JP2016047110A - Abnormality prediction device, abnormality prediction system, and abnormality prediction method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an abnormality prediction device, an abnormality prediction system, and an abnormality prediction method which can output a possibility of occurrence of an abnormality to a user.SOLUTION: An abnormality prediction device comprises: a detection unit 22 for detecting detection information including at least either biological information on a user or body motion information on a body motion of the user; a precursory symptom determination unit (a control unit 27A) for determining whether or not a precursory symptom has occurred to the user on the basis of the detection information detected by the detection unit 22 and a precursory pattern, which is a pattern of the detection information corresponding to a precursory symptom of an abnormality occurring to the user; and an information output unit (the control unit 27A) for outputting notification information indicating that the occurrence of the abnormality to the user is predicted when the precursory symptom determination unit determines that the precursory symptom has occurred.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an abnormality prediction apparatus, an abnormality prediction system, and an abnormality prediction method.

2. Description of the Related Art Conventionally, a portable body abnormality notification device that detects a user's biological information and position information and notifies the user or the like when the body of the user is in an abnormal state is known (for example, Patent Documents). 1).
In the portable body abnormality notification device described in Patent Document 1, various biological information measurement sensors that detect and measure a user's blood pressure, pulse, and body temperature, and a GPS (Global Positioning System) that detects the position information of the user. ) Receiver. And when the said physical abnormality notification apparatus comes to the measurement timing for every fixed period, it measures a positional information and each biological information, and each measured biological information is made into a reference value (normal state value), a caution state value, and an emergency state. Compare with each value. If it is determined that the user is in an abnormal state based on the comparison result, a warning message or the like is displayed on the display screen in a blinking manner, and a buzzer is sounded to issue an alarm.

When a response is made to the alarm by operating a button or the like, the body abnormality alarm device displays a message asking whether or not to contact on the display surface, and an instruction to contact is given. The personal identification information of the user and the measured biological information and position information are automatically reported to the home by the telephone function unit.
On the other hand, when there is no response to the alarm, information indicating emergency, personal identification information, position information, measurement biometric information, and past information thereof are automatically reported to the ambulance fire department.
With such a portable body abnormality notification device, it is possible to quickly cope with a user's abnormality.

JP-A-11-206721

  However, in the portable body abnormality notification device described in Patent Document 1, an alarm is notified when the user enters an abnormal state, and therefore the user is in a state in which an abnormality is predicted to occur. Cannot notify. For this reason, if the user is notified before the abnormality occurs, precautions such as risk avoidance for the abnormality can be taken, but the user is notified after the abnormality occurs. There is a problem that it is difficult to take.

  An object of the present invention is to solve at least a part of the above-described problems, and provides an abnormality prediction apparatus, an abnormality prediction system, and an abnormality prediction method that can output that there is a possibility that an abnormality may occur in a user. One of the purposes is to provide it.

  An abnormality prediction apparatus according to a first aspect of the present invention includes a detection unit that detects detection information including at least one of a user's biological information and body motion information related to the user's body motion, and the detection unit. Based on the detection information being detected and a precursor pattern that is a pattern of the detection information corresponding to a precursor symptom of an abnormality occurring in the user, it is determined whether or not the precursor symptom has occurred in the user. A precursor symptom determining unit for determining, and an information output unit for outputting notification information indicating that the occurrence of an abnormality is predicted for the user when the precursor symptom determining unit determines that the precursor symptom has occurred. It is characterized by providing.

Examples of abnormalities occurring in the user include fainting, epilepsy and convulsions, and those that suddenly develop due to other diseases and are accompanied by at least one of consciousness disorder and movement disorder.
According to the first aspect, whether the precursor symptom has occurred based on the detection information detected by the detection unit and the precursor pattern that is a pattern corresponding to the abnormal precursor symptom (a specific pattern of detection information). It is determined whether or not. And if it determines with the said progenitor symptom having generate | occur | producing, the said alerting | reporting information will be output. According to this, the notification information indicating that the occurrence of the abnormality is predicted can be output to the user at a stage before the occurrence of the abnormality. Therefore, by notifying the notification information by the abnormality prediction device or the external device that receives the notification information, the user or the user's family or medical staff can be notified that the occurrence of the abnormality is predicted. it can. And the said alerting | reporting information is alert | reported to a user, The said user can take prior countermeasures, such as an avoidance action of the danger accompanying abnormality generation | occurrence | production.

In the first aspect, it is preferable to have a notification unit that notifies the user of the notification information input from the information output unit.
According to the first aspect, since the abnormality prediction apparatus has the notification unit that notifies the user of the notification information, when the occurrence of an abnormality is predicted, it can be notified to the user with certainty. Therefore, the user can surely take the above precautions.

In the first aspect, the precursor pattern storage unit that stores the precursor pattern, and when the abnormality occurs in the user, based on the detection information detected before the occurrence timing of the abnormality, the precursor pattern It is preferable to have a precursor pattern update unit that updates the precursor pattern stored in the storage unit.
According to the first aspect, the precursor pattern that is an index as to whether or not an abnormal precursor symptom has occurred in the user is based on detection information detected before the occurrence timing of the abnormality that has occurred in the user, It is updated by the precursor pattern update unit. According to this, the said precursor pattern can be updated based on the detection information actually detected from the user. Therefore, it can be determined more accurately whether or not abnormal prodromal symptoms have occurred in the user.

In the first aspect, the apparatus includes an abnormality determination unit that determines whether or not an abnormality has occurred in the user. When the abnormality determination unit determines that an abnormality has occurred, the precursor pattern update unit It is preferable to update the pattern.
Here, when it is determined by the abnormality determination unit that an abnormality has occurred, there is a high possibility that a precursor symptom of the abnormality has occurred. For this reason, when it is determined that an abnormality has occurred by the abnormality determination unit, the precursor pattern update unit updates the precursor pattern, so that it is easy to extract the precursor pattern corresponding to the precursor symptom from the detection information. it can. Therefore, an appropriate pattern corresponding to the precursor symptom can be automatically retained as the precursor pattern.

In the first aspect, the operation unit receives an input operation of the user, and the precursor pattern update unit receives the operation signal indicating that the abnormality has occurred from the operation unit. Is preferably updated.
According to the first aspect, when an operation signal corresponding to a user's input operation indicating that an abnormality has occurred is input, the precursor pattern update unit updates the precursor pattern. According to this, even when the abnormality prediction device does not have the abnormality determination unit, it is possible to reliably grasp that an abnormality has occurred in the user. Accordingly, since the precursor pattern can be updated based on the detection information actually detected before the operation signal is input, a more appropriate precursor pattern can be held.

In the first aspect, the operation unit is configured to be able to input one of an elapsed time after the occurrence of the abnormality and an occurrence time of the abnormality, and the precursor pattern update unit is configured to perform the operation. It is preferable that the precursor pattern is updated based on the detection information detected before any of the elapsed time input to the unit and the generation time.
Here, when the occurrence time of the abnormality is unknown, the extraction range of the precursor pattern from the detection information detected in the past becomes wide, and it becomes difficult to extract the precursor pattern, and the extraction time tends to be long. On the other hand, if the time of occurrence of the abnormality can be grasped, the extraction range of the precursor pattern can be narrowed, and the extraction time can be easily shortened in addition to the extraction of the precursor pattern.
For this reason, in the first aspect, the precursor pattern update unit updates the precursor pattern based on detection information detected before any of the occurrence time of the abnormality and the input elapsed time is calculated. . According to this, the extraction range can be narrowed compared to the case where the occurrence time of the abnormality is unknown. Therefore, the extraction of the precursor pattern corresponding to the precursor symptom can be performed more accurately in a relatively short time, and can be updated to an appropriate precursor pattern.

In the first aspect, the precursor symptom determination unit has a pattern based on the detection information detected by the detection unit in a state where the abnormality has not occurred in the user. Among the precursor pattern and the normal pattern which is the pattern of the detection information according to the state where the abnormality has not occurred in the user, when the precursor symptom is similar to the precursor pattern, the precursor symptom is given to the user It is preferable to determine that the precursor symptom has not occurred in the user when it is determined that the pattern has occurred and the pattern is similar to the normal pattern.
Here, when determining whether or not a precursor symptom has occurred by matching the pattern based on the detection information and the precursor pattern, if these patterns do not substantially match, the precursor symptom has occurred but the precursor symptom has occurred. May not be determined to have occurred.
In contrast, in the first aspect, when the precursor symptom determination unit determines whether the pattern based on the detection information is similar to the precursor pattern or the normal pattern, and determines that the precursor symptom is similar to the precursor pattern, the precursor symptom is It is determined that it has occurred. According to this, even when the pattern based on the detection information and the precursor pattern do not substantially match, it can be determined that the precursor symptom has occurred if the pattern is more similar to the precursor pattern than the normal time pattern. Therefore, it is possible to reliably detect and grasp the occurrence of the precursor symptoms.

In the first aspect, a normal pattern storage unit that stores the normal pattern, an abnormality determination unit that determines whether or not the abnormality has occurred in the user, and an abnormality has occurred in the user by the abnormality determination unit. A period determining unit that determines whether or not a period determined to have passed a predetermined period, and when the period determining unit determines that the predetermined period has elapsed, the period between the predetermined period It is preferable to have a normal-time pattern update unit that updates the normal-time pattern based on the detection information detected by the detection unit.
According to the first aspect, the normal time pattern update unit updates the normal time pattern stored in the normal time pattern storage unit based on the actually detected detection information. According to this, it can update to the normal time pattern according to a user's state and action. Therefore, it is possible to more accurately determine the occurrence of the precursor symptoms.

Here, in the daily life of the user, the abnormality does not frequently occur depending on the type of abnormality (for example, seizure). On the other hand, in the daily life of the user, the information detected by the detection unit varies depending on the type of action, so the normal pattern needs to be an average pattern over a relatively long period.
On the other hand, the normal pattern updating unit detects during the predetermined period when the period determining unit determines that the period in which the abnormality determining unit has determined that no abnormality has occurred has passed the predetermined period. The normal pattern is updated based on the detected information. According to this, since it can suppress that the process which updates a normal time pattern occurs frequently, the power consumption of an abnormality prediction apparatus can be reduced. In addition, since the normal pattern can be an average pattern over a relatively long period, the normal pattern used in the determination of the occurrence of prodromal symptoms is updated to a pattern having a relatively large fluctuation range of detection information. This can be suppressed. Therefore, it is possible to more appropriately determine the occurrence of precursor symptoms.

In the first aspect, it is preferable that the information output unit outputs information indicating that the abnormality has occurred when it is determined that the abnormality has occurred in the user.
According to the first aspect, not only when it is determined that an abnormal precursor symptom has occurred, but also when it is determined that an abnormality has occurred, information to that effect is output. For this reason, the abnormality predicting device or the external device notifies the information so that, for example, the user, the person near the user, the family of the user, and the medical staff The occurrence can be notified.

In the first aspect, the detection unit detects a biological information detection unit that detects a pulse wave of the user as the biological information, and an acceleration that changes with the body movement of the user as the body movement information. It is preferable to have at least one of the body motion information detection unit.
Here, for example, when a seizure such as fainting occurs as an abnormality, a pulse wave and a change in body movement that are different from the normal time occur.
Therefore, in the first aspect, the detection unit includes at least one of a biological information detection unit that detects a pulse wave and a body motion information detection unit that detects acceleration that changes in accordance with the body motion of the user. By having it, it is possible to appropriately determine the occurrence of abnormalities and precursor symptoms.

An abnormality prediction system according to a second aspect of the present invention comprises: a detection device that detects detection information related to a user; and an information processing device that processes detection information detected by the detection device, wherein the detection An apparatus includes: a detection unit that detects detection information including at least one of the user's biological information and body movement information related to the user's body movement; and detection information that transmits the detection information to the information processing apparatus. A transmission unit, and a notification unit that notifies the user of information received from the information processing device, wherein the information processing device receives the detection information received from the detection device, and the user A precursor symptom determination unit that determines whether or not the precursor symptom has occurred in the user based on a precursor pattern that is a pattern of the detection information corresponding to a precursor symptom of an abnormality occurring in the patient; and the precursor symptom determination unit According When the prodrome is determined to have occurred Te, characterized in that it comprises, a broadcast information transmitting unit that transmits broadcast information to the effect that occurrence of abnormality in said user is foreseen in the detector.
According to the said 2nd aspect, there can exist an effect similar to the abnormality prediction apparatus which concerns on the said 1st aspect.

An abnormality prediction method according to a third aspect of the present invention is an abnormality prediction method performed using a detection device that detects a user's condition, and is related to the user's biological information and the user's body movements. Detection information including at least one of body movement information is detected, and based on the detected information that is detected and a precursor pattern that is a pattern of the detection information according to an abnormal precursor symptom that occurs in the user Determining whether or not the prodromal symptoms have occurred to the user, and if it is determined that the prodromal symptoms have occurred, outputting notification information to the user that an abnormality is predicted to occur. Features.
According to the said 3rd aspect, the effect similar to the abnormality prediction apparatus which concerns on the said 1st aspect can be show | played by performing the said abnormality prediction method using a detection apparatus.

1 is a block diagram showing a configuration of a biological information measurement system according to a first embodiment of the present invention. The block diagram which shows the structure of the control part of the biometric information detection apparatus in the said 1st Embodiment. The flowchart which shows the update process in the said 1st Embodiment. The flowchart which shows the prediction determination process in the said 1st Embodiment. The block diagram which shows the structure of the biometric information measurement system which concerns on 2nd Embodiment of this invention. The block diagram which shows the structure of the control part of the biometric information detection apparatus in the said 2nd Embodiment. The block diagram which shows the structure of the information processing apparatus in the said 2nd Embodiment. The block diagram which shows the structure of the control part of the information processing apparatus in the said 2nd Embodiment.

[First Embodiment]
Hereinafter, a first embodiment of the present invention will be described based on the drawings.
[Overall configuration of biological information measurement system]
FIG. 1 is a block diagram showing a configuration of a biological information measurement system 1A according to the present embodiment.
A biological information measurement system 1A according to the present embodiment corresponds to the abnormality prediction system of the present invention, and is a biological information detection device (hereinafter sometimes abbreviated as a detection device) 2A and information processing that can communicate with the detection device 2A. And a device 9A.
In this biological information measurement system 1A, the detection device 2A detects the biological information and operation information of the user wearing the detection device 2A, and based on these information, it is determined that an abnormal precursor has occurred in the user. Then, a warning is notified to the user.
The information processing apparatus 9A has a function of acquiring various types of information detected by the detection apparatus 2A and uploading the information and the analysis result of the information to a server on the network. Examples of the information processing apparatus 9A include a PC (Personal Computer), a smartphone (multifunctional mobile phone), a tablet, and the like that can execute a biological information analysis program.

  Here, in the biological information measurement system 1A, the detection device 2A has at least any of seizures such as fainting, epilepsy, convulsions, etc., and sudden onset due to other diseases as abnormalities occurring in the user. Detects seizures with or without. For this reason, the nap considered to be included in sleep is not included in the abnormality which generate | occur | produces in a user in this embodiment.

[Configuration of biological information detection apparatus]
Hereinafter, the configuration and operation of the detection apparatus 2A will be described.
The detection device 2A corresponds to the abnormality prediction device of the present invention, and is a wearable device that is worn and used by a user. As described above, the detection device 2A detects biological information and body movement information of the user who wears it, and also notifies a warning when it is determined that an abnormal precursor symptom has occurred.
As shown in FIG. 1, the detection device 2A includes an operation unit 21, a detection unit 22, a notification unit 23, a communication unit 24, a storage unit 25A, an analysis unit 26, and a control unit, which are connected to each other via a bus line BL. 27A. In addition, although not shown in FIG. 1, the detection device 2 </ b> A includes a battery that supplies power to the components.

[Configuration of operation unit]
The operation unit 21 has a plurality of buttons that are exposed in a case constituting the exterior of the detection device 2A, and outputs an operation signal corresponding to the input (pressed) button to the control unit 27A. For example, when an input operation corresponding to the occurrence of a seizure is performed by the user, the operation unit 21 outputs a seizure occurrence signal that is an operation signal indicating the occurrence of the seizure to the control unit 27A. The operation unit 21 is configured to be able to input an occurrence time of the seizure or an elapsed time since the occurrence of the seizure, and when the occurrence time or the elapsed time is input, the operation unit 21 indicates the occurrence time or the elapsed time. The operation signal is output to the control unit 27A. Note that the operation unit 21 is not limited to a configuration having buttons, and detects a touch panel arranged on a display unit 231 that configures a notification unit 23 to be described later, or a user's tap operation, and responds to the tap operation. The configuration may be such that the operation signal is output to the control unit 27A.

[Configuration of detector]
The detection unit 22 includes a biological information detection unit 221 that detects the biological information of the user and a body movement information detection unit 222 that detects the body movement information of the user under the control of the control unit 27A.
The biological information detection unit 221 detects the user's biological information as a signal, and outputs the detected signal to the analysis unit 26. The biological information detection unit 221 includes a pulse wave sensor that detects a user's pulse wave, an electroencephalogram sensor that detects an electroencephalogram, an electrocardiogram sensor that detects electrocardiogram, and a temperature sensor that detects body temperature.
Among these, the pulse wave sensor can be composed of a photoelectric sensor including a light emitting element such as an LED (Light Emitting Diode) and a light receiving element such as a photodiode.
Further, the electroencephalogram sensor can be constituted by, for example, a headset-type sensor worn on the user's head. In this case, the detected electroencephalogram may be output wirelessly or by wire, and output from the detection unit 22 to the analysis unit 26.

  The body motion information detection unit 222 detects the body motion information of the user. The body motion information detection unit 222 includes an acceleration sensor that detects, as the body motion information, acceleration that changes with the user's body motion, and outputs an acceleration signal indicating the detected acceleration to the control unit 27A. Such an acceleration sensor can be exemplified by a three-axis sensor that detects acceleration in each of the X, Y, and Z axes. The acceleration signal that is the detection result of the acceleration sensor can also be used for processing to reduce noise caused by body motion superimposed on the pulse wave signal detected by the pulse wave sensor.

[Configuration of notification unit]
The notification unit 23 notifies the user of various information under the control of the control unit 27A. The notification unit 23 includes a display unit 231, an audio output unit 232, and a vibration unit 233.
The display unit 231 includes various display panels such as a liquid crystal display, a plurality of LEDs, and the like, and displays contents according to notification information input from the control unit 27A. For example, the display unit 231 displays biological information and motion information detected by the detection unit 22 and analyzed by the analysis unit 26. In addition, the display unit 231 displays a message indicating that there is a high possibility that an abnormality will occur in a short time in the future when it is determined in the prediction determination process described later that an abnormal precursor symptom has occurred in the user. To do.

The audio output unit 232 includes audio output means such as a speaker, and outputs audio corresponding to audio information input from the control unit 27A. For example, the voice output unit 232 outputs a warning sound when it is determined in the prediction determination process described later that an abnormal precursor symptom has appeared to the user.
The vibration unit 233 includes a motor whose operation is controlled by the control unit 27A, and notifies the user of, for example, a warning by vibration generated by driving the motor.

[Configuration of communication section]
The communication unit 24 includes a communication module that can communicate with an external device such as the information processing apparatus 9A. For example, the communication unit 24 transmits information stored in the storage unit 25A to the external device in response to a request signal received from the external device. In the present embodiment, the communication unit 24 communicates with an external device wirelessly, but may communicate with the external device via a relay device such as a cradle, or the detection device 2A and the external device may connect a cable. When connecting via an external device, communication with an external device may be performed via the cable.

[Configuration of storage unit]
The storage unit 25A is configured by a storage device having a flash memory or the like, and includes an operation information storage unit 251, a detection information storage unit 252, and a pattern storage unit 253.
The operation information storage unit 251 stores operation information such as various programs and data necessary for the operation of the detection apparatus 2A. As such operation information, the operation information storage unit 251 performs control programs for controlling the operation of the detection device 2A, update processes included in an abnormality prediction process described later, and prediction determination processes, independently. I remember the program.
The detection information storage unit 252 stores detection information including biological information and body movement information detected by the detection unit 22 and an analysis result by the analysis unit 26 described later. The detection information storage unit 252 is configured to sequentially store the detection information, and when the storage capacity is insufficient, overwrite the information stored first with newly acquired information.

The pattern storage unit 253 corresponds to the precursor pattern storage unit and the normal time pattern storage unit of the present invention. The pattern storage unit 253 stores a state identification pattern including a seizure pattern, a precursor pattern, and a normal pattern used in an abnormality prediction process described later. These state identification patterns include time-dependent change patterns of signal waveforms of biological information and motion information detected by the detection unit 22, time-dependent change patterns of parameters obtained by analyzing the information, and time-dependent change patterns. The appearance pattern (including the case where the same information or different information appears with a time difference) is included.
Among such state identification patterns, the seizure pattern is a pattern when a seizure occurs in the user, and the precursor pattern is a pattern when a prodrome of the seizure occurs. Moreover, a normal time pattern is a pattern in case a seizure and the precursor symptom of the said seizure have not generate | occur | produced in the user. These state identification patterns are updated as needed by the control unit 27A described later.

[Configuration of analysis unit]
The analysis unit 26 has a signal processing circuit such as a DSP (Digital Signal Processor), and analyzes various information detected as a signal by the detection unit 22 to calculate various parameters.
For example, the analysis unit 26 calculates a pulse rate per unit time, an estimated blood flow rate, and a pulse fluctuation amount based on the pulse wave signal detected by the pulse wave sensor, and also performs a spectrum on the pulse wave signal. Analysis is performed to obtain an LF (Low Frequency) / HF (High Frequency) value as an index representing a balance between sympathetic nerve activity and parasympathetic nerve activity.
HF has a period of about 3 to 4 seconds, and indicates a fluctuation wave using respiration as a signal source or a total amount of power spectrum in the frequency domain. On the other hand, LF indicates a fluctuating wave called a Mayer wave that uses a blood pressure change with a period of about 10 seconds as a signal source, or a total amount of a power spectrum in the frequency domain.

The analysis unit 26 performs frequency analysis of the electroencephalogram signal detected by the electroencephalogram sensor. Further, the analysis unit 26 calculates the heart contraction interval and the number of extra systoles per unit time based on the electrocardiographic signal detected by the electrocardiographic sensor, and based on the detection result by the temperature sensor, Calculate the temperature of the user. In addition, based on the acceleration signal detected by the body motion information detection unit 222, the analysis unit 26 calculates the user's exercise amount and exercise spectrum per unit time.
Such analysis by the analysis unit 26 is performed at a predetermined cycle, and analysis of biological information and body motion information detected during the cycle is executed. And the analysis result by the said analysis part 26, ie, the calculated various parameters, the said biological information and body movement information, and the said detection information as detection information with the detection time of the signal used for calculation of the said various parameters. It is stored in the storage unit 252.
Note that the parameters calculated by the analysis unit 26 are not limited to the above parameters. That is, the analysis unit 26 may calculate other parameters instead of the parameters or in addition to the parameters.

[Configuration of control unit]
FIG. 2 is a block diagram showing a configuration of the control unit 27A.
The control unit 27A includes a processing circuit such as a CPU (Central Processing Unit) and controls the operation of the detection device 2A autonomously or in response to an operation signal input from the operation unit 21. For example, the control unit 27A executes an abnormality prediction process to be described later, updates the state identification pattern based on the analysis result by the analysis unit 26, and determines that a precursor symptom of the seizure has occurred. When it is determined that it has occurred, a warning is notified.
In order to execute such processing, the control unit 27A performs detection control as a functional unit realized by executing the program stored in the operation information storage unit 251 by the processing circuit as illustrated in FIG. Unit 271, notification control unit 272, communication control unit 273, timing unit 274, information acquisition unit 275, signal determination unit 276, timing determination unit 277, seizure determination unit 278, period determination unit 279, pattern update unit 280, precursor symptom determination A unit 281 and an information output unit 282.

The detection control unit 271 controls the operation of the detection unit 22, and the detection result by the detection unit 22 is stored in the detection information storage unit 252 together with the current date and time (detection time) timed by the time measuring unit 274 described later. Remember.
The notification control unit 272 controls the operation of the notification unit 23. For example, the notification control unit 272 outputs notification information including a display and sound indicating the operation state of the detection device 2A, the detection result by the detection unit 22, and the like to the notification unit 23, and sends the notification information to the notification unit 23. Let me know. Further, the notification control unit 272 drives the motor of the vibration unit 233 as necessary, and notifies predetermined information by vibration generated by driving the motor.
The communication control unit 273 controls the operation of the communication unit 24 that communicates with the external device.
The timer 274 measures the current date and time.
The information acquisition unit 275 functions at the time of execution of each process included in an abnormality prediction process described later, and acquires the detection information stored in the detection information storage unit 252.

The signal determination unit 276, the timing determination unit 277, the seizure determination unit 278, the period determination unit 279, and the pattern update unit 280 function when executing the update process included in the abnormality prediction process.
Among these, the signal determination unit 276 determines whether or not the seizure occurrence signal indicating the occurrence of a seizure is input from the operation unit 21.
The timing determination unit 277 determines whether or not it is time to execute the seizure occurrence determination based on the latest detection information.

The seizure determination unit 278 corresponds to the abnormality determination unit of the present invention. The seizure determination unit 278 is based on the detection information acquired in the latest cycle by the information acquisition unit 275 that operates in a predetermined cycle, and the seizure pattern and the normal time pattern stored in the pattern storage unit 253. To determine if a seizure has occurred. For example, the seizure determination unit 278 determines whether the change in the parameter according to the seizure pattern or the normal pattern is similar to the seizure pattern or the normal pattern included in the acquired detection information. If the seizure determination unit 278 determines that the change in the parameter is similar to the seizure pattern, the seizure determination unit 278 determines that the seizure has occurred in the user. If the seizure determination unit 278 determines that the change is similar to the normal pattern, the seizure determination unit 278 Is determined not to occur.
The period determination unit 279 determines whether a period in which the seizure occurrence signal is not input and a period in which it is not determined that the seizure has occurred have passed a predetermined period. That is, the period determination unit 279 determines whether or not a period in which no seizure has occurred has passed a predetermined period.

The pattern update unit 280 corresponds to the precursor pattern update unit of the present invention. The pattern update unit 280 functions when the signal determination unit 276 determines that the seizure occurrence signal has been input and when the seizure determination unit 278 determines that a seizure has occurred. Then, the pattern update unit 280 extracts the precursor pattern based on detection information detected and analyzed before the seizure occurrence timing, and updates the precursor pattern stored in the pattern storage unit 253.
The pattern update unit 280 extracts the seizure pattern based on detection information detected and analyzed after the seizure occurrence timing, and updates the seizure pattern stored in the pattern storage unit 253.
When it is determined that the seizure occurrence signal has been input and an operation signal indicating the occurrence timing of the seizure is input together with the seizure occurrence signal, the pattern update unit 280 generates the generation timing indicated by the operation signal. The occurrence timing of the seizure is specified based on the above, and the precursor pattern and the seizure pattern are updated based on the detection information detected and analyzed before and after the occurrence timing.
Furthermore, the pattern update unit 280 corresponds to the normal time pattern update unit of the present invention. When the period determination unit 279 determines that the period in which no seizure has occurred has passed a predetermined period, the pattern update unit 280 The normal pattern is extracted based on the detected and analyzed detection information, and the normal pattern stored in the pattern storage unit 253 is updated.

When each pattern is updated by the pattern update unit 280, the state identification pattern stored in the pattern storage unit 253 is updated with the extracted state identification pattern (seizure pattern, precursor pattern, and normal time pattern). May be. This also makes it possible to construct a state identification pattern based on the actual detection information of the user.
However, in consideration of the accuracy of the state identification pattern, it is desirable to update the state identification pattern stored in the pattern storage unit 253 with each average pattern of the extracted state identification patterns.

For example, it is conceivable to update the precursor pattern stored in the pattern storage unit 253 with the average pattern of the newly extracted precursor pattern and the precursor pattern extracted in the past.
Further, for example, a precursor pattern including a newly extracted precursor pattern and a precursor pattern extracted in the past may be generated, and the stored precursor pattern may be updated with the precursor pattern.
Furthermore, for example, only a pattern that matches a newly extracted precursor pattern and a previously extracted precursor pattern is generated as a new precursor pattern, and the stored precursor pattern is updated with the new precursor pattern. It is also possible to do.

The precursor symptom determination unit 281 and the information output unit 282 function in the prediction determination process included in the abnormality prediction process.
Based on the latest detection information (detection information acquired in the latest one cycle) acquired by the information acquisition unit 275 at a predetermined cycle, the precursor symptom determination unit 281 generates a precursor symptom of a seizure to the user. Determine whether or not. Specifically, the precursor symptom determination unit 281 compares the pattern based on the latest detection information with the precursor pattern and the normal time pattern stored in the pattern storage unit 253. Specifically, the precursor symptom determination unit 281 determines that a precursor symptom of a seizure has occurred when it is determined that the temporal change pattern of the parameter included in the latest detection information is more similar to the precursor pattern than the normal pattern. If it is determined that the pattern is more similar to the normal pattern than the precursor pattern, it is determined that no precursor symptoms of the seizure have occurred.

The information output unit 282 outputs notification information to be notified to the notification unit 23 when the precursor symptom determination unit 281 determines that a precursor symptom of a seizure has occurred. Specifically, the information output unit 282 outputs, on the display unit 231 of the notification unit 23, display information including a message indicating that a precursor symptom of a seizure has occurred and a seizure is likely to occur in the short term in the future. The message is displayed. In addition, the information output unit 282 causes the voice output unit 232 of the notification unit 23 to output a voice or warning sound corresponding to the message, and also drives a motor that configures the vibration unit 233 of the notification unit 23 to generate the information. A warning is notified by vibration.
When the seizure determination unit 278 determines that a seizure has occurred in the user, the information output unit 282 outputs notification information including a message indicating that the seizure has occurred to the display unit 231, and the message Is displayed. In addition, the information output unit 282 causes the audio output unit 232 to output a predetermined sound, and further causes the vibration unit 233 to generate vibration.
Note that the notification information may be transmitted to an external device (for example, the information processing apparatus 9A) via the communication unit 24.

[Abnormality prediction processing]
The detection device 2 </ b> A executes the abnormality prediction process according to the program stored in the operation information storage unit 251. This abnormality prediction process includes the following update process and prediction determination process.

[Update processing]
FIG. 3 is a flowchart showing the update process.
The update process is a process of updating the state identification pattern (seizure pattern, precursor pattern, and normal pattern) stored in the pattern storage unit 253, and is repeatedly executed by the control unit 27A.
In this update process, as shown in FIG. 3, first, the signal determination unit 276 determines whether or not the seizure occurrence signal is input from the operation unit 21 (step SA1).
Here, if it is determined that the seizure occurrence signal has been input, the control unit 27A proceeds to step SA7 to be described later.
On the other hand, if it is determined that the seizure occurrence signal is not input, the timing determination unit 277 determines whether or not the determination timing for determining the occurrence of the seizure has come (step SA2). In the determination process of step SA2, a sufficient time has elapsed since execution of the previous seizure occurrence determination (occurrence determination in step SA4 to be described later), and sufficient detection information is accumulated to perform the occurrence determination. It is determined whether or not. This generation timing is decremented when it is determined in the determination process of step SA1 that a seizure generation signal has been input.

If it is determined in the determination process of step SA2 that the determination timing has not come, the control unit 27A returns the process to step SA1.
On the other hand, when it is determined in the determination process of step SA2 that the determination timing has come, the information acquisition unit 275 acquires the latest detection information (detection information detected and analyzed in the latest one cycle). (Step SA3).
Then, the seizure determination unit 278 determines whether or not a seizure has occurred in the user based on the pattern based on the acquired latest detection information and the seizure pattern stored in the pattern storage unit 253 as described above. Is determined (step SA4).
When it is determined in the determination process of step SA4 that a seizure has occurred, the information output unit 282 outputs notification information indicating that the seizure has occurred to the notification unit 23 to notify the notification information, and The control unit 27A shifts the processing to step SA7 described later.

If it is determined in the determination process in step SA4 that no seizure has occurred, the period determination unit 279 determines whether or not the period in which it is determined that no seizure has occurred has passed a predetermined period. (Step SA5).
If it is determined that the predetermined period has not elapsed, the control unit 27A returns the process to step SA1.
On the other hand, when it is determined that the predetermined period has elapsed, the pattern update unit 280 extracts a normal time pattern based on the detection information detected and analyzed within the predetermined period. And the pattern update part 280 updates the normal time pattern memorize | stored in the pattern memory | storage part 253 based on the extracted normal time pattern as mentioned above (step SA6).
After step SA6, control unit 27A returns the process to step SA1.

In step SA7, the pattern update unit 280 obtains a precursor pattern based on detection information detected and analyzed before a seizure occurrence timing (timing at which a seizure occurrence signal is input or timing at which a seizure has occurred). Extract. And the pattern update part 280 updates the precursor pattern memorize | stored in the pattern memory | storage part 253 based on the extracted precursor pattern as mentioned above (step SA7).
When the operation signal indicating the seizure occurrence time or the elapsed time since the occurrence of the seizure is input together with the seizure occurrence signal, as described above, based on the occurrence time or the elapse time. The occurrence timing of the seizure is identified. Then, detection information detected and analyzed before the generation timing is acquired by the information acquisition unit 275, and the stored precursor pattern is updated by the pattern update unit 280 based on the detection information.

Furthermore, the pattern update unit 280 extracts a seizure pattern based on detection information detected and analyzed after the seizure occurrence timing, and based on the extracted seizure pattern, the seizure pattern stored in the pattern storage unit 253 is extracted. Update (step SA8). The execution order of steps SA7 and SA8 may be reversed or simultaneous.
After these steps SA7 and SA8, the control unit 27A returns the process to step SA1.
As described above, one cycle of the update process is completed. As described above, the update process is repeatedly executed by the control unit 27A.

  In steps SA6, SA7, and SA8 described above, each pattern is extracted and updated based on the detected detection information. However, the present invention is not limited to this, and the pattern update unit 280 may add a detected and extracted pattern (acquired pattern) as a new pattern as at least one of a normal pattern, a precursor pattern, and a seizure pattern. For example, although it is one of a normal state (a state in which no abnormality has occurred), a precursor state (a state in which a precursor symptom has occurred) and an abnormal state (a state in which an abnormality has occurred), it is stored. When the degree of correlation of the acquired pattern with respect to the existing pattern is equal to or less than the predetermined value, the pattern update unit 280 functions as a state determination condition adding unit, and the acquired pattern is renewed without overwriting the existing pattern. You may add to the pattern memory | storage part 253 as a pattern. Here, examples of the degree of correlation include the peak intensity ratio of each of the pulse wave signal and the acceleration signal, the integral value ratio of each signal in a predetermined period, and the degree of coincidence of the waveform shape of the pulse wave signal. By comprising in this way, the normal time pattern, precursor pattern, or seizure pattern according to a user can be added and learned. Therefore, not only the existing pattern but also the new pattern added is referred to and the user's state is determined, so that the user's state that could not be detected only by the existing pattern can be determined more appropriately. The detection accuracy of each state can be further improved. In addition, the update of each pattern may be performed by other methods.

Further, in the present embodiment, it is assumed that the detection device 2A automatically detects the occurrence of the seizure in addition to notifying the detection device 2A of the occurrence of the seizure by performing an input operation on the operation unit 21. The control unit 27A includes a signal determination unit 276, a timing determination unit 277, and a seizure determination unit 278. However, the present invention is not limited to this, and even if the control unit 27A includes one of the signal determination unit 276, the timing determination unit 277, and the seizure determination unit 278, the seizure pattern, the precursor pattern, and the normal time pattern can be updated.
For example, when the control unit 27A is configured to include the signal determination unit 276, steps SA2 to SA4 in the update process may be omitted. Further, when the control unit 27A is configured to include the timing determination unit 277 and the seizure determination unit 278, step SA1 in the update process may be omitted.

[Prediction judgment processing]
FIG. 4 is a flowchart showing the prediction determination process.
The prediction determination process is a process of determining whether or not a progenitor symptom has occurred in a predetermined cycle and notifying the user of a warning when it is determined that the prodromal symptom has occurred.
In the prediction determination process, as shown in FIG. 4, first, the information acquisition unit 275 acquires the latest detection information in the same manner as in step SA3 (step SB1).
Thereafter, the precursor symptom determination unit 281 performs the seizure to the user based on the pattern based on the acquired latest detection information and the precursor pattern and the normal pattern stored in the pattern storage unit 253 as described above. It is determined whether or not precursor symptoms have occurred (step SB2).

If it is determined in step SB2 that the precursor symptom has not occurred, the control unit 27A ends the prediction determination process and prepares for the next execution of the prediction determination process.
On the other hand, if it is determined in step SB2 that the precursor symptom has occurred, the information output unit 282 outputs notification information to notify a warning (step SB3). Through this process, the above message is displayed on the display unit 231, a warning is output by the audio output unit 232, and the vibration unit 233 is driven.
Thus, the prediction determination process is completed.

[Effect of the first embodiment]
According to the biological information measuring system 1A according to the present embodiment described above, the following effects can be obtained.
The precursor symptom determination unit 281 determines whether or not the precursor symptom has occurred based on the pattern based on the latest detection information detected by the detection unit 22 and the precursor pattern corresponding to the precursor symptom of the seizure. . When it is determined that the precursor symptom has occurred, the information output unit 282 outputs notification information indicating that there is a high possibility that a seizure will occur in a short period of time. According to this, the said alerting | reporting information can be output in the step before a seizure generate | occur | produces in a user. Accordingly, the notification unit 23 notifies the user that the occurrence of the seizure is predicted by notifying the notification information. Therefore, the user can take a precaution such as a risk avoidance action associated with the occurrence of a seizure.

  The detection device 2A that is used by being worn by the user includes a notification unit 23 that notifies the user of the notification information. According to this, when the occurrence of a seizure is predicted, it can be notified to the user promptly and reliably. Therefore, the user can surely take the above precautions.

  The pattern update unit 280 updates the precursor pattern, which is an index as to whether or not the precursor symptoms of the seizure have occurred in the user, based on detection information detected before the occurrence timing of the seizure that occurred in the user. . According to this, the said precursor pattern can be updated based on the detection information actually detected. Therefore, it is possible to more accurately determine whether or not the precursor symptoms of the seizure have occurred in the user.

  When it is determined by the seizure determination unit 278 that a seizure has occurred, there is a high possibility that a precursor symptom of the seizure has occurred. Therefore, when the seizure determination unit 278 determines that a seizure has occurred, the pattern update unit 280 updates the precursor pattern, so that it is easy to extract the precursor pattern corresponding to the precursor symptom from the detection information. Can do. Therefore, an appropriate pattern corresponding to the precursor symptom can be held as the precursor pattern.

  If it is determined by the signal determination unit 276 that the seizure occurrence signal has been input from the operation unit 21 in response to a user's input operation, the pattern update unit 280 updates the precursor pattern. According to this, the control unit 27A of the detection device 2A can surely grasp that a seizure has occurred in the user. Therefore, since the precursor pattern can be updated based on the detection information actually detected before the input of the seizure occurrence signal, a more appropriate precursor pattern can be held.

Here, when the occurrence timing of the seizure is unknown, the extraction range of the precursor pattern from the detection information detected in the past is widened, which makes it difficult to extract the precursor pattern from the detection information. take time. On the other hand, if the control unit 27A can grasp the occurrence timing of the seizure, the extraction range can be narrowed, the precursor pattern can be easily extracted, and the extraction processing time can be shortened.
For this reason, the operation unit 21 is configured to be able to input the occurrence time of the seizure or the elapsed time since the occurrence of the seizure, and when the occurrence time or the elapsed time is input by the user, Is sent to the control unit 27A. Then, the pattern update unit 280 updates the precursor pattern based on the generation time indicated by the operation signal and the detection information detected before the elapsed time is calculated. According to this, the extraction range can be narrowed compared to the case where the occurrence time of the abnormality is unknown. Therefore, the extraction of the precursor pattern can be performed more accurately in a relatively short time, and can be updated to an appropriate precursor pattern.

When determining the occurrence of a precursor symptom, if it is not determined that the precursor symptom has occurred unless the pattern based on the detection information and the precursor pattern substantially match, the occurrence of the precursor symptom may not be appropriately determined.
On the other hand, the precursor symptom determination unit 281 determines whether the pattern based on the detection information is similar to the precursor pattern or the normal pattern, and determines that the precursor symptom has occurred when it is determined that the pattern is similar to the precursor pattern. . According to this, even when the pattern based on the detection information and the precursor pattern do not substantially match, it can be determined that the precursor symptom has occurred if the pattern is more similar to the precursor pattern than the normal time pattern. Therefore, it is possible to reliably detect and grasp the occurrence of the precursor symptoms.

The pattern update unit 280 updates the normal time pattern stored in the pattern storage unit 253 based on the detection information actually detected by the detection unit 22. According to this, it can update to the normal time pattern according to a user's state and action. Therefore, it is possible to more accurately determine the occurrence of the precursor symptoms.
Here, seizures do not occur frequently in the daily life of the user. On the other hand, in the daily life of the user, the biological information and the body motion information detected by the detection unit 22 vary depending on the type of action, so the normal time pattern needs to be an average pattern in a relatively long cycle. is there.
On the other hand, when the period determining unit 279 determines that the period during which the seizure determining unit 278 determines that no seizure has occurred has passed the predetermined period, the pattern update unit 280 The normal time pattern is updated based on the detected information detected in (1). According to this, since it can suppress that the process which updates a normal time pattern generate | occur | produces frequently, the power consumption of 2 A of detection apparatuses can be reduced. In addition, since the normal pattern can be an average pattern in a relatively long cycle, the normal pattern used in the determination of the occurrence of prodromal symptoms is updated to a pattern having a relatively large fluctuation range of detection information. This can be suppressed. Therefore, it is possible to more appropriately determine the occurrence of precursor symptoms.

  The information output unit 282 outputs the notification information not only when the precursor symptom determination unit 281 determines that a precursor symptom has occurred, but also when the seizure determination unit 278 determines that a seizure has occurred. For this reason, the alerting | reporting part 23 can alert | report the generation | occurrence | production of a seizure to a user, the person who is near the said user, the said user's family, a medical worker, etc. by alerting | reporting the said alerting | reporting information. .

  When a seizure occurs as an abnormality, pulse waves and body movements that are different from normal times occur. For this reason, the detection unit 22 includes a biological information detection unit 221 that detects a pulse wave, and a body motion information detection unit 222 that detects acceleration that changes with the body motion of the user. By analyzing the detected pulse wave and acceleration signals, the control unit 27A can appropriately determine the occurrence of a seizure and a prodrome.

[Second Embodiment]
Next, a second embodiment of the present invention will be described.
The biological information measurement system according to the present embodiment has the same configuration as that of the biological information measurement system 1A. However, the information processing apparatus analyzes the information detected by the detection unit 22, and abnormal and prodromal symptoms. The biological information measurement system 1A is different from the biological information measurement system 1A in that it includes a part of the function of a control unit that performs generation determination and the like. In the following description, parts that are the same as or substantially the same as those already described are assigned the same reference numerals and description thereof is omitted.

FIG. 5 is a block diagram showing a configuration of the biological information measuring system 1B according to the present embodiment.
A biological information measurement system 1B according to the present embodiment corresponds to the abnormality prediction system of the present invention, and includes a biological information detection device 2B and an information processing device 9B as shown in FIG. 5, and is similar to the biological information measurement system 1A. It has a function.

[Configuration of biological information detection apparatus]
The detection device 2B is configured to be able to always communicate with the information processing device 9B, and transmits the detected biological information and body motion information to the information processing device 9B. Further, when the information processing apparatus 9B determines that the precursor symptom has occurred and the notification information is transmitted from the information processing apparatus 9B, the detection apparatus 2B receives the notification information and notifies the user. Such a detection device 2B includes an operation unit 21, a detection unit 22, a notification unit 23, a communication unit 24, a storage unit 25B, and a control unit 27B. That is, the detection device 2B includes the storage unit 25B and the control unit 27B instead of the storage unit 25A and the control unit 27A, but does not include the analysis unit 26.
Among these, the storage unit 25B includes the operation information storage unit 251 and the detection information storage unit 252, but does not include the pattern storage unit 253.

FIG. 6 is a block diagram illustrating a configuration of the control unit 27B.
Similarly to the control unit 27A, the control unit 27B controls the operation of the detection device 2B autonomously or according to a user's input operation. As illustrated in FIG. 6, the control unit 27 </ b> B includes a detection control unit 271, a notification control unit 272, a communication control unit 273, a time measuring unit 274, an information transmission unit 283, and an information output unit 282.

The information transmission unit 283 corresponds to the detection information transmission unit of the present invention. The information transmission unit 283 detects biological information and motion information, which are detection information detected by the detection unit 22 and stored in the detection information storage unit 252, in a predetermined cycle. Send to 9B. In addition, when the seizure occurrence signal is input from the operation unit 21, the information transmission unit 283 immediately transmits the seizure occurrence information including the content of the seizure occurrence signal to the information processing apparatus 9B.
When the notification information is received from the information processing apparatus 9B by the communication unit 24, the information output unit 282 outputs the notification information to the notification unit 23 to display the message on the display unit 231, and the audio output unit 232 The generation of the warning sound and the generation of vibration by the vibration unit 233 are executed.

[Configuration of information processing device]
FIG. 7 is a block diagram illustrating a configuration of the information processing apparatus 9B.
The information processing apparatus 9B is configured by an information processing apparatus such as a PC (including a server), a smartphone, and a tablet, for example, similarly to the information processing apparatus 9A. The information processing device 9B stores biological information and body movement information received from the detection device 2B, and analyzes and stores these pieces of information. In addition, the information processing device 9B executes the update processing of the stored state identification pattern and the prediction determination processing, and transmits notification information to the detection device 2B when it is determined that a progenitor symptom has occurred.
Such an information processing apparatus 9B includes an operation unit 91, a display unit 92, a communication unit 93, a storage unit 94, an analysis unit 95, and a control unit 96.

The operation unit 91 includes a keyboard, a pointing device, a touch panel, and the like, and outputs an operation signal corresponding to a user input operation to the control unit 96.
The display unit 92 is configured by various displays such as liquid crystal and displays an operation screen of the information processing apparatus 9B.
The communication unit 93 includes a module capable of communicating with the detection device 2B, and transmits and receives information to and from the detection device 2B under the control of the control unit 27B. For example, the communication unit 93 receives biological information and body movement information from the detection device 2B and stores them in the storage unit 94. When the seizure occurrence information is received from the detection device 2B, the communication unit 93 controls the seizure occurrence information. The data is output to the unit 96. Further, the communication unit 93 transmits the notification information input from the control unit 96 to the detection device 2B.

The storage unit 94 includes an operation information storage unit 941, a detection information storage unit 942, and a pattern storage unit 943, similarly to the storage unit 25A.
The operation information storage unit 941 stores operation information such as various programs and data necessary for the operation of the information processing apparatus 9B. As such operation information, the operation information storage unit 941 independently executes a control program such as an OS (Operating System) that controls the operation of the information processing apparatus 9B, update processing of abnormality prediction processing, and prediction determination processing. The program to do is memorized.
The detection information storage unit 942 stores detection information including biological information and body movement information received from the detection device 2B, detection time information indicating the time when these pieces of information are detected, and an analysis result by the analysis unit 95 described later. Remember.
The pattern storage unit 943 corresponds to the precursor pattern storage unit and the normal time pattern storage unit of the present invention, and stores the state identification pattern. These state identification patterns are updated as needed by the control unit 96 described later.

  Similar to the analysis unit 26, the analysis unit 95 analyzes the biological information (pulse wave signal) and body motion information (acceleration signal) for each predetermined period acquired from the detection device 2B, and calculates the various parameters. . Then, the analysis unit 95 stores the calculated various parameters in the detection information storage unit 942 as an analysis result by the analysis unit 95.

FIG. 8 is a block diagram showing the configuration of the control unit 96.
The control unit 96 includes a processing circuit such as a CPU and controls the operation of the information processing apparatus 9B autonomously or in response to an operation signal input from the operation unit 91. For example, the control unit 96 executes an abnormality prediction process to be described later, updates the state identification pattern based on the analysis result by the analysis unit 95, and determines that a prodromal symptom has occurred, When it is determined that the alarm has occurred, broadcast information is transmitted.
Such a control unit 96 includes a communication control unit 961 and a time measuring unit 962 as functional units realized by the processing circuit executing the program stored in the operation information storage unit 941 as shown in FIG. , Information acquisition unit 963, reception determination unit 964, timing determination unit 277, seizure determination unit 278, period determination unit 279, pattern update unit 280, precursor symptom determination unit 281 and information transmission unit 965.

The communication control unit 961 controls the operation of the communication unit 93.
The timer unit 962 measures the current date and time.
The information acquisition unit 963 functions when the abnormality prediction process is executed by the information processing apparatus 9B, and acquires the detection information stored in the detection information storage unit 942.
The reception determination unit 964 determines whether or not the seizure occurrence information is received from the detection device 2B.
The timing determination unit 277, the seizure determination unit 278, the period determination unit 279, the pattern update unit 280, and the precursor symptom determination unit 281 function in the same manner as described above.
The information transmission unit 965 corresponds to the notification information transmission unit of the present invention. When it is determined by the precursor symptom determining unit 281 that the precursor symptom has occurred, the information transmitting unit 965 sends notification information including a message that the seizure is likely to occur in the future to the communication unit 93. To the detection device 2B. In addition, when the seizure determination unit 278 determines that a seizure has occurred in the user, the information transmission unit 965 transmits notification information including a message indicating that the seizure has occurred to the detection device 2B via the communication unit 93. To do.

[Abnormality prediction processing]
The information processing apparatus 9B executes an abnormality prediction process in accordance with a program stored in the operation information storage unit 941. This abnormality prediction process includes the following update process and prediction determination process.

[Update processing]
The update process executed by the information processing apparatus 9B according to the present embodiment updates the seizure pattern, the precursor pattern, and the normal time pattern stored in the pattern storage unit 943 by the same flow as the update process executed by the detection apparatus 2A. .
Specifically, in the update process according to the present embodiment, in step SA1 in FIG. 3, the reception determination unit 964 determines whether or not the seizure occurrence information has been received from the detection device 2B.
Here, when it is determined that the seizure occurrence information is received by the reception determination unit 964, the pattern update unit 280 extracts the precursor pattern and the seizure pattern as described above in steps SA7 and SA8. Based on the pattern and the seizure pattern, the precursor pattern and the seizure pattern stored in the pattern storage unit 943 are updated.
Thereafter, the process returns to step SA1.

If it is determined that the seizure occurrence information has not been received in the determination process of step SA1, the timing determination unit 277 determines whether or not it is the determination timing for determining the occurrence of the seizure in step SA2. The
If it is determined in this determination process that the determination timing is not reached, the control unit 96 returns the process to step SA1.
On the other hand, when it is determined that the determination timing has come, the latest detection information is acquired by the information acquisition unit 963 in step SA3.
In step SA4, the seizure determination unit 278 determines whether a seizure has occurred in the user.

If it is determined in the determination process in step SA4 that a seizure has occurred, the process proceeds to steps SA7 and SA8, and the pattern update unit 280 updates the precursor pattern and the seizure pattern as described above. In addition, the information transmission unit 965 transmits notification information indicating that a seizure has occurred to the detection device 2B and the like.
Thereafter, the process returns to step SA1.

If it is determined in the determination process of step SA4 that no seizure has occurred, the period in which the seizure has not occurred by the period determination unit 279 in step SA5 has passed a predetermined period. It is determined whether or not.
If it is determined in step SA5 that the predetermined period has not elapsed, the process returns to step SA1.
On the other hand, if it is determined in step SA5 that the predetermined period has elapsed, a normal pattern based on the detection information detected and analyzed in the predetermined period is extracted by the pattern update unit 280 in step SA6. Then, the normal pattern stored in the pattern storage unit 943 is updated based on the normal pattern.
Thereafter, the process returns to step SA1.

Such an update process is repeatedly executed by the control unit 96 in the same manner as the update process shown in the first embodiment, thereby updating the state identification pattern based on the detected detection information.
As shown in the first embodiment, the control unit 96 is not limited to the configuration including the signal determination unit 276, the timing determination unit 277, and the seizure determination unit 278, but may be configured to include only one of them. Good.

[Prediction judgment processing]
The prediction determination process executed by the information processing apparatus 9B according to the present embodiment determines whether or not a prodromal symptom of the seizure has occurred in the user by the same flow as the prediction determination process executed by the detection apparatus 2A. When it is determined that the precursor symptom has occurred, the notification information is transmitted to the detection device 2B.
Specifically, in the prediction determination process according to the present embodiment, the latest detection information (detection information detected and analyzed in the latest predetermined period) is acquired by the information acquisition unit 963 in step SB1 in FIG. The
Thereafter, in step SB2, the precursor symptom determination unit 281 generates a seizure to the user based on the pattern based on the latest detection information acquired and the precursor pattern and the normal pattern stored in the pattern storage unit 943. It is determined whether prodromal symptoms have occurred.

If it is determined in step SB2 that the precursor symptom has not occurred, the control unit 96 ends the prediction determination process and prepares for the next execution of the prediction determination process.
On the other hand, when it is determined in step SB2 that the precursor symptom has occurred, in step SB3, the information transmission unit 965 transmits the notification information to the detection device 2B. This is notified by the notification unit 23 of the detection device 2B.
Thus, the prediction determination process is completed.

[Effects of Second Embodiment]
According to the biological information measurement system 1B according to the present embodiment described above, the same effects as the biological information measurement system 1A can be obtained, and the following effects can be obtained.
The detection device 2B transmits the detected biological information and motion information to the information processing device 9B, and the information processing device 9B executes the update of the state identification pattern and the determination of the occurrence of prodromal symptoms. And the detection apparatus 2B alert | reports the said alerting | reporting information by the alerting | reporting part 23, when alerting | reporting information is received from information processing apparatus 9B. According to this, the structure of the detection apparatus 2B can be simplified. Therefore, since the detection device 2B can be further downsized, it is possible to configure the detection device 2B that does not disturb the daily activities of the user more reliably. In addition, the power of the detection device 2B can be saved, and the detection device 2B can be operated for a long time using a battery. Therefore, the convenience of the biological information measurement system 1B can be improved.

[Modification of Second Embodiment]
The information processing apparatus 9B includes an analysis unit 95 that analyzes biological information and body motion information included in detection information received from the detection apparatus 2B. However, like the detection device 2A, the detection device 2B may include the analysis unit 26. In this case, the detection apparatus 2B includes the analysis result by the analysis unit 26 together with the biological information and body movement information detected by the detection unit 22 and transmits the detection information to the information processing apparatus 9B. The information processing apparatus 9B The received detection information may be stored in the detection information storage unit 942.

[Modification of Embodiment]
The present invention is not limited to the above-described embodiments, and modifications, improvements, and the like within the scope that can achieve the object of the present invention are included in the present invention.
In each of the embodiments described above, the biological information measurement systems 1A and 1B are configured to detect a seizure including fainting or the like as an abnormality occurring in the user and a prodrome of the seizure. However, the present invention is not limited to this. That is, the detected abnormality of the user may be another abnormality, for example, a disturbance of consciousness.

In each of the above-described embodiments, the detection unit 22 detects the user's pulse wave, brain wave, electrocardiogram, and body temperature as biological information, and the acceleration that changes according to the user's body movement. And a body motion information detection unit 222 that detects information. However, the present invention is not limited to this. For example, the detection unit 22 may have a configuration including any one of the biological information detection unit 221 and the body motion information detection unit 222. For example, the detection device may be configured as a body motion information detection device having the body motion information detection unit 222.
In addition, the biological information detection unit 221 may be configured to detect at least one of these without detecting all of the pulse wave, brain wave, electrocardiogram, and body temperature, instead of or in addition to these. Thus, another biological information such as blood pressure may be detected. For example, when the detection unit 22 does not include an electroencephalogram sensor that detects an electroencephalogram, the degree of freedom of the mounting position for the user of the detection devices 2A and 2B is improved.
Moreover, the detection part 22 is good also as a structure further provided with the positional information detection part which detects a user's positional information. Such a position information detection unit corresponds to a satellite positioning system such as GPS (Global Positioning System), and receives a position information based on a radio wave received from the satellite or a position using a radio wave for communication. An apparatus for calculating information can be exemplified.

In the first embodiment, the detection device 2A includes the notification unit 23 that notifies the notification information input from the information output unit 282. In the second embodiment, the detection device 2B is received from the information processing device 9B. It was set as the structure provided with the alerting | reporting part 23 which alert | reports the alerting | reporting information. However, the present invention is not limited to this. For example, a notification device connected to the detection devices 2A and 2B or a notification device connected to the information processing device 9B may receive the notification information and notify the information processing devices 9A and 9B. The notification information may be notified.
In addition, the notification unit 23 is not limited to the configuration including all of the display unit 231, the audio output unit 232, and the vibration unit 233, and may have a configuration including at least one of them.

  In each of the embodiments described above, the pattern update unit 280 of the detection device 2A and the information processing device 9B detects the seizure pattern, the precursor pattern, and the normal pattern stored in the pattern storage units 253 and 943 by the detection unit 22. It is assumed that updating is performed based on the stored detection information (biological information, operation information, and analysis results thereof). However, the present invention is not limited to this. For example, these state identification patterns may not be updated, and at least one of these state identification patterns may be updated.

  In the first embodiment, when the pattern update unit 280 determines that the seizure occurrence signal is input by the signal determination unit 276 and when the seizure determination unit 278 determines that a seizure has occurred to the user. In each of the above, the precursor pattern stored in the pattern storage unit 253 is updated. In the second embodiment, the pattern update unit 280 determines that the seizure occurrence information has been received by the reception determination unit 964 and the seizure determination unit 278 determines that a seizure has occurred in the user. In each case, the precursor pattern stored in the pattern storage unit 253 is updated. However, the present invention is not limited to this. That is, as described above, the precursor pattern may be updated only when the seizure occurrence signal and the seizure occurrence information are received, and the precursor pattern may be updated only when it is determined that the seizure has occurred.

  In each of the above embodiments, the occurrence of a seizure is notified to the control units 27A and 96 in accordance with the user's input operation on the operation unit 21, and the occurrence time or the elapsed time input by the user is controlled. It is notified to the units 27A and 96, and the pattern update unit 280 updates the precursor pattern based on the occurrence time or detection information detected before the elapsed time is calculated. However, the present invention is not limited to this. That is, the generation time and the elapsed time may not be input.

  In each of the above embodiments, when the precursor symptom determination unit 281 determines that the pattern based on the latest detection information is similar to the precursor pattern among the stored precursor pattern and normal pattern, the precursor symptom of the seizure has occurred. Judged. However, the present invention is not limited to this. That is, the precursor symptom determination unit 281 determines whether or not a precursor symptom of a seizure has occurred based on at least one of the detected biological information and body motion information of the user and a precursor pattern corresponding to the precursor symptom. If possible, any determination process may be used. The same applies to the seizure occurrence determination.

  In each of the above embodiments, when it is determined that the period during which it is determined that no seizure has occurred exceeds the predetermined period, the pattern update unit 280 is based on detection information detected and analyzed during the predetermined period. The stored peacetime pattern is updated. However, the present invention is not limited to this. As described above, the normal pattern may not be updated, and the normal pattern may be updated by a method different from the above method.

  In each of the above embodiments, the notification information is notified by the notification unit 23 when it is determined that a seizure has occurred. At this time, the notification information is not only notified by the notification unit 23 but may be transmitted to an external device connected to the detection device and the information processing device via a network or the like. In this case, it is possible to notify the user that a seizure has occurred to a family member or a medical worker who is away from the user. Further, the detection devices 2A and 2B and the information processing devices 9A and 9B may be connected for communication via a network.

  DESCRIPTION OF SYMBOLS 1A, 1B ... Biological information measurement system (abnormality prediction system), 2A ... Biological information detection apparatus (abnormality prediction apparatus), 2B ... Biological information detection apparatus (detection apparatus), 21 ... Operation part, 22 ... Detection part, 221 ... Living body Information detection unit, 222 ... body motion information detection unit, 23 ... notification unit, 253 ... pattern storage unit (precursor pattern storage unit, normal time pattern storage unit), 278 ... seizure determination unit (abnormality determination unit), 279 ... period determination unit 280 ... pattern update unit (precursor pattern update unit, normal time pattern update unit), 281 ... precursor symptom determination unit, 282 ... information output unit, 283 ... information transmission unit (detection information transmission unit), 9B ... information processing device, 965 ... Information transmitter (broadcast information transmitter).

Claims (12)

A detection unit for detecting detection information including at least one of user's biological information and body motion information related to the user's body motion;
Based on the detection information detected by the detection unit, and a precursor pattern which is a pattern of the detection information corresponding to a precursor symptom of an abnormality occurring in the user, the precursor symptom has occurred in the user. A precursor symptom determination unit for determining whether or not,
An abnormality prediction comprising: an information output unit that outputs notification information indicating that the occurrence of abnormality is predicted to the user when the precursor symptom is determined by the precursor symptom determination unit. apparatus. The abnormality prediction device according to claim 1,
An abnormality prediction device comprising: a notification unit that notifies the user of the notification information input from the information output unit. In the abnormality prediction device according to claim 1 or 2,
A precursor pattern storage unit for storing the precursor pattern;
When the abnormality occurs in the user, based on the detection information detected before the occurrence timing of the abnormality, a precursor pattern update unit that updates the precursor pattern stored in the precursor pattern storage unit; An abnormality prediction apparatus characterized by comprising: In the abnormality prediction device according to claim 3,
An abnormality determination unit that determines whether an abnormality has occurred in the user,
The abnormality prediction device, wherein the precursor pattern update unit updates the precursor pattern when it is determined by the abnormality determination unit that an abnormality has occurred. In the abnormality prediction device according to claim 3 or 4,
An operation unit that receives an input operation of the user;
The said precursor pattern update part updates the said precursor pattern, if the operation signal which shows that the said abnormality generate | occur | produced from the said operation part is input, The abnormality prediction apparatus characterized by the above-mentioned. In the abnormality prediction device according to claim 5,
The operation unit is configured to be able to input one of an elapsed time after the occurrence of the abnormality and an occurrence time of the abnormality in the user,
The precursor pattern update unit updates the precursor pattern based on the detection information detected before any of the elapsed time and the generation time input to the operation unit. Anomaly prediction device. In the abnormality prediction device according to any one of claims 1 to 6,
The precursor symptom determination unit has a pattern based on the detection information detected by the detection unit in a state where the abnormality has not occurred in the user, the precursor pattern, and the precursor symptom to the user. And, among the normal pattern that is the pattern of the detection information according to the state where the abnormality has not occurred, when it is similar to the precursor pattern, it is determined that the precursor symptom has occurred in the user, An abnormality predicting apparatus, wherein when it is similar to the normal pattern, it is determined that the precursor symptom has not occurred in the user. In the abnormality prediction device according to claim 7,
A normal time pattern storage unit for storing the normal time pattern;
An abnormality determination unit for determining whether or not the abnormality has occurred in the user;
A period determination unit that determines whether or not a period during which it is determined that no abnormality has occurred in the user by the abnormality determination unit has passed a predetermined period;
A normal time pattern updating unit that updates the normal time pattern based on the detection information detected by the detection unit during the predetermined period when the period determination unit determines that the predetermined period has elapsed; An abnormality prediction apparatus comprising: In the abnormality prediction device according to any one of claims 1 to 8,
When it is determined that the abnormality has occurred in the user, the information output unit outputs information indicating that the abnormality has occurred. In the abnormality prediction device according to any one of claims 1 to 9,
The detector is
A biological information detector that detects the user's pulse wave as the biological information;
An abnormality prediction apparatus comprising: at least one of a body motion information detection unit that detects an acceleration that changes with the body motion of the user as the body motion information. A detection device for detecting detection information related to the user;
An information processing device that processes detection information detected by the detection device,
The detection device includes:
A detection unit for detecting detection information including at least one of the user's biological information and body motion information related to the user's body motion;
A detection information transmission unit for transmitting the detection information to the information processing apparatus;
A notification unit for notifying the user of information received from the information processing device,
The information processing apparatus includes:
Whether the precursor symptom has occurred in the user based on the detection information received from the detection device and a precursor pattern that is a pattern of the detection information in accordance with an abnormal precursor symptom to occur in the user A precursor symptom determination unit for determining whether or not,
A notification information transmission unit that transmits notification information to the detection device that the occurrence of abnormality is predicted by the user when the precursor symptom determination unit determines that the precursor symptom has occurred. Characteristic abnormality prediction system. An abnormality prediction method performed using a detection device that detects a user's condition,
Detecting detection information including at least one of the user's biological information and body motion information related to the user's body motion,
Based on the detection information being detected and a precursor pattern that is a pattern of the detection information corresponding to a precursor symptom of an abnormality occurring in the user, it is determined whether or not the precursor symptom has occurred in the user. Judgment,
When it is determined that the precursor symptom has occurred, notification information indicating that an abnormality is predicted is output to the user.

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