JP7106463B2 - Information processing device and program - Google Patents

Description

The present invention relates to technology for determining an abnormality based on user's physical data.

2. Description of the Related Art A system has been proposed in which an emergency notification is made when a worker who is engaged in work at a factory, construction site, or the like is in an abnormal situation due to poor physical condition, injury, or the like. For example, in Patent Document 1, a future prediction model that defines the relationship between changes in pulse rate and changes in heart rate and a future trend of heart rate based on the history value of pulse rate are predicted. A mechanism is disclosed to notify when the trend is not normal.

JP 2016-122269 A

When an abnormality is determined based on data relating to the user's body in this manner, it is desirable that the accuracy of the determination be higher.

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to improve accuracy in determining an abnormality based on data relating to a user's body.

In order to solve the above problems, the present invention provides an acquisition unit that acquires measurement data including data measured regarding a user's body, the acquired measurement data, and estimation of the user's heart rate from the measurement data. an estimating unit that estimates the user's heart rate at a future time and a normal range that is a normal heart rate range for the user at the future time, using a model generated for each user for , the estimated heart rate at the future point in time, or the user's heart rate measured when the future point in time comes, is outside the normal range of the estimated heart rate at the future point in time (2) an information processing apparatus comprising: a notification unit that performs notification; and an update unit that updates the model using the acquired measurement data.

The estimating unit performs the estimation using first measurement data measured at a first time period and second measurement data measured at a second time period prior to the first time period. The first measurement data may include measurement data of the same type as the second measurement data and measurement data of a different type from the second measurement data.

The first measurement data includes the heart rate of the user and data measured regarding the user's behavior or data measured regarding the user's surrounding environment, and the second measurement data includes the user's heart rate may be included.

The estimation unit may estimate the activity level of the user and estimate the normal range that differs for each activity level.

The estimating unit determines that the activity level of the user is working when the measured heart rate of the user is equal to or greater than a threshold, and determines that the measured heart rate of the user is less than the threshold. and if the heart rate does not decrease over time, it is determined that the activity level of the user is active during rest, and the measured heart rate of the user is less than the threshold. In addition, when the heart rate decreases with the lapse of time, it may be determined that the activity level of the user is resting.

When estimating the normal range as a heart rate range that can occur at a future point in time with a certain probability or more, the estimation unit may perform estimation using the certain probability that fluctuates.

The estimator may use the certain probability that varies according to parameters not considered in the model.

The updating unit may update the model using the data predicted at the future point in time in addition to the measurement data obtained by measuring in the past.

The reporting unit, when a change in heart rate of the user satisfies a predetermined condition, is smaller than a first distance from the user compared to a first communication device that is the first distance away from the user. The notification may be made to the second communication device, which is separated by the second distance, with priority given to the second communication device.

The present invention provides a computer with an acquisition unit that acquires measurement data including data measured regarding a user's body, the acquired measurement data, and for estimating the heart rate of the user from the measurement data, and an estimating unit that estimates the user's heart rate at a future time and a normal range that is a normal heart rate range for the user at the future time using the model generated in the estimated If the heart rate at the future point in time or the user's heart rate measured at the arrival of the future point in time falls outside the normal range of the estimated heart rate at the future point in time, a notification is provided. and a program for realizing an update unit for updating the model according to the acquired measurement data.

ADVANTAGE OF THE INVENTION According to this invention, the precision when judging abnormality based on the data regarding a user's body can be improved compared with the past.

It is a figure which illustrates the structure of the reporting system which concerns on one Embodiment of this invention. It is a block diagram which shows an example of the hardware constitutions of a server apparatus. It is a block diagram which shows an example of the functional structure of a server apparatus. It is a figure explaining the concept of the abnormality determination based on a heart rate. It is a figure explaining the concept of the abnormality determination based on a heart rate. 4 is a flowchart illustrating the operation of the server device; 4 is a flowchart illustrating the operation of the server device;

[Constitution]
FIG. 1 is a diagram showing an example of a notification system 1 of this embodiment. The notification system 1 includes a measuring device 10 attached to the body of a user whose physical condition is to be monitored (in this embodiment, for example, a worker engaged in work in a factory), and a communication device 20 carried by the user. , a server device 30 for grasping the physical condition of the user, an administrator terminal 40 carried by an administrator who manages the user on business, and a network 2 for communicatively connecting them. . In the reporting system 1, data relating to the user's body is transmitted from the measuring device 10 to the server device 30 via the communication device 20, and when the server device 30 determines that an abnormality has occurred in the user's body, the administrator notifies the user of the fact. The information is notified to the terminal 40 .

The measuring device 10 is a device called a wearable device or an IoT (Internet of Things) device, for example, and measures data related to the user's body. In this embodiment, data regarding the user's body is defined as "heart rate".

The communication device 20 is a portable communication device such as a smart phone. The communication device 20 wirelessly communicates with the measuring device 10 according to a communication standard such as Bluetooth (registered trademark), and wirelessly communicates with the network 2 according to a communication standard such as LTE.

The administrator terminal 40 is a portable communication device such as a smart phone. The administrator terminal 40 performs wireless communication with the network 2 according to communication standards such as LTE, for example.

The network 2 is, for example, a radio communication network conforming to a communication standard such as LTE (Long Term Evolution), and includes a radio base station (not shown) and its higher-level equipment. Although only one measuring device 10, one communication device 20, one server device 30, and one administrator terminal 4 are shown in FIG.

FIG. 2 is a diagram showing the hardware configuration of the server device 30. As shown in FIG. The server device 30 is physically configured as a computer device including a processor 3001, a memory 3002, a storage 3003, a communication device 3004, an input device 3005, an output device 3006, and a bus connecting them. Note that in the following description, the term "apparatus" can be read as a circuit, device, unit, or the like. The hardware configuration of the server device 30 may be configured to include one or more of each device shown in the figure, or may be configured without some of the devices.

Each function in the server device 30 is performed by causing the processor 3001 to perform calculations, controlling communication by the communication device 3004, controlling communication by the communication device 3004, and controlling the and by controlling at least one of reading and writing of data in the storage 3003 .

The processor 3001, for example, operates an operating system and controls the entire computer. The processor 3001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic device, registers, and the like. Also, for example, a baseband signal processing unit, a call processing unit, and the like may be implemented by the processor 3001 .

The processor 3001 reads programs (program codes), software modules, data, etc. from at least one of the storage 3003 and the communication device 3004 to the memory 3002, and executes various processes according to them. As the program, a program that causes a computer to execute at least part of the operations described below is used. The functional blocks of server device 30 may be implemented by a control program stored in memory 3002 and running on processor 3001 . Various processes may be executed by one processor 3001, but may also be executed by two or more processors 3001 simultaneously or sequentially. Processor 3001 may be implemented by one or more chips. Note that the program may be transmitted from the network 2 to the server device 30 via an electric communication line.

The memory 3002 is a computer-readable recording medium, and is composed of at least one of, for example, ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), and RAM (Random Access Memory). may be The memory 3002 may also be called a register, cache, main memory (main storage device), or the like. The memory 3002 can store executable programs (program code), software modules, etc. to perform the methods of the present invention.

The storage 3003 is a computer-readable recording medium, for example, an optical disc such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disc, a magneto-optical disc (for example, a compact disc, a digital versatile disc, a Blu-ray disk), smart card, flash memory (eg, card, stick, key drive), floppy disk, magnetic strip, and/or the like. Storage 3003 may also be called an auxiliary storage device.

The communication device 3004 is hardware (transmitting/receiving device) for communicating between computers via at least one of a wired network and a wireless network, and is also called a network device, a network controller, a network card, a communication module, or the like. The communication device 3004 includes a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc., in order to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). may consist of For example, a transmitting/receiving antenna, an amplifier section, a transmitting/receiving section, a transmission path interface, etc. may be implemented by the communication device 3004 . The transceiver may be physically or logically separate implementations for the transmitter and receiver.

The input device 3005 is an input device (for example, keyboard, mouse, switch, etc.) that receives input from the outside. The output device 3006 is an output device (such as a display) that outputs to the outside. Note that the input device 3005 and the output device 3006 may be integrated (for example, a touch panel).

Each device such as processor 3001 and memory 3002 is connected by a bus for communicating information. The bus may be configured using a single bus, or may be configured using different buses between devices.

The server device 30 includes hardware such as a microprocessor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array). Alternatively, the hardware may implement part or all of each functional block. For example, processor 3001 may be implemented using at least one of these pieces of hardware.

FIG. 3 is a block diagram showing an example of the functional configuration of the notification system 1. As shown in FIG. In the measuring device 10, the physical data measuring unit 11 measures data (here, heart rate) regarding the user's body.

In the communication device 20 , the receiving unit 21 receives the heart rate measured by the physical data measuring unit 11 and the measurement time from the measuring device 10 . In the communication device 20 , the transmission unit 22 transmits to the server device 30 the heart rate received by the reception unit 21 and measurement data including the ambient temperature, the user's position, the number of steps, and the like, in addition to the heart rate. Note that the temperature, the user's position, and the number of steps may be obtained or measured by the communication device 20 or may be obtained or measured by the measuring device 10 .

In the server device 30 , the acquisition section 31 acquires measurement data transmitted from the transmission section 22 of the communication device 20 .

In the server device 30, the estimating unit 32 uses the measurement data acquired by the acquiring unit 31 and an estimation model generated for each user to estimate the user's heart rate from the measurement data. Estimate the user's heart rate at a point in time and a normal range, which is the range of heart rates that is normal for the user at some point in the future. The estimation model used at this time is a model based on so-called multiple regression analysis, which will be described in detail later.

At this time, the estimation unit 32 estimates the user's activity level, and estimates a different normal range for each activity level. The activity level here means, for example, during work (a state in which predetermined work is being performed in the factory), during a break (a state in which the factory is away from the predetermined work and taking a break), and during a break ( There are three levels, such as a state in which the worker is away from the prescribed work in the factory, but is exercising at a prescribed intensity or higher, such as recreation. When the measured heart rate of the user is equal to or greater than the threshold, the estimation unit 32 determines that the activity level of the user is that the user is working, the measured heart rate of the user is less than the threshold, and If the heart rate does not decrease over time, it is determined that the activity level of the user is active during rest, the measured heart rate of the user is less than the threshold, and the heart rate If the number decreases with the passage of time, it is determined that the activity level of the user is resting.

Furthermore, the estimation unit 32 uses the first measurement data measured in the first period and the second measurement data measured in the second period before the first period to obtain the above is estimated. The first measurement data includes the same type of measurement data as the second measurement data and a different type of measurement data from the second measurement data.

More specifically, the first measurement data includes the user's heart rate and data measured regarding the user's behavior or data measured regarding the user's surrounding environment, and the second measurement data includes , which contains the user's heart rate. For example, when estimating the heart rate at a certain time, the estimating unit 32 may determine the user's heart rate measured one minute before that time, the user's activity level one minute before that time (that is, the user's data measured on the behavior of the user), the number of steps of the user collected one minute before that time (i.e. data measured on the behavior of the user), the temperature one minute before that time (i.e. data measured about the environment), the first measurement data including the position of the user one minute before that time (that is, the data measured about the behavior of the user), and the first measurement data measured two minutes before that time. second measurement data including the heart rate obtained from the measurement.

An example of specific formulas for the above estimation algorithm is shown below. First, define each parameter.
α_i,d,t: Deviation of heart rate of user i at time t on day d
β_i,d,t: Rest effect
γ_i,d,t: Various effects (number of steps, temperature, location)
k_{j, i}: Autoregression coefficients of user i (j=1, 2)
y_i,d,t: Heart rate of user i at time t on day d
μ_i: average heart rate of user i
η_i: observed disturbance term of user i
ε_i: User i's state disturbance term
ξ_i: Disturbance term of average heart rate of user i
w_{j, i}: User i's out-of-hours effect (j = 1, 2)
x_all: Overall mean of parameter x
σ_x: Variance of parameter x
ε_i~N(ε_all, σ_ε ²)
η_i~N(η_all, σ_η ²)
μ_i~ N (μ_all, σ_μ ²)
ξ_i~N(ξ_all, σ_ξ ²)
w_{j, i}~N(ε_all, σ_wj ²)

The heart rate deviation of user i at time t on day d is expressed by the following equation.
αi _,d,t = k1 _,i αi _,d,t-1 + k2 _,i αi _,d,t-1 + βi _,d,t + γi _,d,t + _εi
note that,
_{yi ,d,t} =μi+αi _,d,t + _ηi
μ _i = μ _all + ξ _i
β _i,d,t = β _i,d,t-1 + w _1,i (when resting)
βi _,d,t = βi _,d,t-1 + w2 _,i (when active during rest)
β _i,d,t = 0 (when working)
is.
Note that the number of steps and temperature naturally affect the user's heart rate. Location also affects the user's heart rate, since different locations within the factory require different amounts and intensities of exercise for work performed at that location.

The estimating unit 32 calculates the deviation of the heart rate of the user i at time t on day d using the above-exemplified formulas. As a result, the estimation unit 32 estimates the expected heart rate at time t as the heart rate at time t. In addition, the estimating unit 32 can determine the range of heart rate that can occur with a probability equal to or higher than a threshold (for example, 90%) at time t by using the normal range of heart rate at time t. As a result, a heart rate range that can occur at time t with a probability of 90% or more is identified. In other words, a heart rate outside the normal range occurs less than 10% of the time for the user, so it can be considered that some physical abnormality is occurring.

In addition, when estimating the heart rate at a certain time as described above, the user's heart rate measured one minute before that time, the user's activity level, the user's step count, the temperature, the user's position, The heart rate measured two minutes before that time is used. The reason for this is that, as a result of verifying the estimation accuracy using this estimation model, the inventors found that the heart rate measured two minutes ago had a significant effect on the estimation accuracy, but the user's activity two minutes ago This is because the level, the user's step count, the temperature, and the user's location had only a small effect that did not cause a significant difference in the estimation accuracy.

In the server device 30, the notification unit 33 determines whether the heart rate at the future time point estimated by the estimation unit 32 or the user's heart rate measured at the time when the future time point arrives Notify when the heart rate is outside the normal range.

Here, FIGS. 4 and 5 are diagrams for explaining the concept of abnormality determination based on the heart rate. In FIG. 4, the time point of the estimation process by the estimation unit 32 is time t0, and the future time point to be the target of the estimation process is t1. Also, the heart rate range surrounded by the curves gu and gd is the range (that is, the above-described normal range) in which the probability is equal to or higher than the threshold (for example, 90%) at each time point. The notification unit 33 does not perform notification when the heart rate (estimated heart rate) at the future time t1 falls within the normal range (when the heart rate is point hc), but the heart rate at the future time t1 ( If the estimated heart rate) does not fall within the normal range (when the heart rate is point he), a notification is given.

Then, when the time t1 arrives, as shown in FIG. 5, the notification unit 33 indicates that the heart rate (measured heart rate) at the current time t1 is within the normal range estimated at the time to in the past with the current time t1 as the future time. If the heart rate is at point hg', notification is not performed, but if the heart rate at the current time t1 (measured heart rate) does not fall within the above normal range (heart rate is at point he' case) to notify.

In the server device 30 , the update unit 34 updates the estimation model using the measurement data acquired by the acquisition unit 31 . This estimation model is based on, for example, the user's heart rate measured one minute before a certain time, the user's activity level one minute before that time, and the user's activity level collected one minute before that time. The first measurement data including the number of steps, the temperature one minute before that time, and the position of the user one minute before that time, and the second measurement data including the heart rate measured two minutes before that time This is a model based on multiple regression analysis with measurement data as explanatory variables and the user's heart rate at a certain point in time as an objective variable. Therefore, the greater the number of sets of these explanatory variables and objective variables, the higher the estimation accuracy. Therefore, when the acquisition unit 31 acquires the measurement data, the update unit 34 updates the estimation model based on the measurement data.

Then, in the administrator terminal 40, the output unit 41 outputs information corresponding to the notification (for example, that there is an abnormality in the body) using display, sound, vibration, or the like.

[motion]
Next, the operation of this embodiment will be described with reference to FIGS. In FIG. 6, the acquisition unit 31 of the server device 30 acquires measurement data transmitted from the transmission unit 22 of the communication device 20 (step S11).

Next, the estimation unit 32 of the server device 30 uses the measurement data and the estimation model acquired by the acquisition unit 31 to determine the heart rate of the user at a certain point in the future and the heart rate of the user at a certain point in the future. An estimation process for estimating a normal heart rate range for the user is performed (step S12).

At this time, the estimation unit 32 estimates the user's activity level, and estimates a different normal range for each activity level. Specifically, as shown in FIG. 7, when the measured heart rate of the user is equal to or greater than a threshold value (the mode value for the user) (step S21; NO), the estimation unit 32 It is determined that the user is at the activity level of working (step S25). If the measured heart rate of the user is less than the threshold (step S21; YES) and the heart rate does not decrease over time (step S22; NO), the estimation unit 32 It is determined that the activity level of the user is active during rest (step S24). Further, if the measured heart rate of the user is less than the threshold (step S21; YES) and the heart rate decreases over time (step S22; YES), It is determined that the activity level of the user is resting (step S23).

Returning to FIG. 6, the notification unit 33 determines whether the heart rate (estimated value) at the future time estimated by the estimation unit 32 is outside the normal range of the heart rate at the estimated future time, or It is determined whether or not the user's heart rate (actually measured value) measured in step S13 is outside the normal range of the heart rate estimated with the present time as the future in the past (step S13).

The notification unit 33 determines whether the heart rate at the future point in time estimated by the estimation unit 32 or the heart rate of the user measured at the arrival of the future point is within the normal range of the heart rate at the estimated future point in time. If outside (step S13; YES), notification processing is performed (step S14).

Then, the update unit 34 updates the estimation model using the measurement data acquired by the acquisition unit 31 (step S15).

According to the above embodiment, in addition to determining whether the estimated future heart rate is within the normal range, it is also determined whether the measured heart rate is within the normal range. It is possible to improve the accuracy when judging an abnormality based on the conventional method. In addition, since an estimation model generated for each user is used, in this respect as well, it is possible to improve the accuracy when determining an abnormality based on the heart rate.

[Modification]
The invention is not limited to the embodiments described above. The embodiment described above may be modified as follows. Also, two or more of the following modified examples may be combined for implementation.

[Modification 1]
The body-related data is not limited to the heart rate, and may be any body-related data. Parameters used for estimating the heart rate are not limited to those exemplified in the embodiment. For example, the skin temperature of the user, temperature changes in the surroundings of the user, the history of notification to the user by the notification unit 33, or the content of work performed by the user. may be used.

[Modification 2]
In the normal heart rate range, the difference between the upper limit (gu in FIGS. 4 and 5) and the lower limit (gd in FIGS. 4 and 5) of the heart rate considered normal does not change, but the values of the upper and lower limits themselves change. In other cases, both the difference between the upper limit and the lower limit of the normal heart rate and the values of the upper limit and the lower limit themselves change. When the values of the parameters included in the estimation model according to the embodiment change, both the difference between the upper limit and the lower limit of the normal heart rate and the values of the upper limit and the lower limit themselves change. On the other hand, if the design is such that the difference between the upper limit and the lower limit of the normal heart rate does not change even if the parameters included in the estimation model change, the estimating unit 32 is included in the estimation model. A process of changing the difference according to a parameter that does not exist may be separately performed. For example, when the reliability of the estimation model is considered to be low, the estimating unit 32 sets the difference between the upper limit and the lower limit of normal heart rate as the heart rate range that can occur with a probability of 99% or more, for example. If the reliability of the estimation model is considered to be high, the difference between the upper limit and the lower limit of normal heart rate may be set as the heart rate range that can occur with a probability of 90% or more, for example. Also, for example, when the work content of the user has changed significantly, the estimation unit 32 calculates the difference between the upper and lower heart rate limits to be normal, for example, 99% from the heart rate range that can occur with a probability of 90% or more. It may be changed to a heart rate range that can occur with a probability of 10% or more. However, this is only an example, and when the reliability of the estimation model is considered to be low, the estimation unit 32 generates a difference between the upper limit and the lower limit of the normal heart rate, for example, with a probability of 90% or more. possible heart rate range, and if the estimation model is considered to be highly reliable, the difference between the upper limit and the lower limit of the heart rate that is considered normal, for example, the heart rate range that can occur with a probability of 99% or more may be

In this way, when estimating the normal range as the heart rate range that can occur at a certain probability or more at a future time, the estimating unit 32 uses the certain probability of fluctuation (for example, 90% and 99% as described above). %) may be used for estimation. Also, in this case, the estimation unit 32 may use the certain probability that varies according to parameters that are not considered in the estimation model. Parameters that are not considered in the estimation model include, for example, the reliability of the estimation model and the degree of change in user's work content as described above.

[Modification 3]
For example, weather and temperature affect measurement data such as heart rate. Therefore, the estimation model may be updated based on the future weather forecast or the like. In other words, the updating unit 34 may update the model using data predicted in the future in addition to the measurement data obtained by measuring in the past.

[Modification 4]
When a sudden change in the heart rate of the user appears, the administrator terminal 40 of an administrator who is located near the user may be notified. That is, when the change in the user's heart rate satisfies a predetermined condition (for example, when the change rate of the user's heart rate per unit time is equal to or greater than a threshold value), the notification unit 33 detects the user's communication device 20 and the second device. Compared to the first communication device (a certain administrator terminal 40) separated by one distance, the second communication device ( Giving priority to another administrator terminal 40), notification is made to the second communication device. The positions of the communication device 20 and the administrator terminal 40 may be specified by positioning using, for example, GPS (Global Positioning System), and notified to the server device 30 .

[Other Modifications]
The block diagrams used in the description of the above embodiments show blocks in functional units. These functional blocks (components) are implemented by any combination of hardware and/or software. Further, means for realizing each functional block is not particularly limited. That is, each functional block may be implemented by one device physically and/or logically coupled, or may be implemented by two or more physically and/or logically separated devices directly and/or indirectly. These multiple devices may be physically connected (eg, wired and/or wirelessly).

Aspects/embodiments described herein support Long Term Evolution (LTE), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G, 5G, Future Radio Access (FRA), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, UWB (Ultra-WideBand), It may be applied to systems utilizing Bluetooth®, other suitable systems, and/or advanced next generation systems based thereon.

The procedures, sequences, flow charts, etc. of each aspect/embodiment described herein may be interchanged so long as there is no inconsistency. For example, the methods described herein present elements of the various steps in a sample order, and are not limited to the specific order presented.
Each aspect/embodiment described herein may be used alone, in combination, or switched between implementations. In addition, the notification of predetermined information (for example, notification of “being X”) is not limited to being performed explicitly, but may be performed implicitly (for example, not notifying the predetermined information). good too.

As used herein, the terms "system" and "network" are used interchangeably.

The information, parameters, etc. described in this specification may be represented by absolute values, relative values from a predetermined value, or other corresponding information. The names used for the parameters described above are not limiting in any way. Further, the formulas, etc. using these parameters may differ from those explicitly disclosed herein.

As used herein, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining", "determining" means, for example, judging, calculating, computing, processing, deriving, investigating, looking up (e.g., table , searching in a database or other data structure), ascertaining as "determining" or "determining". Also, “judgment” and “decision” are used for receiving (e.g., receiving information), transmitting (e.g., transmitting information), input, output, and access. (accessing) (for example, accessing data in memory) may include deeming that something has been "determined" or "determined". In addition, "judgement" and "decision" are considered to be "judgment" and "decision" by resolving, selecting, choosing, establishing, comparing, etc. can contain. In other words, "judgment" and "decision" may include considering that some action is "judgment" and "decision".

The present invention may be provided as an information processing method including processing steps performed in the server device 30 . Further, the present invention may be provided as a program executed in the server device 30. FIG. Such programs may be provided in a form recorded on a recording medium such as an optical disc, or may be provided in a form such as being downloaded to a computer via a network such as the Internet and installed and made available. It is possible.

Software, instructions, etc. may be transmitted and received over a transmission medium. For example, the software can be used to access websites, servers, or other When transmitted from a remote source, these wired and/or wireless technologies are included within the definition of transmission media.

Information, signals, etc. described herein 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 refer to voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or any of these. may be represented by a combination of

Terms described herein and/or terms necessary for understanding the specification may be replaced with terms having the same or similar meaning.

Any reference to elements using the "first," "second," etc. designations used herein does not generally limit the quantity or order of those elements. These designations may be used herein as a convenient method of distinguishing between two or more elements. Thus, reference to a first and second element does not imply that only two elements can be employed therein, or that the first element must precede the second element in any way.

To the extent that "including," "comprising," and variations thereof are used herein or in the claims, these terms are inclusive, as is the term "comprising." intended to be Furthermore, the term "or" as used in this specification or the claims is not intended to be an exclusive OR.

Throughout this disclosure, where articles have been added by translation, e.g., a, an, and the in English, these articles are used unless the context clearly indicates otherwise. It shall include plural things.

Although the present invention has been described in detail above, it will be apparent to those skilled in the art that the present invention is not limited to the embodiments described herein. The present invention can be embodied in modified and determined aspects without departing from the spirit and scope of the invention as defined by the appended claims. Accordingly, the descriptions herein are for the purpose of illustration and description, and are not intended to have any limiting meaning with respect to the present invention.

DESCRIPTION OF SYMBOLS 1... Notification system 10... Measuring device 20... Communication apparatus 30... Server apparatus 40... Administrator terminal 31... Acquisition part 32... Estimation part 33... Notification part 34... Update part 3001... Processor, 3002... memory, 3003... storage, 3004... communication device, 3005... input device, 3006... output device.

Claims (10)

an acquisition unit that acquires measurement data including data measured about the user's body;
Using the acquired measurement data and a model generated for each user to estimate the user's heart rate from the measurement data, the heart rate of the user at a future point in time and the heart rate at the future point in time an estimating unit that estimates a normal heart rate range for the user;
When the estimated heart rate at the future time point or the user's heart rate measured at the arrival of the future time point is outside the normal range of the estimated heart rate at the future time point , a notification unit that performs notification,
and an updating unit that updates the model using the acquired measurement data. The estimation unit
Performing the estimation using the first measurement data measured in the first period and the second measurement data measured in the second period before the first period,
The first measurement data is
2. The information processing apparatus according to claim 1, comprising measurement data of the same type as said second measurement data and measurement data of a type different from said second measurement data. The first measurement data includes the heart rate of the user and data measured regarding the behavior of the user or data measured regarding the environment surrounding the user,
The information processing apparatus according to claim 2, wherein the second measurement data includes heart rate of the user. The information processing apparatus according to any one of claims 1 to 3, wherein the estimation unit estimates an activity level of the user and estimates the normal range that differs for each activity level. The estimation unit
If the measured heart rate of the user is equal to or higher than the threshold, it is determined that the user is at an activity level of working,
If the measured heart rate of the user is less than the threshold value and the heart rate does not decrease with the passage of time, it is determined that the activity level of the user is active during rest,
When the measured heart rate of the user is less than the threshold value and the heart rate decreases with the passage of time, it is determined that the activity level of the user is resting. 5. The information processing apparatus according to claim 4. The estimation unit
When estimating the normal range as a heart rate range that can occur with a certain probability or more at a future time, the estimation is performed using the certain probability that fluctuates. The information processing apparatus according to any one of items 1 and 2. The estimation unit
7. The information processing apparatus according to claim 6, wherein said certain probability that varies according to parameters not considered in said model is used. 8. The updating unit updates the model using the data predicted at the future point in time in addition to the measurement data obtained by measuring in the past. 1. The information processing apparatus according to 1. The notification unit is
If the change in heart rate of the user satisfies a predetermined condition, a second distance away from the user that is smaller than the first distance compared to a first communication device that is the first distance away from the user. 9. The information processing apparatus according to any one of claims 1 to 8, wherein priority is given to the second communication apparatus, and notification is made to the second communication apparatus. to the computer,
an acquisition unit that acquires measurement data including data measured about the user's body;
Using the acquired measurement data and a model generated for each user to estimate the user's heart rate from the measurement data, the heart rate of the user at a future point in time and the heart rate at the future point in time an estimating unit that estimates a normal heart rate range for the user;
When the estimated heart rate at the future time point or the user's heart rate measured at the arrival of the future time point is outside the normal range of the estimated heart rate at the future time point , a notification unit that performs notification,
and an updating unit that updates the model according to the acquired measurement data.

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