Estimation device, estimation system, estimation method, and program

Abstract

Provided is an estimation device and the like that can improve the real time estimation of the level of fatigue. An estimation device (10) of an embodiment of the present disclosure comprises: a reception unit (110) that receives the change of the heart rate of a target person in a state, including a resting state and an active state, measured by a heart rate measurement device; a fatigue level estimation unit (120) that estimates the level of fatigue of the target person, on the basis of the change of the heart rate and an estimation model that estimates the fatigue level on the basis of the heart rate; and an output unit (130) that outputs the fatigue level.

Description

[Technical field]

[0001] The present disclosure relates to techniques for estimating heart rate. [Background technology]

[0002] Techniques for estimating a fatigue level that indicates the degree of fatigue of a person are disclosed in, for example, the following documents.

[0003] Patent Document 1 describes a method for calculating fatigue level based on the accumulation of exercise load. The fatigue level described in Patent Document 1 decays at a decay rate based on the number of days elapsed since that day and the number of rest days in between.

[0004] Patent Document 2 describes a method for calculating fatigue level from brain fatigue level based on fluctuations in heartbeat intervals and physical fatigue level based on the difference between the supine heart rate measured in a supine position and the standing heart rate measured in a standing position. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2018-033565 A [Patent Document 2] JP 2017-063963 A Summary of the Invention [Problem to be solved by the invention]

[0006] The method of Patent Document 1 requires obtaining an exercise load in order to calculate the degree of fatigue. Moreover, the method of Patent Document 1 does not allow the degree of fatigue to be calculated at short time intervals. The method of Patent Document 2 requires measuring the heart rate in a lying position and the heart rate in a standing position in order to calculate the degree of fatigue. In other words, the person whose degree of fatigue is to be calculated needs to perform a specific movement (i.e., the movement of lying down and the movement of standing up in this example) in order to calculate the degree of fatigue. Therefore, in order to calculate the degree of fatigue, at least the time required to measure the heart rate in a lying position and also to measure the heart rate in a standing position is required.

[0007] An object of the present disclosure is to provide an estimation device etc. that can improve the real-time performance of estimating a fatigue level. [Means for solving the problem]

[0008] An estimation device according to one aspect of the present disclosure includes a receiving means for receiving a trend in the heart rate of a target person in states including a resting state and an active state measured by a heart rate measuring device, an estimation model for estimating a fatigue level based on the heart rate, a fatigue level estimation means for estimating a fatigue level of the target person based on the trend in the heart rate, and an output means for outputting the fatigue level.

[0009] An estimation method according to one aspect of the present disclosure receives a trend in the heart rate of a target person in states including a resting state and an active state, measured by a heart rate measuring device, estimates a fatigue level of the target person based on an estimation model that estimates a fatigue level based on the heart rate and the trend in the heart rate, and outputs the fatigue level.

[0010] A storage medium according to an aspect of the present disclosure stores a program that causes a computer to execute a receiving process for receiving a transition of a heart rate of a target person in a state including a resting state and an active state, the transition being measured by a heart rate measuring device, an estimation model for estimating a fatigue level based on the heart rate, a fatigue level estimation process for estimating a fatigue level of the target person based on the transition of the heart rate, and an output process for outputting the fatigue level. One aspect of the present disclosure is also realized by the above-mentioned program. Effect of the Invention

[0011] The present disclosure has an effect of improving the real-time estimation of fatigue level. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a block diagram illustrating an example of a configuration of an estimation device 10 according to a first embodiment of the present disclosure. [Diagram 2] FIG. 2 is a flowchart illustrating an example of the operation of the estimation device 10 according to the first embodiment of the present disclosure. [Diagram 3] FIG. 3 is a block diagram illustrating an example of a configuration of an estimation system 1 according to the second embodiment of the present disclosure. [Figure 4] FIG. 4 is a block diagram illustrating an example of implementation of the estimation system 1 according to the second embodiment of the present disclosure. [Diagram 5] FIG. 5 is a diagram illustrating an example of a transition of the heart rate received by the receiving section 110 according to the second embodiment of the present disclosure. [Figure 6] FIG. 6 is a flowchart illustrating an example of the operation of the estimation device 100 according to the second embodiment of the present disclosure. [Figure 7] FIG. 7 is a flowchart illustrating an example of the operation of the estimation device 100 according to the modified example of the second embodiment of the present disclosure. [Figure 8] FIG. 8 is a flowchart showing the operation of the receiving process of the estimation device 100 according to the second embodiment of the present disclosure. [Figure 9] FIG. 9 is a diagram illustrating an example of the Borg index with respect to the estimated heart rate. [Figure 10] FIG. 10 is a diagram showing an example of the relationship between the measured maximum heart rate and the cardiopulmonary capacity attainment ratio. [Figure 11] FIG. 11 is a diagram showing another example of the relationship between the measured maximum heart rate and the cardiopulmonary capacity achievable ratio. [Figure 12] FIG. 12 is a diagram showing changes in heart rate and changes in exercise intensity. [Figure 13]FIG. 13 is a diagram showing changes in heart rate and changes in exercise intensity. [Figure 14] FIG. 14 is a diagram showing an example of a transition of the heart rate and an example of a straight line with a calculated slope. [Figure 15] FIG. 15 is a diagram illustrating an example of a hardware configuration of a computer 1000 capable of realizing each of the estimation devices according to the embodiments of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings.

[0014] <First embodiment> First, a first embodiment of the present disclosure will be described.

[0015] <Configuration> FIG. 1 is a block diagram illustrating an example of a configuration of an estimation device 10 according to a first embodiment of the present disclosure. In the example illustrated in FIG. 1, the estimation device 10 includes a receiving unit 110, a fatigue level estimation unit 120, and an output unit 130. The receiving unit 110 receives a transition of a heart rate of a target person in a state including a resting state and an active state, which is measured by a heart rate measurement device. The fatigue level estimation unit 120 estimates a fatigue level of the target person based on an estimation model that estimates a fatigue level based on a heart rate and the transition of the heart rate. The output unit 130 outputs the fatigue level.

[0016] The heart rate measuring device is, for example, a device that is provided in a wearable terminal and measures a heart rate. The transition of the heart rate is, for example, time series data of the heart rate per unit time calculated every predetermined time. The transition of the heart rate is time series data of the heart rate measured in at least one period. Each heart rate (specifically, the value of the heart rate) included in the transition of the heart rate may be associated with a value indicating the time at which the heart rate was measured. When the transition of the heart rate is time series data of the heart rate measured in two or more periods, at least one period may include multiple measurement time points, and the other periods may include only one measurement time point. The fatigue level estimation unit 120 estimates, for example, the fatigue level at the time when the heart rate included in the transition of the heart rate was measured. The estimation model and the method of estimating the fatigue level using the transition of the heart rate will be described in detail later.

[0017] <Operation> Fig. 2 is a flowchart showing an example of the operation of the estimation device 10 according to the first embodiment of the present disclosure. In the example shown in Fig. 2, the receiving unit 110 receives a change in the heart rate (step S10). In other words, the receiving unit 110 receives information representing the change in the heart rate. Next, the fatigue level estimation unit 120 estimates a fatigue level based on the estimation model and the change in the heart rate (step S11). Then, the output unit 130 outputs the estimated fatigue level (step S12).

[0018] <Effects> This embodiment has the effect of improving the real-time performance of fatigue level estimation. This is because the fatigue level estimation unit 120 estimates the fatigue level based on an estimation model and the transition of the heart rate of the target person in states including a resting state and an active state. If the transition of the heart rate of the target person in states including a resting state and an active state is obtained, there is no need to measure the heart rate again to estimate the fatigue level. Therefore, the estimation device 10 of this embodiment can improve the real-time performance of fatigue level estimation.

[0019] <Second embodiment> Next, a second embodiment of the present disclosure will be described in detail with reference to the drawings.

[0020] <Configuration> Fig. 3 is a block diagram showing an example of the configuration of an estimation system 1 according to a second embodiment of the present disclosure. In the example shown in Fig. 3, the estimation system 1 includes an estimation device 100, a heart rate measuring device 200, an output device 300, and a notification device 400. The estimation device 100 is communicatively connected to the heart rate measuring device 200, the output device 300, and the notification device 400.

[0021] <Heart rate measuring device 200> The heart rate measuring device 200 is, for example, a heart rate meter that measures the heart rate per unit time and outputs the measured heart rate per unit time, for example, at predetermined intervals. The heart rate measuring device 200 may transmit the measured heart rate to the estimation device 100 every time the heart rate is measured. The heart rate measuring device 200 may transmit the heart rate obtained by two or more measurements at once to the estimation device 100. In the following description, the heart rate measuring device 200 transmits the measured heart rate to the estimation device 100 every time the heart rate is measured. In addition, a time series of multiple heart rates measured by the heart rate measuring device 200 from the start of measurement of the heart rate to the interruption of measurement is referred to as a transition of the heart rate. As described above, the number of heart rates included in the transition of the heart rate may be one or may be two or more.

[0022] <Output device 300> The output device 300 is, for example, a display. The output device 300 may be an information processing device, such as a computer or a server, different from the estimation device 100. The output device 300 may be a terminal device whose screen can be viewed by an administrator who manages the target person.

[0023] <Notification device 400> The notification device 400 is a device that notifies a target person whose heart rate is being measured by the heart rate measurement device 200. The notification device 400 includes a display, a speaker, a vibrator, a light-emitting element, etc. The notification is performed by at least one of sound, light, vibration, text, images, etc. using the display, speaker, vibrator, light-emitting element, etc.

[0024] FIG. 4 is a block diagram that illustrates an example of implementation of the estimation system 1 according to the second embodiment of the present disclosure. In the example illustrated in FIG. 4, the above-mentioned heart rate measuring device 200 and notification device 400 are included in a wearable device 500. The heart rate measuring device 200 measures the heart rate of a target person wearing the wearable device 500. The notification device 400 notifies the target person wearing the wearable device 500. The wearable device 500 may be a walking assist robot. In the example illustrated in FIG. 4, the output device 300 is not included in the wearable device 500, but the output device 300 may also be included in the wearable device 500. The target person may be able to confirm the output by the output device 300. In this case, the output device 300 may operate as a notification device.

[0025] The notification device 400 may notify an administrator who manages the target person, instead of the target person. In this case, the notification device 400 may be, for example, a terminal device held by the administrator. The notification device 400 may be, for example, a terminal device whose screen can be viewed by the administrator.

[0026] <Estimation device 100> In the example shown in FIG. 3, the estimation device 100 includes a receiving unit 110, a fatigue level estimation unit 120, an output unit 130, an exercise intensity estimation unit 140, a settling time estimation unit 150, and a notification unit 160.

[0027] <Receiving section 110> The receiving unit 110 receives from the heart rate measuring device 200 the transition of the heart rate of the target person in a state including a resting state and an active state, which is measured by the heart rate measuring device 200. As described above, the transition of the heart rate received by the receiving unit 110 is the transition of the heart rate of the target person in a state including the measured resting state and the active state in at least one period. When the receiving unit 110 receives the transition of the heart rate for a plurality of periods, the transition of the heart rate for one or more periods may not include the transition of the heart rate measured in a state including a resting state and an active state. The transition of the heart rate that does not include the transition of the heart rate measured in a state including a resting state and an active state may include only the heart rate measured at one time point.

[0028] Fig. 5 is a diagram showing an example of a change in heart rate received by the receiving unit 110 according to the second embodiment of the present disclosure. Fig. 5 shows a change in heart rate measured when the target person is wearing a robot suit and a change in heart rate measured when the target person is not wearing a robot suit but is wearing a heart rate measuring device 200.

[0029] The receiving unit 110 sends the received change in the heart rate (specifically, information indicating the change in the heart rate) to the fatigue level estimating unit 120.

[0030] <Fatigue Level Estimation Unit 120> The fatigue level estimation unit 120 receives a transition of the heart rate (specifically, information representing the transition of the heart rate) from the receiving unit 110. The fatigue level estimation unit 120 estimates the fatigue level of the target person based on an estimation model for estimating the fatigue level based on the heart rate and the transition of the heart rate. Specifically, the fatigue level estimation unit 120 detects a measured maximum heart rate, which is the maximum heart rate in the transition of the heart rate, and a resting heart rate, which is the heart rate in a resting state, from the received transition of the heart rate. The resting heart rate is, for example, the minimum heart rate in the transition of the heart rate. The fatigue level estimation unit 120 estimates the fatigue level at the fatigue level estimation target time point based on the measured maximum heart rate, the resting heart rate, the heart rate at the fatigue level estimation target time point, and the estimation model. The fatigue level and a specific method for calculating the fatigue level will be described in detail later.

[0031] The fatigue level estimation target time point may be the time point at which the most recent heart rate was measured in the transition of the heart rate measured by the heart rate measuring device 200.

[0032] The fatigue level estimation unit 120 sends the estimated fatigue level to the output unit 130. The fatigue level estimation unit 120 may associate the estimated fatigue level with a time of a fatigue level estimation target time point, and send the fatigue level associated with the time of the fatigue level estimation target time point to the output unit 130.

[0033] The fatigue level estimation unit 120 sends the estimated fatigue level to the notification unit 160. The fatigue level estimation unit 120 may associate the estimated fatigue level with a time of a fatigue level estimation target time point, and send the fatigue level associated with the time of the fatigue level estimation target time point to the notification unit 160.

[0034] The fatigue level estimation unit 120 transmits information representing the transition of the heart rate and the fatigue level estimation target time to the exercise intensity estimation unit 140. The fatigue level estimation unit 120 also transmits information representing the measured maximum heart rate and information representing the resting heart rate to the exercise intensity estimation unit 140. The information representing the measured maximum heart rate is, for example, the value of the measured maximum heart rate and information specifying the time when the measured maximum heart rate was measured. The information representing the resting heart rate is, for example, the value of the resting heart rate and information specifying the time when the resting heart rate was measured. Note that the fatigue level estimation unit 120 may transmit information representing the heart rate at the fatigue level estimation target time to the exercise intensity estimation unit 140 instead of the information representing the transition of the heart rate and the fatigue level estimation target time. The information representing the heart rate at the fatigue level estimation target time may be information representing the transition of the heart rate and the fatigue level estimation target time.

[0035] <Exercise intensity estimation unit 140> The exercise intensity estimation unit 140 receives information representing a change in heart rate, information representing a fatigue level estimation target time point, information representing a measured maximum heart rate, and information representing a resting heart rate from the fatigue level estimation unit 120. The exercise intensity estimation unit 140 may receive information representing a heart rate at a fatigue level estimation target time point from the fatigue level estimation unit 120, instead of the information representing the change in heart rate and the fatigue level estimation target time point.

[0036] The exercise intensity estimation unit 140 estimates the exercise intensity at the intensity estimation target time based on the transition of the heart rate. Specifically, the exercise intensity estimation unit 140 estimates the exercise intensity at the intensity estimation target time based on the measured maximum heart rate, the resting heart rate, and the heart rate at the intensity estimation target time. The exercise intensity and the method of estimating the exercise intensity will be described in detail later.

[0037] The intensity estimation target time may be appropriately specified. The intensity estimation target time may be the same as the fatigue level estimation target time. In the following description, the intensity estimation target time is the same as the fatigue level estimation target time.

[0038] The exercise intensity estimation unit 140 sends the estimated exercise intensity to the output unit 130.

[0039] The exercise intensity estimation section 140 may send to the settling time estimation section 150 information indicating the transition of the heart rate, the fatigue level estimation target time point, information indicating the measured maximum heart rate, and information indicating the resting heart rate.

[0040] <Stationary time estimator 150> The settling time estimation section 150 receives from the exercise intensity estimation section 140 the transition of the heart rate, information indicating the fatigue level estimation target time point, information indicating the measured maximum heart rate, and information indicating the resting heart rate.

[0041] The settling time estimation unit 150 estimates the settling time based on the transition of the heart rate. The settling time is, for example, the time from the settling time estimation target time point until the target person's heart rate reaches the stable sitting state when the state of the target person transitions to a stable sitting state at the settling time estimation target time point. The settling time estimation unit 150 may determine the stable sitting state as a state in which the target person's heart rate becomes the resting heart rate. The settling time estimation unit 150 may determine the fatigue level estimation target time point as the settling time estimation target time point. A method for estimating the settling time will be described in detail later.

[0042] The settling time estimation unit 150 sends the estimated settling time to the output unit 130.

[0043] <Output unit 130> The output unit 130 receives the fatigue level from the fatigue level estimation unit 120. The output unit 130 receives the exercise intensity from the exercise intensity estimation unit 140. The output unit 130 receives the settling time from the settling time estimation unit 150.

[0044] The output unit 130 outputs the received fatigue level, exercise intensity, and settling time. For example, if the fatigue level estimation target time is the time when the most recent heart rate was measured in the received heart rate transition, and the intensity estimation target time is the same as the fatigue level estimation target time, the output unit 130 outputs the most recent fatigue level and exercise intensity. In this case, the heart rate measurement device 200 transmits the continuously measured heart rate to the estimation device 100, and the output unit 130 continuously outputs the fatigue level and exercise intensity, so that the fatigue level and exercise intensity can be known in real time. Also, as described above, the settling time estimation target time may be the same as the fatigue level estimation target time. Then, the output unit 130 may continuously output the settling time in addition to the fatigue level and exercise intensity.

[0045] <Notification section 160> The notification unit 160 receives the fatigue level from the fatigue level estimation unit 120. If the received fatigue level indicates that fatigue is greater than a predetermined level, the notification unit 160 notifies the target person. Specifically, the notification unit 160 determines whether the received fatigue level indicates that fatigue is greater than a predetermined level by comparing the value of the received fatigue level with a threshold value representing the predetermined level. If the received fatigue level indicates that fatigue is greater than the predetermined level, the notification unit 160 controls the notification device 400 so that the notification device 400 issues a notification. More specifically, the notification unit 160 transmits, for example, an instruction to issue a notification to the notification device 400. The notification device 400 that has received the instruction to issue a notification issues a notification to the target person.

[0046] <Operation> Next, the operation of the estimation device 100 according to the second embodiment of the present disclosure will be described in detail with reference to the drawings.

[0047] FIG. 6 is a flowchart illustrating an example of the operation of the estimation device 100 according to the second embodiment of the present disclosure.

[0048] In the example shown in FIG. 6, the receiving unit 110 receives a change in the heart rate from the heart rate measuring device 200 (step S101). Next, the fatigue level estimation unit 120 estimates a fatigue level based on the estimation model and the change in the heart rate (step S102). The exercise intensity estimation unit 140 estimates an exercise intensity based on the change in the heart rate (step S103). The settling time estimation unit 150 estimates a settling time based on the change in the heart rate (step S104). Then, the output unit 130 outputs the fatigue level and the exercise intensity (step S105). The output unit 130 also outputs the settling time (step S106). Note that the output unit 130 may perform the operation of step S105 and the operation of step S106 together. If the fatigue level is not greater than the reference level (NO in step S107), that is, if the fatigue level does not indicate fatigue greater than a predetermined level, the estimation device 100 ends the operation shown in FIG.

[0049] If the fatigue level is greater than the reference level (YES in step S107), that is, if the fatigue level does not indicate that fatigue is greater than the predetermined level, the notification unit 160 performs notification (step S108). Then, the estimation device 100 ends the operation shown in FIG.

[0050] <Effects> The present embodiment described above in relation to the abnormality has the same effect as the first embodiment, for the same reason that the effect of the first embodiment is obtained.

[0051] <Modification of the second embodiment> The receiving unit 110 may send the received change in the heart rate (specifically, information indicating the change in the heart rate) to the exercise intensity estimation unit 140. In this case, the fatigue level estimation unit 120 does not need to send the change in the heart rate to the exercise intensity estimation unit 140. The fatigue level estimation unit 120 does not need to send the measured maximum heart rate and the resting heart rate to the exercise intensity estimation unit 140. In that case, the exercise intensity estimation unit 140 detects the measured maximum heart rate and the resting heart rate in the received change in the heart rate.

[0052] The receiving unit 110 may send the received transition of the heart rate (specifically, information indicating the transition of the heart rate) to the settling time estimation unit 150. In this case, the exercise intensity estimation unit 140 does not need to send the transition of the heart rate to the settling time estimation unit 150. In addition, the exercise intensity estimation unit 140 does not need to send the measured maximum heart rate to the settling time estimation unit 150. In this case, the settling time estimation unit 150 detects the measured maximum heart rate in the transition of the heart rate received.

[0053] In the operation shown in FIG. 6, the receiving unit 110 receives the transition of the heart rate in step S101, but the receiving unit 110 may receive the heart rate, for example, continuously. Then, for example, the fatigue level estimation unit 120 may store the received heart rate. In other words, the fatigue level estimation unit 120 may generate data representing the transition of the heart rate from the multiple heart rates received. Then, the fatigue level estimation unit 120 may hold the data representing the transition of the heart rate. When the fatigue level estimation unit 120 receives the heart rate, the fatigue level estimation unit 120 may update the transition of the heart rate by adding the received heart rate to the end of the transition of the heart rate. The fatigue level estimation unit 120 may estimate the fatigue level as described above based on the transition of the held heart rate. In this case, receiving multiple heart rates corresponds to receiving the transition of the heart rate. Then, in this case, instead of step S101 in FIG. 6, the receiving unit 110 receives the heart rate, and the fatigue level estimation unit 120 updates the transition of the held heart rate using the received heart rate. FIG. 7, described below, illustrates an example of the operation of the estimating device 100 in this case.

[0054] FIG. 7 is a flowchart illustrating an example of the operation of the estimation device 100 according to the modified example of the second embodiment of the present disclosure.

[0055] The operation shown in Fig. 7 differs from the operation shown in Fig. 6 in that the operation of step S201 is performed instead of step S101. In step S201, the estimation device 100 performs a receiving process. In operations from step S102 onwards, the estimation device 100 performs the same operations as the operations from step S102 onwards shown in Fig. 6. Every time the estimation device 100 receives a heart rate from the heart rate measurement device 200, it repeats the operation of Fig. 7.

[0056] Fig. 8 is a flowchart showing the operation of the receiving process of the estimation device 100 according to the second embodiment of the present disclosure. In the example shown in Fig. 8, first, the receiving unit 110 receives the heart rate from the heart rate measuring device 200 (step S211). Specifically, the receiving unit 110 receives information indicating the heart rate from the heart rate measuring device 200. Next, the fatigue level estimation unit 120 updates the transition of the heart rate using the received heart rate (step S212). Specifically, the fatigue level estimation unit 120 updates the transition of the heart rate by adding the received heart rate to the end of the transition of the heart rate.

[0057] <Effects> This embodiment has the same effects as the first embodiment, for the same reasons that the effects of the first embodiment are obtained.

[0058] This embodiment has the effect of preventing the target person from becoming overworked, etc. This is because the notification unit 160 issues a notification when the target person's fatigue level indicates that the fatigue level is greater than a predetermined level.

[0059] <Fatigue level and exercise intensity> The fatigue level in the present disclosure will be described in detail below.

[0060] The Borg scale fatigue level is known as a measure of fatigue. The Borg scale is an index that subjectively evaluates a subject's own sensations during exercise, and is recognized in clinical studies, taking into account the individual's physical strength, environment, and general fatigue factors. The Borg scale fatigue level, which is an example of the Borg scale, is an index that expresses the degree of fatigue on a 15-level scale, with each level representing 10 heartbeats, assuming a resting heart rate of 60 and a maximum estimated heart rate of 220. The maximum estimated heart rate is the heart rate estimated as the maximum heart rate. The Borg scale fatigue level is known as an exercise evaluation index that matches the actual situation even in actual exercise measurements. There is also a modified Borg index that explains nonlinear indicators such as the change in blood lactate level and oxygen saturation. The stages of the Borg scale fatigue level are determined based on the ratio of the heart rate to the maximum heart rate. In the Borg scale fatigue level, it is assumed that the heart rate in a slightly hard state is 60% of the maximum estimated heart rate, and the heart rate in a hard state is 85% of the maximum estimated heart rate. The relationship between heart rate and the percentage of maximum estimated heart rate used in the Borg scale of fatigue is given by the following formula:

[0061]

number

[0062] In the formula 1, a represents the age of the target person, and Y Borg [%] represents the percentage of the maximum estimated heart rate, and X^ (i.e., the variable with a hat above X) represents the heart rate. Borg When [%] is specified, the individual's heart rate X^ can be estimated. In the following explanation, Y Borg [%] is expressed as the Borg index. Borg Since it is possible to estimate an individual's heart rate X^ when [%] is specified, X^ is also denoted as the estimated heart rate.

[0063] The formula 1 can be transformed into the following formula:

[0064]

number

[0065] In the formula 2, k age corresponds to the slope of the line determined by age. age is smaller the younger the age.

[0066] Fig. 9 is a diagram showing an example of the Borg index with respect to the estimated heart rate. Fig. 9 shows the relationship between the estimated heart rate and the Borg index for two people of different ages.

[0067] FIG. 10 is a diagram showing an example of the relationship between the measured maximum heart rate and the cardiopulmonary capacity attainment ratio. The cardiopulmonary capacity attainment ratio is the ratio of the heart rate to the cardiopulmonary limit when the heart rate obtained by subtracting the age from 220 is the limit of cardiopulmonary capacity (hereinafter also referred to as the cardiopulmonary limit). FIG. 10 plots heart rates measured under various conditions. "With Wear" in FIG. 10 indicates that the measurement was made with the walking assist robot worn. "Without Wear" indicates that the measurement was made without the walking assist robot worn.

[0068] FIG. 11 is a diagram showing another example of the relationship between the measured maximum heart rate and the cardiopulmonary capacity achievable ratio.

[0069] The subjective index indicated by the Borg index for the maximum heart rate measured by the subject during the heart rate measurements shown in Figs. 10 and 11 was almost consistent with the subjective state, so it is estimated that the Borg index provides a reasonable subjective index of subjective symptoms to some extent.

[0070] In the formulas 1 and 2, X^ and Y Borg When the expansion is made such that [%] and are the heart rate and Borg index measured at time t, Equation 1 is expressed as follows:

[0071]

number

[0072] Furthermore, Y Borg (t) [%] is the ratio of cardiopulmonary capacity at the heart rate measured at time t to the cardiopulmonary capacity at the time the maximum estimated heart rate was observed, using the resting heart rate as the baseline, within the range of the observed maximum heart rate and resting heart rate, according to the definition of the Borg scale. Y Bo rg (t) [%] is also expressed as the rate of cardiopulmonary capacity attainment or the rate of maximum cardiopulmonary capacity attainment. Therefore, Y Borg (t) [%] is equivalent to the cardiopulmonary capacity contrast of heart rate at time t in the maximum observed heart rate range based on the resting heart rate before exercise. X the maximum observed heart rate max Let us denote the observed resting heart rate as X min It is written as Y Borg (t) [%] is expressed by the following formula.

[0073]

number

[0074] In equation 4, x(t) represents the heart rate measured at time t.

[0075] By the way, at time t, there are two types of exercise intensity: aerobic exercise intensity VO 2max From the definition, it is expressed as follows:

[0076]

number

[0077] From equations 2 and 4, the following equation is obtained.

[0078]

number

[0079] Let the numerator and denominator on the right hand side of number 6 be x max -x min Dividing by gives:

[0080]

number

[0081] Equation 7 is converted into VO 2max When expressed by:

[0082]

number

[0083] The following formulas are parameters used in transforming equation 8.

[0084]

number

[0085] The following equation is obtained by rewriting equation 8 using the parameters shown in equation 9.

[0086]

number

[0087] Formula 10 is expressed as VO 2max The equation is transformed so that (t) is on the left side, resulting in the following equation.

[0088]

number

[0089] As shown in Equation 11, aerobic exercise intensity VO 2max [%] is the Borg estimated heart rate x(t) as a variable. , age parameter with coefficient α and individual cardiopulmonary capacity (maximum observed heart rate x max) and resting heart rate x min ) can be expressed as a simple linear function. Calculations are performed according to the formulas 4 and 11. This makes it possible to quantify exercise intensity taking into account each individual's cardiopulmonary capacity, rather than just age criteria as in the conventional Borg index, and to perform subjective evaluation based on the Borg index in real time.

[0090] The fatigue level estimation unit 120 estimates the fatigue level according to the formula 4. Specifically, the fatigue level estimation unit 120 estimates the maximum value of the heart rate in the transition of the heart rate (i.e., x max ) is detected as the measured maximum heart rate, and the minimum heart rate in the heart rate transition (i.e., x min ) as the resting heart rate. The fatigue level estimation unit 120 uses the heart rate x(t) at the fatigue level estimation target time point (i.e., time t) to calculate the cardiopulmonary capacity achievement rate Y Bo rg The fatigue level estimation unit 120 calculates the calculated cardiopulmonary capacity achievement rate Y Borg The fatigue level corresponding to (t) is regarded as the fatigue level at the time point of fatigue level estimation.

[0091] Fig. 11 is a diagram showing the relationship between the cardiopulmonary capacity achievement rate and examples of indices. Fig. 11 shows the relationship between the cardiopulmonary capacity achievement rate and the Borg index and the modified Borg index. The fatigue level estimation unit 120 determines, for example, an index (for example, the Borg index or the modified Borg index) corresponding to a range that includes the calculated city capacity achievement rate as the fatigue level.

[0092] The exercise intensity estimation unit 140 calculates, for example, VO 2max (t) and calculate the aerobic exercise intensity VO 2max Let (t) be the exercise intensity. The exercise intensity estimation unit 140 may first calculate the parameter k in the formula (10) and store the calculated parameter k. Then, the exercise intensity estimation unit 140 uses the stored parameter k and the heart rate (X^(t)) at the intensity estimation target time point (i.e., time t) to calculate the aerobic exercise intensity VO 2max (t) may be calculated.

[0093] <Settlement time> In the above description of the settling time estimation unit 150, the heart rate transition was measured to include the heart rate transition measured from when the target person reaches a resting state in a state of the maximum heart rate until the target person's heart rate reaches the resting heart rate. However, even if the heart rate transition is not measured in this manner, the settling time estimation unit 150 can estimate the settling time, for example, as follows.

[0094] The settling time estimation unit 150 detects a maximum value and a minimum value of the heart rate in the transition of the heart rate. The settling time estimation unit 150 calculates a gradient of the change in the heart rate between the detected maximum value and the next minimum value detected in the time direction from the time when the maximum value was observed. The settling time estimation unit 150 may calculate a gradient of the change in the heart rate between the detected maximum value and the next minimum value detected after a predetermined time or more has elapsed from the time when the maximum value was observed. The settling time estimation unit 150 may smooth the transition of the heart rate and detect the maximum value and the minimum value in the transition of the heart rate after the smoothing. When multiple gradients are calculated, the settling time estimation unit 150 calculates a statistical value (for example, an average value, a median value, or a median value) of the calculated gradients.

[0095] The settling time estimation unit 150 calculates the time required for the heart rate to reach the heart rate in the stable sitting state when the heart rate decreases at a rate of decrease represented by the calculated slope from the heart rate (x(t)) measured at the settling time estimation target time point (time t). The settling time estimation unit 150 may determine the minimum value of the heart rate in the transition of the heart rate as the heart rate in the stable sitting state.

[0096] The settling time estimation unit 150 may apply the transition of the heart rate between the above-mentioned maximum value and minimum value to an equation other than a straight line (for example, a polynomial of time). Specifically, the settling time estimation unit 150 calculates parameters of a polynomial that represents the transition of the heart rate between the maximum value and the minimum value. The settling time estimation unit 150 calculates the time until the heart rate reaches the heart rate in a stable sitting state when the heart rate decreases according to the polynomial based on the calculated parameters from the heart rate (x(t)) measured at the settling time estimation target time point (time t).

[0097] The settling time estimation unit 150 can also calculate the settling time based on the transition of the exercise intensity calculated from the transition of the heart rate. The settling time estimation unit 150 detects the maximum value and the minimum value in the transition of the exercise intensity, calculates the slope as described above, and calculates the statistical value of the slope. When the exercise intensity decreases according to the statistical value of the calculated slope from the value of the exercise intensity calculated from the heart rate (x(t)) measured at the settling time estimation target time point (time t), the settling time estimation unit 150 calculates the time until the exercise intensity becomes zero as the settling time.

[0098] 12 and 13 are diagrams showing the transition of heart rate and the transition of exercise intensity when wearing a walking assist suit (also referred to as a Robosuit) and when not wearing the suit.

[0099] FIG. 14 is a diagram showing an example of the transition of the heart rate and an example of a straight line with a calculated slope. In the example shown in FIG. 14, the slope of the straight line is calculated at two points. The settling time calculated from the two slopes is T s1 and T s2 It is.

[0100] <About the effects> The effects of the second embodiment of the present disclosure will be further described.

[0101] As mentioned above, the characteristics of the relationship between the time series and heart rate during exercise are expressed by the exercise intensity [%]. Furthermore, the Borg scale subjective symptoms and VO2max numerical information can be displayed in real time using only the heart rate observation data y(t). This has the effect that not only the person but also the observer can easily grasp the subject's remaining physical strength and subjective symptoms, and can easily determine whether the subject is reaching an excessive load or exercise on the heart and lungs. This has the effect of increasing cardiopulmonary capacity and residual cardiopulmonary capacity.

[0102] Furthermore, the time it takes to settle from the maximum heart rate to sitting stability is not determined by the amount of exercise (length of exercise) or load (robot load), but by the time it takes to settle from the maximum heart rate to sitting stability. The relationship between the time it takes to settle down and the exercise intensity [%] for the heart rate to return to the original value at the same walking speed was It is almost linear, and if we approximate it with a polynomial with time t as a variable, The settling time (Ts) can be easily estimated. The inverse of the settling time is the rate at which the subject recovers (body This can be quantified as the strength of force recovery.

[0103] When the relationship between exercise intensity expressed by VO2max and the estimated heart rate based on the Borg index is found, the slope of the line is equivalent to the degree of load as numerical information, and the level of load that directly leads to fatigue can be quantified as a numerical value by comparing the slopes of the lines. By incorporating these relationship equations into the system and linking it with a wearable heart rate monitor, for the same subject, the exercise intensity at that time can be found only from the heart rate measured in real time, which has the effect of quantitatively understanding the current level of use of each individual's maximum cardiopulmonary capacity.

[0104] In addition, in the Borg index, only the age parameter was considered as personal information, but in this embodiment, the expanded Borg index can calculate the cardiopulmonary capacity ratio at time t to the individual's maximum cardiopulmonary capacity only from the individual's maximum heart rate, resting heart rate data, and heart rate at time t, so that the cardiopulmonary capacity ratio determined in advance by the Borg index can be used to understand the individual's cardiopulmonary capacity closer to the current state. Furthermore, the subjective fatigue awareness at time t can be displayed based on the cardiopulmonary ratio determined by the Borg index, so that a third party other than the subject can easily understand the subject's fatigue level during exercise.

[0105] <Other embodiments> The above-mentioned estimation device 10 and estimation device 100 can be realized by a computer including a memory in which a program read from a storage medium is loaded and a processor that executes the program. The estimation device 10 and estimation device 100 can also be realized by dedicated hardware. The estimation device 10 and estimation device 100 can also be realized by a combination of the above-mentioned computer and dedicated hardware.

[0106] FIG. 15 is a diagram illustrating an example of a hardware configuration of a computer 1000 capable of realizing each of the estimation devices according to the embodiment of the present disclosure. In the example illustrated in FIG. 15, the computer 1000 includes a processor 1001, a memory 1002, a storage device 1003, and an I / O (Input / Output) interface 1004. The computer 1000 can also access a storage medium 1005. The memory 1002 and the storage device 1003 are, for example, storage devices such as a RAM (Random Access Memory) and a hard disk. The storage medium 1005 is, for example, a storage device such as a RAM or a hard disk, a ROM (Read Only Memory), or a portable storage medium. The storage device 1003 may be the storage medium 1005. The processor 1001 can read and write data and programs from the memory 1002 and the storage device 1003. The processor 1001 can access, for example, a heart rate measurement device 200, an output device 300, and a notification device 400 via the I / O interface 1004. The processor 1001 can access a storage medium 1005. The storage medium 1005 stores a program that causes the computer 1000 to operate as an estimation device according to an embodiment of the present disclosure.

[0107] The processor 1001 loads a program stored in the storage medium 1005, which causes the computer 1000 to operate as an estimation device according to an embodiment of the present disclosure, into the memory 1002. Then, the processor 1001 executes the program loaded into the memory 1002, causing the computer 1000 to operate as the estimation device according to an embodiment of the present disclosure.

[0108] The receiving unit 110, the fatigue level estimation unit 120, the output unit 130, the exercise intensity estimation unit 140, the settling time estimation unit 150, and the notification unit 160 can be realized, for example, by a processor 1001 that executes a program loaded into a memory 1002. Some or all of the receiving unit 110, the fatigue level estimation unit 120, the output unit 130, the exercise intensity estimation unit 140, the settling time estimation unit 150, and the notification unit 160 can also be realized by a dedicated circuit that realizes the function of each unit.

[0109] Furthermore, some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes.

[0110] (Appendix 1) A receiving means for receiving a transition of a heart rate of a subject person in a state including a resting state and an active state, the transition being measured by a heart rate measuring device; an estimation model for estimating a fatigue level based on a heart rate and a fatigue level estimation means for estimating a fatigue level of the target person based on a transition of the heart rate; an output means for outputting the fatigue level; An estimation device comprising:

[0111] (Appendix 2) The estimation model estimates the fatigue level based on a measured maximum heart rate, which is a maximum heart rate in the transition of the heart rate, and a resting heart rate, which is a heart rate in the resting state. 2. An estimation apparatus as described in claim 1.

[0112] (Appendix 3) The estimation model estimates the fatigue level at a fatigue level estimation target time point further based on a heart rate at the fatigue level estimation target time point. 3. An estimation apparatus as described in claim 2.

[0113] (Appendix 4) an exercise intensity estimation means for estimating exercise intensity at an intensity estimation target time point based on the change in the heart rate; Equipped with The output means further outputs the exercise intensity. 4. The estimation device according to claim 1 ,

[0114] (Appendix 5) The fatigue level estimation means estimates the fatigue level at a time when the most recent heart rate is measured based on the most recent heart rate, the exercise intensity estimation means estimates the exercise intensity at the time when the most recent heart rate was measured based on the most recent heart rate; The output means outputs the fatigue level and the exercise intensity at the time when the most recent heart rate was measured. 5. An estimation apparatus as described in claim 4.

[0115] (Appendix 6) a resting time estimation means for estimating a resting time, which is a time from a resting time estimation target time point until the heart rate of the target person reaches the resting state, when the state of the target person transitions to the resting state at the resting time estimation target time point based on the transition of the measured heart rate; 6. The estimation device according to claim 1, comprising:

[0116] (Appendix 7) A notification means for notifying the user when the degree of fatigue indicates that the fatigue level is greater than a predetermined level. 7. The estimation device according to any one of claims 1 to 6, further comprising:

[0117] (Appendix 8) The heart rate measuring device; An estimation device according to any one of appendix 1 to 7; An estimation system comprising:

[0118] (Appendix 9) receiving a progression of the subject's heart rate over states including resting and active states as measured by a heart rate measuring device; Estimating a fatigue level of the target person based on an estimation model that estimates a fatigue level based on a heart rate and a transition of the heart rate; outputting the fatigue level; Estimation method.

[0119] (Appendix 10) The estimation model estimates the fatigue level based on a measured maximum heart rate, which is a maximum heart rate in the transition of the heart rate, and a resting heart rate, which is a heart rate in the resting state. Estimation method described in Appendix 9.

[0120] (Appendix 11) The estimation model estimates the fatigue level at a fatigue level estimation target time point further based on a heart rate at the fatigue level estimation target time point. Estimation method described in Appendix 10.

[0121] (Appendix 12) Estimating exercise intensity at an intensity estimation target time point based on the change in heart rate; The exercise intensity is further output. 12. The estimation method according to any one of claims 9 to 11.

[0122] (Appendix 13) estimating the fatigue level at the time when the most recent heart rate was measured based on the most recent heart rate; estimating the exercise intensity at the time when the most recent heart rate was measured based on the most recent heart rate; outputting the fatigue level and the exercise intensity at the time when the most recent heart rate was measured; Estimation method described in Appendix 12.

[0123] (Appendix 14) Based on the change in the measured heart rate, a stillness time is estimated, which is a time from a stillness time estimation target time point until the heart rate of the target person changes to the resting state when the state of the target person changes to the resting state at the stillness time estimation target time point. 14. The estimation method according to any one of claims 9 to 13.

[0124] (Appendix 15) If the fatigue level indicates fatigue greater than a predetermined level, a notification is provided. 15. The estimation method according to any one of claims 9 to 14.

[0125] (Appendix 16) A receiving process for receiving a progression of the subject's heart rate in states including a resting state and an active state, the progression being measured by a heart rate measuring device; a fatigue level estimation process for estimating a fatigue level of the target person based on an estimation model that estimates a fatigue level based on a heart rate and a transition of the heart rate; an output process for outputting the fatigue level; A storage medium that stores a program that causes a computer to execute the above.

[0126] (Appendix 17) The estimation model estimates the fatigue level based on a measured maximum heart rate, which is a maximum heart rate in the transition of the heart rate, and a resting heart rate, which is a heart rate in the resting state. 17. The storage medium of claim 16.

[0127] (Appendix 18) The estimation model estimates the fatigue level at a fatigue level estimation target time point further based on a heart rate at the fatigue level estimation target time point. 18. The storage medium of claim 17.

[0128] (Appendix 19) The program is An exercise intensity estimation process for estimating the exercise intensity at the intensity estimation target time point based on the change in the heart rate. on the computer, The output process further outputs the exercise intensity. 19. A storage medium according to any one of appendixes 16 to 18.

[0129] (Appendix 20) the fatigue level estimation process includes estimating the fatigue level at a time point when the most recent heart rate was measured based on the most recent heart rate; the exercise intensity estimation process estimates the exercise intensity at the time when the most recent heart rate was measured based on the most recent heart rate; The output process outputs the fatigue level and the exercise intensity at the time when the most recent heart rate is measured. 20. The storage medium of claim 19.

[0130] (Appendix 21) The program is A stillness time estimation process for estimating a stillness time, which is a time from a stillness time estimation target time until the heart rate of the target person reaches the resting state, when the state of the target person transitions to the resting state at the stillness time estimation target time based on the transition of the measured heart rate. 21. A storage medium according to any one of appendices 16 to 20, which causes a computer to execute the above.

[0131] (Appendix 22) The program is A notification process for notifying the user when the fatigue level indicates that the fatigue level is greater than a predetermined level. 22. The storage medium according to any one of appendices 16 to 21, further causing a computer to execute the steps.

[0132] Although the present invention has been described above with reference to the embodiment, the present invention is not limited to the above embodiment. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. [Explanation of symbols]

[0133] 1. Estimation System 10 Estimation device 100 Estimator 110 Receiving Department 120 Fatigue Level Estimation Unit 130 Output section 140 Exercise intensity estimation part 150 Static time estimation part 160 Notification Department 200 Heart Rate Measuring Device 300 Output Device 400 Notification device 500 Wearable Devices 1000 Computers 1001 Processor 1002 Memory 1003 Storage device 1004 I / O Interface 1005 Storage medium

Claims

1. A receiving means for receiving a transition of a heart rate of a subject person in a state including a resting state and an active state, the transition being measured by a heart rate measuring device; an estimation model for estimating a fatigue level based on a heart rate and a fatigue level estimation means for estimating a fatigue level of the target person based on a transition of the heart rate; exercise intensity estimation means for estimating exercise intensity at an intensity estimation target time point based on the change in heart rate; a settling time estimation means for estimating a settling time, which is a time from a settling time estimation target time point until the target person's heart rate reaches the resting state, when the target person's state has transitioned to the resting state at the settling time estimation target time point, based on a transition of the exercise intensity calculated from the transition of the measured heart rate; an output means for outputting the fatigue level and the exercise intensity; An estimation device comprising:

2. The estimation model estimates the fatigue level based on a measured maximum heart rate, which is a maximum heart rate in the transition of the heart rate, and a resting heart rate, which is a heart rate in the resting state. The estimation device according to claim 1 .

3. The estimation model estimates the fatigue level at a fatigue level estimation target time point further based on a heart rate at the fatigue level estimation target time point. The estimation device according to claim 2 .

4. The fatigue level estimation means estimates the fatigue level at a time when the most recent heart rate is measured based on the most recent heart rate, the exercise intensity estimation means estimates the exercise intensity at the time when the most recent heart rate was measured based on the most recent heart rate; The output means outputs the fatigue level and the exercise intensity at the time when the most recent heart rate was measured. The estimation device according to any one of claims 1 to 3.

5. A notification means for notifying the user when the degree of fatigue indicates that the fatigue level is greater than a predetermined level. The estimation device according to claim 1 , further comprising:

6. The heart rate measuring device; An estimation device according to any one of claims 1 to 5; An estimation system comprising:

7. receiving a progression of the subject's heart rate over states including resting and active states as measured by a heart rate measuring device; Estimating a fatigue level of the target person based on an estimation model that estimates a fatigue level based on a heart rate and a transition of the heart rate; Estimating exercise intensity at an intensity estimation target time point based on the change in heart rate; based on the transition of the exercise intensity calculated from the transition of the measured heart rate, estimating a stillness time, which is a time from the stillness time estimation target time point until the heart rate of the target person reaches the resting state, in a case where the state of the target person transitions to the resting state at the stillness time estimation target time point; outputting the fatigue level and the exercise intensity; Estimation method.

8. A receiving process for receiving a progression of the subject's heart rate in states including a resting state and an active state, the progression being measured by a heart rate measuring device; a fatigue level estimation process for estimating a fatigue level of the target person based on an estimation model that estimates a fatigue level based on a heart rate and a transition of the heart rate; an exercise intensity estimation process for estimating an exercise intensity at an intensity estimation target time point based on the change in the heart rate; a settling time estimation process for estimating a settling time, which is a time from a settling time estimation target time point until the target person's heart rate reaches the resting state, when the target person's state has transitioned to the resting state at the settling time estimation target time point based on a transition of the exercise intensity calculated from the transition of the measured heart rate; an output process for outputting the fatigue level and the exercise intensity; A program that causes a computer to execute the following.

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