Target value setting device

Abstract

The purpose of the present invention is to provide a target value setting device that can set an appropriate target value for each individual.　Provided is a target value setting device 100, wherein a target value calculation unit 103 calculates statistical information (e.g., a variance and an average value) for a prescribed period of behavior of a single user. The target value calculation unit 103 then calculates a target value for the behavior of the single user on the basis of the statistical information. A result communication unit 104 communicates the target value to the single user. The target value is set on the basis of the statistical information so that a load increases relative to normal behavior of the single user, or so that the target value is healthful relative to the normal behavior.

Description

[Technical Field]

[0001] The present invention relates to a target value setting device that sets a target value for a user's behavior. [Background technology]

[0002] Patent document 1 describes that in order to set a target value that is appropriate from a health perspective, the data evaluation unit stores target data that is appropriate from a health perspective, such as a standard range of appropriate weight based on gender and height, and the user inputs their height, gender and target value data, such as a target weight, into the data input unit, and if the data is outside the standard range, the data output unit notifies them that the target weight is not appropriate. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 11-306257 Summary of the Invention [Problem to be solved by the invention]

[0004] Simply presenting the health risks of not making behavioral changes is not effective in changing behavior; it is important to present specific goals for the lifestyle habits that need to be improved. These goals must be neither too high nor too low for the individual, and must be moderately difficult. If the goal is set too high, it becomes the minimum level of satisfaction, making it difficult to achieve. On the other hand, if the goal is set too low, or if no specific goal is set, performance will be lower than if the goal were too high.

[0005] The technique described in Patent Document 1 does not present target values ​​for user behavior, and is therefore not appropriate as target values ​​for encouraging users to change their behavior. Generally, it is conceivable to set a unique target value for user behavior, but the target value may be too high or too low depending on the person, and may not be appropriate.

[0006] In order to solve the above-mentioned problems, an object of the present invention is to provide a target value setting device that can set an appropriate target value for each individual. [Means for solving the problem]

[0007] The target value setting device of the present invention comprises a statistical information calculation unit that calculates statistical information on the behavior of a single user and / or other users over a predetermined period of time, a target value calculation unit that calculates a target value for the behavior of the single user based on the statistical information, and a notification unit that notifies the single user of the target value, and the target value is set based on the statistical information so that the user's behavior is moderately more demanding than normal, or so that the user's behavior is healthier than normal. [Effects of the Invention]

[0008] According to the present invention, it is possible to set an appropriate target value for each individual. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a diagram showing a system configuration including a target value setting device 100 according to the present disclosure. [Figure 2] 1 is a functional block diagram showing the functional configuration of a target value setting device 100. FIG. [Figure 3] FIG. 2 is a diagram showing user behavior information stored in a data storage unit 102. [Figure 4] FIG. 10 is a diagram showing the distribution of the number of steps taken by user A. [Figure 5] 4 is a flowchart showing the overall operation of the target value setting device 100. [Figure 6] 10 is a flowchart showing detailed processing for calculating a target value in step S103. [Figure 7] 10 is a detailed flowchart of processing S203. [Figure 8] FIG. 10 is a diagram showing that the target value is set to the average ±1σ according to the direction of improvement. [Figure 9]1 is a diagram illustrating an example of a hardware configuration of a target value setting device 100 according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0010] The present disclosure will be described with reference to the accompanying drawings. Whenever possible, the same parts are designated by the same reference numerals and redundant description will be omitted.

[0011] FIG. 1 is a diagram showing a system configuration including a target value setting device 100 according to the present disclosure. As shown in the figure, a user 10 holds an input device 20 and a measurement device 30. The target value setting device 100 transmits user behavior measured by the measurement device 30 to the target value setting device 100. The target value setting device 100 calculates a target value for the user based on the user behavior and notifies the user. The measurement device 30 has a sensor function capable of measuring user behavior, such as a gyro sensor or a GPS sensor.

[0012] Possible user behaviors include the number of steps taken, sleep time (or bedtime and wake-up time), frequency of going out, meal time, calorie intake, and the number and duration of communications with others. The number of steps taken, sleep time, and frequency of going out are measured using a gyro sensor, GPS sensor, etc. Sleep time is calculated based on the sleep state, which is determined based on the time during which the input device 20 and the measurement device 30 are not operated. Meal time and calorie intake are determined based on input by the user to the input device 20. If the input device 20, etc., has a call function or communication function, the measurement device 30 measures the frequency or duration of communications with others.

[0013] The input device 20 has a display unit and a speaker for inputting the target value from the target value setting device 100, notifying the user of the target value, and suggesting user actions based on the target value. The functions of the input device 20 and the measurement device 30 are realized by a mobile terminal such as a smartphone.

[0014] The target value setting device 100 of the present disclosure includes a risk calculation function for calculating a health risk of a user, and a transmission function for transmitting a message for behavioral modification to the user.

[0015] The risk calculation function can grasp the user's behavior (such as the number of steps or sleep time) based on the user's operation on the input device 20 and the measurement device 30, and calculate the health risk based on that behavior. The health risk may be the risk of lifestyle-related diseases or the risk of needing care, which can be inferred from the user's behavior, or any other health risk. The transmission function also transmits that health risk to the user. The health risk information includes a message for behavioral change. This message includes a target value set for each user. The behavioral change message is, for example, a message encouraging the user to change their behavior in accordance with the user's health risk determined based on the user's behavioral history. In the present disclosure, the transmission function transmits, for example, a message such as "Let's walk to reduce risk" along with the target value.

[0016] The transmission function and risk calculation function do not have to be included in the target value setting device, but may exist in a separate device as a health risk calculation device.

[0017] 2 is a functional block diagram showing the functional configuration of the target value setting device 100. The target value setting device 100 includes a data acquisition unit 101, a data storage unit 102, a target value calculation unit 103, and a result notification unit 104.

[0018] The data acquisition unit 101 is a part that acquires user behavior information from the measurement device 30 and stores the user behavior information in the data storage unit 102 .

[0019] The data storage unit 102 is a part that stores user behavior information. The user behavior information is information that indicates the user's behavior, such as the number of steps, sleeping hours (or bedtime and wake-up time), frequency of going out, meal times, calorie intake, and number and duration of communication with others, for each user. As shown in FIG. 3, the number of steps is associated with each time period. In FIG. 3, information such as day of the week, weather, and temperature is also associated. Note that the wake-up time and bedtime may be stored for each day, and the sleeping hours may be associated with each time period.

[0020] The target value calculation unit 103 is a part that calculates a target value for each user based on the user behavior information stored in the data storage unit 102. Details will be described later.

[0021] The result notification unit 104 is a part that transmits the target value calculated by the target value calculation unit 103 to the input device 20 .

[0022] Next, the target value calculation process by the target value calculation unit 103 will be described. Fig. 4 is a diagram showing the frequency of user behavior information. In the present disclosure, the number of steps is taken as an example of user behavior, but is not limited to this. In addition to the number of steps, as mentioned above, other examples include sleeping time and frequency of going out.

[0023] FIG. 4(a) is a distribution diagram showing the distribution of the number of steps taken by user A. This distribution diagram is made up of time periods, number of steps, and frequency. Here, frequency refers to the number of times or probability that each step count divided into predetermined units has been reached in the past. As shown in FIG. 4(a), user behavior such as number of steps changes depending on the time of day and other circumstances, so it is desirable to set target values ​​for each situation the user is in.

[0024] The data acquisition unit 101 acquires the feature quantities (time, temperature, precipitation, etc.) of an arbitrary situation and the number of steps (lifestyle habits to be improved) for each predetermined unit of the situation (feature quantities), and the target value calculation unit 103 generates the distribution diagram shown in Fig. 4(a). Note that the arbitrary situation (feature quantities) may be one or more.

[0025] FIG. 4(b) is a distribution diagram with the number of steps (lifestyle habit to be improved) on the horizontal axis and an arbitrary situation (feature amount) on the vertical axis. This is a diagram showing the distribution diagram shown in FIG. 4(a) in a planar form. The target value calculation unit 103 performs clustering on this distribution diagram using a Gaussian mixture model. The purpose of clustering is to understand the differences in the distribution of the number of steps (lifestyle habit to be improved) for each situation and to set a target value according to the situation. Therefore, it is desirable to extract and understand situations in which the distribution of the number of steps (lifestyle habit to be improved) is as different as possible, rather than situations in which the distribution is similar.

[0026] The target value calculation unit 103 performs clustering using an information criterion such as AIC (Akaike information criterion) or BIC (Bayesian information criterion). The smaller the value of an information criterion such as AIC, the better the fit of the model. Therefore, the number of clusters that is considered to be optimal is determined based on the relationship between the number of clusters and the information criterion.

[0027] Based on the assumption that "data belonging to a certain cluster is Gaussian distributed near the center of gravity of that cluster," it is possible to calculate the likelihood based on the actual distribution (if the assumption is correct, how likely is the actual distribution, i.e., how close is it to a Gaussian distribution), and in this disclosure, this likelihood can be used when calculating the information criterion.

[0028] Furthermore, when calculating information criteria such as AIC, the information criteria are calculated based on the likelihood calculated using only the situation (feature) other than the number of steps, without taking the number of steps into consideration, for the results of clustering performed using the number of steps (lifestyle habits to be improved) and the situation (feature). This is done to evaluate the fit of clustering based only on the situation (feature), in order to extract and understand situations where the distribution of the number of steps (lifestyle habits to be improved) is as different as possible.

[0029] In FIG. 4(b), the target value calculation unit 103 determines that the clustering for the two lower distributions is insufficient, and further adds a situation (feature) to perform clustering. The target value calculation unit 103 determines whether separation is insufficient using AIC or BIC. The target value calculation unit 103 calculates an information criterion for each cluster C using user behavior information, and repeats clustering until the calculated value is minimized or the value of the information criterion is no longer expected to decrease by a predetermined value or more compared to before the situation (feature) was added.

[0030] Whether the clustering is sufficient may be determined based on whether the information criterion is smaller than a predetermined reference value, or whether the clustering is sufficient may be determined by comparing whether the information criterion has become smaller or larger compared to before adding or removing features.

[0031] Figure 4(c) is a distribution diagram in which the step count distribution in Figure 4(b) was judged to be insufficiently separated, and the step count was further clustered using the amount of precipitation as a situation (feature). As shown in the figure, this shows that separation was achieved to a degree that can be judged to be sufficient.

[0032] As shown in Figure 4, user behavior information is separated into clusters C1 to C3, and the average number of steps and other values ​​are calculated for each cluster. In cluster C1, the average number of steps and variance for a certain time period are calculated. In clusters C2 and C3, the average number of steps and variance are calculated for each amount of precipitation, without taking time period into consideration. Cluster C3 shows the distribution when there is a lot of precipitation (precipitation above a predetermined value), and cluster C2 shows the distribution when there is little precipitation (precipitation below a predetermined value).

[0033] Next, the operation of the target value setting device 100 of the present disclosure will be described. Fig. 5 is a flowchart showing the overall operation of the target value setting device 100. The data acquisition unit 101 acquires data from all or some of the devices of one user and stores it in the data storage unit 102 (S101). Each device here is a measuring device 30 for measuring each lifestyle habit item (number of steps, etc.). In the present disclosure, one measuring device 30 is shown, but there may be multiple measuring devices, or one measuring device 30 may measure multiple lifestyle habit items (number of steps, sleep time, etc.).

[0034] The target value calculation unit 103 detects abnormal values ​​of the lifestyle habit items and removes them (S102). For example, a lifestyle habit item whose value is extremely large or small compared to other measured lifestyle habit items may be determined to be an abnormal value.

[0035] The target value calculation unit 103 calculates the target values ​​for the lifestyle habit items of the one user (S103). The result notification unit 104 notifies the one user of the target values ​​(S104).

[0036] As will be described later, the target value calculation unit 103 may set a target value for each feature value indicated by the situation in which the user is placed. In this case, the result notification unit 104 notifies the user of a target value according to the situation (feature value) in which the user is placed. For example, the user's behavior may change depending on the weather, time of day, day of the week, etc., and the target value changes accordingly. It is preferable that the result notification unit 104 notifies the user of a target value according to the situation in which the user is placed at the time of notification.

[0037] Next, detailed processing for calculating the target value in step S103 will be described. FIG. 6 is a flowchart showing this processing. The target value calculation unit 103 creates a distribution based on user behavior information for an arbitrary period of time among user behavior information on lifestyle habits to be improved (S201). In the present disclosure, for example, the lifestyle habit to be improved is the number of steps. The distribution is as shown in FIG. 4. The distribution shown in FIG. 4(a) is shown in three dimensions with two situations (features) and one lifestyle habit, but if there is one situation (feature), it will be shown in two dimensions.

[0038] The target value calculation unit 103 determines whether the distribution is a normal distribution or a mixed distribution (S202). In the present disclosure, a normal distribution means that the lifestyle habit to be improved is not composed of multiple distributions and does not need to be separated by clustering.

[0039] Furthermore, if the distribution is a mixed distribution, the target value calculation unit 103 decomposes the distribution into several normal distributions (S203). This allows the timing of the behavior that constitutes each distribution to be determined. Note that, when there are multiple normal distributions, the following steps S204 to S211 are performed for each of them.

[0040] The target value calculation unit 103 calculates the mean value and variance of the user behavior of the lifestyle habit (number of steps) to be improved for one or each normal distribution (S204).

[0041] The target value calculation unit 103 determines whether the variance has been calculated (S205). If the variance has been calculated (S205: YES), the target value calculation unit 103 acquires the direction of improvement of the lifestyle habit to be improved (S206). The direction of improvement of the lifestyle habit indicates the direction in which the health risk of the user's behavior is reduced. For example, if the number of steps is insufficient, a predetermined value such as the variance is added (positive) to the average value. Conversely, the bedtime is improved in the negative (earlier) direction. In this way, a predetermined direction may be acquired according to the lifestyle habit.

[0042] Acquiring the direction of improvement also includes acquiring a message for that improvement. For example, a message such as "Hello! Your health risk for xx is xx%. In your particular case, you may be able to reduce the risk by improving the number of steps you take. First, try to aim to walk xx steps a day." In this message, the "health risk for xx" is, for example, "health risk for frailty." These health risks are calculated from the device operation history. These processes are publicly known, so their explanation will be omitted.

[0043] The target value calculation unit 103 sets the target value to the average ±1σ in accordance with the above improvement direction (S207). A specific example is shown in Figure 8. Figure 8 is a diagram showing a normal distribution, and the average value + 1σ indicates a value slightly higher than the average. This slightly higher value imposes a load on the user's behavior to maintain a moderate level of health.

[0044] On the other hand, if the variance cannot be calculated in step S205 (or if the variance is equal to or less than a predetermined value), the target value calculation unit 103 sets a target value from a constant and an average stored in advance (S208). An example of a case where the variance cannot be calculated is when there is only one day's worth of user behavior information.

[0045] The target value calculation unit 103 determines whether the target value deviates from a predetermined range (S209). If it deviates (S209: YES), the target value calculation unit 103 corrects the target value to the upper or lower limit of the range (S210). A range deviating from the predetermined range indicates a range that is clearly inappropriate as a target value, and this range is set in advance for the target.

[0046] The target value calculation unit 103 outputs the target value (S211). Here, output means outputting the target value and a message including the target value to the result notification unit 104.

[0047] Next, the decomposition of the mixed distribution in process S203 will be described. Fig. 7 is a detailed flowchart of process S203. The target value calculation unit 103 performs clustering using a Gaussian mixture model on the distribution determined to be a mixed distribution (S301). Naturally, the clustering is not limited to the Gaussian mixture model, and other methods may be used.

[0048] The target value calculation unit 103 determines whether the user behavior information included in each distribution satisfies an information criterion as a result of clustering (S302). As described above, the information criterion is AIC or BIC. For example, when AIC is used, the number of parameters used in the AIC is the number of features used when clustering.

[0049] The target value calculation unit 103 calculates the mean and variance of the user behavior information of each distribution that satisfies the information criterion.

[0050] If the information criterion is not satisfied, the target value calculation unit 103 attempts further clustering by adding features (S303). The features to be added are determined according to a predetermined priority order. In the present disclosure, each feature is added in order of priority, such as time of day, precipitation amount, weather, etc. This priority order is assumed to be predetermined.

[0051] The target value calculation unit 103 performs clustering while adding feature amounts until the information criterion is met.

[0052] In the present disclosure, instead of adding a feature, the feature may be replaced. The target value calculation unit 103 may perform clustering by excluding a feature that does not contribute to clustering and adding a new feature. The following methods can be considered as a method for excluding a feature that does not contribute to clustering.

[0053] For example, when clustering is performed by removing one feature (time, precipitation, etc.) in turn, the feature that least deteriorates an information criterion such as AIC is removed. The smaller the value of an information criterion such as AIC, the better the fit. Therefore, features that, when added, would cause the information criterion to exceed a predetermined value may be removed. Also, features that, when added, would not deteriorate the information criterion (or would cause the information criterion to exceed a predetermined value) are features that can be dispensed with, and such features do not contribute to clustering.

[0054] Furthermore, after clustering, when any one feature value and the lifestyle habit item to be improved are plotted on two axes, the feature value with the largest overlapping area (which can be calculated from the probability density of the distribution) between clusters is removed. A distribution based on features with a large overlapping area can be considered to have no ability to separate clusters.

[0055] Next, the effects of the target value setting device 100 of the present disclosure will be described. In the target value setting device 100 of the present disclosure, the target value calculation unit 103 calculates statistical information (e.g., variance and average value) of a user's behavior over a predetermined period. Then, the target value calculation unit 103 calculates a target value for the user's behavior based on the statistical information. The result notification unit 104 notifies the user of the target value. This target value is set based on the statistical information so that the user's behavior is more demanding than usual, or healthier than usual.

[0056] This configuration makes it possible to set appropriate target values ​​for each individual, thereby encouraging behavioral changes aimed at maintaining and improving health.

[0057] Simply presenting risks is not effective in changing users' behavior; it is important to provide specific targets for lifestyle habits that need to be improved.

[0058] Setting a high goal will set a minimum level of satisfaction, making it difficult to achieve satisfaction. On the other hand, setting a low goal or not setting a specific goal will result in lower performance than when the goal is high. Goals can be quite coercive and can cause pressure. Therefore, it is important that the goal value is neither too high nor too low, and is moderately difficult. In this disclosure, the goal is set based on statistical information to create a moderate load.

[0059] Increasing the load on sleep time means setting it to a healthier sleep time. If sleep time is short, it is set to a longer time, and conversely, if sleep time is long, it is set to a shorter time, so that it is neither too high nor too low. In the present disclosure, the target value is set to encourage healthier behavior than usual, but is not too easy. For example, it is possible to set the bedtime or wake-up time as a target value for sleep time to a moderately difficult time.

[0060] In the above disclosure, the average and variance are calculated based on the behavioral information of one user, but this is not limited to this. The average and variance of the behavioral information of other users whose behavior is similar to that of the one user for whom the target value is set may also be used. For example, the other users may be users whose attributes (age, gender, place of residence, occupation, etc.) match those of the one user, but other users may also be included and excluded.

[0061] In the target value setting device 100 of the present disclosure, the statistical information is the average value of a user's behavior over a predetermined period, the median value of that behavior, or the mode thereof, or a value where the frequency of the behavior is equal to or greater than a predetermined value. In the above explanation, the average value has been used as an example, but it is not limited to this, and the median value, etc. may also be used.

[0062] The statistical information further includes variance information that expresses the degree of variance in user behavior over a predetermined period of time. For example, variance or standard deviation may be used.

[0063] By using such statistical information, it becomes possible to set target values ​​for each user based on the current situation.

[0064] The target value setting device 100 of the present disclosure also includes a data acquisition unit 101 that acquires behavioral information (e.g., number of steps) of a user's behavior over a predetermined period of time. When the acquired behavioral information is composed of multiple distributions, the target value calculation unit 103 functions as a clustering unit that performs clustering processing on the behavioral information. The target value calculation unit 103 then sets a target value for the user's behavior for each of the clustered multiple pieces of behavioral information. Note that a target value may be set for at least one piece of behavioral information.

[0065] The target value calculation unit 103 clusters the behavior information (for example, the number of steps) for each specified situation (for example, day of the week, weather, time period, etc.) based on the feature amount.

[0066] This configuration allows us to decompose user behavior based on situation distributions, which are several feature quantities, and understand which timing of behavior constitutes each distribution. For example, we can understand that user behavior changes depending on the day of the week or the weather.

[0067] The target value calculation unit 103 clusters the behavioral information based on the feature of a specified situation (for example, a time period), and when clustering, determines whether the clustering has been performed while satisfying a predetermined condition based on index information related to the clustering (for example, an information criterion such as AIC). If it is determined that the predetermined condition is not satisfied, the target value calculation unit 103 further adds feature of another situation and clusters the user's behavioral information (number of steps).

[0068] With this configuration, the validity of the clustering results can be judged using a predetermined index such as an information criterion. Therefore, by repeating clustering while taking additional conditions (features) into account until the index determines that the clustering is valid, it is possible to more appropriately grasp user behavior.

[0069] The target value calculation unit 103 of the present disclosure may perform clustering using each of the specified multiple situations (features) to obtain multiple clustering results (multiple distributions), and may adopt behavioral information indicated by the clustering results that satisfy predetermined conditions from the clustering results (respective distributions).

[0070] That is, the target value calculation unit 103 generates a distribution of user behavior using several clustering patterns. The predetermined condition here is an information criterion, and behavior information of a distribution clustered using a more appropriate clustering pattern based on the information criterion may be adopted. In the above disclosure, features are added in order, but this may also be clustered in advance using all patterns or multiple patterns using predetermined features.

[0071] The target value calculation unit 103 in the present disclosure handles the day of the week, date, weather, precipitation, or temperature as feature quantities (situations) and performs clustering using these. These feature quantities (situations) are considered to affect the behavior of the user.

[0072] In addition, the target value calculation unit 103 may determine whether the target value is within a predetermined range, and if the target value is not within the predetermined range, may modify the target value so that it is within the range.

[0073] The target value setting device of the present disclosure has the following configuration.

[0074] [1] a statistical information calculation unit that calculates statistical information of the behavior of one user and / or other users over a predetermined period of time; a target value calculation unit that calculates a target value of the behavior of the one user based on the statistical information; a notification unit that notifies the one user of the target value; Equipped with the target value is set based on the statistical information so as to cause the user to be more heavily loaded than usual or to be healthier than usual. Target value setting device.

[0075] [2] The statistical information is an average value of the behavior, a median value of the behavior, or a mode thereof, or a frequency of the behavior equal to or greater than a predetermined value, for the predetermined period. The target value setting device according to [1].

[0076] [3] the statistical information further includes variability information that represents a degree of variability in the behavior over the predetermined period; [2] The target value setting device according to [2].

[0077] [4] a behavior information acquisition unit that acquires behavior information of the one user and / or the other user during a predetermined period; a clustering unit that performs clustering processing on the behavioral information; Equipped with the target value calculation unit sets a target value for the behavior of the one user based on at least one piece of behavior information among the plurality of pieces of clustered behavior information. The target value setting device according to any one of [1] to [3].

[0078] [5] The clustering unit clustering the behavioral information based on a specified situation; [4] The target value setting device according to [4].

[0079] [6] The clustering unit clustering the behavioral information based on a specified situation; When performing the clustering, it is determined whether the clustering has been performed while satisfying a predetermined condition based on index information related to the clustering; If it is determined that the predetermined condition is not satisfied, other situations are added and the behavioral information is clustered. [5] The target value setting device according to [5].

[0080] [7] The clustering unit Clustering is performed using each of the specified multiple situations to obtain multiple clustering results, adopting behavioral information indicated by a clustering result that satisfies a predetermined condition from the clustering result; [5] The target value setting device according to [5].

[0081] [8] The situation is a day of the week, a date, weather, precipitation, or temperature. [5] or [6]. The target value setting device according to [5] or [6].

[0082] [9] an appropriateness determining unit that determines whether the target value is within a predetermined range; a correcting unit that updates the target value so that the target value falls within a predetermined range if the target value is not within the predetermined range; The target value setting device according to any one of [1] to [8], further comprising:

[0083] The block diagrams used to explain the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of hardware and / or software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are connected directly or indirectly (for example, by wire, wirelessly, etc.) and these multiple devices. The functional block may also be realized by combining the single device or multiple devices with software.

[0084] Functions include, but are not limited to, judgment, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, election, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocation, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0085] For example, the target value setting device 100 according to an embodiment of the present disclosure may function as a computer that performs processing of the target value setting method of the present disclosure. Fig. 9 is a diagram illustrating an example of the hardware configuration of the target value setting device 100 according to an embodiment of the present disclosure. The target value setting device 100 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0086] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the target value setting apparatus 100 may be configured to include one or more of the apparatuses shown in the drawings, or may be configured to exclude some of the apparatuses.

[0087] Each function in the target value setting device 100 is realized by loading specified software (programs) onto hardware such as the processor 1001, memory 1002, etc., so that the processor 1001 performs calculations, controls communication via the communication device 1004, and controls at least one of reading and writing data in the memory 1002 and storage 1003.

[0088] The processor 1001 controls the entire computer by running, for example, an operating system. The processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc. For example, the target value calculation unit 103 described above may be realized by the processor 1001.

[0089] The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002 and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. For example, the target value calculation unit 103 may be implemented by a control program stored in the memory 1002 and running on the processor 1001, and similar implementations may be made for other functional blocks. While the above-described various processes have been described as being executed by one processor 1001, they may also be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may also be transmitted from a network via a telecommunications line.

[0090] The memory 1002 is a computer-readable recording medium and may be configured, for example, by at least one of a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing a target value setting method according to an embodiment of the present disclosure.

[0091] Storage 1003 is a computer-readable recording medium, and may be, for example, at least one of an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray disc), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including at least one of memory 1002 and storage 1003.

[0092] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, or a communication module. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). For example, the above-mentioned data acquisition unit 101 and result notification unit 104 may be realized by the communication device 1004. The data acquisition unit 101 and the result notification unit 104 may be implemented as a transmitter and a receiver that are physically or logically separated, or may be integrated into one unit.

[0093] The input device 1005 is an input device (for example, a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (for example, a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may be integrated into one device (for example, a touch panel).

[0094] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

[0095] Furthermore, the target value setting device 100 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0096] The notification of information is not limited to the aspects / embodiments described in the present disclosure and may be performed using other methods. For example, the notification of information may be performed by physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB))), other signals, or a combination thereof. Furthermore, the RRC signaling may be referred to as an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, or the like.

[0097] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0098] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0099] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0100] Each aspect / embodiment described in this disclosure may be used alone, in combination, or switched depending on the implementation. Furthermore, notification of predetermined information (e.g., notification that "X is true") is not limited to being done explicitly, but may be done implicitly (e.g., by not notifying the predetermined information).

[0101] Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0102] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0103] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), these wired and / or wireless technologies are included within the definition of transmission media.

[0104] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0105] Note that terms explained in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of a channel and a symbol may be a signal (signaling). Furthermore, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.

[0106] Furthermore, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information. For example, a radio resource may be indicated by an index.

[0107] The names used for the above-described parameters are not intended to be limiting in any way. Furthermore, the mathematical expressions using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (e.g., PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not intended to be limiting in any way.

[0108] In this disclosure, the terms "Mobile Station (MS)," "user terminal," "User Equipment (UE)," "terminal," etc. may be used interchangeably.

[0109] A mobile station may also be referred to by those skilled in the art as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable terminology.

[0110] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0111] The terms "connected," "coupled," or any variation thereof, refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access." As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using one or more wires, cables, and / or printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and optical (both visible and invisible) range, as some non-limiting and non-exhaustive examples.

[0112] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0113] Any reference to an element using a designation such as "first," "second," etc., used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient way to distinguish between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0114] When used in this disclosure, the terms "include," "including," and variations thereof are intended to be inclusive, similar to the term "comprising." Furthermore, when used in this disclosure, the term "or" is not intended to be an exclusive or.

[0115] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0116] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different." [Explanation of symbols]

[0117] 20...input device, 30...measuring device, 100...target value setting device, 101...data acquisition unit, 102...data storage unit, 103...target value calculation unit, 104...result notification unit.

Claims

1. a statistical information calculation unit that calculates statistical information on the behavior of one user and other users over a predetermined period of time; a target value calculation unit that calculates a target value of the behavior of the one user based on the statistical information; a notification unit that notifies the one user of the target value; Equipped with the statistical information is an average value of the behavior, a median value of the behavior, or a mode thereof, or a value in which the frequency of the behavior is equal to or greater than a predetermined value, during the predetermined period; the statistical information further includes variability information that represents a degree of variability in the behavior over the predetermined period; Target value setting device.

2. A statistical information calculation unit that calculates statistical information on the behavior of one user and other users over a predetermined period of time; a target value calculation unit that calculates a target value of the behavior of the one user based on the statistical information; a notification unit that notifies the one user of the target value; a behavior information acquisition unit that acquires behavior information of the one user and / or other users whose attributes match the one user during a predetermined period; a clustering unit that performs clustering processing on the behavioral information when the behavioral information is composed of a plurality of distributions; Equipped with the target value calculation unit sets a target value for the behavior of the one user for each of the plurality of pieces of behavior information clustered by the clustering unit. Target value setting device.

3. The clustering unit clustering the behavioral information based on a specified situation; The target value setting device according to claim 2 .

4. The clustering unit clustering the behavioral information based on a specified situation; When performing the clustering, it is determined whether the clustering has been performed while satisfying a predetermined condition based on index information related to the clustering; If it is determined that the predetermined condition is not satisfied, another situation is added or the one situation is replaced with another situation, and the behavioral information is clustered. The target value setting device according to claim 3.

5. The clustering unit Clustering is performed using each of the specified multiple situations to obtain multiple clustering results, adopting behavioral information indicated by a clustering result that satisfies a predetermined condition from the clustering result; The target value setting device according to claim 3.

6. The situation is a day of the week, a date, weather, precipitation, or temperature. The target value setting device according to claim 3.

7. A statistical information calculation unit that calculates statistical information about the behavior of one user and other users over a predetermined period of time; a target value calculation unit that calculates a target value of the behavior of the one user based on the statistical information; a notification unit that notifies the one user of the target value; an appropriateness determining unit that determines whether the target value is within a predetermined range; a correcting unit that updates the target value so that the target value falls within a predetermined range if the target value is not within the predetermined range; Equipped with Target value setting device.

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