Activity estimation device, wireless communication terminal, activity estimation system, activity estimation method, and activity estimation program

Abstract

To provide an activity estimation device capable of estimating an activity of a user with a small operation processing amount.SOLUTION: An activity estimation device includes: atmospheric pressure data acquisition means that acquires atmospheric pressure data of the inside of a shoe worn by a user; and movement state estimation means that estimates whether the user is in a movement state or a stop state on the basis of a time change of the atmospheric pressure data. With this configuration, the activity estimation device can estimate whether the user is in the movement state or the stop state on the basis of only a time change in the atmospheric pressure data of the inside of the shoe.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an activity estimation device and the like.

Background Art

[0002] In recent years, in order to manage a person's exercise state and physical condition, the use of wearable devices that a person wears and collects information related to the person's activities has become popular. Among them, wearable devices that monitor the modes of walking and running, which are basic activities of a person, have been proposed.

[0003] For example, in Citation Document 1, the technology of a ground contact mode evaluation system is disclosed. In the technology of this ground contact mode evaluation system, a pressure sensor is built into footwear, pressure information indicating a change in the pressure inside the footwear is acquired, and based on the pressure information, the ground contact mode of the user's (user) foot is classified. In this ground contact mode evaluation system, a portion of the pressure information that periodically shows a large value is specified as the landing timing, and based on the degree of decrease in pressure immediately after the landing timing, the ground contact mode of a runner wearing the footwear and running is determined. Here, the determination of the ground contact mode is to determine whether it is a heel strike that contacts the ground from the heel portion or a forefoot that contacts the ground from the toe portion.

[0004] Also, in Patent Document 2, the technology of a step counting sensor using an acceleration sensor and a calorie consumption calculation device using a pressure sensor is disclosed. When using the calorie consumption calculation device, the user (the person to be measured) fixes the calorie consumption calculation device at the waist position using a fixture such as a belt. First, the calorie consumption calculation device detects the number of steps with the step counting sensor. Also, the pressure sensor detects a change in pressure corresponding to the up and down movement. Then, based on the signal from the step counting sensor and the pressure signal, the determination means determines the exercise state of the person to be measured. By determining the exercise state, a calorie consumption coefficient value corresponding to the exercise state of the person to be measured is selected, and the total calorie consumption amount corresponding to the exercise amount of the person to be measured can be calculated by multiplying the calorie consumption coefficient value by the number of steps.

[0005] Related technology is also disclosed in Patent Document 3. [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] Japanese Patent Publication No. 2021-058524 [Patent Document 2] Japanese Patent Application Publication No. 11-347021 [Patent Document 3] Japanese Patent Publication No. 2016-140639 [Overview of the Initiative] [Problems that the invention aims to solve]

[0007] However, the technology described in Patent Document 1 had the problem of only being able to determine the type of ground contact during running, which is a limited activity. Furthermore, the technology described in Patent Document 2 determines the motion state by analyzing the output of an acceleration sensor and the output of a barometric pressure sensor. This resulted in the problem of requiring a large amount of computational processing for the analysis.

[0008] This invention has been made in view of the above-mentioned problems, and aims to provide an activity estimation device, etc., that can estimate user activity with a small amount of computational processing. [Means for solving the problem]

[0009] To solve the above problems, the activity estimation device includes a pressure data acquisition means for acquiring pressure data inside shoes worn by the user, and a movement state estimation means for estimating whether the user is in a moving state or a stationary state based on the time change of the pressure data.

[0010] Furthermore, the wireless communication terminal of the present invention comprises the above-mentioned activity estimation device and wireless communication means for transmitting and receiving information relating to the activity estimation device.

[0011] Furthermore, the activity estimation system of the present invention comprises the above-mentioned activity estimation device and a pressure measuring device attached to the shoe, wherein the pressure measuring device comprises a pressure measuring means for measuring the air pressure inside the shoe as pressure data and a communication means for transmitting the measured pressure data to the activity estimation device.

[0012] Furthermore, the activity estimation method of the present invention involves a computer acquiring atmospheric pressure data from inside the shoes worn by the user, and estimating whether the user is moving or stationary based on the time change of the atmospheric pressure data.

[0013] Furthermore, the activity estimation program of the present invention causes a computer to perform the following processes: acquiring atmospheric pressure data inside shoes worn by the user, and estimating whether the user is moving or stationary based on the time change of the atmospheric pressure data. [Effects of the Invention]

[0014] The advantage of the present invention is that it can provide an activity estimation device, etc., that can estimate user activity with a small amount of computational processing. [Brief explanation of the drawing]

[0015] [Figure 1] This is a block diagram of an activity estimation device according to the first embodiment. [Figure 2] This is a flowchart showing the operation of the activity estimation device according to the first embodiment. [Figure 3] This is a block diagram showing an activity estimation system according to a second embodiment. [Figure 4] This is a block diagram showing a specific example of the activity estimation system of the second embodiment. [Figure 5] This is a block diagram showing another specific example of the activity estimation system of the second embodiment. [Figure 6] This is a schematic cross-sectional view showing a first specific example of the placement of the pressure measuring device in a shoe according to the second embodiment. [Figure 7]It is a perspective schematic view showing a first specific example of the arrangement of the barometric pressure measurement device of the second embodiment on a shoe. [Figure 8] It is a perspective schematic view showing an arrangement example of a barometric pressure sensor in a first specific example of the arrangement of the barometric pressure measurement device of the second embodiment on a shoe. [Figure 9] It is a cross-sectional schematic view showing a state where the foot moves in the shoe of the second embodiment. [Figure 10] It is a flowchart showing the first operation of the activity estimation device of the second embodiment. [Figure 11] It is a flowchart showing the second operation of the activity estimation device of the second embodiment. [Figure 12] It is a flowchart showing the first half of the third operation of the activity estimation device of the second embodiment. [Figure 13] It is a flowchart showing the second half of the third operation of the activity estimation device of the second embodiment. [Figure 14] It is a graph showing an example of barometric pressure data acquired by the activity estimation device of the second embodiment. [Figure 15] It is a graph showing an example of the correspondence between barometric pressure data acquired by the activity estimation device of the second embodiment and the user's activity. [Figure 16] It is a graph obtained by magnifying part G of FIG. 15. [Figure 17] It is a graph obtained by performing inclination correction on part G of FIG. 15. [Figure 18] It is a graph obtained by magnifying part A of FIG. 15. [Figure 19] It is a graph obtained by magnifying part B of FIG. 15. [Figure 20] It is a graph obtained by magnifying part F of FIG. 15. [Figure 21] It is a graph obtained by magnifying part G of FIG. 15. [Figure 22] It is a block diagram showing a modification example of the activity estimation device of the second embodiment. [Figure 23] It is a table showing an example of a calorie calculation method in the activity estimation device of the second embodiment. [Figure 24]This is a schematic cross-sectional view showing a second specific example of the placement of the pressure measuring device in a shoe according to the second embodiment. [Figure 25] This is a schematic plan view showing a second specific example of the placement of the pressure measuring device in a shoe according to the second embodiment. [Figure 26] This is a schematic cross-sectional view showing a third specific example of the placement of the pressure measuring device in a shoe according to the second embodiment. [Figure 27] This is a schematic plan view showing a third specific example of the placement of the pressure measuring device in a shoe according to the second embodiment. [Figure 28] This is a schematic cross-sectional view showing a fourth specific example of the placement of the pressure measuring device in a shoe according to the second embodiment. [Figure 29] This is a schematic cross-sectional view showing a fifth specific example of the placement of the pressure measuring device in a shoe according to the second embodiment. [Modes for carrying out the invention]

[0016] Embodiments of the present invention will be described in detail below with reference to the drawings. However, the embodiments described below include technically preferred limitations for carrying out the present invention, but do not limit the scope of the invention. Similar components in each drawing are given the same number and their descriptions may be omitted.

[0017] (First embodiment) Figure 1 is a block diagram of the activity estimation device 10 according to the first embodiment. The activity estimation device 10 includes a barometric pressure data acquisition means 1 and a movement state estimation means 2.

[0018] The pressure data acquisition means 1 acquires pressure data inside the shoe 90 worn by the user. The pressure data inside the shoe 90 is, for example, pressure data measured by a pressure measuring means 91 located inside the shoe 90. The measured pressure data is transmitted to the activity estimation device 10 by the communication means 92.

[0019] The movement state estimation means 2 estimates whether the user is in a moving state or a stationary state based on the time change of atmospheric pressure data.

[0020] The pressure measuring means 91 is located inside the shoe 90. The pressure measuring means 91 measures the air pressure inside the shoe 90.

[0021] The communication means 92 communicates with the activity estimation device 10. Specifically, the communication means 92 transmits the atmospheric pressure data measured by the atmospheric pressure measurement means 91 to the activity estimation device 10.

[0022] Figure 2 is a flowchart illustrating the operation of the activity estimation device 10 in the first embodiment. The activity estimation device 10 first acquires atmospheric pressure data inside the shoe 90 (S1). The shoe 90 is worn by the user. Next, the activity estimation device 10 estimates whether the user's activity is in a moving state or a stationary state based on the time change of the atmospheric pressure data (S2).

[0023] The activity estimation device 10 of this embodiment has been described above.

[0024] The activity estimation device 10 of this embodiment includes a pressure data acquisition means 1 and a movement state estimation means 2. The pressure data acquisition means 1 acquires pressure data inside the shoes 90 worn by the user. The movement state estimation means 2 estimates whether the user is moving or stationary based on the time change of the acquired pressure data. When the user walks, runs, or moves using a means of transportation, the pressure data changes more rapidly than the pressure changes due to changes in weather. The means of transportation are, for example, elevators and escalators. Therefore, it is possible to estimate the user's movement based on the rapid changes in pressure data. The activity estimation device 10 of this embodiment can estimate whether the user is moving or stationary based only on the time change of pressure data inside the shoes 90. Therefore, compared to cases that use both the number of steps measured by an acceleration sensor and pressure, as in Patent Document 2, the user's activity can be estimated with less computation.

[0025] (Second embodiment) Next, we will describe a specific configuration example of an activity estimation device and an activity estimation system using the activity estimation device. Figure 3 is a block diagram of the activity estimation system 1000 of the second embodiment. The activity estimation system 1000 includes an activity estimation device 100 and a barometric pressure measuring device 200. Note that the activity estimation system 1000 of the second embodiment is an example of the activity estimation device 10 of the first embodiment.

[0026] The activity estimation device 100 includes a pressure data acquisition unit 110 and a movement state estimation unit 120. The activity estimation device 100 is implemented, for example, on a computer 300. The activity estimation device 100 is an example of the activity estimation device 10 of the first embodiment. The pressure data acquisition unit 110 is an example of the pressure data acquisition means 1, and the movement state estimation unit 120 is an example of the movement state estimation means 2.

[0027] The pressure data acquisition unit 110 acquires pressure data from inside the shoe 400 worn by the user. The pressure data inside the shoe 400 is, for example, pressure data measured by a pressure measuring device 200 placed inside the shoe 400. The measured pressure data is transmitted to the activity estimation device 100 by the communication module 220.

[0028] The movement state estimation unit 120 estimates whether the user is in a moving state or a stationary state based on the time change of atmospheric pressure data.

[0029] The pressure measuring device 200 includes a pressure sensor 210 and a communication module 220. The pressure sensor 210 measures the air pressure inside the shoes 400 worn by the user as pressure data. The communication module 220 transmits the pressure data measured by the pressure sensor 210 to the activity estimation device 100. Here, the pressure sensor 210 is an example of the pressure measuring means 91 of the first embodiment, and the communication module 220 is an example of the communication means 92.

[0030] The pressure sensor 210 is located inside the shoe 400. The pressure sensor 210 measures the air pressure inside the shoe 400.

[0031] The communication module 220 communicates with the activity estimation device 100. Specifically, the communication module 220 transmits the atmospheric pressure data measured by the atmospheric pressure measuring device 200 to the activity estimation device 100.

[0032] Next, a specific example of the activity estimation system 1000 will be described. Figure 4 is a block diagram showing a specific example of the activity estimation system 1000 according to the second embodiment. In this example, the activity estimation device 100 is implemented in a wireless communication terminal 310 equipped with wireless communication means 311. The wireless communication means 311 transmits and receives information about the activity estimation device 100.

[0033] Figure 5 is a block diagram showing another specific example of the activity estimation system 1000 of the second embodiment. In this example, the activity estimation system 1000 includes an activity estimation device 100, a barometric pressure measuring device 200, and a wireless communication terminal 320. The computer 300 and the wireless communication terminal 320 can be connected to a network 500. Barometric pressure data measured by the barometric pressure measuring device 200 is transmitted from the communication module 220 to the wireless communication terminal 320. The barometric pressure data is then transmitted from the wireless communication terminal 320 to the computer 300 via the network 500. For example, if the wireless communication terminal 320 is a smartphone or tablet device owned by the user, the communication module 220 can send barometric pressure data to the wireless communication terminal 320 using short-range wireless technology such as Bluetooth®.

[0034] Next, the configuration of the pressure measuring device 200 and its placement on the shoe 400 will be described. Figure 6 is a schematic cross-sectional view showing a first specific example of the placement of the pressure measuring device 200 of the second embodiment on the shoe 400. Figure 7 is a schematic perspective view showing a first specific example of the placement of the pressure measuring device 200 of the second embodiment on the shoe 400. Figure 8 is a schematic perspective view showing a specific example of the placement of the pressure sensor 210 in the pressure measuring device 200 of the second embodiment. The pressure sensor 210 is placed on the shoe 400.

[0035] As shown in Figure 6, the shoe 400 is worn on the user's foot 900. An insole 410 is placed inside the bottom of the shoe 400. The barometric pressure measuring device 200 is attached to the insole 410. As shown in Figure 7, a recessed section 411 is provided in the arch of the insole 410. A communication module 220 equipped with a battery 221 is housed in the recessed section 411. A cover (not shown) is provided above the recessed section 411 to prevent moisture and dust from entering from the outside. A groove 411a is connected to the recessed section 411. The groove 411a is formed between the recessed section 411 and the upright portion at the heel end. In the following description, this upright portion will be referred to as the heel cup 412. The groove 411a also houses the cable 230. As shown in Figure 8, a pressure sensor 210 is mounted on the end of the cable 230 on the heel cup 412 side. A cover (not shown) is provided in the recessed portion 411 and groove 411a. This cover can be made of, for example, a soft-touch fabric. In this case, the fabric is attached to the entire side of the insole 410 on which the foot 900 rests. Note that the arrangement of the pressure sensor 210 is not limited to the above. The arrangement of the pressure sensor 210 is sufficient as long as air can pass through the gap between the inner space of the shoe 400 and the cover.

[0036] The insole 410 is made of an elastic material with elasticity, such as foamed urethane. The pressure sensor 210 can be, for example, a piezoresistive semiconductor pressure sensor. The cable 230 can be, for example, a flexible printed circuit board (FPC).

[0037] Next, we will explain how to estimate user activity from atmospheric pressure data using a specific example of atmospheric pressure data. First, we will explain the relationship between the time change of atmospheric pressure data and user activity. Figure 9 is a schematic cross-sectional view showing the shoe 400 and foot 900 of the second embodiment. Figure 9 shows the state in which the foot 900 has moved inside the shoe 400. For example, when the state changes from one in which the entire sole of the foot 900 is in contact with the bottom of the shoe 400, as shown in Figure 5, to one in which the heel of the foot 900 is lifted off the insole 410, as shown in Figure 9, the atmospheric pressure inside the shoe 400 changes. In other words, when the user's foot moves due to walking or running, the atmospheric pressure inside the shoe 400 changes.

[0038] Next, the operation of the activity estimation device 100 will be described. Figure 10 is a flowchart showing the first operation of the activity estimation device of the second embodiment. First, the activity estimation device 100's pressure data acquisition unit 110 samples pressure data at a predetermined period (S101). Next, the movement state estimation unit 120 calculates a first difference, which is the difference between a given pressure data and the previous pressure data (S102). If the first difference is greater than or equal to a first threshold (S103_Yes), the movement state estimation unit 120 estimates that the user is in a movement state (S104). The movement state estimation unit 120 then stores the section in which the movement state is continuous as a movement section (S105). At this time, the pressure data from the section in which the movement state is continuous and the data from the section after are added to the movement section. The movement state estimation unit 120 performs this process to estimate the altitude before movement and the altitude after movement. The estimation of altitude will be described later. On the other hand, if the first difference is less than the first threshold (S013_No), the movement state estimation unit 120 estimates that the user is in a stopped state (S106). The movement state estimation unit 120 then stores the section in which the stopped state is continuous as a stopped section (S107). In this way, the acquired atmospheric pressure data is divided into movement sections and stopped sections.

[0039] The movement state estimation unit 120 can also estimate altitude changes. Figure 11 is a flowchart showing the second operation of the activity estimation device of the second embodiment. In the second operation, altitude changes in each movement section and each stopping section are estimated. The movement state estimation unit 120 calculates the difference between the first and last atmospheric pressure data in each movement section and each stopping section as the second difference (S201). Then, based on the second difference, it estimates the altitude change of the location of the shoes 400 in each movement section and stopping section (S202).

[0040] Figure 12 is a flowchart showing the first half of the third operation of the activity estimation device of the second embodiment. Figure 13 is a flowchart showing the second half of the third operation of the activity estimation device of the second embodiment. In the third operation, the movement state estimation unit 120 estimates whether the user's movement is walking, running, or movement using a means of transport. First, the movement state estimation unit 120 generates a graph plotting the atmospheric pressure data for each movement section against time (S301). Next, it generates a first straight line connecting the first and last atmospheric pressure data points on this graph (S302). Next, it generates corrected atmospheric pressure data by correcting the atmospheric pressure data within the movement section so that the slope of the first straight line is zero (S303). Next, it calculates the standard deviation σ of the corrected atmospheric pressure data (S304). Next, based on the calculated standard deviation σ, the movement state estimation unit 120 estimates whether the movement is walking, running, or movement using a means of transport. As is clear from the intensity of the movement, the standard deviations σ, in descending order, are stopping, walking, and running within the means of transport. Therefore, two thresholds are set for the standard deviation σ. A second threshold σ1 is set as the threshold for distinguishing between stopping and walking within the means of transport. A third threshold σ2 is set as the threshold for distinguishing between walking and running. Here, σ1 < σ2. Next, the movement state estimation unit 120 determines whether the standard deviation σ is less than the second threshold σ1 (S305). If the standard deviation σ is less than the second threshold σ1 (S305_Yes), the movement state estimation unit 120 estimates that the user is moving using the means of transport (S306). On the other hand, if the standard deviation σ is greater than or equal to the second threshold σ1 (S305_No), the movement state estimation unit 120 determines whether the standard deviation σ is less than the third threshold σ2 (σ1 ≤ σ < σ2) (S307). If the standard deviation σ is less than the third threshold σ2 (S307_Yes), the movement state estimation unit 120 estimates that the user is walking (S308). On the other hand, if the standard deviation σ is greater than or equal to the third threshold σ2 (S307_No), the movement state estimation unit 120 estimates that the user is running (S309).

[0041] As described above, the movement state estimation unit 120 estimates whether the user's movement is walking, running, or using a means of transport. Although not shown in the diagram, if the altitude changes in each movement section and each stopping section have been estimated in advance, the movement state estimation unit 120 can also estimate whether the walking, running, or movement using a means of transport was uphill, downhill, or on level ground.

[0042] The above explanation used standard deviation as an indicator of variability. However, other indicators of variability may also be used. Other indicators of variability include, for example, variance or the difference between the maximum and minimum values. (Specific example 1) Next, using specific atmospheric pressure data obtained in the experiment, we will explain the relationship between user activity and the time change of atmospheric pressure data inside the shoe 400. Figure 14 is a graph showing an example of atmospheric pressure data obtained by the activity estimation device 100 of the second embodiment. The sampling period for atmospheric pressure data is 1 s. In this specific example, the second threshold σ1 that distinguishes between stopping and walking within the means of movement is 80 Pa. The third threshold σ2 that distinguishes between walking and running is 300 Pa.

[0043] As can be seen from Figure 14, the time variation of atmospheric pressure data has both flat sections and sections where the altitude changes rapidly. As mentioned earlier, if adjacent users of atmospheric pressure data walk or run, changes in atmospheric pressure occur. Therefore, the parts of the atmospheric pressure data that fluctuate in altitude are thought to correspond to the users walking or running. Also, the flat sections of the atmospheric pressure data graph are thought to correspond to the users being stationary. Furthermore, as is obvious from common sense, the absolute value of atmospheric pressure changes with altitude. The relationship between altitude and atmospheric pressure near sea level in a standard atmosphere can be expressed, for example, by the following equation (1). H = 44330 × {1 - (P / 1013)^0.190263}, where the temperature is 15℃ ·····(1) From equation (1), a 1 Pa pressure change corresponds to approximately 8.3 cm near sea level (0 m). Based on this relationship, the change in altitude at the user's location can be estimated.

[0044] Next, a specific example will be described. Figure 15 is a graph showing an example of the correspondence between barometric pressure data acquired by the activity estimation device 100 of the second embodiment and user activity. This barometric pressure data was acquired experimentally. Therefore, the correspondence between user activity and barometric pressure data is known. For this reason, Figure 15 shows the user's activity for each period.

[0045] Next, we will explain how to estimate user activity from the time-dependent changes in atmospheric pressure data. First, we will explain the method of slope correction for calculating the standard deviation in each travel interval.

[0046] Figure 16 is an enlarged graph of section G in Figure 14. Figure 17 is a graph of section G in Figure 14 after slope correction. The movement state estimation unit 120 performs slope correction on this graph. First, the movement state estimation unit 120 generates a first straight line by connecting the first and last atmospheric pressure data points of this movement section. Next, the movement state estimation unit 120 corrects each atmospheric pressure data point within the movement section so that the slope of the first straight line becomes zero. Then, the movement state estimation unit 120 stores the generated corrected atmospheric pressure data as corrected atmospheric pressure data. Figure 17 shows the corrected atmospheric pressure data from Figure 16.

[0047] Next, we will explain an example of estimating the movement state in each movement segment of Figure 15. Figure 18 is an enlarged graph of section A of Figure 15. In Figure 15, the first threshold for distinguishing between movement and stationary states is set to 30 Pa. The movement segments are indicated by triangle markers. The movement state estimation unit 120 sets the third threshold σ2 of the standard deviation for distinguishing between walking and running to 300 Pa. In the case of Figure 18, the movement segment is from 126s to 152s. First, the movement state estimation unit 120 calculates the second difference, which is the difference between the first and last data points in this movement segment. The second difference is approximately 9 Pa. This second difference corresponds to a descent of approximately 0.7 m in altitude. Furthermore, the standard deviation of the atmospheric pressure data in this movement segment calculated using the regression line described above is 78 Pa. Therefore, the movement state estimation unit 120 estimates the user's movement as walking. This walking is also estimated to be a slight downhill. In reality, the user is walking on the first floor, so there is an error in the estimation by the movement state estimation unit 120. However, this error is smaller than the difference between the first and second floors. Therefore, it can be seen that the estimation by the movement state estimation unit 120 provides an estimate of the altitude difference.

[0048] Figure 19 is an enlarged graph of section B of Figure 15. In Figure 19, the movement intervals are 187s-190s and 195s-202s. The second difference between 187s-190s is almost zero, and the second difference between 195s-202s is approximately -36 Pa. From this, the movement state estimation unit 120 estimates that the user (location of the shoe) has risen by approximately 3.0m. The standard deviation after slope correction for the period 195s-201s is 184 Pa. From the above, the movement state estimation unit 120 estimates that the user is walking uphill and has risen by approximately 3m during this period.

[0049] Figure 20 is an enlarged graph of section F in Figure 15. In Figure 20, the movement interval is from 374s to 398s. The second difference in this movement interval is approximately -16 Pa. From this, the movement state estimation unit 120 estimates that the user has risen by approximately 1.2 m. The standard deviation after slope correction during this period is 444 Pa. This is above the third threshold of 300 Pa. Therefore, the movement state estimation unit 120 estimates that the user is in a driving state and is moving on relatively flat ground.

[0050] Figure 21 is an enlarged graph of section G in Figure 15. In Figure 21, 412s-416s and 420s-428s are estimated to be the movement intervals. The second difference in 412s-416s is almost zero. On the other hand, the second difference in 420s-428s is approximately 126 Pa. From this, the movement state estimation unit 120 estimates that the user is descending approximately 10.4 m. Also, the standard deviation after slope correction for the period 420s-428s is 38 Pa. This standard deviation is less than the second threshold of 80 Pa. Therefore, the movement state estimation unit 120 estimates that the user is moving by means of transport in this interval. As noted in the addendum to Figure 15, in reality, the user is moving from the 5th floor to the 3rd floor by elevator.

[0051] (modified version) As described above, the movement state estimation unit 120 can estimate whether the user is walking, running, or stopped, and whether they are going uphill or downhill. Since the intensity of exercise differs for each of these activities, the movement state estimation unit 120 can estimate the user's calorie consumption by setting a guideline calorie consumption coefficient for each activity. Figure 22 is a block diagram showing a modified example of the activity estimation device of the second embodiment. The movement state estimation unit 120 of the modified activity estimation device 101 has a calorie consumption coefficient holding unit 121 that holds the calorie consumption coefficient and a calorie consumption calculation unit 122.

[0052] The calorie consumption coefficients mentioned above are set for each activity, such as walking on flat ground, walking uphill, walking downhill, running on flat ground, running uphill, and running downhill. By calculating the duration of the activity using these calorie consumption coefficients, the user's calorie consumption during that activity can be calculated. Furthermore, by summing the calorie consumption for each activity, the user's total calorie consumption can be estimated.

[0053] Figure 23 is a table showing the setting of the calorie consumption coefficient and an example of its calculation. As shown in Figure 23, the calorie consumption can be calculated for each activity, and the total calorie consumption (Total) can be estimated.

[0054] (Specific example 2) Next, a specific example of how to attach the pressure measuring device 200 to the shoe 400 will be described. The pressure measuring device 200 can have the configuration illustrated in Figure 3-5, but other configurations are also possible. Figure 24 is a schematic cross-sectional view showing a second specific example of the placement of the pressure measuring device 200 of the second embodiment on the shoe 400. Figure 25 is a schematic plan view showing a second specific example of the placement of the pressure measuring device of the second embodiment on the shoe. In the configuration of the second specific example, the communication module 220 is placed in the arch portion of the insole 410, and the pressure sensor 210 is placed under the tongue on the upper side of the shoe 400. The cable 230 is placed along the edge of the insole 410 from the arch portion of the insole 410 to the center of the upper part of the shoe 400. The cable 230 is also placed along the inner surface of the shoe 400 so as to wrap around the upper part of the foot 900 (not shown) from that position. Furthermore, cable 230 extends to near the center of the tongue.

[0055] Figure 26 is a schematic cross-sectional view showing a third specific example of the arrangement of the barometric pressure measuring device 200 of the second embodiment in a shoe 400. Figure 27 is a schematic plan view showing a third specific example of the arrangement of the barometric pressure measuring device of the second embodiment in a shoe. In the configuration of the third specific example, the communication module 220 is placed in the arch portion of the insole 410, and the barometric pressure sensor 210 is placed at the tip of the toe of the insole 410. The cable 230 is placed in the plane of the insole 410. The cable 230 is arranged to meander in the portion between the arch and the toe. By making the cable 230 meander in this way, the bending stress applied to the cable 230 can be mitigated at points where bending stress is applied during walking or running.

[0056] Figure 28 is a schematic cross-sectional view showing a fourth specific example of the placement of the barometric pressure measuring device 200 in a shoe 400 according to the second embodiment. The communication module 220 of the barometric pressure measuring device 200 is located in the sole portion of the shoe 400. The cable 230 extends to the heel portion inside the shoe 400. The barometric pressure sensor 210 is located in the heel cup 412 portion of the insole 410. With this configuration, the barometric pressure measuring device 200 can be placed in the shoe 400 even when using a general-purpose insole 410.

[0057] Figure 29 is a schematic cross-sectional view showing a fifth specific example of the placement of the pressure measuring device in a shoe according to the second embodiment. The communication module 220 is placed in the arch portion of the insole 410. The pressure sensors 210 are placed in three locations: on the communication module 220, at the toe portion of the insole 410, and at the heel cup 412 portion of the insole 410. By using multiple pressure sensors 210 placed in multiple locations in this way, it becomes possible to analyze walking habits and measure pressure more accurately. In addition, vents 421, 422, and 423 are provided in the vicinity of where the pressure sensors 210 are placed in the shoe 400. The presence of vents 421, 422, and 423 improves the responsiveness of the pressure sensors 210 when measuring the outside air pressure. Although not shown in the figure, vents 421, 422, and 423 may be covered with water-repellent nonwoven fabric or a breathable waterproof sheet. This cover ensures the waterproofing of the shoe 400.

[0058] The activity estimation device 100 and other components of this embodiment have been described above.

[0059] The activity estimation device 100 of this embodiment includes a pressure data acquisition unit 110 (pressure data acquisition means) and a movement state estimation unit 120 (movement state estimation means). The pressure data acquisition unit 110 acquires pressure data from inside the shoes 400 worn by the user. The movement state estimation unit 120 estimates whether the user is moving or stationary based on the time change of the acquired pressure data. With this configuration, the activity estimation device 100 of this embodiment can estimate whether the user is moving or stationary based solely on the time change of the pressure data inside the shoes 400. Therefore, compared to the case where both the number of steps measured by an acceleration sensor and the pressure are used, as in Patent Document 2, the user's activity can be estimated with less computation.

[0060] In another embodiment, the activity estimation device 100 has a pressure data acquisition unit 110 (pressure data acquisition means) that samples pressure data at a predetermined period. Then, the movement state estimation unit 120 (movement state estimation means) calculates a first difference. The first difference is the difference between a given pressure data and the previous pressure data. The movement state estimation unit 120 estimates that the user is in a moving state if the first difference is greater than or equal to a first threshold. Also, if the first difference is less than the first threshold, the movement state estimation unit 120 estimates that the user is in a stationary state. By performing the estimation operation described above, it is possible to estimate whether the user is in a moving state or a stationary state based solely on the time change in pressure inside the shoe 400.

[0061] In another embodiment, the activity estimation device 100 has a movement state estimation unit (movement state estimation means) 120 that stores atmospheric pressure data divided into movement sections and stop sections. A movement section is a section in which the movement state is continuous and includes one atmospheric pressure data point before and after that section. A stop section is a section in which the stop state is continuous. With this configuration, the movement state estimation unit 120 can divide the atmospheric pressure data into movement sections and stop sections.

[0062] In another embodiment, the activity estimation device 100 has a movement state estimation unit 120 (movement state estimation means) that calculates a second difference. The second difference is the difference between the first and last atmospheric pressure data in each movement and stopping section. The movement state estimation unit 120 also estimates the change in altitude of the shoe's location in each movement and stopping section based on the second difference. With this configuration, the movement state estimation unit 120 can estimate the change in altitude of the shoe's (user's) location.

[0063] In another embodiment, the activity estimation device 100 has a movement state estimation unit 120 (movement state estimation means) that generates a graph plotting the atmospheric pressure data for each movement section against time. Next, the movement state estimation unit 120 generates a first straight line connecting the first atmospheric pressure data and the last atmospheric pressure data on the graph. Next, the movement state estimation unit 120 generates corrected atmospheric pressure data by correcting the values ​​of the atmospheric pressure data in each movement section so that the slope of the first straight line is zero. Next, the movement state estimation unit 120 calculates an index of the variability of the corrected atmospheric pressure data in the movement section using the corrected atmospheric pressure data. If the index of variability is less than a second threshold, the movement state estimation unit 120 estimates that the user's movement state in the movement section is movement by means of transportation that involves altitude changes. Also, if the index of variability is greater than or equal to the second threshold and less than a third threshold greater than the second threshold, the movement state estimation unit 120 estimates that the user's movement state in the movement section is walking. Furthermore, if the variability index is greater than or equal to the third threshold, the movement state estimation unit 120 estimates that the user's movement state in the movement section is running. In this way, the movement state estimation unit 120 can estimate whether the user's movement is by means of transportation, walking, or running.

[0064] In another embodiment, the activity estimation device 100 has a movement state estimation unit 120 (movement state estimation means) that estimates whether the running state and walking state were uphill, downhill, or on level ground, based on the altitude change in each of the aforementioned movement sections. With this configuration, the movement state estimation unit 120 can estimate whether the walking or running state is uphill, downhill, or on level ground. Furthermore, this estimation is based solely on the time change of atmospheric pressure data. In other words, the movement state estimation unit 120 can estimate the details of the user's activity with a small amount of computation.

[0065] Furthermore, the wireless communication terminal 310 of this embodiment includes one of the above-described activity estimation devices 100 and wireless communication means 311 for transmitting and receiving information about the activity estimation device 100. By including the activity estimation device 100 in the wireless communication terminal 310, for example, a user can estimate their calorie consumption based on the air pressure data inside the shoes 400 they are wearing.

[0066] Furthermore, the activity estimation system 1000 of this embodiment comprises one of the above-described activity estimation devices 100 and a pressure measuring device 200 attached to the shoe 400. The pressure measuring device 200 comprises a pressure sensor 210 (pressure measuring means) that measures the pressure inside the shoe as pressure data, and a communication module 220 (communication means) for transmitting the measured pressure data to the activity estimation device 100. With this configuration, the activity estimation system 1000 can estimate the user's activity based on the pressure inside the shoe 400 worn by the user. In the activity estimation system 1000, since the user's activity is estimated based only on the pressure inside the shoe 400, the user's activity can be estimated with less computation compared to the method that uses both acceleration and pressure as described in Patent Document 2.

[0067] Furthermore, in this embodiment, the activity estimation method involves the computer 300 acquiring atmospheric pressure data from inside the shoes 400 worn by the user, and estimating whether the user is moving or stationary based on the time change in the atmospheric pressure data. With this configuration, the activity estimation method of this embodiment can estimate whether the user is walking, running, or stationary based solely on the time change in the atmospheric pressure data inside the shoes 400. Therefore, compared to cases that use both the number of steps measured by an acceleration sensor and atmospheric pressure, as in Patent Document 2, the user's activity can be estimated with less computation.

[0068] Furthermore, the activity estimation program of this embodiment causes the computer to perform the following processes: acquiring atmospheric pressure data inside the shoes 400 worn by the user, and estimating whether the user is moving or stationary based on the time change in atmospheric pressure data. With this configuration, the activity estimation program of this embodiment can estimate whether the user is walking, running, or stationary based solely on the time change in atmospheric pressure data inside the shoes 400. For this reason, it is possible to estimate the user's activity with less computation than when using both the number of steps measured by an acceleration sensor and atmospheric pressure, as in Patent Document 2.

[0069] The present invention also includes programs that cause a computer to execute the processing of the first and second embodiments described above, and recording media that store such programs. Examples of recording media that can be used include magnetic disks, magnetic tapes, optical disks, magneto-optical disks, semiconductor memory, and the like.

[0070] The present invention has been described above using the first and second embodiments as exemplary examples. However, the present invention is not limited to the above embodiments. That is, the present invention can be applied in various forms that can be understood by those skilled in the art, within the scope of the present invention.

[0071] Some or all of the above embodiments may also be described as follows, but are not limited to the following: (Note 1) A means for acquiring atmospheric pressure data to acquire atmospheric pressure data inside shoes worn by the user, A movement state estimation means that estimates whether the user is in a moving state or a stationary state based on the time change of the aforementioned atmospheric pressure data, An activity estimation device characterized by having the following features. (Note 2) The aforementioned pressure data acquisition means, The barometric pressure data is sampled at a predetermined interval. The aforementioned movement state estimation means The first difference, which is the difference between the aforementioned pressure data and the previous pressure data, is calculated. If the aforementioned first difference is greater than or equal to the first threshold, it is determined that the user is in a moving state. If the first difference is less than the first threshold, it is determined that the user is in a stopped state. The activity estimation device described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned movement state estimation means The barometric pressure data is stored as a movement section, which includes the section in which the movement state is continuous and the section before and after it that includes the barometric pressure data, and the section in which the stop state is continuous is stored as a stop section. The activity estimation device described in Appendix 2, characterized by the features described herein. (Note 4) The aforementioned movement state estimation means The difference between the first and last atmospheric pressure data in each of the aforementioned moving and stopping sections is calculated as the second difference. Based on the second difference, the change in altitude of the shoe's position in each of the aforementioned movement and stopping sections is estimated. The activity estimation device described in Appendix 3, characterized by the features described herein. (Note 5) The aforementioned movement state estimation means A graph is generated by plotting the atmospheric pressure data for each of the aforementioned travel sections against time. A first straight line is generated connecting the first and last pressure data points of the graph. Corrected pressure data is generated by correcting the values ​​of the pressure data within each of the aforementioned movement sections so that the slope of the first straight line becomes zero. Using the corrected pressure data, an index of the variation in the corrected pressure data in the moving section is calculated. If the aforementioned variability index is less than the second threshold, it is estimated that the user's movement state in the movement section is movement by means of transportation involving altitude changes. If the variability index is greater than or equal to a second threshold and less than a third threshold greater than the second threshold, the movement state of the user in the movement section is estimated to be walking. If the aforementioned variability index is greater than or equal to the third threshold, it is estimated that the user's movement state in the movement section is driving. The activity estimation device according to appendix 3 or 4, characterized by the above. (Note 6) The aforementioned movement state estimation means Based on the altitude changes in each of the aforementioned travel sections, it is estimated whether the running and walking conditions were uphill, downhill, or on level ground. The activity estimation device described in Appendix 5, characterized by the features described herein. (Note 7) The aforementioned movement state estimation means When the rate of altitude change in the aforementioned stopping section or walking section is equal to or greater than the third threshold, it is determined that the user is moving using a means of transportation that involves altitude changes. An activity estimation device characterized by the features described in any of the appendices 4 to 6. (Note 8) An activity estimation device described in any one of the appendices 1 to 7, Wireless communication means for transmitting and receiving information related to the activity estimation device, A wireless communication terminal characterized by having the following features. (Note 9) An activity estimation device described in any one of the appendices 1 to 7, A pressure measuring device attached to the aforementioned shoe, It has, The aforementioned pressure measuring device is A pressure measuring means for measuring the air pressure inside the shoe as pressure data, The system includes a communication means for transmitting the measured atmospheric pressure data to the activity estimation device. An activity estimation system characterized by the following: (Note 10) Computers It acquires air pressure data from inside the shoes worn by the user. Based on the time change of the aforementioned atmospheric pressure data, it is estimated whether the user is in a moving state or a stationary state. A method for estimating activity characterized by the following features. (Note 11) A process to acquire air pressure data inside the shoes worn by the user, A process to estimate whether the user is in a moving state or a stationary state based on the time change of the aforementioned atmospheric pressure data, An activity estimation program characterized by having a computer execute it. [Explanation of symbols]

[0072] 1. Means for acquiring atmospheric pressure data 2. Means for estimating movement state 10, 100, 101 activity estimation device 90,400 shoes 91. Atmospheric pressure measurement means 92 Means of communication 110 barometric pressure data acquisition unit 120 Movement state estimation unit 200 bar pressure measuring device 210 barometric pressure sensor 220 Communication Module 230 Cable 300 Computers 310, 320 Wireless Communication Terminals 311 Wireless communication means 410 Insoles 500 Networks 1000 Activity Estimation Systems

Claims

1. A means for acquiring pressure data to acquire pressure data inside shoes worn by the user, A movement state estimation means that estimates whether the user is in a moving state or a stationary state based on the time change of the aforementioned atmospheric pressure data, It has, The aforementioned pressure data acquisition means, The barometric pressure data is sampled at a predetermined interval. The aforementioned movement state estimation means A first difference is calculated, which is the difference between the aforementioned pressure data and the previous pressure data. If the first difference is greater than or equal to the first threshold, it is estimated that the user is in a moving state. If the first difference is less than the first threshold, it is presumed that the user is in a stopped state. The section in which the movement state of the aforementioned pressure data is continuous, and the sections containing the pressure data before and after it, are stored as movement sections, and the section in which the stop state is continuous is stored as stop sections. A graph is generated by plotting the atmospheric pressure data for each of the aforementioned travel sections against time. A first straight line is generated connecting the first and last pressure data points of the graph. Corrected pressure data is generated by correcting the values ​​of the pressure data within each of the aforementioned movement sections so that the slope of the first straight line becomes zero. Using the corrected pressure data, an index of the variation in the corrected pressure data in the moving section is calculated. If the variability index is greater than or equal to a second threshold and less than a third threshold greater than the second threshold, the movement state of the user in the movement section is estimated to be walking. If the aforementioned variability index is greater than or equal to the third threshold, it is estimated that the user's movement state in the movement section is driving. An activity estimation device characterized by the following features.

2. The aforementioned movement state estimation means The difference between the first and last atmospheric pressure data in each of the aforementioned moving and stopping sections is calculated as the second difference. Based on the second difference described above, the change in altitude of the shoe's position in each of the aforementioned movement and stopping sections is estimated. The activity estimation device according to claim 1.

3. The aforementioned movement state estimation means Based on the altitude changes in each of the aforementioned travel sections, it is estimated whether the running and walking were uphill, downhill, or on level ground. The activity estimation device according to claim 1 or 2.

4. If the aforementioned variability index is less than the second threshold, it is estimated that the user's movement state in the movement section is movement by means of transportation. The activity estimation device according to any one of claims 1 to 3.

5. An activity estimation device according to any one of claims 1 to 4, Wireless communication means for transmitting and receiving information related to the activity estimation device, A wireless communication terminal characterized by having the following features.

6. An activity estimation device according to any one of claims 1 to 4, A pressure measuring device attached to the aforementioned shoe, It has, The aforementioned pressure measuring device is A pressure measuring means for measuring the air pressure inside the shoe as pressure data, The system includes a communication means for transmitting the measured atmospheric pressure data to the activity estimation device. An activity estimation system characterized by the following:

7. Computers It acquires air pressure data from inside the shoes worn by the user. In acquiring the aforementioned pressure data, sampling of the pressure data is performed at a predetermined period. Based on the time change of the aforementioned pressure data, a first difference is calculated, which is the difference between the current pressure data and the previous pressure data. If the first difference is greater than or equal to the first threshold, it is estimated that the user is in a moving state. If the first difference is less than the first threshold, it is presumed that the user is in a stopped state. The section in which the movement state of the aforementioned pressure data is continuous, and the sections containing the pressure data before and after it, are stored as movement sections, and the section in which the stop state is continuous is stored as stop sections. A graph is generated by plotting the atmospheric pressure data for each of the aforementioned travel sections against time. A first straight line is generated connecting the first and last pressure data points of the graph. Corrected pressure data is generated by correcting the values ​​of the pressure data within each of the aforementioned movement sections so that the slope of the first straight line becomes zero. Using the corrected pressure data, an index of the variation in the corrected pressure data in the moving section is calculated. If the variability index is greater than or equal to a second threshold and less than a third threshold greater than the second threshold, the movement state of the user in the movement section is estimated to be walking. If the aforementioned variability index is greater than or equal to the third threshold, it is estimated that the user's movement state in the movement section is driving. A method for estimating activity characterized by the following features.

8. A process for acquiring air pressure data inside a shoe worn by a user, A process to estimate whether the user is in a moving state or a stationary state based on the time change of the aforementioned atmospheric pressure data, Have the computer run it, In the process of acquiring the aforementioned pressure data, The barometric pressure data is sampled at a predetermined interval. In the process of estimating whether the user is in a moving state or a stationary state, A first difference is calculated, which is the difference between the aforementioned pressure data and the previous pressure data. If the first difference is greater than or equal to the first threshold, it is estimated that the user is in a moving state. If the first difference is less than the first threshold, it is presumed that the user is in a stopped state. The section in which the moving state of the aforementioned pressure data is continuous, and the sections containing the pressure data immediately before and after it, are defined as the moving section, and the section in which the stationary state is continuous is defined as the stationary section. A graph is generated by plotting the atmospheric pressure data for each of the aforementioned travel sections against time. A first straight line is generated connecting the first and last pressure data points of the graph. Corrected pressure data is generated by correcting the values ​​of the pressure data within each of the aforementioned movement sections so that the slope of the first straight line becomes zero. Using the corrected pressure data, an index of the variation in the corrected pressure data in the moving section is calculated. If the variability index is greater than or equal to a second threshold and less than a third threshold greater than the second threshold, the movement state of the user in the movement section is estimated to be walking. If the aforementioned variability index is greater than or equal to the third threshold, it is estimated that the user's movement state in the movement section is driving. Activity estimation program.

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