users 4. Although there is no particular limitation on the entity that generates the sleep DB 304, in the following description it is assumed that it is the generation unit 33. The generation unit 33 generates the sleep DB 304 based on the sleep diary 303 of each user 4. The following description will also refer to FIG. 12 .

[0096] 12 is a diagram showing an example of the sleep DB 304. The sleep DB 304 stores sleep patterns and sleep scores in association with each other. One record (also called a row) in the sleep DB 304 indicates information about the sleep of a certain user 4.

[0097] In this example, the sleep pattern is determined by a plurality of parameters. The plurality of parameters include, for example, the duration of sleep, the duration of awakening during sleep, the time from going to bed to the onset of sleep, and the intermediate time of sleep. For example, the generation unit 33 extracts parameters from a sleep diary 303 of a certain user 4 and generates one record by associating the extracted parameters with a sleep score. Another record is generated based on the sleep diary 303 of another user 4.

[0098] Any sleep-related parameter may be used, not limited to the above parameters. The parameter may be a parameter obtained by averaging values ​​over multiple days. The multiple days may be counted only for weekdays, only for weekend days, or only for the past N days (N is an integer equal to or greater than 2).

[0099] 11 , for example, the sleep DB 304 having the above-described data structure is generated by the generation unit 33 and stored in the storage unit 30. Note that if the sleep DB 304 already exists, the database may be overwritten (updated).

[0100] The information processing device 3 further includes a search unit 34. The search unit 34 searches the sleep DB 304. Specifically, the search unit 34 searches the sleep DB 304 for (records of) sleep patterns similar to the sleep pattern of the target user 4. In the following, the target user 4 is assumed to be user 4-1. In this case, the search can also be said to search for multiple users 4 who have sleep patterns similar to that of user 4-1.

[0101] The search may be based on the sleep patterns described above, for example, by using a threshold for parameter difference values ​​between sleep patterns, where similarity between the sleep patterns may correspond to difference values ​​below a threshold.

[0102] A specific example will be described. Assume that user 4-1's sleep pattern is as follows: sleep time = 7 hours 30 minutes, time waking up during sleep = 50 minutes, time from going to bed to falling asleep = 30 minutes, time asleep = 2:00 AM. Of the multiple sleep patterns shown in FIG. 12 described above, a sleep pattern is identified in which the sum of the difference values ​​of each parameter is equal to or less than a threshold value. The difference values ​​may be calculated as absolute values. For example, if the threshold value is 9 minutes, the third sleep pattern is identified as a sleep pattern similar to that of user 4-1.

[0103] Note that the above is merely an example of similarity determination, and various known methods capable of determining the similarity between sleep patterns may be used.

[0104] The generation unit 33 generates statistical information about the sleep of multiple users 4 based on the search results of the search unit 34. The statistical information may include statistics of the sleep scores of the multiple users 4. For example, the sleep scores of multiple users 4 having sleep patterns similar to that of user 4-1 are tallied.

[0105] The generated statistical information is transmitted from the information processing device 3 to the terminal device 2-1 of the user 4-1 and presented to the user 4-1. Description will be made with reference to FIGS.

[0106] 13 and 14 are diagrams illustrating examples of statistical information presentation. In the example shown in FIG. 13, a histogram of sleep scores is presented. The horizontal axis of the graph indicates the sleep score, and the vertical axis indicates the number of multiple users 4. Furthermore, the sleep score of user 4-1 in the histogram is also indicated by a white arrow. User 4-1 can easily grasp the position of his or her own sleep score in the histogram. For example, the user 4-1 can visualize and understand any distortions (deviations) in his or her perception of his or her sleep score compared to other users 4. This provides a hint that can be reflected in future sleep score input by user 4-1, increasing the likelihood of generating a more objective sleep diary. As shown in FIG. 14, statistical information may be presented using the average value and standard deviation σ of the sleep scores.

[0107] FIG. 15 is a diagram showing an example of a process (information processing method) executed in the information processing system 100.

[0108] In step S41, the search unit 34 of the information processing device 3 searches for similar data from the sleep DB 304. Specifically, sleep patterns similar to the sleep pattern of user 4-1 are searched for from the sleep DB 304. Here, it is assumed that the sleep patterns of multiple users 4 are found in the search.

[0109] In step S42, the generation unit 33 of the information processing device 3 generates statistical information. Statistical information related to the sleep of multiple users 4 found in the search in the previous step 41, for example, statistical information on sleep scores, is generated. The generated statistical information is transmitted from the information processing device 3 to the users 4.

[0110] In step S43, the UI unit 21 of the terminal device 2 presents the statistical information. For example, the statistical information is presented in the form shown in Figures 13 and 14 described above. Thereafter, the processing of the flowchart ends.

[0111] According to the second embodiment described above, statistical information on the sleep of multiple users 4 is presented to user 4-1. For example, by presenting statistical information on sleep scores, it is possible to provide information that serves as a hint for user 4-1 to input a sleep score.

[0112] 16 is a diagram showing an example of a hardware configuration of an apparatus. The terminal apparatus 2 or the information processing apparatus 3 described above is realized by, for example, a computer 1000 shown in FIG.

[0113] The computer 1000 includes a CPU 1100, a RAM 1200, a ROM (Read Only Memory) 1300, a HDD (Hard Disk Drive) 1400, a communication interface 1500, and an input / output interface 1600. The components of the computer 1000 are connected to each other via a bus 1050.

[0114] The CPU 1100 operates based on programs stored in the ROM 1300 or the HDD 1400 and controls each component. For example, the CPU 1100 loads the programs stored in the ROM 1300 or the HDD 1400 into the RAM 1200 and executes processing corresponding to the various programs. Examples of the programs are the programs 200 and 300 described above with reference to FIG. 1.

[0115] The ROM 1300 stores boot programs such as a Basic Input Output System (BIOS) executed by the CPU 1100 when the computer 1000 is started, and programs that depend on the hardware of the computer 1000 .

[0116] HDD 1400 is a computer-readable recording medium that non-temporarily records programs executed by CPU 1100 and data used by such programs. Specifically, HDD 1400 is a recording medium that records a program for the information processing method according to the present disclosure, which is an example of program data 1450.

[0117] The communication interface 1500 is an interface for connecting the computer 1000 to an external network 1550 (e.g., the Internet). For example, the CPU 1100 receives data from other devices and transmits data generated by the CPU 1100 to other devices via the communication interface 1500.

[0118] The input / output interface 1600 is an interface for connecting the input / output device 1650 and the computer 1000. For example, the CPU receives data from input devices such as a keyboard or a mouse via the input / output interface 1600. The CPU 1100 also transmits data to output devices such as a display, a speaker, or a printer via the input / output interface 1600. The input / output interface 1600 may also function as a media interface for reading programs and the like recorded on a predetermined computer-readable recording medium. Examples of the medium include optical recording media such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), magneto-optical recording media such as an MO (Magneto-Optical Disc), tape media, magnetic recording media, or semiconductor memory.

[0119] When the computer 1000 functions as the terminal device 2 or the information processing device 3 described above, the CPU 1100 of the computer 1000 executes a program loaded onto the RAM 1200 to realize the functions of the processing unit 22, or the acquisition unit 31, the candidate generation unit 32, the generation unit 33, and the search unit 34. The program may be stored in the HDD 1400. The CPU 1100 reads and executes the program data 1450 from the HDD 1400, but as another example, the CPU 1100 may acquire the program from another device via an external network 1550.

[0120] Each of the above components may be configured using general-purpose materials or may be configured using hardware specialized for the function of each component. Such configurations may be changed as appropriate depending on the technical level at the time of implementation.

[0121] 4. Application Examples The information processing system 100 may be modified, expanded, or the like to include various technologies other than those described above. For example, the user 4 ( FIG. 1 ) may be a patient with a disease. Examples of diseases include neurological diseases, muscular degenerative diseases, cardiovascular diseases, psychiatric diseases, diabetes, immune / allergic diseases, and diseases specific to the elderly. More specifically, the information processing system 100 may include Parkinson's disease, muscular dystrophy, cerebellar degenerative diseases, amyotrophic lateral sclerosis (ALS), arrhythmia, heart failure, high blood pressure, depression, dementia, sleep disorders, asthma, hay fever, sarcopenia / frailty, and the like. It is also possible to provide an information processing system 100 that is useful for the healthcare of such a user 4. An example will be described with reference to FIG. 17 .

[0122] 17 is a diagram showing an example of functional blocks of an information processing system 100 according to an application example. The information processing system 100 includes an information acquisition device 51, an information processing device 52, and one or more terminals. Examples of the terminals include a medical professional terminal 53, a community member terminal 54, a life insurance / health insurance terminal 55, a product / service provider terminal 56, and an analysis terminal 57. These devices and terminals are configured to be able to communicate via a network.

[0123] The information acquisition device 51 includes a sensor 511 and a user terminal 512. The sensor 511 and the user terminal 512 may correspond to the wearable device 1 and the terminal device 2 ( FIG. 1 ) described above. The sensing data of the sensor 511 may correspond to the sleep data 301 ( FIG. 1 ).

[0124] The sensing data may include data other than the sleep data 301 described above. Examples of other sensing data include heart rate, heart rate variability, electroencephalogram, blood flow, blood pressure, respiration, lung capacity, electromyography, body temperature, blood glucose level, weight, vibration, impact, and sweat data. Various other information may also be included in the sensing data. For example, the results of a user operation may be included in the sensing data. Examples of the operation results include operation time, operation time (operation timing), input voice, and input document. Furthermore, medication / meal information related to medication and meals of user 4 ( FIG. 1 ) may also be included in the sensing data. Medication / meal information may be input and acquired by user operation, or detected by a sensor installed in a medicine box, tray, or the like. Health checkup results of user 4 may also be included in the sensing data.

[0125] In the information acquisition device 51 , sensing data from a sensor 511 is collected by a user terminal 512 .

[0126] The user terminal 512 includes a communication unit 513, a user interface unit 514, a processing unit 515, and a storage unit 516. An example of information stored in the storage unit 516 is an application program 5161 (application software). Execution of the application program 5161 provides an application used by the user 4. One example of an application is the application that presents and selects sleep diary candidates described above, and the application program 5161 in this case may correspond to the program 200 in FIG. 1 described above. Another example of an application is a rehabilitation application. For example, a rehabilitation menu showing rehabilitation content, etc. is presented (displayed, etc.) by the user interface unit 514. The user 4 performs rehabilitation according to the presented rehabilitation menu.

[0127] The communication unit 513 communicates with other devices, etc. For example, the communication unit 513 receives sensing data from the sensor 511 and receives result information (described later) from the information processing device 52. The communication unit 513 also transmits the sensing data to the information processing device 52.

[0128] The user interface unit 514 accepts operations of the user terminal 512 by the user 4 and presents information to the user 4. The user interface unit 514 may correspond to the UI unit 21 described above.

[0129] The processing unit 515 functions as a control unit that controls each element of the user terminal 512 and executes various processes. For example, the processing unit 515 executes an application program 5161. This provides the various applications described above.

[0130] The information processing device 52 receives and processes the sensing data from the information acquisition device 51. The information processing device 52 includes a communication unit 521, an estimation unit 522, a storage unit 523, a recommendation unit 524, and a processing unit 525. Examples of information stored in the storage unit 523 include patient information 5231, community information 5232, an algorithm DB 5233, a trained model 5234, recommendation information 5235, and anonymously processed information 5236.

[0131] The patient information 5231 includes information about the user 4 who is a patient. Examples of the patient information 5251 include disease information, diagnosis information, medical records, checkup information, medication information, hospital visit history information, rehabilitation history information, etc. of the user 4. The disease information includes the name of the disease of the user 4. The diagnosis information, medical records, checkup information, medication information, and hospital visit history information are information about the diagnosis, medical treatment, checkup, medication, and hospital visit history of the user 4, and are provided, for example, from outside the information processing device 52 (such as the medical professional terminal 53). The rehabilitation history information is information about past rehabilitation that the user 4 underwent, and is obtained, for example, by the rehabilitation application described above and transmitted from the user terminal 512 to the information processing device 52.

[0132] The community information 5232 is information about the community to which the user 4 belongs, and includes information about members and community member terminals 54 .

[0133] The algorithm DB 5233, the trained model 5234, the recommendation information 5235, and the anonymously processed information 5236 will be described later.

[0134] The communication unit 521 communicates with other devices, etc. For example, the communication unit 521 receives sensing data from the user terminal 512.

[0135] The estimation unit 522 performs estimation processing based on the sensing data. For example, the estimation unit 522 calculates various indices that can be used for estimation based on the sensing data. Examples of the indices are the sleep pattern parameters described above (sleep duration, time of awakening during sleep, time from going to bed to onset of sleep, intermediate time of sleep, etc.). Other indices that may be calculated include indices related to the user 4's physical functions, behavior, illness, and emotions. Various algorithms may be used to calculate the indices. The algorithm may be a trained model generated by machine learning using training data. The algorithm may be designed to output an index when sensing data is input, or may be designed to output an index when feature values ​​obtained from the sensing data are input. The feature values ​​may be calculated by the estimation unit 522 based on the sensing data. Calculating a feature value may be interpreted as including generating, extracting, etc. the feature value. Note that the feature value may be the sleep pattern parameter described above.

[0136] Information including the estimation results of the estimation unit 522 is referred to as "result information" and is illustrated. Examples of result information include the sleep diary candidates, sleep diary, statistical information, etc. described above. The communication unit 521 transmits the result information to other devices and terminals, in this example, the user terminal 512, the medical professional terminal 53, the community member terminal 54, and the life insurance / health insurance terminal 55. The recommendation unit 524 and processing unit 525 of the information processing device 52 will be described later.

[0137] In the user terminal 512, the result information is presented by the user interface unit 514. The user 4 can know various indices related to his / her own sleep, physical function, behavior, illness, etc. Individual content can also be presented based on the estimation results.

[0138] The medical staff terminal 53 is a terminal used by a medical staff C. Examples of the medical staff C include doctors, nurses, pharmacists, physical therapists, and caregivers. The medical staff terminal 53 includes a communication unit 531, a user interface unit 532, and a storage unit 533. An example of information stored in the storage unit 533 is medical information 5331. The medical information 5331 includes, for example, medical record information of the user 4, and is used for diagnosing the user 4 by the medical staff using the medical staff terminal 53.

[0139] The communication unit 531 communicates with other devices, etc. For example, the communication unit 531 receives result information from the information processing device 52.

[0140] The user interface unit 532 accepts operations of the medical worker terminal 53 by the medical worker and presents information to the medical worker. For example, result information from the information processing device 52 is presented, and the medical information 5331 is updated accordingly, such as by adding medical record information. Intervention by the medical worker is also possible. For example, individual content such as a rehabilitation menu customized by the medical worker to suit the user 4 is generated. The content is transmitted to the user terminal 512 by the communication unit 531 and presented to the user 4.

[0141] The community member terminal 54 is a terminal used by a member. A member is a member who belongs to the same community as the user 4, such as a family member of the user 4, or another patient (which may be another user 4) who has a similar disease to the user 4. The community member terminal 54 includes a communication unit 541 and a user interface unit 542. The communication unit 541 communicates with other devices, etc. For example, the communication unit 541 receives result information from the information processing device 52.

[0142] The user interface unit 542 accepts operations of the community member terminal 54 by members and presents information to members. For example, result information from the information processing device 52 is presented and shared with members. Individual content based on the estimation results can also be presented.

[0143] Life insurance / health insurance terminal 55 is a terminal used by insurance companies, health insurance companies, etc. Life insurance / health insurance terminal 55 includes a communication unit 551, an analysis unit 552, and a storage unit 553. An example of information stored in storage unit 553 is customer / employee information 5531. Customer / employee information 5531 includes information regarding user 4's life insurance, health insurance, etc.

[0144] The communication unit 551 receives the result information from the information processing device 52. The analysis unit 552 analyzes the result information and identifies (calculates, etc.) insurance premiums and rewards. The identification may involve the work, judgment, etc. of employees of the life insurance company or health insurance company. Insurance premiums may be reduced or changed to a limited plan, etc. The communication unit 551 transmits the identified insurance premiums and recommended insurance premium / reward information to the user terminal 512. The insurance premium / reward information is presented by the user interface unit 514 of the user terminal 512.

[0145] The product / service provider terminal 56 is a terminal used by a company or the like that provides a product / service. Examples of products include wheelchairs, walking aids, rehabilitation equipment, health foods, health equipment, etc. An example of a service is a health application that can be executed on the user terminal 512.

[0146] The product / service provider terminal 56 includes a communication unit 561 and a user interface unit 562. For example, product / service information that associates the result information with products and services is input or generated via the user interface unit 562. For example, a condition indicating the association between an index shown in the result information and a product or service is input, and information including this condition is generated as product / service information. The communication unit 561 transmits the product / service information to the information processing device 52.

[0147] The communication unit 521 of the information processing device 52 receives product / service information from the product / service provider terminal 56 .

[0148] The recommendation unit 524 and processing unit 525 of the information processing device 52 will be described. The recommendation unit 524 generates recommendation information 5235 including information on products and services to be recommended to the user 4 based on the product / service information from the product / service provider terminal 56. For example, based on the conditions input at the product / service provider terminal 56, products and services corresponding to the result information are determined, and recommendation information 5235 recommending them is generated. Content such as the sleep diary candidates, sleep diary, and statistical information described above may be generated as recommendation information 5235. The communication unit 521 transmits the recommendation information 5235 to the user terminal 512 and the community member terminal 54. The recommendation information 5235 is presented by the user interface unit 514 of the user terminal 512 or by the user interface unit 542 of the community member terminal 54.

[0149] The processing unit 525 anonymizes the result information to generate anonymous processed information 5236. The anonymous processed information 5236 describes the anonymized personal information and the result information in association with each other.

[0150] The communication unit 521 of the information processing device 52 transmits the anonymously processed information 5236 to the analysis terminal 57 .

[0151] The analysis terminal 57 is a terminal used by, for example, a company that provides the above-mentioned products / services, a pharmaceutical company that conducts clinical development, etc. The analysis terminal 57 includes a communication unit 571, an analysis unit 572, and a user interface unit 573.

[0152] The communication unit 571 receives the anonymously processed information 5236 from the information processing device 52. The analysis unit 572 performs data analysis based on the anonymously processed information 5236. The analysis may involve the work, judgment, etc. of company employees, etc. The user interface unit 573 presents information related to the data analysis, etc. Examples of analysis include analysis of user demographics for products such as health foods and health equipment, and data analysis for clinical development. The anonymously processed information 5236 can be utilized for various services, such as marketing analysis by manufacturers, analysis of the proportion, age, gender, etc. of users with specific symptoms, and symptom monitoring for patients taking specific medications.

[0153] In the information processing system 100, information about the sleep of the user 4 can be visualized and presented not only on the terminal device 2 but also on the medical staff terminal 53, the community member terminal 54, the life insurance / health insurance terminal 555, etc. This allows people other than the user 4 to understand the information about the sleep of the user 4.

[0154] <Modification of Application Example> In the above application example, a case has been described where sensing data from the sensor 511 is transmitted to the information processing device 52 via the user terminal 512. However, part or all of the sensing data from the sensor 511 may be transmitted directly from the sensor 511 to the information processing device 52 without going through the user terminal 512.

[0155] In the above embodiment, an example has been described in which functions and information related to various services at the life insurance / health insurance terminal 55, product / service provider terminal 56, and analysis terminal 57, such as the recommendation unit 524, processing unit 525, recommendation information 5235, and anonymously processed information 5236, are provided in the information processing device 52. However, these functions and information may also be provided in a server device or the like (service provider server device) managed by the user of the corresponding terminal. The life insurance / health insurance terminal 55, product / service provider terminal 56, and analysis terminal 57 communicate with the corresponding server device or the like to use its functions. This can reduce the processing load on the information processing device 52 and simplify functions to reduce costs.

[0156] Some of the functions of the terminal may be provided in a server device or the like managed by the user of the corresponding terminal. For example, the functions of the analysis unit 552 of the life insurance / health insurance terminal 55 may be provided in a server device or the like managed by an insurance company, health insurance company, etc. The life insurance / health insurance terminal 55 communicates with the server device or the like to use the functions. The functions of the analysis unit 572 of the analysis terminal 57 may be provided in a server device or the like managed by a pharmaceutical company, etc. The analysis terminal 57 communicates with the server device or the like to use the functions. This makes it possible to reduce the processing burden on the life insurance / health insurance terminal 55 and the analysis terminal 57, and to reduce costs by simplifying the functions.

[0157] 5. Summary The technologies described above can be specified, for example, as follows. One of the disclosed technologies is an information processing method executed by a computer. As described with reference to FIGS. 1 to 4 , 7 , and 8 , the information processing method includes acquiring a plurality of pieces of sleep data 301 obtained by a plurality of detection methods, each of which detects the sleep of the same user 4 (step S1), generating a plurality of sleep diary candidates corresponding to the plurality of detection methods based on the plurality of sleep data 301 (step S11), and presenting the plurality of sleep diary candidates to the user 4 in a selectable manner (step S12).

[0158] According to the information processing method, a plurality of sleep diary candidates corresponding to a plurality of detection methods are presented to the user 4 in a selectable manner. The user 4 can select a sleep diary candidate that is closest to his / her own cognitive results based on his / her own subjective opinion, and thus can select a detection method. This makes it possible to select a detection method suitable for generating a sleep diary from the plurality of detection methods.

[0159] 1 and 4, the selection may include at least one of selecting a detection method and selecting a priority of the detection method. For example, such a selection of the detection method is possible.

[0160] 3 and 4, the sleep diary candidate may include a sleep pattern, and the sleep pattern may indicate wakefulness and sleep by time. By providing a sleep pattern that is simply described so that the user 4 can easily understand, it is more likely that a sleep diary candidate suitable for presentation to the user 4 can be generated.

[0161] 1 and 8, the generating step may include converting the sleep data 301 so that the sleep pattern can be described (step S11), thereby enabling the use of various detection methods with different data formats.

[0162] As described with reference to Figures 1, 5, 6, 9, and 10, the information processing method may include generating a sleep diary 303 based on the selection result (steps S24 and S32). This allows the generation of an appropriate sleep diary 303 based on the sleep data 301 obtained by the selected detection method.

[0163] 1, 4, 10, etc., the selection method may include selecting a detection method, and generating may include generating a sleep diary based on the sleep data 301 obtained by the detection method selected by the user 4 (step S31: Yes, step S32). In this case, the selection result of the user 4 can be directly reflected in the sleep diary 303.

[0164] 1 , 4 , 5 , 9 , etc., the selection may include selecting the priority of the detection methods, and the generation may include generating a sleep diary based on the detection methods with high priority, more specifically, on the sleep data 301 that is valid data and obtained by the detection methods with high priority (steps S21, S22: Yes, step S24). In this case, a sleep diary that is in line with the subjective opinions of user 4 can be automatically generated. It is also possible to balance the desires of user 4 with the generation of an appropriate sleep diary.

[0165] 1 and 6, the sleep diary may describe sleep patterns and sleep scores (e.g., sleep depth) in association with each other. For example, a sleep diary having such a data structure can be generated and stored.

[0166] As described with reference to FIGS. 11 to 15 , the information processing method may include presenting to the user 4-1 statistical information about the sleep of multiple users 4 who have sleep patterns similar to that of the user 4-1 (step S43). For example, the statistical information may include statistics about the sleep scores of the multiple users 4. This may provide information (hints) that are useful for the user 4 to input a sleep score.

[0167] As described with reference to FIGS. 11, 12, and 15, the information processing method may include searching for multiple users 4 (e.g., records in the sleep DB 304) who have sleep patterns similar to that of user 4 based on sleep pattern parameters (step S41). The parameters may include at least one of sleep duration, time spent waking up during the night, time from going to bed to starting sleep, and intermediate times during sleep. Similarity may correspond to a difference in parameters between sleep patterns being equal to or less than a threshold. For example, in this manner, multiple users 4 who have sleep patterns similar to that of user 4-1 can be searched for, and their statistical information can be presented.

[0168] 1 and the like, the multiple detection methods may include a detection method using the wearable device 1. When a detection method using the wearable device 1 and another detection method coexist, it becomes possible to select a detection method suitable for generating a sleep diary from the multiple detection methods.

[0169] The information processing device 3 described with reference to Figures 1 to 4, 7, and 8 is also one of the disclosed technologies. The information processing device 3 includes an acquisition unit 31 that acquires multiple pieces of sleep data 301 obtained by multiple detection methods that detect the sleep of the same user 4, and a generation unit 33 that generates multiple sleep diary candidates corresponding to the multiple detection methods based on the multiple pieces of sleep data 301. By presenting the multiple sleep diary candidates generated by the information processing device 3 to the user 4 in a selectable manner, as described above, the user can select a detection method suitable for generating a sleep diary from the multiple detection methods.

[0170] The information processing system 100 described with reference to Figures 1 to 4, 7, and 8 is also one of the disclosed technologies. The information processing system 100 includes a plurality of detection devices (e.g., a wearable device 1 and a terminal device 2) that each detect the sleep of the same user 4, an information processing device 3 that generates a plurality of sleep diary candidates corresponding to the plurality of detection devices based on a plurality of pieces of sleep data 301 obtained by the plurality of detection devices, and the terminal device 2 that presents the plurality of sleep diary candidates to the user 4 in a selectable manner. The information processing system 100 allows a detection device suitable for generating a sleep diary to be selected from a plurality of detection devices (corresponding to a plurality of detection methods).

[0171] The effects described in this disclosure are merely examples and are not limited to the disclosed contents. Other effects may also be obtained.

[0172] Although the embodiments of the present disclosure have been described above, the technical scope of the present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present disclosure. Furthermore, components of different embodiments and modifications may be combined as appropriate.

[0173] The present technology may also be configured as follows. (1) An information processing method executed by a computer, comprising: acquiring a plurality of pieces of sleep data obtained by a plurality of detection methods, each of which detects sleep of the same user; generating a plurality of sleep diary candidates corresponding to the plurality of detection methods based on the plurality of pieces of sleep data; and presenting the plurality of sleep diary candidates to the user in a selectable manner. (2) The information processing method described in (1), in which the selection includes at least one of selecting a detection method and selecting a priority of the detection methods. (3) The information processing method described in (1) or (2), in which the sleep diary candidates include a sleep pattern, and the sleep pattern indicates wakefulness and sleep for each time of day. (4) The information processing method described in (3), in which the generating includes converting the sleep data so as to describe the sleep pattern. (5) The information processing method described in any of (1) to (4), in which the sleep diary is generated based on a result of the selection. (6) The information processing method according to (5), wherein the selection includes selecting a detection method, and wherein the generating includes generating a sleep diary based on sleep data acquired by the detection method selected by the user. (7) The information processing method according to (5) or (6), wherein the selection includes selecting a priority of a detection method, and wherein the generating includes generating a sleep diary based on sleep data acquired by the detection method with the highest priority. (8) The information processing method according to (7), wherein the generating includes generating a sleep diary based on valid data and sleep data acquired by the detection method with the highest priority. (9) The information processing method according to any of (5) to (8), wherein the sleep diary describes a sleep pattern in association with a sleep score. (10) The information processing method according to (9), wherein the sleep score includes a deep sleep level. (11) The information processing method according to any of (1) to (10), wherein statistical information related to the sleep of a plurality of users having sleep patterns similar to that of the user is presented to the user.(12) The information processing method according to (11), wherein the statistical information includes statistics of sleep scores of the multiple users. (13) The information processing method according to (11) or (12), wherein the information processing method includes searching for multiple users having sleep patterns similar to the user's sleep pattern based on sleep pattern parameters. (14) The information processing method according to (13), wherein the parameters include at least one of sleep duration, time of awakening during sleep, time from going to bed to onset of sleep, and intermediate time of sleep. (15) The information processing method according to (13) or (14), wherein the similarity corresponds to a difference value of parameters between sleep patterns being equal to or less than a threshold. (16) The information processing method according to any of (1) to (15), wherein the multiple detection methods include a detection method using a wearable device. (17) An information processing device comprising: an acquisition unit that acquires multiple pieces of sleep data obtained by multiple detection methods that detect the sleep of the same user, and a generation unit that generates multiple sleep diary candidates corresponding to the multiple detection methods based on the multiple pieces of sleep data. (18) An information processing system comprising: multiple detection devices that detect the sleep of the same user, an information processing device that generates multiple sleep diary candidates corresponding to the multiple detection devices based on the multiple pieces of sleep data obtained by the multiple detection devices, and a terminal device that presents the multiple sleep diary candidates to the user in a selectable manner. (19) The information processing system described in (18), wherein the multiple detection devices include a wearable device and the terminal device.

[0174] REFERENCE SIGNS LIST 100 Information processing system 1 Wearable device 2 Terminal device 20 Storage unit 200 Program 21 UI unit 22 Processing unit 3 Information processing device 30 Storage unit 300 Program 301 Sleep data 302 Priority table 303 Sleep diary 304 Sleep DB 31 Acquisition unit 32 Candidate generation unit 33 Generation unit 34 Search unit 4 User

Claims

1. An information processing method executed by a computer, comprising: acquiring a plurality of sleep data obtained by a plurality of detection methods, each of which detects the sleep of the same user; generating a plurality of sleep diary candidates corresponding to the plurality of detection methods based on the plurality of sleep data; and presenting the plurality of sleep diary candidates to the user in a selectable manner.

2. The information processing method according to claim 1, wherein the selection includes at least one of selection of a detection method and selection of a priority of the detection method.

3. The information processing method according to claim 1, wherein the sleep diary candidate includes a sleep pattern, and the sleep pattern indicates wakefulness and sleep for each time of day.

4. The information processing method according to claim 3, wherein said generating includes converting said sleep data so as to be able to describe said sleep pattern.

5. The information processing method according to claim 1, further comprising generating a sleep diary based on the results of said selection.

6. The information processing method according to claim 5, wherein the selection includes selecting a detection method, and the generating includes generating a sleep diary based on sleep data obtained by the detection method selected by the user.

7. The information processing method according to claim 5, wherein the selection includes selecting a priority of the detection methods, and the generating includes generating a sleep diary based on sleep data obtained by the detection methods with the higher priority.

8. The information processing method according to claim 7, wherein said generating step includes generating a sleep diary based on valid data and sleep data obtained by said high priority detection method.

9. The information processing method according to claim 5, wherein the sleep diary describes sleep patterns in association with sleep scores.

10. The information processing method according to claim 9, wherein the sleep score includes a degree of deep sleep.

11. The information processing method according to claim 1, further comprising presenting to the user statistical information relating to the sleep of a plurality of users who have sleep patterns similar to that of the user.

12. The information processing method according to claim 11, wherein the statistical information includes statistics of sleep scores of the plurality of users.

13. The information processing method according to claim 11, further comprising searching for a plurality of users having sleep patterns similar to the sleep pattern of the user based on sleep pattern parameters.

14. The information processing method according to claim 13, wherein the parameters include at least one of sleep duration, time of awakening during sleep, time from going to bed to onset of sleep, and intermediate time of sleep.

15. The information processing method according to claim 13, wherein the similarity corresponds to a difference value of a parameter between the sleep patterns being equal to or less than a threshold value.

16. The information processing method according to claim 1, wherein the plurality of detection methods includes a detection method using a wearable device.

17. An information processing device comprising: an acquisition unit that acquires multiple pieces of sleep data obtained by multiple detection methods, each of which detects sleep of the same user; and a generation unit that generates multiple sleep diary candidates corresponding to the multiple detection methods based on the multiple pieces of sleep data.

18. An information processing system comprising: a plurality of detection devices each detecting sleep of the same user; an information processing device that generates a plurality of sleep diary candidates corresponding to the plurality of detection devices based on a plurality of sleep data obtained by the plurality of detection devices; and a terminal device that presents the plurality of sleep diary candidates to the user in a selectable manner.

19. The information processing system according to claim 18, wherein the plurality of detection devices include a wearable device and the terminal device.

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