Information processing device, information processing method, and information processing program

Abstract

This information processing device comprises a processor. The processor: acquires first biological information that pertains to a plurality of items and is obtained by a measurer measuring a subject at a first point in time; acquires second biological information that pertains to at least one item among the plurality of items and is obtained by the subject performing self-measurement at a second point in time after the first point in time; and estimates, on the basis of the first biological information and the second biological information after the second point in time, biological information that pertains to at least one item among the plurality of items except for the item from which the second biological information was acquired.

Description

Information Processing Apparatus, Information Processing Method, and Information Processing Program

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and an information processing program.

[0002] Conventionally, there is known a technique for checking a health condition by means of a regular health examination and providing information useful for health management and improvement from the results. For example, Japanese Patent Application Laid-Open No. 2018-132959 discloses predicting an index indicating the degree of a user's health determined from the results of a health examination received by the user, from a current value obtained by measuring examination items of the health examination by means different from the health examination.

[0003] In recent years, interest in health management and improvement has been increasing, and there is a demand for enabling the confirmation of a health condition at a desired timing. Examples of items indicating a health condition include, for example, body weight, blood pressure, visceral fat mass, and results of blood tests. Among these, for items that can be self-measured by a user at home or the like, such as body weight and blood pressure, measurement can be actually performed at a desired timing. On the other hand, for items that are difficult to self-measure and require measurement in a health examination or the like, such as visceral fat mass and results of blood tests, it may be difficult to actually perform measurement at a desired timing because the burden on the user and the measurer involved in the measurement is large.

[0004] The present disclosure provides an information processing apparatus, an information processing method, and an information processing program that can promote health management and improvement.

[0005] A first aspect of the present disclosure is an information processing apparatus including a processor. The processor acquires first biological information regarding a plurality of items obtained by a measurer measuring a measurement subject at a first time point, acquires second biological information regarding at least one item among the plurality of items obtained by the measurement subject self-measuring at a second time point after the first time point, and estimates biological information after the second time point regarding at least one item other than the item for which the second biological information has been acquired among the plurality of items, based on the first biological information and the second biological information.

[0006] The processor may output the estimated biological information.

[0007] The processor may output a statement relating to the estimated biometric information.

[0008] The processor may determine, based on the estimated biometric information, whether the subject's health condition has deteriorated, and may notify the subject if their health condition has deteriorated.

[0009] The processor may determine, based on the estimated biometric information, whether the subject's health condition has improved, and may notify the subject if their health condition has improved.

[0010] The processor may acquire new third-party biometric information related to the item from which the biometric information was estimated, which is obtained by the measurer measuring the subject at the time of biometric information estimation, and output a statement corresponding to the difference between the estimated biometric information and the third-party biometric information.

[0011] The processor may correct the second biometric information based on the difference between the first and second biometric information for the same item, and then estimate the biometric information based on the corrected second biometric information.

[0012] The processor may estimate the biological information using an estimation model that takes the first and second biological information as inputs and outputs the biological information from the second time point onward.

[0013] The estimation model may be a machine learning model that has been pre-trained using biometric information on multiple items as training data, which is measured at multiple points in time for each of multiple subjects.

[0014] The processor may estimate the biological information at the second time point.

[0015] The processor may estimate biological information at a third time point, which is after the second time point.

[0016] The processor may estimate the biological information at a second time point, and based on the first biological information, the second biological information, and the estimated biological information at the second time point, it may estimate the biological information at a third time point that occurs after the second time point.

[0017] The processor may estimate biometric information for at least one item other than the item from which the second biometric information has been acquired, and other than a predetermined item that can be self-measured by the person being measured.

[0018] Multiple items may include items measured in a health checkup.

[0019] The first biological information may include three-dimensional data representing the body shape of the person being measured.

[0020] The second set of biometric information may include images obtained by photographing the subject with a camera.

[0021] A second aspect of this disclosure is an information processing method, wherein a computer performs a process to obtain first biometric information relating to a plurality of items obtained by a measurer measuring a subject at a first time point, obtain second biometric information relating to at least one of the plurality of items obtained by the subject measuring themselves at a second time point after the first time point, and estimate biometric information relating to at least one of the plurality of items other than the item for which second biometric information has been obtained, based on the first biometric information and the second biometric information.

[0022] A third aspect of this disclosure is an information processing program that causes a computer to perform a process of acquiring first biometric information relating to a plurality of items obtained by an examiner measuring a subject at a first time point, acquiring second biometric information relating to at least one of the plurality of items obtained by the subject measuring themselves at a second time point after the first time point, and estimating biometric information relating to at least one of the plurality of items other than the item for which second biometric information has been acquired, based on the first biometric information and the second biometric information.

[0023] According to the above embodiments, the information processing device, information processing method, and information processing program of the present disclosure can promote the management and improvement of health.

[0024] This is a diagram showing the schematic configuration of an information processing system. This is a diagram showing an example of biometric information. This is a block diagram showing an example of the hardware configuration of an information processing device. This is a block diagram showing an example of the functional configuration of an information processing device. This is a diagram illustrating the correction of body shape images. This is a diagram illustrating the correction of body shape images. This is a diagram showing an example of information output by an information processing device. This is a diagram showing an example of information output by an information processing device. This is a flowchart showing an example of information processing.

[0025] The following describes an example of an embodiment of the disclosed technology with reference to the drawings. In each drawing, identical or equivalent components and parts are given the same reference numerals, and redundant descriptions are omitted. Furthermore, the dimensional ratios in the drawings are exaggerated for illustrative purposes and may differ from actual ratios.

[0026] First, with reference to Figure 1, an example of the configuration of the information processing system 100 according to this embodiment will be described. The information processing system 100 includes an information processing device 10, a user terminal 12, and a biometric information database 14. The information processing device 10, the biometric information database 14, and the user terminal 12 are connected to each other in a manner that enables communication via a wired or wireless network (not shown). The network is, for example, the Internet, a LAN (Local Area Network), or a WAN (Wide Area Network).

[0027] The information processing system 100 is a system for promoting health management and improvement using biometric information for each of multiple subjects. The user terminal 12 is a terminal device owned by each subject. Specifically, the user terminal 12 is a computer on which software programs are installed for exchanging various information, including biometric information, with the information processing device 10, and for displaying the received information on a display. As the user terminal 12, for example, a smartphone, tablet terminal, wearable device, and personal computer can be appropriately applied.

[0028] The biometric information DB 14 is constructed, for example, by a computer on which a software program providing the functions of a database management system (DBMS) is installed. Specifically, the information processing device 10 may construct the biometric information DB 14, or an external computer (not shown) may construct the biometric information DB 14. The biometric information DB 14 may also be located on the cloud. The information processing device 10 is configured to write and read data from the biometric information DB 14.

[0029] Figure 2 shows an example of data stored in the biometric information database 14. Figure 2 shows biometric information for a single subject. The biometric information database 14 stores biometric information on multiple items such as weight, blood pressure, visceral fat mass, and blood test results (e.g., total cholesterol). The types of items are not particularly limited, and various items commonly used to check health status can be applied. Such biometric information is stored in the biometric information database 14 for each subject.

[0030] Some of the biometric information stored in the biometric information DB 14 is obtained, for example, by measuring subjects at health checkup centers, medical facilities, and fitness clubs and other exercise facilities. The measurers are, for example, medical professionals and sports instructors, and may include multiple different measurers. Examples of such biometric information include visceral fat mass, blood test results, and 3D body shape models (details described later). Such biometric information is transmitted from a terminal device (not shown) owned by the facility that performed the measurement to the information processing device 10, and the information processing device 10 registers the received biometric information in the biometric information DB 14.

[0031] Furthermore, some of the biometric information stored in the biometric information DB 14 is obtained through self-measurement by the person being measured. Examples of such biometric information include weight, which can be measured by a commercially available scale, and blood pressure, which can be measured by a commercially available blood pressure monitor. The person being measured inputs this biometric information into the user terminal 12. The user terminal 12 transmits this biometric information to the information processing device 10, and the information processing device 10 registers the received biometric information in the biometric information DB 14.

[0032] Incidentally, in order to promote health management and improvement, it is desirable to be able to check one's health status at the desired time. For example, for items that can be measured by the person being measured at home, such as weight and blood pressure, the measurement can be taken at the desired time. On the other hand, for items that are difficult to measure by self and require measurement during health checkups, such as visceral fat mass and blood test results, the burden on both the person being measured and the person taking the measurement is significant, making it difficult to actually take the measurement at the desired time.

[0033] Therefore, the information processing device 10 according to this embodiment estimates biological information at a desired estimated time. This makes it possible to check the health status at a desired timing, even for items that are difficult to measure by self, thereby promoting health management and improvement. An example of the configuration of the information processing device 10 according to this embodiment will be described below.

[0034] First, an example of the hardware configuration of the information processing device 10 according to this embodiment will be described with reference to Figure 3. The information processing device 10 includes a CPU (Central Processing Unit) 21, a non-volatile storage unit 22, and a memory 23 as a temporary storage area. The information processing device 10 also includes a display 24, an input unit 25, and a network interface 26. The CPU 21, storage unit 22, memory 23, display 24, input unit 25, and network interface 26 are connected to each other via a bus 28, such as a system bus and a control bus, enabling the exchange of various types of information.

[0035] The storage unit 22 is implemented by a storage medium such as an HDD (Hard Disk Drive), SSD (Solid State Drive), and flash memory. The information processing program 27 of the information processing device 10 is stored in the storage unit 22. The CPU 21 reads the information processing program 27 from the storage unit 22, expands it into the memory 23, and executes the expanded information processing program 27. The CPU 21 is an example of the processor of this disclosure.

[0036] The display 24 is, for example, a liquid crystal display and displays various information. The input unit 25 includes a pointing device such as a mouse and a keyboard, and is used to input various information to the device. The display 24 may be configured as a touch panel and used in conjunction with the input unit 25.

[0037] The network interface 26 is an interface for communicating with external devices, including the user terminal 12, via a network. For this communication, a wired communication standard such as Ethernet (registered trademark) or FDDI (Fiber Distributed Data Interface), or a wireless communication standard such as 4G, 5G, or Wi-Fi (registered trademark) can be used. The information processing device 10 can be, for example, a server computer, a personal computer, a smartphone, a tablet terminal, or a wearable terminal, as appropriate.

[0038] Next, with reference to Figure 4, an example of the functional configuration of the information processing device 10 according to this embodiment will be described. As shown in Figure 4, the information processing device 10 includes an acquisition unit 30, an estimation unit 32, and a control unit 34. The CPU 21 executes the information processing program 27, thereby enabling the acquisition unit 30, estimation unit 32, and control unit 34 to function.

[0039] The acquisition unit 30 acquires first biological information concerning multiple items obtained by the examiner measuring the subject at a first time point. For example, the acquisition unit 30 refers to the biological information DB 14 and acquires the biological information concerning each item measured in the health checkup from the data shown in Figure 2 as first biological information. In other words, the first time point in this case is the time when the health checkup is conducted. Furthermore, the multiple items from which the first biological information is acquired in this case include the items measured in the health checkup.

[0040] Furthermore, the acquisition unit 30 acquires second biological information relating to at least one of several items obtained by the person being measured through self-measurement at a second time point after the first time point. For example, the acquisition unit 30 acquires biological information relating to an item that the person being measured has self-measured from the biological information DB 14 as second biological information. In this case, the second time point is after the health checkup is conducted and is the time when the person being measured performs self-measurement. Also, the items for which second biological information is acquired in this case are some of the items measured during the health checkup that the person being measured can self-measure.

[0041] The estimation unit 32 estimates the biological information for at least one item other than the item for which the second biological information has been acquired, from a plurality of items, based on the first biological information and the second biological information, from the second point in time onward. For example, the estimation unit 32 may estimate the amount of visceral fat at the time of self-measurement based on the weight and amount of visceral fat measured at the time of the health checkup (first point in time) and the weight measured at the time of self-measurement (second point in time).

[0042] Specifically, the estimation unit 32 may estimate the biological information using an estimation model 40 that takes first biological information and second biological information as inputs and outputs biological information from the second time point onward. The estimation model 40 is a machine learning model that has been pre-trained using biological information of multiple items, which is measured at multiple time points for each of multiple subjects, as training data.

[0043] For example, as learning data, biometric information regarding each item measured in each health check may be used for subjects who have undergone health checks two or more times. By using such learning data, it is possible to learn the characteristics of changes in other items when a certain item changes over time. As the estimation model 40, for example, a convolutional neural network, a recurrent neural network, or the like can be applied.

[0044] Alternatively, instead of using the estimation model 40, biometric information may be estimated using data indicating the correlation relationship for each combination of items (for example, body weight and visceral fat mass, body weight and blood pressure, and blood pressure and visceral fat mass, etc.). Specifically, data indicating the correlation relationship for each combination of items may be prepared in advance, and the estimation unit 32 may estimate biometric information by referring to the data indicating the correlation relationship. For example, by referring to data indicating the correlation relationship between body weight and visceral fat mass, it is possible to estimate the increase or decrease in visceral fat mass between each time point based on the increase or decrease in body weight at the time of the health check (the first time point) and the time of self-measurement (the second time point).

[0045] Note that the estimation unit 32 preferably corrects the second biometric information based on the difference between the first biometric information and the second biometric information regarding the same item. In this case, the estimation unit 32 estimates biometric information based on the corrected second biometric information. Due to individual differences in biometric information measurement devices and differences in measurement environments, etc., there may be cases where the measured values in a health check and self-measurement are different even though there is actually no change in biometric information. Therefore, when it is considered that there is actually no change in biometric information, it is preferable to correct the biometric information in self-measurement using the difference in biometric information at each time point. For example, if the body weight in a health check is 64 kg and the body weight in a self-measurement at home within one week after the health check is 66 kg, the measured value of the self-measurement may be corrected by subtracting 2 kg.

[0046] Also, the timing at which the estimation unit 32 estimates the biological information is not limited to the second timing as described above. The estimation unit 32 may estimate the biological information at the second timing, or may estimate the biological information at a third timing after the second timing. For example, the estimation unit 32 may estimate the visceral fat amount at a future time (third timing) compared to the timing of the self-measurement, based on the weight and visceral fat amount measured at the time of the health check (first timing) and the weight measured at the time of the self-measurement (second timing).

[0047] Further, the estimation unit 32 may estimate the biological information at both the second timing and the third timing. In this case, the estimation unit 32 may use the estimated biological information at the second timing for the estimation of the biological information at the third timing. Specifically, the estimation unit 32 may estimate the biological information at the second timing, and may estimate the biological information at the third timing based on the first biological information, the second biological information, and the estimated biological information at the second timing. In this case, the items of the biological information estimated at the second timing and the items of the biological information estimated at the third timing may be the same or different.

[0048] For example, the estimation unit 32 may estimate the visceral fat amount at the time of the self-measurement, based on the weight and visceral fat amount measured at the time of the health check (first timing) and the weight measured at the time of the self-measurement (second timing). Further, the estimation unit 32 may estimate the weight and visceral fat amount at a future time (third timing) compared to the timing of the self-measurement, based on the weight and visceral fat amount measured at the time of the health check, the weight measured at the time of the self-measurement, and the estimated visceral fat amount at the time of the self-measurement.

[0049] Furthermore, the estimation unit 32 may omit estimation for items that the person being measured can easily self-measure, such as weight and blood pressure, regardless of whether the measurement is actually performed. Specifically, the estimation unit 32 may estimate biological information for at least one item that is not one of the items from which the second biological information was acquired among the multiple items from which the first biological information was acquired, and is not one of the predetermined items that the person being measured can self-measure. For example, the predetermined items that can be self-measured may be general items, or they may be set arbitrarily by the person being measured.

[0050] Furthermore, the first biometric information may include three-dimensional data representing the body shape of the person being measured (hereinafter referred to as a 3D body shape model) (see Figure 7). By using such a 3D body shape model, the person being measured can easily recognize changes in their body shape. As a method for generating the 3D body shape model, known techniques such as a method using images obtained by photographing the person being measured from multiple angles with a camera, and a method using a Time of Flight (ToF) camera can be appropriately applied. In other words, the second biometric information in this case includes an image obtained by photographing the person being measured with a camera (hereinafter referred to as a body shape image).

[0051] For the sake of accuracy, it is assumed that a 3D body shape model can only be generated from body shape images taken by the examiner at a health checkup or similar event, and cannot be generated from body shape images taken by the person being measured at home or elsewhere. However, it is possible to correct the generated 3D body shape model based on the difference between the body shape image taken by the examiner at a health checkup or similar event and the body shape image taken by the person being measured at home or elsewhere. For example, the estimation unit 32 may estimate the 3D body shape model at the time of self-measurement based on the body shape image and 3D body shape model obtained at the time of the health checkup (first time point) and the body shape image obtained at the time of self-measurement (second time point).

[0052] As an example, Figure 5 shows a body shape image IMG01 taken from the front of the person being measured. Figure 6 shows a body shape image IMG02 taken from a slightly higher viewpoint than in Figure 5, taking a picture of the same person being measured. As shown in Figures 5 and 6, body shape images tend to have large errors due to differences in how they are taken and differences in camera lens performance, even if there is no actual change in body shape. Therefore, it is preferable for the estimation unit 32 to identify the size and orientation of the person being measured's head from the body shape image and correct the distortion of the body shape image based on the size and orientation of the head. Since the head is considered to have little actual change in body shape, correcting the body shape image based on the head allows for correction of differences in how they are taken and differences in camera lens performance, while reflecting actual changes in body shape.

[0053] Figure 7 shows an example of screen D1 containing various information output by the control unit 34. Screen D1 is displayed on at least one of the user terminal 12's display and the information processing device 10's display 24.

[0054] The control unit 34 may output biological information from the estimated second time point onward. As an example, Figure 7 shows in a table format the measured values ​​at the time of the health checkup (first time point), the measured values ​​and estimated values ​​at the time of self-measurement (second time point), and the estimated values ​​at a time later than the time of self-measurement (third time point). It also shows the 3D body model TDM01 generated at the time of the health checkup and the 3D body model TDM02 estimated at the time of self-measurement. The 3D body model may be rotatable according to user operation, and still images of the model viewed from multiple directions may be displayed side by side.

[0055] Furthermore, the control unit 34 may output a statement regarding the biological information at the second estimated time point and beyond. For example, the control unit 34 may determine whether the subject's health condition has deteriorated based on the biological information at the second estimated time point and notify the subject if their health condition has deteriorated. As an example, in Figure 7, a statement 90 is issued warning that the estimated visceral fat mass has increased (worsened).

[0056] For example, the control unit 34 may determine whether the subject's health condition has improved based on the estimated biological information from the second time point onward, and may notify the subject if their health condition has improved. For example, suppose a subject diagnosed with obesity at the time of the health checkup (first time point) has lost weight at the time of self-measurement (second time point), and it is estimated that they have continued to lose weight at a future time point (third time point). In this case, the control unit 34 may determine that the subject's health condition has improved and notify them with a message such as, "Your obesity is on the decline. Keep up the good work!" In both cases of deterioration and improvement, the notification method is not limited to text; for example, it may use sound.

[0057] Furthermore, the information processing device 10 may perform follow-up on the estimated biological information. Specifically, the acquisition unit 30 may newly acquire third biological information, which is obtained by the examiner measuring the subject at the time of estimation of the biological information, and which pertains to the items for which the biological information was estimated. For example, suppose that biological information is estimated based on the results of a health checkup (first biological information) and the results of self-measurement (second biological information), with the scheduled date of the second health checkup as the estimation point. In this case, the acquisition unit 30 may newly acquire the results as third biological information after the second health checkup has been performed.

[0058] Figure 8 shows an example of screen D2, which includes various information output by the control unit 34 after the estimation of biological information. In the table in Figure 8, in addition to the measured and estimated values ​​similar to those in Figure 7, the measured values ​​from the second health checkup are shown as third biological information. Also shown are the 3D body model TDM01 generated at the time of the first health checkup and the 3D body model TDM03 generated at the time of the second health checkup. Screen D2 is displayed on at least one of the user terminal 12's display and the information processing device 10's display 24.

[0059] Furthermore, the control unit 34 may output a statement corresponding to the difference between the estimated biological information and the third biological information. As an example, in Figure 8, because there was a large error between the estimated visceral fat amount (10 kg) and the actually measured visceral fat amount (8.3 kg), a statement 92 regarding the cause of the error is displayed. The statement regarding the cause of the error may be one that is predetermined for each item of biological information, for example.

[0060] Next, the operation of the information processing device 10 will be explained with reference to Figure 9. In the information processing device 10, the CPU 21 executes the information processing program 27, thereby executing the information processing shown in Figure 9. This processing is executed, for example, when the user issues an instruction to start execution.

[0061] In step S10, the acquisition unit 30 acquires first biological information relating to multiple items obtained by the measurer measuring the subject at a first time point. In step S12, the acquisition unit 30 acquires second biological information relating to at least one of the multiple items obtained by the subject measuring themselves at a second time point after the first time point.

[0062] In step S14, the estimation unit 32 estimates biological information regarding unmeasured items at estimation time points from the second time point onward, based on the first biological information obtained in step S10 and the second biological information obtained in step S12. An unmeasured item is at least one item from among the multiple items for which the first biological information was obtained in step S10, excluding the item for which the second biological information was obtained in step S12. Note that the estimation of biological information only requires the use of at least a portion of the first biological information obtained in step S10 and the second biological information obtained in step S12, and does not require the use of all of them.

[0063] In step S16, the control unit 34 outputs the biological information estimated in step S14. Once step S16 is completed, this information processing is terminated.

[0064] As described above, the information processing device 10 according to this embodiment includes a processor. The processor acquires first biometric information relating to a plurality of items obtained by the measurer measuring the subject at a first time point. The processor also acquires second biometric information relating to at least one of the plurality of items obtained by the subject measuring themselves at a second time point after the first time point. The processor also estimates biometric information relating to at least one of the plurality of items other than the item for which second biometric information has been acquired, based on the first biometric information and the second biometric information, from the second time point onward.

[0065] In other words, according to the information processing device 10 of this embodiment, based on the first biological information and the second biological information, biological information can be estimated at a desired time point in time when biological information has not yet been acquired (measured). This makes it possible to check the health status at a desired time, even for items that are difficult to measure by self. For example, the health status of items that are only measured during health checkups can be checked at intervals shorter than the intervals between health checkups. Therefore, it is possible to promote health management and improvement.

[0066] In the above embodiment, the acquisition unit 30 was described as acquiring second biological information (results of self-measurement) from the biological information DB 14, but the system is not limited to this. The acquisition unit 30 may also directly acquire second biological information from the user terminal 12. In this case, the second biological information may or may not be stored in the biological information DB 14.

[0067] Furthermore, in the above embodiment, the hardware structure of the processing unit that executes various processes, such as the acquisition unit 30, the estimation unit 32, and the control unit 34, can be the various processors shown below. As mentioned above, these various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, as well as a programmable logic device (PLD), such as an FPGA (Field Programmable Gate Array), whose circuit configuration can be changed after manufacturing, and a dedicated electrical circuit, such as an ASIC (Application Specific Integrated Circuit), which has a circuit configuration specifically designed to execute a particular process.

[0068] A single processing unit may be composed of one of these various processors, or it may be composed of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, multiple processing units may be composed of a single processor.

[0069] Examples of configuring multiple processing units with a single processor include, firstly, a configuration where one or more CPUs and software are combined to form a single processor, as exemplified by client and server computers, and this processor functions as multiple processing units. Secondly, a configuration using a processor that realizes the functions of the entire system, including multiple processing units, on a single IC (Integrated Circuit) chip, as exemplified by System on Chip (SoC). Thus, various processing units are configured, in terms of hardware structure, using one or more of the above-mentioned various processors.

[0070] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits, which are combinations of circuit elements such as semiconductor devices.

[0071] Furthermore, although the above embodiment describes a configuration in which the information processing program 27 is pre-stored (installed) in the storage unit 22, the invention is not limited to this configuration. The information processing program 27 may be provided in the form of a recording medium such as a CD-ROM (Compact Disc Read Only Memory), DVD-ROM (Digital Versatile Disc Read Only Memory), or USB (Universal Serial Bus) memory. Alternatively, the information processing program 27 may be provided in the form of a download from an external device via a network.

[0072] Furthermore, this disclosure is also applicable to programs and program products. Specifically, the information processing program 27 in the above embodiment may be provided as a program product. A program product includes any form of product for providing a program. For example, a program product includes a program provided via a network such as the Internet, and a computer-readable recording medium for non-temporarily storing a program.

[0073] The technology of this disclosure can also be appropriately combined with the above-described embodiments and modifications. The descriptions and illustrations shown above are detailed explanations of the parts relating to the technology of this disclosure and are merely examples of the technology of this disclosure. For example, the above descriptions of the configuration, function, operation, and effect are examples of the configuration, function, operation, and effect of the parts relating to the technology of this disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements added, or replaced from the descriptions and illustrations shown above, as long as they do not deviate from the spirit of the technology of this disclosure.

[0074] Regarding the above embodiments, the following further notes are disclosed. [Note 1] An information processing device comprising a processor, wherein the processor acquires first biological information relating to a plurality of items obtained by a measurer measuring a subject at a first time point, acquires second biological information relating to at least one of the plurality of items obtained by the subject measuring himself at a second time point after the first time point, and estimates biological information relating to at least one of the plurality of items other than the item for which the second biological information was acquired, from the second time point onward, based on the first biological information and the second biological information. [Note 2] The information processing device according to Note 1, wherein the processor outputs the estimated biological information. [Note 3] The information processing device according to Note 1 or Note 2, wherein the processor outputs a statement relating to the estimated biological information. [Note 4] The information processing device according to any one of Notes 1 to 3, wherein the processor determines whether the health condition of the subject has deteriorated based on the estimated biological information, and notifies if the health condition of the subject has deteriorated. [Note 5] The information processing device according to any one of Notes 1 to 4, wherein the processor determines whether the health status of the person being measured has improved based on the estimated biological information, and notifies the person being measured if their health status has improved. [Note 6] The information processing device according to any one of Notes 1 to 5, wherein the processor newly acquires third biological information obtained by a measurer measuring the person being measured at the time the biological information is estimated, relating to the item for which the biological information was estimated, and outputs a sentence corresponding to the difference between the estimated biological information and the third biological information. [Note 7] The information processing device according to any one of Notes 1 to 6, wherein the processor corrects the second biological information based on the difference between the first biological information and the second biological information relating to the same item, and estimates the biological information based on the corrected second biological information.[Note 8] The information processing device according to any one of Notes 1 to 7, wherein the processor estimates the biological information using an estimation model that takes the first biological information and the second biological information as inputs and outputs the biological information at the second time point or later. [Note 9] The information processing device according to Note 8, wherein the estimation model is a machine learning model that has been pre-trained using biological information of multiple items measured at multiple time points for each of multiple subjects as training data. [Note 10] The information processing device according to any one of Notes 1 to 9, wherein the processor estimates the biological information at the second time point. [Note 11] The information processing device according to any one of Notes 1 to 10, wherein the processor estimates the biological information at a third time point after the second time point. [Note 12] The information processing device according to any one of Notes 1 to 11, wherein the processor estimates the biological information at the second time point, and estimates the biological information at a third time point after the second time point based on the first biological information and the second biological information estimated at the second time point. [Note 13] The information processing device according to any one of Notes 1 to 12, wherein the processor estimates the biological information with respect to at least one item among the plurality of items other than the item from which the second biological information was acquired, and other than a predetermined item that can be self-measured by the person being measured. [Note 14] The information processing device according to any one of Notes 1 to 13, wherein the plurality of items include items measured in a health checkup. [Note 15] The information processing device according to any one of Notes 1 to 14, wherein the first biological information includes three-dimensional data representing the body shape of the person being measured. [Note 16] The second biological information is an information processing device according to any one of Notes 1 to 15, including an image obtained by photographing the subject with a camera.[Note 17] An information processing method in which a computer performs a process to obtain first biological information relating to multiple items obtained by a measurer measuring a subject at a first time point, obtain second biological information relating to at least one of the multiple items obtained by the subject measuring himself at a second time point after the first time point, and estimate biological information relating to at least one of the multiple items other than the item for which the second biological information was obtained, based on the first biological information and the second biological information. [Note 18] An information processing program in which a computer performs a process to obtain first biological information relating to multiple items obtained by a measurer measuring a subject at a first time point, obtain second biological information relating to at least one of the multiple items obtained by the subject measuring himself at a second time point after the first time point, and estimate biological information relating to at least one of the multiple items other than the item for which the second biological information was obtained, based on the first biological information and the second biological information.

[0075] The disclosure of Japanese Patent Application No. 2024-163797, filed on September 20, 2024, is incorporated herein by reference in its entirety. All documents, patent applications, and technical standards described herein are incorporated herein by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

Claims

1. An information processing device comprising a processor, the processor acquires first biological information relating to a plurality of items obtained by a measurer measuring a subject at a first time point, acquires second biological information relating to at least one of the plurality of items obtained by the subject measuring himself at a second time point after the first time point, and estimates biological information relating to at least one of the plurality of items other than the item for which the second biological information was acquired, from the second time point onward, based on the first biological information and the second biological information.

2. The information processing apparatus according to claim 1, wherein the processor outputs the estimated biological information.

3. The information processing apparatus according to claim 1, wherein the processor outputs a sentence relating to the estimated biological information.

4. The information processing apparatus according to claim 1, wherein the processor determines whether the health condition of the person being measured has deteriorated based on the estimated biological information, and notifies the person being measured if the health condition of the person being measured has deteriorated.

5. The information processing apparatus according to claim 1, wherein the processor determines whether the health status of the person being measured has improved based on the estimated biological information, and notifies the person being measured if their health status has improved.

6. The information processing apparatus according to claim 1, wherein the processor newly acquires third biological information obtained by the measurer taking measurements of the subject at the time of estimation of the biological information, relating to the item for which the biological information was estimated, and outputs a sentence corresponding to the difference between the estimated biological information and the third biological information.

7. The information processing apparatus according to claim 1, wherein the processor corrects the second biological information based on the difference between the first biological information and the second biological information relating to the same item, and estimates the biological information based on the corrected second biological information.

8. The information processing apparatus according to claim 1, wherein the processor estimates the biological information using an estimation model that takes the first biological information and the second biological information as inputs and outputs the biological information at a second time point or later.

9. The information processing apparatus according to claim 8, wherein the estimation model is a machine learning model that has been pre-trained using biological information of multiple items, measured at multiple time points for each of multiple subjects, as training data.

10. The information processing apparatus according to claim 1, wherein the processor estimates the biological information at the second time point.

11. The information processing apparatus according to claim 1, wherein the processor estimates the biological information at a third time point after the second time point.

12. The information processing apparatus according to claim 1, wherein the processor estimates the biological information at a second time point, and estimates the biological information at a third time point after the second time point based on the first biological information, the second biological information, and the biological information at the second time point that was estimated.

13. The information processing apparatus according to claim 1, wherein the processor estimates the biological information with respect to at least one item among the plurality of items other than the item from which the second biological information was acquired, and other than a predetermined item that can be self-measured by the person being measured.

14. The information processing apparatus according to claim 1, wherein the plurality of items include items measured in a health examination.

15. The information processing apparatus according to claim 1, wherein the first biological information includes three-dimensional data representing the body shape of the person being measured.

16. The information processing apparatus according to claim 1, wherein the second biological information includes an image obtained by photographing the subject being measured with a camera.

17. An information processing method in which a computer performs a process to obtain first biological information relating to multiple items obtained by a measurer measuring a subject at a first time point, obtain second biological information relating to at least one of the multiple items obtained by the subject measuring themselves at a second time point after the first time point, and estimate biological information relating to at least one of the multiple items other than the item for which the second biological information was obtained, based on the first biological information and the second biological information.

18. An information processing program that causes a computer to perform the following processes: acquire first biological information concerning multiple items obtained by a measurer measuring a subject at a first time point; acquire second biological information concerning at least one of the multiple items obtained by the subject measuring themselves at a second time point after the first time point; and estimate biological information from the second time point onward, concerning at least one of the multiple items other than the item for which the second biological information was acquired, based on the first and second biological information.

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