JP7792610B2 - Velocity calculation device, velocity calculation method, and velocity calculation program - Google Patents

Description

This disclosure relates to a speed calculation device, a speed calculation method, and a speed calculation program.

Technology has been proposed that calculates numerical values such as acceleration related to the user's hand movements for electronic devices held and used by the user, and based on the calculated results, determines whether the electronic device is being used appropriately and provides feedback to the user. Patent Document 1 discloses a toothbrush management and guidance system that provides guidance on tooth brushing activities when using an electric toothbrush. The management and guidance system disclosed in Patent Document 1 determines whether the user is brushing their teeth appropriately based on information obtained from an acceleration sensor attached to the toothbrush.

Special Publication No. 2020-534879

The management and guidance system disclosed in Patent Document 1 removes the gravity component from the acceleration, improving the accuracy of the calculated acceleration. However, electronic devices may contain noise other than gravity, such as the driving vibration of the electronic device itself or reaction force from the user. In other words, when calculating information corresponding to the movement of an electronic device, a more accurate calculation method that removes noise and other factors from the electronic device is desired.

This disclosure has been made in consideration of these problems with conventional technology. The purpose of this disclosure is to provide a velocity calculation device that can accurately calculate the velocity corresponding to the movement of an electronic device.

A speed calculation device according to an aspect of the present disclosure is provided in an electronic device and calculates a speed corresponding to the movement of the electronic device. The speed calculation device includes a sensor information acquisition unit that acquires sensor information related to acceleration acting on the electronic device from an acceleration sensor; a speed estimation unit that calculates an estimated speed for the movement of the electronic device based on the sensor information; an average speed calculation unit that performs filtering and integration on the sensor information to calculate an average speed corresponding to the movement of the electronic device; a relationship information calculation unit that calculates relationship information indicating the correspondence between the estimated speed and the average speed; and a speed determination unit that determines a speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed calculated by the speed estimation unit.

A speed calculation method according to another aspect of the present disclosure is a speed calculation method executed by a computer, which acquires sensor information relating to the acceleration acting on an electronic device from an acceleration sensor, calculates an estimated speed for the movement of the electronic device based on the sensor information, performs filtering and integration processing on the sensor information to calculate an average speed corresponding to the movement of the electronic device, calculates relationship information indicating the correspondence between the estimated speed and the average speed, and determines a speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed.

A speed calculation program according to another aspect of the present disclosure causes a computer to perform the following processes: acquire sensor information relating to the acceleration of an electronic device from an acceleration sensor; calculate an estimated speed for the movement of the electronic device based on the sensor information; perform filtering and integration on the sensor information to calculate an average speed corresponding to the movement of the electronic device; calculate relationship information indicating the correspondence between the estimated speed and the average speed; and determine the speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed.

This disclosure provides a velocity calculation device that can accurately calculate the velocity corresponding to the movement of an electronic device.

1 is a schematic diagram of an electric toothbrush equipped with a speed calculation device according to an embodiment of the present invention. 1 is a block diagram showing a schematic configuration of a velocity calculation device according to an embodiment of the present invention; 1 is a block diagram showing a functional configuration of a velocity calculation device according to an embodiment of the present invention; 5 is a diagram showing an example of a waveform of acceleration acquired by a sensor information acquisition unit according to the embodiment; FIG. FIG. 2 is a block diagram showing the functional configuration of a speed estimation unit according to the present embodiment. FIG. 10 is a diagram showing an example of a waveform of acceleration converted into absolute values by an absolute value processing unit according to the present embodiment. FIG. 10 is a diagram showing an example of a waveform of acceleration subjected to moving average processing by the first moving average processing unit according to the embodiment. FIG. 2 is a block diagram showing the functional configuration of an average velocity calculation unit according to the present embodiment. FIG. 10 is a diagram showing an example of a waveform of acceleration that has been subjected to low-pass filtering by the first low-pass filter according to the present embodiment. FIG. 10 is a diagram showing an example of a waveform of acceleration that has been subjected to high-pass processing by the high-pass processing unit according to the embodiment. FIG. 4 is a diagram showing an example of a waveform of a velocity calculated by a velocity calculation unit according to the present embodiment. FIG. 10 is a diagram showing an example of a waveform of velocity after low-pass processing by the second low-pass processor according to the embodiment. FIG. 10 is a diagram showing an example of a waveform of a velocity obtained by performing moving average processing in a second moving average processing unit according to the present embodiment. 10A and 10B are diagrams for explaining the process of determining an average speed in an average speed determination processing unit according to the present embodiment. 4 is a flowchart illustrating an example of processing performed by the velocity calculation device according to the present embodiment. 10 is a flowchart illustrating an example of a speed estimation process according to the present embodiment. 10 is a flowchart illustrating an example of an average speed calculation process according to the present embodiment.

Embodiments will be described in detail below with reference to the drawings. However, more detailed descriptions than necessary may be omitted. For example, detailed descriptions of well-known matters or redundant descriptions of substantially identical configurations may be omitted. Note that the accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

(General configuration of velocity calculation device 100)
The velocity calculation device 100 according to this embodiment is provided in an electronic device and calculates the velocity corresponding to the movement of the electronic device. Hereinafter, an embodiment in which an electric toothbrush 1 is applied as the electronic device will be described.

Figure 1 is a diagram showing the appearance of an electric toothbrush 1 equipped with a speed calculation device 100 according to this embodiment. As shown in Figure 1, the electric toothbrush 1 includes an activation switch 10 and a speed calculation device 100. In the example shown in Figure 1, the longitudinal direction of the electric toothbrush 1 (the vertical direction in Figure 1) is defined as the Y-axis direction. The left-right direction in Figure 1 is defined as the X-axis direction, and the depth direction in Figure 1 is defined as the Z-axis direction.

The electric toothbrush 1 is activated and stopped by the user turning the activation switch 10 on and off. The speed calculation device 100 calculates the speed of the user's hand moving while holding the electric toothbrush 1.

Figure 2 is a block diagram showing the configuration of the electric toothbrush 1. As shown in Figure 2, the electric toothbrush 1 includes a speed calculation device 100, an activation switch 10, and a sensor unit 11. In this embodiment, the sensor unit 11 is composed of an acceleration sensor.

The speed calculation device 100 includes a control unit 110, a storage unit 120, and an input/output IF 140 (interface). The speed calculation device 100 may also include a communication IF 130. The speed calculation device 100 may be configured as a general-purpose microcomputer including a CPU (control unit 110), memory (storage unit 120), and input/output IF 140. In this case, a computer program for causing the microcomputer to function as the speed calculation device 100 may be installed on the microcomputer. By executing the computer program, the microcomputer functions as multiple information processing circuits included in the speed calculation device 100. Note that while this embodiment illustrates an example in which the multiple information processing circuits included in the speed calculation device 100 are realized by software, it is of course also possible to configure the information processing circuits by providing dedicated hardware for executing each of the information processes described below. The multiple information processing circuits may also be configured as separate hardware.

The control unit 110 operates based on a program (not shown) stored in the memory unit 120, and executes the functions shown in Figure 3. Note that the program is not limited to being stored in the memory unit 120, and may be stored, for example, in a ROM (not shown) within the speed calculation device 100.

The storage unit 120 acquires and stores sensor information acquired by the sensor unit 11 via the input/output IF 140. As described above, the storage unit 120 may also store programs for each function executed by the control unit 110. The sensor information and programs stored in the storage unit 120 may be configured as physically or logically separated areas within a single storage device. Alternatively, the storage unit 120 for each data item may be configured to reside on multiple physically separate storage devices.

The communication IF 130 is an interface for communication between the speed calculation device 100 and various external devices via a wired and/or wireless network. The user may update the control program of the speed calculation device 100 via the communication IF 130. The user may also obtain sensor information stored in the memory unit 120 via the communication IF 130.

The input/output IF 140 is an interface for sending and receiving data, control signals, etc. between the speed calculation device 100 and the activation switch 10 and sensor unit 11 of the electric toothbrush 1. The input/output IF 140 may also function as a component (interface) for the user to exchange data with the speed calculation device 100.

(Functional Configuration of Velocity Calculation Device 100)
FIG. 3 is a block diagram showing the functional configuration of the velocity calculation device 100 according to this embodiment.

As shown in FIG. 3, the control unit 110 of the speed calculation device 100 has the following functions: a sensor information acquisition unit 111, a speed estimation unit 112, an average speed calculation unit 113, a relationship information calculation unit 114, a speed determination unit 115, and an output unit 116.

The sensor information acquisition unit 111 acquires the sensor information of the electric toothbrush 1 acquired by the sensor unit 11 as acceleration information. In other words, the sensor information acquisition unit 111 acquires sensor information related to the acceleration acting on the electric toothbrush 1 from the sensor unit 11, which is an acceleration sensor. The sensor information acquisition unit 111 also stores the acquired sensor information in the sensor information DB 121.

In this embodiment, the sensor information of the acceleration sensor acquired by the sensor information acquisition unit 111 is acceleration information in a predetermined direction. The predetermined direction is, for example, the Y-axis direction shown in FIG. 1, and the acceleration is acquired when the user holds (grabs) the electric toothbrush 1 and brushes while moving the electric toothbrush 1 in the Y-axis direction, which is the longitudinal direction of the electric toothbrush 1. Note that the predetermined direction of acceleration in the sensor information does not limit the configuration of this embodiment, and may be, for example, acceleration information relative to acceleration in the X-axis or Z-axis direction shown in FIG. 1.

Figure 4 is a diagram showing the waveform of the acceleration of the electric toothbrush 1 acquired by the sensor unit 11. In the diagram shown in Figure 4, the horizontal axis represents time, and the vertical axis represents the acceleration acquired by the sensor unit 11. As shown in Figure 4, the acceleration has a certain periodicity in which positive and negative values are repeated in a predetermined direction. For example, in the example shown in Figure 4, the acceleration waveform is repeated at a cycle of approximately 1.2 seconds. In other words, Figure 4 shows an example in which a user holding the electric toothbrush 1 moves the electric toothbrush 1 back and forth in a predetermined direction at intervals of approximately 1.2 seconds.

The speed estimation unit 112 estimates the speed of the electric toothbrush 1 based on the acceleration information of the electric toothbrush 1 acquired by the sensor information acquisition unit 111. That is, the speed estimation unit 112 calculates an estimated speed for the movement of the electric toothbrush 1 based on the acceleration information corresponding to the sensor information. The speed estimation unit 112 also associates the calculated estimated speed with the sensor information corresponding to the calculated estimated speed and stores it in the sensor information DB 121. Note that the storage location of the estimated speed is not limited to the sensor information DB 121, and the estimated speed may be stored in a memory location other than the sensor information DB 121 in association with the corresponding sensor information.

As shown in FIG. 5, the speed estimation unit 112 further includes a first unit conversion processing unit 112a, an absolute value processing unit 112b, a first moving average processing unit 112c, and an estimated cycle average speed determination unit 112d.

The first unit conversion processing unit 112a converts the acceleration value acquired by the sensor information acquisition unit 111 into the SI unit system (International System of Units). The unit system conversion in the first unit conversion processing unit 112a is performed based on the following equation (1). _{a s} [n] indicates the acceleration at the nth sample in the acceleration information acquired by the sensor information acquisition unit 111. a[n] indicates the acceleration at the nth sample after unit conversion.

The absolute value processing unit 112b performs processing to convert the acceleration (a) converted to SI units in the first unit conversion processing unit 112a into an absolute value. The absolute value processing in the absolute value processing unit 112b is performed in order to determine the magnitude of the average acceleration per cycle in the first moving average processing unit 112c, which will be described later. Fig. 6A shows an example of the waveform of the acceleration (a _a ) converted to an absolute value by the absolute value processing unit 112b. As shown in Fig. 6A, the absolute value processing unit 112b displays the acceleration (a) converted to SI units in the first unit conversion processing unit 112a in a form in which the negative portion is folded back to the positive side.

The first moving average processing unit 112c calculates a moving average over a predicted one cycle period for the acceleration (a _a ) converted to an absolute value by the absolute value processing unit 112b. That is, the first moving average processing unit 112c calculates the average acceleration per cycle over a predetermined period. The first moving average processing unit 112c performs the process shown in the following equation (2). The overlined a[n] is the acceleration (a _m ) calculated by the first moving average processing unit 112c.

Fig. 6B is a diagram showing an example of acceleration after moving average processing. In Fig. 6B, the acceleration (a _m ) after moving average processing is shown by a dotted line. In the example shown in Fig. 6B, one section is 1.2 seconds, which is one cycle, and 120 samples are taken in one cycle. In other words, in the example shown in Fig. 6B, the number of samples T per cycle in the above formula (2) is calculated as 120.

The estimated cycle average speed determiner 112d determines the moving average of the acceleration calculated by the first moving average processor 112c as the estimated cycle average speed (overlined V _e ). In this embodiment, the estimated cycle average speed determiner 112d determines the acceleration (a _m ) obtained by the moving average process as the estimated cycle average speed. This is based on the characteristic that, for example, when the electric toothbrush 1 is reciprocated in a predetermined direction, the acceleration is approximated by a trigonometric function, so that "acceleration ≈ speed." The estimated cycle average speed corresponds to the estimated speed.

For example, in the example shown in Fig. 6B, when the moving average acceleration (a _m ) is 2.8 m/s ² , the estimated cycle average velocity determiner 112d determines the estimated cycle average velocity (overlined V _e ) to be 2.8 m/s. That is, in the example shown in Fig. 6B, the estimated velocity is estimated to be 2.8 m/s.

Next, we will explain the average speed calculation unit 113. The average speed calculation unit 113 performs filtering and integration processing on the sensor information to calculate the average speed corresponding to the movement of the electric toothbrush 1.

As shown in FIG. 7, the average speed calculation unit 113 has as its functions a second unit conversion processing unit 113a, a first low-pass processing unit 113b, a high-pass processing unit 113c, and a speed calculation unit 113d. The average speed calculation unit 113 also has as its functions a second low-pass processing unit 113e, a second moving average processing unit 113f, and an average speed determination processing unit 113g.

The second unit conversion processing unit 113a converts the acceleration acquired by the sensor unit 11 into SI units (International System of Units). The unit conversion processing performed by the second unit conversion processing unit 113a is performed based on the above formula (1), similar to the first unit conversion processing unit 112a described above.

The first low-pass processing unit 113b performs low-pass processing (low-pass filter processing) as a filtering process on the acceleration (a _s ) converted to SI units by the second unit conversion processing unit 113a. The first low-pass processing unit 113b performs general low-pass processing as shown in the following equation (3). Here, k ₁ is a predetermined coefficient that can be set depending on the characteristics of the electronic device to which the velocity calculation device 100 is applied. a ₁ represents the acceleration performed by the first low-pass processing unit 113b. The first low-pass processing unit 113b performs low-pass processing as a filtering process to pass low-frequency components of the acceleration, i.e., remove high-frequency components, thereby making it possible to remove high-frequency noise such as drive noise and reaction force noise of the electric toothbrush 1.

Figure 8A is a graph showing an example of the results of low-pass filtering performed by the first low-pass filtering unit 113b.

The high-pass processing unit 113c performs high-pass processing (high-pass filter processing) as a filtering process on the acceleration (a _l ) that has been low-pass processed by the first low-pass processing unit 113b. The high-pass processing unit 113c performs general high-pass processing as shown in the following equation (4). Here, k ₂ is a predetermined coefficient that can be set depending on the characteristics of the electronic device to which the velocity calculation device 100 is applied. _{a h} represents the acceleration performed by the high-pass processing unit 113c. The high-pass processing unit 113c performs high-pass processing as a filtering process, and passes high-frequency components of the acceleration, i.e., removes low-frequency components, making it possible to remove the component of gravity acting on the electric toothbrush 1.

Figure 8B is a graph showing an example of the results of high-pass processing performed by the high-pass processing unit 113c.

The velocity calculation unit 113d calculates the velocity by integrating the result of the high-pass processing performed by the high-pass processing unit 113c. The velocity calculation unit 113d performs the integration process as shown in the following equation (5). Here, s in equation (5) is the sampling time of the acceleration sensor. For example, if one interval is 1.2 seconds and has 120 samples, the sampling time s is 10 ms. V _i indicates the velocity calculated by the velocity calculation unit 113d.

FIG. 8C is a graph showing an example of the velocity (V _i ) calculated by the velocity calculation unit 113d.

The second low-pass processing unit 113e performs low-pass processing (low-pass filter processing) as a filter process on the velocity (V _i ) calculated by the velocity calculation unit 113d. The second low-pass processing unit 113e performs general low-pass processing as shown in the following equation (6). Here, _k3 is a predetermined coefficient that can be set depending on the characteristics of the electronic device to which the velocity calculation device 100 is applied. V _l indicates the velocity performed by the second low-pass processing unit 113e. The second low-pass processing unit 113e performs this as data preprocessing for the average velocity determination processing unit 113g described below.

Fig. 8D is a graph showing an example of the results of low-pass filtering performed by the second low-pass processor 113e. In Fig. 8D, the velocity (V _l ) subjected to low-pass filtering by the second low-pass processor 113e is shown as a waveform indicated by a dotted line. Note that, to clearly show the results of the low-pass filtering performed by the second low-pass processor 113e, the waveform of the velocity (V _i ) shown in Fig. 8D is an example of a waveform of the velocity (V _i ) in a case different from the velocity (V _i ) shown in Fig. 8C .

The second moving average processor 113f performs moving average processing on the velocity (V _l ) that has been subjected to low-pass filtering by the second low-pass filter 113e, over a predicted one-cycle interval. Specifically, the processing shown in the following equation (7) is performed.

8E is a diagram showing an example of the speed at which the moving average processing is performed by the second moving average processing unit 113f. In FIG. 8E, the speed (V _m ) at which the moving average processing is performed is indicated by a dashed line.

The average speed determination processing unit 113g calculates the average speed between the maximum speed and the minimum speed for the moving average (V _m ) of the speed calculated by the second moving average processing unit 113f. That is, the average speed determination processing unit 113g calculates the average speed between the maximum speed and the minimum speed of the previous cycle. Specifically, the average speed is calculated using the following equation (8). The overlined V[n] indicates the average speed in the cycle at the nth sample. n _max indicates the nth sample of the maximum speed immediately before the extreme value (upper or lower limit) of the speed (moving average). n _min indicates the nth sample of the minimum speed immediately before the extreme value (upper or lower limit) of the speed (moving average).

8F is a diagram illustrating the calculation process of the average speed in the average speed determination processor 113g. At timing (1) in FIG. 8F, the average speed determination processor 113g measures the average speed A between sample point n _max , which is the maximum speed, and sample point n _min, which is the minimum speed. This average speed A is recognized as the speed of the previous cycle at the lower limit of the moving average shown in (2) in FIG. 8F.

Similarly, at timing (3) in Fig. 8F, the average speed determination processor 113g measures the average speed B between sample point n _min , which is the minimum speed, and sample point n _max , which is the maximum speed. This average speed B is recognized as the speed of the previous cycle at the upper limit of the moving average shown in (4) in Fig. 8F.

In this way, by performing moving average processing in the second moving average processing unit 113f, the results of the moving average processing appear with a delay relative to the time corresponding to the actual speed. This makes it easier to associate the average speed in a specified section with the speed obtained by moving average processing, allowing the average speed determination processing unit 113g to calculate the average speed with greater accuracy.

The relationship information calculation unit 114 calculates a relationship equation for determining the speed based on the estimated speed, which is the estimated average cycle speed (overlined V _e ) of the past cycle, and the average speed (overlined V) calculated by the average speed determination processing unit 113g. That is, the relationship information calculation unit 114 calculates relationship information indicating the correspondence between the estimated speed (overlined V e ) and the average speed (overlined V). The relationship information calculation unit 114 uses the least squares method to calculate a relationship equation (linear approximation) between the estimated average cycle speed of the past cycle (estimated speed, overlined V _e ) and the average cycle speed (overlined V) calculated by the average speed determination processing unit 113g. This enables the speed calculation device 100 to calculate a relationship equation (relationship information) that more accurately indicates the correspondence between the estimated speed and the average speed. In this embodiment, the relationship equation corresponds to the relationship information.

The relational expression calculated by the relational information calculation unit 114 is determined by equation (9), where α and β are coefficients in the relational expression.

α and β in the above formula (9) are determined by the following formulas (10) and (11).

The speed determination unit 115 determines the cycle average speed based on α and β and the relational expression calculated by the relationship information calculation unit 114. Specifically, the speed determination unit 115 determines the speed corresponding to the current movement of the electric toothbrush 1 based on the relational expression, which is the relationship information, and the current estimated speed calculated by the speed estimation unit 112. That is, by applying the current estimated cycle average speed (overlined V _e [n _now ]) estimated by the speed estimation unit 112 to the above formula (9), a more accurate speed (overlined V [n _now ]) can be determined.

The output unit 116 outputs a predetermined determination result according to the speed (overlined V[n _now ]) determined by the speed determination unit 115. Here, the predetermined determination result may be a result of determining whether or not the determined speed (overlined V[n _now ]) poses any problems when using the electric toothbrush 1. For example, the output unit 116 may be configured to output the determination result using a predetermined application (not shown).

(Processing flow of the velocity calculation device 100)
Next, the velocity calculation process (velocity calculation method) in the velocity calculation device 100 will be described with reference to the flowcharts in Figures 9 to 11. The series of operations of the velocity calculation device 100 shown in the flowcharts in Figures 9 to 11 begins when the activation switch 10 is turned on to activate the electric toothbrush 1, and ends when the activation switch 10 is turned off. The flowcharts shown in Figures 9 to 11 also end when the power switch (not shown) is turned off or an interrupt occurs to end the process. In the following description of the flowcharts, content that is the same as that described in the above description of the velocity calculation device 100 will be omitted or simplified.

In step S901, the control unit 110 determines whether the activation switch 10 is on. If the control unit 110 determines in step S901 that the activation switch 10 is on (step S901: YES), the process proceeds to step S902. On the other hand, if the control unit 110 determines in step S901 that the activation switch 10 is not on (step S901: NO), the process returns to step S901. In other words, the control unit 110 repeatedly performs the process of step S901 until the activation switch 10 is on.

In step S902, the sensor information acquisition unit 111 acquires the sensor information of the electric toothbrush 1 acquired by the sensor unit 11 as acceleration information. In this embodiment, the sensor information of the acceleration sensor acquired by the sensor information acquisition unit 111 is acceleration information in a predetermined direction. Next, processing proceeds to step S903.

In step S903, the speed estimation unit 112 estimates the speed of the electric toothbrush 1 based on the acceleration information of the electric toothbrush 1 acquired by the sensor information acquisition unit 111. That is, the speed estimation unit 112 calculates an estimated speed for the movement of the electric toothbrush 1 based on the acceleration information corresponding to the sensor information. Specifically, the speed estimation unit 112 estimates the speed through the process shown in the flowchart of FIG. 10. Details of the process of the flowchart shown in FIG. 10 will be described later. Next, the process proceeds to step S904.

In step S904, the average speed calculation unit 113 performs filtering and integration on the sensor information to calculate the average speed corresponding to the movement of the electric toothbrush 1. Specifically, by the processing shown in the flowchart of FIG. 11, the average speed calculation unit 113 performs filtering and integration on the sensor information to calculate the average speed corresponding to the movement of the electric toothbrush 1. Details of the processing in the flowchart shown in FIG. 11 will be described later. Next, the processing proceeds to step S905.

In step S905, the relationship information calculation unit 114 calculates a relationship equation for determining the speed based on the estimated speed, which is the estimated average cycle speed (overlined V _e ) of the past cycle, and the average speed (overlined V) calculated by the average speed determination processing unit 113g. That is, the relationship information calculation unit 114 calculates relationship information indicating the correspondence between the estimated speed (overlined V e ) and the average speed (overlined V). The relationship information calculation unit 114 uses the least squares method to calculate a relationship equation (linear approximation) between the estimated average cycle speed of the past cycle (estimated speed, overlined V _e ) and the average cycle speed (overlined V) calculated by the average speed determination processing unit 113g. This enables the speed calculation device 100 to calculate a relationship equation (relationship information) that more accurately indicates the correspondence between the estimated speed and the average speed. In this embodiment, the relationship equation corresponds to the relationship information. Next, the process proceeds to step S906.

In step S906, the speed determination unit 115 determines the cycle average speed based on α and β and the relational expression calculated by the relationship information calculation unit 114. Specifically, the speed determination unit 115 determines the speed corresponding to the current movement of the electric toothbrush 1 based on the relational expression, which is the relationship information, and the current estimated speed calculated by the speed estimation unit 112. That is, by applying the current estimated cycle average speed (overlined V _e [n _now ]) estimated by the speed estimation unit 112 to the above equation (9), a more accurate speed (overlined V [n _now ]) can be determined. Next, the process proceeds to step S907.

In step S907, the control unit 110 determines whether the activation switch 10 is off. If the control unit 110 determines in step S907 that the activation switch 10 is off (step S907: YES), the process ends. On the other hand, if the control unit 110 determines in step S907 that the activation switch 10 is not off (step S907: NO), the process returns to step S902 and repeats the process from step S902.

(Speed estimation process)
Next, the speed estimation process in step S903 in FIG. 9 will be described with reference to the flowchart in FIG.

In step S1001, the first unit conversion processing unit 112a converts the acceleration value acquired by the sensor information acquisition unit 111 into the SI unit system (International System of Units). The unit system conversion in the first unit conversion processing unit 112a is performed based on the above-mentioned equation (1). Next, processing proceeds to step S1002.

In step S1002, the absolute value processing unit 112b converts the acceleration (a) converted to SI units by the first unit conversion processing unit 112a into an absolute value. The absolute value processing by the absolute value processing unit 112b is performed so that the magnitude of the average acceleration per cycle can be calculated by the first moving average processing unit 112c. Next, processing proceeds to step S1003.

In step S1003, the first moving average processing unit 112c calculates a moving average over a predicted one cycle period for the acceleration (a _a ) converted into absolute values by the absolute value processing unit 112b. That is, the first moving average processing unit 112c calculates the average acceleration per cycle over a predetermined period. The first moving average processing unit 112c performs the process shown in equation (2) above. Next, the process proceeds to step S1004.

In step S1004, the estimated cycle average speed determiner 112d determines the moving average of the acceleration calculated by the first moving average processor 112c as the estimated cycle average speed (estimated speed, overlined V _e ). In this embodiment, the estimated cycle average speed determiner 112d determines the acceleration (a _m ) obtained by the moving average process as the estimated cycle average speed (estimated speed). This is based on the characteristic that, for example, when the electric toothbrush 1 is reciprocated in a predetermined direction, the acceleration is approximated by a trigonometric function, so that "acceleration ≈ speed." Then, the process returns to step S903 in the flowchart shown in FIG. 9 .

(Average speed calculation process)
Next, the average speed calculation process in step S904 in FIG. 9 will be described with reference to the flowchart in FIG.

In step S1101, the second unit conversion processing unit 113a converts the acceleration acquired by the sensor unit 11 into SI units (International System of Units). The unit conversion processing performed by the second unit conversion processing unit 113a is performed based on the above formula (1), similar to the first unit conversion processing unit 112a described above. Next, processing proceeds to step S1102.

In step S1102, first low-pass processing unit 113b performs low-pass processing on the acceleration (a _s ) converted to SI units by second unit conversion processing unit 113a. First low-pass processing unit 113b performs general low-pass processing as shown in equation (3) above. In step S1102, first low-pass processing unit 113b passes low-frequency components of the acceleration, i.e., removes high-frequency components, thereby making it possible to remove high-frequency noise such as that due to the drive or reaction force of electric toothbrush 1. Next, processing proceeds to step S1103.

In step S1103, the high-pass processor 113c performs high-pass processing on the acceleration (a _l ) that has been low-pass processed by the first low-pass processor 113b. The high-pass processor 113c performs general high-pass processing as shown in the above equation (4). In step S1103, the high-pass processor 113c passes the high-frequency components of the acceleration, i.e., removes the low-frequency components, thereby making it possible to remove the component of gravity acting on the electric toothbrush 1. Next, the process proceeds to step S1104.

In step S1104, the velocity calculation unit 113d calculates the velocity by integrating the result of the high-pass processing performed by the high-pass processing unit 113c. The velocity calculation unit 113d performs the integration process as shown in equation (5) above. Next, processing proceeds to step S1105.

In step S1105, the second low-pass processor 113e performs low-pass filtering on the velocity (V _i ) calculated by the velocity calculator 113d. The second low-pass processor 113e performs general low-pass filtering as shown in the above equation (6). Next, the process proceeds to step S1106.

In step S1106, the second moving average processor 113f performs moving average processing on the velocity (V _l ) that has been subjected to low-pass filtering by the second low-pass filter 113e, over a predicted one-cycle period. Specifically, the processing shown in equation (7) above is performed. Next, the processing proceeds to step S1107.

In step S1107, the average speed determination processing unit 113g calculates the average speed between the maximum speed and the minimum speed for the moving average (V _m ) of the speeds calculated by the second moving average processing unit 113f. Specifically, the average speed is calculated using the above-mentioned equation (8). Thereafter, the processing returns to step S904 in the flowchart shown in FIG. 9.

As described above, the speed calculation device 100 includes a sensor information acquisition unit 111, a speed estimation unit 112, an average speed calculation unit 113, a relationship information calculation unit 114, and a speed determination unit 115. The sensor information acquisition unit 111 acquires sensor information related to the acceleration acting on the electronic device from an acceleration sensor. The speed estimation unit 112 calculates an estimated speed for the movement of the electronic device based on the sensor information. The average speed calculation unit 113 performs filtering and integration processing on the sensor information to calculate an average speed corresponding to the movement of the electronic device. The relationship information calculation unit 114 calculates relationship information indicating the correspondence between the estimated speed and the average speed. The speed determination unit 115 determines a speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed calculated by the speed estimation unit 112.

In other words, the velocity calculation device 100 calculates the velocity corresponding to the movement of the electronic device using relationship information that indicates the correspondence between the estimated velocity estimated for the movement of the electronic device and the average velocity corresponding to the movement of the electronic device. This allows the velocity calculation device 100 to calculate the velocity corresponding to the movement of the electronic device more accurately than simply calculating the estimated velocity estimated for the movement of the electronic device as the velocity corresponding to the movement of the electronic device.

Furthermore, the filtering process of the average velocity calculation unit 113 of the velocity calculation device 100 may include low-pass filtering to remove high-frequency components. This enables the velocity calculation device 100 to remove high-frequency noise such as that caused by the driving force or reaction force of the electronic device when calculating the velocity corresponding to the movement of the electronic device.

Furthermore, the filtering process of the average velocity calculation unit 113 of the velocity calculation device 100 may further include high-pass filtering to remove low-frequency components. This allows the velocity calculation device 100 to remove the gravity component acting on the electronic device by removing low-frequency components when calculating the velocity corresponding to the movement of the electronic device.

Furthermore, the relationship information calculation unit 114 of the speed calculation device 100 may calculate relationship information indicating the correspondence between an estimated speed estimated for the movement of the electronic device and an average speed corresponding to the movement of the electronic device using the least squares method. This enables the speed calculation device 100 to calculate relationship information that more accurately indicates the correspondence between the estimated speed and the average speed.

The average speed calculation unit 113 of the speed calculation device 100 may also calculate the average speed by performing moving average processing. This causes the results of the moving average processing to appear with a delay relative to the time corresponding to the actual speed, making it easier to associate the average speed in a specified section with the speed obtained by moving average processing. This allows the speed calculation device 100 to calculate the average speed with greater accuracy.

(Other embodiments)
Although the present embodiment has been described above, the embodiment is not limited to these, and various modifications are possible within the scope of the gist of the embodiment. It is also possible to combine some or all of the various embodiments to create a new embodiment. In other words, the above-described embodiment is intended to illustrate the technology of the present disclosure, and various modifications, substitutions, additions, omissions, etc. may be made within the scope of the claims or their equivalents.

In the above-described embodiment, the electronic device is an electric toothbrush 1. The speed calculation device 100 according to this embodiment may also be applied to, for example, an iron or electric shaver as a device for determining the hand movements of a user using the electronic device. In this case, the interval of one cycle, which was set to 1.2 seconds in the case of the electric toothbrush 1 described above, may be set to a time shorter or longer than 1.2 seconds to suit the electronic device. Furthermore, the application of the speed calculation device 100 is not limited to electronic devices held by the user in the hand; for example, electronic devices to which the speed calculation device 100 can be applied may be devices worn on the user's body. This makes it possible to realize a speed calculation device 100 that can determine whether the user's body movements are appropriate for a specific purpose.

Furthermore, a computer program (speed calculation program) that causes a computer to execute the above-described speed calculation method and a computer-readable recording medium on which the program is recorded are included within the scope of this embodiment. Any type of computer-readable recording medium may be used. Furthermore, the above-described computer program is not limited to being recorded on the above-described recording medium, but may also be transmitted via a telecommunications line, a wireless or wired communication line, a network such as the Internet, or the like.

The following describes the features of the velocity calculation device 100, velocity calculation method, and velocity calculation program according to this embodiment.

(1) A velocity calculation device 100 that is provided in an electronic device and calculates a velocity corresponding to the movement of the electronic device has the following configuration.
(i) The electronic device includes a sensor information acquisition unit 111 that acquires sensor information relating to acceleration applied to the electronic device from an acceleration sensor.
(ii) A speed estimation unit 112 is included that calculates an estimated speed of the movement of the electronic device based on sensor information.
(iii) An average speed calculation unit 113 that performs filtering and integration on the sensor information to calculate an average speed corresponding to the movement of the electronic device is included.
(iv) A relationship information calculation unit 114 is included that calculates relationship information indicating the correspondence between the estimated speed and the average speed.
(v) A speed determination unit 115 is included that determines a speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed calculated by the speed estimation unit 112.

According to the present disclosure, the velocity calculation device 100 calculates the velocity corresponding to the movement of the electronic device using relationship information indicating the correspondence between the estimated velocity estimated for the movement of the electronic device and the average velocity corresponding to the movement of the electronic device. This enables the velocity calculation device 100 to calculate the velocity corresponding to the movement of the electronic device more accurately than simply calculating the estimated velocity estimated for the movement of the electronic device as the velocity corresponding to the movement of the electronic device.

(2) The filtering process may include low-pass filtering to remove high-frequency components.

According to the present disclosure, the velocity calculation device 100 is able to remove high-frequency noise such as that caused by the driving force or reaction force of an electronic device when calculating the velocity corresponding to the movement of the electronic device.

(3) The filtering process may further include high-pass filtering to remove low-frequency components.

According to the present disclosure, the velocity calculation device 100 can remove the gravity component acting on the electronic device by removing low-frequency components when calculating the velocity corresponding to the movement of the electronic device.

(4) The relationship information calculation unit 114 may calculate the relationship information using the least squares method.

According to the present disclosure, the speed calculation device 100 is able to calculate relationship information that more accurately indicates the correspondence between the estimated speed and the average speed.

(5) The average speed calculation unit 113 may further calculate the average speed by performing moving average processing.

According to the present disclosure, the speed calculation device 100 displays the results of moving average processing with a delay relative to the time corresponding to the actual speed, making it easy to associate the average speed in a specified section with the speed obtained by moving average processing. This allows the speed calculation device 100 to achieve greater accuracy in calculating the average speed.

(6) A computer-implemented speed calculation method includes the following steps:
(i) The process includes acquiring sensor information relating to the acceleration applied to the electronic device from an acceleration sensor.
(ii) A process for calculating an estimated speed of the movement of the electronic device based on the sensor information.
(iii) The process includes filtering and integrating the sensor information to calculate an average velocity corresponding to the movement of the electronic device.
(iv) The process includes calculating relationship information indicating the correspondence between the estimated speed and the average speed.
(v) determining a speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed;

According to the present disclosure, the speed calculation method calculates the speed corresponding to the movement of the electronic device using relationship information indicating the correspondence between an estimated speed estimated for the movement of the electronic device and an average speed corresponding to the movement of the electronic device. This makes it possible for the speed calculation method to calculate the speed corresponding to the movement of the electronic device more accurately than simply calculating the estimated speed estimated for the movement of the electronic device as the speed corresponding to the movement of the electronic device.

(7) A speed calculation program executed by a computer includes the following processes.
(i) The process includes acquiring sensor information relating to the acceleration applied to the electronic device from an acceleration sensor.
(ii) A process for calculating an estimated speed of the movement of the electronic device based on the sensor information.
(iii) The process includes filtering and integrating the sensor information to calculate an average velocity corresponding to the movement of the electronic device.
(iv) The process includes calculating relationship information indicating the correspondence between the estimated speed and the average speed.
(v) determining a speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed;

According to the present disclosure, the speed calculation program calculates the speed corresponding to the movement of the electronic device using relationship information indicating the correspondence between the estimated speed estimated for the movement of the electronic device and the average speed corresponding to the movement of the electronic device. This enables the speed calculation program to calculate the speed corresponding to the electronic device with greater accuracy than simply calculating the estimated speed estimated for the movement of the electronic device as the speed corresponding to the movement of the electronic device.

This disclosure is applicable to electronic devices that are held by the user and moved in a predetermined direction. Specifically, this disclosure is applicable to electric toothbrushes, electric shavers, irons, etc.

REFERENCE SIGNS LIST 1 Electric toothbrush 10 Operation switch 11 Sensor unit 100 Speed calculation device 111 Sensor information acquisition unit 112 Speed estimation unit 113 Average speed calculation unit 114 Related information calculation unit 115 Speed determination unit 116 Output unit 121 Sensor information DB

Claims (7)

A velocity calculation device provided in an electronic device and calculating a velocity corresponding to a movement of the electronic device,
a sensor information acquisition unit that acquires sensor information relating to acceleration applied to the electronic device from an acceleration sensor;
a speed estimation unit that calculates an estimated speed of the movement of the electronic device based on the sensor information;
an average speed calculation unit that performs filtering and integration on the sensor information to calculate an average speed corresponding to the movement of the electronic device;
a relationship information calculation unit that calculates relationship information indicating a correspondence relationship between the estimated speed and the average speed based on the past estimated speed and the past average speed;
a speed determination unit that determines the speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed calculated by the speed estimation unit. The velocity calculation device of claim 1, wherein the filtering process includes low-pass filtering that removes high-frequency components. The velocity calculation device of claim 2, wherein the filtering process further includes high-pass filtering to remove low-frequency components. The velocity calculation device described in any one of claims 1 to 3, wherein the relationship information calculation unit calculates the relationship information using the least squares method. The velocity calculation device of any one of claims 1 to 4, wherein the average velocity calculation unit further calculates the average velocity by performing moving average processing. 1. A computer-implemented method for calculating velocity, comprising:
Acquires sensor information relating to acceleration applied to the electronic device from an acceleration sensor;
calculating an estimated speed of the movement of the electronic device based on the sensor information;
filtering and integrating the sensor information to calculate an average velocity corresponding to the movement of the electronic device;
calculating relationship information indicating a correspondence relationship between the estimated speed and the average speed based on the past estimated speed and the past average speed;
A speed calculation method for determining a speed corresponding to a current movement of the electronic device based on the relationship information and the current estimated speed. Acquires sensor information relating to acceleration applied to the electronic device from an acceleration sensor;
calculating an estimated speed of the movement of the electronic device based on the sensor information;
filtering and integrating the sensor information to calculate an average velocity corresponding to the movement of the electronic device;
calculating relationship information indicating a correspondence relationship between the estimated speed and the average speed based on the past estimated speed and the past average speed;
A speed calculation program that causes a computer to execute a process of determining a speed corresponding to the current movement of the electronic device based on the relationship information and the current estimated speed.