Information processing apparatus, information processing method and information processing program

Abstract

To obtain an information processing apparatus, an information processing method and an information processing program in which severity of disease can be prevented.SOLUTION: An information processing apparatus 10 comprises at least one processor, and the processor acquires vital information measured over time from a user, and derives a degree of severity risk in a case where the user is affected by a disease, on the basis of abnormal tendency which instantaneously occurs in the vital information.SELECTED DRAWING: Figure 3

Description

[Technical Field]

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

[0002] Conventionally, there are known techniques for estimating the risk of aggravation of various diseases when a user is affected by them. For example, Patent Document 1 describes a technique for predicting the severity of various diseases (such as terminal care, severe diabetes-related hypoglycemia, chronic heart failure, angina pectoris, and myocardial infarction) based on the user's biological information.

[0003] Furthermore, for example, Patent Document 2 describes that the risk of infection with an infectious disease is assessed according to attribute information such as the user's age, sex, condition (for example, symptoms such as fever), medical history, medication history, vaccination history, test results, etc. It also describes that the infection risk is increased as the possibility of infection, the possibility of onset after infection, and the possibility of the disease becoming severe increase, thereby identifying users who should be examined with priority and preventing the spread of the infectious disease. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2020-021509 [Patent Document 2] Japanese Patent Application Publication No. 2019-160015 Summary of the Invention [Problem to be solved by the invention]

[0005] The novel coronavirus disease (COVID-19), which has been spreading in recent years, has different symptoms for different individuals, and it is known that those with underlying conditions (e.g., diabetes, and chronic respiratory, cardiac, kidney, and liver diseases) tend to be at a higher risk of developing severe symptoms. Users who have been diagnosed with and are aware of their underlying conditions can take measures to prevent the infection from worsening by taking thorough infection prevention measures themselves and seeking priority medical treatment after infection. In other words, in order to take measures to prevent the infection from worsening, it is necessary to diagnose in advance whether or not the user has an underlying condition.

[0006] On the other hand, it is believed that there are users in the world who have not yet been diagnosed with an underlying disease but who show signs of developing an underlying disease (so-called "pre-disease" and "pre-illness" states). It is also believed that there are users who are not diagnosed with an underlying disease because they are not chronically unwell, but whose condition temporarily deteriorates to the same extent as that of a person with an underlying disease. It is also believed that there are users who have a condition that would be diagnosed as having an underlying disease but have not been diagnosed because they do not have any subjective symptoms, etc. The risk of these users becoming severely ill from the infection is also believed to be the same as that of users who have been diagnosed with an underlying disease.

[0007] Therefore, there is a need for a technology that can prevent an infectious disease from becoming severe by deriving the risk of the infectious disease becoming severe while taking into account temporary changes in the condition without relying on a prior diagnosis. However, the technologies described in Patent Documents 1 and 2 cannot derive the risk of the infectious disease becoming severe while taking into account temporary changes in the condition without relying on a prior diagnosis.

[0008] The present disclosure provides an information processing device, an information processing method, and an information processing program that can prevent a disease from becoming severe. [Means for solving the problem]

[0009] A first aspect of the present disclosure is an information processing device comprising at least one processor, which acquires vital information measured over time from a user and derives the degree of risk of the user's condition becoming severe if the user contracts a disease based on an abnormal trend that momentarily appears in the vital information.

[0010] In the first aspect, the abnormal tendency relates to an underlying disease of the user, and the disease may be a disease different from the underlying disease.

[0011] In the first aspect, the abnormal tendency may be a phenomenon in which, during a measurement period of the vital information, the period during which the vital information is normal is longer than the period during which the vital information is abnormal.

[0012] In the first aspect, vital information of the user may be acquired by monitoring it over time.

[0013] In the first aspect, the disease is an infectious disease, and the user may be a person who has been tested for the infectious disease and received a negative test result, or a person who has not yet been tested for the infectious disease.

[0014] In the first aspect, the disease may be an infectious disease, and the user may have been tested for the infectious disease and received a positive test result.

[0015] In the first aspect, the processor may acquire attribute information indicating attributes of the user, and derive the degree of risk of aggravation based on the vital information and the attribute information.

[0016] In the first aspect, the attribute information may indicate at least one of the user's age, sex, and medical history.

[0017] In the first aspect, the processor may determine whether or not there is an abnormal tendency in the vital information by using a plurality of predetermined thresholds that differ for each piece of attribute information.

[0018] In the first aspect, the processor may acquire a plurality of different types of vital information measured from the user, and derive the degree of risk of aggravation based on the plurality of types of vital information.

[0019] In the first aspect, when the derived degree of risk of aggravation is equal to or greater than a predetermined degree, the processor may notify another device installed in the medical institution of information related to the user.

[0020] In the first aspect, the processor may suggest a method for preventing a disease.

[0021] In the first aspect, the processor may acquire behavioral information indicating the user's behavior, determine based on the behavioral information whether the user is taking measures to prevent disease, and issue a warning if it determines that the user is not taking measures to prevent disease.

[0022] In the first aspect, the method of preventing the disease may be determined according to the degree of risk of the disease becoming severe, which is calculated by the processor.

[0023] In the first aspect, the vital information may indicate at least one of a blood glucose level, a blood glucose equivalent value, an electrocardiogram, arterial oxygen saturation, and blood pressure.

[0024] A second aspect of the present disclosure is an information processing method in which a computer acquires vital information measured over time from a user and executes a process to derive the degree of risk of the user's condition becoming severe if the user contracts a disease based on any abnormal trends that momentarily appear in the vital information.

[0025] A third aspect of the present disclosure is an information processing program that causes a computer to execute a process of acquiring vital information measured over time from a user and deriving the degree of risk of the user's condition becoming severe if the user contracts a disease based on any abnormal trends that momentarily appear in the vital information. [Effects of the Invention]

[0026] According to the above aspects, the information processing device, information processing method, and information processing program of the present disclosure can prevent a disease from becoming severe. [Brief explanation of the drawings]

[0027] [Figure 1] FIG. 1 is a schematic configuration diagram of an information processing system. [Figure 2] FIG. 2 is a block diagram illustrating an example of a hardware configuration of an information processing device. [Figure 3] FIG. 2 is a block diagram illustrating an example of a functional configuration of an information processing device. [Figure 4] FIG. 10 is a diagram showing an example of vital information and its abnormal tendency. [Figure 5] FIG. 10 is a diagram for explaining a blood glucose spike. [Figure 6] FIG. 1 is a diagram for explaining the characteristics of HbA1c. [Figure 7] FIG. 10 is a diagram illustrating an example of a screen displayed on a display. [Figure 8] FIG. 10 is a diagram illustrating an example of a screen displayed on a display. [Figure 9] FIG. 10 is a diagram illustrating an example of control according to the degree of risk of aggravation. [Figure 10] FIG. 10 is a diagram illustrating an example of control according to the degree of risk of aggravation. [Figure 11] FIG. 10 is a diagram illustrating an example of a screen displayed on a display. [Figure 12] 10 is a flowchart illustrating an example of an update process in the information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0028] Hereinafter, examples of embodiments for implementing the technology of the present disclosure will be described in detail with reference to the drawings. First, an example of the configuration of an information processing system 1 according to this embodiment will be described with reference to FIG. 1. As shown in FIG. 1, the information processing system 1 includes an information processing device 10 and a measurement device 3. The information processing device 10 and the measurement device 3 are connected by wireless or wired communication. In this case, for example, Wi-Fi (registered trademark) and Bluetooth (registered trademark) can be applied as appropriate as wireless communication standards.

[0029] The measuring device 3 measures at least one type of vital information of the user over time and transmits the measured vital information to the information processing device 10 via wired or wireless communication. "Measurement over time" means that the vital information is continuously measured at predetermined time intervals. Furthermore, multiple measuring devices 3 that measure different types of vital information may be connected to the information processing device 10.

[0030] Vital information is information indicating at least one of blood glucose level, blood glucose equivalent value, electrocardiogram, arterial oxygen saturation (SpO2), and blood pressure. As the measuring device 3 for measuring blood glucose level, for example, a blood glucose self-metering device using the fingertip prick method may be applied. The blood glucose equivalent value is vital information correlated with the blood glucose level, such as the glucose level in interstitial fluid or blood. As the measuring device 3 for measuring the blood glucose equivalent value, for example, a measuring device that measures the glucose level in interstitial fluid as the blood glucose equivalent value by inserting a filament subcutaneously, and a measuring device that measures the glucose level in blood as the blood glucose equivalent value by using infrared rays may be applied.

[0031] For example, an electrocardiograph that measures an electrocardiogram, a pulse oximeter that measures SpO2, and a sphygmomanometer that measures blood pressure may be applied as the measurement device 3. For example, a wearable device such as a smart watch equipped with sensors that measure the above-mentioned various vital information may be applied as the measurement device 3.

[0032] The information processing device 10 derives the degree of risk of disease aggravation based on abnormal trends in the vital signs information measured by the measurement device 3. In the following embodiment, the novel coronavirus disease (COVID-19) will be used as an example of a disease, but the technology of the present disclosure is also applicable to other infectious diseases (e.g., influenza virus infection, etc.) and various diseases other than infectious diseases. The configuration and functions of the information processing device 10 will be described below.

[0033] First, an example of the hardware configuration of an information processing device 10 according to this embodiment will be described with reference to Fig. 2. As shown in Fig. 2, the information processing device 10 includes a CPU 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 such as a liquid crystal display, an input unit 25 such as a keyboard, a mouse, a touch panel, and buttons, and a network I / F (Interface) 26. The network I / F 26 communicates with the measurement device 3 and an external network (not shown) via wired or wireless communication. The CPU 21, the storage unit 22, the memory 23, the display 24, the input unit 25, and the network I / F 26 are connected via a bus 28 such as a system bus and a control bus so as to be able to exchange various information with each other.

[0034] The storage unit 22 is realized by a storage medium such as a hard disk drive (HDD), a solid state drive (SSD), or a flash memory. The storage unit 22 stores an information processing program 27 for the information processing device 10. The CPU 21 reads the information processing program 27 from the storage unit 22, loads it into the memory 23, and executes the loaded information processing program 27. The CPU 21 is an example of a processor of the present disclosure. For example, a smartphone, a tablet terminal, a wearable terminal, a personal computer, a server computer, or the like can be appropriately applied as the information processing device 10.

[0035] Next, an example of the functional configuration of the information processing device 10 according to this embodiment will be described with reference to Fig. 3. As shown in Fig. 3, the information processing device 10 includes an acquisition unit 30, a derivation unit 32, and a control unit 34. The CPU 21 executes the information processing program 27, causing the CPU 21 to function as the acquisition unit 30, the derivation unit 32, and the control unit 34.

[0036] The acquisition unit 30 acquires vital information measured over time from the user by the measurement device 3 from the measurement device 3. The derivation unit 32 derives the degree of risk of disease aggravation based on an abnormal trend that momentarily appears in the vital information acquired by the acquisition unit 30. An "abnormal trend that momentarily appears" refers to a phenomenon in which vital information is basically normal, but an abnormality is temporarily observed in the vital information. In other words, because the period in which vital information is normal is longer, continuous monitoring of the vital information is required to detect an abnormality.

[0037] An example of vital information and its abnormal tendency is shown in Figure 4. Below, a specific example of a method for deriving the degree of risk of aggravation according to the momentarily occurring abnormal tendency for each piece of vital information shown in Figure 4 will be described.

[0038] [Blood glucose level or blood glucose equivalent] As shown in Figure 4, an example of an abnormal tendency that appears momentarily in blood glucose levels or blood glucose equivalents is a blood glucose spike. Figure 5 shows a diagram illustrating the diurnal fluctuation of blood glucose levels or blood glucose equivalents in which a blood glucose spike is observed. A "blood glucose spike" is a symptom seen in people at risk of developing diabetes, in which blood glucose levels temporarily rise and fall sharply about 1 to 2 hours after eating, even if fasting blood glucose levels are within the normal range.

[0039] The derivation unit 32 may determine that a severe blood glucose spike is observed and derive that the risk of severe illness is high when the blood glucose level or blood glucose equivalent value acquired by the acquisition unit 30 temporarily exceeds a predetermined threshold TH1. On the other hand, the derivation unit 32 may determine that a mild blood glucose spike is observed and derive that the risk of severe illness is medium when the blood glucose level or blood glucose equivalent value acquired by the acquisition unit 30 does not exceed the threshold TH1 but temporarily exceeds a predetermined threshold TH2 (where TH1>TH2). In the example of FIG. 5, the blood glucose level or blood glucose equivalent value temporarily exceeds the predetermined threshold TH1, so the derivation unit 32 derives that the risk of severe illness is high.

[0040] FIG. 6 shows long-term fluctuations in blood glucose levels or blood glucose equivalents from the present time up to four months ago. Generally, blood glucose and HbA1c values ​​obtained through blood tests are used to diagnose diabetes. HbA1c is a value that represents a weighted average of blood glucose levels over the past few months, with the weighting increasing the closer to the present time. It is a value that is not dependent on the diurnal fluctuations in blood glucose levels, as shown in FIG. 5. However, with HbA1c, as shown in FIG. 6, pattern A (shown by the dotted line), in which blood glucose levels have recently dropped sharply, pattern B (shown by the solid line), in which blood glucose levels have recently risen sharply, and pattern C (shown by the dashed-dotted line), in which blood glucose levels have not fluctuated, may all show similar values. In other words, it is difficult to accurately capture the fluctuation trends in blood glucose levels or blood glucose equivalents using HbA1c.

[0041] Therefore, the derivation unit 32 may derive that the blood glucose level is on an improving trend and that the risk of aggravation is low when the blood glucose level or blood glucose equivalent value over time acquired by the acquisition unit 30 shows a sharp downward trend as in pattern A. On the other hand, the derivation unit 32 may derive that the blood glucose level is on a worsening trend and that the risk of aggravation is high when the blood glucose level or blood glucose equivalent value acquired by the acquisition unit 30 shows a sharp upward trend as in pattern B.

[0042] [electro-cardiogram] As shown in Figure 4, an example of an abnormal tendency that may momentarily appear in an electrocardiogram is arrhythmia (e.g., atrial fibrillation and atrial flutter). Arrhythmia is a type of underlying disease of COVID-19, and it is known that there is a high possibility of developing heart disease when infected with COVID-19. Therefore, the derivation unit 32 may derive that there is a high risk of the condition becoming severe when a movement indicative of arrhythmia is observed in the electrocardiogram acquired by the acquisition unit 30.

[0043] [SpO2] As shown in FIG. 4, sleep apnea syndrome is an example of an abnormal tendency that may momentarily appear in SpO2. Sleep apnea syndrome is a type of underlying disease of COVID-19, and it is known that there is a high possibility of developing respiratory failure when infected with COVID-19. The SpO2 value decreases when an apneic state occurs. Therefore, the derivation unit 32 may derive that a tendency toward sleep apnea syndrome is observed and that the risk of the condition becoming severe is high when the SpO2 during sleep acquired by the acquisition unit 30 falls below a predetermined threshold.

[0044] [blood pressure] As shown in Figure 4, nocturnal hypertension is an example of an abnormal tendency that may momentarily appear in blood pressure. It is known that users with nocturnal hypertension are likely to have vascular endothelial damage and organ damage, and are more likely to develop cardiovascular disease when infected with COVID-19. Therefore, the derivation unit 32 may derive that a tendency toward nocturnal hypertension is observed and that the risk of worsening is high when the nighttime blood pressure acquired by the acquisition unit 30 is equal to or higher than a predetermined threshold.

[0045] Furthermore, the derivation unit 32 may derive the degree of risk of aggravation by combining multiple types of vital information. Specifically, the acquisition unit 30 acquires multiple different types of vital information measured from the user from the measurement device 3. The derivation unit 32 derives the degree of risk of aggravation based on the multiple types of vital information acquired by the acquisition unit 30. For example, the derivation unit 32 may derive that the risk of aggravation is low when a mild abnormal trend is observed in only one type of vital information, and that the risk of aggravation is high when a mild abnormal trend is observed in multiple types of vital information.

[0046] If there is insufficient vital information to derive the degree of risk of aggravation, the control unit 34 may present a method for acquiring the vital information. FIG. 7 shows an example of a screen D1 indicating a period during which vital information should be acquired, as an example of a method for acquiring vital information. Screen D1 is a screen displayed on the display 24 by the control unit 34. As shown in FIG. 7, if some of the vital information measured over time is missing, the control unit 34 may notify the user of this and take precautions to prevent the missing information.

[0047] FIG. 8 shows an example of a screen D2 on which the measuring device 3 from which vital information should be acquired is designated, as an example of a method for acquiring vital information. Screen D2 is a screen displayed on the display 24 by the control unit 34. The SpO2 measuring device 3 can be a wearable device such as a smartwatch equipped with a sensor that measures blood oxygen levels using reflected light. However, the accuracy of SpO2 measurements by a wearable device is lower than that of a pulse oximeter that measures blood oxygen levels using transmitted light. Therefore, for example, as shown in FIG. 8, after the derivation unit 32 derives that there is a possibility of sleep apnea syndrome (i.e., there is a risk of aggravation) based on the SpO2 measured by the wearable device, the control unit 34 may recommend acquiring SpO2 using a pulse oximeter.

[0048] The control unit 34 also performs various controls depending on the calculated risk of aggravation. FIG. 9 shows control details depending on the risk of aggravation when the user has already been tested for an infectious disease and the test result was positive. If the user is already infected with an infectious disease, it is preferable to prevent the disease from becoming severe by taking appropriate measures according to the risk of aggravation. Therefore, as shown in FIG. 9, the control unit 34 may cooperate with a medical institution, such as arranging hospitalization or medical care, issuing instructions for monitoring vital signs, and scheduling a medical examination. That is, if the calculated risk of aggravation is equal to or higher than a predetermined level, the control unit 34 may notify another device installed in the medical institution of information about the user. This configuration allows the medical institution to identify users who are at high risk of aggravation and should receive priority medical treatment, thereby effectively preventing the disease from becoming severe.

[0049] FIG. 10 shows control details according to the degree of risk of developing severely when the user has already been tested for an infectious disease and the test result was negative, and when the user has not yet been tested for an infectious disease. For example, for a user with a high risk of developing severely, the control unit 34 may instruct a medical institution to monitor the user's vital signs so that prompt treatment can be provided in the event of infection. Furthermore, for example, as shown in FIG. 10, the control unit 34 may present a method of preventing the disease. In this case, the method of preventing the disease may be based on the level of the risk of developing severely. The various control details according to the degree of risk of developing severely, shown in FIGS. 9 and 10, are pre-stored in the storage unit 22, for example.

[0050] The control unit 34 may also monitor whether the user is taking measures to prevent disease. Specifically, the control unit 34 acquires behavioral information indicating the user's behavior and determines whether the user is taking measures to prevent disease based on the behavioral information. Examples of behavioral information include information indicating the user's location, information indicating movements obtained by sensors such as an acceleration sensor and a gyro sensor, and information indicating whether the user is wearing a mask obtained by analyzing video images captured by a camera. For example, the control unit 34 may determine whether the user has visited a restaurant or a crowded place based on the information indicating the user's location. For example, the control unit 34 may determine whether the user has washed their hands and gargled based on information indicating movements obtained by sensors.

[0051] Furthermore, the control unit 34 may perform control to issue a warning when it is determined that the user is not taking measures to prevent a disease. Fig. 11 shows an example of a screen D3 that is displayed on the display 24 when the user is not wearing a mask, which is an example of a method of preventing a disease. In this way, by monitoring whether the user is properly taking measures to prevent a disease and issuing a warning if the user is not taking measures, it is possible to contribute to preventing the spread of infectious diseases and the aggravation of the disease.

[0052] Next, the operation of the information processing device 10 according to this embodiment will be described with reference to Fig. 12. In the information processing device 10, the CPU 21 executes the information processing program 27, thereby executing the information processing shown in Fig. 12. The information processing is executed, for example, when a command to start execution is received from the user via the input unit 25.

[0053] In step S10, the acquisition unit 30 acquires, from the measurement device 3, vital information measured over time from the user by the measurement device 3. In step S12, the derivation unit 32 derives the degree of risk of disease aggravation based on an abnormal trend that momentarily appears in the vital information acquired in step S10. In step S14, the control unit 34 performs various controls according to the degree of risk of disease aggravation derived in step S12 (for example, notifying other devices installed in the medical institution of information about the user, and presenting disease prevention methods according to the degree of risk of disease aggravation).

[0054] In step S16, the control unit 34 acquires behavioral information indicating the user's behavior. In step S18, the control unit 34 determines whether the user is taking a preventive measure against disease based on the behavioral information acquired in step S16. If it is determined that the user is not taking a preventive measure against disease (i.e., if step S18 is N), in step S20, the control unit 34 performs control to issue a warning to take a preventive measure against disease, and ends this information processing. On the other hand, if it is determined that the user is taking a preventive measure against disease (i.e., if step S18 is Y), the process of step S20 is not performed, and this information processing ends directly.

[0055] As described above, the information processing device 10 according to a preferred embodiment of the present disclosure includes at least one processor, which acquires vital sign information measured over time from a user and derives a degree of risk of disease aggravation based on momentary abnormal trends that appear in the vital sign information. That is, the information processing device 10 according to this embodiment can derive a risk of disease aggravation taking into account temporary changes in the user's condition without relying on a prior diagnosis, thereby preventing the disease from aggravating.

[0056] In the above embodiment, the information processing device 10 may vary the method of deriving the degree of risk of aggravation depending on the user's attributes. Specifically, the acquisition unit 30 may acquire attribute information indicating the user's attributes. The attribute information is, for example, information indicating at least one of the user's age, gender, and medical history. The acquisition unit 30 may acquire attribute information input by the user via the input unit 25, or may acquire attribute information via a network from an electronic medical record managed by an external management server (not shown) installed in a medical institution or the like.

[0057] The derivation unit 32 may derive the degree of risk of severe illness based on the vital information and the attribute information. For example, the derivation unit 32 may determine whether or not there is an abnormal tendency in the vital information using a plurality of predetermined thresholds that differ for each attribute information. That is, the derivation unit 32 may vary the likelihood of determining an abnormal tendency for each user by varying the threshold for determining an abnormal tendency for each attribute information. For example, with regard to COVID-19, it is known that the elderly are at a higher risk of severe illness than the young, men are at a higher risk of severe illness than the females, and those with a medical history (e.g., underlying diseases) are at a higher risk of severe illness than those without. By varying the method for deriving the degree of risk of severe illness depending on these attributes, the risk of severe illness can be more appropriately derived.

[0058] In the above embodiment, the degree of risk of aggravation is expressed in three levels, high, medium, and low (see FIGS. 9 and 10), but this is not limiting. The degree of risk of aggravation may be expressed, for example, as a numerical value.

[0059] In each of the above embodiments, the following various processors can be used as the hardware structure of a processing unit that executes various processes, such as the acquisition unit 30, the derivation unit 32, and the control unit 34. As described above, the various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, as well as dedicated electrical circuits that are processors having a circuit configuration specifically designed to execute specific processes, such as a programmable logic device (PLD), a processor whose circuit configuration can be changed after manufacture, such as an FPGA (Field Programmable Gate Array), and an ASIC (Application Specific Integrated Circuit).

[0060] A single processing unit may be configured with one of these various processors, or may be configured with 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). Also, multiple processing units may be configured with a single processor.

[0061] Examples of configuring multiple processing units with a single processor include, first, a form in which one processor is configured with a combination of one or more CPUs and software, and this processor functions as multiple processing units, as typified by computers such as client and server. Second, a form in which a processor is used to realize the functions of the entire system including multiple processing units with a single IC (Integrated Circuit) chip, as typified by systems on chips (SoCs). In this way, various processing units are configured using one or more of the above-mentioned various processors as a hardware structure.

[0062] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements.

[0063] In addition, in each of the above embodiments, the information processing program 27 is described as being pre-stored (installed) in the storage unit 22, but this is not limiting. The information processing program 27 may be provided in a form recorded on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a USB (Universal Serial Bus) memory. The information processing program 27 may also be downloaded from an external device via a network. Furthermore, the technology of the present disclosure extends to not only information processing programs but also storage media that non-temporarily store information processing programs.

[0064] The technology of the present disclosure can also be combined as appropriate with the above-described exemplary embodiments. The above-described description and illustrations are detailed descriptions of the parts related to the technology of the present disclosure and are merely examples of the technology of the present disclosure. For example, the above description of the configuration, function, action, and effect is an example of the configuration, function, action, and effect of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or new elements may be substituted in the above-described description and illustrations, within the scope of the gist of the technology of the present disclosure. [Explanation of symbols]

[0065] 1. Information Processing Systems 3. Measuring equipment 10. Information processing equipment 21 CPU 22 Memory section 23 Memory 24 displays 25 Input section 26 Network I / F 27 Information Processing Program 28 Bus 30 Acquisition Department 32 Derivation part 34 Control Unit D1~D3 screen

Claims

1. at least one processor; The processor: Acquiring vital information measured over time from the user; Based on the abnormal trends that appear momentarily in the vital signs, the degree of risk of the patient becoming seriously ill in the event of contracting a disease is calculated. Information processing device.

2. The abnormal tendency is related to an underlying disease of the user, The disease is a disease different from the underlying disease. The information processing device according to claim 1 .

3. The abnormal tendency is a phenomenon in which, during a measurement period of the vital information, the period during which the vital information is normal is longer than the period during which the vital information is abnormal.

3. The information processing device according to claim 1.

4. The processor: The vital information of the user is monitored over time and acquired. The information processing device according to any one of claims 1 to 3.

5. the disease is an infectious disease, The user is a person who has been tested for the infectious disease and the test result is negative, or a person who has not been tested for the infectious disease. The information processing device according to any one of claims 1 to 4.

6. the disease is an infectious disease, The user has been tested for the infectious disease and the test result was positive. The information processing device according to any one of claims 1 to 4.

7. The processor: acquiring attribute information indicating attributes of the user; Deriving the degree of risk of aggravation based on the vital information and the attribute information. The information processing device according to any one of claims 1 to 6.

8. The attribute information indicates at least one of the user's age, sex, and medical history. The information processing device according to claim 7 .

9. The processor: Using a plurality of predetermined thresholds that differ for each of the attribute information, it is determined whether or not the vital information has an abnormal tendency.

9. The information processing device according to claim 7 or 8.

10. The processor: acquiring a plurality of different types of vital information measured from the user; Deriving the degree of risk of aggravation based on the plurality of types of vital information. The information processing device according to any one of claims 1 to 9.

11. The processor: If the calculated degree of risk of aggravation is equal to or greater than a predetermined degree, information about the user is notified to another device installed in the medical institution. The information processing device according to any one of claims 1 to 10.

12. The processor: To provide a method for preventing the disease The information processing device according to any one of claims 1 to 11.

13. The processor: acquiring behavioral information indicating the behavior of the user; determining whether the user is taking a preventive measure against the disease based on the behavioral information; If it is determined that the user is not taking preventative measures against the disease, a warning is issued. The information processing device according to any one of claims 1 to 12.

14. The disease prevention method corresponds to the degree of the risk of the disease becoming severe, which is calculated by the processor.

14. The information processing device according to claim 12 or 13.

15. The vital information indicates at least one of a blood glucose level, a blood glucose equivalent value, an electrocardiogram, an arterial blood oxygen saturation level, and a blood pressure. The information processing device according to any one of claims 1 to 14.

16. Acquiring vital information measured over time from the user; Based on the abnormal trends that appear momentarily in the vital signs, the degree of risk of the patient becoming seriously ill in the event of contracting a disease is calculated. An information processing method in which processing is performed by a computer.

17. Acquiring vital information measured over time from the user; Based on the abnormal trends that appear momentarily in the vital signs, the degree of risk of the patient becoming seriously ill in the event of contracting a disease is calculated. An information processing program that causes a computer to execute a process.

Images