Health monitoring system and health monitoring method

Abstract

Provided are a health monitoring system and a health monitoring method which enable daily constant health monitoring without imposing a significant burden on a subject, and contribute to the prevention and improvement of lifestyle-related diseases while maintaining the quality of sleep, leading to healthy longevity.　The health monitoring system uses a non-invasive biometric measurement device for performing biometric measurement of the subject, and is characterized by comprising: a measurement means that is remotely operated from the outside to acquire the internal conditions of the body, such as the inside of an organ or the digestive system, and to measure spatiotemporal information on the internal environmental of the body using an in-vivo cybernetic avatar capable of interacting in vivo; and a visualization means for visualizing the spatiotemporal information on the internal environment of the body measured by the measurement means, the visualization means synthesizing and displaying a measurement result obtained by the biometric measurement device and a measurement result of the spatiotemporal information on the internal environmental of the body obtained by the in-vivo cybernetic avatar.

Description

Health monitoring system and health monitoring method

[0001] The present invention relates to a health monitoring system and a health monitoring method, and more particularly to a health monitoring method suitable for preventing and improving lifestyle-related diseases while maintaining the quality of sleep.

[0002] Recently, research into the relationship between lifestyle-related diseases and sleep has progressed, and it has been shown that lack of sleep has a wide range of effects, including daytime sleepiness and fatigue, an increase in physical and mental complaints such as headaches, emotional instability, and reduced work efficiency related to impaired attention and judgment. Furthermore, it has become clear that when various sleep problems, including lack of sleep, become chronic, they are associated with an increased risk of developing obesity, high blood pressure, type 2 diabetes, heart disease, and cerebrovascular disease, as well as worsening symptoms, and are involved in an increased mortality rate.

[0003] In the daily health monitoring method, the subject's biological information can be monitored using a biometric device, such as a blood pressure monitor, a weight scale, a smartphone-compatible predictive thermometer, a wristband-type life recorder, a pocket-type activity monitor, an upper arm hoseless blood pressure monitor, or a body composition monitor.

[0004] For example, many of the biometric devices mentioned above are designed to work with various devices from the same manufacturer, and cannot be used in combination with devices from other manufacturers. Furthermore, while wristband-type life recorders can measure sleep over a 24-hour period, they have the problem of poor accuracy.

[0005] The results of an annual health check are not enough.

[0006] Frequent medical checkups and diagnoses at hospitals can lead to early detection of illness, but medical expenses can be enormous.

[0007] It is desirable to realize a health monitoring method that enables healthy longevity by performing health monitoring as simply as possible, thereby reducing medical expenses and leading to healthy longevity while maintaining a healthy lifestyle.

[0008] Furthermore, as a recent trend, research is also being conducted into monitoring the spatiotemporal internal environment using cybernetic avatars. As an information processing system using cybernetic avatars, for example, an information processing system that assigns an avatar to an operator and provides a predetermined service has been proposed (Patent Document 1).

[0009] JP 2023-145956 A JP 2022-40919 A ​​JP 6719788 A JP 2018-81397 A JP 2024-40773 A

[0010] The biometric device of Patent Document 2 mentioned above is capable of measuring the sleep of a subject, but suffers from the problem of low measurement accuracy. Another method involves having the subject stay overnight at a hospital and undergoing an overnight polysomnogram test, which is accurate, but places an excessive burden on the subject. The EEG measurement device of Patent Document 2 is useful because it allows sleep measurement at home and provides measurement accuracy almost similar to that of an overnight polysomnogram test. However, this is insufficient because lifestyle-related diseases are not caused solely by sleep problems.

[0011] The methods described in Patent Documents 3 and 4 mentioned above lead to improvements in lifestyle-related diseases, but they are not something that can be easily done at home.

[0012] In the above-mentioned Patent Document 5, weight data is used to generate information on improving lifestyle-related diseases, but there is a problem in that the improvement effect is limited when weight data alone is used.

[0013] The present invention has been devised in view of the above-mentioned problems, and an object of the present invention is to provide a health monitoring system and health monitoring method that enable constant daily health monitoring with relatively little burden on the subject, that helps prevent and improve lifestyle-related diseases while maintaining sleep quality, and that leads to a long and healthy life.

[0014] Another object of the present invention is to provide a health monitoring system and a health monitoring method that are capable of maintaining the quality of sleep and monitoring health and pre-illness with high accuracy.

[0015] Another object of the present invention is to provide a health monitoring method that enables visualization of health monitoring results, encourages behavioral changes in subjects, and enables them to live long, healthy lives.

[0016] It is still another object of the present invention to provide a health monitoring method that can predict the current health condition or the point at which a future disease will worsen.

[0017] In order to achieve the above object, a health monitoring system according to a first aspect of the invention comprises a non-invasive biometric device for measuring the biometric status of a subject, measurement means that is remotely operated from the outside to grasp the internal conditions of the subject, such as the internal organs and digestive system, and measures spatiotemporal internal environment information using an in-vivo cybernetic avatar, and visualization means that visualizes the spatiotemporal internal environment information measured by the measurement means, wherein the visualization means synthesizes and displays the measurement results from the biometric device and the measurement results of the spatiotemporal internal environment information from the in-vivo cybernetic avatar, and the visualization means visualizes the measurement results from the biometric device and the spatiotemporal internal environment information measured by the in-vivo cybernetic avatar, and a body display area for displaying body measurement data, an in-vivo cybernetic avatar display area for displaying the spatiotemporal internal environment information of the subject's body, and a sleep state display area for displaying the subject's sleep state throughout the night on a specific day, and displaying the information using the body display area, the in-vivo cybernetic avatar display area, and the sleep state display area, and not displaying the spatiotemporal internal environment information measured by the measurement means as it is, but linking the type of the in-vivo cybernetic avatar with the part of the human body on which the in-vivo cybernetic avatar is placed to create an avatar image showing a healthy state and a pre-illness state, Furthermore, when the in-vivo cybernetic avatar is placed in the brain, heart, stomach, or intestines, the visualization means displays avatar images of the brain, heart, stomach, and intestines in different display forms depending on whether the avatar is in a healthy state or a pre-disease state, and also displays display patterns for at least the three major disease avatars of "cancer," "cerebral infarction," and "heart disease." If the disease type is "cancer," the visualization means displays an avatar image of the person attacking cancer cells in the healthy state, and an avatar image of the cancer cells gaining momentum in the pre-disease state. In the case of cerebral infarction, the visualization means displays an avatar image of red blood cells swimming freely through blood vessels in the healthy state, and an avatar image of red blood cells having difficulty swimming due to arteriosclerosis in the blood vessels in the pre-disease state. In the case of heart disease, the visualization means displays an avatar image of the heart smiling in the healthy state, and an avatar image of the heart's blood vessels clogged and the heart suffering in the pre-disease state. The sleep state display area divides sleep states into three stages: light sleep, medium sleep, and deep sleep, and displays health and pre-disease.

[0018] The health monitoring system according to a second aspect of the present invention is the health monitoring system of the first aspect, which comprises an electroencephalogram (EEG) measuring device for measuring sleep at home, the electroencephalogram measuring device comprising an electroencephalogram measuring unit attached to the forehead of the subject and a device main body for recording and storing the measurement results, the electroencephalogram measuring unit comprising a plurality of forehead electrodes integrally provided on a horizontal sheet portion, a vertically elongated flat cable extending vertically from the horizontal sheet portion, and left and right arm portions having left and right ear electrodes provided at the tips of the flat cables branching off to the left and right from the vertically elongated flat cable, the plurality of forehead electrodes being attached to the center of the forehead of the subject, and the left and right ear electrodes being attached behind the left and right ears of the subject, to perform an overnight sleep test on a specific day.

[0019] The health monitoring system of the third invention is the first or second invention, characterized in that the in vivo cybernetic avatar is a capsule-type device, a helical ring-type device, a stent-type device, or a combination thereof.

[0020] A health monitoring system according to a fourth aspect of the present invention is the health monitoring system of the first or second aspect of the present invention, further comprising a body-wearable device, and the body-wearable device measures the amount of exercise of the subject.

[0021] delete

[0022] The health monitoring method of the sixth invention is characterized by comprising a biometric information acquisition step of acquiring biometric information of a subject using at least a sphygmomanometer, a thermometer, and a weight scale; a behavioral information acquisition step of acquiring behavioral information, which is physical activity information, from a body-wearable device; a health checkup result information acquisition step of acquiring health checkup result information including at least brain images and in-vivo endoscopic images; an analysis step of analyzing the acquired biometric information, behavioral information, and health checkup result information of the subject; and an estimation step of estimating the subject's future health condition using the results of the above analysis and the subject's biometric information, behavioral information, and health checkup result information.

[0023] The health monitoring method according to the seventh invention is the same as that of the sixth invention, and further comprises an electroencephalogram (EEG) measurement step of measuring the electroencephalogram (EEG) of the subject's sleep state at home, and is characterized in that the electroencephalogram (EEG) measurement step performs a sleep test equivalent to a polysomnogram test.

[0024] According to the present invention having the above configuration, it is possible to realize a health monitoring system and health monitoring method that enables constant daily health monitoring with relatively little burden on the subject, helps prevent and improve lifestyle-related diseases while maintaining sleep quality, and leads to a long and healthy life.

[0025] According to the present invention, it is possible to realize a health monitoring system and a health monitoring method that are capable of maintaining the quality of sleep and of monitoring health and pre-illness with high accuracy.

[0026] Furthermore, according to the present invention, it is possible to realize a health monitoring method that makes it possible to visualize health monitoring results, encourage behavioral changes in subjects, and achieve healthy longevity.

[0027] According to the present invention, a health monitoring method can be realized that can predict the current health state or the location where a disease will worsen in the future.

[0028] FIG. 1 is a functional block diagram of a health monitoring system according to an embodiment of the present invention. FIG. 2 is a functional block diagram of a health monitoring system according to an embodiment of the present invention. FIG. 3 is a diagram illustrating an example of spatiotemporal internal body environment information according to an embodiment of the present invention. FIG. 4 is a diagram illustrating an example of a measurement result composite display. FIG. 5(a) is an external configuration diagram illustrating an example of the electroencephalogram measuring device of FIG. 1, and FIG. 5(b) is a diagram illustrating an example of a device main body that records and transmits sleep measurement data. FIG. 6 is an external view of a capsule endoscope as an in-vivo sensor and a diagram illustrating an example of the configuration of its tip portion. FIG. 7(a) is a diagram illustrating an example of a helical-type device as an in-vivo sensor, FIG. 7(b) is a diagram illustrating an example of a ring-type device as an in-vivo sensor, and FIG. 7(c) is a diagram illustrating an example of a stent-type device as an in-vivo sensor. FIG. 8 is a system configuration diagram of a cloud server network-connected to a mobile communication terminal. FIG. 9 is a diagram illustrating an example of a mobile communication terminal to which the present invention is applied. FIG. 10 is a diagram illustrating an example of a personal computer to which the present invention is applied. FIG. 11 is a diagram illustrating an example of a body display area according to an embodiment of the present invention. FIG. 12 is a diagram illustrating an example of an in-vivo cybernetic avatar display area according to the present invention. FIG. 13 is a diagram showing an example of a display of three major disease avatars. FIG. 14 is a diagram showing an example of a sleep state display area. FIG. 15 is a diagram showing criteria for display in the physical activity display area. FIG. 16 is a flowchart showing a health monitoring method in an embodiment of the present invention. FIG. 17 is a flowchart showing a health monitoring method in a biometric device. FIG. 18 is a flowchart showing a health monitoring method in a body-wearable device. FIG. 19 is a diagram showing other examples of lifestyle-related disease names. FIG. 20 is a diagram showing an example of a physical activity display area in an embodiment of the present invention. FIG. 21 is a diagram showing an example of personal health checkup data (part 1) used in an embodiment of the present invention. FIG. 22 is a diagram showing an example of personal health checkup data (part 2) used in an embodiment of the present invention. FIG. 23 is a configuration diagram of an online collaboration system for sharing health monitoring results of subjects. FIG. 24 is a diagram showing an example of measurement data from a body-wearable device.Fig. 25 is a diagram for explaining the process of combining measurement data from various measurement devices. Fig. 26 is a functional block diagram of a health management application in an embodiment of the present invention. Fig. 27 is a flowchart showing a health monitoring method in an embodiment of the present invention. Fig. 28 is a flowchart showing a health monitoring method in another embodiment of the present invention. Fig. 29 is a schematic block diagram of an integrated data analysis service system to which the present invention is applied. Fig. 30 is a schematic block diagram of a biometric device verification service system to which the present invention is applied.

[0029] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, exemplary embodiments of the present invention will be described with reference to the accompanying drawings.

[0030] First, health monitoring systems 100a and 100b according to embodiments of the present invention will be described with reference to FIGS. 1, 2, 3, and 4. FIG.

[0031] Fig. 1 is a functional block diagram of a health monitoring system according to an embodiment of the present invention, Fig. 2 is a functional block diagram of a health monitoring system according to an embodiment of the present invention, Fig. 3 is a diagram showing an example of spatiotemporal internal body environment information according to an embodiment of the present invention, and Fig. 4 is a diagram showing an example of a composite display of measurement results.

[0032] As shown in FIG. 1, the health monitoring system 100a of this embodiment includes a biometric device 1, an in-vivo CA (cybernetic avatar) measurement unit 2, a measurement result synthesis unit 3, and a visualization unit 4.

[0033] As shown in Figure 2, the health monitoring system 100b of this embodiment includes a biometric device 1, an in-vivo CA (cybernetic avatar) measurement unit 2, a measurement result synthesis unit 3, a visualization unit 4, and an electroencephalogram (EEG) measurement device 5. The health monitoring system 100b shown in Figure 2 is the same as that shown in Figure 1 except for the electroencephalogram (EEG) measurement device 5.

[0034] The biometric device 1 is a device that non-invasively measures the biometric information of a subject in daily life. Examples of the biometric device 1 include a blood pressure monitor, a thermometer, a weight scale, and the like. While the example in FIG. 1 shows the devices as an integrated unit, they may be configured as separate units and connected to the health monitoring system 100a via wireless communication. The biometric device may also include a blood glucose meter, and since a blood glucose meter collects blood from a fingertip or the like and measures it, it also includes a non-invasive measurement device. The biometric device 1 may perform measurements daily and store the measurement data, or may perform measurements every other day or every week.

[0035] The in-vivo CA measurement unit 2 is remotely operated from the outside to grasp the internal conditions of the body, such as the organs and digestive system, and measures spatiotemporal internal body environment information using an in-vivo cybernetic avatar (CA) that can interact within the body.

[0036] The measurement result synthesizing unit 3 synthesizes the measurement result of the biometric device 1 and the measurement result of the in-vivo CA measuring unit 2 .

[0037] The visualization unit 4 visualizes the biometric data combined by the measurement result combination unit 3 and the spatiotemporal internal body environment information measured by the in vivo CA measurement unit 2, and displays them on a mobile communication terminal or the like. The visualization unit 4 may be configured to combine and display the measurement results from the biometric device 1 and the measurement results of the spatiotemporal internal body environment information measured by the in vivo CA measurement unit 2. An example of the spatiotemporal internal body environment information is shown in FIG. 3. The spatiotemporal internal body environment information includes in vivo pH measurement information, in vivo imaging information, core body temperature information, sleep state information, blood glucose level information, etc. Other biometric information may also be included. FIG. 4 shows an example of a visualization display by the visualization unit 4. FIG. 4 shows an example of a display screen of, for example, a mobile communication terminal, and is composed of a body display area, an in vivo cybernetic avatar display area, a sleep state display area, and a physical activity display area. The body display area is an area where daily biometric data is displayed. The in vivo cybernetic avatar display area is an area where in vivo spatiotemporal internal body environment information is displayed. The sleep state display area is an area where the sleep state throughout the night on a specific day is displayed. This embodiment is characterized by its visualization display format. While various measurement results may be displayed as is, visualizing the subject's health status and pre-disease state using avatars provides an opportunity for the subject to change their behavior. In particular, lifestyle-related diseases are caused by daily lifestyle habits (e.g., diet, exercise, smoking, stress), and therefore, unless the subject improves their lifestyle, they will not be able to achieve a long and healthy life. Therefore, by displaying the subject's health status and pre-disease state using avatars, visualization that appeals to the subject's visual sense is provided. Naturally, conventional numerical information and trend displays may also be used. Recent research has revealed that sleep plays an important role in preventing lifestyle-related diseases. Therefore, to maintain sleep quality, a well-known electroencephalogram (EEG) measuring device 5 that can be easily measured at home is used. The electroencephalogram measuring device 5 is described below.

[0038] The EEG measurement device 5 measures the sleep state of a subject at home or elsewhere. An example of the EEG measurement device 5 is shown in Figures 5(a) and 5(b). The EEG measurement device 5 comprises an EEG measurement unit worn on the subject's head and a device main unit 20 for recording and storing the measurement results. The EEG measurement unit includes a horizontally elongated portion 6 equipped with a left center forehead electrode 6a, a reference electrode 6b, and a right center forehead electrode 6c; a vertically elongated portion 8 (flat cable) extending vertically from the horizontally elongated portion 6; and a left arm portion and a right arm portion each having a left ear electrode 7a and a right ear electrode 7b at their respective ends. The flat cable 8 has a connector 10 at its end for connection to the device main unit 20. Its extremely simple and unique shape allows it to be easily worn by a single subject in a short time and is available at low cost. Its design also takes into consideration comfort and does not disturb sleep. This allows the subject to use the device easily at home, enabling sleep assessment under normal circumstances. Furthermore, because the forehead electrodes (6a, 6b, 6c) are integrally formed on the sheet-like horizontal portion 6 and their relative positions are fixed, simply attaching the sheet-like horizontal portion 6 to the forehead allows the electrodes to be positioned in the same relative positions each time. By attaching the forehead electrodes (6a, 6b, 6c) to the subject's forehead, eye movements can be detected in addition to EEG. Furthermore, by attaching the left ear electrode 7a and the right ear electrode 7b behind the subject's left and right ears, neck electromyography can be detected in addition to EEG. Therefore, the ability to utilize eye movements and neck electromyography signals in addition to EEG improves the accuracy of sleep assessment.

[0039] As shown in Fig. 6(b), the device main body 20 has a control unit 21, a connector unit 22, a memory unit 23, an operation unit 24, a display unit 25, and a battery 26. A known device (Patent Document 2) can be used as the electroencephalogram measuring device shown in Figs. 6(a) and 6(b). Details are as described in Patent Document 2, and therefore a description thereof will be omitted.

[0040] Although wearable devices can measure sleep, their accuracy is low, so the results can only be used as a reference. While going to a hospital for an overnight polysomnogram test provides accurate sleep measurements, the method requires the subject to stay overnight at the hospital, placing a significant burden on the subject. Using the simple EEG measurement device described above to perform measurements at home is relatively less invasive and highly accurate, allowing for accurate measurement of sleep quality.

[0041] 6(a) and 6(b) are diagrams showing the configuration of a capsule endoscope 30 as an in-vivo CA sensor used in the in-vivo CA measurement unit 2. FIG.

[0042] As shown in Figures 6(a) and 6(b), the capsule endoscope 30 includes a distal end cover 31, LED illuminators 32a, 32b, 32c, and 32d, and an objective lens 34. Although not shown, the capsule endoscope 30 also includes a CMOS sensor element, electrical circuitry, and an internal battery that capture images by receiving light from the LED illuminators 32a, 32b, 32c, and 32d through the objective lens 34. The capsule endoscope 30 is housed in a case that does not consume power so that it can be used only when the capsule endoscope is in use. When the capsule endoscope 30 is removed from the case, the power switch is turned on. Measurements are performed using a wireless communication sensor for capturing image information from the capsule endoscope 30 and a device for recording signals from the wireless communication sensor. Measurements typically take approximately eight hours. Figures 6(a) and 6(b) are similar to known devices, and therefore will not be described here.

[0043] Figure 7(a) is a diagram showing an example of a helical-type device as an in-vivo sensor, Figure 7(b) is a diagram showing an example of a ring-type device as an in-vivo sensor, and Figure 7(c) is a diagram showing an example of a stent-type device as an in-vivo sensor.

[0044] As shown in FIG. 7A, the helical device 40 has a sensor 41 that measures information such as pH in the living body, core body temperature, and blood sugar level.

[0045] As shown in FIG. 7B, the ring-shaped device 42 has biosensors 42, 43, and 44 that measure information such as pH in the living body, core body temperature, and blood sugar level.

[0046] As shown in FIG. 7(c), the stent-type device 42 has biosensors 47, 48, and 49 for measuring information such as pH, core body temperature, and blood sugar level in the living body.

[0047] In the above embodiment, an in vivo sensor has been described, but the present invention can be implemented by applying the intracellular sensing technology disclosed in Japanese Patent Nos. 5,551,355 and 5,526,345.

[0048] FIG. 8 is a system configuration diagram of a cloud server 63 connected to a mobile communication terminal 50 and a network 62.

[0049] As shown in FIG. 8, the mobile communication terminal 50 has a CPU 51, a ROM 52, a RAM 53, a display 54, a biometric authentication memory unit 55, an ID / password authentication unit 56, a touch input unit 57, a camera 58, a speaker 59, a microphone 60, and a communication interface 61.

[0050] The mobile communication terminal 50 is connected to a cloud server 63 via a network 62 such as an internetwork or a broadband network. In such a communication system, a health monitoring system may be implemented using software, and health monitoring may be performed by installing a health monitoring app 72 on a mobile communication terminal 70 as shown in FIG. 9 and executing the health monitoring app 72. The example in FIG. 9 shows a state in which an icon for the health monitoring app 72 is displayed on a screen 71. FIG. 10 shows an example of a personal computer. The personal computer includes a camera 73, a display 74, a screen 75 that displays the visualized information in the display format shown in FIG. 4, and a fingerprint authentication unit 76 displayed on the keyboard. Biometric authentication may be performed using face authentication using the camera 73.

[0051] The visualization display of the present invention will be described below. FIG. 11 shows an example of a body display area. In the example of FIG. 11, blood pressure 120 / 80 mmHg, pulse rate 60 bpm, body temperature 36.8°C, and weight 54 kg are displayed. A minimum amount of personal information is registered in the health monitoring app when a user registers. For example, information such as height, age, gender, and BMI may be registered. Other information may also be registered. An individual's health checkup results (see FIGS. 21 and 22) may be digitized and stored in a mobile communication device or the like, and a comparison display may be performed. For example, if the weight has increased significantly compared with the weight in the health checkup results, the user may not be healthy, but may be predicted to be in pre-illness (1) or pre-illness (2) (here, pre-illness (2) indicates a worse health condition than pre-illness (1)), and an estimate may be displayed.

[0052] Figure 12 shows an example of a display pattern displayed in the in-vivo cybernetic avatar display area. In the in-vivo CA measurement unit 2, the type of in-vivo CA measured is linked to the associated body part and turned into an avatar to show the healthy state and pre-illness state. Since the subject is not an expert even if the numerical values ​​of the measurement information are displayed as is, the subject's behavior is encouraged to change. When the in-vivo sensor is placed in the brain part, the displayed image of the brain avatar changes depending on the healthy state, pre-illness (1) state, and pre-illness (2) state. For healthy, an image of a smiling brain is displayed; for pre-illness (1), an image of the brain appearing to be slightly distressed is displayed; and for pre-illness (2), an image of the brain appearing to be distressed is displayed.

[0053] Similarly, if an in-vivo sensor is placed in the heart, the avatar image of the heart is changed and displayed as healthy, pre-disease (1), or pre-disease (2). If an in-vivo sensor is placed in the stomach, the avatar image of the stomach is changed and displayed as healthy, pre-disease (1), or pre-disease (2). Furthermore, if an in-vivo sensor is placed in the intestine, the avatar image of the intestine is changed and displayed as healthy, pre-disease (1), or pre-disease (2). The type of in-vivo CA may be configured to create and display an avatar image for each organ.

[0054] In this way, displaying an in vivo cybernetic avatar appeals intuitively to the subject's visual sense, and is expected to promote behavioral change.

[0055] FIG. 13 shows example display patterns for avatars displaying the three major diseases. Examples of the diseases shown are cancer, cerebral infarction, and heart disease. For cancer, the healthy state shows an avatar image attacking cancer cells, the pre-disease (1) state shows an avatar image in which cancer cells are slightly gaining momentum, and the pre-disease (2) state shows an avatar image in which cancer cells are also gaining momentum. For cerebral infarction, the healthy state shows an avatar image in which red blood cells are swimming freely through blood vessels, the pre-disease (1) state shows an avatar image in which blood vessels have slightly developed arteriosclerosis, making it difficult for red blood cells to swim, and the pre-disease (2) state shows an avatar image in which blood vessels have developed arteriosclerosis, making it difficult for red blood cells to swim. For heart disease, the healthy state shows an avatar image in which the heart's blood vessels are slightly clogged, the pre-disease (1) state shows an avatar image in which the heart's blood vessels are slightly clogged, causing slight pain, and the pre-disease (2) state shows an avatar image in which the heart's blood vessels are clogged and enlarged, causing pain.

[0056] FIG. 14 shows an example of a display pattern for the sleep status display area. It illustrates the relationship between sleep status and health, pre-illness (1), and pre-illness (2). Sleep status data measured by the EEG measurement device shown in FIG. 6 is uploaded to the cloud server 63, and a report of the EEG analysis service results is received. Sleep status is then categorized into three stages, for example, "light sleep," "moderate sleep," and "deep sleep." Light sleep indicates a high risk of illness, so pre-illness (2) is displayed. Moderate sleep indicates disrupted lifestyle habits, so pre-illness (1) is displayed. Deep sleep indicates that sleep quality is maintained, so "healthy" is displayed. Since sleep quality assessment can be performed at home, similar to an overnight polysomnography test, it is effective in preventing and improving lifestyle-related diseases. FIG. 19 shows an example of a lifestyle-related disease. While FIG. 14 describes the display of avatar images for the three major diseases, similar avatar images may also be displayed for hypertension, dementia, diabetes, hyperlipidemia, hyperuricemia, pulmonary hypertension, and other conditions.

[0057] FIG. 15 shows a list of recommendations in the physical activity and exercise guide 2023 for health promotion. The list of recommendations in FIG. 15 is used as a standard for the amount of physical activity displayed in the physical activity display area. In FIG. 15, subjects are divided into elderly people, adults, and children, and physical activity (including daily activities and exercise) and sedentary behavior. For elderly people, daily activities are walking or physical activity of an equivalent intensity (3 METs or more) for 40 minutes or more per day (6,000 steps or more per day), and exercise is multi-component exercise such as aerobic exercise, strength training, balance exercise, and flexibility exercise for 3 days or more per week, and strength training for 2-3 days per week.

[0058] For example, if the subject is elderly and 67 years old, the recommended daily step count is 6,000 steps or more. Therefore, the physical activity display area shown in FIG. 20 displays the number of steps for daily activities as 7,500, which exceeds the recommended value and is therefore displayed as OK. Exercise options include one aerobic exercise OK, three strength training OK, and two balance exercise OK. Here, exercise is displayed by converting it into METs and exercise. METs are a unit that expresses the intensity of physical activity as a multiple of resting time. For example, sitting and resting corresponds to 1 MET, and normal walking corresponds to 3 METs. Exercise is a unit that expresses the amount of physical activity. It is calculated by multiplying the intensity of physical activity (METs) by the duration of physical activity (hours). The more intense the physical activity, the shorter the time required for one exercise. Energy expenditure (Kcal) is calculated by 1.05 x exercise (METs x hours) x body weight (kg).

[0059] Figure 16 is a flowchart showing a health monitoring method according to an embodiment of the present invention. First, an in-vivo CA measurement step is performed (step 101). Internal conditions, such as those inside the organs and digestive system, are grasped by remote control from the outside, and spatiotemporal internal body environment information is measured using an in-vivo cybernetic avatar that can interact with the body (step 102). Next, a measurement result recording step is performed (step 103). The recorded measurement results are then transmitted to a mobile communication terminal (step 104). A measurement result synthesis step is performed (step 105), in which the measurement results from the biometric device and the measurement results of the spatiotemporal internal body environment information from the in-vivo cybernetic avatar are synthesized and displayed. A visualization step is performed (step 106), in which the measurement results synthesized in the measurement result synthesis step 105 are visualized, as shown in Figure 4.

[0060] 17 is a flowchart showing a health monitoring method using a biometric device. First, a biometric measurement step is performed (step 201). Next, a measurement result recording step is performed (step 202). Next, the recorded measurement results are transmitted to a mobile communication terminal (step 203). Next, the recorded measurement results are transmitted to the mobile communication terminal (step 204).

[0061] FIG. 18 is a flowchart illustrating a health monitoring method using a body-worn device, and FIG. 24 shows an example of a body-worn device capable of 24-hour continuous monitoring. Devices that can be used 24 hours a day include ring-type (finger ring type), watch-type, and tracker-type devices, and data is not compatible between manufacturers. For example, a ring-type device manufactured by Company A has a health app A dedicated to Company A and can utilize physical activity data A. Similarly, a watch-type device manufactured by Company B has a health app B dedicated to Company B and can utilize physical activity data B. A tracker device manufactured by Company C has a health app B dedicated to Company C and can utilize physical activity data C. In this embodiment, the health monitoring method extracts a portion of the physical activity data A, B, or C obtained by measurement using these body-worn devices, synthesizes it with in-vivo CA measurement data, and visualizes it. FIG. 25 shows an example of the synthesized display of the measurement results. First, a physical activity amount measurement step is performed (step 301). Next, a measurement result recording step is performed (step 302). Next, the recorded measurement results are transmitted to the portable communication terminal (step 303). Next, the recorded measurement results are transmitted to the portable communication terminal (step 304).

[0062] FIG. 23 is a configuration diagram of an online collaboration system for sharing health monitoring results of subjects.

[0063] As shown in FIG. 23, the online collaboration system 80 includes an online collaboration server 81 , subject terminals 82 a and 82 b , a communication network 83 , primary care doctor terminals 84 a and 84 b , and an administrator terminal 85 .

[0064] The subject terminals 82a, 82b are connected to a family doctor terminal 84a or a hospital terminal 84b via a communication network 83, and measurement data of the subject may be shared. By sharing data, the subject's measurement data can be obtained, enabling the family doctor or hospital doctor to provide appropriate medical treatment, which is expected to lead to a reduction in medical expenses.

[0065] FIG. 26 is a functional block diagram of a health management application according to an embodiment of the present invention.

[0066] As shown in FIG. 26 , the health management app 400 in this embodiment has a blood pressure recording unit 401, a weight recording unit 402, a body temperature recording unit 403, a body-worn device recording unit 404, a sleep recording unit 405, a step count recording unit 406, an exercise recording unit 407, a pre-illness visualization unit 408, an external linkage unit 409, and a health management dashboard unit 401.

[0067] The health management application 400 is installed in advance on a mobile communication device such as a smartphone, a tablet PC, a portable laptop, a desktop computer, or the like, and then used. For example, the application may be installed in advance on a mobile communication device, and the health management application 400 may be launched, and measurement data from a blood pressure monitor, a weight scale, and a thermometer may be automatically recorded using a short-range wireless communication function. Alternatively, the measurement data may be manually entered by the subject. When using the health management application 400, height data, age, and gender (male or female; gender entry may be omitted if not desired) are required. The subject's name (nickname is acceptable) should also be entered, as this is the minimum information required for effective health management.

[0068] The blood pressure recording unit 401 records the subject's systolic blood pressure data and diastolic blood pressure data, which are measurement data from the sphygmomanometer. If the sphygmomanometer can measure pulse rate, pulse data may be recorded at the same time. It is desirable to measure blood pressure multiple times, such as in the morning, afternoon, and evening. If blood pressure cannot be measured in the afternoon, the afternoon measurement may be omitted. At the very least, measurement should be performed and recorded once when waking up in the morning.

[0069] The weight recording unit 402 receives and records weight data from a weight scale via wireless, wired, or manual input. The weight scale may be a body composition scale. Weight is measured and recorded at least once in the morning when the user wakes up.

[0070] The temperature recording unit 403 may automatically record the temperature data from the thermometer if it has a communication function. If the thermometer does not have a communication function, the subject must manually input the temperature data.

[0071] The body-worn device recording unit 404 records various measurement data from the body-worn device, such as sleep measurement data, heart sound data, and pulse data.

[0072] The sleep recording unit 405 records sleep-related data from the electroencephalogram measuring device described above.

[0073] The step count recording unit 406 is linked to a pedometer and allows automatic input or manual input by the subject. Automatic input is more preferable in order to reduce the burden of recording on the subject.

[0074] The exercise recording unit 407 manually inputs whether or not muscle training or resistance exercise has been performed.

[0075] The pre-disease visualization unit 408 displays a pre-disease avatar. Various other data may also be visualized.

[0076] The external linking unit 409 has a function to transmit the above-mentioned measurement data to a family doctor's terminal or a hospital terminal for data sharing, or a data conversion function to convert and transfer data for linking with other health management apps.

[0077] The health management dashboard unit 401 controls the overall health condition data, such as displaying trends of health management data, displaying various charts, etc. It also outputs reports of health management data.

[0078] The health management application 400 described above records the subject's subjective symptoms. For example, sleepiness upon waking up is evaluated on a three-point scale and recorded. This is to obtain data from the subject that cannot be obtained from measurement data and to use it to determine whether the subject is healthy or not. For example, sleepiness may be rated as "refreshed," "normal," or "sleepy." Other subjective symptom parameters may also be set as subjective symptom parameters.

[0079] In this specification, pre-illness refers to a state in which there are no subjective symptoms but tests show abnormalities, and a state in which there are subjective symptoms but tests show no abnormalities. Health refers to a state in which there are no subjective symptoms but tests show no abnormalities. Illness refers to a crossover state in which there are subjective symptoms but tests show abnormalities.

[0080] FIG. 27 is a flowchart illustrating a health monitoring method according to an embodiment of the present invention.

[0081] The health monitoring method of this embodiment comprises a biometric information acquisition step 501 of acquiring biometric information of the subject using at least a sphygmomanometer, a thermometer, and a weight scale; a behavioral information acquisition step 502 of acquiring behavioral information, which is physical activity information, from a body-wearable device; a health checkup result information acquisition step 503 of acquiring health checkup result information including at least brain images and in-vivo endoscopic images; an analysis step 504 of analyzing the acquired biometric information, behavioral information, and health checkup result information of the subject; and a health condition estimation step 505 of estimating the future health condition of the subject using the results of the above analysis and the biometric information, behavioral information, and health checkup result information of the subject.

[0082] At least blood pressure data, body temperature data, and weight data are acquired in the biological information acquisition step 501. Blood glucose data may also be acquired as other biological information.

[0083] In the behavior information acquisition step 502, physical activity information (step count data, muscle training data, etc.) is acquired.

[0084] In the health check result information acquisition step 503, in-vivo information of the subject's brain image and in-vivo endoscopic image is acquired and used in the next analysis step.

[0085] In the analysis step 504, the acquired biological information, behavioral information, and health check result information of the subject are analyzed. Genetic testing and other information may also be added to the analysis data. By creating a health condition model using the health check big data and utilizing AI analysis technology, prediction accuracy can be improved.

[0086] In the health condition estimation step 505, the results of the above analysis and the subject's biological information, behavioral information, and health examination result information are used to estimate the subject's future health condition, predict whether the subject is healthy or not, and predict areas that will deteriorate in the future.

[0087] FIG. 28 is a flowchart illustrating a health monitoring method according to another embodiment of the present invention.

[0088] A health monitoring method according to another embodiment includes an electroencephalogram (EEG) measuring step 601, a biological information acquiring step 602, a behavioral information acquiring step 603, a health checkup result information acquiring step 604, an analysis step 605, and a health condition estimating step 606. Here, the biological information acquiring step 602, the behavioral information acquiring step 603, the health checkup result information acquiring step 604, the analysis step 605, and the health condition estimating step 606 are similar to the biological information acquiring step 501, the behavioral information acquiring step 502, the health checkup result information acquiring step 503, the analysis step 504, and the health condition estimating step 505, respectively, and therefore their explanations will be omitted and only the electroencephalogram measuring step 601 will be described.

[0089] In the EEG measurement step 601, EEG measurements of the sleep state of the subject are performed at home. In the EEG measurement step 601, a sleep test equivalent to a polysomnogram test is performed. The EEG measurement device used is the one shown in FIG. 5. Here, by performing sleep measurement, the influence of sleep on the subject's progression to lifestyle-related diseases can be taken into account, thereby improving the accuracy of prediction of the subject's health state.

[0090] FIG. 29 is a schematic block diagram of an integrated data analysis service system to which the present invention is applied.

[0091] As shown in FIG. 29 , this integrated data analysis service system 700 integrates a sleep analysis service 701, a brain image analysis service 702, a health checkup analysis service 703, and a pre-disease prediction service 704, providing them as a solution package to support diagnosis at hospitals and clinics. Current analysis services are each provided as a single service, which poses a problem of inability to provide comprehensive assessments. This service is provided as one means to solve this problem. For example, the sleep analysis service "InSomnograf" provided by S'UIMIN Co., Ltd. can be used as the sleep analysis service 701. For example, the device disclosed in Japanese Patent Laid-Open Publication No. 2022-40919 (Patent Document 2) can be used as a brain measurement device. For example, the brain analysis service disclosed in International Patent Publication No. 2023-190880 can be used as the brain image analysis service 702. This brain analysis service is effective because it analyzes the entire brain image, and is desirable because it allows brain image analysis that is not affected by the resolution of the brain scan image.

[0092] FIG. 30 is a schematic block diagram of a biometric device verification service system to which the present invention is applied.

[0093] As shown in FIG. 30, this biometric device verification service system 800 is composed of a biometric device verification unit 801, biometric device measurement big data 802, and an AI biometric device proposal unit 803. Since biometric devices vary from company to company and have different measurement accuracy, the resulting prediction results may differ. This system verifies the biometric device using measurement big data and uses AI to propose a biometric device that guarantees prediction accuracy. This is expected to have the effect of maintaining a consistent prediction accuracy of AI analysis results.

[0094] Thus, according to the embodiments of the present invention, it is possible to realize a health monitoring system and a health monitoring method that enable constant daily health monitoring with relatively little burden on the subject, that helps prevent and improve lifestyle-related diseases while maintaining sleep quality, and that leads to a long and healthy life.

[0095] Furthermore, according to the embodiments of the present invention, it is possible to realize a health monitoring system and a health monitoring method that are capable of maintaining the quality of sleep and monitoring health and pre-illness with high accuracy.

[0096] Furthermore, according to the embodiment of the present invention, it is possible to realize a health monitoring method that can visualize health monitoring results, encourage behavioral changes in subjects, and achieve healthy longevity.The health monitoring method of this embodiment can predict the current health state and body parts that will deteriorate in the future.

[0097] The present invention can be applied to a health monitoring system and a health monitoring method that can prevent and improve lifestyle-related diseases while maintaining the quality of sleep.

[0098] 1 Biometric measurement device 2 In-vivo CA measurement unit 3 Measurement result synthesis unit 4 Visualization unit 5 Electroencephalogram measurement device 6 Electroencephalogram measurement unit 6a, 6b, 6c: Electrodes 7a, 7b Electrodes 8, 9 Flat cable 10 Connector 20 Device main body 21 Control unit 22 Connector unit 23 Memory unit 24 Operation unit 25 Display unit 26 Battery 30 Capsule endoscope 31 Tip cover 32a, 32b, 32c, 32d LED illumination 34 Objective lens 40 Helical device 41 Biometric sensor 42 Ring device 43, 44, 45 Biometric sensor 46 Stent device 47, 48, 49 Biometric sensor 50 Portable communication terminal 51 CPU 52 ROM 53 RAM 54 Display 55 Biometric authentication memory unit 56 ID / password authentication unit 57 Touch input unit 58 Camera 59 Speaker 60 Microphone 61 Communication interface 62 Network 63 Cloud server 70 Portable communication terminal 71 Portable screen 72 Health monitoring application 73 Camera 74 Display 75 Personal computer screen 76 Biometric authentication unit 80 Online linkage system 81 Online linkage server 82a, 82b Subject terminal 83 Network 84a Family doctor terminal 84b Hospital terminal 85 Administrator terminal 100a, 100b Health monitoring system 101 In-vivo CA measurement step 102 Time-space internal body environment measurement step 103 Measurement result recording step 104 Measurement result transmission step 105 Measurement result synthesis step 106 Visualization step 201 Biometric measurement step 202 Measurement result recording step 203 Measurement result transmission step 204 Recording to portable communication terminal step 301 Physical activity amount measurement step 302 Measurement result recording step 303 Measurement result transmission step 304 Recording to mobile communication terminal step 400 Health management application 401 Blood pressure recording unit 402 Weight recording unit 403 Body temperature recording unit 404 Body-worn device recording unit 405 Sleep recording unit 406 Step count recording unit 407 Exercise recording unit 408 Pre-disease visualization unit 409 External linkage unit 410 Health management dashboard unit 501, 602 Biometric information acquisition step 502, 603 Behavioral information acquisition step 503, 604 Health check result information acquisition step504, 605 Analysis step 505, 606 Health condition estimation step 601 EEG measurement step 700 Integrated data analysis service system 701 Sleep analysis service 702 Brain image analysis service 703 Health check analysis service 704 Future prediction service 800 Biometric device verification unit 801 Biometric device measurement big data 803 AI biometric device proposal unit

Claims

1. A health monitoring system comprising: a non-invasive biometric device for measuring the biometrics of a subject; measurement means for remotely controlling the device from the outside to grasp the internal conditions of the subject's organs, digestive system, etc., and for measuring spatiotemporal internal environment information using an in-vivo cybernetic avatar; and visualization means for visualizing the spatiotemporal internal environment information measured by the measurement means, wherein the visualization means synthesizes and displays the measurement results from the biometric device and the measurement results of the spatiotemporal internal environment information from the in-vivo cybernetic avatar, the visualization means has a body display area in which the subject's daily biometric data is displayed, an in-vivo cybernetic avatar display area in which the subject's spatiotemporal internal environment information is displayed, and a sleep state display area in which the subject's sleep state throughout the night on a particular day is displayed; and the visualization means performs display using the body display area, the in-vivo cybernetic avatar display area, and the sleep state display area; and the visualization means does not display the spatiotemporal internal environment information measured by the measurement means as is, but rather associates the type of the in-vivo cybernetic avatar with the part of the human body on which the in-vivo cybernetic avatar is placed, and displays an avatar image indicating a healthy state and a pre-illness state; Furthermore, when the in-vivo cybernetic avatar is placed in the brain, heart, stomach, or intestines, the visualization means displays avatar images of the brain, heart, stomach, and intestines in different display forms depending on whether the avatar is in a healthy state or a pre-disease state, and also displays display patterns for at least the three major disease avatars of "cancer," "cerebral infarction," and "heart disease." If the disease type is "cancer," the visualization means displays an avatar image of the brain attacking cancer cells in the healthy state and an avatar image of the cancer cells gaining momentum in the pre-disease state. In the case of cerebral infarction, the visualization means displays an avatar image of red blood cells swimming freely through blood vessels in the healthy state and an avatar image of red blood cells having difficulty swimming due to arteriosclerosis in the blood vessels in the pre-disease state. In the case of heart disease, the visualization means displays an avatar image of the heart smiling in the healthy state and an avatar image of the heart suffering due to clogged blood vessels in the pre-disease state. In the sleep state display area, the sleep states are divided into three stages: light sleep, medium sleep, and deep sleep, and display the health and pre-disease states.

2. A health monitoring system as described in claim 1, which has an electroencephalogram (EEG) measuring device for measuring sleep at home, said EEG measuring device comprising an EEG measuring unit attached to the forehead of the subject and a device main body for recording and saving the measurement results, said EEG measuring unit comprising a plurality of forehead electrodes integrally attached to a horizontal sheet portion, a vertically elongated flat cable extending vertically from said horizontal sheet portion, and left and right arm portions having left and right ear electrodes attached to the tips of the flat cables branching out to the left and right from said vertically elongated flat cable, said plurality of forehead electrodes being attached to the center of the forehead of the subject and said left and right ear electrodes being attached behind the left and right ears of the subject to perform an overnight sleep test of the subject's sleep state on a specific day.

3. A health monitoring system according to claim 1 or 2, wherein the in vivo cybernetic avatar is a capsule-type device, a helical ring-type device, a stent-type device, or a combination thereof.

4. A health monitoring system according to claim 1 or 2, further comprising a body-wearable device, which measures the subject's exercise amount.

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