JP6442336B2 - Anomaly detection terminal and program - Google Patents

Description

  The present invention relates to an anomaly detection terminal capable of detecting an anomaly such as a human fall and a program used for the anomaly detection terminal.

  Conventionally, there are systems that detect and report accidents such as health problems and falls of the elderly. The following Patent Document 1 discloses a detection unit including a piezoelectric sensor that detects body movement and respiration or pulse of a human body, a determination unit that determines normality or abnormality of health based on detection data from the detection unit, and the determination It is equipped with a wearable device that is integrated with a communication means for reporting that the means has determined abnormality, and is attached to the subject, and the detection signal from the piezoelectric sensor is inverted and amplified through a low-pass filter. The presence / absence of breathing is determined based on the difference (LFBM), the pulse wave and body movement are determined based on the difference between the maximum value and the minimum value (HFBM) of the inverted and amplified output through the high-pass filter, and the high-pass filter output (HPFO) There is disclosed a safe living support device for elderly living alone, characterized in that it is configured to determine body movement.

  In this device, when a resting state in which body movement is not detected continues for 60 minutes, it is determined that the body is in an abnormal state, and also when a resting state continues for 5 minutes after a fall has been detected, The emergency call is made after warning by the buzzer. However, if a predetermined body movement is detected after a fall is detected, it is determined that there is no need for notification because the user has acted, and the 5-minute timer is reset (fall detection is canceled). .

JP 2002-360522 A

  However, the impact of a fall accident on the human body is not uniform, and the user may become unable to move immediately after the fall, or may move immediately after the fall, but the user's condition may change suddenly after a certain amount of time (for example, If you lose consciousness due to bleeding in the brain, etc.).

  In the latter case, according to the technique described in Patent Document 1, even if a fall is detected, it is canceled and a relatively long monitoring time (60 minutes, which is the monitoring time in the resting state) from the time when the user cannot move. ) May not be reported until lapse of time, and emergency treatment may be delayed.

  In view of the circumstances as described above, an object of the present invention is to provide an abnormality detection terminal capable of preventing a detection from being canceled even though an abnormal situation due to a fall has actually occurred in a user. And providing a program.

  In order to achieve the above object, an abnormality detection terminal according to an aspect of the present invention is a terminal that is carried by a user and detects the user's fall, a motion sensor, a fall detection unit, a detection cancellation unit, An abnormality determination unit and a body motion detection unit are included. The motion sensor detects the motion of the terminal and outputs motion data. The fall detection means detects the fall of the user based on the motion data output by the motion sensor. The detection canceling unit cancels the detection of the fall when a predetermined cancel signal is input after the fall is detected. The abnormality determination unit determines that an abnormality has occurred in the user when the detection of the fall is not canceled. The body motion detection means detects the user's body motion based on the motion data output by the motion sensor. The abnormality determination unit monitors the detection of the body movement by the body movement detection unit for a predetermined first period after the detection of the fall is canceled, and a body movement under a predetermined condition is not detected during the monitoring. In this case, it is determined that the abnormality has occurred in the user.

  As a result, even if the fall detection is canceled, the abnormality detection terminal monitors the detection of body movement for the first period thereafter, and if the body movement under the predetermined condition is not detected, the abnormality detection terminal falls to the user in order to determine an abnormal state. It is possible to prevent the detection from being canceled even though an abnormal situation due to the above has actually occurred. Here, the first period is, for example, 60 minutes, but is not limited thereto. The predetermined cancellation signal may be automatically input when, for example, a user's body movement is detected, or may be automatically input upon detection of some event other than body movement, or by a user operation. It may be entered.

  The abnormality determination unit may determine that the abnormality has occurred in the user when a state in which the body movement is not detected by the body movement detection unit continues for a second period in the first period. Here, the second period is shorter than the first period, for example, 15 minutes, but is not limited thereto.

  The abnormality determination unit may determine that the abnormality has occurred in the user when the state in which the body movement is not detected by the body movement detection unit continues for a third period. Here, the second period may be set shorter than the third period. Here, the third period is, for example, 60 minutes, but is not limited thereto.

  As a result, the abnormality detection terminal detects the body movement detection monitoring period after the fall detection is canceled (first period) rather than the period (third period) in which an abnormal state is determined in the normal time when no fall is detected (non-falling). For example, when the user can move immediately after a fall, but after a certain amount of time has passed, the user suddenly changes and becomes unable to move. Abnormal conditions can be detected quickly. In other words, if body motion is not detected after canceling the fall detection, it is considered that there is a higher possibility that the user is experiencing some abnormality than when there was no fall. Even if it is less than the determination period, it is determined as an abnormal state.

  The fall detection means detects the fall when the motion data satisfies a first condition relating to the user's fall possibility, and the motion data is different from the first condition relating to the fall possibility. When the above condition is satisfied, a quasi-fall may be detected as an event according to the fall. In this case, the abnormality determination unit may determine that the abnormality has occurred in the user when the quasi-falling is detected in the first period.

  As a result, the abnormality detection terminal detects an event in which the user falls although there is no impact at the time of the fall, such as when the user tries to stand up after falling down but falls down without standing up. And even if it is the body movement detection monitoring period after cancellation of fall detection, when the above-mentioned event is detected, it waited for the period when body movement was not detected to continue for a predetermined period (second period). Therefore, it is possible to determine the abnormality without any failure, and to detect the abnormal situation of the user after the fall without any omission. In addition, when a quasi-fall is detected, it is considered that the possibility that the user is in an abnormal state is higher than normal, so that the continuation of the state in which body movement is not detected is determined as an abnormal state in normal time Even if the period is shorter than the period (third period), it is possible to avoid a delay in determining the abnormal state by determining the abnormal state.

  An abnormality detection terminal according to another aspect of the present invention is a terminal that is carried by a user and detects the user's fall, and includes a motion sensor, a fall detection means, a detection cancellation means, a body motion detection means, An abnormality determination means. The motion sensor detects the motion of the terminal and outputs motion data. The fall detection means detects the fall of the user based on the motion data output by the motion sensor. The detection canceling unit cancels the detection of the fall when a predetermined cancel signal is input after the fall is detected. The body motion detection means detects the user's body motion based on the motion data output by the motion sensor. The abnormality determining unit determines that an abnormality has occurred in the user when the state in which the body movement is not detected by the body movement detecting unit continues for a first period and when the detection of the fall is not canceled. . Furthermore, the abnormality determination means shortens the first period to a second period shorter than the first period when the detection of the fall is canceled.

  A program according to still another aspect of the present invention is based on the motion data output by the motion sensor in an abnormality detection terminal having a motion sensor that detects the motion of the abnormality detection terminal carried by the user and outputs the motion data. The step of detecting the user's fall, the step of canceling the detection of the fall when a predetermined cancel signal is input after the detection of the fall, and the user when the detection of the fall is not canceled A step of determining that an abnormality has occurred; a step of detecting body motion of the user based on motion data output by the motion sensor; and the body motion for a predetermined period after the detection of the fall is canceled. And detecting that the user is in the abnormal state when body movement under a predetermined condition is not detected during the monitoring.

  As described above, according to the present invention, it is possible to prevent the detection from being canceled even though an abnormal situation due to a fall actually occurs in the user.

It is a figure which shows the structure of the abnormality detection terminal which concerns on one Embodiment of this invention. It is the flowchart which showed the flow of the life monitoring process by the said abnormality detection terminal. It is the figure which showed the change of the acceleration accompanying a user's fall. It is a figure for demonstrating the detection method of an acceleration peak. It is the figure which compared and showed the change of the acceleration accompanying a user's fall, and the change of the acceleration when a user swings a bat. It is the figure which compared and showed the change of the acceleration when the said detection is canceled after a fall detection, and the change of the acceleration when the said detection is not canceled after a fall detection. It is the flowchart which showed the flow of the fall monitoring process by the said abnormality detection terminal. It is the flowchart which showed the flow of the progress monitoring process after the fall detection cancellation in the fall monitoring process shown in FIG. It is the figure which compared and showed the change of the acceleration when a user's fall is detected, and the change of the acceleration at the time of the low impact generation | occurrence | production which does not lead to fall detection.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[Abnormality detection terminal configuration]
FIG. 1 is a diagram illustrating a configuration of an abnormality detection terminal according to an embodiment of the present invention.

  The abnormality detection terminal 100 according to the present embodiment is, for example, a wristband type (watch type) wearable terminal, and is worn on, for example, the wrist or arm of a user such as an elderly person. In addition to the wristband type, for example, a pendant type that can be hung from the neck, a head mount type that can be attached to the head on an ear or the like, or a waist-mounted type such as a belt shape or a belt loop hanging shape can be used.

  As shown in the figure, the abnormality detection terminal 100 includes an acceleration sensor 11, a mounting sensor 12, a battery 13, a wireless communication unit 14, a notification unit 15, an operation display unit 16, an emergency button 17, and a control unit 18.

  The acceleration sensor 11 is composed of, for example, a triaxial sensor, and detects the movement of the abnormality detection terminal 100 (the movement of the user wearing the abnormality detection terminal 100). The acceleration sensor 11 outputs acceleration data detected at a predetermined sampling period. Instead of the acceleration sensor 11, other motion sensors such as an angular velocity sensor may be used.

  The wearing sensor 12 is provided, for example, in the wristband portion of the abnormality detection terminal 100, and detects the wearing state of the abnormality detection terminal 100 on the human body (arm) of the user. As a detection method of the mounting sensor 12, for example, a capacitance type is adopted, but other types of sensors such as an induction type, an ultrasonic type, a photoelectric type, and a magnetic type may be used. When the abnormality detection terminal 100 has a band shape and is connected to both ends of the anomaly detection terminal 100 and attached to the user's wrist, the connection between the ends is detected by a contact switch or an energized state. Wearing can also be detected.

  The battery 13 supplies power to each part of the abnormality detection terminal 100. As the battery 13, for example, a rechargeable battery such as a lithium polymer battery, a lithium ion battery, or a nickel metal hydride battery is used.

  The wireless communication unit 14 wirelessly communicates with a remote monitoring center C via a mobile communication network such as 3G or LTE (Long Term Evolution), for example, and an abnormality of the user detected by the abnormality detection terminal 100 (control unit 18). To the monitoring center C. The wireless communication unit 14 can also wirelessly communicate with a home security terminal connected to the monitoring center C by, for example, BLE (Bluetooth (registered trademark) Low Energy) or specific low power wireless.

  A supervisor is stationed at the monitoring center C, and when an abnormality report is received from the abnormality detection terminal 100 (or via the security terminal in the house), necessary measures such as dispatch of emergency personnel to the user's site are taken. Taken.

  The notification unit 15 is configured as a vibration device, for example, and notifies the user of an abnormality or operation acceptance by a stimulus by vibration. In addition to vibration, notification may be made by voice.

  The operation display unit 16 is configured as a touch panel display, for example, and performs various display processes such as abnormality notification together with the notification by the notification unit 15 or instead of the notification. Further, the operation display unit 16 may function as an input unit for a user cancel operation for abnormality detection (reporting). A separate cancel button may be provided as an input unit for the cancel operation.

  The emergency button 17 is an emergency operation unit for the user to make an emergency report to the monitoring center C in an emergency.

  The control unit 18 comprehensively controls each unit of the abnormality detection terminal 100 and executes various calculations in accordance with inputs from the sensors and the operation unit. The control unit 18 performs monitoring processing to determine whether a fall abnormal state, an emergency abnormal state, and a life abnormal state have occurred in the user by the monitoring processing units of the life monitoring unit 181, the emergency monitoring unit 182 and the fall monitoring unit 183. Execute.

  The life monitoring unit 181, the emergency monitoring unit 182, and the fall monitoring unit 183 may each be configured as a dedicated hardware circuit or may be configured as software (program). When the life monitoring unit 181, the emergency monitoring unit 182 and the fall monitoring unit 183 are configured as software, they are stored in a storage device such as a RAM (Random Access Memory) or a flash memory (not shown) included in the abnormality detection terminal 100. Hereinafter, these three types of monitoring processes will be described.

(Life monitoring)
Life monitoring means that the life monitoring unit 181 of the control unit 18 monitors whether the user (the wearer of the abnormality detection terminal 100) is moving to the extent that it occurs in daily life based on the output of the acceleration sensor 11, and the user If it is detected that a state where the patient cannot move due to a sudden illness or the like is detected, this is a function for reporting this.

  Specifically, the life monitoring unit 181 detects a movement (body movement) from the output of the acceleration sensor 11 in a state where the user wears the abnormality detection terminal 100 (detected by the wearing sensor 12), and performs daily life. When the level of body movement does not continuously occur for a certain period (for example, 1 hour), it is determined that a life abnormality has occurred in the user.

The determination of the presence or absence of body movement is performed by observing the peak of acceleration or the amount of change. For example, 1) When a peak value greater than or equal to a certain value (for example, 12 m / s ² ) is detected, or 2) When the amount of acceleration change per unit time exceeds a certain value, the life monitoring unit 181 Judge that there is body movement.

  Then, the life monitoring unit 181 notifies the user that it has been determined that there is a life abnormality through the vibration or sound of the notification unit 15 or the screen of the operation display unit 16, and after the notification, for a predetermined cancellation time (for example, 10 seconds). When a body movement is detected or a predetermined cancel operation is input from the user, the life abnormality is canceled (no abnormality is reported to the monitoring center C).

(Emergency monitoring)
The emergency monitoring is a function in which the emergency monitoring unit 182 of the control unit 18 notifies the monitoring center C when the user presses the emergency button 17 for the emergency response by the monitoring center C.

  Specifically, when the user presses and holds the emergency button 17 (for example, for 2 seconds), the emergency monitoring unit 182 determines that an emergency abnormality has occurred in the user. The emergency monitoring unit 182 notifies the monitoring center C of the emergency abnormality of the user and notifies the user that the abnormality has been confirmed via the notification unit 15 or the operation display unit 16.

  Even when life abnormality and fall abnormality occur in the user, when the emergency abnormality occurs, the emergency abnormality is given priority.

(Fall monitoring)
The fall monitoring is a function in which the fall monitoring unit 183 of the control unit 18 automatically detects the fall of the user (the wearer of the abnormality detection terminal 100) based on the output of the acceleration sensor 11 and reports the occurrence of the fall accident. is there.

  Specifically, the fall monitoring unit 183 detects a fall event having a characteristic like a fall from the output of the acceleration sensor 11 while the user is wearing the abnormality detection terminal 100, and evaluates the detection result. To detect falls.

  If a body movement such as a user standing up and walking is detected within a predetermined time (for example, 15 seconds) after the fall is detected, the fall monitoring unit 183 automatically cancels the detection of the fall event without confirming the fall abnormality. .

  When the fall monitoring unit 183 determines that the fall is abnormal, the fall monitoring unit 183 notifies the user of the vibration or sound of the notification unit 15 or the screen of the operation display unit 16, and after the notification, for a predetermined cancellation time (for example, 20 seconds). When a predetermined cancel operation is input from the user, the fall abnormality is canceled (no abnormality is reported to the monitoring center C). Although the detection method of a user's body movement is mentioned later, it is good also as the detection method in a life monitoring.

  In addition, although details will be described later, in the present embodiment, the fall monitoring unit 183 performs a progress monitoring process for monitoring the user's body movement for a predetermined period after the fall detection is canceled, so that the user falls. Even after a certain amount of time has passed, the situation suddenly changes so that it can be remedied.

[Operation of anomaly detection terminal]
Next, the monitoring operation of the abnormality detection terminal 100 configured as described above will be described. In the following description, the control unit 18 or each monitoring unit of the abnormality detection terminal 100 will be described as the main operating subject, but this operation is also performed in cooperation with a program executed under the control of the control unit 18. .

(Overview of life monitoring process)
First, an outline of the life monitoring process will be described. FIG. 2 is a flowchart showing the flow of the life monitoring process.

  As shown in the figure, the life monitoring unit 181 of the control unit 18 obtains triaxial acceleration data (ax, ay, az) from the acceleration sensor 11 (step 21).

  Subsequently, the life monitoring unit 181 scalarizes the three-axis acceleration data, which is a vector (step 22).

  Subsequently, the life monitoring unit 181 cuts high-frequency components by using a moving average (low-pass filter) for the scalarized acceleration data (step 23). Note that this processing may be omitted when body motion detection is performed based on the amount of change in acceleration.

  Subsequently, the life monitoring unit 181 calculates a change amount per unit time (for example, 1 second) with respect to the scalar value of the acceleration obtained by cutting the high frequency component (step 24). Here, the acceleration data when the user moves causes a large change in the value within a short period. Therefore, the life monitoring unit 181 obtains a difference from the value of the previous acceleration data, defines the amount of change in acceleration per unit time as the sum of absolute values of the difference over the unit time, and performs the above calculation. .

  Subsequently, the life monitoring unit 181 determines whether or not the user has a body movement based on whether or not the amount of change in acceleration per unit time is a certain value or more (step 25). However, as described above, the life monitoring unit 181 determines whether or not there is body movement by detecting whether or not the peak value of acceleration is equal to or greater than a predetermined value, not the amount of acceleration change per unit time. Good.

  When it is determined that there is no body movement (No in Step 25), the life monitoring unit 181 determines whether or not the stationary state of the user whose body movement is not detected continues for a certain period (for example, 1 hour), that is, the user It is determined whether or not there has been no body movement for a certain time from the time when the time was last moved (step 26). On the other hand, when it is determined that there is a body motion (Yes in Step 25), the life monitoring unit 181 resets the count of the duration time of the stationary state and returns to Step 21 described above.

  When the life monitoring unit 181 determines that the stationary state has continued for a certain period of time (Yes in step 26), the life monitoring unit 181 determines that a life abnormality has occurred in the user, and notifies the notification unit 15 or the operation display unit 16 to that effect. To the user (step 27). On the other hand, if it is determined that the stationary time has not continued for a certain period (No in Step 26), the life monitoring unit 181 returns to Step 21 described above.

  Subsequently, the life monitoring unit 181 determines whether the user's body movement is detected within a predetermined cancellation time (for example, 10 seconds) or a predetermined cancellation operation by the user is input (step 28).

  If it is determined that body motion detection or cancellation operation input has been made within the cancellation time (Yes), the life monitoring unit 181 cancels the detection of the above life abnormality (step 31).

  On the other hand, if the body movement is not detected within the predetermined cancellation time and the cancellation time has passed without input of the cancellation operation (Yes in step 29), the life monitoring unit 181 reports a life abnormality to the monitoring center C. (Step 30).

  The life monitoring unit 181 repeatedly executes the steps described above as long as the user wears the abnormality detection terminal 100.

(Basic fall detection logic)
Next, in describing the fall monitoring process by the fall monitoring unit 183, basic logic for detecting a user's fall will be described.

  The fall monitoring unit 183 detects a fall of the user by analyzing a change in acceleration and extracting a fall event in which a characteristic that is likely to fall appears.

  For example, the fall monitoring unit 183 detects the fall by evaluating the characteristics of the impact applied to the abnormality detection terminal 100 during the fall. However, the fall monitoring unit 183 can detect the fall by evaluating the fall characteristics that occur in the process of the user falling, and comprehensively evaluate the fall likelihood based on the impact and the fall likelihood based on the fall characteristic. Thus, the final fall determination can be performed. Below, it demonstrates focusing on the example which evaluates an impact.

―Falling judgment by impact characteristics―
Similar to the life monitoring unit 181, the fall monitoring unit 183 scalarizes acceleration data output for each of the three axes and performs a moving average process (low-pass filter) as pre-processing for fall determination. This preprocessing can be shared with the life monitoring unit 181. In the following description, when calculating the acceleration change amount, the change amount may be calculated using scalarized acceleration data before the moving average process is performed.

  Since the fall involves the collision of the user's body with the ground or the like, the acceleration changes greatly due to the impact applied to the terminal. Therefore, an event that seems to fall is detected based on the acceleration change amount at the acceleration peak.

FIG. 3 is a diagram showing a change in acceleration accompanying a user's falling. As shown in the figure, the fall monitoring unit 183 first determines, from the input acceleration data, an acceleration peak (for example, (1) in the figure) that is a threshold Th _p (for example, 40 m / s ² ) or more to be processed for fall determination. ) Is detected.

  Subsequently, the fall monitoring unit 183 obtains the total acceleration change amount (total change amount H) for a predetermined period including the detected peak time (for example, 100 ms, 50 ms before and after). Specifically, a difference from the value of the immediately preceding acceleration data is obtained, and the sum of the absolute values of the differences over the predetermined time is defined as the total acceleration change amount H. Note that the timing at which the total change in acceleration is maximized does not necessarily coincide with the acceleration peak timing. Therefore, the fall monitoring unit 183 obtains the total change amount of the acceleration for the predetermined period for each acceleration sampling period, and calculates the maximum total change amount in the period near the detected peak time (for example, 50 ms before and after). The total change amount H of acceleration corresponding to the acceleration peak may be used.

Then, the fall monitoring unit 183 determines that a fall event has occurred when the calculated total change amount H is equal to or greater than a predetermined fall reference value (H ≧ Th _a ).

  FIG. 4 is a partially simplified view of FIG. 3 for explaining a method of detecting an acceleration peak when the user falls.

As shown in the figure, the fall monitoring unit 183 obtains a point Pa that falls from the threshold value Th _p . Similarly, the fall monitoring unit 183 obtains a point Pb that rises from the threshold value Th _p . A point P (peak time) at which the acceleration value is maximum between the point Pa and the point Pb is detected as an acceleration peak, and the acceleration value at the peak time is obtained as the peak value P.

―Characteristics of acceleration change during a fall―
FIG. 5 is a diagram comparing the change in acceleration accompanying the user's falling (FIG. A) and the change in acceleration when the user swings the bat (FIG. B).

  As shown in the figure, when an impact occurs such as a fall, the acceleration sensor 11 is strongly shaken, so that the output of each axis is an acceleration generated in daily life (for example, a relatively large operation such as swinging a bat). The acceleration changes more drastically than the acceleration of the acceleration. In other words, the amount of change in acceleration per unit time increases during a fall.

  Therefore, the fall monitoring unit 183 calculates the amount of change in acceleration by accumulating the change in acceleration value in a certain period before and after as the amount of change in acceleration at a certain point in the scalarized acceleration data.

  Specifically, the fall monitoring unit 183 obtains a difference (absolute value) from the immediately preceding acceleration for each sampling data of acceleration within a predetermined period, and integrates them over the predetermined period.

-Fall detection modification 1 (peak value)-
Instead of the above, the fall monitoring unit 183 may determine that a fall event has occurred by detecting an acceleration peak value P equal to or greater than a threshold value.

  Further, the fall monitoring unit 183 may obtain a fall evaluation value based on the acceleration peak value P and a fall evaluation value based on the total change amount H described above, and determine a fall event based on the total evaluation value.

  Further, the fall monitoring unit 183 may determine the fall event based on the ratio of the total change amount H to the acceleration peak value P (ratio = H / P).

-Fall detection modification 2 (drop characteristics)-
Since the fall is a phenomenon that causes a fall toward the ground, the acceleration is lower than the gravitational acceleration (9.8 m / s ² ) during the fall. Therefore, the fall monitoring unit 183 may analyze the acceleration data immediately before the peak and evaluate the free fall characteristics.

  Specifically, as shown in FIG. 3, the fall monitoring unit 183 traces the time from the peak (1) in the figure, obtains the intersection (2) with the gravitational acceleration, and from that time, for a certain period (for example, 500 ms = Acceleration average value A until the fall determination period) is calculated. (Period (2)-(3))

Then, the fall monitoring unit 183 determines that the event is a fall event when the average acceleration value A is less than a predetermined fall reference value (A <Th _b , for example, Th _b = 8.5 m / s ² ).

-Modification 3 for fall detection (combined use of impact and drop features)-
The fall monitoring unit 183 may use both the fall determination process using the impact feature and the fall determination process using the fall feature.

First, the fall monitoring unit 183 obtains an impact evaluation value Es based on the acceleration peak value P as follows.
Es = P × c (c: adjustment coefficient for comprehensive evaluation)

Subsequently, the fall monitoring unit 183 obtains a drop evaluation value Ef based on the acceleration average value A as follows.
Ef = (a−A) × b (a: fall standard constant (for example, 8.5 m / s ² ), b: adjustment coefficient)

Then, the fall monitoring unit 183 _calculates the total evaluation value Et by adding the impact evaluation value Es and the drop evaluation value Ef, and determines that the event is a fall event when the total evaluation value Et is equal to or more than the fall reference value Thc.

(Automatic cancellation determination (body motion detection))
Next, a process for automatically canceling the detection after a fall is detected as described above will be described.

  When the fall monitoring unit 183 detects a fall, if the user subsequently moves, the fall monitoring unit 183 automatically cancels the fall detection because the user is considered not in a dangerous state.

  That is, the fall monitoring unit 183 observes the presence or absence of a user's movement (body movement) during the cancellation determination time (for example, 15 seconds) from the time when the fall is detected (or peak time), and observes the acceleration peak or change amount. Determine by. In this case, the fall monitoring unit 183 ignores the user's movement during a predetermined delay time (for example, 3 seconds) immediately after the fall is detected as a movement accompanying the fall.

Specifically, the fall monitoring unit 183 cancels the fall detection in the following cases 1) to 4), for example. In the automatic cancellation determination, any one of the following cancellation conditions may be used, and the fall detection may be canceled when any one of the conditions is satisfied using a plurality of conditions.
1) When a peak value above a certain level (for example, 12m / s ² ) is detected a predetermined number of times 2) When the sum of the above peak values exceeds a predetermined value 3) The total value obtained by accumulating the acceleration change amount exceeds a certain value 4) When the amount of acceleration change per unit time exceeds a certain value

  On the other hand, if the user's body movement is not detected before the cancellation determination time elapses after the fall detection, the fall monitoring unit 183 determines the fall abnormality.

  FIG. 6 shows a comparison between a change in acceleration when the detection is canceled after the fall detection (FIG. A) and a change in acceleration when the detection is not canceled after the fall detection (FIG. B). FIG.

  As shown in FIG. 5A, when it is canceled after the fall is detected, a change in acceleration of a certain level or more can be seen even after the acceleration peak value. In other words, in this case, it is assumed that the user is living in the same way as before the fall after the fall, so it may be possible to cancel the fall detection.

  On the other hand, as shown in Fig. B, if the detection is not canceled after the fall is detected (abnormal report), an acceleration change occurs before the acceleration peak value after the acceleration peak value. You can see that it is not. That is, in this case, it is estimated that the user cannot move as it is after the fall, so it is considered that the user should report the abnormality without canceling the fall detection.

(Progress monitoring process after canceling fall detection)
Next, the progress monitoring process after canceling the detection of the fall is described.

  The impact of a fall accident on the user's human body is not uniform, and the user may be unable to move immediately after the fall, or may move immediately after the fall, but the user's condition may change suddenly after a certain amount of time (for example, If you lose consciousness due to bleeding in the brain, etc.).

  In the latter case, if the fall detection is canceled by the above-described processing, there is a possibility that the emergency treatment will be delayed without being notified of an abnormality until a relatively long life monitoring time (for example, 1 hour) elapses after the user cannot move. is there.

  Therefore, in the present embodiment, the fall monitoring unit 183 monitors the user's body movement for a predetermined period of time whether or not the body movement at the daily life level occurs at a predetermined frequency even after the fall detection is canceled. The processing is to be executed. This progress monitoring process is time-limited monitoring for a fixed time (for example, 1 hour) after canceling the fall detection.

  FIG. 7 is a flowchart showing the flow of the fall monitoring process by the fall monitoring unit 183.

  As shown in the figure, the fall monitoring unit 183 evaluates the presence / absence of a fall based on the change in the acceleration data for each acceleration data acquisition cycle output from the acceleration sensor 11 as described above (step 71). ).

  If the fall monitoring unit 183 determines that a fall event has been detected (Yes in step 72), the fall monitoring unit 183 turns on the fall flag (step 73).

  Subsequently, as described above, the fall monitoring unit 183 determines whether or not the user's body movement is detected within a cancellation time (for example, 15 seconds) after the fall is detected (step 74). In this case, the user's movement for a predetermined delay time (for example, 3 seconds) immediately after the fall detection is ignored as the movement accompanying the fall.

  The fall monitoring unit 183 confirms the fall abnormality and reports the abnormality to the monitoring center C (step 76) when the cancellation time has not elapsed within the cancellation time and the cancellation time has elapsed (Yes in step 75). Although not shown in the figure, as described above, the fall monitoring unit 183 informs the user that the fall abnormality has been detected after the step 75 by the notifying unit 15 or the operation display unit 16, and is predetermined. If the cancel operation is input from the user within the cancel operation time (for example, 10 seconds or 20 seconds), the overturn abnormality is canceled, and if the cancel operation is not input within the cancel time, the overturn abnormality is determined.

  If the fall monitoring unit 183 determines that body movement is detected within the cancellation time (Yes in step 74), the fall detection is temporarily canceled (step 77), and the daily body movement is detected by the user. A progress monitoring process is executed as to whether or not to be performed (step 78).

  The detection method of the body movement is the same as the detection method by the life monitoring unit 181. However, the time for determining non-detection of body movement (the duration of the stationary state) is a time (for example, 15 minutes) shorter than the determination time (for example, 1 hour) in the life monitoring. In other words, this progress monitoring process executes a life monitoring process in which the determination time concerning the continuation of non-detection of body movement is shortened. Note that the body movement detection method in the progress monitoring process is different from the life monitoring process and may be the same method as the body movement detection in the automatic cancellation determination of the fall monitoring unit 183 described above.

  FIG. 8 is a flowchart showing the flow of the progress monitoring process after the overturn detection cancellation shown in step 78 of FIG.

  As shown in the figure, when the fall detection unit 183 cancels the fall detection, the fall monitoring unit 183 detects the user's body movement based on the acceleration data (step 81).

  Subsequently, the fall monitoring unit 183 determines whether body movement is detected (step 82).

  If it is determined that body movement has been detected (Yes), the fall monitoring unit 183 determines whether or not an elapsed monitoring time (for example, 1 hour) has elapsed (step 85).

  The fall monitoring unit 183 terminates the progress monitoring process when the elapsed monitoring time has elapsed with the body motion detected (Yes in step 85), and the normal fall monitoring process (after step 71 in FIG. 7). Return to.

  On the other hand, if it is determined that the state in which no body movement is detected (stationary time) has continued for a predetermined determination time (for example, 15 minutes) (Yes in step 83), the fall monitoring unit 183 determines the fall abnormality, and the monitoring center C An abnormality is reported to (step 84). That is, the canceled fall detection is restored and the abnormality is determined.

  Here, the abnormality in this case may be output separately from the case where the fall abnormality is confirmed without canceling the fall detection (when the user's body movement is not detected immediately after the fall). This makes it possible for emergency personnel dispatched to the fall site of the user to perform treatments according to the distinction between the two (for example, whether the user cannot move due to a large trauma due to the fall, or due to abnormalities in the brain such as intracerebral hemorrhage) It is distinguished whether it cannot move).

[Summary]
As described above, according to the present embodiment, the fall monitoring unit 183 of the abnormality detection terminal 100 monitors the detection of the user's body movement for a predetermined period after the fall detection is canceled, and the life monitoring process. If no stationary time body movement shorter than the stationary time in is detected, the fall is judged to be abnormal, preventing the user from canceling the detection even though an abnormal situation due to the fall actually occurs be able to.

[Modification]
The present technology is not limited to the above-described embodiment, and various modifications can be made without departing from the gist of the present technology.

  In the above-described embodiment, the progress monitoring process after the fall detection cancellation by the fall monitoring unit 183 is executed on the condition that the fall detection is canceled by detecting the user's body movement or inputting a cancel operation. However, in addition to these, for example, when a sensor other than the acceleration sensor 11 is detected, or when the fall detection is canceled by a remote command or the like, the progress monitoring process is executed on the basis of the input of some cancel signal. Also good.

  The above embodiment has been described on the assumption that the abnormality detection terminal 100 has a life monitoring function by the life monitoring unit 181. However, the abnormality detection terminal 100 may not have the life monitoring function.

  In the above-described embodiment, the life monitoring process by the life monitoring unit 181 and the progress monitoring process by the fall monitoring unit 183 have been described as being executed in parallel. However, the life monitoring unit 181 executes the progress monitoring process. It is good. In this case, the life monitoring unit 181 normally makes an abnormality determination when the user's stationary time continues for a predetermined time (for example, 1 hour), but when the fall detection is canceled, the predetermined time is shortened ( (For example, 15 minutes) Life monitoring processing is executed. Further, the life monitoring unit 181 and the fall monitoring unit 183 may be configured as one processing unit.

  In the above-described embodiment, the explanation has been made assuming that the user has fallen from a standing (walking) state. There may be cases where the person falls down again without standing up. However, in this case, since the impact due to the fall is lower than the fall from the standing (walking) state, the acceleration data includes the predetermined fall due to the change amount, peak value, fall characteristics, or a combination thereof. It may not meet the criteria and be detected as a fall event.

FIG. 9 is a diagram showing a comparison between a change in acceleration when a user's fall is detected (FIG. A) and a change in acceleration when a low impact occurs that does not lead to fall detection (B in FIG. 9). is there. As shown in the figure, at the time of low impact, it can be seen that the peak value of the acceleration is less than the threshold Th _1.

  Therefore, the fall monitoring unit 183 detects the fall due to the low impact as a semi-fall, distinguishing it from the fall, and if the semi-fall is detected after canceling the fall detection, the progress monitoring process is being executed. Also, the fall abnormality may be confirmed.

Specifically, the fall monitoring unit 183 detects the fall when the acceleration data satisfies the first condition regarding the user's fall possibility (for example, when the peak value is equal to or greater than Th _{1 in} FIG. 9), and the acceleration data When the second condition regarding the possibility of falling is satisfied (for example, when the peak value is greater than or equal to Th _{2 and} less than Th _{1 in} FIG. 9), the quasi-fall is detected as an event similar to the fall. When the semi-fall is detected within the elapsed monitoring time (for example, 1 hour) after canceling the fall detection, the fall monitoring unit 183 cancels the progress monitoring process and determines the fall abnormality.

  Thereby, although there is no impact at the time of the fall, it is possible to detect the abnormal situation of the user after the fall without omission by detecting the event that the user falls. In addition, when a semi-fall is detected after a fall, it is considered that the user is likely to be in an abnormal state, so in that case, by determining the abnormality without waiting for the abnormality determination by the progress monitoring process, It is possible to avoid a delay in determining the abnormal state of the user.

  In the above-described embodiment, the abnormality detection terminal 100 is configured to include various sensors, a notification unit, an operation display unit, a wireless communication unit, and the like as a wearable terminal. However, at least a part of these units of the abnormality detection terminal 100 is used. May be provided in another device (for example, a mobile terminal such as a smartphone carried by the user), and the same processing as in the above-described embodiment may be executed by cooperation processing with the other device.

11 ... Acceleration sensor 12 ... Mounting sensor 12
14 ... Wireless communication unit 14
DESCRIPTION OF SYMBOLS 18 ... Control part 181 ... Life monitoring part 182 ... Emergency monitoring part 183 ... Fall monitoring part 100 ... Abnormality detection terminal C ... Monitoring center

Claims (6)

In an abnormality detection terminal that is carried by a user and detects the user's fall,
A motion sensor that detects the motion of the abnormality detection terminal and outputs motion data;
A fall detection means for detecting the fall of the user based on the motion data;
When a predetermined cancellation signal is input after the detection of the fall, a detection cancellation means for canceling the detection of the fall, and
An abnormality determining means for determining that an abnormality has occurred in the user when the detection of the fall is not canceled;
Body movement detecting means for detecting the user's body movement based on the movement data;
The abnormality determination unit monitors the detection of the body movement by the body movement detection unit for a predetermined first period after the detection of the fall is canceled, and a body movement under a predetermined condition is not detected during the monitoring. An abnormality detection terminal that determines that the abnormality has occurred in the user. The abnormality detection terminal according to claim 1,
The abnormality determination unit determines that the abnormal state has occurred in the user when a state in which the body movement is not detected by the body movement detection unit continues for a second period in the first period. . The abnormality detection terminal according to claim 2,
The abnormality determination unit determines that the abnormality has occurred in the user when the state in which the body movement is not detected by the body movement detection unit continues for a third period;
The second period is set shorter than the third period. An abnormality detection terminal. The abnormality detection terminal according to claim 3,
The fall detection means detects the fall when the motion data satisfies a first condition relating to the user's fall possibility, and the motion data is different from the first condition relating to the fall possibility. Detecting a quasi-fall as an event in accordance with the fall when the condition of
The abnormality determination unit determines that the abnormality has occurred in the user when the quasi-falling is detected in the first period. In an abnormality detection terminal that is carried by a user and detects the user's fall,
A motion sensor that detects the motion of the abnormality detection terminal and outputs motion data;
A fall detection means for detecting the fall of the user based on the motion data;
When a predetermined cancellation signal is input after the detection of the fall, a detection cancellation means for canceling the detection of the fall, and
Body motion detecting means for detecting the user's body motion based on the motion data;
When the state in which the body motion is not detected by the body motion detection unit continues for a first period, and when the detection of the fall is not canceled, it is determined that an abnormality has occurred in the user, and the detection of the fall is performed. An abnormality detection terminal comprising: an abnormality determination unit that shortens the first period to a second period shorter than the first period when canceled. In the abnormality detection terminal having a motion sensor that detects the movement of the abnormality detection terminal carried by the user and outputs movement data,
Detecting the user's fall based on the motion data;
A step of canceling the detection of the fall when a predetermined cancellation signal is input after the detection of the fall; and
Determining that an abnormality has occurred in the user if the detection of the fall is not canceled;
Detecting the user's body movement based on the movement data;
Monitoring the detection of the body movement for a predetermined period after the detection of the fall is canceled, and determining that the abnormality has occurred in the user when no body movement of a predetermined condition is detected during the monitoring. The program to be executed.

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