WO2016039241A1

WO2016039241A1 - Method for estimating running intensity favorable for training and running assistance device

Info

Publication number: WO2016039241A1
Application number: PCT/JP2015/074990
Authority: WO
Inventors: 好二郎石井
Original assignee: 学校法人同志社
Priority date: 2014-09-10
Filing date: 2015-09-02
Publication date: 2016-03-17
Also published as: JPWO2016039241A1

Abstract

The present invention addresses the problem of providing a method for estimating running intensity favorable for training without drawing blood and a running assistance device for assisting in running at a running intensity that is favorable for training without drawing blood. This method for estimating comprises finding a second maximum stride, which is the stride when the heartrate is the maximum heartrate, on the basis of strides and heartrates measured when running multiple times at different running speeds, and estimating an estimated LT stride, which is the stride when running at the lactate threshold (first estimating step S1B to fourth estimating step S4B). The lactate threshold is the product of the second maximum stride and a predetermined ratio (for example, a ratio found from first preparation step S1A to fifth preparation step S5A).

Description

Running intensity estimation method suitable for training and running support device

The present invention relates to a running strength estimation method suitable for training and a running support device that supports running at a running strength suitable for training.

In Japan, running enthusiasts (hereinafter simply referred to as “runners”) are increasing year by year as health consciousness increases. And there are many runners who are trying full marathon in earnest, and the number of runners in the marathon event recognized by the Japan Land Federation has doubled between FY2004 and FY2009. It is said. This phenomenon, which can also be called a running boom, is expected to expand further in the future.

By the way, it is known that in order to improve the marathon recording (performance), it is necessary to improve the maximum oxygen intake (VO ₂ max). For this purpose, the running intensity equal to the lactic acid work threshold is used. It is said that it is effective to perform training with a running intensity exceeding the lactate work threshold (for example, see Non-Patent Document 1). As shown in FIG. 18, when the running strength is increased, the oxidation cannot catch up with the production of lactic acid, and the lactic acid concentration in blood (hereinafter referred to as “lactic acid level”) increases rapidly. When this rapid increase is observed, that is, when the straight line C1 and the straight line C2 intersect, the running intensity is referred to as a lactic acid work threshold.

On the other hand, training with a running intensity exceeding the lactate work threshold places an excessive burden on the heart. Therefore, in order to improve marathon recording, it is desirable to perform training with a running intensity equal to the lactic acid work threshold. Training with a running intensity equal to the lactic acid work threshold has the advantage that lipids and carbohydrates can be consumed in a balanced manner.

In addition, the lactic acid work threshold is often called “LT” after the initial of Lactate Threshold. Hereinafter, in this specification, the lactic acid work threshold is referred to as LT.

However, it is necessary to collect blood in order to measure LT. For this reason, it is very difficult for many runners to know the relationship between the running intensity of training performed by themselves and LT.

The present invention has been made in view of such a situation, and the problem is that an estimation method for estimating a running intensity suitable for training without blood collection, and suitable for training without blood collection. An object of the present invention is to provide a running support device that supports running at a strong running intensity.

In order to solve the above-described problem, a running support device according to the present invention includes:
(1) An input unit that accepts an input of the runner's age, (2) a position measuring unit that measures the position of the runner during running, and (3) a runner's stride based on the change in position measured by the position measuring unit. A stride calculation unit for calculating the heart rate, (4) a heart rate measurement unit for measuring the heart rate during or immediately after the run of the runner, and (5) the age input from the input unit, and the relationship between the age and the maximum heart rate A storage unit storing a relational expression, a stride obtained by the stride calculation unit, a heart rate measured by the heart rate measurement unit, and a predetermined ratio; and (6) a runner while referring to the storage unit. A calculation unit for determining the degree of coincidence between the current stride and the LT stride that is a stride when the runner runs at the lactic acid work threshold, and (7) the calculation unit The degree of coincidence obtained Te and a notifying unit for notifying the runner,
The calculation unit creates a regression line (“second regression line” in the embodiment) from the stride and heart rate when the runner performs a plurality of runs at different running speeds as advance preparations, as well as age and relational expressions. The maximum stride (“second maximum stride” in the embodiment) corresponding to the maximum heart rate determined from (the “second maximum heart rate” in the embodiment) is calculated based on the regression line, and the calculation unit When the runner is running as a training, the LT stride is estimated by the product of the maximum stride obtained in advance and the ratio stored in the storage unit, and the LT stride and the current stride are calculated in real time. It is characterized by comparing.

The ratio stored in the storage unit of the running support device can be determined experimentally, for example, by executing the following first to fifth preparation steps.
(1A) A first preparation step of causing a subject to perform a plurality of times of running with different running speeds and measuring a stride during each running and a heart rate and a lactate value during or immediately after each running.
(2A) A second preparation step of calculating an actual LT heart rate, which is a heart rate when the subject runs at the lactic acid work threshold based on the heart rate and the lactic acid value measured in the first preparation step.
(3A) A third preparation step of creating a regression line (“first regression line” in the example) indicating the relationship between the stride and heart rate measured in the first preparation step.
(4A) A subject maximum stride (“first maximum stride” in the embodiment) that is a stride corresponding to the subject maximum heart rate (“first maximum heart rate” in the embodiment) obtained from the age of the subject is a third preparation step. The 4th preparatory step calculated | required based on the regression line created in (4).
(5A) A subject LT stride (“first LT stride” in the example) that is a stride corresponding to the actual LT heart rate is obtained based on the regression line created in the third preparation step, and the above ratio is calculated by the formula “subject 5th preparatory step calculated | required by "LT stride / test subject maximum stride".

The ratio stored in the storage unit of the running support device is a calculated value calculated based on a plurality of ratios obtained by executing the first to fifth preparation steps for a plurality of subjects. preferable. In this case, the average value of all or some of the plurality of ratios can be used as the calculated value. The range of the calculated value is, for example, 75.9% to 93.77%.

The position measuring unit of the running support device is, for example, a GPS receiver. In addition, the notification unit of the running support device, for example, the runner perceives according to the degree of coincidence between the runner's current stride and the LT stride, which is a stride when the runner runs with the lactic acid work threshold. A device that changes light, sound, vibration, or a combination of two or more of these.

The running support device preferably has a shape that can be attached to the body of the runner, for example, the shape of a wristwatch.

Moreover, in order to solve the said subject, the estimation method of the running intensity suitable for the training which concerns on this invention is the following.
(1B) a first estimation step for causing a runner to perform a plurality of runs with different running speeds, and measuring a stride during each running and a heart rate during or immediately after each running; and (2B) a first estimation step. A second estimation step for creating a regression line (a “second regression line” in the example) indicating the relationship between the stride and the heart rate measured in Step 3, and (3B) the maximum heart rate of the runner from the age of the runner (in the example A third estimation step for obtaining a maximum stride that is a stride corresponding to the maximum heart rate (“second maximum stride” in the embodiment) based on the regression line, and (4B ) The product of the maximum stride obtained in the third estimation step and a predetermined ratio is the stride when the runner runs at the lactic acid work threshold. Performing an estimation step and a fourth estimation step of estimating an estimated LT stride, characterized in that.

The ratio in the estimation method can be determined experimentally, for example, by executing preparation steps including the following first to fifth preparation steps.
(1A) A first preparation step of causing a subject to perform a plurality of times of running with different running speeds and measuring a stride during each running and a heart rate and a lactate value during or immediately after each running.
(2A) A second preparation step of calculating an actual LT heart rate, which is a heart rate when the subject runs at the lactic acid work threshold based on the heart rate and the lactic acid value measured in the first preparation step.
(3A) A third preparation step of creating a regression line (“first regression line” in the example) indicating the relationship between the stride and heart rate measured in the first preparation step.
(4A) A subject maximum stride (“first maximum stride” in the embodiment) that is a stride corresponding to the subject maximum heart rate (“first maximum heart rate” in the embodiment) obtained from the age of the subject is a third preparation step. The 4th preparatory step calculated | required based on the regression line created in (4).
(5A) A subject LT stride (“first LT stride” in the example) that is a stride corresponding to the actual LT heart rate is obtained based on the regression line created in the third preparation step, and the above ratio is calculated by the formula “subject 5th preparatory step calculated | required by "LT stride / test subject maximum stride".

The estimation step of the estimation method further includes (5B) a regression line (“third regression line” in the embodiment) indicating the relationship between the running speed of each running in the first estimation step and the stride measured in the first estimation step. A fifth estimation step to be created; and (6B) a sixth estimation step in which a running speed corresponding to the estimated LT stride is obtained based on the regression line created in the fifth estimation step, and the obtained running speed is set to the estimated LT running speed. And may further be included.

The ratio used in the fourth estimation step of the estimation method is preferably a calculated value calculated based on a plurality of ratios obtained by executing the first to fifth preparation steps for a plurality of subjects. . In this case, the average value of all or some of the plurality of ratios can be used as the calculated value. The range of the calculated value is, for example, 75.9% to 93.77%.

According to the present invention, it is possible to provide an estimation method capable of estimating a running intensity suitable for training without blood collection. Further, according to the present invention, it is possible to provide a running support device that can support running at a running intensity suitable for training without collecting blood.

It is a flowchart of the estimation method which concerns on the Example of this invention. It is a flowchart of the estimation method which concerns on another Example of this invention. It is a flowchart of the estimation method which concerns on another Example of this invention. It is the table | surface which put together the various data obtained by performing the preparation step of the estimation method which concerns on this invention. It is the table | surface following FIG. 4 which put together the various data obtained by performing the preparation step of the estimation method which concerns on this invention. It is the table | surface following FIG. 5 which put together the various data obtained by performing the preparation step of the estimation method which concerns on this invention. It is the table | surface following FIG. 6 which summarized the various data obtained by performing the preparatory step of the estimation method which concerns on this invention. It is the table | surface which put together the various data obtained by performing the estimation step of the estimation method which concerns on this invention. It is the table | surface following FIG. 8 which summarized the various data obtained by performing the estimation step of the estimation method which concerns on this invention. It is the table | surface following FIG. 9 which put together the various data obtained by performing the estimation step of the estimation method which concerns on this invention. It is the table | surface following FIG. 10 which summarized the various data obtained by performing the estimation step of the estimation method which concerns on this invention. The graph (A) for explaining the first regression line created by the estimation method according to the present invention and its usage, the graph (B) for explaining the second regression line and its usage, and the third regression line and its It is a graph (C) for demonstrating how to use. It is a graph which shows the estimation precision of the estimation method which concerns on this invention. It is a graph which shows the estimation precision of the estimation method which concerns on a comparative example. It is a graph which shows the estimation precision of the estimation method which concerns on this invention. It is a graph which shows the estimation precision of the estimation method which concerns on a comparative example. It is a block diagram which shows schematic structure of the running assistance apparatus which concerns on the Example of this invention. It is a graph for demonstrating the definition of a lactic acid work threshold value.

Hereinafter, embodiments of a running intensity estimation method and a running support apparatus suitable for training according to the present invention will be described with reference to the accompanying drawings.

<Preferred method for estimating running strength>
FIG. 1 shows a flowchart of the estimation method according to the present invention. As shown in the figure, the estimation method of the present invention includes a preparation step including a first preparation step S1A to a fifth preparation step S5A and an estimation step including a first estimation step S1B to a fourth estimation step S4B. ing. The preparation step is executed to obtain a ratio used in the fourth estimation step S4B of the estimation step. Once the preparatory step is executed and the ratio is obtained, the running strength suitable for training, that is, the estimated LT stride that is a stride during LT is estimated by simply executing the estimation step that does not require blood collection. be able to.

In the estimation method according to the present invention, as shown in FIG. 2, the estimation step may further include a fifth estimation step S5B and a sixth estimation step S6B. In this case, the estimated LT running speed, which is the running speed at the time of LT, can be finally estimated.

FIGS. 1 and 2 are flow charts in the case where one ratio obtained by executing the preparation step for one subject is used in the estimation step. The estimation method according to the present invention is shown in FIG. As shown in FIG. 5, a preparation step is performed on a plurality of subjects to obtain a plurality of ratios, and one ratio calculated based on the plurality of ratios is estimated (first estimation step S1B to sixth estimation step S6B). Alternatively, the first estimation step S1B to the fourth estimation step S4B) may be used. Hereinafter, each step in the embodiment shown in FIG. 3 will be described in detail.

[Preparation steps]
[First preparation step S1A]
In the first preparation step S1A, the subject is caused to perform a plurality of runs with different running speeds, and the stride during each running, the heart rate during or immediately after each running, and the lactate value are measured.

In this example, 32 running enthusiasts aiming to complete a full marathon (breakdown is 17 males and 15 females. Age is 45.8 ± 9.5 years old). Stages were performed, strides at 300 m and 700 m points were measured, and heart rate and lactic acid levels were measured during each stage interval (immediately after running). To measure heart rate, we used Polar's portable heart rate measuring device “Polar Accurex Plus”, and to measure lactic acid, we used a simple lactate meter “Lactate Pro” made by ARKRAY. .

In this example, the set times of each subject at each stage are as shown in Table 1. For example, for a subject whose full marathon target time is 3 and a half hours, the first stage set time is 6 minutes 00 seconds, the second stage set time is 5 minutes 30 seconds, and the third stage set time is Was set to 5 minutes 00 seconds, the fourth stage set time was 4 minutes 30 seconds, and the fifth stage set time was set to 4:00 seconds.

The data of each subject obtained by executing this step is shown in the stride sequence, heart rate sequence, and lactate sequence in FIGS. 4 is a table summarizing data of subjects 1 to 8, FIG. 5 is a table summarizing data of subjects 9 to 16, FIG. 6 is a table summarizing data of subjects 17 to 24, and FIG. 3 is a table summarizing data of subjects 25 to 32. Moreover, the stride shown in the stride row of each figure is the average value of the stride at the 300 m point and the stride at the 700 m point.

[Second preparation step S2A]
In the second preparation step S2A, an actual LT heart rate, which is a heart rate at the time of LT, is calculated based on the heart rate and lactate value measured in the first preparation step S1A.

In this example, the actual LT heart rate of each subject was calculated using lactic acid management software “MEQNET LT Manager” manufactured by ARKRAY. The actual LT heart rate of each subject calculated by executing this step is shown in the actual LT heart rate column of FIGS. In the present invention, the measurement points of each stage are plotted on a two-dimensional coordinate space in which the horizontal axis represents the heart rate and the vertical axis represents the lactic acid value, and the regression line created from the measurement points of the first to third stages and the first The heart rate at the intersection with the regression line created from the measurement points of the third to fifth stages may be used as the actual LT heart rate.

In addition, you may perform this step after 3rd preparatory step S3A mentioned later or 4th preparatory step S4A (however, before 5th preparatory step S5A).

[Third preparation step S3A]
In the third preparation step S3A, a first regression line is created based on the stride and heart rate measured in the first preparation step S1A.

As an example, the first regression line of subject 1 is shown in FIG. When a first regression line was created by plotting five measurement points of the subject 1 on a two-dimensional coordinate space with the horizontal axis as the heart rate and the vertical axis as the stride, the slope was 0.00714 and the intercept was 0.22457. became. The slope and intercept of the first regression line may be obtained using the SLOPE function and the INTERCEPT function of Microsoft's spreadsheet software. The slope and intercept of the first regression line for each subject created by executing this step are shown in FIGS.

[Fourth preparation step S4A]
In the fourth preparation step S4A, the first maximum stride that is a stride corresponding to the maximum heart rate of the subject (hereinafter referred to as “first maximum heart rate”) based on the first regression line created in the third preparation step S3A. Ask for.

In this example, the first maximum heart rate was determined using the relational expression “maximum heart rate = 220−age”, and the first maximum stride corresponding to this was determined based on the first regression line. As shown in FIG. 12 (A), the first maximum stride corresponding to the first maximum heart rate of 175 times / minute of the subject 1 (45 years old) was 1.4744 m. The first maximum stride of each subject obtained by executing this step is shown in the first maximum stride row of FIGS.

[Fifth preparation step S5A]
In the fifth preparation step S5A, a first LT stride, which is a stride corresponding to the actual LT heart rate obtained in the second preparation step S2A, is obtained based on the first regression line created in the third preparation step S3A.

As shown in FIG. 12 (A), the first LT stride corresponding to the subject 1's actual LT heart rate of 135 times / minute was 1.18887 m. The first LT stride of each subject obtained by executing this step is shown in the first LT stride row of FIGS.

In the fifth preparation step S5A, the ratio of the first LT stride to the first maximum stride is further obtained.

As described above, since the first maximum stride and the first LT stride of the subject 1 are 1.4744 m and 1.18887 m, respectively, the ratio of the first LT stride to the first maximum stride is 80.62%.

When one ratio obtained by executing the preparation step for one subject shown in FIGS. 1 and 2 is used in the estimation step, this 80.62% is used in the estimation step described later. . On the other hand, in this embodiment (FIG. 3), the final ratio is calculated based on the ratio of 32 obtained by executing the first preparation step S1A to the fifth preparation step S5A for 32 subjects. This is used in the estimation step described later.

More specifically, in this embodiment, the final ratio used in the estimation step is calculated by taking the average of the ratio of each subject shown in the ratio column of FIGS. As shown in FIG. 4 to FIG. 7, there is a considerable variation in the proportion of each subject. However, by taking the average, it is possible to calculate a ratio suitable for accurately estimating the suitable running intensity of any runner.

In this example, the average value of the ratio of each subject was 84.88%. As described above, in this example, the ratio was obtained based on data obtained from various subjects with different age (sex) and marathon records (performance). For this reason, the above 84.88% is considered to be a highly versatile value that can be used to estimate a suitable running strength of many runners. On the other hand, if the subject is a different person, the average value is considered to vary. In this case, the range of variation is expected to be 75.99% to 93.77% because the standard deviation of the proportion of each subject was 8.89%.

Other suitable calculation values include, for example, the median value. When calculating the average value or the median value, a known method for noise removal such as excluding the maximum value and the minimum value of the ratio of each subject may be used.

This is the preparation step of the estimation method according to the present invention. Next, the estimation step of the estimation method according to the present invention will be described.

[Estimation step]
[First estimation step S1B]
In the first estimation step S1B, a runner who wants to know a running intensity suitable for training performs a plurality of runs with different running speeds, and measures the stride during each running and the heart rate during or immediately after each running. Unlike the first preparation step S1A, it is not necessary to measure the lactic acid value in this step.

In this embodiment, the same runner 1 as the subject 1 in the preparation step is allowed to perform five stages of 1,000 m incremental increase as in the first preparation step S1A, and the strides at the 300 m point and the 700 m point are measured. Heart rate was measured during the interval (immediately after running). As in the first preparation step S1A, a heart rate measurement device “Polar Accurex Plus” manufactured by Polar was used for the heart rate measurement. The data of the runner 1 obtained by executing this step is shown in the stride string and heart rate string of FIG.

[Second estimation step S2B]
In the second estimation step S2B, a second regression line is created based on the stride and heart rate measured in the first estimation step S1B.

The second regression line of Runner 1 is shown in FIG. When a second regression line was created by plotting five measurement points of the runner 1 on a two-dimensional coordinate space with the horizontal axis representing the heart rate and the vertical axis representing the stride, the slope was 0.00714 and the intercept was 0.22457. became. The slope and intercept of the second regression line may be obtained using the SLOPE function and the INTERCEPT function of Microsoft spreadsheet software. FIG. 8 shows the slope and intercept of the second regression line for the runner 1 created by executing this step.

[Third estimation step S3B]
In the third estimation step S3B, based on the second regression line created in the second estimation step S2B, a second maximum stride that is a stride corresponding to the runner's maximum heart rate (hereinafter referred to as “second maximum heart rate”). Ask for.

In this example, the second maximum heart rate was determined using the relational expression “maximum heart rate = 220−age”, and the second maximum stride corresponding to this was determined based on the second regression line. As shown in FIG. 12 (B), the second maximum stride corresponding to the second maximum heart rate of 175 times / minute for runner 1 (45 years old) was 1.4744 m. The second maximum stride of the runner 1 obtained by executing this step is shown in the second maximum stride row of FIG.

[Fourth estimation step S4B]
In the fourth estimation step S4B, the product of the second maximum stride obtained in the third estimation step S3B and the final ratio (average value) obtained in the fifth preparation step S5A is estimated as a stride at the time of LT. Hereinafter, this stride is referred to as “estimated LT stride”.

As described above, the second maximum stride is 1.4744 m. Further, the average value of the ratios of the subjects shown in the ratio columns of FIGS. 4 to 7 is 84.88% as shown in the ratio average value column of FIG. Therefore, in this embodiment, 1.4744 m × 0.8488 = 1.2514 m is estimated as the estimated LT stride. The estimated LT stride of the runner 1 obtained by executing this step is shown in the estimated LT stride sequence of FIG.

When the fifth estimation step S5B and the sixth estimation step S6B described later are not executed, the estimated LT stride estimated in this step is a suitable running strength for the runner 1. In this case, the runner 1 can perform training with an intensity approximate to LT by running so that the stride matches the estimated LT stride.

[Fifth estimation step S5B]
In the fifth estimation step S5B, a third regression line indicating the relationship between the running speed in each running of the first estimation step S1B and the stride measured in the first estimation step S1B is created.

Runner 1's 1st to 5th stage settings are 6 minutes 00 seconds, 5 minutes 30 seconds, 5 minutes 00 seconds, 4 minutes 30 seconds, 4 minutes 00 seconds (see Table 1). The running speed is 166.7 m / min, 181.8 m / min, 200.0 m / min, 222.2 m / min, 250.0 m / min. The stride in each stage of the runner 1 is as shown in the stride row of FIG.

When a third regression line was created by plotting five measurement points of the runner 1 on a two-dimensional coordinate space with the horizontal axis as the stride and the vertical axis as the running speed, as shown in FIG. 194.029, section became -31.994. The slope and intercept of the third regression line may be obtained by using the SLOPE function and the INTERCEPT function of Microsoft spreadsheet software. FIG. 8 shows the slope and intercept of the third regression line for the runner 1 created by executing this step.

[Sixth Estimation Step S6B]
In the sixth estimation step S6B, the running speed corresponding to the estimated LT stride obtained based on the third regression line is set as the estimated LT running speed.

As shown in FIG. 12C, the estimated LT running speed corresponding to the estimated LT stride 1.2514 m of the runner 1 was 210.82 m / min. The estimated LT running speed of the runner 1 obtained by executing this step is shown in the estimated LT speed train of FIG.

In the present embodiment, the estimated LT running speed obtained in the sixth estimation step S6B is a suitable running strength for the runner 1. Therefore, the runner 1 can perform training at an intensity approximate to LT by running so that the running speed matches the estimated LT running speed.

The estimated LT running speed obtained by executing the estimating step on the same runner 2 to runner 32 as the subject 2 to the subject 32 is shown in the estimated LT speed train of FIGS. 8 is a table summarizing the data of runners 1 to 8, FIG. 9 is a table summarizing the data of runners 9 to 16, FIG. 10 is a table summarizing the data of runners 17 to 24, and FIG. A table summarizing the data of runners 25 to 32. The values shown in the estimation error strings in FIGS. 8 to 11 are estimation errors obtained by the calculation formula “estimation error = (estimated LT running speed−actual LT running speed) / actual LT running speed × 100”. . The actual LT running speeds of runners 1 to 32 (= subjects 1 to 32) are described in the actual LT speed trains of FIGS.

Subsequently, the result of evaluating the estimation accuracy of the estimation method according to the present invention will be described.

FIG. 13 shows a two-dimensional coordinate space in which the horizontal axis represents the actual LT running speed that is the running speed during LT, the average value of the estimated LT running speed estimated by the estimation method according to the present invention, and the vertical axis represents the estimation error. 6 is a graph plotting estimation results of runners 1 to 32. As shown in the figure, the average value of the estimation error was −0.6%, and the 95% confidence interval was ± 23.4%. This indicates that the estimation method according to the present invention can estimate the running speed during LT with an accuracy of −24.0% to + 22.8% for 95% of runners.

As a comparative example, FIG. 14 shows a graph when the running speed when the heart rate is 75%, 80%, or 85% of the maximum heart rate (= 220−age) is estimated as the LT running speed. As shown in FIG. 5C, assuming that the running speed at 85% maximum heart rate is the estimated LT running speed, the average value of the estimation error is −4.7% and the 95% confidence interval is ± 21.8%. became.

FIG. 15 is a graph in which the estimation results of the runners 1 to 32 are plotted on a two-dimensional coordinate space in which the horizontal axis indicates the estimated LT running speed estimated by the estimation method according to the present invention and the vertical axis indicates the actual LT running speed. is there. This result indicates that there is a significant correlation between the estimated LT running speed and the actual LT running speed.

As a comparative example, FIG. 16 shows a graph when the running speed when the heart rate is 75%, 80%, or 85% of the maximum heart rate (= 220−age) is estimated as the LT running speed. As shown in FIG. 5C, if the running speed at 85% maximum heart rate is the estimated LT running speed, as in the estimation method according to the present invention, there is a significant difference between the estimated LT running speed and the actual LT running speed. A good correlation was observed.

As described above, according to the estimation method according to the present invention, there is a significant correlation with the actual LT running speed, and −24.0% to +22 with respect to the actual LT running speed of 95% of the runners. An estimated LT running speed with an accuracy of .8% could be obtained.

Here, it seems that the result of the estimation method according to the present invention is not different from the result of the comparative example shown in FIG. 14 (C) and FIG. 16 (C). However, since there are individual differences in the maximum heart rate, the maximum heart rate obtained by the relational expression “maximum heart rate = 220−age” may deviate greatly from the actual maximum heart rate. For this reason, in the estimation by the comparative example in which the running speed at the 85% maximum heart rate is the estimated LT running speed, there is a possibility that high estimation accuracy as shown in FIGS. 14C and 16C may not be obtained. . On the other hand, in the estimation method according to the present invention, even if the maximum heart rate (first maximum heart rate) used for obtaining the ratio is greatly deviated from the actual maximum heart rate, in the fourth estimation step S4B Since the deviation tends to be canceled when the ratio obtained in the fifth preparation step S5A is multiplied by the second maximum stride, it is less affected by the deviation of the maximum heart rate.

<Running support device>
Next, the running support apparatus according to the present invention will be described.

FIG. 17 shows a block diagram of the running support apparatus 10 according to the present invention. The running support device 10 has a shape that can be attached to the body of a running runner (hereinafter referred to as “user”) such as a wristwatch. As shown in FIG. 1, the running support apparatus 10 includes an input unit 11, a position measurement unit 12, a stride calculation unit 13, a heart rate measurement unit 14, a storage unit 15, a calculation unit 16, and a notification unit 17.

The input unit 11 includes a touch panel or a plurality of physical buttons. The user can input a numerical value such as his / her age through the input unit 11.

The position measuring unit 12 includes a GPS receiver capable of receiving a signal from a GPS satellite, for example. The position measuring unit 12 outputs a signal related to the position of the user wearing the running support device 10 in real time. Note that “real time” in the present specification does not only mean that they are strictly the same, but also includes that they are shifted in time so that no trouble occurs in the subsequent stage.

The stride calculation unit 13 includes a microcomputer having a calculation function. The stride calculation unit 13 obtains the user's stride in real time based on the change in the signal related to the position output from the position measurement unit 12, and outputs a signal related to the obtained stride.

The heart rate measuring unit 14 measures the heart rate based on a change in the internal pressure of the artery due to pulsation within a predetermined period. The heart rate measuring unit 14 outputs a signal related to the measured heart rate.

The storage unit 15 includes a memory device capable of rewriting data. The storage unit 15 includes the user age input from the input unit 11, the user stride obtained by the stride calculation unit 13, the user heart rate measured by the heart rate measurement unit 14, the age, A relational expression indicating the relationship with the maximum heart rate (in this embodiment, “maximum heart rate = 220−age”) and a predetermined ratio are stored. In the present embodiment, 84.88% obtained by executing the preparation step (see FIG. 3) for a plurality of subjects is stored as a ratio, but this is merely an example. As described above, the ratio may be obtained by executing a preparation step (see FIGS. 1 and 2) for one subject. Further, the ratio may be obtained by another method.

The calculation unit 16 includes a microcomputer having a calculation function. The microcomputer constituting the calculation unit 16 may be the same as the microcomputer constituting the stride calculation unit 13. The calculation unit 16 is used when the user wearing the running support device 10 before setup is running as setup (preparation) and when the user wearing the setup running support device 10 is running as training. Behaves differently when performing

Specifically, when the user performs a plurality of runs at different running speeds as setups, the calculation unit 16 calculates the second from the stride during running and the heart rate during or immediately after running stored in the storage unit 15. Create a regression line. Then, the calculation unit 16 obtains the second maximum heart rate of the user from the user's age and the relational expression stored in the storage unit 15, and further calculates the second maximum stride corresponding to the second maximum heart rate. Obtained based on two regression lines. This operation corresponds to the first estimation step S1B to the third estimation step S3B of the estimation method according to the present invention. The obtained second maximum stride is stored in the storage unit 15.

On the other hand, when the user is running as training, the calculation unit 16 estimates the user's LT stride from the product of the second maximum stride stored in the storage unit 15 and a predetermined ratio. (Fourth estimation step S4B). Then, the calculation unit 16 compares the LT stride obtained by the estimation with the current stride of the user measured by the position measurement unit 12 and the stride calculation unit 13 in real time, and outputs a signal regarding the degree of coincidence between the two. To do.

The notification unit 17 includes a device that changes light, sound, vibration, or a combination of two or more of these that can be perceived by the user. The notification unit 17 changes light, sound, vibration, or a combination of two or more thereof in real time in accordance with the signal output from the calculation unit 16. This informs the user in real time whether the current stride is suitable for training.

When the light emitted from the notification unit 17 indicates that the current stride is shorter than the LT stride, the user can perform running at an intensity approximate to LT by increasing the stride. On the other hand, when the light emitted by the notification unit 17 indicates that the current stride is longer than the LT stride, the user can run at a strength approximate to LT by reducing the stride. .

As described above, the running intensity estimation method and the running support apparatus suitable for training according to the present invention have been described. However, the configuration of the present invention is not limited to the above configuration and departs from the gist of the present invention. It goes without saying that various improvements and modifications can be made within the range not to be performed.

For example, the relational expression regarding the maximum heart rate used in the fourth preparation step S4A and the third estimation step S3B and the relational expression regarding the maximum heart rate stored in the storage unit 15 are “maximum heart rate = 206.9-0”. .67 × age ”or the like.

Further, the number of runnings in the first preparation step S1A and the first estimation step S1B may be two or more. However, from the viewpoint of estimation accuracy, the number of runnings is preferably 5 or more as in the embodiment.

Also, the shape of the running support device is not limited to the shape of a wristwatch, and may be, for example, a shape that can be worn on a running shoe, or a shape that can be worn on the upper arm or waist of a runner.

Also, the specific configuration of each element constituting the running support device can be appropriately replaced with another configuration capable of realizing an equivalent function.

Running with a strength (stride or speed) that approximates LT is an extremely effective way to make an excellent record in a marathon race. Therefore, the running intensity estimating method and the running support device suitable for training according to the present invention can be used not only for training but also for marathon races.

DESCRIPTION OF SYMBOLS 10 Running support apparatus 11 Input part 12 Position measurement part 13 Stride calculation part 14 Heart rate measurement part 15 Storage part 16 Calculation part 17 Notification part

Claims

An input unit that accepts an input of the age of the runner;
A position measuring unit for measuring the position of the runner during running;
A stride calculation unit for obtaining a stride of the runner based on the change in the position measured by the position measurement unit;
A heart rate measuring unit for measuring a heart rate during or immediately after the run of the runner;
The age input from the input unit, a relational expression indicating the relationship between age and maximum heart rate, the stride obtained by the stride calculating unit, and the heart rate measured by the heart rate measuring unit A storage unit storing a predetermined ratio;
While referring to the storage unit, an arithmetic unit for obtaining a degree of coincidence between the current stride of the runner and the LT stride that is a stride when the runner has run at a lactic acid work threshold;
A notification unit for notifying the runner of the degree of coincidence obtained by the calculation unit;
With
The computing unit creates a regression line from the stride and the heart rate when the runner performs a plurality of runs at different running speeds as a preliminary preparation, and the maximum obtained from the age and the relational expression. Find the maximum stride corresponding to your heart rate based on the regression line,
Further, the calculation unit estimates the LT stride from a product of the maximum stride obtained in advance and the ratio stored in the storage unit when the runner is running as training. The running support device that compares the LT stride and the current stride in real time.
2. The running support apparatus according to claim 1, wherein the ratio is obtained experimentally by executing the following first to fifth preparation steps.
(1) A first preparation step of causing a subject to perform a plurality of runs with different running speeds and measuring a stride during each running and a heart rate and a lactate value during or immediately after each running.
(2) Second preparation for calculating an actual LT heart rate, which is a heart rate when the subject runs with the lactic acid work threshold based on the heart rate and the lactic acid value measured in the first preparation step. Step.
(3) A third preparation step for creating a regression line indicating the relationship between the stride measured in the first preparation step and the heart rate.
(4) A fourth preparation step of obtaining a subject maximum stride that is a stride corresponding to the subject maximum heart rate obtained from the age of the subject based on the regression line created in the third preparation step.
(5) A subject LT stride, which is a stride corresponding to the actual LT heart rate, is obtained based on the regression line created in the third preparation step, and the ratio is calculated by the formula “subject LT stride / subject maximum stride”. 5th preparation step obtained by
The ratio stored in the storage unit is a calculated value calculated based on a plurality of ratios obtained by executing the first to fifth preparation steps for a plurality of subjects. The running support apparatus according to claim 2.
The running support device according to claim 3, wherein the calculated value is an average value of all or a part of the plurality of ratios.
The running support device according to claim 4, wherein the calculated value is in a range of 75.9% to 93.77%.
The running support apparatus according to any one of claims 1 to 5, wherein the position measuring unit is a GPS receiver.
The notification unit is a device that changes light, sound, vibration, or a combination of two or more thereof that can be perceived by the runner in accordance with the degree of matching. The running support device according to claim 6.
The running support device according to any one of claims 1 to 7, wherein the running support device can be attached to a body of the runner.
The running support device according to claim 8, which has a wristwatch shape.
A first estimation step for causing the runner to perform a plurality of runs with different running speeds and measuring a stride during each run and a heart rate during or immediately after each run;
A second estimation step for creating a regression line indicating the relationship between the stride measured in the first estimation step and the heart rate;
A third estimation step of obtaining a maximum heart rate of the runner from the age of the runner and obtaining a maximum stride that is a stride corresponding to the maximum heart rate based on the regression line;
A fourth estimation step for estimating a product of the maximum stride obtained in the third estimation step and a predetermined ratio as an estimated LT stride that is a stride when the runner performs running at a lactic acid work threshold;
A method for estimating a running intensity suitable for training, comprising executing an estimation step including:
11. The estimation method according to claim 10, wherein the ratio is obtained experimentally by executing a preparation step including the following first to fifth preparation steps.
(1) A first preparation step of causing a subject to perform a plurality of runs with different running speeds and measuring a stride during each running and a heart rate and a lactate value during or immediately after each running.
(2) Second preparation for calculating an actual LT heart rate, which is a heart rate when the subject runs with the lactic acid work threshold based on the heart rate and the lactic acid value measured in the first preparation step. Step.
(3) A third preparation step for creating a regression line indicating the relationship between the stride measured in the first preparation step and the heart rate.
(4) A fourth preparation step of obtaining a subject maximum stride that is a stride corresponding to the subject maximum heart rate obtained from the age of the subject based on the regression line created in the third preparation step.
(5) A subject LT stride, which is a stride corresponding to the actual LT heart rate, is obtained based on the regression line created in the third preparation step, and the ratio is calculated by the formula “subject LT stride / subject maximum stride”. 5th preparation step obtained by
The estimating step comprises:
A fifth estimation step for creating a regression line indicating the relationship between the running speed of each running in the first estimation step and the stride measured in the first estimation step;
A running speed corresponding to the estimated LT stride is obtained based on the regression line created in the fifth estimating step, and a sixth estimating step using the obtained running speed as the estimated LT running speed;
The estimation method according to claim 10, further comprising:
The ratio used in the fourth estimation step is a calculated value calculated based on a plurality of ratios obtained by executing the first to fifth preparation steps for a plurality of subjects. Item 12. The estimation method according to Item 11.
The estimation method according to claim 13, wherein the calculated value is an average value of all or a part of the plurality of ratios.
The estimation method according to claim 14, wherein the calculated value is in a range of 75.99% to 93.77%.