Activity amount calculation device and activity amount calculation method

Abstract

To calculate an activity amount based on an actual condition of an analysis object.SOLUTION: In order to solve an above-mentioned problem, an active amount calculation device 1 of the present invention calculates an activity amount of an analysis object, and has: an information acquisition unit 11 that acquires a result of measurement of the activity of the analysis object from a sensor 21; and an operation unit 12 that calculates first speed information and second speed information on the analysis object on the basis of, the measurement result, and calculates the activity amount of the analysis object by using the first speed information and the second speed information. In the activity amount calculation device 1, the operation unit 12 calculates at least one of the first speed information and the second speed information by using positional information on point group information that is included in the measurement result and indicates the analysis object.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technique for calculating the amount of activity of a subject such as a human being, and particularly to a technique for calculating the amount of activity based on human activity, behavior, and movements (hereinafter referred to as activity) measured by a sensor or the like. [Background technology]

[0002] In recent years, advances in communication technology and sensor technology have made it possible to measure human activity in daily life for the purpose of health management. Patent Document 1 is a background technology in this technical field. Patent Document 1 states that "by estimating at least one of a pedestrian's exercise intensity and activity amount using a pedestrian distance image acquired from a distance image, it is possible to estimate the effect of exercise of a pedestrian walking inside a building without having to wear an estimation device that estimates at least one of exercise intensity and activity amount on the pedestrian." [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-99267 Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, at least one of the exercise intensity and activity amount of a pedestrian can be estimated using a pedestrian distance image acquired from a distance image. Therefore, according to Patent Document 1, it is possible to grasp the amount of exercise of an individual and use it for health management without using a wearable device that may be forgotten to be worn or may run out of battery.

[0005] However, Patent Document 1 focuses on the issue of forgetting to wear the sensor, and does not consider the accuracy of grasping the amount of exercise, etc. Human activity is complex, and it is difficult to calculate the amount of activity that matches the actual situation using a single measurement with an image as in Patent Document 1. [Means for solving the problem]

[0006] In order to solve the above problems, in the present invention, a plurality of pieces of speed information are used to calculate the activity amount of an analysis subject who is the subject of the activity. At least one of the plurality of pieces of speed information is calculated based on the position information of the analysis subject. Note that it is desirable to use local speed information that indicates local characteristics of the analysis subject's activity and overall speed information that indicates overall characteristics of the subject's activity as the plurality of pieces of speed information.

[0007] More specific The present invention may employ, for example, the configuration described in the claims below. An activity amount calculation device for calculating an activity amount of a subject to be analyzed, comprising: a radio wave sensor that measures the activity of the subject of analysis; The analysis device includes an information acquisition unit that acquires measurement results for the activity of the subject to be analyzed, and a calculation unit that calculates first speed information and second speed information of the subject to be analyzed based on the measurement results and calculates an activity amount of the subject to be analyzed using the first speed information and the second speed information, and the calculation unit calculates at least one of the first speed information and the second speed information using position information of point cloud information that is included in the measurement results and indicates the subject to be analyzed. The first velocity information indicates a local characteristic of the activity of the subject to be analyzed and is local velocity information that is the maximum value of the velocity of each point included in the point cloud information, and the second velocity information indicates a degree of movement of the subject to be analyzed and is overall velocity information that indicates an overall characteristic of the activity and is calculated as velocity information that indicates the velocity of the center of gravity position in the point cloud information, and the calculation unit calculates the local velocity information using position information of the point cloud information. The activity amount calculation device is

[0008] The present invention also includes an activity amount calculation method using an activity amount calculation device and an activity amount calculation system including the same. Furthermore, the present invention also includes an activity amount calculation program that causes the activity amount calculation device to function as a computer. [Effects of the Invention]

[0009] According to the present invention, it is possible to calculate an amount of activity that is more in line with the actual situation regarding the activity of a person to be analyzed, and by ensuring the accuracy of this calculation, more appropriate health management becomes possible. Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram showing a configuration of an activity amount calculation system according to a first embodiment. [Figure 2] 10 is a flowchart illustrating processing by the activity amount calculation device according to the first embodiment. [Figure 3] FIG. 10 is a block diagram showing a configuration of an activity amount calculation system according to a second embodiment. [Figure 4] FIG. 10 is a block diagram showing a configuration of an activity amount calculation system according to a third embodiment. [Figure 5] 13 is a first example of a display unit of an external terminal in the third embodiment. [Figure 6] 13 is a second example of the display unit of the external terminal in the third embodiment. [Figure 7] 13 is an example of a display unit for providing feedback to an external terminal in the third embodiment. [Figure 8] FIG. 10 is a diagram showing display contents in the first embodiment. [Figure 9] FIG. 10 is a configuration diagram showing an implementation of an activity amount calculation system in Examples 2 and 3. DETAILED DESCRIPTION OF THE INVENTION

[0011] Each embodiment of the present invention will be described in detail below with reference to the drawings. However, the present invention is not limited to the following embodiments, and various modifications and application examples within the technical concept of the present invention are also included within its scope. [Example]

[0012] 1 is a block diagram showing the configuration of an activity amount calculation system according to Example 1. Example 1 is an example having a basic configuration compared to the other examples. The activity amount calculation system is configured with an activity amount calculation device 1 and a sensor 21.

[0013] The activity amount calculation device 1 is made up of an information acquisition unit 11, a calculation unit 12, a storage unit 13, and a display unit 14. These will be explained after the sensor 21.

[0014] The sensor 21 has the function of measuring the activities of the subject and outputting the measurement results. As an example of measurement, the sensor 21 captures the subject as a collection of at least two or more points. In other words, the sensor 21 measures a point cloud consisting of multiple points for the subject and acquires point cloud information including the location information of each point. A representative example is the radio wave sensor 22. In this specification, the radio wave sensor 22 is defined as a general term for sensors that use radio waves to detect the presence and movement of objects, such as microwave sensors, millimeter wave sensors, and TOF sensors. Using the radio wave sensor 22, the subject can be measured as a point cloud without contact or wearing the device. Each point in this point cloud has coordinate information, which is a type of location information. The higher the frequency of the radio wave sensor 22, the more points it contains, thereby improving spatial resolution. Furthermore, because the radio wave sensor 22 does not infringe on privacy, it can be installed in spaces where people live, such as inside a home or a facility. Note that the locations where various sensors are installed are not limited to these and may include a home garden, a place outside, etc. Furthermore, by making the sensor 21 non-wearable, various measurements can be made without the need to wear it. In other words, forgetting to wear it can be prevented. Furthermore, by using a sensor that can measure without wearing it, the subject's awareness of measurement can be reduced, and more natural activity can be measured. In other words, the amount of activity can be calculated that is more in line with reality.

[0015] Alternatively, an image sensor 23 may be used as the sensor 21. The image sensor 23 can measure and record the subject of analysis as a still image or video using a camera. Because these images are a collection of pixels, each pixel that captures the subject of analysis corresponds to a point cloud of the radio wave sensor 22, and similarly, coordinate information can be included in the point cloud information.

[0016] Furthermore, by utilizing the techniques disclosed in the following papers, etc., it is possible to estimate the three-dimensional shape of unseen parts from the two-dimensional image acquired by the image sensor 23. SM Ali Eslami et al., “Neural scene representation and rendering”, Science 15 Jun 2018:Vol. 360, Issue 6394, pp. 1204-1210 The estimated three-dimensional shape may then be used to estimate the three-dimensional distribution shape of the point cloud.

[0017] The sensor 21 may output not only the point cloud information but also the moving speed of each point of the point cloud and the center of gravity calculated by a calculation device implemented inside the sensor 21. Furthermore, the point cloud information may be the result of measurement by the sensor 21 itself, or may be created by the sensor 21 or the activity amount calculation device 1 using the measurement result.

[0018] Next, a description will be given of the activity amount calculation device 1. The activity amount calculation device 1 is realized by a so-called computer, and has an information acquisition unit 11, a calculation unit 12, a storage unit 13, and a display unit 14. Each of these components will be described below.

[0019] First, the information acquisition unit 11 has an interface function and accepts input of various information and data. To this end, it has, for example, a communication function with other devices such as the sensor 21 and an input function from the user. As an example, it acquires point cloud information from the sensor 21 and physical information of the subject of analysis (hereinafter referred to as physical information 41). The physical information 41 includes, for example, height, weight, date of birth, BMI, body fat percentage, visceral fat level, muscle mass, body water percentage, and internal body age. Furthermore, the physical information 41 may also include information indicating activity-related conditions such as the presence or absence of activity-related equipment (e.g., elderly orthotics), shoes, clothing, etc.

[0020] The information acquisition unit 11 may be realized as multiple components. For example, it may be realized as multiple components such as an input device used by a user and an interface with a communication function. Here, the information acquisition unit 11 may acquire point cloud information of the sensor 21 by directly connecting to the sensor 21 via Ethernet, wireless communication, or the like. As another example, when sensor data is collected in a locally installed PC via a gateway, the information acquisition unit 11 acquires the sensor data by accessing the PC via a local network or the Internet. As yet another example, when sensor data is collected in a server directly or via a gateway, the information acquisition unit 11 acquires the sensor data by accessing the server via the Internet. Alternatively, the sensor data may be stored on an external server and received in a file format such as CSV. In this case, the information acquisition unit 11 may acquire information by implementing a function to read CSV data.

[0021] In addition, there are multiple ways for the information acquisition unit 11 to acquire the physical information 41, such as by referring to the application form filled out by the person being analyzed when applying for the service and having the system administrator, who is the user, enter the information, or by storing the information entered by the system administrator in the storage unit 13 and referencing it.

[0022] Furthermore, the information acquiring unit 11 may acquire information other than the point cloud information from the sensor 21. For example, the information acquiring unit 11 may acquire information on presence / absence estimated based on the point cloud information, information on the posture of the person being analyzed estimated from the vertical spread of the point cloud and information on falls estimated from a sudden change in that posture, and the respiratory rate and heart rate of the person being analyzed estimated from minute fluctuations in the point cloud.

[0023] Next, the calculation unit 12 calculates the amount of activity using the information acquired by the information acquisition unit 11. For this purpose, the calculation unit 12 can be realized by a processor such as a CPU, and performs calculations (described later) in accordance with an activity amount calculation program stored in the storage unit 13. The calculation unit 12 may also be realized by dedicated hardware or an FPGA (Field-Programmable Gate Array). An example of the calculation by the calculation unit 12 will be described below. The activity amount calculation program can be stored in a storage medium, and may be distributed to the activity amount calculation device 1 via a network.

[0024] The calculation unit 12 calculates the amount of activity using multiple pieces of speed information, more preferably two types of speed information. For example, as shown in the following (Equation 1), the calculation unit 12 calculates the amount of activity E, which has units of energy, using two types of speed information and the weight of the person being analyzed. In (Equation 1), t1, t2, m, V1, and V2 represent the time when calculation of the amount of activity starts, the time when calculation of the amount of activity ends, the weight of the person being analyzed, the first speed information, and the second speed information, respectively.

[0025] In this embodiment, it is desirable to use velocity information indicating local characteristics of the subject's activity as the first velocity information. In this embodiment, for example, it is local velocity information, which is local velocity information at each of multiple points at which the sensor 21 captures the subject. When calculating the activity amount E, it is more desirable to use the maximum value of the local velocity information at each of these points as a representative value. Note that, a specific example of local velocity information may be the velocity of the extremities of the body, such as the hands, feet, and head.

[0026] The local velocity information can also be expressed as the “degree of vibration of the subject.” In other words, the velocity of the fastest moving point among the measured points may be used.

[0027] Furthermore, it is desirable to use overall speed information that indicates the overall characteristics of the activity of the subject of analysis as the second speed information. In this embodiment, the overall speed information is, for example, the speed components in a plane perpendicular to the vertical direction of the speed at the center of gravity of multiple points at which the sensor 21 captures the subject of analysis, and represents the speed at which the entire body moves around in a room. Another way to express the overall speed information is as the "mobility degree of the subject of analysis," which can be described as the movement speed in a plane (XY direction) if the vertical direction is the Z-axis direction.

[0028] Incidentally, having two types of speed information, the first speed information and the second speed information, has the advantage of being able to capture the activity level of the subject of analysis from a more multifaceted perspective. For example, if a subject is doing exercises without moving from the spot, the local speed information may have a value greater than 0, but the overall movement speed information may be 0. If the activity level E were evaluated using only the overall movement speed information, there is a concern that exercises that do not move from the spot may result in an underestimated calculation of the activity level. Similarly, there is a possibility that a subject may walk indoors without vibrating their limbs excessively, and in that case, there is a concern that calculating the activity level E using only the local speed information may result in an underestimation.

[0029]

number

[0030] Here, the definition of the activity amount is not limited as long as it is an index that correlates with the degree of human activity (activity). For example, the minimum, maximum, average, variance, standard deviation, etc. of the speed of each point in the point cloud may be used, or the center of gravity of the point cloud may be calculated and the minimum, maximum, average, variance, standard deviation, etc. may be calculated for that point and used as the activity amount. Furthermore, the activity amount may be calculated using these velocities and physical information 41, and may be a value having a unit of exercise amount, for example, obtained by multiplying any one type of speed information of the subject of analysis by the body weight.

[0031] Furthermore, V1 and V2 in (Equation 1) may be velocity information calculated using different methods, such as taking the time average value between times t1 and t2 when calculating the activity amount, or one of them may replace the other. Taking the time average value can reduce the influence of noise that enters the sensor for a short period of time. Also, depending on the sensor specifications, it may not be possible to calculate two types of velocity information. In such cases, it is effective to use one of them instead of the other. In (Equation 1), the unit before dividing by 4.184 is (J: joule), and after division it becomes (cal). Either of these units can be used for calculation depending on the application.

[0032] The amount of activity may be calculated for each body part of the subject to be analyzed. To this end, the calculation unit 12 calculates the amount of activity using Equation 2.

[0033]

number

[0034] In (Equation 2), m X0 indicates the mass (weight) of any part. V X1 and V X2 Each of the mass m of each part indicates the first velocity information and the second velocity information of the corresponding part. The parts can be set to arms, legs, trunk, etc. This makes it possible to calculate the amount of activity that is more in line with the actual state of the activity. In order to identify the first velocity information and the second velocity information of each part, it is desirable that the calculation unit 12 executes machine learning on the measurement results (e.g., images) of the sensor 21 to identify the part of the planned point. The mass m of each part x0 The weight may be acquired by the information acquiring unit 11 as the body information 41, or may be estimated from the standard mass balance of each part of the human body and the total body weight.

[0035] The calculation unit 12 may also calculate values ​​other than the amount of activity. For example, the calculation unit 12 may calculate a value indicating presence / absence estimated using point cloud information or a value indicating the posture of the subject of analysis estimated from the vertical spread of the point cloud. Furthermore, the calculation unit 12 may calculate information about falls estimated from a sudden change in posture, or the subject's respiratory rate and heart rate estimated from minute fluctuations in the point cloud. Furthermore, the calculation unit 12 may estimate the subject's physique from the point cloud information and estimate the weight based on average human data relating physique to weight.

[0036] The storage unit 13 has a function of storing information. Therefore, the storage unit 13 can be realized by a storage such as a memory or a hard disk drive. In this embodiment, the storage unit 13 stores at least one of the information acquired by the information acquisition unit 11 and the activity amount calculated by the calculation unit 12. Furthermore, when the calculation unit 12 performs calculations according to an activity amount calculation program, the storage unit 13 stores this activity amount calculation program. The acquired information and calculated activity amount are stored for each analysis subject. In this case, the storage unit 13 may tag and store this information and activity amount with attributes such as the age, sex, origin, language, religion, and hobbies and preferences of the corresponding analysis subject. Furthermore, by using religion and origin as attributes, it is possible to take into account habits involving activities such as worship.

[0037] The calculation unit 12 may also perform time series analysis on the accumulated information. Here, time series analysis is defined as performing operations such as visualization of various data using graphs with time on the horizontal axis, calculation and error analysis of the rate of change of data values ​​over time, moving averages, variances, standard deviations, etc., and polynomial approximations. These time series analyses may include comparisons with the average values ​​of people belonging to the same category in terms of age, gender, origin, religion, lifestyle, occupation, medical history, etc.

[0038] The display unit 14 displays the information calculated by the calculation unit 12 and the information in the storage unit 13. The information is displayed to the administrator of the activity amount calculation device 1, the user of the system, the person to be analyzed, etc. The display method can also adopt any format such as numbers, characters, tables, graphs, etc. The display unit 14 may be realized by an independent terminal device such as a mobile terminal.

[0039] 2 is a flowchart illustrating the processing of the activity amount calculation device 1 in this embodiment. The activity amount calculation device 1 starts processing in response to an operation by a system administrator or operator who is a user of the system (step S1).

[0040] First, the information acquisition unit 11 acquires sensor data, which are the measurement results of the sensor 21, and physical information 41 (step S2). Note that the sensor data and physical information 41 do not have to be acquired at the same time. For example, the physical information 41 is acquired in advance as a preparation work, and the sensor data is acquired when the sensor 21 performs measurement.

[0041] Next, storage unit 13 stores the acquired sensor data and physical information 41 (step S3). Note that this step may be omitted, and the following processing may be performed on sensor data and physical information 41 acquired in step S2.

[0042] Next, the calculation unit 12 calculates the amount of activity using the sensor data and the physical information 41 (step S4). This calculation of the amount of activity is performed using (Equation 1) and (Equation 2), as described above.

[0043] Next, the calculation unit 12 outputs the calculated amount of activity. As a result, the display unit 14 displays the calculated amount of activity. Also, the accumulation unit 13 accumulates the amount of activity (step S5).

[0044] The calculation unit 12 also receives an instruction from the user to calculate the time-series changes via the information acquisition unit 11. Then, the calculation unit 12 reads out the activity amount used to calculate the time-series changes from the storage unit 13 (step S6). The read-out activity amount is the activity amount of the subject of the calculation of the time-series changes. This activity amount is not limited to the activity amount of the subject of analysis calculated in step S4, but can also include the activity amounts of other people. This makes it possible to compare the activity status of each subject of analysis.

[0045] The activity amounts that are read out are the current activity amount calculated in step S4 and the past activity amounts that have been accumulated in the past in order to calculate the time-series change.

[0046] Next, the calculation unit 12 calculates a time series change using the amount of activity read out in step S6. The calculation of the time series change is as described above (step S7).

[0047] In step S7, the calculation unit 12 may calculate the amount of activity for each of the physical information 41, particularly for each activity condition. Alternatively, the calculation unit 12 may calculate the amount of activity for each activity content. In this case, the calculation unit 12 identifies the activity content based on the first speed information, the second speed information, a user's instruction, image processing of sensor data, or the like. In this case, the storage unit 13 stores the activity content and conditions of the analysis subject and others for each time period.

[0048] Next, the display unit 14 displays the current activity amount calculated in step S4 and the time-series change in the activity amount calculated in step S7 (step S8). The display unit 14 may display only one of the current activity amount and the time-series change, or may also display the activity amount and time-series change of other people. It is desirable that the display contents correspond to instructions input by the user via the information acquisition unit 11.

[0049] An example of the display content in this step is shown in FIG. 8. FIG. 8(a) is a graph showing the amount of activity for each type of activity of the subject of analysis. In FIG. 8(a), the types of activity used are exercise (gymnastics), exercise (walking), cleaning, eating, relaxation (reading), relaxation (email), and relaxation (TV). In addition, FIG. 8(a) displays the amount of activity for each of these types of activities, with and without elderly prostheses, which is one type of activity condition. Note that while FIG. 8(a) displays the amount of activity for one subject of analysis, it may also be displayed in a way that allows comparison with the activity amounts of others. Furthermore, time series changes may also be displayed.

[0050] FIG. 8(b) plots the first velocity information and the second velocity information of the subject on the respective axes, with and without the use of an elderly person's orthotic device. In FIG. 8(b), the first velocity information is the movement velocity in the xy plane, and the second velocity information is the hand tip velocity. In FIG. 8(b), the area of ​​the rectangle with the origin and the plotted point as its opposite vertices represents the relationship between the first velocity information and the second velocity information. Specifically, this relationship indicates that increasing both, rather than just one, is effective in increasing the area. This relationship may be treated as the "amount of activity." Thus, this embodiment is not limited to the amount of activity; any index related to the subject's activity may be calculated and output. The display shown in FIG. 8 may also be used in Examples 2 and 3, described below.

[0051] Furthermore, in step S8, the display unit 14 may display an alert. In this case, in step S7, the calculation unit 12 compares the calculated time-series change with a threshold set in the accumulation unit 13. Then, if the comparison result satisfies a predetermined condition, an alert is displayed on the display unit 14. The predetermined condition includes a case where the amount or degree of decrease in the amount of activity is equal to or less than a predetermined value. In other words, an alert can be output depending on the change in the activity of the person being analyzed. Furthermore, an alert may be output when the amount of activity is equal to or less than a predetermined threshold.

[0052] The activity amount calculation device 1 may end the process at step S8, or may return to the point immediately after the start of the process (step S1) and execute the above steps. [Example]

[0053] Next, a description will be given of Example 2. Example 2 is an example in which cooperation is carried out with businesses that provide services and products to elderly people, such as insurance companies and day care service providers. In this embodiment, first, a business operator prepares a service and a product linked to the activity amount calculation device 1. Then, when a subscriber applies for subscription to the service or product, the business operator delivers various sensors to the subscriber's home. After installation, the various sensors secure power by connecting to a power source, using batteries, or by energy harvesting using sunlight or vibration, and start measurement.

[0054] FIG. 3 is a block diagram showing the configuration of an activity amount calculation system in Example 2 based on the above assumptions. In FIG. 3, an external server 51 is a computer device managed and used by a business operator, and 22 to 32 are various sensors. These are connected to the activity amount calculation device 1. Sensor data measured by the various sensors is transmitted to the external server 51 directly or via a gateway.

[0055] The type of sensor used can be changed depending on the service and product. For example, a combination of a radio wave sensor 22, an image sensor 23, a human presence sensor 24, an illuminance sensor 25, a temperature, humidity, and air pressure sensor 26, a door open / close sensor 27, multiple vibration sensors 28, a pressure sensor 29, and a wearable sensor 30 may be used. Some or all of the human presence sensor 24, the illuminance sensor 25, and the temperature, humidity, and air pressure sensor 26 may be combined into one environmental sensor. Data linkage with other commercially available devices, such as an online-connectable weighing scale 31 and a body composition scale 32, may also be included. It is desirable for the weighing scale 31 and the body composition scale 32 to output physical information 41 to the information acquisition unit 11.

[0056] The administrator of the external server 51 is not limited, and may be a server managed by a business operator, a server managed by a sensor manufacturer, or a generally available rental server. In this embodiment, in addition to the business operator, a third party such as a system builder may also be involved. In this case, the external server 51 and the third party's server may store the physical information 41 and the sensor data in different environments, and the physical information 41 and the sensor data may be read into the activity amount calculation device 1 to make them available. However, these servers must be able to communicate with the activity amount calculation device 1 built in either the third party's internal environment, the business operator's internal environment, or a cloud environment.

[0057] Here, the information acquisition unit 11 of the activity amount calculation device 1 acquires sensor data collected by an external server 51 or a third-party server. The information acquisition unit 11 also acquires physical information 41. The physical information 41 can be acquired by inputting it from the sensor 21, reading the details written on a service or product subscription application form, or inputting it to a personal page on a provider's website on the external server 51. Furthermore, it is possible to separately prepare a measuring instrument such as a grip strength meter or a body composition meter, and acquire the results of the measuring instrument with the activity amount calculation device 1, or to acquire the physical information 41 in cooperation with a third party such as another provider, a local government, or a non-profit organization. As described above, the physical information 41 may be acquired from the above-mentioned servers, or the activity amount calculation device 1 may acquire it from the user or another device or apparatus. The sensor data and physical information 41 acquired by the information acquisition unit 11 are stored in the storage unit 13.

[0058] Furthermore, the calculation unit 12 calculates the amount of activity from the sensor data and physical information 41 acquired by the information acquisition unit 11. This calculation is performed in the same manner as in the first embodiment. Here, the sensor 21 includes at least one type of sensor, such as a radio wave sensor 22 and an image sensor 23, a human presence sensor 24, an illuminance sensor 25, a temperature, humidity, and air pressure sensor 26, a door opening / closing sensor 27, and a vibration sensor 28. In this case, the movement speed of the person to be analyzed may be calculated based on the difference in the time at which these sensors react, and the movement speed may be used to calculate the amount of activity.

[0059] Furthermore, the storage unit 13 stores the physical information 41 acquired by the information acquisition unit 11. Then, the calculation unit 12 searches the storage unit 13 for history data such as the past physical information and activity amount of the same person. Then, the calculation unit 12 can perform time series analysis using the search results. That is, step S7 of the first embodiment is executed.

[0060] The calculation unit 12 also outputs the calculated current activity amount and the time-series analysis results. As a result, the accumulation unit 13 accumulates the activity amount and time-series change results calculated by the calculation unit 12 for each analysis subject, by category such as the analysis subject's age, sex, origin, religion, lifestyle, occupation, medical history, etc.

[0061] Furthermore, the display unit 14 displays the activity amount and the time series analysis results calculated by the calculation unit 12. This makes it possible to present the activity amount and the time series analysis results to the system operator or the person in charge of the business. Here, it is desirable that the information displayed to the person in charge of the business be displayed on the external server 51 or a terminal connected thereto. Note that the display content may differ between the system operator and the business. For example, it is desirable to display the following information to the system operator in addition to the current activity amount of the person being analyzed and the time series change in the activity amount: Information about the operating status of sensor 21 Information about the battery status of Sensor 21 The indicated value of the sensor 21 is not processed by the calculation unit 12. Information about the date, time, number, duration and content of the operator's access to the system.

[0062] For businesses, for example, in addition to the current activity level of the subject of analysis and the time series change in activity level, the information may be converted and displayed as information specifically required by each business. Specifically, for insurance companies, it is desirable to display the past insurance application history of other people and the time series change in activity level, which can provide information for inferring the applicability of insurance for the current subject of analysis. Based on this information, insurance companies can consider intervention measures to correct the time series change in the subject's activity level in a direction that reduces the applicability of insurance. Such intervention measures include making recommendations to increase the subject's activity level, such as "Take a 30-minute walk every day" or "There's a bazaar in town, why don't you join us?"

[0063] Furthermore, for day care service providers, by showing the dates of day care services and the time series changes in activity levels, the service provider can provide material for examining the impact of the content of day care services on the activity levels of the subjects of analysis. Based on this information, the day care service provider can consider a program to correct the time series changes in activity levels for each subject of analysis in a desirable direction.

[0064] The business operator can provide feedback to the system administrator about the displayed content. The feedback can be provided verbally, by email, or by posting on the system administrator's homepage. The system administrator can change the displayed content based on the feedback from the business operator. This concludes the description of the second embodiment. [Example]

[0065] Next, a third embodiment will be described. The third embodiment is an example in which the present invention is applied to a so-called monitoring service. FIG. 4 is a block diagram showing the configuration of an activity amount calculation system in the third embodiment. FIG. 4 shows a case in which an individual who wants to monitor his / her elderly parents utilizes the activity amount calculation system. The activity amount calculation system of this embodiment is composed of an activity amount calculation device 1, an external server 51, an external terminal 52, and a sensor 21 provided in a home 54, which are connected via a network. In this case, it is desirable that the activity amount calculation device 1, the external server 51, and the external terminal 52 are connected within a business operator, such as through an intranet. Although the external server 51 is depicted separately in FIG. 4, it is desirable that it be configured in a single housing.

[0066] Here, this embodiment differs from embodiments 1 and 2 in that the storage unit 13 and the display unit 14 are provided in other devices. That is, the storage unit 13 is provided in the external server 51, and the display unit 14 is provided in the external terminal 52. In the following explanation, the contents that overlap with embodiments 1 and 2 will be omitted, and only the differences will be described.

[0067] First, an individual who wants to watch over their elderly parents subscribes to a monitoring service that utilizes an activity amount calculation system. When subscribing to this service, various types of sensors 21 are sent to the individual who wants to watch over their elderly parents depending on the service plan. After the sensors 21 are installed in the elderly parent's home 54, they secure a power source, start measuring, and save the data on an external server 51 or the like.

[0068] 4, the information acquisition unit 11 of the activity amount calculation device 1 communicates with the storage unit 13 and behavior recognition unit 15 of the external server 51. Specifically, the information acquisition unit 11 acquires sensor data, physical information 41, and activity information indicating daily behavior of a subject to be analyzed. Here, the subject to be analyzed in this embodiment is an elderly parent.

[0069] Here, the behavior recognition unit 15 has a function of recognizing the daily behavior of the person being analyzed in the home based on data from the sensor 21. This recognition utilizes measurement results from sensors that can detect the presence of a person in a specific location, such as a human presence sensor, a millimeter wave sensor, or an image sensor. The behavior recognition unit 15 then executes the following recognition method. How to associate and recognize places and actions. A method of clustering data from at least two or more types of sensors21 and associating and recognizing the characteristics and behavior of sensors that respond in each cluster. A method of using machine learning or other methods to learn the relationship between the self-reported behavior of the subject and sensor data, and creating a classifier that classifies the sensor data into behavior.

[0070] Here, with regard to the behavior recognition method using clustering, specifically, for data belonging to a certain cluster, if there is no reaction from the human presence sensor, it is possible to recognize that the person is out, and if the human presence sensor reacts in the bedroom at night and the reading of the illuminance sensor is small, it is possible to recognize that the person is asleep, etc.

[0071] Furthermore, the calculation unit 12 acquires information from the information acquisition unit 11 or the storage unit 13 provided in the external server 51, calculates the amount of activity, and calculates the time series changes for each unit time and each activity content.

[0072] As described above, the storage unit 13 is provided in an external server 51 separate from the activity amount calculation device 1, and can exchange data with the information acquisition unit 11, the calculation unit 12, and the display unit 14 provided in the external terminal 52. This external terminal 52 may be a smart device 55, such as a smartphone or a tablet, that can be used by individuals who want to watch over their elderly parents.

[0073] The calculation unit 12 outputs the calculation results to the storage unit 13 provided in the external server 51 and the display unit 14 provided in the external terminal 52. The calculation results are the amount of activity and time-series changes described above, which are calculated by the same calculations as in Examples 1 and 2. Therefore, a description of this calculation method will be omitted.

[0074] Next, FIG. 5 shows a first example of the display unit 14 in the external terminal 52 of this embodiment. This example is a display for an individual who is watching over an elderly parent. The display unit 14 displays the "current daily behavior," "activity amount," and "time series change in activity amount" of the elderly parent who is the subject of analysis, as well as recommendations that are the analysis results of these. Here, the user can freely select the unit of "activity amount" from (J), (cal.), or (METs). However, (METs) may also be calculated by measuring (J) or (cal.) and (METs) separately with the sensor 21 in a preliminary measurement test, approximating the relationship between them using a formula, and using the approximation formula.

[0075] Furthermore, as shown in Figure 5, if the time series change in activity level is on a downward trend, a recommendation such as "You seem to be feeling down lately. Would you like to go out with me this weekend?" may be displayed. Note that Figure 5 shows graphs for the entire lifestyle, cooking, and cleaning as examples of time series change in activity level, but similar graphs could also be shown for sleep, eating, relaxation, bathing, toileting, laundry, etc.

[0076] FIG. 6 is a second example of the display unit 14 of the external terminal 52 of this embodiment. This example is also a display for an individual who watches over elderly parents. As shown in FIG. 6, the display unit 14 displays "current daily activity," "today's daily activity," "activity level," "time series change in activity level" recognized by the behavior recognition unit 15, and feedback taking these contents into consideration. "Today's daily activity" is displayed in the form of a pie chart. Here, as shown in FIG. 6, if the time series change in activity level is on the rise and sufficient sleep time is being secured, the feedback may include displaying a comment such as "Mr. / Ms. XX has been sleeping well recently. The activity level is also on the rise and is healthy." Therefore, individuals who want to watch over their elderly parents can check the above-mentioned content through the display unit 14, and can also provide feedback on their evaluation of the display results through the display unit 14 of the external terminal 52. FIG. 7 shows an example of the display unit 14 for providing feedback on the external terminal 52 in this embodiment. In this example, a touch panel in which the display screen and input unit are integrated is used as the display unit 14, but the display screen and input unit may also be provided separately. The display unit 14 in FIG. 7 not only provides feedback on a 10-point rating of the display results in response to input from the user, but can also change the physical information 41. In other words, this information is reflected in the content of the storage unit 13.

[0077] 5 to 7 may be periodically distributed from the activity amount calculation device 1, or may be distributed in response to a request from the external terminal 52. Furthermore, when the activity amount or a time-series change satisfies a predetermined condition, the activity amount calculation device 1 may distribute the information to the external terminal 52. For example, the activity amount calculation device 1 may be configured to output an alert when the activity amount is equal to or less than a predetermined threshold. <Implementation example> Finally, implementation examples in Examples 2 and 3 will be described. Fig. 9 is a configuration diagram showing the implementation of the activity amount calculation system in each Example. In each Example, the activity amount calculation system includes an activity amount calculation device 1, a sensor 21, an external terminal 52, an external server 51-1, and an external server 51-2, which are connected to each other via a network such as the Internet.

[0078] Here, the activity amount calculation device 1 has an information acquisition unit 11, a calculation unit 12, a storage unit 13, and a display unit 14. Here, the storage unit 13 and the display unit 14 may be provided in other devices, as described in Example 3. The calculation unit 12 calculates the above-mentioned activity amounts and time-series changes in the activity amounts according to an activity amount calculation program (not shown). The activity amount calculation device 1 may be connected to terminal devices 16-1 and 16-2 and may perform the same display as the display unit 14. For this reason, the display unit 14 may be omitted from the activity amount calculation device 1. It is preferable that the activity amount calculation device 1 and the terminal devices 16-1 and 16-2 are connected via a local network such as an intranet.

[0079] The external server 51-1 is a server used by an insurance company and is connected to the external terminal 52-1 via a local network. The external server 51-1 has a storage unit 13 and a behavior recognition unit 15. The behavior recognition unit 15 executes the above-mentioned processing according to a behavior recognition program. Therefore, the behavior recognition unit 15 can also be realized by a processor. The behavior recognition program can be stored in a storage medium and distributed to the external server 51 via a network. The external terminal 52-1 is a terminal device used by an employee of the insurance company.

[0080] The external server 51-2 differs from the external server 51-1 only in that the user is a day service provider, and therefore a description thereof will be omitted. Similarly, a description of the external terminal 52-2 will be omitted. Furthermore, a description of the sensor 21 and the external terminal 52 will be omitted because they have been described in each embodiment.

[0081] 9 is merely an example, and the activity amount calculation device 1 can also be realized as a so-called personal computer. In this case, the activity amount calculation device 1 may be installed in a home 54, or may be realized as an external terminal 52 or as another device, including a home appliance, used by the user.

[0082] This concludes the description of the embodiments and implementation examples of the present invention, but the present invention is not limited to these. For example, by using sensor data from the sensor 21 with consideration for privacy, the privacy of the person being analyzed can be ensured.

[0083] The above embodiment also has the following advantages. That is, by not contacting or not wearing the sensor 21 on the subject of analysis, the amount of activity can be calculated for natural activities, such as those taking place at home. This allows the content of the activity to be determined more accurately. Furthermore, by calculating a value in units of energy, the amount of activity can be compared relatively even if the subject of analysis and the activity are different. [Explanation of symbols]

[0084] 1: Activity amount calculation device 11: Information acquisition department 12: Arithmetic section 13: Storage section 14: Display section 15: Behavior recognition section 21: Sensor 22: Radio wave sensor 23: Image sensor 24: Human sensor 25: Illuminance sensor 26: Temperature, humidity and pressure sensor 27: Open / close sensor 28: Vibration sensor 29: Pressure sensor 30: Wearable sensors 31: Weight scale 32:Body composition monitor 41: Physical information 51: External server 52: External terminal 54: Inside the house

Claims

1. 1. An activity amount calculation device for calculating an activity amount of an analysis subject, a radio wave sensor that measures the activity of the subject of analysis; an information acquisition unit that acquires measurement results of the activity of the subject of analysis measured by the radio wave sensor; a calculation unit that calculates first speed information and second speed information of the subject to be analyzed based on the measurement results, and calculates an activity amount of the subject to be analyzed using the first speed information and the second speed information; the calculation unit calculates at least one of the first velocity information and the second velocity information using position information of point cloud information that is included in the measurement results and indicates the person to be analyzed; the first velocity information is local velocity information that indicates a local characteristic of the activity of the subject and is a maximum value of the velocity of each point included in the point cloud information; the second speed information is overall speed information that indicates the degree of movement of the analysis subject and indicates an overall characteristic of the activity, and is calculated as speed information that indicates the speed of a center of gravity position in the point cloud information, The calculation unit calculates the local velocity information using position information of the point cloud information.

2. The activity calculation device according to claim 1 , The activity amount calculation device, wherein the overall velocity information is velocity information indicating velocity components in a plane perpendicular to the vertical direction at the center of gravity position.

3. 3. The activity calculation device according to claim 1, The calculation unit further determines the amount of activity using the body weight of the person to be analyzed.

4. In the activity amount calculation device according to claim 3, The calculation unit calculates the activity amount using the following (Equation 1) where ti is the time to start calculating the activity amount, t2 is the time to end calculating the activity amount, m is the weight of the person to be analyzed, v1 is the local velocity information, and v2 is the overall velocity information. [Equation 1]

5. 1. An activity calculation method using an activity amount calculation device that calculates an activity amount of an analysis subject, an information acquisition unit acquires measurement results from a radio wave sensor that measures the activity of the person being analyzed; a calculation unit calculating first speed information and second speed information of the analysis subject based on the measurement results, and calculating an activity amount of the analysis subject using the first speed information and the second speed information; the calculation unit calculates at least one of the first velocity information and the second velocity information using position information of point cloud information that is included in the measurement results and indicates the person to be analyzed; the first velocity information is local velocity information that indicates a local characteristic of the activity of the subject and is a maximum value of the velocity of each point included in the point cloud information; the second speed information is overall speed information that indicates the degree of movement of the analysis subject and indicates an overall characteristic of the activity, and is calculated as speed information that indicates the speed of a center of gravity position in the point cloud information, The activity amount calculation method, wherein the calculation unit calculates the local velocity information using position information of the point cloud information.

6. 6. The activity amount calculation method according to claim 5, The activity amount calculation method, wherein the overall velocity information is velocity information indicating velocity components in a plane perpendicular to a vertical direction at the center of gravity position.

7. 7. The activity calculation method according to claim 5, The activity amount calculation method further includes the step of determining the activity amount by using the body weight of the subject to be analyzed.

8. In the activity amount calculation method according to claim 7, The calculation unit calculates the activity amount using the following (Equation 1), where ti is the time when calculation of the activity amount starts, t2 is the time when calculation of the activity amount ends, m is the weight of the person to be analyzed, v1 is the local velocity information, and v2 is the overall velocity information. [Equation 1]

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