WO2022009819A1

WO2022009819A1 - Information processing system, information processing method, and program

Info

Publication number: WO2022009819A1
Application number: PCT/JP2021/025239
Authority: WO
Inventors: 滉允清水
Original assignee: 株式会社Arblet
Priority date: 2020-07-09
Filing date: 2021-07-05
Publication date: 2022-01-13
Also published as: JP6830704B1; JP2022016262A; JP2022015768A

Abstract

[Problem] To provide an information processing system, an information processing method, and a program in which an abnormality occurrence signal generation unit issues a notification through an abnormality occurrence signal indicating, in particular, an abnormality in a user on the basis of measurement data about the user. [Solution] An information processing system 1 receives measurement data over a network from a measurement device worn by a user and generates biometric data and an abnormality occurrence signal from the measurement data, and comprises a data management unit that causes the measurement data and the biometric data to be stored in association with user information related to the user, a biometric data generation unit that executes predetermined computations on the measurement data and generates the biometric data, an abnormality occurrence signal generation unit that generates the abnormality occurrence signal for indicating an abnormality occurring to the user on the basis of the biometric data, and a vehicle management unit that controls a self-driving vehicle on the basis of the abnormality occurrence signal.

Description

Information processing system, information processing method and program

This disclosure relates to information processing systems, information processing methods and programs.

It is effective for health management to continuously acquire the biometric data of the user using a measuring device and to detect the disease at an early stage and detect the change in the medical condition from the change. For that purpose, it is necessary to grasp various health conditions from a plurality of acquired biometric data.

For example, a blood pressure information measuring system that acquires a user's electrocardiographic waveform data and pulse waveform data from a measuring device and generates blood pressure information is known (see, for example, Patent Document 1). Further, for example, a development support server that generates a mathematical model that is a causal relationship for performing an operation from a user's measurement data to biometric information data and provides the mathematical model so that it can be used is also known (for example, Patent Document 2). reference.).

Japanese Patent No. 6202510 Japanese Patent No. 6257015 Japanese Unexamined Patent Publication No. 2017-197070

By the way, in recent years, efforts have been made toward the practical application of services using autonomous vehicles. Not only self-driving vehicles owned by individual users but also services for allocating self-driving vehicles are being developed (see, for example, Patent Document 3).

However, in any case, since the self-driving vehicle operates to the destination without being driven by the driver including the user, there is no person to judge the situation when an unexpected situation occurs in the vehicle. There can be. Therefore, for example, if the user on board becomes unconscious, an abnormality can be found from the behavior of the vehicle if it is not an autonomous driving vehicle, but in the case of an autonomous driving vehicle, the vehicle continues to operate in an orderly manner. Therefore, the discovery of anomalies may be delayed. It is also possible to detect anomalies with a camera or microphone, but these interfaces may not be sufficient depending on the content of the anomaly (for example, a sudden change in the user's biometric information).

In addition, the above-mentioned autonomous driving vehicle calculates an operation route from map information and the like when the destination is determined, and automatically operates along the operation route. However, users and passengers in the autonomous driving vehicle Even if an abnormality occurs, it is assumed that the destination cannot be changed to a medical institution or the like, and it may be difficult to take appropriate and prompt measures.

Therefore, in the present disclosure, an information processing system, an information processing method, and a program for controlling an autonomous driving vehicle based on an abnormality occurrence signal generated based on measurement data acquired from a measurement device worn by a user will be described.

The information processing system according to one aspect of the present disclosure is an information processing system that receives measurement data from a measuring device worn by a user via a network and generates biometric data and an abnormality generation signal from the measured data. A data management unit that stores the measurement data and the biometric data in association with user information about the user, a biometric data generation unit that executes a predetermined operation on the measurement data and generates the biometric data, and the biometric data. Based on the above, an abnormality generation signal generation unit for generating an abnormality generation signal for indicating the abnormality occurrence of the user, and a vehicle management unit for controlling an automatically driving vehicle based on the abnormality generation signal are provided.

The information processing method according to one aspect of the present disclosure is an information processing method that receives measurement data from a measuring device worn by a user via a network and generates biometric data and an abnormality generation signal from the measured data. The management unit performs a step of storing the measurement data and the biometric data in association with the user information about the user, and the biometric data generation unit executes a predetermined operation on the measurement data to generate the biometric data. The step, the step of generating the abnormality generation signal for indicating the abnormality occurrence of the user based on the biometric data by the abnormality generation signal generation unit, and the automatic driving vehicle based on the abnormality generation signal by the vehicle management unit. With steps to control.

Further, the program according to one aspect of the present disclosure receives measurement data from a measurement device worn by a user via a network, and executes an information processing method in a computer that generates biometric data and an abnormality generation signal from the measurement data. In the information processing program, the information processing method includes a step of storing the measurement data and the biometric data in association with user information about the user by the data management unit, and the biometric data generation unit for the measurement data. A step of generating the biometric data by executing a predetermined calculation, a step of generating an anomaly generation signal for indicating the user's abnormality occurrence based on the biometric data by the abnormality generation signal generation unit, and vehicle management. The unit executes a step of controlling an automatically driving vehicle based on the abnormality occurrence signal.

According to the present disclosure, since the information processing system according to the present embodiment can detect a change in the user's biometric information based on the measurement data from the measuring device worn by the user, the user's biometric information is abrupt. When an abnormality such as a change occurs, it can be promptly dealt with by notifying the outside or transporting it to a hospital.

It is a block block diagram which shows the information processing system which concerns on one Embodiment of this disclosure. It is another block block diagram which shows the information processing system which concerns on one Embodiment of this disclosure. It is a figure which shows the hardware configuration of the management server 100 of FIG. 1 or FIG. It is a block diagram illustrating the function of the storage unit 120 and the control unit 130 of FIG. It is a schematic diagram which shows the example of the tag information associated with the measurement data of FIG. It is a figure for demonstrating the example of the electrocardiographic waveform and the pulse waveform measured by the measuring apparatus 300 of FIG. 1 or FIG. It is a flowchart which shows the example of the process of the information processing system 1 of FIG.

The contents of the embodiments of the present invention will be listed and described. The system according to the embodiment of the present invention has the following configurations.

[Item 1]
An information processing system that receives measurement data from a measurement device worn by a user via a network and generates biometric data and an abnormality occurrence signal from the measurement data.
A data management unit that stores the measurement data and the biometric data in association with the user information about the user.
A biometric data generation unit that executes a predetermined operation on the measurement data and generates the biometric data.
An abnormality generation signal generation unit that generates an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biometric data.
A vehicle management unit that controls an autonomously driven vehicle based on the abnormality occurrence signal is provided.
An information processing system characterized by this.
[Item 2]
The measurement data is data including at least one of the electrocardiogram, pulse wave, temperature, acceleration, and angular velocity of the user.
The information processing system according to item 1, wherein the information processing system is characterized by the above.
[Item 3]
The biometric data includes blood pressure information, heartbeat information, blood oxygen level information, electrocardiographic information, respiratory rate, body temperature information, step count information, walking speed information, stride information, center of gravity position information, posture information, and behavior type. Data including at least one of information, stress information, exercise amount information, exercise load information, travel distance information, and activity amount information.
The information processing system according to any one of items 1 and 2, wherein the information processing system is characterized by the above.
[Item 4]
When the abnormality generation signal generation unit detects an abnormality regarding blood pressure information, the abnormality generation signal generation unit generates the abnormality generation signal.
The information processing system according to any one of items 1 to 3, wherein the information processing system is characterized by the above.
[Item 5]
The abnormality generation signal generation unit generates the abnormality generation signal when an abnormality is detected in the heartbeat information.
The information processing system according to any one of items 1 to 4, wherein the information processing system is characterized by the above.
[Item 6]
The abnormality generation signal generation unit generates the abnormality generation signal when an abnormality is detected with respect to the temperature information.
The information processing system according to any one of items 1 to 5, wherein the information processing system is characterized by the above.
[Item 7]
The abnormality generation signal generation unit generates the abnormality generation signal when an abnormality is detected in the operation information of the portion to which the measuring device is attached.
The information processing system according to any one of items 1 to 6, wherein the information processing system is characterized by the above.
[Item 8]
The vehicle management unit operates the self-driving vehicle to a medical institution based on the abnormality occurrence signal.
The information processing system according to any one of items 1 to 7, wherein the information processing system is characterized by the above.
[Item 9]
The vehicle management unit operates the self-driving vehicle to the user's position based on the abnormality occurrence signal and the user's position information.
The information processing system according to any one of items 1 to 7, wherein the information processing system is characterized by the above.
[Item 10]
The vehicle management unit operates the self-driving vehicle to the position of the medical worker based on the abnormality occurrence signal and the position information of the medical worker.
The information processing system according to any one of items 1 to 7, wherein the information processing system is characterized by the above.
[Item 11]
The information processing system is
Further, a management server having at least the abnormality generation signal generation unit is provided.
The management server notifies the contact related to the user of the occurrence of the abnormality based on the generation of the abnormality occurrence signal.
The information processing system according to any one of items 1 to 10, wherein the information processing system is characterized by the above.
[Item 12]
It is an information processing method that receives measurement data from a measuring device worn by a user via a network and generates biometric data and an abnormality occurrence signal from the measured data.
A step of storing the measurement data and the biometric data in association with the user information about the user by the data management unit.
A step of executing a predetermined operation on the measurement data by the biometric data generation unit to generate the biometric data, and a step of generating the biometric data.
A step of generating an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biological data by the abnormality generation signal generation unit, and a step of generating the abnormality generation signal.
The vehicle management unit comprises a step of controlling an autonomously driven vehicle based on the abnormality occurrence signal.
An information processing method characterized by that.
[Item 13]
An information processing program that receives measurement data from a measurement device worn by a user via a network and executes an information processing method on a computer to generate biometric data and an abnormality occurrence signal from the measurement data.
The information processing method is
A step of storing the measurement data and the biometric data in association with the user information about the user by the data management unit.
A step of executing a predetermined operation on the measurement data by the biometric data generation unit to generate the biometric data, and a step of generating the biometric data.
A step of generating an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biological data by the abnormality generation signal generation unit, and a step of generating the abnormality generation signal.
A step of controlling an autonomous vehicle based on the abnormality occurrence signal by the vehicle management unit,
To execute,
An information processing program characterized by this.

Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The embodiments described below do not unreasonably limit the contents of the present disclosure described in the claims. Also, not all of the components shown in the embodiments are essential components of the present disclosure. In addition, the features shown in each embodiment can be applied to other embodiments as long as they do not contradict each other.

(Embodiment 1)
<Structure>
FIG. 1 is a block configuration diagram showing an information processing system 1 according to the first embodiment of the present disclosure. The information processing system 1 receives, for example, the user's measurement data from the measurement device 300 via the network NW at the management server 100, and generates biometric data by performing a predetermined calculation on the measurement data. It is an information processing system that generates an abnormality occurrence signal based on the biometric data and controls the automatically driven vehicle 400 by the abnormality occurrence signal.

The information processing system 1 has a management server 100, a user terminal device 200, a measuring device 300, an autonomous driving vehicle 400, and a network NW. The management server 100, the user terminal device 200, and the autonomous driving vehicle 400 are connected via the network NW. The network NW is composed of the Internet, an intranet, a blockchain network, a wireless LAN (Local Area Network), a WAN (Wide Area Network), and the like.

The management server 100 is, for example, a device that receives user's measurement data from the measurement device 300 via a network via the user terminal device 200 and calculates the measurement data into biometric data, for example, various Web services. It consists of the server equipment provided.

The user terminal device 200 is an information processing device possessed by the user, such as a personal computer, a tablet terminal, a smartphone, a smart watch, a mobile phone, a PHS, or a PDA. It is used for displaying on a waveform graph or the like. User information such as a user's identification number, date of birth, gender, height, and weight is registered in the user terminal device 200 in advance, and user information including the age calculated from the date of birth is associated with the measurement data. Is transmitted to the management server 100 via the network NW.

The measuring device 300 is a device that measures the biometric data of the user, and is, for example, a wearable device that is used by being worn on the body such as the wrist or arm of the user. The measuring device 300 is, for example, a plurality of types of devices for measuring data of a user's electrocardiogram, pulse wave, temperature (body temperature), acceleration, and angular velocity.

As an example of the specific configuration of the measuring device 300, a device may be configured in which two electrodes are brought into contact with the skin and the electrocardiogram is acquired as electrocardiographic waveform data from the time change of the difference in the detected potential. The radio wave type may be data acquired by a galvanic skin reaction. In addition, each light is radiated to the skin from LEDs that emit green, red, and infrared light, and the time change in the intensity of the light received by the photodiode causes a pulse wave due to the change in the volume of the blood vessel caused by the heartbeat of the user's heart. It may be configured by a device that acquires pulse waveform data, and the pulse waveform that can be detected by this method is a photoelectric volume pulse waveform. Further, the device may be configured to acquire the user's skin temperature as data by a temperature sensor in contact with the user's skin. Further, it may be configured by a 3-axis acceleration sensor that detects the variation state of each of the orthogonal XYZ axes, and the user's motion is acquired as acceleration data, and for example, the measuring device 300 is attached to the user's wrist, arm, or the like. In this case, the measuring device 300 acquires acceleration data as an acceleration in which the swing of the wrist, arm, or the like and the movement of the whole body are combined. Further, it may be configured by a gyro sensor (angular velocity sensor) that detects the rotational angular velocity in each of the orthogonal XYZ axes, and the user's motion is acquired as angular velocity data, for example, the measuring device 300 is attached to the user's wrist, arm, or the like. If so, the measuring device 300 acquires the angular velocity data as the angular velocity in which the rotation of the wrist, the arm, or the like and the movement of the whole body are combined.

Between the user terminal device 200 and the measuring device 300, Bluetooth (registered trademark), short-range wireless communication (Near Field radio Communication = NFS), Afero (registered trademark), Zigbee (registered trademark), Z-Wave (registered trademark). ) Or is connected using a wireless LAN or the like. In addition, instead of such a wireless connection, a wired connection may be made. Further, the user terminal device 200 and the measuring device 300 may be an integrated device. For example, the measuring device 300 may be provided with a communication function so as to be able to directly communicate with the management server 100. May be good.

There are one or more user terminal devices 200, and they are connected to the network NW for the number of users who use the measuring device 300. There are one or a plurality of measuring devices 300, and they are connected to the number of user terminal devices 200 used by one user. When one user uses a plurality of measuring devices 300, the plurality of measuring devices 300 are connected to one user terminal device 200.

The autonomous driving vehicle 400 may have a known configuration and may be managed by the management server 100, for example, but as illustrated in FIG. 2, the vehicle management server 500 that manages the autonomous driving vehicle 400 is independent. It is desirable that the management entity can be separated if the configuration is such that the management server 100 and the management server 100 are linked via the network NW. The control of the autonomous driving vehicle 400 may also be a known method. For example, the vehicle management unit 520 is provided, and the server acquires the GPS information of the autonomous driving vehicle 400 to recognize the position information of each vehicle and recognizes the position information of each vehicle. Manage the route information instructed by the server. Further, a part or all of the functions of the vehicle management unit 520 may be provided in the management server 100 shown in FIG. 1 or FIG.

On the other hand, in the self-driving vehicle 400, known driving control is performed according to map information, position information, information on the route to the destination, etc., and further, the surroundings of the self-driving vehicle 400 are based on sensors such as cameras possessed by the self-driving vehicle 400. Operation control is performed according to the situation.

The autonomous driving vehicle 400 may have a known configuration as described above, and is controlled by having a control unit and a storage unit (not shown). Further, the self-driving vehicle 400 may include a storage unit 420 in which, for example, a medical device such as an AED, a drug, an injection, a first aid item such as a bandage, a direct telephone call to a medical institution, or the like is stored. The storage unit 420 is provided with, for example, a door having an electronic lock, and an abnormality occurrence signal or an abnormality occurrence from a management server 100, a user terminal device 200, a measuring device 300, an automatic driving vehicle 400, a vehicle management server 500, or the like. It may be unlocked by an instruction signal based on the signal so that the stored object can be used.

<Management server 100>
FIG. 3 is a diagram showing a hardware configuration of the management server 100. FIG. 4 is a block diagram illustrating the functions of the storage unit 120 and the control unit 130. The configuration shown in the figure is an example, and may have other configurations.

The management server 100 includes a communication unit 110, a storage unit 120, a control unit 130, and an input / output unit 140. These functional units are realized by executing a predetermined program for the management server 100.

The communication unit 110 is a communication interface for communicating with the user terminal device 200, and communication is performed according to a communication protocol such as TCP / IP (Transmission Control Protocol / Internet Protocol).

The storage unit 120 stores programs for executing various control processes and functions in the control unit 130, input data, and the like, and is composed of a RAM (RandomAccessMemory), a ROM (ReadOnlyMemory), and the like. To. Further, as shown in FIG. 4, the storage unit 120 associates the measurement data DB 121, which stores the measurement data by the measuring device 300 with the user information, and the biometric data calculated from the measurement data with the user information. The biometric data DB 122 to be stored and the user information DB 123 to store the user information including the user identification number are stored. Further, the user information includes the account information generated by the data management unit 131, and the user information DB 123 may store the account information in association with other user information. Further, the storage unit 120 temporarily stores the data that has communicated with the user terminal device 200. The data structure of the DB is not limited to this, and a part of the above-mentioned DB may be stored in the user terminal device 200 or the measuring device 300.

The control unit 130 controls the overall operation of the management server 100, and is composed of a CPU (Central Processing Unit) and the like. Further, as shown in FIG. 4, the control unit 130 includes functional units such as a data management unit 131, a biological data generation unit 132, an abnormality generation signal generation unit 133, and a data output unit 134.

The data management unit 131 generates account information for each user who uses the measuring device 300. This account information generation is performed when the user who uses the measuring device 300 registers the account information on the user terminal device 200. Therefore, the data management unit 131 controls whether or not the user terminal device 200 of the user can access various DBs in the storage unit 120 for each account. The data management unit 131 stores various data such as measurement data, biometric data, and user support data in a corresponding DB in association with user information. Further, at this time, the data management unit 131 can associate the measurement data with predetermined tag information and store it.

FIG. 5 is a schematic diagram showing an example of tag information associated with the measurement data of FIG. The data D1 shown in FIG. 5 is the measurement data of the measuring device 300. The tag T1 is tag information associated with the data D1, and for example, the time information in which the measuring device 300 measures the data D1 or the time information in which the data D1 is transmitted from the measuring device 300 to the user terminal device 200 is time-series. It is stored as data. Alternatively, both the measured time information and the transmitted time information may be associated. For example, in the first line of the tag T1 shown in FIG. 5, "20180620120746144" is stored, but it indicates 12:07:46:144 ms on June 20, 2018. Such time information can be obtained from the communication log. This makes it possible to grasp which time zone the measurement data belongs to.

It should be noted that the association of measurement data with such tag information is not limited to time information, and physical information or activity information indicating the user's physical condition or activity state may be freely entered and stored as tag information. Have them choose from a given option (for example, in response to the question "How are you feeling now?", Choose one of "1: good, 2: normal, 3: bad", etc.) and make that choice. You may try to remember the answer you gave. As a result, when the control unit 150 generates biometric data, it is possible to generate more accurate biometric data by associating the tag information with the biometric data.

Further, for example, the data management unit 131 can sort the data D1 in the time order of the tag T1 as shown in FIG. The reason for this configuration is that the measurement data is acquired in chronological order based on the biometric data of the user, and it is easier to process if the measurement data is arranged in chronological order. When receiving via the unit 110, the received data may be reversed (the transmitted data transmitted later is received before the transmitted data transmitted earlier) due to a change in the communication status or the like. This is to prevent inconsistency in the measurement data at that time. This makes it possible to prevent inconsistencies in the measured data.

The biometric data generation unit 132 performs a predetermined operation on the measurement data stored in the measurement data DB 121 to generate biometric data. This biometric data may be any information as long as it can be calculated from the measurement data, for example, the user's blood pressure information, heartbeat information, blood oxygen level information, maximum oxygen intake information, electrocardiographic information, etc. Breath rate, body temperature information, step count information, stride information, center of gravity position information, posture information, action type information, stress information, exercise amount information, exercise load information, movement distance information, movement speed information, activity amount information, hands or legs, etc. It is data such as operation information of the mounting part of the above, and is calculated from the measurement data by a known method. The biometric data generated by the calculation is stored in the biometric data DB 122.

Here, an example is a method of calculating the maximum blood pressure and the minimum blood pressure, which are biological data, from the measurement data. FIG. 6 is a diagram for explaining an example of an electrocardiographic waveform and a pulse wave measured by the measuring device 300 of FIG. 1, and is a diagram for explaining an example of the electrocardiographic waveform and the pulse wave of the user measured by the measuring device 300 and stored in the storage unit 120. And the photoelectric volume pulse waveform, the velocity pulse waveform in which the photoelectric volume pulse waveform is first-order differentiated by time, and the acceleration pulse waveform in which the photoelectric volume pulse waveform is second-order differentiated by time are shown. FIG. 6 shows an electrocardiographic waveform, a photoelectric volume pulse waveform, a velocity pulse waveform, and an acceleration pulse waveform in order from the top. The vertical axis shows the intensity of each waveform, and the electrocardiographic waveform and the photoelectric volume pulse waveform are represented by MV indicating the potential. The horizontal axis shows the passage of time, and shows the passage of time from left to right.

The electrocardiographic waveform is a waveform showing a periodic change in an electrical signal that causes a human heart to beat. In the electrocardiographic waveform, the names of P wave, Q wave, R wave, S wave, and T wave are assigned to the inflection points of the shape, respectively, and indicate one cycle of heartbeat. The P wave represents the atrial contraction, the Q wave, the R wave, and the S wave represent the state of ventricular contraction, and the T wave represents the start of ventricular dilation.

The photoelectric volume pulse waveform is a waveform showing changes in blood pressure and volume in the peripheral vascular system accompanying the beating of the human heart. In the photoelectric volume pulse waveform, the names of A wave, P wave, V wave, and D wave are assigned to the inflection points of the shape, respectively, and indicate one cycle of the heartbeat. With the A wave as the reference point at the time when the arterial pulse wave is generated, the P wave is the Percussion wave (shock wave) generated by the left ventricular ejection, the V wave is the Valley wave (wave due to the overlapping uplift) generated when the aortic valve is closed, and the D wave. Indicates a Dicrotic wave (overlapping wave) which is a reflected vibration wave.

The velocity pulse waveform is the first derivative of the photoelectric volume pulse waveform with respect to time. The acceleration pulse waveform is a first-order derivative of the velocity pulse waveform, that is, a second-order derivative of the photoelectric volume pulse waveform. As shown in FIG. 6, the acceleration pulse waveform has a wave (initial contraction positive wave), b wave (initial contraction negative wave), c wave (mid-contraction re-rise wave), and d wave (contraction) at each peak of the waveform. The names of the late re-descending wave), the e wave (extended early positive wave), and the f wave (extended early negative wave) are assigned.

The ratio of the intensity of the b wave to the intensity of the a wave and the ratio of the intensity of the f wave to the intensity of the e wave are parameters indicating the elasticity, that is, the elasticity of the blood vessel, respectively. The main vascular components are vascular endothelium (Endothelium), elastic fibers (Elastin), proteins (Collagen), and smooth muscle (Smooth Muscle). These components have different properties, and Collagen and Elastin have a strong influence on the elasticity of blood vessels at the maximum blood pressure and the minimum blood pressure, respectively. Therefore, the elasticity that differs depending on the blood pressure value is indicated by the parameters of the ratio of the intensity of the b wave to the intensity of the a wave (b / a) and the ratio of the intensity of the f wave to the intensity of the e wave (f / e). These values also fluctuate depending on the influence of age, gender, and environment variables. Therefore, the values of (b / a) and (f / e) can be calculated as the characteristic information of the acceleration pulse waveform.

As shown in FIG. 6, the time difference between the time Tr at which the R wave is generated and the time Tp at which the P wave is generated is the ventricular systolic pulse wave propagation time PTT_SYS. The time of the difference between the time Tt in which the T wave is generated and the time Td in which the D wave is generated is the ventricular diastolic pulse wave propagation time PTT_DIA. That is, from the R wave time Tr and T wave time Tt of the electrocardiographic waveform, and the T wave time Tp and D wave time Td of the photoelectric volume pulse waveform, the ventricular systolic pulse wave propagation time PTT_SYS and the ventricular diastole period. The pulse wave propagation time PTT_DIA can be calculated.

Further, it is known that the relationship between the pulse wave velocity and the Young's modulus of the arterial wall has a correlation expressed by a predetermined formula, and the relationship between the Young's modulus and the blood pressure value is also shown by a predetermined formula. It is known to be correlated. Therefore, the maximum blood pressure can be obtained by a predetermined formula of the ventricular systolic pulse wave velocity PTT_SYS, and the minimum blood pressure can be obtained by a predetermined formula of the ventricular diastolic pulse wave propagation time PTT_DIA. This makes it possible to calculate the maximum blood pressure and the minimum blood pressure.

Further, exemplifying a method of calculating heart rate information which is biological data from measurement data, particularly a resting heart rate, for example, electrocardiographic waveform data measured by a measuring device 300 worn by a user at rest (for example, FIG. 6). Heart rate information can be obtained from the intervals of QRS waves in (electrocardiographic waveform data, etc.).

Further, exemplifying the method of calculating the temperature information which is the biological data from the measurement data, for example, the user's skin temperature data measured by the temperature sensor of the measuring device 300 worn by the user can be obtained as the temperature information.

Further, exemplifying a method of calculating motion information of a wearing part such as a user's hand, which is biological data, from measurement data, for example, a measuring device from acceleration data and angular velocity data measured by the measuring device 300 worn by the user. It is possible to obtain motion information on how fast and at what angle the site where the 300 is attached (for example, wrist or ankle) is moving.

The abnormality generation signal generation unit 133 generates an abnormality generation signal based on biological data such as the above-mentioned blood pressure information, heart rate information, temperature information, and operation information of the wearing site. More specifically, the biometric data constantly calculated by the biometric data generation unit 132 at predetermined intervals is stored in the biometric data DB 122, and the abnormality generation signal generation unit 133 and the past biometric data stored in the biometric data DB 122. When comparing current biometric data (for example, comparison with data from a few minutes ago, comparison with the average value of a predetermined period in the past, comparison with resting time, etc.) and there is a difference of more than a predetermined threshold. Generates an anomaly occurrence signal. This makes it possible to confirm the occurrence of abnormalities in biometric data such as blood pressure information, heart rate information, and temperature information, for example, when the physical condition deteriorates significantly, and in biometric data such as motion information of the wearing site, for example, lose consciousness. It is possible to confirm the occurrence of an abnormality in the event of a fall. Further, the generation of the abnormality generation signal based on the operation information of the mounting site is not limited to this, and for example, after the comparison result has a difference of a predetermined threshold value or more, the user is not operating from the subsequent operation information. An abnormality occurrence signal may be generated when it is determined that the continuation has continued for a predetermined period. Further, an abnormality occurrence signal may be generated when it is determined that an abnormality has occurred in a plurality of biometric data (for example, there are a plurality of biometric data whose comparison results have a difference of a predetermined threshold value or more). ..

The generated abnormality occurrence signal is linked to user information such as a medical institution or a close relative, directly from the data output unit 134 of the management server 100 or indirectly via the user terminal device 200 or the measuring device 300, for example. It may be controlled to send a notification indicating an abnormality (for example, a notification via a predetermined application stored in a device such as a PC or a smartphone or a notification using an e-mail address) to the contact. The user terminal device 200 may start a call with the above contact. At this time, the user's past biometric data, the current biometric data status, and the current location information may be transmitted together with the notification, or the contact device may be authorized to view the user's biometric data. It may be given. This makes it possible to automatically notify the occurrence of an abnormality even when it is difficult for the user to notify the occurrence of the abnormality. In addition, since appropriate information is shared especially with the medical institution, it becomes possible to immediately deal with the medical institution when dealing with the user.

Further, the generated abnormality generation signal is transmitted to the vehicle management unit 520, for example, in the management server 100, directly from the management server 100, or indirectly via the user terminal device 200 or the measuring device 300. The abnormality occurrence signal or the instruction signal based on the abnormality occurrence signal is recognized, and the vehicle management unit 520 may change the destination of the automatic driving vehicle 400 on which the user rides to a medical institution or the like. More specifically, the destination of the autonomous driving vehicle 400 is based on the position information of the autonomous driving vehicle 400, for example, map information registered in the management server 100 or the vehicle management server 500, registration information of a medical institution in advance, and the like. It may be set to a nearby medical institution by searching, or may be set to a family medical institution associated with user information and registered in the user information DB 123, for example. In addition, the above-mentioned notification to the medical institution or the like may be linked to notify the medical institution selected by the change of destination.

Further, the generated abnormality generation signal is, for example, in the management server 100, directly from the management server 100, or indirectly via the user terminal device 200 or the measuring device 300, in the vehicle management unit 520. In addition to recognizing the abnormality occurrence signal or the instruction signal based on the abnormality occurrence signal, for example, the location information of the medical staff registered in advance in the management server 100 (for example, arbitrary address information or medical engagement at a predetermined cycle). The vehicle management unit 520 also recognizes the location information acquired from the user terminal (not shown), and when resetting the movement route to move to the medical institution as described above, the above medical staff The location information point, or any point derived from the location information point and the current location of the auto-driving vehicle 400 (for example, medical staff can board the auto-driving vehicle 400 in the shortest time considering each other's moving speeds). Point, etc.) may be included as a relay point. This allows for more appropriate first aid before arriving at the medical institution.

Further, the generated abnormality generation signal is, for example, directly from the data output unit 134 of the management server 100, or indirectly via the user terminal device 200, the measurement device 300, and the vehicle management server 500, and the automated driving vehicle 400. The storage unit 420, which is transmitted to the server and stores, for example, an AED, a drug, an injection drug, or the like, may be unlocked and made available. This makes it possible to smoothly perform first aid and the like even when passengers are on board, for example.

Further, the generated abnormality generation signal is, for example, directly from the data output unit 134 of the management server 100, or indirectly via the user terminal device 200, the measurement device 300, and the vehicle management server 500, for the autonomous driving vehicle 400. It may be configured like a cot, for example, the backrest of the seat may automatically fall over, the window may be opened automatically, the lamp provided outside the vehicle may be automatically turned on, or the vehicle may be automatically turned on. The equipment mounted on the self-driving vehicle may automatically operate appropriately in connection with the occurrence of an abnormality, such as the horn or the siren provided outside the vehicle automatically operating.

As described above, the data output unit 134 outputs biological data, abnormality occurrence signals, various notifications, etc. to each device such as the user terminal device 200 and the vehicle management server 500. In the user terminal device 200 or the like, the output data may be displayed on the screen via, for example, a dedicated application so that the user can easily confirm the data.

The input / output unit 140 is an information input device such as a keyboard and a mouse, and an output device such as a display.

<Processing flow>
The processing flow of the information processing method executed by the information processing system 1 will be described with reference to FIG. 7. FIG. 7 is a flowchart showing an example of processing of the information processing system 1 of FIG.

As the process of step S101, the data management unit 131 generates account information for each user who uses the measuring device 300, and acquires predetermined user information from the user terminal device 200 or the like. The registered user information is stored in the user information DB 123 by the data management unit 131. The process of step S101 may be performed as a pre-process for the user to use the measuring device 300, or may be performed when the user uses the measuring device 300 for the first time.

When the user uses the measuring device 300 as the process of step S102, the measurement data is transmitted from the measuring device 300 to the management server 100 via the user terminal device 200, and is received via the communication unit 110. The data management unit 131 stores the measurement data associated with the user information in the measurement data DB 121 of the storage unit 120.

As the process of step S103, the measurement data is read by the biological data generation unit 132, and the biological data is generated by a predetermined calculation or the like. The generated biometric data is stored in the biometric data DB 122 by the data management unit 131.

As the process of step S104, the biometric data is read by the abnormality generation signal generation unit 133, the past biometric data and the current biometric data are compared at a predetermined cycle, and it is determined whether or not the abnormality generation signal is generated. For example, if there is no difference of the predetermined threshold value or more, the process returns to step S102, and if there is a difference of the predetermined threshold value or more, the process proceeds to the next step 105.

As the process of step S105, at least one of the biometric data, the abnormality occurrence signal, and the notification is output to the user terminal device 200, the vehicle management unit 520, and the autonomous driving vehicle 400 by the data output unit 134.

(Embodiment 2)
In the first embodiment described above, the information processing system assumes that the user is in the autonomous driving vehicle 400, but it is also useful when the user is outside the autonomous driving vehicle 400. That is, when the above-mentioned abnormality occurrence signal is generated, the user's position information is acquired by the GPS or the like provided in the user terminal device 200 or the measuring device 300, and the vehicle management is performed by combining the position information and the abnormality occurrence signal. By recognizing by the unit 520, the self-driving vehicle 400 can be directed to the place where the user who has the abnormality is present.

Then, for example, people around the user may use the autonomous driving vehicle 400 to transport the user to a medical institution, or the user may take out necessary equipment or the like from the storage unit 420 provided in the autonomous driving vehicle 400 and use it. It is possible to respond quickly to abnormalities in.

<Effect>
As described above, since the information processing system according to the present embodiment can detect a change in the user's biometric information based on the measurement data from the measuring device worn by the user, a sudden change in the user's biometric information is possible. When an abnormality such as the above occurs, it is possible to take prompt action by notifying the outside of the automatically driven vehicle, transporting the vehicle to a hospital by the automatically driven vehicle, or directing the automatically driven vehicle.

Although the embodiments related to the disclosure have been described above, these can be implemented in various other embodiments, and can be implemented by making various omissions, substitutions, and changes. These embodiments and variations as well as those with omissions, substitutions and modifications are included in the technical scope of the claims and the equivalent scope thereof.

1 Information system 100 Management server 200 User terminal device 300 Measuring device 400 Automated driving vehicle 500 Vehicle management server NW network

Claims

An information processing system that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
A data management unit that stores measurement data and biometric data in association with user information about the user.
A biometric data generation unit that executes a predetermined operation on the measurement data and generates the biometric data.
An abnormality generation signal generation unit that generates an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biometric data.
A vehicle management unit that controls an autonomously driven vehicle based on the abnormality occurrence signal is provided.
The autonomous driving vehicle is automatically controlled based on the acquired route information at least before the generation of the abnormality occurrence signal, and is controlled so that the backrest of the seat falls down based on the abnormality occurrence signal.
An information processing system characterized by this.
An information processing system that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
A data management unit that stores measurement data and biometric data in association with user information about the user.
A biometric data generation unit that executes a predetermined operation on the measurement data and generates the biometric data.
An abnormality generation signal generation unit that generates an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biometric data.
A vehicle management unit that controls an autonomously driven vehicle based on the abnormality occurrence signal is provided.
Based on the abnormality occurrence signal, the self-driving vehicle is controlled to unlock the storage unit in which at least one of a medical device, a drug, an injectable drug, an emergency treatment product, and a direct telephone call to a medical institution is stored.
An information processing system characterized by this.
An information processing system that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
A data management unit that stores measurement data and biometric data in association with user information about the user.
A biometric data generation unit that executes a predetermined operation on the measurement data and generates the biometric data.
An abnormality generation signal generation unit that generates an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biometric data.
A vehicle management unit that controls an autonomously driven vehicle based on the abnormality occurrence signal is provided.
The vehicle management unit sets a relay point for contacting the medical staff based on the position information of the medical staff on the route from the current location to the medical institution while the user is in the self-driving vehicle. Control the self-driving vehicle from the current location to the medical institution via the relay point.
An information processing system characterized by this.
The abnormality generation signal generation unit generates the abnormality generation signal when an abnormality is detected in the blood pressure information of the user.
The information processing system according to any one of claims 1 to 3, wherein the information processing system is characterized by the above.
The abnormality generation signal generation unit generates the abnormality generation signal when an abnormality is detected in the heartbeat information of the user.
The information processing system according to any one of claims 1 to 4, wherein the information processing system is characterized by the above.
The abnormality generation signal generation unit generates the abnormality generation signal when an abnormality is detected in the skin temperature information of the user.
The information processing system according to any one of claims 1 to 5, wherein the information processing system is characterized by the above.
The abnormality generation signal generation unit generates the abnormality generation signal when an abnormality is detected in the operation information of the part of the user who is equipped with the measuring device.
The information processing system according to any one of claims 1 to 6, wherein the information processing system is characterized by the above.
It is an information processing method that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
A step of storing the measurement data and the biometric data in association with the user information about the user by the data management unit.
A step of executing a predetermined operation on the measurement data by the biometric data generation unit to generate the biometric data, and a step of generating the biometric data.
A step of generating an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biological data by the abnormality generation signal generation unit, and a step of generating the abnormality generation signal.
The vehicle management unit includes a step of controlling the self-driving vehicle based on the abnormality occurrence signal.
The autonomous driving vehicle is automatically controlled based on the acquired route information at least before the generation of the abnormality occurrence signal, and is controlled so that the backrest of the seat falls down based on the abnormality occurrence signal.
An information processing method characterized by that.
It is an information processing method that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
A step of storing the measurement data and the biometric data in association with the user information about the user by the data management unit.
A step of executing a predetermined operation on the measurement data by the biometric data generation unit to generate the biometric data, and a step of generating the biometric data.
A step of generating an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biological data by the abnormality generation signal generation unit, and a step of generating the abnormality generation signal.
The vehicle management unit includes a step of controlling the self-driving vehicle based on the abnormality occurrence signal.
Based on the abnormality occurrence signal, the self-driving vehicle is controlled to unlock the storage unit in which at least one of a medical device, a drug, an injectable drug, an emergency treatment product, and a direct telephone call to a medical institution is stored.
An information processing method characterized by that.
It is an information processing method that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
A step of storing the measurement data and the biometric data in association with the user information about the user by the data management unit.
A step of executing a predetermined operation on the measurement data by the biometric data generation unit to generate the biometric data, and a step of generating the biometric data.
A step of generating an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biological data by the abnormality generation signal generation unit, and a step of generating the abnormality generation signal.
The vehicle management unit includes a step of controlling the self-driving vehicle based on the abnormality occurrence signal.
The vehicle management unit sets a relay point for contacting the medical staff based on the position information of the medical staff on the route from the current location to the medical institution while the user is in the self-driving vehicle. Control the self-driving vehicle from the current location to the medical institution via the relay point.
Including more steps,
An information processing method characterized by that.
An information processing program that executes an information processing method in a computer that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
The information processing method is
A step of storing the measurement data and the biometric data in association with the user information about the user by the data management unit.
A step of executing a predetermined operation on the measurement data by the biometric data generation unit to generate the biometric data, and a step of generating the biometric data.
A step of generating an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biological data by the abnormality generation signal generation unit, and a step of generating the abnormality generation signal.
The vehicle management unit executes a step of controlling the autonomous driving vehicle based on the abnormality occurrence signal.
The autonomous driving vehicle is automatically controlled based on the acquired route information at least before the generation of the abnormality occurrence signal, and is controlled so that the backrest of the seat falls down based on the abnormality occurrence signal.
An information processing program characterized by this.
An information processing program that executes an information processing method in a computer that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
The information processing method is
A step of storing the measurement data and the biometric data in association with the user information about the user by the data management unit.
A step of executing a predetermined operation on the measurement data by the biometric data generation unit to generate the biometric data, and a step of generating the biometric data.
A step of generating an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biological data by the abnormality generation signal generation unit, and a step of generating the abnormality generation signal.
The vehicle management unit executes a step of controlling the autonomous driving vehicle based on the abnormality occurrence signal.
Based on the abnormality occurrence signal, the self-driving vehicle is controlled to unlock the storage unit in which at least one of a medical device, a drug, an injectable drug, an emergency treatment product, and a direct telephone call to a medical institution is stored.
An information processing program characterized by this.
An information processing program that executes an information processing method in a computer that receives measurement data from a measurement device worn by a user via a network and generates an abnormality occurrence signal based on the measurement data.
The information processing method is
A step of storing the measurement data and the biometric data in association with the user information about the user by the data management unit.
A step of executing a predetermined operation on the measurement data by the biometric data generation unit to generate the biometric data, and a step of generating the biometric data.
A step of generating an abnormality generation signal for indicating the occurrence of an abnormality of the user based on the biological data by the abnormality generation signal generation unit, and a step of generating the abnormality generation signal.
The vehicle management unit executes a step of controlling the autonomous driving vehicle based on the abnormality occurrence signal.
The vehicle management unit sets a relay point for contacting the medical staff based on the position information of the medical staff on the route from the current location to the medical institution while the user is in the self-driving vehicle. Control the self-driving vehicle from the current location to the medical institution via the relay point.
Including more steps,
An information processing program characterized by this.