Speed ​​estimation method, speed estimation device, speed estimation system, and computer program

Abstract

The present invention estimates a walking speed of a quadrupedal animal. This speed estimation method is for estimating a walking speed of a quadrupedal animal, and comprises: determining a walking cycle of the animal using an acceleration acquired from an acceleration sensor 11 attached to the animal's body; and, by using a relationship among walking speed, walking cycle, and size of a prescribed portion indicative of the physical size of the animal determined in advance, estimating the walking speed of the animal from an acquired size of the prescribed region indicative of the physical size of the animal and the walking cycle determined from the acceleration.

Description

[Technical field]

[0001] The present disclosure relates to a speed estimation method, a speed estimation device, a speed estimation system, and a computer program. [Background technology]

[0002] In recent years, with the increase in pet populations and their longer life spans, animal healthcare, which involves monitoring pets' daily health conditions and the amount of exercise they receive, has been attracting attention.

[0003] Patent Document 1 describes a pedometer that includes an acceleration sensor that detects the acceleration of a pedestrian, a calculation unit that calculates the acceleration data output from the acceleration sensor and outputs the calculation results, a memory unit that stores the acceleration data and the calculation results, and a display unit that displays the calculation results, wherein the calculation unit calculates the walking pitch, stride length and walking speed of the pedestrian using the period and amplitude derived from the acceleration data, and displays them on the display unit.

[0004] Patent Document 2 describes an animal activity measuring device that is characterized by comprising a three-dimensional acceleration sensor that is fixed to an animal and detects acceleration signals (Gx, Gy, Gz) in the X direction, which is the forward / backward direction of the animal, the Y direction, which is the left / right direction, and the Z direction, which is the up / down direction of the animal; a memory unit that accumulates acceleration signals from the acceleration sensor; a tilt angle calculation unit that calculates a left / right tilt angle θx about the X axis of an XY plane relative to the Z direction and a front / back tilt angle θy about the Y axis based on the acceleration signal; and a tilt angle two-dimensional display control unit that displays the left / right tilt angle θx of the XY plane and the front / back tilt angle θy of the XY plane in two-dimensional graphics on a screen. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2006-118909 A [Patent Document 2] JP 2011-217928 A Summary of the Invention [Problem to be solved by the invention]

[0006] None of the documents describe estimating the walking speed of a quadrupedal animal, and it is desirable to grasp the amount of movement of a quadrupedal animal from its walking speed, for example. The present disclosure provides a speed estimation method, a speed estimation device, a speed estimation system, and a computer program capable of estimating the walking speed of a quadrupedal animal. [Means for solving the problem]

[0007] The speed estimation method disclosed herein is a speed estimation method for estimating the walking speed of a quadrupedal animal, which determines the animal's walking period using acceleration obtained from an acceleration sensor attached to the animal's body, and estimates the animal's walking speed from the walking period determined from the acquired size of a specific part of the animal's physique and the acceleration, using a predetermined relationship between the walking period and the size of a specific part of the animal's physique.

[0008] The speed estimation device disclosed herein is a speed estimation device that estimates the walking speed of a quadrupedal animal and includes a calculation device, which calculates the animal's walking period using acceleration obtained from an acceleration sensor attached to the animal's body, and estimates the animal's walking speed from the walking period calculated from the size of a specific part of the animal's physique and the acceleration using a predetermined relationship between the walking period and the size of a specific part of the animal's physique that is represented by the size and acceleration of the specific part of the animal that represents the animal's physique.

[0009] The speed estimation system disclosed herein is a speed estimation system that estimates the walking speed of a quadrupedal animal, and includes a measuring device having an acceleration sensor attached to the animal and detecting the animal's movement and a communication device that transmits the acceleration detected by the acceleration sensor, and a speed estimation device including a computing device, wherein the computing device determines the animal's walking period using the acceleration obtained from the measuring device, and estimates the animal's walking speed from the walking period determined from the acquired size of a specific part of the animal's physique and the acceleration, using a predetermined relationship between the walking period and the size of a specific part of the animal's physique.

[0010] These general and specific aspects may be realized by a system, a method, and a computer program, as well as combinations thereof. Effect of the Invention

[0011] According to the speed estimation method, speed estimation device, speed estimation system, and computer program disclosed herein, the walking speed of a quadrupedal animal can be estimated, and therefore, for example, the amount of momentum of the quadrupedal animal can be understood from its walking speed. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a schematic diagram illustrating a speed estimation system according to an embodiment. [Diagram 2] 2 is a block diagram showing a configuration of a measurement device of the speed estimation system of FIG. 1. [Figure 3A] 2 shows an example of XYZ axes used in the speed estimation system of FIG. 1. [Figure 3B] 3B shows an example of the XYZ axes as viewed from a different direction from that shown in FIG. 3A. [Figure 4] 1 is a block diagram showing a configuration of a speed estimation device according to an embodiment. [Figure 5A] 1 is a graph showing the results of measuring the walking cycle of dogs of various body lengths. [Figure 5B] 1 is a graph showing the results of measuring the walking cycle when walking at various speeds. [Figure 5C]This is a graph comparing the results of measuring the gait cycle when dogs belonging to different groups were made to walk at various speeds. [Figure 6] 2 is an example of a waveform showing acceleration obtained by the speed estimation system of FIG. 1. [Figure 7A] 7 is an example of a moving average waveform obtained from the waveform in FIG. 6. [Figure 7B] 7 is another example of a moving average waveform obtained from the waveform of FIG. 6. [Figure 8] FIG. 7B is a diagram for explaining how to determine a walking period using the waveform in FIG. 7A. [Figure 9] 5 is a flowchart illustrating an example of a speed estimation process in the speed estimation device of FIG. [Figure 10] FIG. 11 is a diagram illustrating a method for determining a walking period according to the first modified example. [Figure 11] FIG. 11 is a schematic diagram showing a speed estimation system according to a second modification. [Figure 12] FIG. 11 is a schematic diagram showing a speed estimation system according to a third modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] A speed estimation system, a speed estimation device, and a speed estimation method according to the embodiments will be described below with reference to the drawings. The speed estimation system, the speed estimation device, and the estimation method of the present disclosure estimate the walking speed of a quadrupedal animal. Specifically, the animal may be a quadrupedal animal that can be kept by humans. The speed estimation system according to the embodiments uses acceleration obtained by an acceleration sensor as the motion state of the animal. In the following description, the same components are denoted by the same reference numerals and description thereof will be omitted.

[0014] In the following description, unless otherwise specified, the "walking cycle" can be the period from when the right front leg lands to when the next right front leg lands. However, the "right front leg" is just an example, and can be any one of the four legs. Alternatively, the "walking cycle" can be determined using the waveform of acceleration obtained by an acceleration sensor. A method for determining the walking cycle will be described later, but for example, the walking cycle can be the period from one peak to the next peak in the waveform of acceleration measured by the acceleration sensor. The acceleration sensor used here can measure at least one of the accelerations in the x-axis, y-axis, or z-axis directions. For example, a three-axis acceleration sensor capable of measuring acceleration in three axes, x, y, and z, can be used to measure the acceleration. Alternatively, a six-axis sensor capable of measuring angular velocity in three axes, x, y, and z, can be used to measure the acceleration instead of the acceleration sensor. In this case, the walking cycle is determined using the acceleration and angular velocity.

[0015] Speed ​​Estimation System As shown in FIG. 1, a speed estimation system 1 according to an embodiment includes a measurement device 10 that is attached to an animal and measures acceleration that represents the state of the animal during movement. The speed estimation system 1 also includes a speed estimation device 20 that is owned by a user such as the owner of the animal. The speed estimation device 20 executes a process of receiving and registering the size of the animal, a process of determining the walking cycle of the animal from the acceleration measured by the measurement device, and a process of estimating the walking speed from the size and walking cycle of the animal. The measurement device 10 and the speed estimation device 20 are configured to be connectable via a network. In the following, an example will be described in which the animal is a dog, and the movement state of the dog during a walk is measured by an acceleration sensor, and the walking speed is estimated according to the movement state.

[0016] <Measuring Equipment> The measurement device 10 is a device attached to a dog, which is an animal whose walking speed is to be estimated as described above. As shown in FIG. 2, the measurement device 10 includes an acceleration sensor 11, a storage device 12, a communication device 13, and a calculation device 14. The measurement device 10 can be attached to a "leash," a "collar," a "harness," or the like used for walking the dog whose walking speed is to be estimated. Here, the "leash" is a string that connects a person to a dog during a walk. The "collar" is a ring that is attached around the dog's neck. For example, the collar may be formed so that a leash can be attached to the collar. The "harness" is a so-called harness that is attached to the dog's body. The harness may be formed so that a leash can be attached to the harness. Generally, when walking a dog, one end of the leash is attached to at least one of a collar or a harness, and the other end is held by a human such as the owner.

[0017] Here, if the measuring device 10 is attached to a lead, it is considered that the movement state of the animal measured by the acceleration sensor 11 will be unstable because the movement caused by factors other than the dog's movement is large compared to a collar or harness. Therefore, the measuring device 10 may be attached to a collar or harness that fits the dog more closely than a lead and is less susceptible to influences other than the dog's movement. When the measuring device 10 is attached to a collar or harness, it is possible to reduce the occurrence of shaking. The measuring device may also be attached to a harness. In the case of a harness, it is possible to reduce the risk of rotation by fitting closely to the torso. Furthermore, the measuring device 10 may be attached to a position along the spine of the animal. For example, the measuring device 10 may be attached to the harness so that the position of the acceleration sensor 11 in particular of the measuring device 10 is arranged along the spine of the dog.

[0018] The acceleration sensor 11 acquires at least one of the moving direction of the animal, the left-right direction set with respect to the moving direction, and / or the rate of change of the speed in the up-down direction set with respect to the moving direction. Here, as shown in FIG. 3A and FIG. 3B, when the dog moves forward, the moving direction is the y-axis direction, the left-right direction with respect to the moving direction of the y-axis is the x-axis direction, and the up-down direction with respect to the moving direction of the y-axis is the z-axis direction. The acceleration sensor 11 may be a three-axis acceleration sensor capable of measuring the acceleration of three axes of the x, y, and z-axes. As described above, instead of the acceleration sensor 11, a six-axis sensor capable of measuring the acceleration of three axes of the x, y, and z-axes and the angular velocity of three axes of the x, y, and z-axes may be used. In addition, in order to correct the axis of the acceleration sensor 11 or the angular velocity sensor, the measurement device 10 may have a three-axis geomagnetic sensor.

[0019] The storage device 12 is a recording medium for recording various information. The storage device 12 is realized by, for example, a RAM, a ROM, a flash memory, an SSD (Solid State Drive), a hard disk drive, other storage devices, or an appropriate combination of these. The storage device 12 stores a measurement program P1, which is a computer program executed by the arithmetic device 14, and various data such as measurement data D1 obtained by measuring acceleration and velocity.

[0020] The communication device 13 enables data communication with an external device (for example, the speed estimation device 20). The communication device 13 transmits the measurement data stored in the storage device 12 to the speed estimation device 20 at a predetermined timing. The predetermined timing may be, for example, a regular timing during a dog walk or a timing when the dog walk is finished. The above-mentioned data communication may be performed according to a known wireless or wired communication standard. When performing data communication during a dog walk, the communication device 13 may perform wireless communication. The communication device 13 may employ, for example, a communication circuit capable of performing communication according to the Bluetooth (registered trademark) standard.

[0021] The arithmetic unit 14 is a controller that controls the entire measuring device 10. The arithmetic unit 14 executes processes such as measuring acceleration with the acceleration sensor 11, storing the measurement data, and transmitting the measurement data by executing a measurement program P1 stored in the storage device 12. The arithmetic unit 14 may be various processors such as a CPU, an MPU, a GPU, an FPGA, a DSP, an ASIC, etc. Furthermore, the arithmetic unit 14 may be a hardware circuit designed specifically to realize a predetermined function.

[0022] <Speed ​​estimation device> As shown in the block diagram of FIG. 4, the speed estimation device 20 includes an input device 21, an output device 22, a communication device 23, a calculation device 24, and a storage device 25, and is realized by an information processing device such as a personal computer or a mobile terminal owned by a user.

[0023] The input device 21 is an operation button, a keyboard, a mouse, a touch panel, a microphone, etc., which are used for inputting operations and data. The output device 22 is a display, a speaker, etc., which are used for outputting processing results and data.

[0024] The communication device 23 enables data communication with the measurement device 10 and other external devices (not shown). The above-mentioned data communication may be performed according to a known communication standard. For example, the speed estimation device 20 may include, as the communication device 23, a plurality of circuits that comply with different communication standards, such as a circuit that enables wired data communication and a circuit that enables wireless data communication. For example, wired data communication is performed by using, as the communication device 23, a communication controller of a semiconductor integrated circuit that operates in compliance with the Ethernet (registered trademark) standard and / or the USB (registered trademark) standard. Wireless data communication is performed by using, as the communication device 23, a communication controller of a semiconductor integrated circuit that operates in compliance with the IEEE802.11 standard for LAN (Local Area Network) and / or the fourth / fifth generation mobile communication system, so-called 4G / 5G, for mobile communication.

[0025] The storage device 25 is a recording medium for recording various information. The storage device 25 is realized by, for example, a RAM, a ROM, a flash memory, an SSD (Solid State Drive), a hard disk drive, other storage devices, or an appropriate combination of them. The storage device 25 stores an estimation program P2, which is a computer program executed by the arithmetic device 24, a corresponding model D2, size data D3, accumulated data D4, and moving average data D5.

[0026] The corresponding model D2 is a model showing the relationship between the size of a predetermined part representing the physique of an animal, the walking cycle of an animal of that size, and the walking speed of the animal. This corresponding model D2 is a model obtained by measuring the walking cycle at a predetermined walking speed for a plurality of animals whose sizes of the predetermined parts have been measured in advance. By using the corresponding model D2, the walking speed can be estimated based on the size of the predetermined part of the animal and the walking cycle. For example, the corresponding model D2 may be a formula that derives the walking speed during a walk from the size of a predetermined part representing the physique of a dog and the walking cycle measured during a walk of a dog of that size. In addition, for example, the corresponding model D2 may be a table that specifies the relationship between the range of the size of the predetermined part, the walking cycle of a dog whose predetermined size is in the corresponding range, and the walking speed during the walk. The size of the predetermined part representing the physique can be, for example, at least one of the body length, body height, length of the forelimbs, or length of the hind limbs. Here, the "body length" of an animal refers to the length from the chest to the tip of the buttocks. The "body height" refers to the height from the ground to the back when the animal is standing on all four legs. "Forelimb length" refers to the height from the ground to the base of the front legs when the animal is standing on all fours. "Hind limb length" refers to the height from the ground to the base of the hind legs when the animal is standing on all fours.

[0027] For example, dogs with similar heights will have similar front and rear leg lengths, and similar body lengths. And dogs with similar heights will have similar walking cycles when walking at the same speed, regardless of breed. Therefore, the walking speed under the conditions can be estimated from the size of a specific part that represents the dog's physique and its walking cycle. Table 1 shows a comparison of correlation coefficients between the body length, body height, and front leg length and the walking cycle when multiple dogs are attached with acceleration sensors and made to walk on a treadmill at a speed of 3 km / h and when made to walk on a treadmill at a speed of 4 km / h. According to this, at a speed of 4 km / h, the correlation between the walking cycle and the body length, body height, and front leg length is extremely high for all of them. Also, at a speed of 3 km / h, the correlation between the body length and the walking cycle is the highest. Therefore, when estimating the walking speed from the size of a specific part that represents the physique and its walking cycle, the body length may be used as the size of a specific part that represents the physique. [Table 1]

[0028] FIG. 5A is a graph showing the correlation between the body length and the walking cycle of a dog. In FIG. 5A, the horizontal axis is the body length, and the vertical axis is the walking cycle. The straight line L1 in FIG. 5A shows the relationship between the walking cycle and each body length measured when multiple dogs (three dogs with different body lengths) are made to wear harnesses equipped with acceleration sensors and walk on a treadmill at a speed of 3 km / h. The straight line L2 shows the relationship between the walking cycle and the body length measured when the same multiple dogs are made to walk on a treadmill at a speed of 4 km / h. Specifically, the straight lines L1 and L2 in FIG. 5A are regression lines obtained by plotting the relationship between the body length and the walking cycle of the three dogs and using the least squares method or the like based on these points. In the example of FIG. 5A, the correlation coefficient between the straight line L1 and the actual result is 0.9323, and the correlation coefficient between the straight line L2 and the actual result is 0.9494, both of which are high values. Therefore, as shown by the straight lines L1 and L2 in FIG. 5A, the walking cycle of a dog at a given walking speed can be theoretically obtained from the sizes of given parts that represent the dog's physique.

[0029] FIG. 5B is a graph showing a line L3 indicating the relationship of the walking period according to the walking speed obtained from the theoretical relationship for obtaining the walking period of the dog's walking speed from the size of a specific part of the dog as shown in FIG. 5A for a certain dog. In FIG. 5B, the horizontal axis is the walking speed, and the vertical axis is the walking period. The line L3 in FIG. 5B is a regression line obtained based on the points plotted for the walking period actually measured when the dog is made to walk on a treadmill at speeds of 2 km, 3 km, 4 km, and 5 km per hour. In the example of FIG. 5A, the correlation coefficient between the line L3 and the actual measurement results is also a high value of 0.9797. Therefore, in the correspondence model D2, the correspondence relationship as described above in FIG. 5A and FIG. 5B is specified.

[0030] In this case, the corresponding model D2, an example of which is shown in FIG. 5A and FIG. 5B, can be a model for a dog in which at least one of the ratio of body length to body height, the ratio of body length to front leg length, or the ratio of body length to rear leg length is within a predetermined range. For example, there are multiple types of dogs, and for most of them, the ratio of body length to body height, and the ratio of body length to front leg or rear leg length are within a predetermined range. For example, dogs may be classified into large dogs, medium dogs, and small dogs by size, but regardless of their size, for most types of dogs, the above-mentioned ratios tend to be within a predetermined range. For dogs that meet these conditions, the relationship between walking speed and walking cycle tends to fall within a predetermined range for each size of a predetermined part that represents the physique, so that the walking speed can be derived from the size of a predetermined part that represents the physique and the walking cycle.

[0031] On the other hand, for dogs whose size of a predetermined part expressing the physique is outside a predetermined range, it is difficult to derive a walking speed according to the size of the predetermined part and the walking cycle using the correspondence model D2 described above with reference to Figs. 5A and 5B. For example, dachshunds, corgis, etc. are so-called short-legged dog breeds, and compared to other types of dogs, the length of their legs is short relative to their body length. If the ratio of the size of the predetermined part expressing such a physique is different from that of most types of dogs, it is difficult to obtain a walking speed according to the size of the body length, etc. and the walking cycle in the same manner as most other types of dogs. Therefore, the correspondence model D2 can be determined for each group for which a predetermined condition is set.

[0032] FIG. 5C includes a straight line L4 showing the relationship of the walking period according to the walking speed of a so-called short-legged dog breed in addition to the straight line L3 shown in FIG. 5B. Specifically, the straight line L3 also shown in FIG. 5B shows the relationship derived from the walking speed and walking period of a toy poodle selected as an example of a general dog that is not a short-legged dog breed. In contrast, the straight line L4 shows the relationship derived from the walking speed and walking period of a dachshund selected as an example of a short-legged dog breed. Specifically, the straight line L4 is a straight line obtained by plotting the walking period actually measured when a single dachshund is made to walk on a treadmill at speeds of 2.5 km, 4 km, and 4.5 km per hour, and using the plotted points. In the example shown in FIG. 5C, the correlation coefficient between the straight line L4 and the actual measurement result is 0.9589, which is a high value. Therefore, in the case of a dog other than a short-legged dog breed, the walking speed is obtained using the straight line L3, and in the case of a short-legged dog breed, the walking speed is obtained using the straight line L4, so that the walking speed can be accurately obtained according to the physique of the dog.

[0033] Table 1 and FIG. 5B above show an example of using the size of a predetermined part to represent the physique of an animal. FIG. 5C shows an example of dividing dogs into two types: so-called short-legged dog breeds such as dachshunds, whose legs are short relative to their body length, and dogs other than short-legged dog breeds, whose body length and leg length are normal, such as toy poodles. However, a method other than the method of using the size of a predetermined part or dividing dogs into short-legged dog breeds and other than short-legged dog breeds may be used. For example, a corresponding model D2 generated for each dog breed in more detail may be used. Also, for example, a corresponding model D2 generated for each group including several dog breeds may be used.

[0034] The size data D3 is size data of a predetermined part that represents the physique of the dog that is the subject of walking speed estimation input via the input device 21.

[0035] The accumulated data D4 is data that accumulates the measurement data D1 received from the measuring device 10. This accumulated data D4 is data that associates acceleration and speed with the time when they were measured. FIG. 6 is an example of a waveform showing acceleration included in the accumulated data D4. In FIG. 6, the horizontal axis represents time and the vertical axis represents sensor intensity. The waveform of the accumulated data D4 shown in FIG. 6 is an example that includes all accelerations [0.1 mG] on the X-axis, Y-axis, and Z-axis.

[0036] The moving average data D5 is data obtained by moving average of the waveform shown by the accumulated data D4. For example, FIG. 7A is an example of a waveform obtained by moving average of the waveform shown in FIG. 6 over three intervals. Here, "interval" refers to a certain time when the data has periodicity. In the example of FIG. 7A, one interval is 2.5 seconds. That is, data of the first interval is obtained from 0 to 2.5 seconds, data of the second interval is obtained from 2.5 to 5 seconds, and data of the third interval is obtained from 5 to 7.5 seconds. The moving average of the three intervals means that each of the data is averaged as 2.5 seconds. Note that the 2.5 seconds of one interval is only an example, and it is ideal to divide the intervals so that the start of the first interval and the start of the second interval are in the same phase. Also, FIG. 7B is an example of a waveform obtained by moving average of the waveform shown in FIG. 6 over eight intervals.

[0037] The arithmetic device 24 is a controller that controls the entire speed estimation device 20. The arithmetic device 24 executes a series of processes for estimating the walking speed of the target animal by executing an estimation program P2 stored in the storage device 25. The arithmetic device 24 may be various processors such as a CPU, an MPU, a GPU, an FPGA, a DSP, an ASIC, etc. Furthermore, the arithmetic device 24 may be a hardware circuit designed specifically to realize a predetermined function.

[0038] <Registering size data> The calculation device 24 acquires the sizes of the predetermined parts that represent the physique of the dog, and registers the size data D3 in the storage device 25. For example, the user inputs size data D3 indicating the sizes of the predetermined parts that represent the physique of the dog via the input device 21 at the timing of initial setup when the use of the speed estimation device 20 is started. Note that for grown-up dogs, the sizes of the predetermined parts usually do not change significantly. Therefore, once the calculation device 24 registers the size data D3 input at the timing of initial setup, it can acquire, specifically read and use, this size data D3 from the storage device 25 in subsequent walking speed estimations.

[0039] Calculating walking cycle The arithmetic device 24 determines the walking period of the animal using the acceleration obtained from the acceleration sensor 11 attached to the body of the animal. For example, the walking period determined by the arithmetic device 24 can be the period between adjacent peaks in a waveform representing the acceleration obtained by the acceleration sensor 11. Specifically, when the arithmetic device 24 obtains the measurement data D1 from the measurement device 10, it generates a waveform representing the acceleration and accumulates it as accumulated data D4. Furthermore, the arithmetic device 24 determines the walking period from the waveform represented in the accumulated data D4.

[0040] At this time, the arithmetic unit 24 calculates a moving average of the values ​​obtained by the acceleration sensor from the stored data D4, and can calculate the walking period of the animal from the waveform represented by this moving average of acceleration.

[0041] FIG. 8 shows an example of a walking cycle obtained by one peak (peak1) in the waveform of FIG. 7A and a peak (peak2) adjacent to this peak. In FIG. 8, P1 indicates a walking cycle obtained from the waveform of the Z axis. Also, P2 indicates a walking cycle obtained from the waveform of the X axis. In the example shown in FIG. 8, the peak is easy to identify in the waveform showing the acceleration in the Z axis direction, which is the vertical direction of the walking dog. Also, in the example shown in FIG. 8, the peak is easy to identify in the waveform showing the acceleration in the X axis direction, which is the horizontal direction of the walking dog. Furthermore, in the example shown in FIG. 8, the waveform showing the acceleration in the Y axis direction, which is the moving direction (front-back direction) of the dog, changes relatively little, but the position of each peak is linked to the waveform in the Z axis direction. In this case, the calculation device 24 can easily identify the walking cycle by using the waveform of either the acceleration showing the vertical direction or the horizontal direction. Furthermore, by further using the waveform showing the acceleration in the Y axis direction, the peak can be detected more accurately from the waveform showing the acceleration in the Z axis direction.

[0042] Although Fig. 8 shows an example of determining a walking cycle from one set of adjacent vertices, the calculation device 24 can sequentially determine a plurality of walking cycles from a plurality of sets of adjacent vertices. Specifically, as long as the dog continues to walk, the vertices are continuously present and the walking cycle is continuously observed. Therefore, the calculation device 24 can continuously determine each walking cycle by the above-mentioned method.

[0043] 《Walking speed estimation》 The calculation device 24 estimates the walking speed according to the size data D3 registered in the storage device 25 and the obtained walking cycle using the corresponding model D2. As described above, the calculation device 24 can continuously obtain the walking cycle, so that the calculation device 24 can estimate the walking speed continuously using the continuous walking cycle. Here, as described above with reference to FIG. 5C, when a relationship between a walking cycle and a walking speed different for each group is defined, the calculation device 24 estimates the walking speed using the corresponding model D2 corresponding to the group to which the dog to be predicted belongs. For example, in the example shown in FIG. 5C, when the dog is not a short-legged dog breed, the calculation device 24 estimates the walking speed using the straight line L3. When the dog is a short-legged dog breed, the calculation device 24 estimates the walking speed using the straight line L4.

[0044] Walking speed estimation method A walking speed estimation method implemented in the speed estimation device 20 according to the embodiment will be described with reference to the flowchart shown in Fig. 9. Since the specific processing of each step in the flowchart has been described above, each step will be described in a simplified manner.

[0045] First, at the time of registration, the arithmetic device 24 acquires the size of a predetermined part that represents the physique of the target dog via the input device 21 (S01). Here, the arithmetic device 24 stores the acquired size of the predetermined part in the storage device as size data D3.

[0046] Next, during a walk, the arithmetic device 24 acquires measurement data D1 including acceleration obtained by the acceleration sensor 11 from the measurement device 10 (S02). Here, the arithmetic device 24 stores the acquired measurement data D1 in the storage device 25 as accumulated data D4 to be accumulated.

[0047] Furthermore, the arithmetic unit 24 uses the accumulated data D4 to calculate a moving average of the acceleration (S03). Here, the arithmetic unit 24 stores the calculated moving average in the storage device 25 as moving average data D5.

[0048] The calculation device 24 calculates the walking period using the moving average data D5 obtained in step S03 (S04). Note that, although the walking period can be calculated more accurately by using the moving average data D5, the walking period may be calculated from the accumulated data D4. In that case, the process of step S03 is not necessary, and in step S04, the calculation device 24 calculates the walking period using the accumulated data D4.

[0049] Thereafter, the calculation device 24 uses the corresponding model D2 to estimate the walking speed according to the size of the size data D3 and the walking cycle obtained in step S03 (S05). At this time, the calculation device 24 estimates the walking speed using the corresponding model D2 according to the group to which the dog to be predicted belongs.

[0050] The arithmetic device 24 outputs the estimation result of step S05 (S06). In the flowchart shown in Fig. 9, the processes of steps S02 to S06 are performed during a walk, but the timing is not limited to the walk and may be when the user returns home after the walk.

[0051] In this manner, in the speed estimation device 20, the walking period of the animal is obtained using the acceleration obtained from the acceleration sensor while the animal is walking, and the walking speed can be estimated according to the size and walking period of the animal.

[0052] <Variation 1> The example described above using FIG. 8 is an example in which the walking period is obtained using adjacent peaks of the waveform. However, the walking period is not limited to this method, and can be obtained using various methods. For example, the calculation device 24 may determine the walking period as a period including adjacent intersections among a waveform indicating the acceleration obtained by the acceleration sensor 11 and an intermediate line connecting one positive peak of the waveform and a negative peak adjacent to the positive peak.

[0053] For example, as shown in FIG. 10, when an intermediate line (Middle) is provided in the middle between a peak on the positive side and a peak on the adjacent negative side, P3, which is the period from n1 to n5 of the intersection point between the waveform indicating acceleration and the intermediate line, is set as the walking cycle. In this case, the waveform in the Z-axis direction, which is the up-down direction of a walking dog, is easy to identify the peak on the positive side and the peak on the negative side. Therefore, in this case, the calculation device 24 may obtain the walking cycle from the waveform of acceleration indicating the up-down direction. In the waveform shown as an example in FIG. 10, the period from n1 to n5 before the peak on the positive side is set as the walking cycle. However, this is not necessarily limited to this as long as it is a period including five intersection points, and for example, the period from n2 to n6 may be set as the walking cycle. In addition, FIG. 10 shows an example including five intersection points, but the number of intersection points varies depending on the shape of the waveform indicating acceleration. For example, the number of intersection points may be other numbers such as three, seven, and nine. In these cases, the number of intersection points is also odd. In this case, the number of intersections between the Z-axis waveform and the intermediate line used to determine the walking cycle may be determined so as to match the walking cycle provisionally determined using, for example, two peaks of the X-axis waveform. The Z-axis waveform shown in FIG. 8 has a repeating pattern of large, small, large, small peaks that are easy to understand. From the Z-axis waveform shown in FIG. 8, it is easy to accurately determine the walking cycle using the interval between the two peaks on the positive side. However, the difference between the size of each peak is not necessarily as clear as shown in FIG. 8. For example, each peak may appear at the same size. When the size of each peak is about the same, the walking cycle can be accurately determined by using the number of intersections between the Z-axis waveform and the intermediate line, as shown in FIG. 10.

[0054] <Variation 2> The above-mentioned speed estimation system 1 has been described as an example including a measuring device 10 attached to an animal and a speed estimation device 20 such as a mobile terminal held by a user, i.e., a dog owner. However, the speed estimation system is not limited to this form. For example, as in a speed estimation system 1A according to a second modification shown in FIG. 11, the speed estimation device 20A may be provided separately from a user terminal 30 held by a dog owner, i.e., at the dog's home. In this speed estimation system 1A, the measurement data D1 accumulated in the storage device 12 of the measuring device 10 is transmitted collectively when the dog returns home after one walk. Then, when the speed estimation device 20A acquires the measurement data D1, it executes a speed estimation process and transmits the result to the user terminal 30, and causes the user terminal 30 to output it. In this speed estimation device 20A, if the size of a specific part of the dog can be acquired from the user terminal 30 via the communication device 23, the input device 21 is not necessary.

[0055] <Variation 3> A speed estimation system 1B according to a third modification shown in FIG. 12 is an example in which a speed estimation device 20B is present outside the dog and the owner's home in a state in which communication is possible via a network. In the speed estimation system 1B according to the third modification, a user terminal 30 transmits measurement data D1 received from a measuring device 10 to the speed estimation device 20B. When the speed estimation device 20 acquires the measurement data D1, the speed estimation device 20 executes a speed estimation process and transmits the result to the user terminal 30, which outputs the result. Note that, in the speed estimation device 20B, the input device 21 is not necessary if the size of a predetermined part of the dog can be acquired from the user terminal 30 via the communication device 23. For example, the speed estimation system 1B may be formed using a cloud network or the like.

[0056] Variation 4 In the above example, an example of predicting the walking speed using the size data D3 of the dog input by the user via the input device 21 has been described. However, the acquisition of the size data D3 of the dog is not limited to the input via the input device 21. For example, dogs of the same breed generally have similar body sizes. Therefore, in the speed estimation system 1, average size data indicating the average size of a predetermined part for each breed may be stored in the storage device 25 in advance and used. In this case, when the calculation device 24 acquires the breed of the dog for which the walking speed is to be estimated input by the user via the input device 21, the calculation device 24 refers to the average size data in the storage device 25, extracts the average size of the predetermined part of the acquired breed, and predicts it as the size of the predetermined part of the dog. The calculation device 24 may also estimate the walking speed of the dog using the predicted size of the predetermined part.

[0057] <Variation 5> Also, a size of a predetermined part of a dog may be predicted using a photo of the dog. For example, the storage device 25 stores a prediction model that has learned the relationship between the photo of the dog and the breed of the dog. The prediction model may be constructed by performing machine learning using a photo of the dog for each breed and a label of the breed of the dog as training data. Also, the storage device 25 stores average size data indicating an average size of a predetermined part for each breed. When the calculation device 24 acquires a photo of the dog, the calculation device 24 acquires a prediction result of the dog's breed from the photo of the dog using the prediction model. Also, the calculation device 24 refers to the average size data and predicts the average size of the predetermined part of the acquired breed as the size of the predetermined part of the dog. The calculation device 24 may estimate the walking speed of the dog using the predicted size.

[0058] Variation 6 Also, a photo of the dog may be used to predict the size of a specific part of the dog. For example, the calculation device 24 acquires a photo including a dog and a marker used to specify the size of the specific part of the dog. The marker is not limited as long as it can be used to specify the size, but for example, if the size of the measuring device 10 is fixed, the measuring device 10 may be used as the marker. Specifically, the calculation device 24 uses a photo of a dog wearing a harness to which the measuring device 10 is attached, and can predict the size of the specific part of the dog from the relationship between the size ratio of the dog included in the photo and the measuring device 10 as a marker. Also, the calculation device 24 may estimate the walking speed of the dog using the predicted size.

[0059] <1> A speed estimation method for estimating a walking speed of a quadrupedal animal, comprising the steps of: determining a walking period of the animal using acceleration obtained from an acceleration sensor attached to the body of the animal; estimating the walking speed of the animal from the acquired size of a predetermined part representing the animal's physique and the walking period calculated from the acceleration, using a predetermined relationship between the size of a predetermined part representing the animal's physique, the walking period, and the walking speed; Speed ​​estimation method. <2> The animal is a dog, The size is at least one of body length, body height, and forelimb length. <1> The speed estimation method according to claim 1 . <3> The animal is a dog whose body length to body height ratio or body length to front leg length ratio is within a predetermined range. <2> The speed estimation method according to claim 1 . <4> The walking cycle is a section between one peak and an adjacent peak of a waveform representing acceleration obtained by the acceleration sensor. <1> from <3> 13. The speed estimation method according to claim 12, <5> The waveform showing the acceleration is a moving average of the values ​​obtained by the acceleration sensor. <4> The speed estimation method according to claim 1 . <6> obtaining a breed of the dog whose walking speed is to be estimated; referring to average size data showing the average size of the predetermined part for each dog breed, predicting the average size of the predetermined part of the dog breed as the size of the predetermined part of the dog; Using the predicted size, estimate the walking speed of the dog. <2> The speed estimation method according to claim 1 . <7> Obtaining the size of the predetermined part of the animal; The obtained size is used to estimate the walking speed of the animal. <1> from <5> 13. The speed estimation method according to claim 12, <8> obtaining a photograph of the dog; predicting the breed of the dog from the captured photograph using a predictive model that predicts the breed of the dog from a photograph of the dog; referring to average size data showing the average size of the predetermined part for each dog breed, predicting the average size of the predetermined part of the dog breed as the size of the predetermined part of the dog; Using the predicted size, estimate the walking speed of the dog. <2> The speed estimation method according to claim 1 . <9> acquiring a photograph including the animal and a marker that is used to identify the size of the predetermined part of the animal; predicting a size of the predetermined part of the animal based on a relationship between the animal and the marker included in the photograph; The predicted size is used to estimate the average speed of the animal. <1> from <5> 13. The speed estimation method according to claim 12, <10> acquiring a size of the predetermined part of the animal by either inputting the size by a user via an input device or reading the size from a storage device; The obtained size is used to estimate the walking speed of the animal. <1> from <5> 13. The speed estimation method according to claim 12, <11> A speed estimation device for estimating a walking speed of a quadruped animal, comprising: a calculation device; The computing device includes: determining a walking period of the animal using acceleration obtained from an acceleration sensor attached to the body of the animal; estimating the walking speed of the animal from the acquired size of a predetermined part representing the animal's physique and the walking period calculated from the acceleration, using a predetermined relationship between the size of a predetermined part representing the animal's physique, the walking period, and the walking speed; Speed ​​estimation device. <12> A speed estimation system for estimating a walking speed of a quadruped animal, comprising: a measuring device including an acceleration sensor attached to the animal and detecting the movement of the animal, and a communication device transmitting the acceleration detected by the acceleration sensor; a speed estimation device including a calculation device, The computing device includes: Using the acceleration acquired from the measurement device, a walking period of the animal is calculated; estimating the walking speed of the animal from the acquired size of a predetermined part representing the animal's physique and the walking period calculated from the acceleration, using a predetermined relationship between the size of a predetermined part representing the animal's physique, the walking period, and the walking speed; Speed ​​estimation system. <13> The measuring device is attached to a location along the spine of the animal. <12> A speed estimation system as described in <14> The acceleration sensor acquires at least one of a rate of change in the moving direction of the animal, a left-right direction set with respect to the moving direction, and / or a rate of change in an up-down direction set with respect to the moving direction. <12> or <13> A speed estimation system as described in <15> <1> from <10> 13. A computer program product for causing a computing device to execute the speed estimation method according to any one of claims 1 to 12. As described above, examples of the technology disclosed in the present application have been shown and the above embodiments have been described. However, the technology in the present disclosure is not limited to these, and may be applied to embodiments in which modifications, substitutions, additions, omissions, etc. are made as appropriate.

[0060] The speed estimation method, speed estimation device, and speed estimation system described in all claims of the present disclosure are realized by cooperation of hardware resources (e.g., processor, memory) and computer programs. [Industrial Applicability]

[0061] The speed estimation method, speed estimation device, speed estimation system, and computer program disclosed herein are useful for determining the walking speed of a four-legged animal. [Explanation of symbols]

[0062] 1,1A,1B Speed ​​Estimation System 10. Measurement Equipment 20,20A,20B Speed ​​estimation device 30 User terminals 11 Acceleration Sensor 12 Storage device 13. Communications Equipment 14 Arithmetic unit 21 Input Devices 22 Output Devices 23 Communication Equipment 24 Arithmetic unit 25 Storage device D1 Measurement data D2 Compatible Models D3 size data D4 Accumulated Data D5 Moving Average Data P1 Measurement Program P2 Estimation Program

Claims

1. A speed estimation method for estimating a walking speed of a quadrupedal animal, comprising the steps of: determining a walking period of the animal using acceleration obtained from an acceleration sensor attached to the body of the animal; estimating the walking speed of the animal from the acquired size of a predetermined part representing the animal's physique and the walking period calculated from the acceleration, using a predetermined relationship between the size of a predetermined part representing the animal's physique, the walking period, and the walking speed; Speed ​​estimation method.

2. The animal is a dog, The size is at least one of body length, body height, and forelimb length. The method of claim 1 .

3. The animal is a dog whose body length to body height ratio or body length to front leg length ratio is within a predetermined range. The method of claim 2 .

4. The walking cycle is a section between one peak and an adjacent peak of a waveform representing acceleration obtained by the acceleration sensor. A method for estimating speed according to any one of claims 1 to 3.

5. The waveform showing the acceleration is a moving average of the values ​​obtained by the acceleration sensor. The method of claim 4 .

6. obtaining a breed of the dog whose walking speed is to be estimated; referring to average size data showing the average size of the predetermined part for each dog breed, predicting the average size of the predetermined part of the dog breed as the size of the predetermined part of the dog; Using the predicted size, estimate the walking speed of the dog. The method of claim 2 .

7. Obtaining the size of the predetermined part of the animal; The obtained size is used to estimate the walking speed of the animal. The method of claim 1 .

8. obtaining a photograph of the dog; predicting the breed of the dog from the captured photograph using a predictive model that predicts the breed of the dog from a photograph of the dog; referring to average size data showing the average size of the predetermined part for each dog breed, predicting the average size of the predetermined part of the dog breed as the size of the predetermined part of the dog; Using the predicted size, estimate the walking speed of the dog. The method of claim 2 .

9. acquiring a photograph including the animal and a marker that is used to identify the size of the predetermined part of the animal; predicting a size of the predetermined part of the animal based on a relationship between the animal and the marker included in the photograph; The predicted size is used to estimate the average speed of the animal. The method of claim 1 .

10. acquiring a size of the predetermined part of the animal by either inputting the size by a user via an input device or reading the size from a storage device; The obtained size is used to estimate the walking speed of the animal. The method of claim 1 .

11. A speed estimation device for estimating a walking speed of a quadruped animal, comprising: a calculation device; The computing device includes: determining a walking period of the animal using acceleration obtained from an acceleration sensor attached to the body of the animal; estimating the walking speed of the animal from the acquired size of a predetermined part representing the animal's physique and the walking period calculated from the acceleration, using a predetermined relationship between the size of a predetermined part representing the animal's physique, the walking period, and the walking speed; Speed ​​estimation device.

12. A speed estimation system for estimating a walking speed of a quadruped animal, comprising: a measuring device including an acceleration sensor attached to the animal and detecting the movement of the animal, and a communication device transmitting the acceleration detected by the acceleration sensor; a speed estimation device including a calculation device, The computing device includes: Using the acceleration acquired from the measurement device, a walking period of the animal is calculated; estimating the walking speed of the animal from the acquired size of a predetermined part representing the animal's physique and the walking period calculated from the acceleration, using a predetermined relationship between the size of a predetermined part representing the animal's physique, the walking period, and the walking speed; Speed ​​estimation system.

13. The measuring device is attached to a location along the spine of the animal. The speed estimation system of claim 12.

14. The acceleration sensor acquires at least one of a rate of change in the moving direction of the animal, a left-right direction set with respect to the moving direction, and / or a rate of change in an up-down direction set with respect to the moving direction. A speed estimation system according to claim 12 or 13.

15. A computer program for causing a computing device to execute the speed estimation method described in claim 1.

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