JP2013190377A - State detection device, electronic apparatus, measurement system and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a state detection device that performs acceleration measurement and can estimate a moving speed while suppressing a calculation amount, and further to provide an electronic apparatus, a measurement system, a program or the like.SOLUTION: A state detection device 100 includes: an acquisition section 110 for acquiring detected acceleration from an acceleration sensor 200; an integration processing section 120 that performs integration processing for integrating values obtained from at least one coordinate axis component of the detected acceleration for a given period of time and obtains an integrated acceleration value I; and a speed index value arithmetic section 130 for obtaining a speed index value r used for estimating a speed in accordance with a relational expression of r=aI+bI+c, where coefficients (a) and (b) and constant (c) are given real numbers.

Description

    The present invention relates to a state detection device, an electronic device, a measurement system, a program, and the like.

  Devices that measure walking and running conditions and calculate movement distances and movement speeds from them are roughly divided into two approaches.

  First, as a first approach, there is a method in which distance information or speed information is acquired from the outside, separately from information on whether the user is walking or running, and the measurement of the walking and running situation is corrected. Typical examples of the first approach include a method using a positioning system such as GPS (Global Positioning System), a method using an IC tag (RFID: Radio Frequency IDentification), and the like.

  On the other hand, as a second approach, there is a method in which physical information associated with walking or running such as acceleration is obtained in more detail and the stride is corrected or the speed or distance is estimated regardless of the stride. Although there are various methods in the second approach, the second approach can be further classified into the following two approaches: A approach and B approach.

  First, the approach A will be described. Ideally, human walking or running can be approximated as a uniform motion. Actually, since there is a speed fluctuation cycle for each step, there is no acceleration at all, but from the viewpoint of center of gravity movement, the change in acceleration is not large. However, as you can see from the foot, while running, the foot is swung out in front of the center of gravity, placed on the ground, and kicked back further. As described above, since the acceleration motion, which is greatly different from the center of gravity, is cyclically repeated for the foot, it is possible to measure the stride and the like by measuring the foot motion. Although the hand is not as much as the foot, there is a cyclic acceleration motion due to the arm free motion. Therefore, in the approach of A, the stride and the like are accurately estimated by a measuring device attached to the limbs, and the measurement accuracy of speed and distance is improved.

  On the other hand, the approach of B tries to calculate the speed and distance by a measuring device attached to parts other than the limbs, for example, the chest and the waist. The chest and waist are close to the position of the center of gravity, and for the reasons described above, acceleration motion is not as clear as with feet and hands. There is enough vibration to detect each step, but the stride cannot be measured directly like a foot. For this reason, many measurement methods have been devised for improving accuracy, and a prior art as disclosed in Patent Document 1 is disclosed.

JP 2008-292294 A

  First, in the first approach, first, there is a problem that speed estimation cannot be performed in a place where there is no external infrastructure or where it cannot be used (in the case of GPS). Secondly, frequent wireless communication with the outside is required. Third, power consumption is large and the battery life becomes too short. Fourth, there is an error when running around a small place. There are problems such as being big.

  On the other hand, among the second approaches, the approach A does not have the first to fourth problems described above. However, for example, when using a foot pod type device worn on the foot, In addition to the chest display device, it is necessary to attach a sensor to the foot, which impairs convenience for the user.

  Further, in the above-described Patent Document 1 that adopts the approach B, the first to fourth problems described above are not present as in the approach A, but square root calculation is required in generating the acceleration composite vector, and the average value is further increased. There is a problem that the amount of calculation is large because division is required to obtain.

  Therefore, the present applicant proposes a technique for estimating the moving speed and moving distance of the user based on the approach B of the second approach, and having a smaller calculation amount.

  According to some aspects of the present invention, it is possible to provide a state detection device, an electronic device, a measurement system, a program, and the like that can perform an acceleration measurement and suppress a calculation amount while estimating a moving speed and the like. it can.

One embodiment of the present invention obtains an acceleration integrated value I by performing an accumulating process of accumulating a value obtained from at least one coordinate axis component of the detected acceleration for a given period, and an acquisition unit that acquires the detected acceleration from an acceleration sensor. An integration processing unit, and a speed index value calculation unit that obtains a speed index value r used for estimating the speed according to a relational expression of r = aI ² + bI + c (coefficients a, b, and constant c are given real numbers). It relates to the state detection device.

  In one aspect of the present invention, the speed index value is calculated from the detected acceleration by performing only multiplication and addition. Therefore, operations such as square root and division are unnecessary, and the amount of calculation can be suppressed.

  In one aspect of the present invention, when the first coordinate axis Y of the motion analysis coordinate system is a coordinate axis parallel to a vertical line, the integration processing unit performs the first coordinate axis of the detected acceleration as the integration process. A process for obtaining the acceleration integrated value I by acquiring a component and integrating at least values corresponding to the absolute value of the first coordinate axis component may be performed.

  Thereby, for example, even when coordinate axis components having different signs exist among coordinate axis components of a plurality of detected accelerations used for the same integration process, it is possible to correctly calculate the acceleration integration value.

In one aspect of the present invention, in the motion analysis coordinate system, when the first coordinate axis Y, the second coordinate axis X, and the third coordinate axis Z are orthogonal to each other, the integration processing unit is As the integration process, a first integrated value I _y is obtained based on the first coordinate axis component of the detected acceleration, a second integrated value I _x is obtained based on the second coordinate axis component of the detected acceleration, A third integrated value I _z is obtained based on the third coordinate axis component of the detected acceleration, and the first integrated value I _y , the second integrated value I _x, and the third integrated value I _z are obtained. You may perform the process which calculates | requires the said acceleration integrated value I by integrating | accumulating.

  As a result, for example, it is possible to perform an integration process using all three axes of the coordinate axis components of the detected acceleration to obtain an acceleration integrated value and improve speed estimation accuracy.

  In the aspect of the invention, the integration processing unit may calculate the nth power of the first coordinate axis component as a value corresponding to the absolute value of the first coordinate axis component of the detected acceleration in the motion analysis coordinate system ( n may be a positive even number), and a process of integrating the obtained nth power of the first coordinate axis component may be performed.

  Thus, when the nth power of the first coordinate axis component (n is a positive even number) is used as the value corresponding to the absolute value of the first coordinate axis component of the detected acceleration, the first coordinate axis component is obtained only by multiplication processing. It is possible to obtain a value corresponding to the absolute value of, and to reduce the amount of calculation.

  Moreover, in one aspect of the present invention, the apparatus includes a storage unit that stores the coefficients a and b and the constant c obtained from actual measurement values, and the speed index value calculation unit is the coefficient a acquired from the storage unit. , B and the constant c, the speed index value r may be obtained.

  This makes it possible to suppress variations in speed estimation accuracy between users, for example.

  Further, according to one aspect of the present invention, an exercise state determination unit that determines an exercise state of a user is included, and the speed index value calculation unit determines the coefficients a and b and the constant c to be used according to the exercise state. You may switch.

  Thereby, for example, it is possible to suppress variation in speed estimation accuracy for each motion state.

In one embodiment of the present invention includes a calibration processing unit for performing the calibration process based on the speed measurement, the speed index value calculation unit, the user of the moving speed of the reference when determining the estimated speed V _d a reference speed V _s and the coefficient a is a rate of, among b and the constant c, and at least one value may be changed based on the result of the calibration process.

As a result, for example, the state detection device of the present embodiment can determine the values of the coefficients a, b, the constant c, and the reference speed V _s regardless of the external device.

  Moreover, in one aspect of the present invention, a distance index value calculation unit that calculates a distance index value s based on the speed index value r determined by the speed index value calculation unit may be included.

  Thus, by performing only multiplication and addition, it is possible to obtain the user's moving distance as a distance index value. That is, operations such as square root and division are not required, so that the amount of calculation can be suppressed.

In one aspect of the present invention, a distance estimation value for obtaining a distance estimated value D _d by performing a multiplication process based on the distance index value s obtained by the distance index value calculation unit and a reference distance D _s. An arithmetic unit may be included.

Thereby, for example, it is possible to calculate the distance estimated value D _d that can be more easily understood based on the distance index value. That is, it becomes possible to present a value that is easier to understand for the user.

In the aspect of the present invention, the integration processing unit may calculate the acceleration integration value I _T1 obtained at each of the preceding speed estimation timings T1 to Ti (i is a positive integer of 2 or more) at the speed estimation timing M1. Acceleration integrated value I _M1 is obtained from the sum of ˜I _Ti , and at the next speed estimation timing M2 after the speed estimation timing M1, the acceleration integration value I _T2 obtained at each of the preceding speed estimation timings _{T2 to T} (i + 1) is obtained. Acceleration integrated value I _M2 may be obtained from the sum of ˜IT _{(i + 1)} .

  This makes it possible to give hysteresis characteristics to the speed index value.

In one embodiment of the present invention, the said speed index value r determined by the speed index value calculation section, based on the reference velocity V _s, performs multiplication processing, velocity estimates to obtain the estimated speed V _d An arithmetic unit may be included.

Thereby, for example, based on the speed index value, it is possible to calculate a speed estimated value V _d that can be more easily understood.

  Another aspect of the present invention is an electronic apparatus including the state detection device and the acceleration sensor.

  Moreover, the other aspect of this invention is related with the measurement system containing the said state detection apparatus.

  Accordingly, for example, it is possible to cause the server to execute a part of processing performed by the state detection device, and it is possible to reduce the processing amount of the state detection device.

  Moreover, the other aspect of this invention is related with the program which functions a computer as said each part.

FIG. 1A and FIG. 1B are system configuration examples of this embodiment. Explanatory drawing of the outline | summary of a speed estimation process. Explanatory drawing of a reference speed, a speed index value, and a speed estimated value. The graph showing the relationship between an acceleration integrated value and a speed estimated value. Explanatory drawing of a three-axis motion analysis coordinate system. The relationship figure of the number of axes and a correlation coefficient. Explanatory drawing of a calibration process. Explanatory drawing of a moving average process. FIG. 9A and FIG. 9B are mounting examples of this embodiment. The flowchart explaining the flow of a process of this embodiment.

  Hereinafter, this embodiment will be described. First, an outline of the present embodiment will be described, and then a system configuration example of the present embodiment will be described. Then, the method of the present embodiment will be described in detail with specific examples, and finally, the flow of processing of the present embodiment will be described using a flowchart. In addition, this embodiment demonstrated below does not unduly limit the content of this invention described in the claim. In addition, all the configurations described in the present embodiment are not necessarily essential configuration requirements of the invention.

1. Outline As shown in equation (1), the approximate distance d is obtained by multiplying the step length p by the step length p, which is a relationship between human walking and running and distance known since BC.

  For example, since one step is 60cm and ten steps, the measurement method of about 6m is still widely used today, and ancient Chinese literature used to measure the area of the land with "steps". Also appears.

  If it can be measured that it took time t to move the distance d, the traveling speed v can be obtained as shown in Equation (2).

  However, it is also true that the measurement method as described above involves a large error. This is mainly due to the fact that the human stride p is not always constant.

Considering that there are many cases where the left and right steps are different, the sum of the _left foot stride p _left and the right foot stride p _right is defined as one cycle width w as shown in Equation (3), and the distance or the like is determined based on w. The calculation is more accurate.

  For this reason, in a device that measures walking and running conditions and calculates the distance and speed from there, two approaches have been taken.

  First, as a first approach, there is a method in which distance information or speed information is acquired from the outside, separately from information on whether the user is walking or running, and the measurement of the walking and running situation is corrected. Typical examples of the first approach include a method using a positioning system such as GPS (Global Positioning System), a method using an IC tag (RFID: Radio Frequency IDentification), and the like.

  On the other hand, as a second approach, there is a method in which physical information associated with walking or running such as acceleration is obtained in more detail and the stride is corrected or the speed or distance is estimated regardless of the stride. Although there are various methods in the second approach, the second approach can be further classified into the following two approaches: A approach and B approach.

  First, the approach A will be described. Ideally, human walking or running can be approximated as a uniform motion. Actually, since there is a speed fluctuation cycle for each step, there is no acceleration at all, but from the viewpoint of center of gravity movement, the change in acceleration is not large. However, as you can see from the foot, while running, the foot is swung out in front of the center of gravity, placed on the ground, and kicked back further. As described above, since the acceleration motion, which is greatly different from the center of gravity, is cyclically repeated for the foot, it is possible to measure the stride and the like by measuring the foot motion. Although the hand is not as much as the foot, there is a cyclic acceleration motion due to the arm free motion. Therefore, in the approach of A, the stride and the like are accurately estimated by a measuring device attached to the limbs, and the measurement accuracy of speed and distance is improved.

  On the other hand, the approach of B tries to calculate the speed and distance by a measuring device attached to parts other than the limbs, for example, the chest and the waist. The chest and waist are close to the position of the center of gravity, and for the reasons described above, acceleration motion is not as clear as with feet and hands. There is enough vibration to detect each step, but the stride cannot be measured directly like a foot. For this reason, many measurement methods have been devised for improving accuracy, and a prior art as disclosed in Patent Document 1 described above is disclosed.

  Next, problems of each approach will be described. First, in the first approach, first, there is a problem that speed estimation cannot be performed in a place where there is no external infrastructure or where it cannot be used (in the case of GPS). Secondly, frequent wireless communication with the outside is required. Third, power consumption is large and the battery life becomes too short. Fourth, there is an error when running around a small place. There are problems such as being big.

  On the other hand, among the second approaches, the approach A does not have the first to fourth problems described above. However, for example, when using a foot pod type device worn on the foot, In addition to the chest display device, it is necessary to attach a sensor to the foot, which impairs convenience for the user.

  Further, in the above-described Patent Document 1 that adopts the approach B, the first to fourth problems described above are not present as in the approach A, but square root calculation is required in generating the acceleration composite vector, and the average value is further increased. There is a problem that the amount of calculation is large because division is required to obtain.

  Therefore, the present applicant proposes a technique for estimating the moving speed and moving distance of the user based on the approach B of the second approach, and having a smaller calculation amount. That is, the state detection apparatus of the present embodiment can perform acceleration measurement by attaching it to a part other than the user's hand or foot, and can estimate the moving speed or the like while suppressing the calculation amount.

  As described above, various methods have been devised in the past for measuring acceleration by measuring acceleration. In the case of the present embodiment, first, in the range from 1 axis to 3 axes, an acceleration sensor is used. There is a feature not found in other prior art that the number of measurable axes is not questioned. However, the accuracy increases as the number of axes increases.

  Second, there is a feature that an index indicating speed can be calculated from acceleration by performing only multiplication and addition. That is, calculations such as square root and division are not required, so that the amount of calculation can be suppressed.

  Third, there is a feature that it is possible to estimate the moving speed and the like independently of the number of steps, the step length, the walking pitch, and the like. Furthermore, it is also possible to use the measured number of steps, step length, walking pitch, etc., for correcting the speed estimation result.

2. System Configuration Example FIG. 1A shows an example where a user 10 wears an electronic device 900 including the state detection device of the present embodiment on the chest. In the present embodiment, the electronic device 900 is attached to the chest, but may be attached to a position other than the chest as long as it is a part other than the hand or foot.

  Next, FIG. 1B shows a detailed configuration example of the state detection apparatus 100 of the present embodiment and the electronic apparatus 900 (or measurement system) including the same.

  The state detection apparatus 100 includes an acquisition unit 110, an integration processing unit 120, a speed index value calculation unit 130, a speed estimation value calculation unit 140, a storage unit 150, an exercise state determination unit 160, and a distance index value calculation unit. 170, a distance estimated value calculation unit 180, and a calibration processing unit 190. Examples of the electronic device 900 including the state detection device 100 include an acceleration sensor 200, a pedometer including an antenna unit 300 and a wireless communication unit 400 illustrated in FIG. Note that the state detection apparatus 100 and the electronic device 900 including the state detection apparatus 100 are not limited to the configuration in FIG. 1B, and some of these components may be omitted or other components may be added. Various modifications are possible. In addition, some or all of the functions of the state detection apparatus 100 according to the present embodiment may be realized by a server connected to the antenna unit 300 and the wireless communication unit 400 by communication.

  Next, processing performed in each unit will be described.

  The acquisition unit 110 acquires detected acceleration from the acceleration sensor 200. The acquisition unit 110 is an interface unit that communicates with the acceleration sensor 200, and uses a bus or the like.

  The integration processing unit 120 performs an integration process to be described later based on the detected acceleration, and obtains an acceleration integrated value.

  The speed index value calculation unit 130 obtains a speed index value used for estimating the speed based on the acceleration integrated value.

  The speed estimated value calculation unit 140 performs a multiplication process based on the speed index value and the reference speed to obtain a speed estimated value.

  The storage unit 150 stores information such as coefficients used when the speed index value is obtained and serves as a work area for each unit. The function of the storage unit 150 can be realized by a memory such as a RAM or an HDD (hard disk drive).

  The exercise state determination unit 160 determines the user's exercise state.

  The distance index value calculation unit 170 obtains a distance index value based on the speed index value.

  The distance estimated value calculation unit 180 performs multiplication processing based on the distance index value and the reference distance to obtain a distance estimated value.

  The calibration processing unit 190 performs a later-described calibration process based on the actually measured speed value.

  The integration processing unit 120, the speed index value calculation unit 130, the speed estimation value calculation unit 140, the exercise state determination unit 160, the distance index value calculation unit 170, the distance estimation value calculation unit 180, and the calibration process The unit 190 can be realized by hardware such as various processors (CPU or the like), ASIC (gate array or the like), a program, or the like.

  The acceleration sensor 200 is composed of, for example, an element whose resistance value is increased or decreased by an external force, and detects triaxial acceleration information. However, the number of axes of the acceleration sensor 200 in the present embodiment is not limited to three axes.

3. Method of this Embodiment First, data obtained in the state detection process of this embodiment are shown in FIG. 2 in order. In this embodiment, first, the detected acceleration is acquired from the acceleration sensor 200 (S101). Next, an acceleration integrated value described later is calculated based on the acquired detected acceleration (S102), and a speed index value described later is calculated based on the calculated acceleration integrated value (S103). Based on the calculated speed index value, a speed estimated value to be described later is calculated (S104). Roughly speaking, in the present embodiment, the moving speed (or moving distance) of the user, which is the object of the present embodiment, is obtained through such an intermediate value. The value finally obtained as the user's moving speed (movement distance) may be a speed index value (distance index value) or a speed estimation value (distance estimation value). The reason will be described later. Hereinafter, the method of this embodiment will be described in detail.

The state detection apparatus 100 according to the present embodiment performs an accumulation process for accumulating a value obtained from at least one coordinate axis component of the detected acceleration for a given period, and an acquisition unit 110 that acquires the detected acceleration from the acceleration sensor 200. An integration processing unit 120 for obtaining a value I, and a speed index value calculation for obtaining a speed index value r used for estimating a speed according to a relational expression of r = aI ² + bI + c (coefficients a, b, and constant c are given real numbers). Part 130.

  Here, the detected acceleration refers to an acceleration detected by the acceleration sensor 200. For example, when the acceleration sensor 200 detects accelerations with respect to three axes of the X axis, the Y axis, and the Z axis, the detected acceleration is represented by a vector A as shown in Expression (4). In Expression (4), x represents an X-axis component, y represents a Y-axis component, and z represents a Z-axis component. However, the detected acceleration is not necessarily a vector having three-axis acceleration as a component, and may be expressed in a mathematically equivalent form.

  Further, the integration process in the present embodiment is a process of integrating a value obtained from at least one coordinate axis component of the detected acceleration for a given period. Specifically, for example, the X-axis component which is at least one coordinate axis component of the detected acceleration is added three times detected continuously.

In this way, the value obtained as a result of the integration process is referred to as an acceleration integrated value. Specifically, the acceleration integrated value I in this example is as shown in Equation (5). In the formula (5), X-axis component of the detected acceleration in the timing of x ₁ is, x ₂ is an X-axis component of the acceleration detected by the next timing of x _1, x ₃ is the acceleration detected by the next timing of x ₂ X Refers to the axial component.

  In this example, a period in which acceleration is detected three times in succession is set as a given period. However, the given period is not limited to this, and may be set arbitrarily. Ideally, a given period is a time that can include two cycles, with one step on the left and right as one cycle. In order to determine this time, the traveling pitch may be measured to obtain the time, but for simplification of processing, a time width that is considered to always include two cycles in normal traveling such as 4 seconds or 8 seconds. May be set as a given period.

  In addition, although an example in which the integration process is performed for only one coordinate axis component has been described here, the present invention is not limited to this. An example of performing integration processing for all three-axis acceleration components will be described later.

  Then, the calculated acceleration integrated value I is substituted into equation (6) to obtain the speed index value r. In equation (6), the coefficients a and b and the constant c are given real numbers. The processing for obtaining the speed index value r according to the equation (6) can be modified as long as it is mathematically equivalent to this processing.

  Here, the speed index value is a value representing the moving speed of the user. That is, the speed index value is a concept including a speed estimation value described later. Therefore, specification of the user's moving speed, which is one of the objects of the present embodiment, is achieved at the stage of obtaining the speed index value.

Further, the speed index value does not necessarily have to be a value represented by the international unit system. As an example in which the speed index value is a value expressed by a unit other than the international unit system, for example, a ratio (magnification) of a reference speed and a user's moving speed as shown in FIG. 3, the vertical axis as the velocity is a graph comparing the velocity _{V s} (reference speed) of the speed _{V 1} and Sample 2 (SP2) based on the velocity _{V 2} of the (DS) of the sample 1 (SP1). Speed index values r ₁ and r ₂ , which are ratios (magnifications) between the reference speed and the user's moving speed, are obtained as r in Expression (6). In the following description of the embodiments, the speed index value is treated as a ratio (magnification) between the reference speed and the moving speed of the user.

  Thereby, it becomes possible to obtain | require a user's moving speed as a speed index value. Further, it is possible to calculate the speed index value from the detected acceleration by performing only multiplication and addition. That is, calculations such as square root and division are not required, so that the amount of calculation can be suppressed.

  As described above, the state detection apparatus 100 according to the present embodiment can perform acceleration measurement by attaching to a part other than the user's hand or foot, and can estimate the moving speed or the like while suppressing the calculation amount.

Speed The state detecting device 100 of this embodiment, the speed index value r determined by the speed index value calculation section 130, based on the reference velocity V _s, performs multiplication processing, for obtaining the estimated speed V _d An estimated value calculation unit 140 may be included.

That is, in the example of FIG. 3 described above, according to equation (7) and (8) to calculate the sample 1 (SP1) velocity estimate _{V 1} of the and the sample 2 velocity estimates _{V 2} of (SP2).

Here, the reference speed V _s refers to a speed that serves as a reference for the moving speed of the user, and is a value that is in one-to-one correspondence with the combination of the coefficients a and b and the constant c in Expression (6). As the reference speed V _s , for example, an average value of the walking speed of a human calculated statistically may be used. However, the reference speed V _s is not limited thereto and may be set to any value. Incidentally, in this case, in conformity to change the reference speed V _s, combinations of coefficients a, b and the constant c in equation (6), should be changed to a value corresponding to the reference velocity V _s of the modified There is. This is because, coefficients a, unless the combination of b and a constant c correspond to the reference velocity V _s, also the speed index value r obtained from the combination and the acceleration cumulative value I such as these coefficients, the reference speed V _s and the speed estimated value This is because the V _d ratio (magnification) is not correctly represented. Thus, for example, when the reference velocity V _s is set to a much larger value than the moving speed of the user, it is necessary to reset the coefficients a, b and the constant c in the pre-change smaller value.

Here, the speed estimation value _Vd is a speed index value in a narrow sense and refers to a value estimated as the moving speed of the user. It is desirable that the estimated speed value V _d be expressed mainly in the international unit system, since a value that can be easily understood at a glance is suitable. However, it is not limited to this. In the example of FIG. 3 described above, V ₁ and V ₂ are the speed estimation value V _d .

Thereby, for example, based on the speed index value, it is possible to calculate a speed estimated value V _d that can be more easily understood. That is, it becomes possible to present a value that is easier to understand for the user.

  When the speed estimated value is obtained as described above, the relationship between the acceleration integrated value and the speed estimated value is, for example, as shown in FIG. FIG. 4 is a graph in which the horizontal axis is an acceleration integrated value and the vertical axis is a speed estimation value (m / s), and a square point such as P1 represents an actual estimation result. Referring to the result of FIG. 4, it can be seen that the acceleration integrated value and the speed estimated value are represented by a curve S1 as shown in the figure. The points distributed in the range of W1 in the graph are points estimated when the user is walking, and the points distributed in the range of R1 are points estimated when the user is running. It is.

In addition, the coordinate axis component of the detected acceleration is not always a positive value. If the coordinate axis component of the detected acceleration changes from positive to negative, the above-described integration process may not be performed correctly. Specifically, for example, when processing for accumulating the amount of acceleration detected twice is performed, an acceleration of 1 (m / s ² ) north is detected at the first time, and 1 (m / s ² ) at the second time. ^When the acceleration of ² ) is detected, although it has actually moved, the acceleration integrated value becomes 0 (m / s ² ), and correct speed estimation cannot be performed.

  Therefore, when the first coordinate axis Y of the motion analysis coordinate system is a coordinate axis parallel to the vertical line, the integration processing unit 120 acquires the first coordinate axis component of the detected acceleration as the integration processing, and at least the first Processing for obtaining the acceleration integrated value I may be performed by integrating values corresponding to the absolute value of the coordinate axis component.

  Here, as the value corresponding to the absolute value of the first coordinate axis component, the absolute value itself of the first coordinate axis component may be used.

  In addition, the integration processing unit 120 obtains the nth power of the first coordinate axis component (n is a positive even number) as a value corresponding to the absolute value of the first coordinate axis component of the detected acceleration in the motion analysis coordinate system. Processing for integrating the nth power of the first coordinate axis component may be performed.

  In this case, the acceleration integrated value I is obtained by, for example, equation (9). In Expression (9), i represents a sample number, j represents a sample start number, m represents a sampling number, and i, j, and m are positive integers.

  As a premise, here, it is assumed that the acceleration sensor coordinate system and the motion analysis coordinate system coincide with each other, and the first coordinate axis Y of the motion analysis coordinate system is a coordinate axis parallel to the vertical line. The motion analysis coordinate system refers to a coordinate system used as a reference when performing speed estimation processing or the like. The motion analysis coordinate system may be a local coordinate system or a world coordinate system (global coordinate system). The acceleration sensor coordinate system refers to a local coordinate system (body coordinate system) used as a reference when the acceleration sensor 200 detects acceleration. Therefore, the detected acceleration is an acceleration (vector) expressed in the acceleration sensor coordinate system. Therefore, when the acceleration sensor coordinate system and the motion analysis coordinate system do not match, it is necessary to perform coordinate conversion processing of the detected acceleration. The method of coordinate conversion processing is arbitrary, and a known method may be used.

  Thereby, for example, even when coordinate axis components having different signs exist among coordinate axis components of a plurality of detected accelerations used for the same integration process, the acceleration integration value can be calculated correctly without canceling out in the integration process. It becomes possible.

  Further, when the nth power of the first coordinate axis component (n is a positive even number) is used as a value corresponding to the absolute value of the first coordinate axis component of the detected acceleration, the first coordinate axis component is obtained only by multiplication processing. It is possible to obtain a value corresponding to the absolute value, and it is possible to suppress the calculation amount.

  So far, an example in which uniaxial coordinate axis components are integrated has been described, but in this embodiment, the acceleration integrated value may be obtained by integrating not only one axis but three axis coordinate axis components.

That is, in the motion analysis coordinate system, when the first coordinate axis Y, the second coordinate axis X, and the third coordinate axis Z are orthogonal to each other, the integration processing unit 120 performs first detection acceleration as the integration processing. The first integrated value I _y is obtained based on the coordinate axis component of the first acceleration, the second integrated value I _x is obtained based on the second coordinate axis component of the detected acceleration, and the third integrated value is obtained based on the third coordinate axis component of the detected acceleration. seeking I _z, it may be subjected to a treatment for obtaining the acceleration cumulative value I by integrating the first integrated value I _y and the second integrated value I _x and a third integrated value I _z.

  Here, the second coordinate axis component of the detected acceleration refers to an acceleration component of one coordinate axis of two coordinate axes representing a horizontal plane, for example. The third coordinate axis component of the detected acceleration refers to an acceleration component of the other coordinate axis different from the second coordinate axis, for example, out of two coordinate axes representing a horizontal plane. More specifically, when the Y-axis direction coincides with the vertical direction G as shown in FIG. 5, for example, the X-axis component is the second coordinate axis component and the Z-axis component is the third coordinate axis component. .

Further, the acceleration integrated value I is, for example, from equation (10), the first integrated value I _y is from equation (11), the second integrated value I _x is from equation (12), and the third integrated value I _z is It is obtained by equation (13). In Expressions (10) to (13), i represents a sample number, j represents a sample start number, m represents a sampling number, and i, j, m, and n are positive integers.

As a modification, any one or all of the first integrated value I _y , the second integrated value I _x , and the third integrated value I _z are multiplied by an arbitrary coefficient, or the acceleration integrated value I is calculated. At this time, any constant term may be integrated. Further, an acceleration integrated value may be obtained by performing a mathematically equivalent operation.

  A more specific example will be described with reference to FIG. First, in FIG. 5, it is assumed that the acceleration represented by SP1 is detected after the acceleration represented by SP1 is detected. At this time, when the integration processing of the two detected accelerations is performed, the acceleration integrated value becomes as shown in Expression (14). In equation (14), n = 2.

  Here, the relationship between the number of detected acceleration axes (horizontal axis) used in the integration process and the correlation coefficient (vertical axis) is shown in the graph of FIG. The correlation coefficient represents a correlation value between the estimated speed value estimated in the present embodiment and the actual moving speed of the user. The larger the correlation coefficient, the more the estimated speed value and the actual moving speed of the user are. It shows that it is approximate. Further, series A represents data about subject A, series B represents data about subject B, and series C represents data about subject C. As shown in FIG. 6, in all the series data, it can be confirmed that the correlation coefficient increases as the number of axes increases from one axis to three axes. That is, it can be seen that the speed estimation accuracy is improved by increasing the number of axes.

  As a result, for example, it is possible to perform an integration process using all three axes of the coordinate axis components of the detected acceleration to obtain an acceleration integrated value and improve speed estimation accuracy.

  The coefficients a and b and the constant c are preferably set to different values depending on the number of axes to be used and a predetermined period for performing the integration process.

  Furthermore, it is desirable to set values suitable for each user to be used for the coefficients a and b and the constant c described above. This is because the way of walking and running differ depending on the user, and even if the acceleration integrated value is the same, the actual moving speed is not always the same.

  Therefore, the state detection apparatus 100 of the present embodiment may include a storage unit 150 that stores the coefficients a and b and the constant c obtained from the actual measurement values. Then, the speed index value calculation unit 130 may obtain the speed index value r based on the coefficients a and b and the constant c acquired from the storage unit 150.

  Here, the actual measurement value indicates, for example, the actual moving speed of the user.

  As a result, it is possible to store the appropriate coefficients a, b and constant c specified based on the actually measured values and use the stored coefficients a, b and constant c when obtaining the speed index value. Become. Therefore, it is possible to suppress variations in speed estimation accuracy among users.

  In addition, it is desirable that the coefficients a and b and the constant c described above are set to values suitable for the current user exercise state. This is because the actual moving speed is not always the same when the user is walking and when the user is running, even if the integrated acceleration value is the same.

  Therefore, the state detection device 100 of the present embodiment may include an exercise state determination unit 160 that determines the user's exercise state. Then, the speed index value calculation unit 130 may switch the coefficients a and b and the constant c to be used according to the exercise state.

  Here, the exercise state means, for example, a state in which the user is walking, running, or stopped. Further, more detailed information may be considered as the exercise state. More detailed information is information such as the moving speed, moving distance, and moving time of the user.

  At this time, the exercise state may be determined by comparing the previously estimated speed estimated value with a predetermined threshold. For example, when the estimated speed value is larger than a predetermined threshold for a certain period, it is determined that the exercise state is a running state. However, the determination method of the exercise state is not limited to this.

  This makes it possible to use appropriate coefficients a and b and a constant c specified according to the motion state when determining the speed index value. Accordingly, it is possible to suppress variations in speed estimation accuracy for each motion state.

  Note that different values for the coefficients a and b and the constant c are not necessarily used for each user and each exercise state, and may be used in all cases.

  Up to this point, the example in which the values of the coefficients a, b and the constant c are specified in the external device has been described. However, the state detection apparatus 100 according to the present embodiment determines the values of the coefficients a, b, the constant c, and the like. Also good.

That is, the state detection apparatus 100 according to the present embodiment may include a calibration processing unit 190 that performs a calibration process based on the actually measured speed value. Then, the speed index value calculation unit 130 obtains at least one value of the reference speed V _s , which is a reference speed of the user's moving speed when obtaining the speed estimated value V _d , the coefficients a, b, and the constant c. The change may be made based on the result of the calibration process.

  Here, the actually measured speed value is one of the above-described actually measured values, and means a value obtained by measuring the actual moving speed of the user with an external device or the like.

However, in practice, it may be difficult to directly acquire (measure) the actual speed measurement value. Therefore, the state detecting device 100 of this embodiment also includes a result of the predetermined distance the user walks or running, the calibration processing unit 190 for performing a carry boot Deployment process based on the distance estimate D _d to be described later good. In this case, the user's moving speed is estimated based on a result of the user walking or running a predetermined distance and a distance estimation value D _d described later, and the estimated moving speed is used as a measured speed value. Calibration processing may be performed. That is, the actually measured speed value may be a value estimated from a distance actually moved by the user.

The calibration process refers to, for example, a process of adjusting values such as the coefficients a and b, the constant c, and the reference speed V _s to appropriate values.

A specific example will be described with reference to FIG. FIG. 7 is a graph in which the vertical axis represents the movement speed (m / s) and the horizontal axis represents the integrated acceleration value, and when the initial values (default values) of the coefficients a and b, the constant c, and the reference speed V _s are used. The relationship between the acceleration integrated value and the moving speed is shown. Here, the actual moving speed of the user is shown as a curve UD. Further, it shows a velocity estimate V _d obtained by multiplying the reference speed V _s and the speed index value r before performing the calibration process as a curve AD.

At this time, when for example the acceleration cumulative value is I _k is the speed measurement and the speed estimated value V ₁ together, although consistent, when the acceleration cumulative value is I _m, the velocity estimate V ₂ , speed measurement is V _3, speed measurement and the speed estimated value does not match. Therefore, it is necessary acceleration cumulative value makes the calibration process so that the speed actual value and speed estimation value matches even when a I _m.

Therefore, the calibration processing of this embodiment, a case acceleration cumulative value is I _k, the two points when it is I _m, and obtains the speed measurement, which is compared with a reference velocity V _s, the formula ( 15) and the speed index values (r _k and r _m ) expressed in the equation (16) are _obtained .

Then, in the equation (6), when the acceleration cumulative value is I _k, the speed index value r _k, and the when the acceleration cumulative value is I _m, as the speed index value is r _m, coefficient a, b, and constant c are adjusted. In some cases, adjusting the reference velocity V _s. In this example, the time acceleration cumulative value is I _k, the two points when it is I _m, processing was carried out to determine the speed index value, but is not limited to the present embodiment.

Here, the result of the calibration process is, for example, the speed index value r (r _k and r _m ) in the above-described example, or the coefficients a and b, the constant c, and the like obtained based on the speed index value r. or even in that either or information indicating all changes of the reference velocity V _s. However, it is not limited to these.

As a result, for example, the state detection apparatus 100 according to the present embodiment can determine the values of the coefficients a, b, the constant c, and the reference speed V _s regardless of an external device. Therefore, when the user uses the apparatus, it is possible to save the trouble of preparing other devices and performing the calibration process, thereby improving convenience.

  Further, the state detection apparatus 100 of the present embodiment may include a distance index value calculation unit 170 that calculates the distance index value s based on the speed index value r calculated by the speed index value calculation unit 130.

  Here, the distance index value and the distance estimated value have the same relationship as the speed index value and the speed estimated value described above. For this reason, the description relating to speed in the above description may be replaced with distance, and thus detailed description thereof is omitted.

  When obtaining the distance index value based on the speed index value, the speed index value may be simply multiplied by the travel time.

  This makes it possible to obtain the user's moving distance as a distance index value. Further, it is possible to calculate a speed index value from the detected acceleration by performing only multiplication and addition. That is, operations such as square root and division are not required, so that the amount of calculation can be suppressed.

In addition, the state detection apparatus 100 according to the present embodiment performs a multiplication process based on the distance index value s obtained by the distance index value calculation unit 170 and the reference distance D _s , and obtains the distance estimated value D _d. An estimated value calculation unit 180 may be included.

Specifically, the distance estimated value _Dd is obtained according to the equation (17). However, by performing mathematically equivalent thereto operations, it may be determined distance estimate D _d. Since the reference distance is a concept similar to the reference speed, detailed description thereof is omitted.

Thereby, for example, it is possible to calculate the distance estimated value D _d that can be more easily understood based on the distance index value. That is, it becomes possible to present a value that is easier to understand for the user.

  Here, the acceleration may change greatly due to, for example, the user shaking left and right during movement. It is desirable to minimize the change in the movement speed due to such factors. For this reason, in this embodiment, a moving average value of acceleration integrated values used when calculating the speed index value is obtained, and a hysteresis characteristic is given to the speed index value.

That is, at the speed estimation timing M1, the integration processing unit 120 determines the acceleration from the sum of the acceleration integration values I _T1 to ITi obtained at each of the preceding speed estimation timings _{T1 to Ti} (i is a positive integer of 2 or more). The integrated value I _M1 is obtained, and at the speed estimation timing M2 next to the speed estimation timing M1, the sum of the acceleration integrated values I _T2 to IT (i + 1) obtained at each of the preceding speed estimation timings _{T2 to T (i + 1)} . From the above, the acceleration integrated value I _M2 may be obtained.

  Here, the speed estimation timing refers to timing for performing speed estimation processing. The speed estimation timing may come at the same cycle as the timing (sampling timing) at which the detected acceleration is acquired, or may come at a cycle different from the sampling timing.

  Here, FIG. 8 shows a specific example when i = 4. In the example of FIG. 8, for simplification of description, it is assumed that the speed estimation timing (M1 and M2) and the sampling timing are the same timing and come in the same cycle. At this time, the integrated acceleration value obtained at the speed estimation timing M1 is as shown in Expression (18), and the integrated acceleration value obtained at the speed estimation timing M1 is as shown in Expression (19).

  Further, in Expression (18) and Expression (19), division by i = 4 is performed, but the values of the coefficients a and b and the constant c may be adjusted without actually performing division. Even if the division is not performed, it is possible to give a hysteresis characteristic to the speed index value, thereby reducing unnecessary calculations.

  This makes it possible to give hysteresis characteristics to the speed index value. Therefore, for example, it is possible to suppress a change in the movement speed due to factors such as the user shaking left and right during movement.

  Next, a method for mounting the state detection device 100 of the present embodiment on the electronic device 900 (component arrangement method) will be described with reference to FIGS. 9A and 9B. 9A shows the front surface of the first electronic substrate 700 included in the electronic device 900, and FIG. 9B shows the back surface of the first electronic substrate 700. FIG. 9A and 9B, the frame representing the first electronic board 700 is drawn away from the frame representing the electronic device 900 in order to avoid confusion in the illustration. Are in agreement. The same applies to a second electronic substrate 800 described later.

  First, the electronic device 900 of the present embodiment may include the state detection device 100 and the acceleration sensor 200.

  In addition, the electronic apparatus 900 according to the present embodiment includes a state detection device 100, an acceleration sensor 200, a wireless communication unit 400, an antenna unit 300, a battery 500 (battery) that operates the state detection device 100 and the wireless communication unit 400. Socket).

  For example, the electronic device 900 is a pedometer or the like. Note that reference numeral 600 in FIG. 9B denotes a heartbeat measurement electrode terminal, which is mounted as necessary. In the present embodiment, the heart rate measurement electrode terminal 600 may not be provided.

  Here, the wireless communication unit 400 performs control related to communication between the state detection device 100 and the antenna unit 300. The wireless communication unit 400 can be realized by hardware such as various processors (CPU and the like), ASIC (gate array and the like), a program, and the like.

  The antenna unit 300 is a device that radiates (transmits) high-frequency energy as radio waves (electromagnetic waves) into space, or conversely converts (receives) radio waves (electromagnetic waves) in space into high-frequency energy. Note that the antenna unit 300 of the present embodiment has at least a transmission function. Furthermore, one or a plurality of antenna units 300 are provided for the electronic device 900. For example, when a plurality of antenna units 300 are provided, the apertures of the antennas may be different.

  However, when the acceleration sensor 200 and the antenna unit 300 are mounted on the same substrate, an error may occur in the detection result of the acceleration sensor 200 due to the influence of radio waves (electromagnetic waves) emitted from the antenna unit 300. For this reason, conventionally, the acceleration sensor 200 and the antenna unit 300 are installed separately on different substrates so that no error occurs in the detection result of the acceleration sensor 200. However, in this case, the electronic device 900 becomes large due to the thickness of each substrate, and if this is attached to the chest or the like during exercise, there is a problem that the exercise is hindered.

  Therefore, in the present embodiment, as shown in FIGS. 9A and 9B, the state detection device 100, the acceleration sensor 200, the wireless communication unit 400, and the battery 500 are mounted on the first electronic substrate 700. The antenna unit 300 may be mounted on the first direction DR1 side of the wireless communication unit 400, and the acceleration sensor 200 may be mounted on the second direction DR2 side of the wireless communication unit 400.

  Here, the second direction DR2 is a direction different from the first direction DR1, and is substantially opposite to the first direction DR1, for example, as shown in FIG. 9A.

  As a result, it is possible to mount the acceleration sensor 200 and the antenna unit 300 apart from each other, and it is possible to make an error caused by the radio wave emitted by the antenna unit 300 less likely to occur in the detection result of the acceleration sensor 200. Become.

  Furthermore, the electronic device 900 can be made more compact by mounting the state detection device 100, the acceleration sensor 200, the wireless communication unit 400, the antenna unit 300, and the battery 500 on a single substrate. It becomes. Thereby, even if the electronic device 900 is worn on the chest or the like during exercise, it is possible to prevent the exercise from being hindered.

  In the electronic device 900, the antenna unit 300 may be mounted on the second electronic substrate 800 attached to the first direction side of the wireless communication unit 400.

  Note that it is desirable to exclude the substrate pattern on the back surface of the second electronic substrate 800. In addition, the second electronic substrate 800 is desirably disposed so as to overlap the end of the first electronic substrate 700 as illustrated in FIGS. 9A and 9B. However, the present invention is not limited to this. For example, the second electronic substrate 800 may be partially overlapped with the first electronic substrate 700.

  As a result, it is possible to mount the acceleration sensor 200 and the antenna unit 300 further apart from each other, and the detection result of the acceleration sensor 200 is less likely to cause an error caused by the radio wave emitted by the antenna unit 300. It becomes possible.

  In the electronic device 900, the state detection device 100, the acceleration sensor 200, and the wireless communication unit 400 are mounted on the front surface of the first electronic substrate 700, and the battery 500 is mounted on the back surface of the first electronic substrate 700. Also good.

  Thereby, the electronic device 900 can be further thinned.

  In addition, the measurement system of the present embodiment may include the state detection device 100.

  For example, an example of such a measurement system is a measurement system including the above-described electronic device, and a part or all of the state detection device 100 is connected to the antenna unit 300 and the wireless communication unit 400 by communication. And a measurement system that realizes this function.

  Accordingly, for example, it is possible to cause the server to execute a part of processing performed by the state detection device 100, and it is possible to reduce the processing amount of the state detection device 100.

  Note that the state detection apparatus 100 and the like of the present embodiment may realize part or most of the processing by a program. In this case, a processor such as a CPU executes the program, thereby realizing the state detection device 100 according to the present embodiment. Specifically, a program stored in the information storage medium is read, and a processor such as a CPU executes the read program. Here, the information storage medium (computer-readable medium) stores programs, data, and the like, and functions as an optical disk (DVD, CD, etc.), HDD (hard disk drive), or memory (card type). It can be realized by memory, ROM, etc. A processor such as a CPU performs various processes according to the present embodiment based on a program (data) stored in the information storage medium. That is, in the information storage medium, a program for causing a computer (an apparatus including an operation unit, a processing unit, a storage unit, and an output unit) to function as each unit of the present embodiment (a program for causing the computer to execute processing of each unit) Is memorized.

4). Processing Flow Hereinafter, the processing flow of this embodiment will be described with reference to the flowchart of FIG.

  First, the detected acceleration is acquired from the acceleration sensor (S201). At this time, the detected acceleration acquired from the acceleration sensor is represented by a value in the acceleration sensor coordinate system. Therefore, coordinate conversion processing of detected acceleration is performed from the acceleration sensor coordinate system to the motion analysis coordinate system (S202).

  Next, an integration process is performed for each coordinate axis component of the detected acceleration after the coordinate conversion process (S203), and a total sum of the integrated values of each coordinate axis is calculated (S204). That is, the processing of the above-described formula (10) is performed.

Here, based on the detected acceleration, a determination processing of the user's motion state (S205), carried out on the basis of the result of the determination process in motion state, the coefficients a, b, a switching process of the constant c and the reference speed V _s (S206).

  Then, as shown in Expression (6), a speed index value is calculated based on the sum of the integrated values of the respective coordinate axes, the coefficients a and b, and the constant c (S207), and the speed index value is expressed as in Expression (7). And the reference speed are multiplied to calculate a speed estimated value (S208).

  Finally, the estimated distance value is calculated by multiplying the estimated speed value by the travel time (S209) and output to the display unit, the wireless communication unit, etc. (S210).

  Although the present embodiment has been described in detail as described above, it will be easily understood by those skilled in the art that many modifications can be made without departing from the novel matters and effects of the present invention. Accordingly, all such modifications are intended to be included in the scope of the present invention. For example, a term described at least once together with a different term having a broader meaning or the same meaning in the specification or the drawings can be replaced with the different term in any part of the specification or the drawings. Further, the configurations and operations of the state detection device, the electronic device, the measurement system, and the program are not limited to those described in the present embodiment, and various modifications can be made.

100 status detection device, 110 acquisition unit, 120 integration processing unit,
130 speed index value calculation unit, 140 speed estimation value calculation unit, 150 storage unit,
160 exercise state determination unit, 170 distance index value calculation unit, 180 distance estimation value calculation unit,
190 calibration processing unit, 200 acceleration sensor, 300 antenna unit,
400 wireless communication unit, 500 battery (battery socket), 600 heart rate measurement electrode terminal,
700 first electronic substrate, 800 second electronic substrate, 900 electronic device

Claims (14)

An acquisition unit for acquiring detected acceleration from the acceleration sensor;
An integration processing unit for performing integration processing for integrating a value obtained from at least one coordinate axis component of the detected acceleration for a given period, and obtaining an acceleration integrated value I;
A speed index value calculator that obtains a speed index value r used for estimating the speed according to a relational expression of r = aI ² + bI + c (coefficients a, b, and constant c are given real numbers);
A state detection device. In claim 1,
When the first coordinate axis Y of the motion analysis coordinate system is a coordinate axis parallel to the vertical line,
The integration processing unit
As the integration process, a process of obtaining a first coordinate axis component of the detected acceleration, integrating at least a value corresponding to an absolute value of the first coordinate axis component, and obtaining the acceleration integrated value I is performed. A state detection device. In claim 2,
In the motion analysis coordinate system, when the first coordinate axis Y, the second coordinate axis X, and the third coordinate axis Z are orthogonal to each other,
The integration processing unit
As the integration process, a first integrated value I _y is obtained based on the first coordinate axis component of the detected acceleration, a second integrated value I _x is obtained based on the second coordinate axis component of the detected acceleration, A third integrated value I _z is obtained based on the third coordinate axis component of the detected acceleration, and the first integrated value I _y , the second integrated value I _x, and the third integrated value I _z are obtained. A state detection apparatus that performs a process of calculating the acceleration integrated value I by integrating the values. In claim 2 or 3,
The integration processing unit
As the value corresponding to the absolute value of the first coordinate axis component of the detected acceleration in the motion analysis coordinate system, the nth power (n is a positive even number) of the first coordinate axis component is obtained, and the obtained first A state detection apparatus that performs a process of accumulating the nth power of a coordinate axis component. In any one of Claims 1 thru | or 4,
A storage unit for storing the coefficients a and b and the constant c obtained from actual measurement values;
The speed index value calculator is
A state detection apparatus that obtains the speed index value r based on the coefficients a and b and the constant c acquired from the storage unit. In any one of Claims 1 thru | or 5,
Including an exercise state determination unit for determining an exercise state of the user;
The speed index value calculator is
A state detection apparatus, wherein the coefficients a and b and the constant c to be used are switched according to the motion state. In any one of Claims 1 thru | or 6.
Including a calibration processing unit for performing a calibration process based on the actual speed measurement value,
The speed index value calculator is
At least one value of the reference speed V _s , which is a speed used as a reference of the moving speed of the user when obtaining the speed estimated value V _d , the coefficients a and b, and the constant c is used as a result of the calibration process. A state detection device that changes based on the above. In any one of Claims 1 thru | or 7,
A state detection device comprising a distance index value calculation unit for determining a distance index value s based on the speed index value r determined by the speed index value calculation unit. In claim 8,
A distance estimation value calculation unit that performs a multiplication process based on the distance index value s obtained by the distance index value calculation unit and a reference distance D _s to obtain a distance estimation value D _d is included. State detection device. In any one of Claims 1 thru | or 9,
The integration processing unit
In the speed estimation timing M1, the acceleration integration value I _M1 is obtained from the sum of the acceleration integration values I _{T1 to} I _Ti obtained at each of the preceding speed estimation timings _{T1 to Ti} (i is a positive integer of 2 or more),
Wherein the next speed estimated timing M2 velocity estimated timing M1, acceleration cumulative value from the sum of the preceding velocity estimated timing T2~T acceleration cumulative value obtained in each of the _{(i + 1) I T2 ~I} T (i + 1) I M2 A state detection apparatus characterized by obtaining In any one of Claims 1 thru | or 10.
And said speed index value r determined by the speed index value calculation section, based on the reference velocity V _s, performs multiplication processing, characterized in that it comprises a speed estimation value calculating unit for obtaining the estimated speed V _d State detection device.   12. An electronic device comprising the state detection device according to claim 1 and the acceleration sensor.   A measurement system comprising the state detection device according to claim 1. An acquisition unit for acquiring detected acceleration from the acceleration sensor;
An integration processing unit for performing integration processing for integrating a value obtained from at least one coordinate axis component of the detected acceleration for a given period, and obtaining an acceleration integrated value I;
As a speed index value calculation unit for determining the speed index value r based on an equation of r = aI ² + bI + c (coefficients a, b, and constant c are given real numbers),
A program characterized by operating a computer.

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