Information processing program, information processing device, and information processing method

Abstract

To provide an information processing program, an information processing device, and an information processing method which output an alarm concerning a heart rate, with a reference for which an individual difference is taken into consideration.SOLUTION: An information processing program causes a computer to execute processing of acquiring the moving average value of the heart rate of an operator at predetermined time intervals, determining whether time series data of the acquired moving average value is on a decreasing trend in a range of a predetermined width with reference to an initial value acquired in starting an operation, and outputting an alarm in a case of determining that the time series data is not on a decreasing trend in the range of the predetermined width.SELECTED DRAWING: Figure 10

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program for outputting a warning regarding a heart rate. [Background technology]

[0002] Remote monitoring using wireless technology is being carried out. Patent Document 1 proposes a health monitoring technology for a vehicle driver as an example of remote monitoring. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-154115

[0004] In outdoor work sites, worker health management is also required as an occupational health measure. With the recent digital transformation of health management, it is now possible to manage vital data on an individual basis. There are also products on the market that measure the heart rate and surface skin temperature of people who are the subject of health management, and issue an alert if abnormal data is measured. Summary of the Invention [Problem to be solved by the invention]

[0005] However, most conventional products use a general definition of normal data to detect serious abnormalities that may be life-threatening. In order to prevent accidents, it is necessary to detect minor abnormalities when managing the health of workers. In such cases, it is difficult to determine the thresholds between normal and abnormal data because values ​​such as heart rate vary depending on individual differences and the actual work conditions. Therefore, it is difficult to say that worker health management using conventional technology is highly practical.

[0006] The present invention has been made in view of the above circumstances, and an object of the present invention is to provide an information processing device and an information processing method that output a warning regarding the heart rate based on a criterion that takes individual differences into consideration. [Means for solving the problem]

[0007] An information processing program according to one embodiment of the present application causes a computer to execute a process of acquiring a moving average value of a worker's heart rate at a predetermined time interval, determining whether the acquired time series data of the moving average value shows a decreasing trend within a predetermined range based on an initial value acquired at the start of work, and outputting an alarm if it is determined that the moving average value does not show a decreasing trend within the predetermined range. Effect of the Invention

[0008] According to one aspect of the present application, it is possible to output a warning regarding the heart rate based on a standard that takes into account individual differences, thereby creating an environment in which workers can work safely and with peace of mind. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is an explanatory diagram showing an example of the configuration of a health management system; [Diagram 2] FIG. 2 is a block diagram showing an example of a hardware configuration of a wearable device. [Diagram 3] A block diagram showing an example of the hardware configuration of a supervisor terminal. [Figure 4] FIG. 13 is an explanatory diagram showing an example of an actual measurement value DB. [Diagram 5] FIG. 13 is an explanatory diagram showing an example of a heart rate DB. [Figure 6] FIG. 11 is an explanatory diagram showing an example of a reference DB. [Figure 7] FIG. 11 is an explanatory diagram showing an example of a constant DB. [Figure 8] FIG. 11 is an explanatory diagram showing a determination algorithm. [Figure 9] 13 is a flowchart illustrating an example of a procedure for initial value setting processing. [Figure 10]13 is a flowchart illustrating an example of a procedure for a determination process. [Figure 11] 13 is a flowchart illustrating another example of the procedure of the initial value setting process. [Figure 12] FIG. 13 is an explanatory diagram showing another example of a constant DB. [Figure 13] FIG. 11 is an explanatory diagram showing an example of a reference waveform DB. [Figure 14] 10 is a flowchart illustrating another example of a procedure of the determination process. [Figure 15] FIG. 11 is an explanatory diagram showing another example of the configuration of the physical condition management system. [Figure 16] FIG. 2 is a block diagram showing an example of a hardware configuration of a worker terminal. [Figure 17] FIG. 13 is an explanatory diagram showing another example of a constant DB. [Figure 18] FIG. 13 is an explanatory diagram showing another example of the reference waveform DB. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] (Embodiment 1) The embodiment will be described below with reference to the drawings. FIG. 1 is an explanatory diagram showing an example of the configuration of a health management system. The health management system 100 includes a wearable device 1 and a supervisor terminal 2. The wearable device 1 is a device worn by a worker who is the subject of health management. The wearable device 1 is, for example, a smart watch. Although only one wearable device 1 is shown in FIG. 1, multiple devices may be used. The supervisor terminal 2 is a terminal used by a supervisor who supervises construction work. The supervisor terminal 2 is, for example, a smartphone, a tablet computer, etc. The wearable device 1 and the supervisor terminal 2 communicate with each other by short-range wireless communication. For example, the standard up to Bluetooth (registered trademark) 3.x, so-called Classic Bluetooth (registered trademark), is used, and the supervisor terminal 2 becomes the master and the wearable device 1 becomes the slave to perform communication. ZigBee (registered trademark) or UWB (Ultra-Wide Band) may be adopted as the short-range wireless standard.

[0011] 2 is a block diagram showing an example of the hardware configuration of a wearable device. The wearable device 1 includes a control unit 11, a storage unit 12, a biometric information acquisition unit 13, a motion detection unit 14, a communication unit 15, a clock unit 16, a display panel 17, and an operation unit 18. Each component is connected to each other by a bus B.

[0012] The control unit 11 has one or more arithmetic processing devices such as a CPU (Central Processing Unit), an MPU (Micro-Processing Unit), etc. The control unit 11 reads out and executes a control program 1P (program, program product) stored in the storage unit 12, thereby performing various information processing, control processing, etc., and realizing functional units such as an acquisition unit, a determination unit, and an output unit.

[0013] The storage unit 12 is configured using a non-volatile memory element such as a flash memory or an EEPROM (Electrically Erasable Programmable Read Only Memory). The storage unit 12 stores various programs executed by the control unit 11 and various data required for the processing of the control unit 11. The storage unit 12 stores a control program 1P executed by the control unit 11. The storage unit also stores an actual measurement value DB121, a heart rate DB122, a reference DB123, a constant DB124, and a reference waveform DB125. Note that the reference waveform DB125 is not necessary in this embodiment.

[0014] The biometric information acquisition unit 13 is, for example, a vital sensor. The biometric information acquisition unit 13 acquires biometric information such as the worker's body temperature, heart rate, and blood pressure. For example, the heart rate is measured using photoplethysmography. This is a method that utilizes the fact that blood has the property of reflecting green light. In this method, light from a green LED (Light Emitting Diode) is applied to blood vessels, and the light reflected by the blood is detected by an optical sensor such as a photodiode. When the heart beats, the amount of blood flowing through the wrist increases, and more green light is absorbed, while the amount of light absorbed decreases between heartbeats. In this way, the heart rate can be measured based on the change in reflected light captured by the optical sensor.

[0015] The motion detection unit 14 includes, for example, an acceleration sensor and a gyroscope, and detects the acceleration and direction of the motion of the worker.

[0016] The communication unit 15 includes a short-range wireless communication module such as Bluetooth (registered trademark) or Wi-Fi. The communication unit 15 communicates with the supervisor terminal 2.

[0017] The timekeeping unit 16 is composed of a real-time clock and an interval timer. The timekeeping unit 16 returns the current time in response to a request from the control unit 11. The interval timer also causes the control unit 11 to periodically execute an interrupt process.

[0018] The display panel 17 can be configured with a liquid crystal panel, an organic EL (Electro Luminescence) display, etc. The operation unit 18 can be configured with, for example, a touch panel incorporated in the display panel 17, and allows the supervisor to perform predetermined operations on the display panel 17. The operation unit 18 may include physical switches such as push button switches and rotary switches.

[0019] 3 is a block diagram showing an example of the hardware configuration of the supervisor terminal 2. The supervisor terminal 2 includes a control unit 21, a main memory unit 22, an auxiliary memory unit 23, a communication unit 24, a display panel 25, and an operation unit 26. Each component is connected by a bus B.

[0020] The control unit 21 has one or more arithmetic processing devices such as a CPU, an MPU, a GPU, etc. The control unit 21 provides various functions by reading and executing a control program 2P (program, program product) stored in the auxiliary storage unit 23.

[0021] The main memory unit 22 is an SRAM, a DRAM, a flash memory, etc. The main memory unit 22 mainly temporarily stores data necessary for the control unit 21 to execute arithmetic processing.

[0022] The auxiliary storage unit 23 is a flash memory or SSD, etc., and stores various data necessary for the control unit 21 to execute processing. The auxiliary storage unit 23 may be an external storage device connected to the supervisor terminal 2. The various DBs, etc. stored in the auxiliary storage unit 23 may be stored in a database server or cloud storage.

[0023] The communication unit 24 communicates with the wearable device 1 by short-range wireless communication. The communication unit 24 also communicates with other computers via mobile communication networks such as LTE (Long Term Evolution), 4G lines, and 5G lines. The control unit 21 may use the communication unit 24 to download the control program 2P from other computers via the Internet or the like, and store the control program 2P in the auxiliary storage unit 23.

[0024] The display panel 25 can be configured with a liquid crystal panel or an organic EL display, etc. The operation unit 26 can be configured with, for example, a touch panel built into the display panel 25, and can perform predetermined operations performed by the supervisor on the display panel 25. The operation unit 26 can also perform operations on a software keyboard displayed on the display panel 25. The operation unit 26 may also be a hardware keyboard, a mouse, etc.

[0025] 4 is an explanatory diagram showing an example of an actual measurement value DB. The actual measurement value DB 121 stores the heart rate acquired by the biological information acquisition unit 13. The actual measurement value DB 121 includes a date column, a time column, and a heart rate column. The date column stores the date when the heart rate was acquired. The time column stores the time when the heart rate was acquired. The heart rate column stores the acquired heart rate value.

[0026] FIG. 5 is an explanatory diagram showing an example of a heart rate DB. The heart rate DB 122 stores heart rates that have been subjected to preprocessing such as normalization. The heart rate DB 122 includes a date column, a time column, a 30-second column, and a 2-minute average column. The date column stores the date on which the heart rate is considered to have been measured. The time column stores the time on which the heart rate is considered to have been measured. The 30-second column stores the average heart rate for 30 seconds. For example, the average value of the heart rate measured from 0 to 29 seconds per minute is set to the heart rate at 0 seconds. The average value of the heart rate measured from 30 to 59 seconds per minute is set to the heart rate at 30 seconds. If no data exists for 30 seconds, it is interpolated from the data before and after. The 2-minute average column stores the average value of the heart rate from 2 minutes before the time stored in the time column to the relevant time.

[0027] FIG. 6 is an explanatory diagram showing an example of a criteria DB. The criteria DB 123 stores data related to criteria for performing anomaly determination. The criteria DB 123 includes a date column, a time column, and an initial value column. The date column stores the date when the value was determined. The time column stores the time when the value was determined. The initial value column stores the initial value of the determination criteria. The determination will be described later.

[0028] FIG. 7 is an explanatory diagram showing an example of a constant DB. The constant DB 124 stores constants of a formula used to determine abnormality. The constant DB 124 includes a date column, a time column, a slope column, and a variance column. The date column stores the date when the constants were determined. The time column stores the time when the constants were determined. The slope column stores the slope of the regression line. The variance column stores a value corresponding to the width of the area determined to be normal, centered on the regression line. For example, the value in question is the variance of the heart rate.

[0029] Next, the management of a worker's physical condition using heart rate will be described. The inventors had a number of workers wear smart watches capable of measuring heart rate, and measured their heart rates while they were working. As a result, as an overall consideration, it was found that the heart rate is high immediately after the start of work, and then gradually decreases as the work continues. In addition, the inventors found that the instantaneous value of the heart rate fluctuates wildly and cannot be used as an indicator of physical condition management, but that it can be used for physical condition management by monitoring the moving average value. As a result, the inventors found that it is possible to determine whether a worker's physical condition is deteriorating by grasping the moving average value of the heart rate at the start of work, and then by determining whether or not it shows a gradual decreasing trend within a certain range of variance.

[0030] FIG. 8 is an explanatory diagram showing the judgment algorithm. In the graph shown in FIG. 8, the horizontal axis is elapsed time in seconds, and the vertical axis is heart rate in bpm (beats per minutes). First, the heart rate is measured at the start of work to determine an initial value b. For example, the heart rate is measured for two minutes, and the average value for the two minutes is calculated. Since the heart rate tends to decrease over time, a negative slope a (a<0) is determined. The slope a is determined in advance from heart rate data for multiple workers, and is stored in the slope column of the constant DB 124. The regression line f(t) showing the relationship between elapsed time t and heart rate is defined as follows:

[0031] f(t) = at + b…(1)

[0032] The regression line is a linear line with an intercept at the initial value b and a slope a. Two lines are defined that are parallel to the regression line and are at a distance s (predetermined width, predetermined distance) from the regression line. s is the variance value of the heart rate distribution. Hereinafter, this will be referred to as variance s. Like the slope a, the variance s is determined in advance and stored in the variance column of the constant DB 124. The two lines are defined as follows:

[0033]

number

[0034] Thereafter, the average value h for the previous two minutes is calculated every 30 seconds. The calculated average value h is plotted on the graph shown in Figure 8. If the point to be plotted falls between the two lines (second line, third line) that sandwich the regression line (first line), it is judged as normal. If it does not fall between the two lines, it is judged as abnormal and an alert (warning) is output. In other words, if the average value h at the elapsed time t satisfies the following equation (4), it is judged as normal, and if not, it is judged as abnormal. Note that the above equations (2) and (3) are just examples. For example, an equation in which the intercepts of the regression line are b+s and bs may also be used.

[0035]

number

[0036] Next, the process performed by the wearable device 1 will be described. FIG. 9 is a flow chart showing an example of the procedure of the initial value setting process. The control unit 11 of the wearable device 1 judges whether or not work has started (step S1). The control unit 11 judges whether or not work has started based on the current time obtained from the clock unit 16 and the motion information of the worker obtained from the motion detection unit 14. The worker may input the start of work using the operation unit 18, and the control unit 11 may detect it. Also, the supervisor terminal 2 may transmit the start of work to the wearable device 1 based on the operation of the supervisor. When the control unit 11 judges that work has not started (NO in step S1), it ends the process. When the control unit 11 judges that work has started (YES in step S1), it calculates the initial value (step S2). As described above, for example, the average value for two minutes immediately after the start of work is set as the initial value. The control unit 11 stores the initial value in the reference DB 123 (step S3), and ends the process. The control unit 11 periodically executes the initial value setting process until it detects the start of work. Furthermore, when the control unit 11 detects the start of work, after the initial value setting process, it sets a timer interrupt so as to periodically execute the determination process described below.

[0037] FIG. 10 is a flow chart showing an example of the procedure of the judgment process. The judgment process is executed, for example, every 30 seconds by a timer interrupt by an interval timer. 30 seconds is an example of a "predetermined time interval". The control unit 11 updates the 30-second value of the heart rate (step S11). The 30-second value is a value to be stored in the 30-second column of the heart rate DB 122. The control unit 11 refers to the actual measurement value DB 121 and calculates the 30-second value. The control unit 11 stores the 30-second value in the 30-second column of the heart rate DB 122. The control unit 11 calculates and stores the average value (moving average value) of the heart rate for the previous two minutes (time period) (step S12). The control unit 11 stores the calculated average value in the two-minute average column of the heart rate DB 122. The control unit 11 judges whether the calculated average value is within the normal range (step S13). The control unit 11 inputs the elapsed time at the time of calculating the moving average value into the above-mentioned formula (2) and formula (3) to obtain the upper and lower limit values ​​of the heart rate regarded as normal. If the average value is between the upper and lower limits, the control unit 11 determines that the average value is within the range. If the average value is equal to or greater than the upper limit value, or equal to or less than the lower limit value, the control unit 11 determines that the average value is not within the range. If the control unit 11 determines that the calculated average value is within the normal range (YES in step S13), the control unit 11 ends the process. If the control unit 11 determines that the calculated average value is not within the normal range (NO in step S13), the control unit 11 outputs an alarm (step S14). The control unit 11 outputs a beep from a speaker (not shown) and vibrates a vibrator (not shown) to notify of an abnormality. The determination process is executed every 30 seconds, but may be executed at time intervals other than 30 seconds. Although the average heart rate for 30 seconds is calculated in step S11, the time length may be other than 30 seconds. In step S21, a two-minute moving average value is calculated, but a time length other than two minutes may be used. In accordance with the change, the column name of the heart rate DB 122 may be changed. Furthermore, the time length such as 30 seconds or 2 minutes may be set to a different value depending on the worker using the wearable device 1.

[0038] This embodiment has the following advantages. It is possible to accurately determine whether a worker's physical condition is abnormal based on whether the worker's heart rate is gradually decreasing within a certain range. In addition, since the initial value that serves as the basis for the determination criterion is calculated for each worker when they start work, it is possible to detect abnormalities in physical condition without being affected by individual differences or daily differences in physical condition.

[0039] (Variation 1) This modification relates to a form in which the initial value is different between the morning and the afternoon. According to the analysis by the inventors, it has been found that the heart rate is generally higher in the afternoon than in the morning. Therefore, the initial value used for determining the afternoon is set to a value larger than that for the morning.

[0040] FIG. 11 is a flowchart showing another example of the procedure of the initial value setting process. The control unit 11 of the wearable device 1 judges whether or not work has started (step S21). The judgment method is the same as that of step S1 described above. If the control unit 11 judges that work has not started (NO in step S21), the process ends. If the control unit 11 judges that work has started (YES in step S21), the control unit 11 judges whether or not it is currently morning (step S22). If the control unit 11 judges that it is currently morning (YES in step S22), it calculates an initial value (step S23). The calculation of the initial value is the same as that of step S2 described above. The control unit 11 stores the initial value in the reference DB 123 (step S24) and ends the process. If the control unit 11 judges that it is currently afternoon, not morning (NO in step S22), it updates the initial value (step S25). For example, the initial value for morning is multiplied by 1.2 to set the new initial value. The control unit 11 moves the process to step S24. If the worker is not working in the morning and the initial value for the morning has not been calculated, the initial value is calculated.

[0041] In this modified example, the initial value is updated at the start of work in the afternoon, so the judgment takes into account that the heart rate is higher in the afternoon than in the morning, making it possible to ensure judgment accuracy. Also, since the initial value for the afternoon is determined based on the initial value for the morning, it is expected that even if the worker's physical condition is worse at the start of work in the afternoon than in the morning, it will be quickly detected.

[0042] (Variation 2) This modified example relates to a form in which a width (variance) that defines a normal range is determined for each worker. The value stored in the variance column of constant DB 124 is the variance s of the heart rate. The variance s is used to calculate an upper limit and a lower limit for determining that the heart rate is normal. The value of variance s is considered to differ depending on the cardiopulmonary capacity of each worker. Therefore, the heart rate is measured in advance for each worker, and the variance s is determined for each worker. The determined value is then stored in the variance column of constant DB 124 of each worker's wearable device 1.

[0043] In this modification, the information processing performed by wearable device 1 is almost the same as in the first embodiment.

[0044] In this modification, the value of the variance s (distance) in the formula for calculating the upper and lower limits of the heart rate that are determined to be normal is determined for each worker, which makes it possible to perform normal / abnormal determination taking into account the cardiopulmonary capacity of each worker.

[0045] (Variation 3) This modified example relates to a form in which the slope of the regression line and the width (variance) that defines the normal range are determined according to the attributes of the worker. The tendency of heart rate fluctuations differs depending on the age and sex of the worker. This modified example addresses this point.

[0046] Fig. 12 is an explanatory diagram showing another example of the constant DB. The constant DB 124 in this modification includes a date column, a time column, an age column, a gender column, a slope column, and a variance column. The values ​​stored in the date column, the time column, the slope column, and the variance column are similar to those in the constant DB 124 shown in Fig. 7 above, so description thereof will be omitted. The age column stores the generation of the worker to whom the corresponding slope and range are applied. The gender column stores the gender of the worker to whom the corresponding slope and range are applied.

[0047] In this modification, the information processing performed by the wearable device 1 is almost the same as that in the embodiment 1. The following describes the differences. In the determination process, when the upper and lower limits of the range in which the heart rate is considered normal are calculated using the above-mentioned formulas (2) and (3), the values ​​of the slope a and variance s corresponding to the attributes (age, sex) of the worker are obtained from the constant DB 124 and calculated.

[0048] The constant DB 124 in this modification may be stored in another computer, for example, the supervisor terminal 2, and only the records corresponding to the workers using the wearable device 1 may be transferred to the wearable device 1 and stored in the storage unit 12. In this case, the determination process is the same as in the first embodiment.

[0049] In this modified example, in the equation for calculating the upper and lower limits of the heart rate at which a worker's physical condition is determined to be normal, the values ​​of the slope a and variance s are determined according to the attributes of the worker, which is expected to improve the accuracy of the determination.

[0050] (Embodiment 2) This embodiment relates to a form in which abnormalities in heart rate are determined not by a value at a single point in time, but by a value over a certain period of time. In this embodiment, the heart rate is measured for each worker in advance as a preliminary step. At that time, the measurement is performed while performing actual work or while performing the same movements as the actual work. The measurement time for each measurement is about 10 to 20 minutes. This is because each task repeats units of time length of about 10 to 20 minutes. Therefore, the measurement time for each task may be changed according to the length of the unit task. Furthermore, measurements are performed for multiple tasks for each worker. The measurement results are stored in the memory unit 12 of the wearable device 1 as point sequence data.

[0051] The reference waveform DB stores waveform data (reference time series data) of the heart rate that serves as the judgment standard. FIG. 13 is an explanatory diagram showing an example of the reference waveform DB. The reference waveform DB 125 includes a task sequence, a time sequence, and a heart rate sequence. The task sequence stores the content of the task. The time sequence stores the elapsed time from a reference time. The heart rate sequence stores the heart rate corresponding to the elapsed time. The heart rate here is assumed to be the average heart rate over 30 seconds, as in the first embodiment.

[0052] In this embodiment, a reference waveform is measured for each task and stored in reference waveform DB 125. Therefore, when starting a task, a worker operates operation unit 18 of wearable device 1 to input the details of the task to be started. Control unit 11 stores the inputted details of the task in memory unit 12.

[0053] FIG. 14 is a flowchart showing another example of the procedure of the judgment process. The judgment process is executed, for example, every 30 seconds by timer interruption by an interval timer, as in the first embodiment. The control unit 11 updates the 30-second value of the heart rate (step S31). The control unit 11 calculates and stores the average value (moving average value) of the heart rate for the previous two minutes (step S32). Steps S31 and S32 are the same as steps S11 and S12 described above, so the explanation is omitted. The control unit 11 judges whether it is judgment timing or not (step S33). Since the judgment is performed on a task-by-task basis, the control unit 11 judges that it is judgment timing when it detects that one task has been completed. If the control unit 11 judges that it is not judgment timing (NO in step S33), it ends the process. If the control unit 11 judges that it is judgment timing (YES in step S33), it calculates the DTW value (step S34). The DTW value is a value calculated by DTW (Dynamic Time Warping) of the similarity between two waveforms. When calculating the DTW value, the control unit 11 reads out from the reference waveform DB 125 a reference waveform that is stored in the storage unit 12 and corresponds to the work content.

[0054] In DTW, for waveforms x and y of different lengths, the value wx of waveform x at time t corresponds to the value wy of waveform y at time t through alignment as w = (wx, wy). In this case, if there are k total waveform alignments, the set W of correspondences is expressed by equation (4).

[0055] W = {w1, w2, …, wK}…(5)

[0056] In this case, the distance between the waveforms is defined by equation (6).

[0057]

number

[0058] It can be said that the smaller the DTW value, the more similar the waveforms x and y are. In this embodiment, the DTW value is calculated between the reference waveform stored in the reference waveform DB 125 and the waveform (time series data) of the heart rate during the work that was just completed and acquired by the biological information acquisition unit 13. The control unit 11 judges whether the calculated DTW value exceeds a threshold value (step S35). For example, the threshold value is 1. When the control unit 11 judges that the calculated DTW value does not exceed the threshold value (NO in step S35), the process ends. When the threshold value is not exceeded, it can be considered that the latest heart rate waveform is similar to the reference waveform and that there is no abnormality in the physical condition of the worker. When the control unit 11 judges that the calculated DTW value exceeds the threshold value (YES in step S35), the control unit 11 outputs an alarm (step S36) and ends the process. When the threshold value is exceeded, it means that the latest heart rate waveform is far from the reference waveform and that there is a possibility that there is an abnormality in the physical condition of the worker.

[0059] This embodiment has the following effects. Whether or not there is an abnormality in the physical condition of a worker is judged using a heart rate waveform having a time width, so that abnormalities can be detected with high accuracy. If the time length of the waveform used for the judgment is 20 minutes, the time interval for making the judgment is 20 minutes, so that the judgment shown in embodiment 1 etc. may be used in combination. In this case, the format of the alarm output may be changed between when an abnormality is detected using the judgment method of embodiment 1 etc. and when it is detected using the judgment method of this embodiment, so that it is possible to distinguish which judgment method was used to detect the abnormality.

[0060] (Embodiment 3) In the above-mentioned first embodiment (including the modified example) and second embodiment, it is assumed that all the processes described are performed by the wearable device 1. This embodiment relates to an embodiment in which the processes are shared between the wearable device 1 and the worker terminal 3.

[0061] Fig. 15 is an explanatory diagram showing another example of the configuration of a health management system. The health management system 100 includes a wearable device 1, a supervisor terminal 2, and a worker terminal 3. The wearable device 1 and the supervisor terminal 2 have the same configuration as in embodiment 1, so their explanation will be omitted. In Fig. 15, one wearable device 1 and one worker terminal 3 are shown, but there may be multiple of each.

[0062] The wearable device 1 worn by a worker communicates with a worker terminal 3 carried by the worker via short-range wireless. The worker terminal 3 also communicates with a supervisor terminal 2 via a network N. The network N is a mobile communication network such as a Long Term Evolution (LTE) communication network. A local wireless LAN may also be constructed as the network N by installing a Wi-Fi access point or the like at the work site. Alternatively, the worker terminal 3 and supervisor terminal 2 may communicate with each other via an ad-hoc mode of the wireless LAN or the like.

[0063] 16 is a block diagram showing an example of the hardware configuration of the worker terminal 3. The worker terminal 3 includes a control unit 31, a main memory unit 32, an auxiliary memory unit 33, a communication unit 34, a display panel 35, and an operation unit 36. Each component is connected by a bus B.

[0064] The control unit 31 has one or more arithmetic processing devices such as a CPU, an MPU, a GPU, etc. The control unit 31 provides various functions by reading and executing a control program 3P (program, program product) stored in the auxiliary storage unit 33.

[0065] The main memory unit 32 is an SRAM, a DRAM, a flash memory, etc. The main memory unit 32 mainly temporarily stores data necessary for the control unit 31 to execute arithmetic processing.

[0066] The auxiliary storage unit 33 is a hard disk or SSD, etc., and stores various data necessary for the control unit 31 to execute processing. The auxiliary storage unit 33 stores an actual measurement value DB331, a heart rate DB332, a reference DB333, a constant DB334, and a reference waveform DB335. The actual measurement value DB331, the heart rate DB332, the reference DB333, the constant DB334, and the reference waveform DB335 are similar to the actual measurement value DB121, the heart rate DB122, the reference DB123, the constant DB124, and the reference waveform DB125 described above, respectively, and therefore description thereof will be omitted. The wearable device 1 in this embodiment may not store the heart rate DB122, the reference DB123, the constant DB124, and the reference waveform DB125 in the storage unit 12. The actual measurement value DB331 is a mirror of the actual measurement value DB121.

[0067] The communication unit 34 communicates with the wearable device 1 by short-range wireless communication. The communication unit 34 communicates with the supervisor terminal 2 via the network N.

[0068] The display panel 35 and operation unit 36 ​​are similar to the display panel 25 and operation unit 26 of the supervisor terminal 2, respectively, so their explanation will be omitted.

[0069] In this embodiment, the wearable device 1 stores the heart rate acquired by the biological information acquisition unit 13 in the actual measurement value DB 121, and transmits the update contents of the actual measurement value DB 121 to the worker terminal 3. The control unit 31 of the worker terminal 3 reflects the received update contents in the actual measurement value DB 331. In this way, the actual measurement value DB 331 becomes a mirror of the actual measurement value DB 121.

[0070] In this embodiment, the initial value setting process (FIGS. 9 and 11) described in embodiment 1 is executed by the wearable device 1, but the calculated initial values ​​are stored in the reference DB 333 of the worker terminal 3. The judgment process (FIGS. 10 and 14) is executed by the worker terminal 3. In the judgment process, an alarm is issued from the worker terminal 3, and alarm information is transmitted from the worker terminal 3 to the supervisor terminal 2. Note that the processes shared by the wearable device 1 and the worker terminal 3 are not limited to those described above, and may be changed depending on the information processing capabilities of the wearable device 1 and the worker terminal 3. In accordance with this, the databases located in the wearable device 1 and the worker terminal 3 are also changed as appropriate.

[0071] In this embodiment, information processing is shared between the wearable device 1 and the worker terminal 3, so that necessary processing can be performed in a reasonable processing time even if the processing power of the wearable device 1 is low. Also, by having the worker carry the wearable device 1 and the worker terminal 3, communication with the wearable device 1 is stabilized. Furthermore, by transmitting an alarm from the worker terminal 3 configured as a smartphone or the like to the supervisor terminal 2, it becomes possible to more reliably issue an alarm to the supervisor.

[0072] This embodiment may be combined with embodiment 1 (including the modified example) or embodiment 2. For a worker who does not carry a worker terminal 3, the wearable device 1 communicates directly with the supervisor terminal 2. For a worker who carries a worker terminal 3, the wearable device 1 communicates with the worker terminal 3, and the worker terminal 3 communicates with the supervisor terminal 2.

[0073] (Embodiment 4) In any of the above-mentioned embodiments and modified examples, it is assumed that the worker performs the work with standard equipment. In this embodiment, it is assumed that the worker uses an assist tool. For example, the assist tool is compression wear or an assist suit. Compression wear is also called pressure wear and is made of a material fabric that has stretch and elasticity. When compression wear is worn, pressure is applied to the muscles, and movement is supported. An assist suit supports movement by using elastic shock cords or artificial muscles.

[0074] FIG. 17 is an explanatory diagram showing another example of the constant DB. The constant DB 124 includes a task column, an assist tool column, a slope column, a variance column, a date column, and a time column. The task column stores the task name that can identify each task performed by the worker. The assist tool column further includes a presence / absence column and a type column. The presence / absence column stores the presence or absence of an assist tool. "None" indicates a case where an assist tool is not used. "Present" indicates a case where an assist tool is used. The type column is set to a value when an assist tool is used. For example, the type column stores the value of compression wear or an assist suit. The slope column stores the slope of the regression line. The variance column stores the variance corresponding to the distance between each of the two straight lines indicating the normal range and the regression line. The date column stores the date when the slope and variance were measured or determined. The time column stores the time when the slope and variance were measured or determined. The constant DB 124 is created for each worker or for each worker attribute (age, sex, years of experience) and distributed to each worker's wearable device 1 or worker terminal 3. The determination process using the constant DB 124 is similar to that in the first embodiment, and therefore will not be described.

[0075] FIG. 18 is an explanatory diagram showing another example of the reference waveform DB. The reference waveform DB 125 includes a task sequence, an assisting tool sequence, an elapsed time sequence, a heart rate sequence, a date sequence, and a time sequence. The task sequence stores the task name that can identify each task performed by the worker. The assisting tool sequence further includes a presence / absence column and a type column. The presence / absence column stores the presence or absence of an assisting tool. "Absent" indicates a case where an assisting tool is not used. "Present" indicates a case where an assisting tool is used. The type column is set to a value when an assisting tool is used. For example, the type column stores a value of compression wear or an assisting suit. The elapsed time column stores the elapsed time from a reference time. The heart rate column stores the heart rate corresponding to the elapsed time. The date column stores the date when the slope and variance were measured or determined. The reference waveform DB 125 is created for each worker or for each worker attribute (age, sex, years of experience) and distributed to the wearable device 1 or worker terminal 3 of each worker. The determination process using the reference waveform DB 125 is similar to that in the second embodiment, and therefore will not be described.

[0076] In this embodiment, even when the worker uses an assisting tool, the worker's physical condition abnormality can be detected from the heart rate. Although the worker uses compression wear or an assisting suit when using an assisting tool, both compression wear and an assisting suit may be used as long as there are no problems or defects in use. In this case, the slope and variance when both are used are determined and stored in the constant DB 124. Also, reference waveform data when both are used is determined and stored in the reference waveform DB 125.

[0077] In all of the embodiments, it is assumed that there is only one supervisor terminal 2, but there may be multiple. In that case, it is assumed that it will be difficult for each wearable device 1 or each worker terminal 3 to communicate with multiple supervisor terminals 2. In that case, each wearable device 1 or each worker terminal 3 communicates with only one supervisor terminal 2, and that supervisor terminal 2 transfers alarms, etc. to the other supervisor terminals 2. In addition, the wearable devices 1 are divided into groups with the same number of supervisor terminals 2, and one supervisor terminal 2 and wearable devices 1 or worker terminals 3 are assigned to each group. Then, the wearable devices 1 or worker terminals 3 communicate with supervisor terminals 2 belonging to the same group.

[0078] In the physical condition management system 100, it is important that stable communication is possible between the wearable device 1 and the supervisor terminal 2 or the worker terminal 3. To stabilize the communication, a wireless repeater may be provided.

[0079] In the first embodiment, the information processing performed by the wearable device 1 may be performed by the supervisor terminal 2. Also, a server computer may be provided, the wearable device 1 and the server computer may communicate with each other, and some of the information processing performed by the wearable device 1 may be performed by the server computer. Also, the supervisor terminal 2 may communicate with the server computer, and heart rate data measured by the wearable device 1 may be sent to the server computer via the supervisor terminal 2, and the server computer may perform judgment processing, etc. In this case, an alarm may be output from the server computer to the supervisor terminal 2, or from the server computer via the wearable device 1 to the supervisor terminal 2.

[0080] In the third embodiment, the information processing performed by the physical condition management system 100 is shared between the wearable device 1 and the worker terminal 3, but this is not limited to the above. The processing may be performed by the supervisor terminal 2, or by a separately provided server computer. Even if the judgment processing and the like is performed by the supervisor terminal 2, the worker terminal 3, or the server computer, it is necessary to obtain heart rate data from the wearable device 1. Therefore, these computers can obtain the data by directly communicating with the wearable device 1, or via another computer.

[0081] The technical features (constituent elements) described in each embodiment can be combined with each other, and by combining them, new technical features can be formed. The embodiments disclosed herein are illustrative in all respects and should not be considered as limiting. The scope of the present invention is defined by the claims, not by the above meaning, and is intended to include all modifications within the scope and meaning equivalent to the claims. In addition, the claims are written in a format in which a claim cites two or more other claims (multiple claim format), but this is not limited to this format. The claims may be written in a format in which multiple claims cite at least one other claim (multi-multi claim format). [Explanation of symbols]

[0082] 100: Health Management System 1: Wearable devices 11: Control section 12: Storage section 121: Actual value DB 122: Heart rate database 123: Standard DB 124: Constant DB 125: Reference waveform DB 13: Biometric information acquisition unit 14: Motion detection unit 15: Communications Department 16: Timekeeping section 17: Display panel 18:Operation section 1P: Control program 2: Supervisor terminal 21: Control section 22: Main memory 23: Auxiliary storage section 24: Communications Department 25: Display panel 26:Operation section 2P: Control program 3: Worker terminal 31: Control section 32: Main memory 33:Auxiliary storage section 331: Actual value DB 332: Heart rate database 333: Standard DB 334: Constant DB 335: Reference waveform DB 34: Communications Department 35: Display panel 36:Operation unit 3P: Control program B: Bus N: Network

Claims

1. Obtaining a moving average value of the worker's heart rate at a predetermined time interval; determining whether the acquired time series data of the moving average value shows a decreasing trend within a predetermined range based on an initial value acquired at the start of work; If it is determined that the decreasing trend is not within the range of the predetermined width, an alarm is output. An information processing program that causes a computer to execute processing.

2. A first straight line is generated, the horizontal axis of which represents the elapsed time from the calculation of the initial value, the vertical axis of which represents the heart rate, and the first straight line has a predetermined negative slope and an intercept of the initial value; generating a second line and a third line parallel to the first line and spaced apart from the first line by the predetermined width; Calculating an average value of the heart rate for a predetermined time period, When the calculation time point is set as the elapsed time and the moving average value is plotted on a plane including the first line, the second line, and the third line, If the point to be drawn is not between the second line and the third line and is not on either the second line or the third line, it is determined that the trend is not decreasing within the range of the predetermined width. The information processing program according to claim 1 .

3. The inclination is determined according to the attributes of the worker. The information processing program according to claim 2.

4. The predetermined range is the variance of the heart rate distribution of the worker. The information processing program according to any one of claims 1 to 3.

5. The predetermined width is determined according to the attributes of the worker. The information processing program according to any one of claims 1 to 3.

6. The initial value is the average value for the first two minutes after the start of work. The information processing program according to any one of claims 1 to 3.

7. If the initial value is calculated in the morning and the work start time is in the afternoon, the initial value is changed to a value multiplied by a predetermined coefficient. The information processing program according to any one of claims 1 to 3.

8. Calculating a similarity between reference time series data of the heart rate associated with the ID and the work content of the worker and the time series data of the heart rate in a predetermined time period; If the calculated similarity exceeds a predetermined threshold, an alarm is output. The information processing program according to any one of claims 1 to 3.

9. The time length of the reference time series data is greater than the time interval, and the similarity is a DTW value. The information processing program according to claim 8.

10. an acquisition unit that acquires a moving average value of the worker's heart rate at a predetermined time interval; a determination unit that determines whether the acquired time series data of the moving average value shows a decreasing trend within a predetermined range based on an initial value acquired at the start of work; an output unit that outputs an alarm when it is determined that the decreasing trend is not within the range of the predetermined width; An information processing device comprising:

11. The computer Obtaining a moving average value of the worker's heart rate at a predetermined time interval; determining whether the acquired time series data of the moving average value shows a decreasing trend within a predetermined range based on an initial value acquired at the start of work; If it is determined that the decreasing trend is not within the range of the predetermined width, an alarm is output. An information processing method for performing a process.

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