Analysis device and analysis method

Abstract

The present invention estimates the mealtime of a subject. This analysis device is provided with: an acquisition unit for acquiring a pulse wave of a subject which is measured continuously by a wearable device in a first period of time after a meal period in which the subject takes a meal; a change detection unit for detecting a before-meal pulse wave of the subject; and an index estimation unit for estimating the change in a metabolism index that correlates with the hardness of a blood vessel of the subject.

Description

Analytical device and analytical method

[0001] The present disclosure relates to an analysis device and the like that analyzes the pulse wave of a subject.

[0002] Dietary therapy, one of the treatment methods for diabetes, aims to suppress rapid changes in blood sugar levels after meals. In order to continue dietary therapy, it is important for the patient to recognize the connection between the contents of the food and the physical reactions when ingested.

[0003] Patent Document 1 discloses a technique for acquiring a pulse wave of a subject and estimating a blood glucose level based on a metabolic index calculated from the waveform of the acquired pulse wave.

[0004] Japanese Patent No. 6807481

[0005] An analysis device according to one aspect of the present disclosure includes an acquisition unit that acquires pulse waves of a subject measured continuously using a wearable device during a first period following a meal period in which the subject consumes a meal, a detection unit that detects the subject's pre-meal pulse waves from the pulse waves acquired by the acquisition unit, and an index estimation unit that estimates a change in a metabolic index that correlates with the stiffness of the subject's blood vessels based on the change in the pulse waves detected by the detection unit.

[0006] An analysis method according to one aspect of the present disclosure includes an acquisition step of acquiring a subject's pulse wave continuously measured using a wearable device during a first period following a meal period in which the subject ingests a meal; a detection step of detecting the subject's pre-meal pulse wave in the acquired pulse wave; and an index estimation step of estimating a change in a metabolic index correlated with the stiffness of the subject's blood vessels based on the change in the detected pulse wave.

[0007] 1 is a diagram showing an example of an overall outline of an analysis system according to the present embodiment; FIG. 1 is a diagram showing a state in which a subject wears a measurement device; FIG. 2 is a functional block diagram showing an example configuration of an analysis system; FIG. 3 is a diagram showing an example of changes in a pulse wave detected by the analysis device; FIG. 4 is a diagram showing an example presentation presented by the analysis device; FIG. 5 is a diagram showing another example presentation presented by the analysis device; FIG. 6 is a flowchart showing an example of a processing flow in the analysis device; FIG. 7 is a functional block diagram showing an example configuration of an analysis system according to another embodiment; FIG. 8 is a functional block diagram showing an example configuration of an analysis system according to yet another embodiment; FIG. 9 is a diagram showing an example configuration of an analysis system according to yet another embodiment; FIG. 10 is a diagram showing an example of an overall outline of an analysis system including a server; FIG. 11 is a functional block diagram showing another example configuration of an analysis system; FIG. 12 is a diagram showing an example presentation presented by the analysis device; FIG. 13 is a diagram showing another example presentation presented by the analysis device; FIG. 14 is a flowchart showing an example of a processing flow in the analysis device; FIG. 15 is a functional block diagram showing an example configuration of an analysis system according to another embodiment; FIG. 16 is a functional block diagram showing an example configuration of an analysis system according to yet another embodiment;

[0008] It is not easy to make subjects aware of problems with their diet and to establish appropriate eating habits. To establish appropriate eating habits, it is effective to encourage subjects to do so based on the amount of time that has passed since the last meal.

[0009] An analysis device according to one aspect of the present disclosure provides an analysis system or the like that is capable of estimating a meal time, which is any timing during a subject's meal period.

[0010] According to one aspect of the present disclosure, an analysis device can estimate a subject's meal times without receiving active input from the subject. The analysis device can also present the estimated meal times to the subject, encouraging the subject to be aware of their own meal times and providing encouragement to the subject based on the amount of time elapsed since the meal time. Furthermore, the analysis device can help the subject recognize problems with their own diet (e.g., inconsistencies in meal times) and help them establish appropriate eating habits.

[0011] Furthermore, in order to help subjects establish appropriate eating habits, it is effective to have them recognize the connection between the contents of their meals and their own physical reactions after consuming the meal.

[0012] According to one aspect of the present disclosure, an analysis device presents a message to a subject according to the magnitude of change in a metabolic index of the subject after a meal. Because metabolic indices are correlated with vascular stiffness, the magnitude of change in a metabolic index of the subject after a meal can be said to represent the magnitude of the impact of the subject's meal on the subject. Therefore, by presenting a message to the subject according to the magnitude of change in metabolic indices, the analysis device can enable the subject to recognize the association between the content of their meal and their own physical reaction after consuming the meal. In this way, the analysis device can enable the subject to recognize problems with their diet and establish appropriate eating habits.

[0013] [Embodiment 1] [Summary] Insulin is a peptide hormone that plays an important role in glucose metabolism. Diabetes is a metabolic disorder caused by insufficient insulin action. Subjects who are suffering from or at risk of developing diabetes (i.e., those with insufficient insulin secretion) experience a significant rise in blood glucose levels after meals. Here, "meal" refers to the general intake of nutrients that affect the endocrine system involved in metabolism, and includes all eating and drinking, including only the intake of beverages, including alcoholic beverages. Furthermore, meals are not limited to meal times such as breakfast, lunch, and dinner.

[0014] The present inventors focused on the fact that the "vascular state" changes due to fluctuations in blood glucose levels before and after meals and reactions of the secretory system, such as insulin secretion, which in turn changes the waveform of the pulse wave. They then discovered that it is possible to estimate a subject's blood glucose level and blood glucose-related indicators (metabolic indicators) that are affected by insulin secretion capacity, based on the subject's pulse wave. The present inventors then invented an analysis device 10 and an analysis method that enable the implementation of their invention.

[0015] The analysis device 10 acquires pulse waves of a subject continuously measured during a first period following a meal period during which the subject consumes a meal, and detects the subject's pre-meal pulse wave from the acquired pulse waves. The analysis device 10 then estimates a metabolic index correlated with the subject's vascular stiffness based on changes in the detected pulse waves. The analysis device 10 also estimates the subject's mealtime based on the estimated changes in the metabolic index. The mealtime refers to the period between the meal start time when the subject begins eating and the meal end time when the subject ends eating, i.e., any timing during the meal period during which the subject is eating. Here, the subject's pulse waves during the first period are acquired using a wearable device (measurement device 20).

[0016] This allows the analysis device 10 to estimate a metabolic index correlated with vascular hardness caused by a meal for a subject who has eaten a meal, and to estimate the meal time based on the metabolic index. The analysis device 10 can also take action based on the estimated meal time. Actions based on the meal time may include, for example, presenting the meal time to the subject or providing a notification based on the time elapsed since the meal time. This allows the analysis device 10 to make the subject aware of information related to their meal time and the time elapsed since the meal time, and to encourage the subject to make efforts to maintain or improve their diet and eating habits.

[0017] Hereinafter, one embodiment of the present disclosure will be described.

[0018] [Analysis System 1] First, an overview of an analysis system 1 including an analysis device 10 according to this embodiment will be described with reference to Figures 1, 2, and 3. Figure 1 is a diagram showing an example of an overall overview of the analysis system 1. Also, Figure 2 is a diagram showing a state in which a measurement device 20 is worn by a subject. Figure 3 is a functional block diagram showing an example configuration of the analysis system 1. As shown in Figure 1, the analysis system 1 includes the analysis device 10 and the measurement device 20. The analysis system 1 is a system in which the analysis device 10 analyzes the pulse wave of the subject measured by the measurement device 20 and presents the results to the subject. Details of the measurement device 20 and the analysis device 10 will be described below.

[0019] [Measuring Device 20] As shown in FIG. 3, the measuring device 20 includes a sensor unit 21 and a communication unit 22.

[0020] The sensor unit 21 continuously detects displacement of the subject's body surface to acquire a pulse wave. A pulse wave is a waveform obtained from the body surface that represents the change in blood volume over time in the blood vessels caused by the inflow of blood. In this specification, acquiring a pulse wave by the sensor unit 21 is referred to as measuring a pulse wave. Here, "continuously detecting" refers to detecting displacement of the subject's body surface at predetermined regular intervals, for example. The predetermined regular period can be set to, for example, 1 minute, 10 minutes, 30 minutes, or 1 hour. The predetermined regular interval may be changed depending on predetermined conditions, for example.

[0021] Furthermore, the sensor unit 21 may detect the subject's body surface by increasing the measurement frequency during the first period compared to other periods in accordance with an instruction from the analysis device 10. The measurement frequency may indicate, for example, the number of measurements during a predetermined period.

[0022] The communication unit 22 communicates wirelessly with the analysis device 10 and transmits the subject's pulse wave acquired by the sensor unit 21 to the analysis device 10 as pulse wave data.

[0023] When communication between the measurement device 20 and the analysis device 10 is established, the communication unit 22 may transmit the pulse wave data to the analysis device 10 at a predetermined timing. The predetermined timing may be a timing specified by the analysis device 10.

[0024] For example, when communication between the measurement device 20 and the analysis device 10 is not established, the measurement device 20 stores the pulse wave acquired by the sensor unit 21 as pulse wave data in a storage unit (not shown). When communication between the measurement device 20 and the analysis device 10 is established, the measurement device 20 transmits the pulse wave data that it had stored up until then to the analysis device 10, and while communication is established, it transmits the pulse wave data to the analysis device 10 at predetermined timings.

[0025] Furthermore, communication unit 22 may process the pulse wave data so that it is easier for analysis by analysis device 10, rather than transmitting the pulse wave data itself, and transmit the processed pulse wave data to analysis device 10. If the volume of the processed pulse wave data is smaller than the volume of the pulse wave data, the volume of data transmitted to analysis device 10 can be reduced.

[0026] The measuring device 20 is a wearable device that can be worn by the subject at all times. As shown in FIG. 1 , the measuring device 20 may be, for example, in the shape of a ring that can be worn on the subject's finger. FIG. 2 is a diagram illustrating an example of how the measuring device 20 is used. FIG. 2 shows the subject wearing the measuring device 20 on his or her right hand. As shown in FIG. 2 , the ring-shaped measuring device 20 allows the subject to wear the measuring device 20 at all times without feeling uncomfortable, and eliminates the need to remove the measuring device 20 each time a measurement is performed. By using the measuring device 20, the analysis system 1 can reduce the risk of forgetting to measure, etc. Here, the measuring device 20 may be worn anywhere on the subject's body as long as it can continuously measure the subject's pulse wave. It is not limited to being a wearable device worn on a finger. For example, the measuring device 20 may be a wristband-type device that can be worn on the wrist or a collar-type device that can be worn around the neck.

[0027] The measuring device 20 may include an acceleration sensor (not shown) and a temperature sensor (not shown). If the measuring device 20 includes an acceleration sensor, the measuring device 20 can detect the subject's movements. If the measuring device 20 includes a temperature sensor, the measuring device 20 can measure the subject's body temperature. For example, the analysis system 1 can determine the subject's behavior (e.g., walking, sleeping, eating, etc.) based on the subject's finger movements detected by the measuring device 20. The analysis system 1 can also determine the subject's health condition, etc., based on the subject's body temperature measured by the measuring device 20.

[0028] [Analysis Device 10] Next, the analysis device 10 will be described with reference to Fig. 3. As shown in Fig. 3, the analysis device 10 includes an acquisition unit 11, a control unit 12, a presentation unit 13, and a storage unit 14. The control unit 12 also includes a change detection unit (detection unit) 121, an index estimation unit 122, and a time estimation unit 123.

[0029] The acquisition unit 11 acquires, from the measurement device 20, pulse wave data of the subject continuously measured by the measurement device 20. The acquisition unit 11 may acquire pulse wave data of the subject continuously measured during a period (first period) following a meal period in which the subject ingests a meal. In this specification, the "predetermined period after the subject actually eats a meal" is referred to as the "first period." The first period may be, for example, a period from 30 minutes after a meal to one and a half hours after the meal, or a period from immediately after eating to four hours. The analysis device 10 may continuously acquire pulse wave data during the period in which communication with the measurement device 20 is established. In this case, the pulse wave data acquired by the analysis device 10 may include pulse wave data during the first period. As described below, changes in the pulse wave occur after the subject eats a meal. The analysis device 10 detects changes in the pulse wave due to eating by analyzing the continuously measured pulse waves of the subject. Furthermore, by performing an analysis based on this change, the analysis device 10 can estimate that the timing of the change occurred during the "first period." Therefore, by acquiring and analyzing pulse wave data during a period that includes the first period, the analysis device 10 can estimate the meal time, which is the timing when the subject ate a meal. As described above, the first period is a convenient name that indicates a period during which a change in the pulse wave can be detected, and the analysis device 10 does not need to know the first period.

[0030] The acquisition unit 11 may acquire pulse wave data at a predetermined frequency, in which case the acquisition frequency during the first period may be higher than the acquisition frequency during periods other than the first period, thereby enabling a rapid analysis of changes in the pulse wave after a meal.

[0031] Furthermore, the pulse wave of the subject acquired by the acquisition unit 11 may include a pulse wave measured during the subject's meal period. By including a pulse wave measured during the subject's meal period, the pulse wave measured during that period can also be analyzed by the analysis device 10.

[0032] Furthermore, the pulse wave of the subject acquired by the acquisition unit 11 may include a period (second period) before the subject's meal period. The pulse wave of the period before the subject's meal period can be used when the change detection unit 121 (described later) detects a change in the subject's pulse wave.

[0033] The control unit 12 controls the analysis device 10 and includes the change detection unit 121, the index estimation unit 122, and the time estimation unit 123, as described above.

[0034] The change detection unit 121 detects the pulse wave of the subject before a meal from the pulse wave acquired by the acquisition unit 11, and detects changes from the pulse wave of the subject before a meal.

[0035] The change detection unit 121 may detect a change by comparing the pulse wave during the first time period acquired by the acquisition unit 11, beat by beat, with the pulse wave during one beat before the subject's meal. Alternatively, the change detection unit 121 may detect a change by comparing the pulse wave during a predetermined period (e.g., 10 minutes) during the first time period with the pulse wave during the same period before the subject's meal.

[0036] Here, when calculating a metabolic index (e.g., AI) described below, the metabolic index may be calculated using a representative pulse waveform generated using an average value calculated by collecting multiple pulse waveforms for one beat over a predetermined period of time as "for each pulse wave." Alternatively, the metabolic index may be calculated from each of multiple pulse waveforms for one beat over a predetermined period of time, and the average may be used as the metabolic index for the predetermined period of time. More specifically, for example, if 70 pulse waves are acquired over one minute as "for each pulse wave," the metabolic index may be calculated from each of the 70 pulse waves, and the average may be used as the metabolic index for that one minute.

[0037] When detecting changes for each pulse wave beat, the change detection unit 121 may detect changes from, for example, differences in peak values ​​or differences in the way the pulse wave falls. Here, the change detection process by the change detection unit 121 will be described with reference to FIG. 4 . FIG. 4 is a diagram illustrating an example of changes in the pulse wave detected by the analysis device 10. Graph 401 in FIG. 4 is an example of a pulse wave before a meal, and graph 402 is an example of a pulse wave during a first period. Comparing peak X1 of graph 401 with peak X2 of graph 402, it can be seen that peak X2 of graph 402 is larger than peak X1 of graph 401. It can also be seen that the way the falling portion falls is different between point Y1 of graph 401 and point Y2 of graph 402. In this way, the change detection unit 121 detects changes in the pulse wave from the differences between peaks X1 and X2 and between points Y1 and Y2.

[0038] Alternatively, a change in the pulse wave may be detected from the ratio Y1 / X1 of the second peak Y1 to the first peak X1 in graph 401 and the ratio Y2 / X2 of the second peak Y2 to the first peak X2 in graph 402. That is, the change detection unit 121 may detect a change in the pulse wave based on whether or not the ratio Y2 / X2 to the ratio Y1 / X1 has changed by a predetermined value or more.

[0039] Returning to Figure 3, when detecting a change from the pulse wave for a specified period, the change detection unit 121 may detect the change by comparing the pulse wave for a specified period in the first period with the pulse wave for a specified period of the subject before eating.

[0040] The index estimation unit 122 estimates a metabolic index correlated with the stiffness of the blood vessels of the subject based on the change detected by the change detection unit 121. Examples of metabolic indexes include, but are not limited to, an index AI (Augmentation Index) expressed as the ratio of the waveform size of the forward wave of the pulse wave to that of the reflected wave region that appears later than the forward wave, or a pulse transit time PTT (Pulse Transit Time) that is the time difference between the forward wave and the reflected wave of the pulse wave.

[0041] The index estimation unit 122 estimates metabolic indices based on an estimation formula created by, for example, regression analysis. The estimation formula is stored in advance in the analysis device 10.

[0042] Here, we will explain the estimation theory for estimating metabolic indicators based on pulse waves. After a meal, an increase in blood glucose levels causes a decrease in blood fluidity (increased viscosity), vascular dilation, and an increase in circulating blood volume. Vascular dynamics and hemodynamics are determined so that these conditions are in equilibrium. A decrease in blood fluidity occurs, for example, due to an increase in plasma viscosity or a decrease in red blood cell deformability. Vascular dilation occurs due to the secretion of insulin and digestive hormones, an increase in body temperature, and other factors. Vascular dilation suppresses a decrease in blood pressure, thereby increasing the pulse rate. Furthermore, an increase in circulating blood volume compensates for the blood consumption required for digestion and absorption. These factors also affect the stiffness of blood vessels.

[0043] The changes in vascular dynamics and hemodynamics before and after a meal due to these factors are also reflected in the pulse wave, so the index estimation unit 122 can estimate a metabolic index correlated with vascular stiffness based on the changes in the waveform of the pulse wave acquired via the acquisition unit 11.

[0044] Based on the above estimation theory, an estimation formula for estimating metabolic indices can be created by performing regression analysis based on sample data of pre- and post-prandial metabolic indices and pulse waves obtained from multiple subjects. During estimation, the metabolic indices of the subject can be estimated by applying the created estimation formula to indices based on the subject's pulse waves. In particular, by performing regression analysis using sample data in which the variation in metabolic indices is close to a normal distribution, the metabolic indices of the subject to be tested can be estimated regardless of whether the subject is pre- or post-prandial.

[0045] A metabolic index, for example, the value of the index AI (AI value), tends to decrease after a meal and reach its lowest peak some time after the meal. In other words, the subject is considered to have been eating at a time some time before the metabolic index reaches its lowest peak. Therefore, by identifying the time when the metabolic index reaches its lowest peak, the time estimation unit 123 can estimate the subject's meal time to be several tens of minutes before that time.

[0046] The time estimation unit 123 acquires the metabolic index estimated by the index estimation unit 122 and estimates the meal time based on the change in the metabolic index. The time estimation unit 123 may identify a time point at which the metabolic index significantly changed and estimate the meal time from the identified time point. For example, the time estimation unit 123 may identify the time when the metabolic index reached its lowest peak after rising from a predetermined reference value (reference value) that serves as a reference for the change in the metabolic index, and estimate the meal time to be several tens of minutes before that time (e.g., 90 minutes before that time). The time estimation unit 123 may cause the presentation unit 13 to present the estimated meal time. The time estimation unit 123 may provide the subject with other information depending on, for example, the elapsed time from the estimated meal time to the time the estimation was made. The time estimation unit 123 may also store log data 142 including the estimated meal time in the storage unit 14. The log data 142 may associate the estimated meal time with other data, such as a record of the corresponding metabolic index, a record of the pulse wave, and information indicating the time the estimation was made.

[0047] The time estimation unit 123 may also estimate the subject's meal times based on, in addition to changes in metabolic indices, the relationship between the subject's past meal times and information indicating the subject's condition at those past meal times. In this case, the log data 142 stores a plurality of correct answer data related to the subject's past meal times in association with the subject's pulse waves measured after each past meal time. The correct answer data is information indicating the time the subject actually ate a meal. The correct answer data may be input by the subject himself / herself or by a person managing the subject's meals. The correct answer data may be recorded in association with the subject's pulse wave at that meal time. The time estimation unit 123 may adjust estimation parameters for estimating the meal times based on the correspondence between the plurality of recorded correct answer data and the pulse waves associated with each correct answer data. The time estimation unit 123 can improve the accuracy of estimating the subject's meal times by using the adjusted estimation parameters to estimate the meal times based on changes in the detected metabolic indices.

[0048] Further, other information may be associated with the correct answer data stored in the log data 142. For example, information indicating vibrations associated with the subject's movements detected at the estimated meal time and information indicating the subject's body temperature may be associated with the correct answer data. In this case, the time estimation unit 123 may further use this information to adjust the estimation parameters. This can further improve the accuracy of the meal time estimation performed by the time estimation unit 123.

[0049] The timing at which the correct data is input is not particularly limited. As an example, the correct data may be input by the subject operating the measuring device 20 when the subject is about to eat. In this case, pulse wave measurement values ​​may be recorded more frequently for a predetermined period after the correct data is input. Alternatively, the correct data may be input at any timing after the subject has eaten. In this case, the control unit 12 records the input correct data in association with information indicating the subject's pulse wave at the time when the correct data was input, which is already recorded in the log data 142.

[0050] Furthermore, the reference value for the change in metabolic index may be a value during a period when the metabolic index is stable and low. For example, the time estimation unit 123 may use a metabolic index estimated based on the pulse wave of the subject when waking up or when fasting as a reference (first reference), and identify meal times based on changes in the metabolic index relative to the reference. Here, the subject's "waking up" may refer to, for example, when the subject wakes up from sleep, or may be defined by a sleep stage (e.g., REM sleep, which is close to waking up). Furthermore, the subject's "fasting" may refer to, for example, when the subject has not eaten for a predetermined period (e.g., after a fasting period of 10 hours or more), or when the subject has eaten less than a predetermined reference amount.

[0051] The method for identifying the subject's wake-up time or fasting time is not particularly limited. As an example, the measurement device 20 may be provided with an input unit (not shown) that can input the wake-up time or the time of fasting state. As another example, the measurement device 20 may estimate the subject's fall asleep and wake-up time from the subject's pulse, acceleration indicating changes in posture, body surface temperature, etc. Furthermore, the fasting time may be automatically set after a predetermined time has elapsed since eating, or may be estimated from changes in the pulse wave.

[0052] Alternatively, the time estimation unit 123 may use a metabolic index estimated based on pulse waves previously measured for the subject as a reference (first reference). The reference may be, for example, an average of values ​​of metabolic indexes estimated in the past during a period with relatively little fluctuation, or the lowest value of metabolic indexes estimated in the past.

[0053] Furthermore, the time estimation unit 123 may identify a reference by referring to the log data 142 in the storage unit 14, and then identify the meal time of the subject's most recent meal based on a change in the most recent metabolic index relative to the reference. By using a metabolic index based on a previously measured pulse wave as a reference, it is possible to identify how the metabolic index fluctuates over time relative to past metabolic indexes, and to manage the chronic progression of conditions such as diabetes.

[0054] The presentation unit 13 presents the meal times estimated by the time estimation unit 123 to the subject. Examples of the presentation unit 13 include a display, a monitor, etc. Fig. 5 is a diagram showing an example of presentation by the analysis device 10. In the presentation example shown in Fig. 5, the meal times are presented in area 131 of the presentation unit 13, metabolic indices are presented in area 132, and pulse wave data are presented in area 133.

[0055] FIG. 6 is a diagram showing another example of presentation by the analysis device 10. The analysis device 10 may perform presentation as shown in FIG. 6. 601 in FIG. 6 is another example of presentation including meal times. In 601 in FIG. 6, meal times are presented in area 611, and information on AI values ​​as metabolic indicators is presented in area 612. 602 in FIG. 6 is also a presentation example of fluctuations in metabolic indicators. In 602 in FIG. 6, AI values ​​as metabolic indicators are presented in area 621, and fluctuations in the AI ​​values ​​are presented in area 622.

[0056] The analysis device 10 may also present other information. If the difference in meal times over a predetermined period (e.g., one week) exceeds a preset reference value, an evaluation result indicating that meal times were irregular may be presented. As yet another example, if the interval between a subject's meal times is too long or too short, the analysis device 10 may present a message encouraging the subject to eat meals at appropriate intervals.

[0057] The storage unit 14 stores data used by the analysis device 10 , including pulse wave data 141 and log data 142 .

[0058] The pulse wave data 141 is data on the subject's pulse wave before a meal, which is used by the change detection unit 121 to detect changes in the pulse wave. This may be a pulse wave measured in advance, or a pulse wave measured before the most recent meal. The log data 142 is data in which the meal time estimated by the time estimation unit 123 is associated with the pulse wave and metabolic index used for the estimation.

[0059] As described above, the analysis device 10 according to the present disclosure includes an acquisition unit 11 that acquires pulse waves of a subject continuously measured using a wearable device (measurement device 20) during a first period following a meal period in which the subject ingests a meal. The analysis device 10 also includes a change detection unit 121 (detection unit) that detects the subject's pre-meal pulse waves among the pulse waves acquired by the acquisition unit 11. The analysis device 10 also includes an index estimation unit 122 that estimates a change in a metabolic index that correlates with the subject's vascular stiffness based on the change in the pulse wave detected by the change detection unit 121. The analysis device 10 also includes a time estimation unit 123 that estimates a meal time, which is any timing during the meal period, based on the change in the metabolic index.

[0060] This allows the analysis device 10 to estimate the subject's meal times without receiving active input from the subject. The analysis device 10 can also present the estimated meal times to the subject, encouraging the subject to be aware of their own meal times and providing encouragement to the subject based on the amount of time that has elapsed since the meal time. Furthermore, the analysis device 10 can help the subject recognize problems with their own diet (e.g., inconsistencies in meal times), leading to the establishment of appropriate eating habits.

[0061] [Processing Flow] Next, the processing flow in the analysis device 10 will be described with reference to FIG. 7 . FIG. 7 is a flowchart showing an example of the processing flow in the analysis device 10. As shown in FIG. 7 , the acquisition unit 11 acquires pulse waves continuously measured by the measurement device 20 during a first period (S101, acquisition step). Next, the change detection unit 121 detects a pre-meal pulse wave from the pulse waves acquired by the acquisition unit 11 (S102, detection step). Then, the index estimation unit 122 estimates a metabolic index based on the change in the pulse wave detected by the change detection unit 121 (S103, index estimation step). Thereafter, the time estimation unit 123 estimates the subject's meal time based on the change in the metabolic index estimated by the index estimation unit 122 (S104, time estimation step). Then, the presentation unit 13 presents the subject's meal time estimated by the time estimation unit 123 (S105, presentation step).

[0062] The above is the flow of processing in the analysis device 10.

[0063] [Embodiment 2] Another embodiment of the present disclosure will be described below. For convenience of explanation, components having the same functions as those described in the above embodiment will be denoted by the same reference numerals, and their descriptions will not be repeated. Furthermore, descriptions of the present embodiment that overlap with the above embodiment will be omitted.

[0064] The main configuration of an analysis system 1A according to this embodiment is shown in Fig. 8. As shown in Fig. 8, the analysis system 1A includes a measurement device 20A and an analysis device 10A. As shown in Fig. 8, the measurement device 20A differs from the measurement device 20A in the first embodiment in that it includes an acceleration sensor 23.

[0065] As shown in Fig. 8, the analysis device 10A includes a control unit 12A including a time estimation unit 123A. The analysis device 10A differs from the analysis device 10A in the first embodiment in that the control unit 12 is replaced with a control unit 12A including a time estimation unit 123A and an acceleration detection unit 124. In the analysis system 1A according to this embodiment, the time estimation unit 123A of the analysis device 10A estimates the meal times of the subject based on a combination of a metabolic index and another index. As an example, the time estimation unit 123A estimates the meal times based on a metabolic index and the acceleration of the subject's physical movement.

[0066] The acceleration sensor 23 is a sensor capable of outputting an output value corresponding to the acceleration of the subject's physical movement. The subject's physical movement includes, for example, the subject's movement of moving, standing up, sitting down, etc. Alternatively, the acceleration sensor 23 may be a sensor capable of outputting an output value corresponding to the subject's physical movement performed while the subject is eating, such as lifting or lowering dishes or chewing.

[0067] The acceleration detection unit 124 acquires an output value corresponding to the acceleration of the subject's physical movement from the acceleration sensor 23 via the acquisition unit 11, and detects what movement the subject has made. For example, the acceleration detection unit 124 detects that the subject has moved and then sat down, based on the acquired output value. The acceleration detection unit 124 outputs information indicating the detected movement of the subject to the time estimation unit 123A.

[0068] The time estimation unit 123A acquires information indicating the subject's movements detected by the acceleration detection unit 124, in addition to information indicating the metabolic indices estimated by the index estimation unit 122, and estimates the subject's meal times based on this information. In other words, the time estimation unit 123A estimates the subject's meal times based on the metabolic indices and the acceleration of physical movements.

[0069] For example, if a metabolic index increases after the subject moves and sits down, the time estimation unit 123A estimates that the metabolic index increased because the subject sat down and ate, and estimates the meal time based on the change in the metabolic index. In this way, the time estimation unit 123A can improve the accuracy of estimating the subject's meal time by performing estimation using other indices in addition to the metabolic index. Furthermore, the subject's actions used by the time estimation unit 123A to estimate the subject's meal time are not limited to moving and sitting down, but may be any action related to the subject's meal. An example of an action related to the subject's meal may be, for example, the subject walking, stopping, and then walking again. When such an action is detected, the time estimation unit 123A may determine that the subject may have eaten at some point while standing still, and estimate the meal time by combining information indicating the action with the subject's metabolic index.

[0070] The time estimation unit 123A may also estimate the mealtime in more detail. For example, the time estimation unit 123A may estimate at least one of the subject's mealtime start time and mealtime end time based on metabolic indices and the acceleration of physical movements. More specifically, the time estimation unit 123A may estimate, as the subject's mealtime start time, a time before the mealtime estimated based on metabolic indices and at which it is detected that the subject has sat down based on the output value of the acceleration sensor 23. The time estimation unit 123A may also estimate, as the subject's mealtime end time, a time after the estimated mealtime and at which it is detected that the subject has stood up or at which the subject's eating-related movements have stopped. The time estimation unit 123A may also determine whether to estimate the mealtime based on the acceleration of the subject's physical movements. For example, if the metabolic indices increase while the subject is moving, the time estimation unit 123A may determine that the increase in metabolic indices is not due to eating and may not estimate the mealtime.

[0071] (Modification) In the analysis system 1A according to this embodiment, the time estimation unit 123A of the analysis device 10A may use an index other than the acceleration of the subject's physical movement as another index to be combined with the metabolic index. As an example, the time estimation unit 123A may estimate a meal time based on the metabolic index and the subject's body surface temperature. In this case, the measurement device 20A includes a temperature sensor capable of measuring the subject's body surface temperature and transmits information indicating the subject's body surface temperature to the analysis device 10A. The control unit 12A of the analysis device 10A acquires information indicating the subject's body surface temperature in addition to information indicating the subject's pulse wave. The time estimation unit 123A estimates the subject's meal time based on the metabolic index estimated by the index estimation unit 122 and information indicating the subject's body surface temperature. Generally, when a subject eats a meal, the body surface temperatures of the subject's hands and feet tend to rise after eating. In other words, when a metabolic index fluctuates and the subject's body surface temperature rises, it is highly likely that the subject ate a meal before the rise in body surface temperature occurred. Therefore, the time estimation unit 123A can estimate the meal times of the subject more accurately by grasping the timing of the rise in the subject's body surface temperature and performing estimation in combination with the metabolic index. The time estimation unit 123A may also perform estimation by combining the subject's metabolic index with two or more other indexes. For example, the time estimation unit 123A may estimate meal times by combining the subject's metabolic index, the acceleration of the subject's physical movement, and the subject's body surface temperature.

[0072] [Embodiment 3] Another embodiment of the present disclosure will be described below. For convenience of explanation, components having the same functions as those described in the above embodiment will be denoted by the same reference numerals, and their descriptions will not be repeated. Furthermore, descriptions of the present embodiment that overlap with the above embodiment will be omitted.

[0073] FIG. 9 shows the main configuration of an analysis system 1B according to this embodiment. As shown in FIG. 9, the analysis system 1B includes an analysis device 10B and a measurement device 20. The analysis system 1B differs from the analysis system 1 in the first embodiment in that it includes an analysis device 10B instead of the analysis device 10. As shown in FIG. 9, the analysis device 10B includes a control unit 12B and a memory unit 14B. The analysis device 10B differs from the analysis device 10 in the first embodiment in that it includes a control unit 12B including a time estimation unit 123B instead of the control unit 12 including the time estimation unit 123. The analysis device 10B also differs from the analysis device 10 in that it includes a memory unit 14B that stores behavior record data 143 and an estimation model 144 in addition to the data stored in the memory unit 14.

[0074] The behavior record data 143 is data indicating the subject's behavior, such as the subject's meal time, meal start time, meal end time, meal duration, and the period from the end of one meal to the start of the next meal. The subject's behavior record data 143 may be data input to the analysis device 10B by the subject or another person, or may be data indicating the subject's behavior detected by a sensor capable of detecting the subject's behavior, such as a temperature sensor or acceleration sensor (not shown). The analysis device 10B may also acquire and use the subject's behavior record data from an external device that stores the subject's behavior record data. The estimation model 144 is a trained estimation model that has been trained based on the subject's past behavior record, for example, each data included in the subject's behavior record data 143.

[0075] After estimating the metabolic index, the time estimation unit 123B identifies the behavior of the subject, such as the subject's meal times, based on changes in the metabolic index using the estimation model 144. In other words, the time estimation unit 123B estimates meal times based on a combination of the metabolic index and a learning result based on the subject's past behavioral records.

[0076] Furthermore, the time estimation unit 123B may estimate at least one of the meal start time and the meal end time based on a combination of metabolic indicators and learning results based on the subject's past behavioral records.

[0077] [Embodiment 4] Yet another embodiment of the present disclosure will be described below. For convenience of explanation, components having the same functions as those described in the above embodiment will be denoted by the same reference numerals, and their description will not be repeated. Furthermore, description of the present embodiment that overlaps with the above embodiment will be omitted.

[0078] FIG. 10 shows the main configuration of an analysis system 1C according to this embodiment. As shown in FIG. 10, the analysis system 1C includes an analysis device 10C and a measurement device 20. The analysis system 1C differs from the analysis system 1 in the first embodiment described above in that it includes an analysis device 10C instead of the analysis device 10. As shown in FIG. 10, the analysis device 10C includes a control unit 12C including an alert unit 125, and an alarm issuing unit 15. The analysis device 10C differs from the analysis device 10 in the first embodiment described above in that it includes the alert unit 125 in the control unit 12C and the alarm issuing unit 15.

[0079] The alert unit 125 issues various alerts from the alert issuing unit 15 in accordance with preset conditions. The preset conditions may be, for example, conditions related to an estimated metabolic index of the subject or meal times.

[0080] For example, when the metabolic index is low or is expected to become low, the alert unit 125 outputs an alert urging the subject to take food, etc. As an example, the alert unit 125 acquires an estimated metabolic index, and when the metabolic index falls below a preset second standard, outputs a predetermined alert to the subject.

[0081] For example, if the metabolic index indicates a blood glucose level, the second criterion may be a criterion that allows the subject to be evaluated as being in a hypoglycemic state if the metabolic index falls below the criterion.

[0082] The alert output by the alert unit 125 may include at least one of a notification of the situation and a message to alert the subject or a destination designated by the subject. More specifically, the alert may be a message such as, "Your metabolic index has fallen below the reference value," "You might want to refresh yourself by having a light meal or some fluids," or "Your metabolic index has fallen below the reference value. You might want to refresh yourself by having a light meal or some fluids." The alert unit 125 may also output an alert to encourage the subject to eat food if the time since the estimated mealtime exceeds a third reference value—in other words, if a certain amount of time has passed since the last meal. By outputting an alert when the metabolic index is low or if a certain amount of time has passed since the last meal, the subject can be made aware that it is advisable to eat food, even if they are not aware of any illness.

[0083] The third criterion may be, for example, a criterion that, when the metabolic indicator indicates blood glucose level, indicates that the subject is in a hypoglycemic state if the subject does not eat for a period of time that exceeds the criterion.

[0084] Furthermore, when the estimated metabolic index falls below a fourth predetermined standard, the alert unit 125 may output advice regarding the next meal. The next meal may mean lunch for breakfast on one day, or breakfast on the next day.

[0085] The fourth standard may be, for example, a standard in which, when the metabolic index is a value related to dietary content, if the metabolic index falls below the standard, it can be said that the subject's dietary content has a negative impact on their health.

[0086] The advice may be, for example, a message such as "We have detected that you may have exercised after a meal. Avoid exercising immediately after a meal." The analysis system 1C may also include an acceleration sensor (not shown) that can detect whether the subject is exercising, and may provide advice that associates the subject's exercise with the timing of meals. For example, if the subject's mealtime is detected and the subject's exercise is detected after the mealtime, the advice may include a message such as "Exercise has been detected. You may feel hungry because you were more active than usual, but chew your food slowly."

[0087] The alarm issuing unit 15 issues an alert in accordance with instructions from the alert unit 125. The alarm issuing unit 15 may output the alert by sound, or may output the alert by emitting a color that catches the target's eye, such as red or yellow. Alternatively, the alarm issuing unit 15 may output a text or audio message as the alert. The alarm issuing unit 15 may also be formed integrally with the presentation unit 13. The alarm issuing unit 15 may be provided in the measurement device 20. In this case, the alert unit 125 causes the alarm issuing unit 15 to output an alert by issuing an instruction to the alarm issuing unit 15 via the communication unit 22 of the measurement device 20.

[0088] 11 is a diagram showing an example of an overall overview of an analysis system 1D including a server 30. As shown in FIG. 11 , the analysis system 1D further includes a server 30 in addition to the analysis device 10 and measurement device 20 described above.

[0089] The analysis device 10 and the server 30 are connected to each other via a network so that they can communicate with each other.

[0090] The server 30 performs part or all of the analysis processing that was previously performed by the analysis device 10. By performing the analysis processing on the server 30, the processing load on the analysis device 10 can be reduced.

[0091] [Variation 2] In the embodiment described above, the pulse wave measured by the measurement device 20 is analyzed by the analysis device 10. However, this is not limited to this, and some of the functions of the analysis device 10 may be shared by the measurement device 20. An analysis system 1E employing such a configuration will be described with reference to FIG. 12. FIG. 12 is a functional block diagram showing an example configuration of the analysis system 1E. The measurement device 20E of the analysis system 1E measures and analyzes the pulse wave, and the analysis device 10E acquires the analysis results obtained from the measurement device 20E and presents them on the presentation unit 13.

[0092] 12 , the measuring device 20E includes a control unit 12 (change detection unit 121, index estimation unit 122, time estimation unit 123) and a storage unit 14 (pulse wave data 141, log data 142) in addition to a sensor unit 21 and a communication unit 22. The measuring device 20E analyzes the measured pulse waves and estimates the subject's meal times. The measuring device 20E transmits the measured pulse waves, analysis results, estimated meal times, etc. to the analysis device 10E.

[0093] The analysis device 10E includes at least a presentation unit 13, and presents the pulse wave, analysis results, determined messages, etc. received from the measurement device 20E. That is, in the analysis system 1E, the analysis device 10E functions as a presentation device that presents the pulse wave, analysis results, determined messages, etc.

[0094] This allows the same effects as those of the analysis system 1 described above to be achieved.

[0095] In the analysis system 1E, the analysis device 10E may include some of the functions of the control unit 12 (e.g., the time estimation unit 123) and some of the memory unit 14 (i.e., the log data 142). When this configuration is adopted, the measurement device 20E performs an analysis process on the measured pulse wave and transmits the measured pulse wave and the analysis results to the analysis device 10E. The analysis device 10E presents information such as meal times based on the analysis results received from the measurement device 20D.

[0096] [Embodiment 5] Yet another embodiment of the present disclosure will be described below. For convenience of explanation, components having the same functions as those described in the above embodiment will be denoted by the same reference numerals, and their description will not be repeated. Furthermore, description of the present embodiment that overlaps with the above embodiment will be omitted.

[0097] The analysis device 10F according to this embodiment acquires pulse waves of a subject continuously measured during a first period after a meal period in which the subject ingests a meal, detects the subject's pre-meal pulse wave from the acquired pulse waves, estimates a metabolic index correlated with the subject's vascular stiffness based on changes in the detected pulse wave, and presents the subject with a message corresponding to the magnitude of change in the estimated metabolic index during the first period.

[0098] In this way, the analysis device 10F estimates a metabolic index that correlates with the vascular hardness caused by the meal for the subject who has eaten a meal, and presents the subject with a message according to the magnitude of change in the estimated metabolic index during the first period. In this way, the analysis device 10F allows the subject to recognize the association between the contents of the meal and their own physical reactions after eating the meal, and can encourage the subject to make an effort to maintain or improve the contents of their meal and their eating habits.

[0099] [Analysis System 1] An overview of an analysis system 1F including an analysis device 10 according to this embodiment will be described with reference to Fig. 13. Fig. 13 is a functional block diagram showing an example configuration of the analysis system 1F. As shown in Fig. 13, the analysis system 1F includes an analysis device 10F and a measurement device 20.

[0100] [Measuring Device 20] As shown in FIG. 13, the measuring device 20 includes a sensor unit 21 and a communication unit 22.

[0101] The sensor unit 21 acquires the pulse wave of the subject. More specifically, the sensor unit 21 acquires the pulse wave of the subject by detecting a change in the volume (expansion or contraction) of the blood vessels based on the reflected light of light irradiated onto the blood vessels of the subject. The light irradiated onto the blood vessels of the subject may be, for example, light of an infrared wavelength.

[0102] Furthermore, the sensor unit 21 may measure the pulse wave of the subject at a higher measurement frequency during the first period compared to other periods in accordance with an instruction from the analysis device 10F. The measurement frequency may indicate, for example, the number of measurements during a predetermined period.

[0103] [Analysis Device 10F] Next, the analysis device 10F will be described with reference to Fig. 13. As shown in Fig. 13, the analysis device 10F includes an acquisition unit 11, a control unit 12F, a presentation unit 13, and a storage unit 14F. The control unit 12F also includes a change detection unit (detection unit) 121, an index estimation unit 122, and a message determination unit 126.

[0104] The acquisition unit 11 acquires, from the measurement device 20, pulse wave data of the subject continuously measured by the measurement device 20. The first period may be set by the user from predetermined options or may be set arbitrarily. The first period may also be automatically set from past pulse wave data. Alternatively, if the user does not select the first period, the first period may also be automatically set from past pulse wave data.

[0105] The control unit 12F controls the analysis device 10F, and includes the change detection unit 121, the index estimation unit 122, and the message determination unit 126, as described above.

[0106] The message determination unit 126 determines a message according to the magnitude of the change in the metabolic index estimated by the index estimation unit 122 during the first period.

[0107] For example, if the change in metabolic index during the first period exceeds the negative evaluation criterion (fifth criterion), the message determination unit 126 may determine a message that negatively evaluates the dietary content of the subject as a message corresponding to the magnitude of the change. The message may be verbal, numerical, or a combination of these. The determined message may be, for example, verbal, such as "A little more," "So close," or "Disappointing," or numerical, such as "20 points" or "20 / 100 points." It may also be a message that specifically encourages the subject to review their diet, such as "Your score has dropped significantly. What did you eat for dinner?"

[0108] An example of a negative evaluation criterion is when the post-meal ratio relative to the pre-meal ratio is half or less. Here, the pre-meal ratio and the post-meal ratio will be described with reference to FIG. 4 . As described above, graph 401 in FIG. 4 is an example of a pulse wave before a meal, and graph 402 is an example of a pulse wave in a first period. The pre-meal ratio is the ratio Y1 / X1 of the second peak Y1 to the first peak X1 in graph 401. The post-meal ratio is the ratio Y2 / X2 of the second peak Y2 to the first peak X2 in graph 402.

[0109] 13 , if the change in the metabolic index during the first period does not exceed the positive evaluation criterion (sixth criterion), the message determination unit 126 may determine a message that will provide a positive evaluation of the dietary content ingested by the subject as a message corresponding to the magnitude of the change. The message may be in language, numbers, or a combination of these. For example, the determined message may be in language such as "excellent," "good," or "good," or in numbers such as "85 points" or "85 / 100 points."

[0110] A positive evaluation criterion is, for example, when the post-meal ratio exceeds half of the pre-meal ratio.

[0111] Furthermore, the message determination unit 126 may determine a message including information about the manner of change in a metabolic index as a message according to the magnitude of the change. Examples of the manner of change in a metabolic index include the way the pulse wave rises, the slope, the height of the peak, the absolute amount, etc. An example of a message including information about the manner of change in a metabolic index is, "The shape of the pulse wave has changed sharply. Was the food you ate appropriate?"

[0112] The message determining unit 126 may determine a message including an indicator indicating the subject's condition other than the metabolic indicator as a message according to the magnitude of the change. The subject's condition is, for example, the subject's physical condition.

[0113] For example, the message determination unit 126 may use the subject's level of exercise obtained from an acceleration sensor as the subject's condition and determine a message such as, "It seems you didn't exercise much today. Adjust your diet and exercise together."

[0114] The message determination unit 126 may also determine a message such as "You seem to be tired today" as the state of the subject based on the heart rate and the subject's body temperature acquired from a body temperature sensor.

[0115] Furthermore, the message determining unit 126 may determine a message such as "It seems like the time between eating and starting sleep was short" based on the detection results of the acceleration sensor or the like.

[0116] For example, the analysis device 10F determines that the subject's body is not sufficiently recovered based on the subject's heart rate obtained the previous day and detection results from an acceleration sensor, etc., such as that the subject's resting heart rate last night was high, or that the subject's sleep time was short, or that the estimated daily sitting time was long (sitting all the time and inactive), etc. When the analysis device 10F determines that the subject's body is not sufficiently recovered, it determines and displays the message described above.

[0117] The presentation unit 13 presents to the subject the message determined by the message determination unit 126. Fig. 14 is a diagram showing an example of presentation by the analysis device 10F. In the presentation example shown in Fig. 14, a message is presented in area 134 of the presentation unit 13, a metabolic index is presented in area 132, and pulse wave data is presented in area 133.

[0118] Fig. 15 is a diagram showing another example of presentation by the analysis device 10F. The analysis device 10F may perform presentation as shown in Fig. 15. 1501 in Fig. 15 is a presentation example including a dietary evaluation. In 1501 in Fig. 15, the dietary evaluation is presented in area 1511, and information on the AI ​​value as a metabolic index is presented in area 1512. 1502 in Fig. 15 is also a presentation example of a metabolic index fluctuation. In area 1521 of 1502 in Fig. 15, the AI ​​value as a metabolic index is presented, and the fluctuation state of the AI ​​value is presented in area 1522.

[0119] The storage unit 14F stores data used by the analysis device 10F, including pulse wave data 141 and message data 145.

[0120] The message data 145 is data used by the message determination unit 126 to determine a message.

[0121] As described above, the analysis device 10F according to the present disclosure includes an acquisition unit 11 that acquires pulse waves of a subject continuously measured using a wearable device during a first period following a meal period during which the subject ingests a meal. The analysis device 10F also includes a change detection unit 121 that detects the subject's pre-meal pulse wave from among the pulse waves acquired by the acquisition unit 11. The analysis device 10F also includes an index estimation unit 122 that estimates a metabolic index correlated with the subject's vascular stiffness based on a change in the pulse wave detected by the change detection unit 121. The analysis device 10F also includes a message determination unit 126 that determines a message according to the magnitude of the change in the metabolic index estimated by the index estimation unit 122 during the first period. The analysis device 10F also includes a presentation unit 13 that presents the message determined by the message determination unit 126 to the subject.

[0122] This allows the subject to recognize the connection between the contents of their meals and their own physical reactions after eating, and also helps them recognize problems with their own diet, which can lead to the establishment of appropriate eating habits.

[0123] [Processing Flow] Next, the processing flow in the analysis device 10F will be described with reference to FIG. 16. FIG. 16 is a flowchart showing an example of the processing flow in the analysis device 10F. The processing of S201 to S203 shown in FIG. 16 is similar to the processing of S101 to S101 shown in FIG. 7, and therefore description thereof will be omitted. After performing the processing of S203, the message determination unit 126 determines a message according to the magnitude of change in the metabolic index during the first period estimated by the index estimation unit 122 (S204, message determination step). Then, the presentation unit 13 presents the message determined by the message determination unit 126 (S205, presentation step).

[0124] The above is the flow of processing in the analysis device 10F.

[0125] Sixth Embodiment Another embodiment of the present disclosure will be described below. For convenience of explanation, the same reference numerals will be used to designate components having the same functions as those described in the above embodiment, and the description thereof will not be repeated.

[0126] 17 is a functional block diagram showing an example of the configuration of the main components of an analysis system 1G according to this embodiment. The analysis system 1G includes a measurement device 20 and an analysis device 10G. As shown in FIG. 17 , the analysis device 10G differs from the analysis device 10F according to the fifth embodiment in that a control unit 12G includes an alert unit 125G, and the analysis device 10G includes a warning unit 15.

[0127] When the metabolic index estimated by the index estimation unit 122 exceeds an alert criterion (seventh criterion), the alert unit 125G outputs an alert to the subject from the alarm issuing unit 15. For example, when the metabolic index is a value related to dietary content, the seventh criterion may be a criterion that indicates that the dietary content of the subject has an adverse effect on health when the metabolic index exceeds the criterion.

[0128] Seventh Embodiment Another embodiment of the present disclosure will be described below. For ease of explanation, the same reference numerals will be used to designate components having the same functions as those described in the above embodiment, and the description thereof will not be repeated.

[0129] Fig. 18 is a functional block diagram showing an example configuration of an analysis system 1H according to this embodiment. The analysis system 1H includes a measurement device 20 and an analysis device 10H. As shown in Fig. 18, the analysis device 10H differs from the analysis device 10F of the fifth embodiment in that a control unit 12H includes a recording control unit 127, diet evaluation data 146 is stored in a memory unit 14H, and the analysis device 10H includes an input unit 16.

[0130] The input unit 16 accepts input of the meal contents taken by the subject from the subject. The meal contents may be input by inputting characters, or may be selected from pre-prepared options. Also, previously input meal contents may be selected. The meal contents may be input together with the time of intake. The input meal contents may be items such as "rice, vegetables, miso soup" or specific names such as "white rice, lettuce, tomato, carrot, wakame seaweed, tofu." Also, the order in which the items were consumed may be recorded.

[0131] The input unit 16 may accept input of the subject's meal contents at a predetermined timing after a meal, or may accept input before a meal.

[0132] The recording control unit 127 associates the input meal details with the metabolic indices estimated by the index estimation unit 122 and stores them as meal evaluation data 146 in the storage unit 14H.

[0133] Furthermore, the message determination unit 126 may determine a message including an evaluation of the subject's meal as the message to be presented to the subject, based on the change in metabolic index during the first period. An example of a message including an evaluation of the subject's meal is, using the length of meal time estimated from the detection results of the acceleration sensor, "Your meal time may have been short. Eating your meal slowly will result in a gentler change in glucose metabolism, which is ideal."

[0134] Furthermore, the message determination unit 126 may determine, as a message to be presented to the subject, a message including an evaluation result of the subject's dietary behavior and advice based on the evaluation result. For example, the message determination unit 126 may determine, based on the meal content input by the subject, a message such as "It seems you ate a lot of carbohydrates. Control the amount of carbohydrates in each meal, and it is also important to start with vegetables." The relationship between meal content and nutrients may be stored in advance.

[0135] 19 is a diagram showing an example of an overall overview of an analysis system 1I including a server 30. As shown in FIG. 19, the analysis system 1I further includes a server 30 in addition to the analysis device 10F and measurement device 20 described above.

[0136] The analytical device 10F and the server 30 are connected to each other via a network so that they can communicate with each other.

[0137] The server 30 performs part or all of the analysis processing that was previously performed by the analysis device 10F. By performing the analysis processing on the server 30, the processing load on the analysis device 10F can be reduced.

[0138] [Variation 4] In the embodiment described above, the pulse wave measured by the measurement device 20 is analyzed by the analysis device 10F. However, this is not limited to this, and some of the functions of the analysis device 10F may be shared by the measurement device 20. An analysis system 1J employing such a configuration will be described with reference to FIG. 20. FIG. 20 is a functional block diagram showing an example configuration of the analysis system 1J. The measurement device 20J of the analysis system 1J measures and analyzes the pulse wave, and the analysis device 10J acquires the analysis results obtained from the measurement device 20J and presents them on the presentation unit 13.

[0139] 20 , the measurement device 20J includes a control unit 12F (change detection unit 121, index estimation unit 122, message determination unit 126) and a storage unit 14F (pulse wave data 141, message data 145) in addition to a sensor unit 21 and a communication unit 22. The measurement device 20J performs an analysis process on the measured pulse wave and determines a message to be presented by the analysis device 10J based on the analysis results. The measurement device 20J transmits the measured pulse wave, the analysis results, the determined message, etc. to the analysis device 10J.

[0140] The analysis device 10J includes at least a presentation unit 13, and presents the pulse wave, analysis results, determined messages, etc. received from the measurement device 20J. That is, in the analysis system 1J, the analysis device 10J functions as a presentation device that presents the pulse wave, analysis results, determined messages, etc.

[0141] This makes it possible to achieve the same effects as the above-described analysis system 1F.

[0142] In the analysis system 1J, the analysis device 10J may have some of the functions of the control unit 12F (e.g., the message determination unit 126) and some of the memory unit 14F (i.e., the message data 145). When this configuration is adopted, the measurement device 20J performs an analysis process on the measured pulse wave and transmits the measured pulse wave and the analysis results to the analysis device 10J. The analysis device 10J determines a message to present based on the analysis results received from the measurement device 20J and presents the message.

[0143] [Example of Implementation by Software] The functions of the analytical devices 10, 10A to 10J and the measuring devices 20E, 20J (hereinafter referred to as "devices") can be realized by a program that causes a computer to function as the devices, and a program that causes a computer to function as each control block of the devices (particularly each part included in the control units 12, 12A, 12B, 12C, 12F, 12G, 12H).

[0144] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The functions described in each of the above embodiments are realized by executing the program using the control device and storage device.

[0145] The program may be non-transitory and may be recorded on one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

[0146] In addition, some or all of the functions of each control block can be realized by a logic circuit. For example, an integrated circuit in which a logic circuit that functions as each control block is formed is also included in the scope of the present disclosure. In addition, the functions of each control block can be realized by, for example, a quantum computer.

[0147] Furthermore, each process described in each embodiment may be executed by artificial intelligence (AI), in which case the AI ​​may run on the control device or on another device (for example, an edge computer or a cloud server).

[0148] The invention according to the present disclosure has been described above based on the drawings and examples. However, the invention according to the present disclosure is not limited to the above-described embodiments. In other words, the invention according to the present disclosure can be modified in various ways within the scope of the present disclosure, and embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the invention according to the present disclosure. In other words, it should be noted that a person skilled in the art can easily make various modifications or corrections based on the present disclosure. It should also be noted that these modifications or corrections are included in the scope of the present disclosure.

[0149] [Summary] Analysis devices 10, 10A, 10B, 10C, 10D, 10F, 10G, 10H, and 10I and measurement devices 20E and 20J according to aspect 1 of the present disclosure include an acquisition unit 11 that acquires pulse waves of a subject that are continuously measured using a wearable device (measuring device 20, 20A, 20E, and 20J) during a first period following a meal period in which the subject ingests a meal, a change detection unit 121 (detection unit) that detects the pulse wave of the subject before the meal in the pulse waves acquired by the acquisition unit 11, and an index estimation unit 122 that estimates a change in a metabolic index that correlates with vascular stiffness of the subject based on the change in the pulse wave detected by the change detection unit 121.

[0150] The analysis devices 10, 10A, 10B, 10C, 10D and measurement device 20E according to aspect 2 of the present disclosure may be provided with a time estimation unit 123 that estimates a meal time, which is any timing during the meal period, based on changes in the metabolic index in the first aspect.

[0151] In the analysis devices 10, 10A, 10B, 10C, and 10D and the measurement device 20E according to aspect 3 of the present disclosure, in aspect 2, the time estimation unit 123 may estimate at least one of the subject's mealtime start time and mealtime end time based on a combination of the metabolic index and another index.

[0152] In the analysis devices 10, 10A, 10B, 10C, 10D and measurement device 20E according to aspect 4 of the present disclosure, in aspect 3, the other indicator may be at least one of the acceleration of the subject's physical movement and the subject's body surface temperature.

[0153] In the analysis devices 10, 10A, 10B, 10C, and 10D and the measurement device 20E according to aspect 5 of the present disclosure, in any of aspects 2 to 4, the time estimation unit 123 may estimate the meal time based on a combination of the metabolic index and a learning result based on the subject's past behavioral record.

[0154] In the analysis devices 10, 10A, 10B, 10C, 10D and measurement device 20E according to aspect 6 of the present disclosure, in any of aspects 2 to 5, the time estimation unit 123 may estimate the meal times of the subject based on, in addition to changes in the metabolic index, the relationship between the subject's past meal times and information indicating the subject's condition at the subject's past meal times.

[0155] In the analysis devices 10, 10A, 10B, 10C, and 10D and the measurement device 20E according to aspect 7 of the present disclosure, in any of aspects 2 to 6, the time estimation unit 123 may estimate the meal time based on a change in the metabolic index, with a metabolic index estimated based on a pulse wave measured in the past when the subject woke up or when fasting as a first standard.

[0156] The analysis devices 10, 10A, 10B, 10C, and 10D and the measurement device 20E according to aspect 8 of the present disclosure may further include an alert unit 125 that outputs a predetermined alert to the subject when the metabolic index estimated by the index estimation unit 122 falls below a second standard in any of aspects 2 to 7.

[0157] The analysis devices 10, 10A, 10B, 10C, and 10D and the measurement device 20E according to aspect 9 of the present disclosure may further include an alert unit 125 that outputs an alert to encourage the subject to eat food when the time elapsed since the meal time estimated by the time estimation unit 123 exceeds a third standard in any of aspects 2 to 8.

[0158] The analysis devices 10, 10A, 10B, 10C, and 10D and the measurement device 20E according to aspect 10 of the present disclosure may further include an alert unit 125 that outputs advice to the subject regarding their next meal if the metabolic index estimated by the index estimation unit 122 falls below a fourth standard in any of aspects 2 to 9.

[0159] The analysis devices 10F, 10G, 10H, and 10I and the measurement device 20J according to aspect 11 of the present disclosure include, in aspect 1, a message determination unit 126 that determines a message according to the magnitude of change in the metabolic index estimated by the index estimation unit 122 during the first period, and a presentation unit 13 that presents the message determined by the message determination unit 126 to the subject.

[0160] In the analysis devices 10F, 10G, 10H, and 10I and the measurement device 20J according to aspect 12 of the present disclosure, in aspect 11, the message determined by the message determination unit 126 may be a message that provides a negative evaluation of the dietary content ingested by the subject if the change in the metabolic index during the first period exceeds a fifth criterion.

[0161] In the analysis devices 10F, 10G, 10H, and 10I and the measurement device 20J according to aspect 13 of the present disclosure, in aspect 11 or 12, the message determined by the message determination unit 126 may be a message that provides a positive evaluation of the dietary content ingested by the subject if the change in the metabolic index during the first period does not exceed a sixth criterion.

[0162] In the analysis devices 10F, 10G, 10H, and 10I and the measurement device 20J according to aspect 14 of the present disclosure, in any of aspects 11 to 13, the pulse wave of the subject acquired by the acquisition unit 11 may include the meal period of the subject.

[0163] In the analysis devices 10F, 10G, 10H, and 10I and the measurement device 20J according to aspect 15 of the present disclosure, in any of aspects 11 to 14, the pulse wave of the subject acquired by the acquisition unit 11 may include a second period prior to the meal period.

[0164] In the analysis devices 10F, 10G, 10H, and 10I and the measurement device 20J according to aspect 16 of the present disclosure, in any of aspects 11 to 15, the message determined by the message determination unit 126 may include information regarding the manner of change in the metabolic index.

[0165] In the analysis devices 10F, 10G, 10H, and 10I and the measurement device 20J according to aspect 17 of the present disclosure, in any of aspects 11 to 16, the message determined by the message determination unit 126 may include an indicator indicating the condition of the subject other than the metabolic indicator.

[0166] The analysis device 10G according to aspect 18 of the present disclosure may be configured to include an alert unit 124 that outputs an alert to the subject when the metabolic index estimated by the index estimation unit 122 exceeds a seventh standard in any of aspects 11 to 17.

[0167] In the analysis device 10H according to aspect 19 of the present disclosure, in any of aspects 11 to 18, the message determined by the message determination unit 126 may include an evaluation of the meal based on changes in the metabolic index during the first period.

[0168] The analysis device 10H according to aspect 20 of the present disclosure may be any of aspects 11 to 19, further including a recording control unit 127 that records the contents of the meal in association with the metabolic index estimated based on the pulse wave during the first period.

[0169] The analysis device 10H according to aspect 21 of the present disclosure may be any of aspects 11 to 20, further comprising an input unit 16 that accepts input of the meal contents from the subject.

[0170] In the analysis device 10H according to aspect 22 of the present disclosure, in any of aspects 11 to 21, the message determined by the message determination unit 126 may include an evaluation result regarding the subject's eating behavior and advice based on the evaluation result.

[0171] The analysis method according to aspect 23 of the present disclosure includes an acquisition step of acquiring a pulse wave of a subject continuously measured using a wearable device (measuring device 20, 20A, 20E, 20J) during a first period after a meal period in which the subject ingests a meal; a detection step of detecting a pulse wave of the subject before the meal from the acquired pulse wave; and an index estimation step of estimating a change in a metabolic index correlated with the stiffness of the subject's blood vessels based on a change in the detected pulse wave.

[0172] The analysis method according to Aspect 24 of the present disclosure is in Aspect 23, and further includes a time estimation step of estimating a meal time, which is any timing during the meal period, based on a change in the metabolic index.

[0173] The analysis method according to aspect 25 of the present disclosure is the same as that of aspect 23, and includes a message determination step of determining a message according to the magnitude of change in the metabolic index estimated in the index estimation step during the first period, and a presentation step of presenting the message determined in the message determination step to the subject.

[0174] DESCRIPTION OF SYMBOLS 1, 1A to 1J Analysis system 10, 10A to 10J Analysis device 11 Acquisition unit 12 Control unit 121 Change detection unit (detection unit) 122 Index estimation unit 123, 123A, 123B Time estimation unit 124 Acceleration detection unit 125, 125G Alert unit 126 Message determination unit 127 Recording control unit 13 Presentation unit 14 Memory unit 141 Pulse wave data 142 Log data 143 Behavior record data 144 Estimation model 145 Message data 146 Diet evaluation data 15 Alert unit 16 Input unit 20, 20A, 20E, 20J Measurement device 21 Sensor unit 22 Communication unit 23 Acceleration sensor 30 Server

Claims

1. an acquisition unit that acquires a pulse wave of the subject that is continuously measured during a first period after a meal period in which the subject ingests a meal using a wearable device; a detection unit that detects a pulse wave of the subject before a meal from the pulse wave acquired by the acquisition unit; and an index estimation unit that estimates a change in a metabolic index that correlates with the hardness of the subject's blood vessels based on the change in the pulse wave detected by the detection unit.

2. The analysis device according to claim 1 , further comprising a time estimation unit that estimates a meal time, which is any timing during the meal period, based on a change in the metabolic index.

3. The time estimation unit, estimating at least one of a meal start time and a meal end time of the subject based on a combination of the metabolic index and other indexes; The analytical device according to claim 2 .

4. The other indicator is at least one of an acceleration of the subject's physical movement and a body surface temperature of the subject. The analytical device according to claim 3 .

5. The time estimation unit, The meal time is estimated based on a combination of the metabolic index and a learning result based on a past behavioral record of the subject. The analytical device according to any one of claims 2 to 4.

6. The time estimation unit, estimating the meal times of the subject based on a relationship between the change in the metabolic index and information indicating the state of the subject at the past meal times of the subject; The analytical device according to any one of claims 2 to 4.

7. The time estimation unit, The meal time is estimated based on a change in the metabolic index, which is determined based on a pulse wave of the subject when waking up or when fasting that has been previously measured, as a first standard. The analytical device according to any one of claims 2 to 4.

8. An alert unit that outputs a predetermined alert to the subject when the metabolic index estimated by the index estimation unit falls below a second standard. The analytical device according to any one of claims 2 to 4.

9. and an alert unit that outputs an alert to encourage the subject to eat food when the time that has elapsed since the meal time estimated by the time estimation unit exceeds a third criterion. The analytical device according to any one of claims 2 to 4.

10. and an alert unit that outputs advice to the subject regarding a next meal when the metabolic index estimated by the index estimation unit falls below a fourth standard. The analytical device according to any one of claims 2 to 4.

11. a message determination unit that determines a message according to a magnitude of a change in the metabolic index estimated by the index estimation unit during the first period; The analysis device according to claim 1 , further comprising: a presentation unit that presents the message determined by the message determination unit to the subject.

12. The analysis device according to claim 11 , wherein the message determined by the message determination unit is a message that results in a negative evaluation of the meal content ingested by the subject if the change in the metabolic index during the first period exceeds a fifth criterion.

13. 13. The analysis device according to claim 11, wherein the message determined by the message determination unit is a message that provides a positive evaluation of the food content ingested by the subject if the change in the metabolic index during the first period does not exceed a sixth criterion.

14. The analysis device according to claim 11 , wherein the pulse wave of the subject acquired by the acquisition unit includes the meal period of the subject.

15. The analyzer according to claim 11 , wherein the pulse wave of the subject acquired by the acquisition unit includes a second period before the meal period.

16. The analysis device according to claim 11 , wherein the message determined by the message determination unit includes information on a state of change in the metabolic index.

17. The analysis device according to claim 11 , wherein the message determined by the message determination unit includes an index indicating a state of the subject other than the metabolic index.

18. The analysis device according to claim 11 , further comprising an alert unit that outputs an alert to the subject when the metabolic index estimated by the index estimation unit exceeds a seventh standard.

19. The analysis device according to claim 11 , wherein the message determined by the message determination unit includes an evaluation of the meal based on a change in the metabolic index during the first period.

20. The analyzer according to claim 11 , further comprising a record control unit that records the meal details and the metabolic index estimated based on the pulse wave during the first period in association with each other.

21. The analysis device according to claim 11 , further comprising an input unit configured to receive an input of the meal content from the subject.

22. The analysis device according to claim 11 , wherein the message determined by the message determination unit includes an evaluation result regarding the subject's eating behavior and advice based on the evaluation result.

23. an acquisition step of acquiring a pulse wave of the subject continuously measured during a first period after a meal period in which the subject consumes a meal using a wearable device; A detection step of detecting a pulse wave of the subject before a meal from the acquired pulse wave; an index estimating step of estimating a change in a metabolic index correlated with a vascular stiffness of the subject based on the detected change in the pulse wave; Analytical methods including:

24. The analysis method according to claim 23, further comprising a time estimation step of estimating a meal time, which is any timing during the meal period, based on a change in the metabolic index.

25. a message determination step of determining a message according to a magnitude of change in the metabolic index estimated in the index estimation step during the first period; The analysis method according to claim 23, further comprising a presentation step of presenting the message determined in the message determination step to the subject.