JP6945908B1 - Information processing systems, servers, information processing methods and programs - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a management server, a data management method and a data management program for providing user support data including advice and alerts for improving rehabilitation. In an information processing system 1 in which a management server 100 and a user terminal device are connected via a network, the management server 100 transmits measurement data from a measurement device worn by the user via the network at a predetermined cycle. The biometric data generation unit 132 that receives the data from the measurement data, generates biometric data and user support data from the measurement data, executes a predetermined calculation on the measurement data, and generates at least the exercise information, and the exercise information and the reference exercise information. It is provided with a user support data generation unit 133 that generates user support data including information related to the user's rehabilitation operation according to the comparison result of the above. [Selection diagram] Fig. 3

Description

The present disclosure relates to an information processing system, a server, an information processing method and a program that generate user support data based on measurement data acquired from a measuring device.

It is effective for health management to continuously acquire user's biological data using a measuring device and to detect a disease at an early stage or detect a change in a 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, there is known 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 (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 biological 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

By the way, for example, some stroke sufferers have sequelae such as dysfunction, and it is expected that functional recovery can be expected by continuing continuous rehabilitation. However, rehabilitation costs will not be covered by insurance after a certain period (6 months) after the onset of symptoms, and you will be forced to bear the cost at your own expense. However, the cost is said to be about 300,000 yen in two months, which is a high amount to be borne by an individual.

In addition, the onset of stroke disease is particularly common among the elderly, but it is also a problem that there are many new cases in the working population aged 40 to 65 years. Maintaining and securing employment resources in a society with a declining birthrate and an aging population is indispensable for supporting Japan's social security system in the future, and it is important to support as many people as possible to reintegrate into society. For that purpose, it is necessary to realize continuous rehabilitation in a form that bears less cost for individuals. Moreover, not only stroke but also those suffering from illnesses requiring rehabilitation are in the same situation.

Therefore, in the present disclosure, an information processing system, a server, an information processing method, and a program that generate user support data based on the measurement data acquired from the measuring device 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 at a predetermined cycle and generates biometric data and user support data from the measured data. Therefore, information related to the rehabilitation operation of the user according to the comparison result between the biometric data generation unit that executes a predetermined calculation on the measurement data and generates at least the exercise information and the exercise information and the reference exercise information. It is provided with a user support data generation unit that generates user support data including the above.

The server in one aspect of the present disclosure is a server that receives measurement data from a measurement device worn by a user via a network at a predetermined cycle and generates biometric data and user support data from the measurement data. User support including information related to the user's rehabilitation operation according to the comparison result between the biometric data generator that executes a predetermined calculation on the measured data and generates at least the exercise information and the exercise information and the reference exercise information. It includes a user support data generation unit that generates data.

The information processing method according to one aspect of the present disclosure is an information processing method in which measurement data is received from a measuring device worn by a user via a network at a predetermined cycle, and biometric data and user support data are generated from the measured data. Therefore, the biological data generation unit executes a predetermined calculation on the measurement data to generate at least exercise information, and the user support data generation unit responds to the comparison result between the exercise information and the reference exercise information. A step of generating user assistance data including information related to the user's rehabilitation operation is included.

Further, the program according to one aspect of the present disclosure is an information processing method that receives measurement data from a measurement device worn by a user via a network at a predetermined cycle and generates biometric data and user support data from the measurement data. The information processing method is a program to be executed by a computer, in which the biometric data generation unit executes a predetermined calculation on the measurement data to generate at least exercise information, and the user support data generation unit. A step of generating user support data including information related to the user's rehabilitation movement according to the result of comparison between the exercise information and the reference exercise information is included.

According to the present disclosure, the information processing system according to the present embodiment generates user support data including advice and alerts for improving rehabilitation based on the measurement data via the user support data generation unit. As a result, for example, the user can easily obtain an improvement instruction for carrying out appropriate rehabilitation, and the convenience of the user is improved. It also improves rehabilitation adherence.

It is a 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. It is a block diagram which illustrated the function of the storage part 120 and the control part 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. It is a flowchart which shows the example of the processing of the information processing system 1 of FIG.

The contents of the embodiments of the present invention will be described in a list. 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 at a predetermined cycle and generates biometric data and user support data from the measurement data.
A biological data generation unit that executes a predetermined calculation on the measurement data and generates at least exercise information.
It is provided with a user support data generation unit that generates user support data including information related to the user's rehabilitation operation according to the comparison result between the movement information and the reference movement information.
An information processing system characterized by this.
[Item 2]
The information related to the rehabilitation operation is an alert notification regarding the rehabilitation operation of the user.
The information processing system according to item 1, wherein the information processing system is characterized by the above.
[Item 3]
The information related to the rehabilitation operation is an advice notification regarding the rehabilitation operation of the user.
The information processing system according to item 1, wherein the information processing system is characterized by the above.
[Item 4]
The information related to the rehabilitation operation is a notification indicating that the rehabilitation operation of the user deviates from the reference operation.
The information processing system according to item 1, wherein the information processing system is characterized by the above.
[Item 5]
Information related to the rehabilitation operation is transmitted to a user terminal of another user different from the user.
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 other different users include at least one of a clinical therapist, an occupational therapist, and a sports trainer.
Item 5. The information processing system according to Item 5.
[Item 7]
The user support data includes evaluation information regarding rehabilitation operation for each user account.
The information processing system according to item 1 to item 6, wherein the information processing system is characterized by the above.
[Item 8]
Generate or select a rehabilitation item or rehabilitation menu according to the comparison result.
The information processing system according to item 1 to item 7, wherein the information processing system is characterized by the above.
[Item 9]
The biological data generation unit generates at least one of blood pressure information, heart rate information, blood oxygen concentration, blood oxygen amount information, maximum oxygen uptake information, respiratory rate, and body temperature information.
The user support data generation unit rehabilitates when an abnormal value is detected in at least one of blood pressure information, heart rate information, blood oxygen concentration, blood oxygen amount information, maximum oxygen uptake information, respiratory rate, and body temperature information. Edit an item or rehabilitation menu,
The information processing system according to item 1 to item 8, wherein the information processing system is characterized by the above.
[Item 10]
A server that receives measurement data from a measurement device worn by a user via a network at a predetermined cycle and generates biometric data and user support data from the measurement data.
A biological data generation unit that executes a predetermined calculation on the measurement data and generates at least exercise information.
It is provided with a user support data generation unit that generates user support data including information related to the user's rehabilitation operation according to the comparison result between the movement information and the reference movement information.
A server characterized by that.
[Item 11]
It is an information processing method that receives measurement data from a measurement device worn by a user via a network at a predetermined cycle and generates biometric data and user support data from the measurement data.
A step of executing a predetermined calculation on the measurement data by the biological data generation unit to generate at least exercise information, and
The user support data generation unit includes a step of generating user support data including information related to the user's rehabilitation operation according to the comparison result between the exercise information and the reference exercise information.
An information processing method characterized by the fact that.
[Item 12]
A program that causes a computer to execute an information processing method that receives measurement data from a measurement device worn by a user via a network at a predetermined cycle and generates biometric data and user support data from the measurement data.
The information processing method is
A step of executing a predetermined calculation on the measurement data by the biological data generation unit to generate at least exercise information, and
The user support data generation unit includes a step of generating user support data including information related to the user's rehabilitation operation according to the comparison result between the exercise information and the reference exercise information.
A program characterized by that.

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, user's measurement data from the measurement device 300 via the network NW at a predetermined periodic timing on the management server 100, and performs a predetermined calculation on the measurement data. Is a system that generates biometric data and generates user support data based on the biometric data.

The information processing system 1 includes a management server 100, a user terminal device 200, a measuring device 300, and a network NW. The management server 100 and the user terminal device 200 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), a BLE (Bluetooth Low Energy), and the like.

The management server 100 is, for example, a device that receives user's measurement data from the measurement device 300 via the network via the user terminal device 200 at a predetermined periodic timing and calculates the measurement data into biometric data. Yes, for example, it is composed of a server device that provides various Web services.

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 to display a waveform graph or the like, or to display user support data (details will be described later) generated based on biometric data. User information such as a user's identification number, date of birth, gender, height, weight, stride, etc. is registered in the user terminal device 200 in advance, and user information including age calculated from the date of birth is measured data. It is transmitted to the management server 100 via the network NW in association with.

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, it may be configured by a device 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 pulse wave is generated by the change in the volume of blood vessels caused by the heartbeat of the user's heart due to the temporal change in the intensity of the light received by the photodiode. 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 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 mutation state of each of the orthogonal XYZ axes, and the user's movement is acquired as acceleration data, and for example, the measuring device 300 is attached to the user's wrist or arm. 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 acquires the user's motion as angular velocity data. For example, the measuring device 300 is attached to the user's wrist or arm. 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. Other examples include those that measure pulse waves from fingers using a camera lens such as a smartphone, those that measure heart rate, respiratory rate, pulse waves, heat, etc. in a non-contact manner using a Doppler sensor or camera, and metals. The heart rate and the like may be measured by a weak current flowing by holding the hand grip made of the product with both hands.

Between the user terminal device 200 and the measuring device 300, Bluetooth (registered trademark), Near Field radio Communication (NFC), Afero (registered trademark), Zigbee (registered trademark), Z-Wave (registered trademark) ), Or is connected using a wireless LAN or the like. A wired connection may be made instead of such a wireless connection. Further, the user terminal device 200 and the measuring device 300 may be integrated devices, for example, the measuring device 300 may be provided with a communication function by mounting a SIM, or a management server may be provided by BLE (Bluetooth Low Energy) or the like. It may be configured to be able to communicate directly with 100.

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.

<Management server 100>
FIG. 2 is a diagram showing a hardware configuration of the management server 100. FIG. 3 is a block diagram illustrating the functions of the storage unit 120 and the control unit 130. The illustrated configuration 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 each function in the control unit 130, input data, and the like, and is composed of a RAM (Random Access Memory), a ROM (Read Only Memory), and the like. NS. Further, as shown in FIG. 3, the storage unit 120 associates the measurement data DB 121 that stores the measurement data by the measuring device 300 with the user information and the biometric data calculated and generated from the measurement data with the user information. The biometric data DB 122 to be stored, the user support data DB 123 that stores the user support data generated based on the biometric data in association with the user information, and the user information DB 124 that stores 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 124 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. 3, the control unit 130 includes functional units such as a data management unit 131, a biological data generation unit 132, a user support data 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 in the user terminal device 200. Therefore, the data management unit 131 controls whether or not the user terminal device 200 and other terminal devices 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. 4 is a schematic diagram showing an example of tag information associated with the measurement data of FIG. The data D1 shown in FIG. 4 is the measurement data of the measuring device 300. The tag T1 is tag information associated with the data D1. 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. 4, "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.

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, by associating the tag information with the biometric data, it is possible to generate more accurate biometric data, and the user support generated based on the tag information can be generated. The data can also be more personalized.

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 therefore 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 biological data generation unit 132 performs a predetermined calculation on the measurement data stored in the measurement data DB 121 to generate the biological data. This biological 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, electrocardiographic information, respiratory rate, body temperature information, etc. Data such as step count information, stride length information, position information of the center of gravity, posture information, action type information, stress information, exercise amount information, exercise load information, movement distance information, movement speed information, activity amount information, movement information of hands or legs, etc. It 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.

In addition, for example, measurement data by a known learning device, biometric data generated based on the measurement data (for example, heartbeat information, blood pressure information, etc.) and positive biometric data (for example, heartbeat information based on a known medical device) A machine learning model is created in advance based on the teacher data associated with the correspondence with the blood pressure information (for example, information indicating the degree and range of the error may be included), and the biological data generation unit 132. May generate biometric data using the determination using the machine learning model as the above-mentioned predetermined calculation (analysis).

Here, a method of calculating the maximum blood pressure and the minimum blood pressure, which are biological data, from the measurement data will be illustrated. FIG. 5 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 of a user's electrocardiographic waveform measured by the measuring device 300 and stored in the storage unit 120. And the photoelectric volume pulse waveform, the velocity pulse waveform obtained by the application first-order differentiation of the photoelectric volume pulse waveform, and the acceleration pulse waveform obtained by second-order differentiation of the photoelectric volume pulse waveform with time are shown. FIG. 5 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.

An electrocardiographic waveform is a waveform that indicates a periodic change in an electrical signal that causes the beating of a human heart. 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 the heartbeat. The P wave represents atrial contraction, the Q wave R wave S wave represents the state of ventricular contraction, and the T wave represents the initiation 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 ejection of the left ventricle, the V wave is the Valley wave (wave due to 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 a first-order 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. 5, 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 late re-falling wave), e-wave (extended early positive wave), and 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. 5, 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 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 velocity PTT_DIA. This makes it possible to calculate the maximum blood pressure and the minimum blood pressure.

Further, exemplifying a method of calculating motion information of a hand or leg, which is biological data, from measurement data, for example, the measuring device 300 is mounted from acceleration data and angular velocity data measured by the measuring device 300 worn at the time of rehabilitation. It is possible to obtain motion information on how fast and at what angle the part (for example, wrist or ankle) is moving. Further, the current position information of the portion where the measuring device 300 is mounted may be calculated based on the above-mentioned measurement data (for example, acceleration data or angular velocity data) or operation information. At this time, instead of the accurate position, for example, a plurality of ranges may be provided in the height direction of the position information, and the current position information may indicate a rough position such as upper, middle, or lower.

Further, exemplifying a method of calculating walking information which is biological data from measurement data, for example, walking information can be obtained from waveform data of acceleration data measured by a measuring device 300 worn at the time of rehabilitation by a known calculation method or the like. Can be done.

In addition, a method of calculating walking speed information, which is biological data, from measurement data will be exemplified. For example, a known calculation method or the like from the waveform data of acceleration data measured by the measuring device 300 worn by the user on the wrist may be used alone or in combination (for example, averaging or weighting). The walking speed information can be obtained by, for example, the walking speed information is calculated by integrating the acceleration data at predetermined time intervals. In addition to this, the user terminal device 200 or the measuring device 300 is provided with a GPS function, and more accurate walking speed information is referred to by referring to the position information by GPS and the walking speed information calculated from the time information related to the position information. May be obtained. However, especially when it is indoors or underground or when the moving distance is relatively short (for example, within a few meters), the GPS accuracy generally decreases. Therefore, for example, the user operates the user terminal device 200 by GPS. It may be possible to select whether to use the information in combination (or to use it instead of the calculation by the acceleration sensor), the GPS reception sensitivity information in the user terminal device 200, and the distance calculated by the GPS or the acceleration sensor. You may choose whether to use the GPS information based on the information or the like.

In addition, a method of calculating stride information, which is biological data, from measurement data will be exemplified. For example, a known calculation method or the like from the waveform data of acceleration data measured by the measuring device 300 worn by the user on the wrist may be used alone or in combination (for example, averaging or weighting). Because the stride information can be obtained by, for example, when walking, the hand is waved like a pendulum, so that the information of the above-mentioned acceleration sensor (for example, the timing when the acceleration component in the traveling direction is the smallest or the timing when the acceleration component is switched in the opposite direction, or the progress Since the interval of one step (that is, pitch information) can be determined based on the timing when the acceleration component in the direction perpendicular to the direction is the smallest or the timing when the top and bottom are switched, the stride information can be obtained by using the time information. Can be done. Alternatively, for example, when the ground is kicked out, the acceleration component in the kicking direction is synthesized, so that it is also possible to determine the interval of one step at the timing of occurrence of the acceleration component in the direction.

Further, exemplifying a method of calculating activity amount information which is biological data from measurement data, for example, acceleration data measured by a measuring device 300 which is worn on a daily basis is frequency-analyzed. It is possible to obtain activity amount information by calculating according to a predetermined condition such as what percentage of the day the activity is associated with high and low and the activity of a predetermined frequency or more occupies.

Further, exemplifying a method of calculating momentum information which is biological data from measurement data, for example, exercise including walking is performed by a known calculation method or the like from acceleration data measured by a measuring device 300 which is worn on a daily basis. Since the acceleration data during the operation can be specified, the momentum information can be obtained by calculating under predetermined conditions using, for example, frequency analysis. Further, by further using additional information such as angular velocity information and tag information, it is possible to obtain more accurate momentum information.

Further, exemplifying a method of calculating exercise load amount information which is biological data from measurement data, for example, in the activity amount information and the exercise amount information derived from the acceleration data measured by the measuring device 300 which is worn on a daily basis. On the other hand, for example, exercise load information can be obtained by weighting with heartbeat information that increases with exercise load. Further, for example, if vector information of acceleration data is added, state information such as walking environment (hill, stairs, etc.) and posture (standing position, sitting position, etc.) can be specified, so that state information may be further used. Further, by further using additional information such as angular velocity information and tag information, it is possible to obtain more accurate exercise load information.

The user support data generation unit 133 includes exercise information (activity amount information, exercise amount information, exercise load amount information, etc.) including the above-mentioned movement information or the above-mentioned walking information (walking speed information, stride information, step count information, etc.) as biometric data of the user. Also included) and the reference motion information or reference walking information (reference movement information) as the reference biometric data stored in the biometric data DB 122, and the user including advice and alerts based on the difference with respect to the reference biometric data. Generate support data. The reference biometric data includes, for example, motion information or walking information, exercise information, and motion of a healthy person when a predetermined motion is performed on a part where the measuring device 300 is attached as rehabilitation by a physical therapist or an occupational therapist. Information, walking information, and exercise information, which are stored in the biometric data DB 122 in advance. Further, the user support data includes, for example, motion information when a predetermined motion is performed on a portion where the measuring device 300 is attached as rehabilitation performed by the user at home, walking information at the time of rehabilitation, and exercise information. , Detects the difference in movement from the reference biometric data, and notifies an alert when there is a large difference from the reference biometric data in the movement speed and angle of the wearing part, walking, stride, and movement (for example, moving too fast). , Includes moving in the wrong direction, simply indicating that it is misaligned, etc., or includes advice notifications indicating the degree of the difference (for example, which direction should be moved more). It is associated with the user information and stored in the user support data DB 123. Further, as an alert notification, for example, when the user terminal device 200 or the measuring device 300 is equipped with a vibration device or a light emitting device, the device is operated (for example, vibration and / or issuance) at the time of rehabilitation. It is possible to intuitively know the operation error. In the above, support during rehabilitation at home is assumed, but it is not limited to this, and user support data is transmitted to other user terminal devices (physiotherapist terminal, occupational therapist terminal, sports trainer terminal, etc.). By doing so, it is also useful for inexperienced physiotherapists or occupational therapists to refer to this when performing user rehabilitation and use it as auxiliary information, and it is not a sports trainer or physiotherapist, but it is constant. Rehabilitation guidance can be given to patients while referring to user support data even when sending to a terminal of a knowledgeable person. For example, there is a shortage of human resources in specialists such as physiotherapists (especially in non-urban areas). (Problem in) can also be solved. It can also be used for training purposes in medical schools. When used for training purposes, the evaluation obtained by scoring the above differences for each user account (for each student user account) may be used as user support data. For the evaluation, it is preferable to store the correspondence between the difference and the evaluation in the user support data DB 123 in advance.

The rehabilitation may be performed based on the instruction from the physiotherapist or the like as described above, but the rehabilitation menu may be transmitted from the management server 100 to the user terminal 200 as user support data. The rehabilitation menu is scored based on the answers to the preliminary questionnaire data, and based on the score, rehabilitation items may be combined and generated, or may be selected from a plurality of pre-stored rehabilitation menus, or the above biometric data. Based on the comparison result between the standard biometric data and the reference biometric data, the movements with a large difference or the movements with a small difference can be determined, and the optimal rehabilitation items are combined to generate a rehabilitation menu, or multiple rehabilitations stored in advance. It may be selected from the menu.

The user support data generation unit 133 generates, for example, the user's blood pressure transition data based on the blood pressure information generated from the measurement data by the measuring device 300 worn at the time of rehabilitation. Then, for example, abnormal values such as sudden rise and fall of blood pressure are monitored by calculating the slope of blood pressure transition data and comparing with reference blood pressure information (including past blood pressure information such as a predetermined day before), and the abnormal value occurs. If so, generate user assistance data including alert notifications. The user support data generation unit 133 may also generate blood pressure transition data before and after the abnormal value as the user support data in addition to the alert. Further, when the abnormality is detected, the control unit 130 directly from the management server 100 or indirectly via the user terminal device 200 or the measuring device 300, a medical institution or a close relative, a physiotherapist, Notifications indicating abnormalities to contacts linked to user information such as occupational therapists and sports trainers (for example, notifications via a predetermined application stored in a device such as a PC or smartphone, notifications using an email address, etc. ) May be transmitted. This makes it possible to detect blood pressure abnormalities at an early stage during rehabilitation, and it is possible to automatically notify others of blood pressure abnormalities even if the user cannot be contacted due to a sudden onset. Further, the rehabilitation menu may be changed (including the change and deletion of the rehabilitation item in the rehabilitation menu) according to the detection of the abnormal value. In addition to blood pressure information, biological data such as heart rate information, blood oxygen amount information, maximum oxygen uptake information, respiratory rate, and body temperature information may be used.

The data output unit 134 outputs biological data and user support data to the user terminal device 200. In the user terminal device 200, the output data may be displayed on the screen via, for example, a dedicated application so that the user can easily check the output 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 data support method executed by the information processing system 1 will be described with reference to FIG. FIG. 6 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 124 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 biometric data generation unit 132, and the biometric 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 user support data generation unit 133, and the user support data is generated by a predetermined calculation or the like. The generated user support data is stored in the user support data DB 123 by the data management unit 131.

As the process of step S105, the biometric data and / or the user support data is read by the data output unit 134 and output to the user terminal device 200.

<Effect>
As described above, the information processing system according to the present embodiment generates user support data including advice and alerts for improving rehabilitation based on the measurement data via the user support data generation unit 133. As a result, for example, the user can easily obtain an improvement instruction for carrying out appropriate rehabilitation, and the convenience of the user is improved.

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 modifications, as well as those omitted, replaced and modified, are included in the technical scope of the claims and the equivalent scope thereof.

1 Information processing system 100 Management server 200 User terminal equipment 300 Measuring equipment NW network

Claims (7)

An information processing system that receives measurement data from a measurement device worn by a user via a network at a predetermined cycle and generates biometric data and a predetermined notification from the measurement data.
A biological data generation unit that executes a predetermined calculation on the measurement data and generates at least exercise information.
A user support data generation unit that corrects the user's rehabilitation behavior based on the degree of difference between the exercise information and the reference exercise information or generates a notification regarding the difference is provided.
The notification is transmitted to a user terminal of another user different from the user as auxiliary information when the other user performs rehabilitation of the user.
The measurement data is data measured by the measuring device attached to only one body part.
An information processing system characterized by this. The other different users include at least one of a clinical therapist, an occupational therapist, and a sports trainer.
The information processing system according to claim 1. Generate or select a rehabilitation item or rehabilitation menu according to the comparison result.
The information processing system according to claim 1 or 2. The biological data generation unit generates at least one of blood pressure information, heart rate information, blood oxygen concentration, blood oxygen amount information, maximum oxygen uptake information, respiratory rate, and body temperature information.
The user support data generation unit rehabilitates when an abnormal value is detected in at least one of blood pressure information, heart rate information, blood oxygen concentration, blood oxygen amount information, maximum oxygen uptake information, respiratory rate, and body temperature information. Edit an item or rehabilitation menu,
The information processing system according to any one of claims 1 to 3, wherein the information processing system is characterized by the above. A server that receives measurement data from a measurement device worn by a user via a network at a predetermined cycle and generates biometric data and a predetermined notification from the measurement data.
A biological data generation unit that executes a predetermined calculation on the measurement data and generates at least exercise information.
A user support data generation unit that corrects the user's rehabilitation behavior based on the degree of difference between the exercise information and the reference exercise information or generates a notification regarding the difference is provided.
The notification is transmitted to a user terminal of another user different from the user as auxiliary information when the other user performs rehabilitation of the user.
The measurement data is data measured by the measuring device attached to only one body part.
A server that features that. It is an information processing method that receives measurement data from a measuring device worn by a user via a network at a predetermined cycle and generates biometric data and a predetermined notification from the measured data.
A step of executing a predetermined calculation on the measurement data by the biological data generation unit to generate at least exercise information, and a step of generating at least exercise information.
The user support data generation unit includes a step of modifying the user's rehabilitation behavior based on the degree of difference between the exercise information and the reference exercise information or generating a notification regarding the difference, depending on the comparison result.
The notification is transmitted to a user terminal of another user different from the user as auxiliary information when the other user performs rehabilitation of the user.
The measurement data is data measured by the measuring device attached to only one body part.
An information processing method characterized by the fact that. A program that causes a computer to execute an information processing method that receives measurement data from a measurement device worn by a user via a network at a predetermined cycle and generates biometric data and a predetermined notification from the measurement data.
The information processing method is
A step of executing a predetermined calculation on the measurement data by the biological data generation unit to generate at least exercise information, and a step of generating at least exercise information.
The user support data generation unit includes a step of modifying the user's rehabilitation behavior based on the degree of difference between the exercise information and the reference exercise information or generating a notification regarding the difference, depending on the comparison result.
The notification is transmitted to a user terminal of another user different from the user as auxiliary information when the other user performs rehabilitation of the user.
The measurement data is data measured by the measuring device attached to only one body part.
A program characterized by that.

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