JP2013113761A - State detector, electronic equipment and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a state detector for enhancing the accuracy of estimating a step by performing processing based on average acceleration, reference average acceleration and a reference step, electronic equipment, and a program.SOLUTION: A state detection device 100 includes an acquisition part 110 for acquiring an acceleration detection value from an acceleration sensor 10, an average acceleration calculation part 162 for calculating average acceleration in each given period on the basis of the acceleration detection value, a reference information acquisition part 164 for acquiring reference average acceleration and a reference step, and a step estimation part 160 for estimating a step on the basis of a radio of the average acceleration to the reference average acceleration, and the reference step.

Description

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

  2. Description of the Related Art Devices that detect an object state based on an acceleration value from an attached acceleration sensor are known. For example, if the state detection target is a person, an acceleration sensor is attached to the user's body, and the user's state (for example, an exercise state such as walking or running) is detected. A typical example is a pedometer that detects the user's walking / running and counts the number of steps such as walking. There is also a method for measuring a moving distance by calculating a user's stride.

  Conventionally, in distance measurement, a method for estimating a distance by taking a product of a walking / running step (corresponding to detection of one step) and a stride has been proposed. However, such a method is easy to process, but if the step length calculation accuracy is poor, the distance measurement accuracy also deteriorates.

  Patent Document 1 proposes a method for improving the accuracy of distance estimation by calculating a stride based on a user's pitch.

JP 7-333000 A

  In the method of Patent Document 1, the stride is calculated based on the pitch. However, the relationship between the pitch and the stride is not linear, and there is a large individual difference for each user, and sufficient accuracy cannot be obtained in calculating the stride. As a result, the accuracy of distance estimation is not sufficient.

  According to some aspects of the present invention, it is possible to provide a state detection device, an electronic device, a program, and the like that improve the estimation accuracy of the stride by performing processing based on the average acceleration, the reference average acceleration, and the reference stride.

  One aspect of the present invention is an acquisition unit that acquires an acceleration detection value from an acceleration sensor, an average acceleration calculation unit that calculates an average acceleration for a given period based on the acceleration detection value, a reference average acceleration, The present invention relates to a state detection device including a reference information acquisition unit that acquires a reference stride, a stride estimation unit that estimates a stride based on the ratio of the average acceleration to the reference average acceleration, and the reference stride.

  According to one aspect of the present invention, the average acceleration is acquired based on the acceleration detection value from the acceleration sensor, and the reference average acceleration and the reference stride are acquired. Then, the stride is estimated based on the ratio of the average acceleration to the reference average acceleration and the reference stride. By performing the processing based on the average acceleration, it becomes possible to improve the accuracy of stride estimation.

  In one aspect of the present invention, the apparatus includes a step detection unit, and the reference information acquisition unit calculates the reference stride based on input distance information and the number of steps detected by the step detection unit in a reference information acquisition period. You may get it.

  Thereby, it becomes possible to acquire the reference stride based on the input distance information and the number of steps.

  In the aspect of the invention, the reference information acquisition unit may acquire the reference average acceleration based on the average acceleration acquired in the reference information acquisition period and the number of steps.

  Thereby, it becomes possible to acquire the reference average acceleration based on the average acceleration and the number of steps.

  In one aspect of the present invention, the stride length estimation unit may be configured such that the reference average acceleration is NA, the reference stride length is NS, a coefficient is C, and the average acceleration acquired at a given timing is An. The stride Sn corresponding to the timing at which the average acceleration An is acquired may be obtained by Sn = C × (An / NA) × NS.

  In this way, specifically, it becomes possible to estimate the stride from the above formula.

  In the aspect of the invention, the input distance information may be user input information or external data.

  As a result, user input information or external data can be used as input distance information used for reference stride calculation.

  In one aspect of the present invention, the reference information acquisition unit obtains a reference average acceleration candidate based on the average acceleration in the signal value acquisition period and the number of steps detected in the signal value acquisition period, When there is a reference information acquisition instruction, the reference average acceleration candidate may be acquired as the reference average acceleration in association with the reference stride during the signal value acquisition period.

  This makes it possible to obtain a reference average acceleration candidate during the signal value acquisition period, and to determine whether or not to use the reference average acceleration candidate as the reference average acceleration based on the presence or absence of a reference information acquisition instruction. .

  In the aspect of the invention, the reference information acquisition unit may acquire the reference distance information of the running or the walking in the signal value acquisition period when the reference information acquisition instruction is given.

  Thereby, since the reference distance information is acquired at the time of the reference information acquisition instruction, it is possible to calculate the reference stride.

  In the aspect of the invention, the reference distance information may be user input information or external data.

  This makes it possible to use user input information or external data as reference distance information used for reference stride calculation.

  In the aspect of the invention, the average acceleration calculation unit may calculate the average acceleration for each given period set based on a timing at which a step is detected by the step detection unit.

  This makes it possible to calculate the average acceleration based on the step detection timing.

  In one aspect of the present invention, a filter processing unit that performs a band-pass filter process on the acceleration detection value, and a control unit that changes a filter characteristic of the band-pass filter process in the filter processing unit are included. The step detection unit detects step cycle information based on the acceleration detection value after the band pass filter processing, and the control unit detects the step cycle information based on the step cycle information detected by the step detection unit. The filter characteristics of the band pass filter process may be adaptively changed.

  As a result, it is possible to filter the acceleration detection value and adaptively change the characteristics of the filter used for the filter processing based on the step period.

  Moreover, in one aspect of the present invention, a distance information calculation unit that calculates distance information of running or walking based on the stride estimated by the stride estimation unit may be included.

  Thereby, it becomes possible to calculate distance information based on the estimated stride.

  Further, according to one aspect of the present invention, a determination unit that determines whether the vehicle is in a running state or a walking state based on the acceleration detection value is included, and the distance information calculation unit is determined by the determination unit to be in the driving state. The distance information is calculated based on the stride estimated by the stride estimation unit, and the distance information is determined based on a predetermined stride when the determination unit determines that the walking state is established. May be calculated.

  As a result, it is possible to determine the stride used for calculating the distance information based on the determination result after determining whether the vehicle is in the running state or the walking state.

  According to another aspect of the present invention, an acquisition unit that acquires an acceleration detection value from an acceleration sensor, an average speed calculation unit that calculates an average speed for a given period based on the acceleration detection value, and a reference The present invention relates to a state detection device including a reference information acquisition unit that acquires an average speed and a reference stride, a ratio of the average speed to the reference average speed, and a stride estimation unit that estimates a stride based on the reference stride. .

  Another aspect of the invention relates to an electronic apparatus including the state detection device according to any one of the above.

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

The figure explaining the frequency characteristic example of an acceleration detected value. The wave form diagram of the acceleration detection value before a filter process and after a filter process. The figure explaining the difference of the distance calculation accuracy by the method of a conventional method and this embodiment. 1 is a system configuration example of an electronic device or the like including a state detection device of the present embodiment. The system configuration example of the state detection apparatus of this embodiment. A configuration example of a filter used for filter processing. Explanatory drawing of average acceleration. Explanatory drawing of the distance calculation process in the case of acquiring input distance information. The flowchart explaining the filter process and the adaptive change process of a filter characteristic. The flowchart for demonstrating a walk running determination process. The flowchart for demonstrating step length estimation processing. The flowchart for demonstrating the stride estimation process in the case of acquiring input distance information. The structural example of the system which runs the program concerning this embodiment.

  Hereinafter, this embodiment will be described. 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 present invention.

1. First, the method of this embodiment will be described. The state detection apparatus of this embodiment is worn by a person (user) and detects a state related to the person's walking / running. Specifically, based on the sensor signal from the acceleration sensor, the number of steps for walking / running, detection of the step period (step frequency), running state discrimination (discrimination of whether walking or running, etc.), stride length Performs estimation and accompanying distance information calculation.

  Conventionally, a method for performing these processes by frequency analysis using FFT or the like has been proposed, but it is difficult to accurately detect the number of steps and cope with fluctuations in the step frequency, and it is also possible to capture fluctuations in the FFT frame period. Have difficulty. Therefore, in this embodiment, processing is performed using the acceleration detection value instead of frequency analysis. That is, instead of the frequency axis, for example, a time change of the acceleration detection value is used.

  However, as shown in FIG. 1, the acceleration detection value includes signals of various frequencies in addition to the step frequency that is originally intended to be processed, and the time change of the acceleration detection value is, for example, the broken line in FIG. It will be a complicated shape. Therefore, filter processing is performed instead of using the acceleration detection value as it is. Specifically, a filtering process may be performed in which the step frequency is passed and the other frequencies are not passed. In this way, a clean signal waveform as shown by the solid line in FIG. 2 can be acquired.

  The problem here is when the step frequency fluctuates. The step frequency corresponds to the walking / running pitch of the user, but the pitch naturally changes even when the user intends to continue a certain movement. Furthermore, when the exercise itself changes (change from jogging to dash, change from walking to running, etc.), it cannot be considered that the change in pitch is not taken into consideration. As described above, the filter process is for passing the step frequency and not passing the others. However, if the step frequency is changed, the correspondence between the pass band of the filter and the step frequency is lost. End up.

  Therefore, the present applicant adaptively changes the characteristics of the filter used for the filter processing (frequency characteristics in a narrow sense) based on the step period information (which may be the step period or the step frequency). Suggest a method. In this way, even when the step frequency changes, it is possible to perform a filtering process that passes the step frequency and does not pass the others, and accurate state detection can be performed. Specifically, the characteristics of the filter used for the filter processing at the next timing may be changed based on the step frequency detected at a certain timing.

  In the present embodiment, it is assumed that the acceleration sensor is attached to the arm (for example, attached to the wrist like a wristwatch). This is due to the user's request to view the detection data during exercise. For example, when an acceleration sensor is attached to the leg, if the display unit is provided integrally with the acceleration sensor, it is difficult for the user to see the display unit during exercise. That is, it must operate in conjunction with other devices suitable for display browsing such as a wristwatch type device, a head mounted display, and a smartphone. Therefore, it is necessary to frequently use the communication function, which is disadvantageous from the viewpoint of power saving. In that respect, as long as it is a wristwatch type device as described above, there is no problem even if a display unit is provided as a unit, and therefore, an internal closed process is sufficient (however, communication with a host computer or the like provided separately) Does not prevent).

  However, it is necessary to consider a problem that does not occur when the acceleration sensor is attached to the arm part and attached to the leg part. When attached to the leg, the acceleration detection value resulting from the movement of the leg that is directly linked to the number of steps can be directly obtained. Since a step frequency due to walking or the like appears as the lowest frequency peak during human walking / running, a low-pass filter is sufficient for the filter processing that passes the step frequency and does not pass others. However, when worn on the arm, both the right foot and the left foot move while the arm is swung once, so the arm swings to half the step frequency as shown in FIG. Corresponding frequency peaks appear. That is, since the arm swing frequency remains in the low-pass filter, it is necessary to use a band-pass filter.

  Even if the processing is based on the acceleration detection value of the frequency component corresponding to the arm swing frequency while passing the arm swing frequency using a low-pass filter and not passing the others, step detection, stride estimation, etc. Is possible. However, as long as one cycle of arm swing corresponds to walking / running of two steps, processing can be performed only in units of two steps. Considering that there is a large demand from the user to count the number of steps in units of one step, it is desirable to perform processing by a band pass filter instead of a low pass filter when wearing an arm.

  Moreover, although it is possible to acquire a beautiful acceleration signal waveform and perform step detection by performing the above-described filter processing, there is another problem in estimating the movement distance of the user by exercise. Conventionally, a method has been proposed for estimating distance by taking the product of the step count (steps) of walking / running and the step length, but the method is easy but the accuracy of calculating the step length is low and the distance estimation accuracy is low. It had become.

  For example, FIG. 3 shows a distance estimation result when three users travel a known distance (800 m) at three different speeds of high speed, medium speed, and low speed. At this time, the distance is estimated from the product of the stride calculated based on the exercise result at the medium speed and the number of steps in the broken line. As is clear from FIG. 3, a value close to the correct answer (800 m) can be obtained with medium speed exercise, which is the same situation as when calculating the stride, but the estimation accuracy is greatly reduced during high speed / low speed exercise. . This is because the stride is extended at high speed and the number of steps tends to be smaller than that at medium speed, so that the travel distance is estimated to be short. Similarly, since the stride is reduced at low speed and the number of steps tends to be larger than that at medium speed, the moving distance is estimated to be longer.

  On the other hand, a method of estimating the stride based on the pitch (step frequency) has been proposed, but the relationship between the pitch and the stride is not linear, and the influence of individual differences is great and not effective.

  Therefore, the applicant estimates the stride based on the average acceleration and the reference information (reference average acceleration / reference stride), and calculates the movement distance based on the estimated stride. Details of the average acceleration and the like will be described later with reference to FIG. 7 and the like, but by using the method of this embodiment, it is possible to improve the accuracy of distance estimation. Specifically, the solid line in FIG. 3 is an actual measurement value when the method of the present embodiment is used, and the motion state (for example, moving speed, etc.) changes between the calculation of the stride (reference stride) and the distance estimation. Even if it does, it turns out that the value near a correct answer is obtained compared with the conventional method.

  In the following, after describing the system configuration example, filter adaptation processing, walking / running determination processing using a signal after adaptively changing characteristics, and stride estimation processing, and distance information calculation processing based thereon are also described. Shall. Finally, details of each process will be described using a flowchart.

2. System Configuration Example FIG. 4 shows a configuration example of the state detection apparatus according to the present embodiment and an electronic apparatus including the state detection apparatus. The electronic apparatus (for example, a wristwatch type device including a state detection device) includes an acceleration sensor 10, a storage unit 20, a communication unit 30, a display unit 40, an operation unit 50, and a state detection device 100. However, the electronic apparatus is not limited to the configuration shown in FIG. 4, and various modifications such as omitting some of these components (for example, the communication unit 30 may be omitted) or adding other components. Implementation is possible.

  The acceleration sensor 10 is, for example, a triaxial acceleration sensor. The storage unit 20 serves as a work area for the state detection device 100 and the like, and its function can be realized by a memory such as a RAM or an HDD (hard disk drive). The storage unit 20 stores information that is assumed to be presented to the user, such as the user's travel distance information calculated by the distance information calculation unit 170, and also stores user information such as filter characteristic parameters used by the filter processing unit 120. Internal information that is not expected to be stored is also stored.

  The communication unit 30 communicates with an external device. As the external device, a host computer that performs analysis processing of information detected by the state detection device 100 can be considered. The communication unit 30 is preferably realized wirelessly in consideration of communication in a state worn by the user, but may be wired.

  The display unit 40 is for displaying various display screens, and can be realized by, for example, a liquid crystal display or an organic EL display. Although the display part 40 shall display the information by the state detection apparatus 100, you may display other information. For example, if the electronic device is a wristwatch type device, the time may be displayed. Further, if the display unit 40 is realized by a touch panel, an interface for operation may be displayed. In this case, part or all of the functions of the operation unit 50 are realized by the display unit 40.

  The operation unit 50 is for a user to perform various operations of the electronic device, and can be realized by various buttons and the like. The various buttons may be mechanical buttons or images displayed on a touch panel or the like.

  The state detection device 100 detects the state of an electronic device (in a narrow sense, a user wearing the electronic device). The state may be a state relating to a posture of standing or sleeping, or a state relating to movement indicating whether or not the vehicle is on a vehicle. In a narrow sense, it may represent an exercise state represented by walking or running.

  Next, a detailed configuration example of the state detection apparatus 100 will be described with reference to FIG. As shown in FIG. 5, the state detection apparatus 100 includes an acquisition unit 110, a filter processing unit 120, a control unit 130, a step detection unit 140, a step cycle information detection unit 142, a step count unit 144, The determination unit 150 includes a stride length estimation unit 160, an average acceleration calculation unit 162, a reference information acquisition unit 164, and a distance information calculation unit 170. However, the state detection apparatus 100 is not limited to the configuration in FIG. 5, and various modifications such as omitting some of these components or adding other components are possible.

  The acquisition unit 110 acquires sensor information from the acceleration sensor 10. If the acceleration sensor 10 is a three-axis acceleration sensor, three values corresponding to the xyz axes are acquired. The acquisition unit 110 is configured as an interface between the acceleration sensor 10 and the state detection device 100, and may output the sensor signal from the acceleration sensor 10 to the filter processing unit 120 as it is or when outputting to the filter processing unit 120. Pre-processing may be performed.

  As preprocessing, for example, three acceleration signal values of xyz may be combined (for example, processing for obtaining the square root of the sum of squares) to calculate a combined acceleration, or acceleration due to the landing of the user's foot may be removed. May be low pass filter processing for both, or both. Low-pass filter processing is performed because walking / running detection is based on the acceleration due to the movement of the user's body, so the acceleration due to the landing impact interferes with the processing, and the acceleration of the landing impact appears mainly at high frequencies. That is the reason. Further, instead of calculating the combined acceleration, a process for obtaining a value related to a specific axis may be performed after performing a coordinate conversion process to a coordinate system different from the sensor coordinate system.

  In the present embodiment, information input from the acceleration sensor 10 to the acquisition unit 110 is expressed as sensor information, and information output from the acquisition unit 110 to the filter processing unit 120 is expressed as an acceleration detection value. If no pre-processing is performed at all, the sensor information and the acceleration detection value represent the same information, but in general, since the above-described processing, noise reduction processing, and the like are performed, the sensor information and the acceleration detection value are It becomes different information.

  The filter processing unit 120 performs a filter process on the acceleration detection value output from the acquisition unit 110. In this embodiment, since walking / running detection (determination) and subsequent step length estimation are assumed, a step frequency corresponding to the user's walking / running pitch is allowed to pass, and frequencies other than the step frequency are non-passed. What is necessary is just to perform the filter processing to be passed. In the present embodiment, considering the case where a peak frequency that should not pass is generated at a frequency lower than the step frequency (for example, when an acceleration sensor is attached to the arm), the filter process is a band-pass filter process. It will be explained as a thing.

  The control unit 130 controls the characteristics of the filter used in the filter processing unit 120 based on the step cycle information (for example, step frequency) output from the step cycle information detection unit 142. Details will be described later.

  The step detection unit 140 detects a step based on the signal after the filter processing in the filter processing unit 120. The step corresponds to the user's walking / running, and the step is detected once for each step. Since the acceleration detection value after the filter processing can be approximated to a sine wave of a step frequency component as shown by the solid line in FIG. 2, the step detection signal may be output once in one cycle of the signal. Specifically, it is only necessary to detect the upper peak (lower peak) of the signal waveform, and peak detection can be performed by obtaining a difference value (gradient) between the target timing and the timing before and after the target timing and from the zero cross of the difference value. . For example, the point at which the difference value between the signal values at adjacent timings switches from plus (minus) to minus (plus) may be set as the upper (lower) peak. In addition, the difference value is not only obtained from the adjacent timing, but the difference between the signal value before two timings and after two timings may be used. For example, the difference value from two timings before and the difference value from one timing are both positive (minus), the difference value from one timing and the difference value from two timings are both negative (plus). In some cases, the current timing may be the upper (lower) peak.

  The output from the step detector 140 may simply be a pulse signal notifying that a step has been detected. The pulse signal is information for outputting whether or not a detection has been made, and the content of the information may not be particularly significant. However, the step detection unit 140 acquires the acceleration detection value after the filter processing in order to perform step detection as described above. Therefore, it is possible to include not only the step detection but also the magnitude of the acceleration detection value at that time (the acceleration peak value that is the peak of the acceleration detection value if step detection is performed by peak detection) in the output information. is there. Furthermore, the acceleration detection value at a timing other than the step detection time may be output. Here, the output of the step detection unit 140 is expressed as step detection information. The step detection information is output to the step cycle information detection unit 142, the step count unit 144, the determination unit 150, and the average acceleration calculation unit 162. The content of the step detection information may differ depending on each part as an output destination, and details will be described later in the description of each part.

  The step cycle information detection unit 142 detects step cycle information based on the step detection information from the step detection unit 140. Here, the step period information may be a step period or a step frequency. The step detection information here may be the pulse signal described above, and the time from the input of the previous pulse signal to the input of the current pulse signal corresponds to the step period, and the reciprocal corresponds to the step frequency. Further, the step cycle information may be other information obtained based on the step cycle or the step frequency. The step frequency information is output to the control unit 130.

  The step count unit 144 counts steps. The value counted by the step count unit 144 corresponds to the number of steps of the user. Simply, it may be a counter that increments each time step detection information (here, a pulse signal) is input from the step detection unit 140. Further, the step count unit 144 may perform other processes instead of a simple counter. For example, the accuracy of detecting the number of steps may be improved by excluding step detection due to movement, noise, or the like other than walking.

  The determination unit 150 determines whether the user is in a walking state or a traveling state. The determination is made based on step detection information from the step detection unit 140. Although details will be described later, it is assumed that the step detection information here includes not only a pulse signal but also an acceleration peak value.

  The stride estimation unit 160 estimates the stride of the user. The stride is estimated based on the average acceleration / reference information (reference average acceleration / reference stride). Moreover, you may use the determination result in the determination part 150 in the step estimation.

  The average acceleration calculation unit 162 calculates the average acceleration based on the step detection information from the step detection unit 140. The average acceleration corresponds to an average value of acceleration detection values after filtering in a time from detection of a certain step to detection of the next step. Therefore, the step detection information here needs to include not only the pulse signal but also the acceleration detection value after filtering at a timing other than the step detection time. Therefore, although not shown in FIG. 5, the average acceleration calculation unit 162 may be connected to the filter processing unit 120 to directly acquire the acceleration detection value after the filter processing from the filter processing unit 120. In this case, simple step detection information such as a pulse signal is sufficient.

  The reference information acquisition unit 164 acquires reference information based on the average acceleration calculated by the average acceleration calculation unit 162, the step count number by the step count unit 144, and the like. The reference information acquisition unit 164 may include a reference average acceleration calculation unit 166 that calculates a reference average acceleration and a reference stride calculation unit 168 that calculates a reference stride. Since each part after the step estimation unit 160 relates to the step estimation process, details will be described later.

  The distance information calculation unit 170 calculates distance information (movement distance) based on the user's walking / running based on the stride estimated by the stride estimation unit 160. Details will be described later.

3. The filter processing for the acceleration detection value acquired by the filter adaptation acquisition unit 110 will be described. Here, assuming a case where an acceleration sensor is mounted on the arm, processing using a band-pass filter will be described as filter processing. However, the sensor mounting part is not necessarily limited to the arm part.

  In the state detection device of the present embodiment, information related to the user's walking / running is acquired. However, since the acceleration detection value has a peak value at a frequency other than the step frequency of walking / running, the time-change waveform of the acceleration detection value has a complicated shape as shown by a broken line in FIG. For example, if an acceleration sensor is attached to the arm, when the step frequency is set to 2F, a peak of the arm swing frequency appears at F, which is half the frequency (the arm is swung while the foot walks twice). For). Moreover, a peak also appears in a high frequency band such as 3F or 4F as a combination of the arm swing frequency and the step frequency.

  Therefore, the filter processing unit 120 performs bandpass filter processing that passes 2F and does not pass others. However, it is not necessary to pass only the 2F frequency strictly. Due to the realistic design of the bandpass filter, the passband has a certain width, but even if the frequencies between F and 2F and between 2F and 3F are passed, there is no peak value in the frequency band. The effect on the subsequent processing is not great. In other words, the characteristics of the bandpass filter may be any filter that allows 2F to pass in the narrow sense and does not pass F or less and 3F or more. For pass / non-pass, for example, the frequency band included in the pass band determined by the cutoff frequency may be defined as pass, and the other frequency band may be defined as non-pass.

  The band pass filter may be constituted by, for example, a general biquadratic filter (IIR filter) shown in FIG. This filter is expressed by the following equation (1), where x is the input value and y is the output value. Further, the filter coefficients in FIG. 6 are specifically expressed by the following equations (2) to (8).

y [n] = (b0 / a0) * x [n] + (b1 / a0) * x [n-1] + (b2 / a0) * x [n-2]-(a1 / a0) * y [ n-1]-(a2 / a0) * y [n-2]
(1)
b0 = α (2)
b1 = 0 (3)
b2 = -α (4)
a0 = 1 + α (5)
a1 = -2cos (2πf) (6)
a2 = 1-α (7)
α = sin (2πf) / Q (8)
Here, f represents the center frequency of the bandpass filter, and Q is a coefficient that determines the filter bandwidth. That is, various band pass filters can be configured by setting f and Q.

  That is, the control unit 130 obtains a step frequency from the output value from the step cycle information detection unit 142 (or the step frequency itself may be output), and f in the above formulas (1) to (8) is set as the step frequency. Process to change to.

  Thus, the filter used in the filter processing unit 120 based on the step frequency obtained at the current timing (for example, the reciprocal when the time between the step detection one timing before and the latest step detection is set as the step period). It becomes possible to change characteristics and perform filter processing at subsequent timings. Since the filter characteristics adaptively change based on the detected step period information, even if the step frequency changes during exercise, it is possible to perform appropriate filter processing.

  Note that Q in the above equation (8) may be a fixed value, or may be adaptively changed based on filter period information. However, it is a condition that the frequency of F or 3F is not included in the passband.

  In addition, since the filter characteristic is adaptively changed according to the user's exercise state, it is necessary to determine a given filter characteristic at the start of exercise (at the start of system operation). This may be a fixed value, but if the exercise to be performed is known (for example, whether to dash a short distance or jog a long distance), it is desirable to change the value according to the exercise. If the initial value is appropriately set, the subsequent filter characteristics can be adaptively set by the method of the present embodiment.

  The change of the filter characteristic in the control unit 130 may be performed for each step (every step) or for each specific number of steps. If it is performed for each step, it becomes possible to cope with a change in the step frequency at a high speed. Moreover, if it carries out for every specific step number (for example, every 10 steps), since the frequency of the process in the control part 130 can be made low, power saving etc. can be anticipated. Further, depending on the mounting position of the acceleration sensor, it is conceivable that the step frequency is biased between when the right foot is stepped on and when the left foot is stepped on. In such a case, it is good to carry out every step number (for example, every two steps) instead of every step. If you want to change the characteristics for each step even though there is a bias, the process will be complicated, but prepare two sets of parameters, a right foot filter parameter and a left foot filter parameter, depending on the stepping foot. The parameters used may be changed. In this case, the right foot filter parameter is updated using the step frequency when the right foot is stepped on, and the left foot filter parameter is updated using the step frequency when the left foot is stepped on.

4). Next, the walking / running determination process in the determination unit 150 will be described. Here, the determination is simply made based on the signal value of the acceleration signal (mainly a sine wave of the step frequency) after the filter processing in the filter processing unit 120.

  For example, the peak acceleration which is the peak value of acceleration is obtained, and the peak acceleration is compared with the threshold value. When the first threshold value is Th1 and the second threshold value is Th2 (<Th1), if the peak acceleration is smaller than Th2, it is determined that the vehicle is not in a walking state or a running state. This corresponds to an arm swinging motion other than walking / running, such as when the arm is moved during a stop. Further, when the peak acceleration is equal to or greater than Th2 and smaller than Th1, it is determined as a walking state. When the peak acceleration is equal to or greater than Th1, the running state is determined.

  Here, a value of about 0.2 (G) is assumed as Th2, and a value of about 0.5 (G) is assumed as Th1. Although the sensor value detected by the acceleration sensor may have a magnitude of about 10 (G), since the direct current component is removed by the band-pass filter process, the threshold value may be the above level.

  Further, not only the magnitude of the acceleration signal but also information relating to step detection may be used to determine walking and running. For example, when the electronic device including the state detection device of this embodiment is a wristwatch type device, the display unit 40 may be provided as shown in FIG. It is conceivable to refer to the information (movement distance, movement speed, etc. at that time) displayed in 40. In that case, it is assumed that the relative position of the arm with respect to the user's body is kept constant to some extent, and the arm swinging operation is not performed, as in the case of viewing time with a wristwatch. Since the acceleration sensor is included in the wristwatch-type device and acquires an acceleration signal related to the arm, the magnitude of the acceleration signal becomes small unless the arm swinging operation is performed.

  Even in such a case, if the user is walking or running, the acceleration caused by those motions can be detected by the acceleration sensor. Therefore, the sensor information has a peak at the step frequency 2F, and it is not necessary to change the above-described step detection processing, step cycle information detection processing, filter characteristic change processing in the control unit 130, and the like.

  However, when the user looks at the wristwatch type device while running, the acceleration detection value becomes small even though the running state continues as an exercise, and the above threshold determination makes the walking state or the stopped state ( A state where neither the running state nor the walking state is determined).

  Therefore, in consideration of such a case, the walking / running determination may be performed using information related to step detection (for example, step period) in addition to the acceleration signal value. An example of a specific method is shown. Here, for the sake of simplicity, it is determined whether the vehicle is in a walking state or a running state, and the stop state is not considered. First, as a first stage process, threshold determination using the magnitude of the acceleration signal value is performed. When the threshold value is larger than the threshold value, it is determined as a running state, and when it is equal to or less than the threshold value, it is determined as a walking state. When the exercise state does not change from the previous exercise state (running → running, walking → walking), and when the exercise state is shifted in a high speed direction (walking → running), the determination result by the threshold determination is Use as is. As described above, since it is a problem that the acceleration signal value is reduced by referring to the display unit 40, if the acceleration signal value is changed in the same or larger direction, the reference of the display unit 40 is referred to. It is because it is thought that it is not performed.

  On the other hand, when the motion state is shifted in a low speed direction (running → walking), it is necessary to appropriately determine whether the motion itself has really changed or whether the display unit 40 is being referred to. Therefore, here, a comparison process between the step period in the immediately preceding state and the latest step period is performed. For example, if the user's movement itself has changed from running to walking, the acceleration signal value should decrease and the step period should also change (the direction of change varies depending on the user, for example, walking is a step compared to running) Tend to have a long period). That is, if the step period has changed to some extent, it is determined that the exercise itself has changed, and the walking state that is the result of the initial threshold determination is used as it is. On the other hand, if the change in the step period is small, it is considered that the equivalent motion state is continuing, and therefore it is determined that the decrease in the acceleration signal value is due to the reference of the display unit 40. In this case, what is determined to be the walking state in the threshold determination is corrected to the running state.

  It should be noted that it is not necessary to simply consider changes in the exercise state. That is, if it is determined to be a walking state, a determination process based on a step cycle may be performed regardless of whether it is a running state or a walking state. This example will be described later with reference to the flowchart of FIG.

5. Step length estimation / distance information calculation processing Next, the step length estimation processing and the distance information calculation processing based on the estimated step length and the like will be described. In this embodiment, the user's stride is estimated based on the average acceleration and the reference information (reference average acceleration, reference stride).

5.1 Average Acceleration First, the average acceleration used for stride estimation according to the present embodiment will be described. The average acceleration corresponds to an average value of acceleration signal values in a given period. Specifically, the average acceleration calculation unit 162 calculates the average acceleration based on the acceleration detection value after the filter processing by the filter processing unit 120 and the step detection information (pulse signal or the like) from the step detection unit 140.

  Details will be described with reference to FIG. In addition, the horizontal axis of FIG. 7 represents time. The step detection in FIG. 7 corresponds to the timing at which a step is detected by the step detection unit 140, for example, the timing at which the average acceleration calculation unit 162 receives a pulse signal from the step detection unit 140. n-1, n, n + 1, and the like correspond to the number of step detections. For example, n is the nth step detection timing. Since one step detection corresponds to one step of the user, the step detection rate is about 1 to 2 times per second, whereas the sensor information acquisition rate from the acceleration sensor is higher than this. is assumed. Therefore, the output rate of the acceleration detection value from the filter processing unit 120 is also higher than the step detection, and the output timing corresponds to each line of the acceleration detection value in FIG.

  The average acceleration is an average value of acceleration detection values after filtering in the time from the previous step detection to the target step detection. That is, if the magnitude of the acceleration detection value is f (s) and the time from the (n−1) th step detection to the nth step detection is Tn, the average acceleration An corresponding to the nth step detection is 9).

5.2 Calibration Further, in the stride estimation of the present embodiment, a reference average acceleration that is a reference of the average acceleration and a reference stride that is a reference of the stride are used. A given value may be used for the reference average acceleration and the reference stride. However, the average acceleration and stride will vary depending on the user, and the standard values will change. It is desirable to be determined based on a value obtained by running. That is, it is preferable to perform calibration to actually acquire the reference average acceleration and reference stride by actually walking and running. In the step estimation process of the present embodiment, even if the exercise state (traveling speed) at the time of acquiring reference information and the exercise state at the time of step estimation / distance calculation change as shown in FIG. Step length estimation and distance calculation are possible. Therefore, it is desirable that the exercise in calibration is essentially equivalent to the exercise at the time of estimating the stride that is assumed thereafter, but it is not always necessary to do so, and the calibration in a somewhat different exercise state is necessary. It may be.

  An example of calibration is shown. After setting the mode to the calibration mode, the user walks (runs) a known distance D (for example, D = 400 m is known if making a round of a 400 m track) and inputs the distance D. The acceleration detection value is acquired and the step is detected by walking / running. Further, the step count unit 144 also counts the step count number N (step count), which is the number of step detections.

  As described above, since the average acceleration is calculated for each step detection, the average acceleration calculation unit 162 performs N average accelerations (based on the above equation (9) by N step detections). A1-AN) will be acquired. Note that the 0th step detection time may be the start time of a reference information acquisition period (for example, a period from the start to the end of walking / running of D = 400 m). If D, N, and A1 to AN are given, the reference stride NS and the reference average acceleration NA are expressed by the following expressions (10) and (11).

  That is, the reference stride NS is obtained by dividing the movement distance D and the number of steps N, and the reference average acceleration NA is obtained as an average value of A1 to AN.

5.3 Stride Estimation / Distance Information Calculation In the present embodiment, the stride estimation / distance information calculation process is performed using reference information (reference average acceleration / reference stride) acquired before the process. The stride estimation process in the stride estimation unit 160 estimates the stride corresponding to the step for each step detection. The step length corresponding to the step is estimated based on NA and NS acquired in advance and the average acceleration An corresponding to the step. Specifically, when the average acceleration at the nth step detection (walking at the nth step) is An and the estimated stride at that time is Sn, Sn is represented by the following equation (12). Given.

  Here, C is a coefficient determined according to the individual and the running state. That is, the estimated stride can be obtained from the product of the ratio of the average acceleration to the reference average acceleration and the reference stride.

  The distance information calculation process in the distance information calculation unit 170 may take the sum of the estimated stride. In this embodiment, since the step length for each step (that is, the movement distance for each step) is estimated, the total movement distance is nothing but the sum of the estimated step lengths. The distance information calculation process may be changed based on the determination result in the determination unit 150. For example, when it is determined that the vehicle is in the running state, distance information is calculated using the estimation result obtained by the stride estimation unit 160, and when it is determined that the user is in the walking state, the distance information is obtained using a given fixed value as the stride. It may be calculated. This is because walking is a stable operation compared to running, and the variation in the stride is small, so that using a fixed value does not cause a big problem.

5.4 Modification 1 (Calibration Modification)
The calibration method is not limited to that described above. In the above-described example, it is known in advance that the calibration is performed, and it is not assumed that the stride estimation / distance information calculation is performed during the calibration operation. For example, the above calibration is performed when the reference information is not held, such as when a product equipped with the state detection device of the present embodiment is purchased and used for the first time.

  However, if the reference information is already held, it is possible to perform calibration while performing step length estimation and distance information calculation. As described above, the average acceleration is calculated in order to estimate the stride even when the calibration is not performed. Further, since step detection is also essential, it is assumed that the step count number N is also calculated. In other words, since A1 to AN and N are acquired even during normal use other than calibration, if the moving distance D is known, the reference average acceleration and the reference stride can be calculated.

  In the method of this embodiment, since the moving distance can be estimated by calculating the distance information based on the stride estimation, it is possible to basically walk and run an unknown distance (for example, jogging on a public road). However, in view of the fact that the device equipped with the state detection device of the present embodiment can also present other information such as the moving speed and the number of steps, even when traveling and walking a known distance (for example, running on a track, etc.) It is quite possible to wear a device.

  In such a case, the user can perform calibration by inputting his / her movement distance D to the device after the end of running / walking. As described above, since the average accelerations A1 to AN and the step count number N are acquired during exercise, the reference average acceleration and the reference stride can be calculated from the above equations (10) and (11) using the input D. It is.

5.5 Modification 2 (step length estimation / distance information calculation when reference distance information is acquired)
You may use the external apparatus which acquires reference | standard distance information with the state detection apparatus of this embodiment. The reference distance information is information related to the moving distance of the user, and is assumed to have higher value accuracy than the distance information calculation based on the stride estimation of the present embodiment. As an external device, for example, GPS is conceivable.

  Since the position information of the user can be acquired by using the GPS, it is possible to calculate the moving distance of the user based on the change in the position information. By using GPS, accurate distance information can be calculated. However, only by calculating the distance information by GPS, the distance information is acquired between the acquisition timings of the next GPS signal after acquiring the GPS signal at a certain timing. It will not be updated at all. That is, in order to calculate the movement distance in detail, it is necessary to acquire signals from the GPS with high frequency. However, GPS generally has a problem that power consumption is large, and if signals are acquired frequently, the operation time of the device is shortened. In particular, when the state detection device according to the present embodiment is incorporated into a conventional wristwatch, the wristwatch is required to continuously operate for several thousand to several tens of thousands of hours, so that power consumption due to operation of GPS or the like cannot be ignored.

  Therefore, it is conceivable to solve this problem by using the method of this embodiment as an auxiliary. That is, the power consumption can be reduced by setting the GPS signal acquisition rate low. Accordingly, the period during which the GPS signal cannot be obtained (that is, the time during which the travel distance is not updated as it is) becomes longer. Therefore, the travel distance is calculated by the method of the present embodiment during this period.

  Specifically, NS and NA are acquired before the first timing with reference to the first timing at which the GPS signal is acquired. Then, the acceleration detection value is acquired from the first timing to the second timing which is the next GPS signal acquisition timing, and the movement distance is calculated based on the above equations (9) and (12).

  A specific example is shown in FIG. The horizontal axis of FIG. 8 represents time, and shows GPS signal acquisition timing and step detection timing. In FIG. 8, for the sake of simplicity, the GPS signal acquisition timing is described as being coincident with one of the step detection timings. However, it is more common that this is not the case.

  First, a GPS signal is acquired at time T1, and comparison processing with a GPS signal before T1 is performed, thereby calculating reference distance information D1 representing a moving distance from a reference position (for example, a position at the start of walking / running). To do. Since the next GPS signal cannot be acquired until T2, distance information is calculated based on the stride estimation in the period from T1 to T2. If steps are detected at T1 and t1, a step length d1 corresponding to one step of T1 to t1 can be calculated from the above equations (9) and (12) based on the acceleration detection value during that time. Then, the movement distance from the reference position at time t1 can be calculated as D1 + d1. Similarly, if a step is detected at t2 after t1, the stride d2 between t1 and t2 is calculated by the above-described method, and the movement distance is obtained as D1 + d1 + d2. Hereinafter, D1 + Σd may be set as the movement distance until T2.

  And if the next GPS signal is acquired in T2, the reference distance information D2 showing the movement distance from the reference position in T2 will be calculated using the past GPS signal or the like. Here, since it is assumed that the calculation of the travel distance information based on the GPS signal is superior in accuracy, the travel distance based on the estimation of the stride so far is reset when the GPS signal is obtained. In the example of FIG. 8, two movement distances “D1 + Σd” and “D2” from the reference position at time T2 can be considered, but more accurate D2 is adopted.

  Further, between T2 and T3, the difference value from D2 may be obtained based on the stride estimation to calculate the travel distance information. When the GPS signal is acquired at T3, D3 is set as the travel distance. The same applies to the subsequent steps.

5.6 Modification 3 (example with reference average speed)
The process using the average acceleration and the reference average acceleration has been described above. However, the method of the present embodiment is not limited to this, and an average speed and a reference average speed may be used.

  Specifically, if the acceleration signal f (s) after the bandpass filter processing is acquired, the speed signal g (s) at the timing s is expressed by the following equation (13) by setting the sampling period of the acceleration signal to dt. ).

  Thereby, the speed signal g (s) can be acquired at the same timing as the acceleration signal f (s). Therefore, the average acceleration Vn can be obtained by the following equation (14) similarly to the above equation (9).

  Since the reference average speed is expressed by the following equation (15) as in the above equation (11), the stride is obtained by the following equation (16) as in the above equation (12).

6). Detailed Processing Details of each processing described above will be described with reference to FIGS.

6.1 Filter Adaptation Processing Details of the filter adaptation processing will be described with reference to FIG. When this process is started, it is first determined whether walking or running has ended (S101). This is a process termination condition, and in the case of Yes, the filter adaptation process is terminated. In the case of No in S101, sensor signals from the acceleration sensor (three sensor signals x, y, and z if a three-axis acceleration sensor) are acquired (S102).

  The acquired sensor signals are combined (for example, the square root of the sum of squares of x, y, z) is calculated, and the combined acceleration is calculated (S103). By performing low-pass filter processing on the calculated combined acceleration, an acceleration component due to landing impact is removed (S104).

  Then, the bandpass filter process is performed on the signal after the lowpass filter process using a bandpass filter having a preset characteristic (S105). Based on the signal after the bandpass filter processing, it is determined whether or not a step corresponding to the user's walking has been detected (S106). If no step is detected, the process returns to S101 to acquire the sensor signal. Repeat the filtering process. If a step is detected in S106, a step period is calculated (S107), and the characteristics of the bandpass filter are changed based on the calculated step period (S108). Specifically, as described above, the band pass filter is such that the time corresponding to the time between the latest step detection and the previous step detection is set as the step period, and the step frequency which is the reciprocal of the step period becomes the center frequency. What is necessary is just to change the frequency characteristic.

  In FIG. 9, the characteristics of the bandpass filter are changed for each step detection. However, the characteristics of the bandpass filter may be changed for each step detection.

6.2 Walking and Traveling Determination Process Details of the walking and traveling determination process will be described with reference to FIG. When this process is started, first, the peak value (acceleration peak value) of the acceleration detection value after the filter process is detected (S201). This is to detect the upper peak or the lower peak in the time change waveform of the acceleration detection value. However, in the flowchart of FIG. 10, it is assumed that the peak is an upper peak (if the lower peak is used, the peak value is a negative value). Therefore, it is necessary to invert the sign or take an absolute value).

  Then, a step cycle T1 corresponding to the timing at which the acceleration peak value is detected and a step cycle T2 corresponding to a timing earlier than the timing are acquired (S202). T1 and T2 may be calculated by the determination unit 150 based on the step detection by the step detection unit 140, or the determination unit 150 may acquire the value detected by the step cycle information detection unit 142. In addition, T2 specifically corresponds to a step period at the timing immediately before T1, but is not limited thereto, and may be calculated using values of several past steps.

  The walking / running determination is first performed based on the determination based on the acceleration peak value. The acceleration peak value is compared with a threshold value Th1 (for example, 0.5 G).

  If the acceleration peak value is smaller than Th1 (No in S203), a comparison is made with a threshold Th2 (eg, 0.2 G) that satisfies Th2 <Th1 (S205). If the acceleration peak value is smaller than Th2, it is determined that the vehicle is stopped (S208), and the process ends.

  If the acceleration peak value is smaller than Th1 and equal to or greater than Th2, determination is performed using the step periods T1 and T2 acquired in S202. Specifically, it is determined whether or not the variation of T1 with respect to T2 is within a given threshold. For example, if the allowable variation is 10%, it may be determined whether T1 / T2 is in the range of 0.9 to 1.1 (S206).

  When the fluctuation of the step cycle is small (Yes in S206), the actual motion state corresponds to the running state, but the acceleration is not performed by swinging the arm by referring to the display unit 40 of the wristwatch type device. It is determined that the peak value has become small, the process proceeds to S204, the driving state is determined, and the process is terminated. In addition, when the fluctuation of the step cycle is large (No in S206), the acceleration peak value is not affected by the reference of the wristwatch type device (that is, the acceleration peak value takes a small value due to a change in the movement state). It is judged that it is a walking state (S207), and a process is complete | finished.

6.3 Stride Estimation / Distance Information Calculation Processing Details of the step estimation / distance information calculation processing will be described with reference to FIG. FIG. 11 corresponds to processing from the start to the end of walking / running. When this process is started, first, a reference average acceleration NA and a reference stride NS are acquired (S301). As described above, the values acquired by the reference information acquisition unit 164 at the timing prior to the current process are used for NA and NS.

  Next, an acceleration detection value f (s) is acquired. f (s) is an acceleration detection value after the bandpass filter processing is performed by the filter processing unit 120, and is acquired at a rate corresponding to the sensor information acquisition rate of the acceleration sensor, for example. That is, the rate is generally higher than the step detection rate in the step detection unit 140. Then, the sum of f (s) is obtained (S303, in FIG. 11, the variable representing the sum is F).

  Then, it is determined whether or not a step has been detected (S304). If no step is detected, the process returns to S302 and the acquisition and accumulation of f (s) are repeated. Since F is initialized after step detection as will be described later in S312, F corresponds to the sum of acceleration detection values f (s) during a period from a certain step detection to the next step detection. Become.

  When a step is detected, a time T from the previous step detection to the step detection is acquired. Here, T corresponds to a step period.

Then, the average acceleration A corresponding to the latest step is obtained as A = F / T (S306). The processing in S303 and S306 corresponds to the above-described equation (9). Further, A _Σ which is the sum of average acceleration from the start of walking / running is calculated (S307), and a variable N representing the step count (corresponding to the number of steps) is incremented (S308).

Thereafter, determined from the above expression a stride S corresponding to the latest step (12) (S309), a cumulative sum of stride length S from the start of walking and running to calculate the S _sigma (S310).

Since various types of information are acquired through the processing up to S310, processing such as displaying on the display unit 40 at this timing may be performed (not shown in FIG. 11). For example, it may be possible to display N representing the number of steps, S _Σ representing the moving distance from the start of walking / running, and the like.

Then, it is determined whether the walking / running is finished (S311). If not finished, F is initialized (S312), and the process returns to S302. Since F represents the sum of acceleration detection values between adjacent steps, initialization is required in S312. On the other hand, N, A _Σ , and S _Σ are values that are meaningful for the accumulation from the start of walking / running, and therefore need not be initialized. Since A and S are values acquired for each step, they may be initialized at the timing of S312. However, since overwriting is performed in S306 and S309, initialization is not necessarily required.

  If it is determined in S311 that walking / running has ended, it is determined whether or not to execute calibration (S313). If calibration is not performed, the process ends. If calibration is to be performed, an accurate movement distance D in walking / running is acquired (S314), and a reference average acceleration NA and a reference stride NS are acquired from the above-described equations (10) and (11) (S315). The NA and NS acquired here will be used at the time of next walking and running.

Note that in order to perform accurate stride estimation (and distance information calculation), data used at the time of calibration needs to be as accurate as possible. Accordingly, in FIG. 11, S _Σ is the estimated movement distance, but since S _Σ is an estimated value and accuracy is not ensured, it is not assumed that S _Σ is used as D acquired in S 314. For D, for example, the user inputs a distance known to the user.

6.4 Modification of Stride Estimation / Distance Information Calculation Processing A modification of stride estimation / distance information calculation processing will be described in detail with reference to FIG. FIG. 12 shows an example in which a reference moving distance (reference distance information) can be acquired by some means, and corresponds to, for example, acquiring a GPS signal.

  Since S401 to S404 are the same as S301 to S304, a detailed description thereof will be omitted. Further, the processing in S405 to S412 in the case of Yes in S404 is the same as the processing in S305 to S312 in the case of Yes in S304.

  If YES in step S411, that is, if walking / running is ended, unlike the flowchart of FIG. 11, the processing ends without performing processing related to calibration.

If no step is detected in S404, it is determined whether or not reference distance information D (for example, distance information based on GPS signals) has been acquired (S414). If not acquired, the process returns to S402. When D is acquired, the D represents the moving distance from the previous acquisition of the reference distance information, and is more accurate than a method such as distance information calculation based on stride estimation. Therefore, the calibration can be performed by using the acquired D, the step count number N at that time (exactly from the time of acquisition of the previous reference distance information to the present), and the average acceleration accumulation A _Σ . Yes (S415).

  In the flowchart of FIG. 12, since the calibration is performed every time the reference distance information is acquired, the variables necessary for not affecting the next calibration are initialized (S416), and the process returns to S402. .

In this example, calibration can be performed as appropriate even if there is no explicit calibration instruction or the like. Since the reference distance information is assumed to be more reliable than the distance information calculated based on the stride estimation, the reference distance information is moved based on the acquired reference distance information at the timing when the reference distance information is acquired. The distance is obtained (details are as described above with reference to FIG. 8). Then, in a period in which the reference distance information is not acquired, distance information calculation based on stride estimation is performed as a process for obtaining a difference value with respect to the reference distance information. That, S407 of A _sigma, S408 is the N, S410 of S _sigma is reset at the reference distance information acquisition. Therefore, if a value from the start to the end of walking / running is required, another variable for holding each value must be prepared (N is equivalent to the number of steps) Is assumed).

6.5 Details of Processing In the present embodiment described above, the state detection apparatus 100 obtains an acceleration detection value from the acceleration sensor 10 as shown in FIG. 5 and a given value based on the acceleration detection value. An average acceleration calculation unit 162 that calculates an average acceleration for each period of time, a reference information acquisition unit 164 that acquires a reference average acceleration and a reference stride, and a stride estimation 160 that estimates a stride. The stride estimation unit 160 estimates the stride based on the ratio between the reference average acceleration and the average acceleration and the reference stride. Note that the given period may be set based on the timing at which the step is detected by the step detection unit 140, and the average acceleration may be calculated for each given given period.

  Here, the given period is preferably a period (one step) from a certain step detection timing to the next step detection timing. This is because the movement distance in one step (one step walk) can be obtained as the stride, and the movement distance can be estimated in detail. However, it does not preclude obtaining an average acceleration for each of a plurality of steps and estimating a moving distance in units of a plurality of steps.

  The average acceleration corresponds to an average value of acceleration detection values in the given period. Specifically, it is as described with reference to FIG. 7, and corresponds to the above equation (9). In the above formula (9), division is not performed by the time interval Tn representing the given period, but the number of acceleration detection values in the given period. This is because, unlike step detection or the like, it is assumed that acceleration detection values are acquired at regular intervals. The reference average acceleration is information serving as a reference for the average acceleration, and the reference stride is information serving as a reference for the stride.

  Specifically, first to M-th periods (M is an integer of 2 or more) are set, and the i-th (1 ≦ i ≦ M−1) period is a period before the i + 1-th period. And In this case, the state detection apparatus 100 according to the present embodiment includes the reference information acquisition unit 164 that acquires the reference average acceleration and the reference stride in a period before the i-th period, and the acceleration sensor 10 in the i-th period. An acquisition unit 110 for acquiring a detected acceleration value, an average acceleration calculation unit 162 for calculating an average acceleration for a given period included in the i-th period based on the detected acceleration value, and walking in the i-th period Or the stride estimation part 160 which estimates the stride corresponding to driving | running | working is included. The stride estimation unit 160 estimates the stride based on the ratio between the reference average acceleration and the average acceleration and the reference stride. Each of the first to M periods corresponds to a period from the start to the end of calibration, or a period from the start to the end of the exercise to be a stride estimation target. As described above, both stride length estimation and calibration may be performed in one period.

  Thereby, the stride estimation process based on the average acceleration, the reference average acceleration, and the reference stride becomes possible. Specifically, the reference average acceleration and the average acceleration are used in the form of a ratio. That is, the estimated stride value changes depending on whether the change in the average acceleration is large or small with respect to the reference average acceleration, and in which direction the change is. Further, when changing the estimated stride according to the ratio, it is desirable that a reference value before change is set, and in this embodiment, the reference stride is used. In the conventional example in which the stride is estimated based on the pitch, the accuracy of the estimated stride is low due to factors such as the pitch being not linear with the stride. However, according to the method of this embodiment, as shown in FIG. Therefore, it is possible to estimate the stride with high accuracy.

  Further, the state detection apparatus 100 may include a step detection unit 140 as shown in FIG. The reference information acquisition unit 164 (in a narrow sense, the reference stride calculation unit 168 included in the reference information acquisition unit 164) is based on the input distance information and the number of steps detected by the step detection unit 140 in the reference information acquisition period. , Get the reference stride. The input distance information may be user input information or external data. In the description of FIG. 5 and the like, the step detection unit 140 detects a step, the number of steps is detected by the step count unit 144, and the step period is detected by the step period information detection unit 142. I was supposed to. However, these units do not need to be independent, and may be configured by one block as a broad step detection unit. In the following description, it is assumed that the step detection unit 140 is a broad step detection unit, and not only the step detection but also the number of steps and step cycle information are detected.

  Note that the step detection unit 140 of the present embodiment may detect a user's running or walking step or the like. That is, the state detection apparatus 100 according to the present embodiment includes a step detection unit 140 that detects at least the number of steps of running or walking (for example, detects the step of running or walking, the number of steps, and step cycle information), and includes reference information The acquisition unit 164 may acquire the reference stride based on the input distance information and the number of steps detected by the step detection unit 140 in the reference information acquisition period.

  Here, the step corresponds to the movement per unit of the mounting target of the acceleration sensor 10. For example, if the acceleration sensor 10 is worn by a person (user) and the state detection device 100 detects a user's running or walking step, the step corresponds to the user's walking, A step is detected once by one step of walking. In the present embodiment, it is assumed that the steps are related to running or walking, but the broad steps are not limited thereto. If the acceleration sensor 10 is mounted on a vehicle (or a user riding on the vehicle), the step corresponds to an operation as a unit in the operation of the vehicle. For example, if the vehicle is a car, the step may correspond to the rotation of the mounted engine. Specifically, in the case of a gas turbine engine having a turbine, it may be considered that one rotation of the turbine corresponds to one step.

  The reference information acquisition period is a period for acquiring reference information, and may be a period from the start to the end of walking / running, for example. The input distance information is distance information input from a user or an external device, and is information corresponding to the moving distance of the user in the reference information acquisition period. The number of steps represents the number of steps detected in the reference information acquisition period.

  As a typical example, walking / running whose main purpose is calibration (acquisition of reference information) can be considered. That is, it is not necessary to perform stride estimation at that time. The user travels a known distance (for example, 800 m) for calibration, and inputs the known distance as input distance information. The reference information acquisition period at this time is a period from the start of 800 m travel to the end.

  This makes it possible to calculate the reference stride based on the input distance information and the number of steps. Specifically, when the input distance information is D and the number of steps is N, the reference stride NS may be given by the above equation (10). That is, the movement distance per step is obtained by dividing the movement distance by the number of steps, and this is used as the reference stride. Since the reference stride is used for estimating the stride in subsequent exercises, an appropriate value should be set, and it is desirable that the input distance information accurately reflects the movement distance of the user in the reference information acquisition period. Therefore, the input distance information is preferably user input information for inputting a known distance by the user, or external data with high accuracy obtained by an external device (for example, GPS).

  The reference information acquisition unit 164 (in a narrow sense, the reference average acceleration calculation unit 166 included in the reference information acquisition unit 164) calculates the reference average acceleration based on the average acceleration acquired in the reference information acquisition period and the number of steps. You may get it.

  This makes it possible to calculate the reference average acceleration from the average acceleration and the number of steps. The reference information acquisition period is assumed to be a period from the start to the end of walking / running or a period determined by external data acquisition timing. Therefore, the number of steps (number of steps) N detected in the reference information acquisition period is generally a certain size and is an integer of at least 2 (N = 1 is not prevented, but in such a case) The question remains about the reliability of the calculated reference information). Since the average acceleration is assumed to be calculated once per step, N average accelerations A1 to AN are acquired in the reference information acquisition period. Based on this N and A1 to AN, information that can serve as a reference for the average acceleration may be obtained and used as a reference average acceleration. For example, as shown in the above equation (11), if an average value of A1 to AN is taken, Good.

  The stride length estimation unit 160 also has a step length corresponding to the timing at which An is acquired, where NA is the reference average acceleration, NS is the reference step length, C is the coefficient, and An is the average acceleration acquired at a given timing. Sn may be obtained by Sn = C × (An / NA) × NS.

  This makes it possible to estimate the stride based on the above equation (12). In other words, if the coefficient C is not taken into consideration, when the average acceleration An matches the reference average acceleration NA, the step length Sn is the same as the reference step NS, and if An is k times NA, Sn is also NS times k. Therefore, in the conventional example using the pitch, the pitch and the stride are not linear, so sufficient accuracy cannot be obtained. However, by using the average acceleration, it is possible to estimate the stride by an easy calculation having linearity. It becomes possible. Note that C is a coefficient determined by the exercise state and individual differences, and further accuracy improvement can be achieved by appropriately setting C.

  The reference information acquisition unit 164 may obtain a reference average acceleration candidate based on the average acceleration and the number of steps in the signal value acquisition period. When there is a reference information acquisition instruction, a reference average acceleration candidate is acquired as a reference average acceleration. At that time, the acquired reference average acceleration is associated with the reference stride in the signal value acquisition period acquired based on the reference information acquisition instruction. In the case of the reference information acquisition instruction, the reference information acquisition unit 164 acquires reference distance information representing the travel distance of the running / walking in the signal value acquisition period. The reference distance information may be user input information or external data.

  Here, the signal value acquisition period is a period during which a signal value (sensor information of the acceleration sensor in a narrow sense) is acquired, and is a period from the start to the end of walking / running, for example. The reference information acquisition instruction is an instruction for obtaining acquisition of reference information, and may be performed by a user operating the operation unit 50 or may be performed based on a signal from an external device. It is assumed that the reference information acquisition instruction is accompanied by input of reference distance information corresponding to the moving distance of the user in the signal value acquisition period.

  Thereby, it becomes possible to acquire the reference information based on the average acceleration acquired mainly for the step length estimation. As a typical usage example of the state detection apparatus 100 of the present embodiment, first, calibration without step length estimation is performed by exercise in the reference information acquisition period, the reference information is acquired, and the acquired reference information is used thereafter. It is conceivable to perform stride estimation (without calibration in that case) in the above movements (each movement is performed in the signal value acquisition period). If it is desired to update the reference information, calibration without the stride estimation is performed again. In other words, the calibration and the stride estimation are typically performed exclusively.

  However, as described above, the average acceleration (A1 to AN) is calculated also in the step length estimation, and the number of steps N is acquired along with the step detection. That is, the NA can be calculated by the above equation (11) even if the exercise is not intended for calibration. In normal exercise, since the movement distance D in the exercise is not acquired, it is impossible to calculate the reference stride using the above equation (10), and it is not meaningful even if NA can be calculated. This is because the reference stride and the reference average acceleration should be acquired in association with each other based on the movement in the same period. However, if only D can be obtained by turning it back, it is possible to perform calibration even in an exercise for the purpose of stride estimation. That is, even if the purpose is not calibration, NA is calculated every time and set as a reference average acceleration candidate. When a reference information acquisition instruction is received and reference distance information D is input, a reference stride is calculated based on D and N, and a reference average acceleration candidate may be adopted as a reference average acceleration. In this way, it becomes possible to perform both stride length estimation and calibration in one exercise.

  In the present embodiment, the processing period for the exercise whose main purpose is calibration is the reference information acquisition period, and the moving distance with high accuracy in the reference information acquisition period is the input distance information. On the other hand, a processing period in an exercise whose main purpose is stride estimation is a signal value acquisition period, and a highly accurate moving distance in the signal value acquisition period is reference distance information. In other words, terms are used according to the purpose of exercise, but there may be little difference in the physical meanings of the reference information acquisition period and signal value acquisition period, and input distance information and reference distance information. .

  Further, the state detection apparatus 100 may include a filter processing unit 120 that performs a band-pass filter process on the acceleration detection value, and a control unit 130 that changes a filter characteristic of the band-pass filter process. And the step detection part 140 detects a step period based on the acceleration detection value after a band pass filter process. The control unit 130 changes the filter characteristics of the bandpass filter process based on the step period detected by the step detection unit 140.

  Thereby, it becomes possible to appropriately filter the acceleration detection value acquired by the acquisition unit 110. Furthermore, it is possible to adaptively change the filter characteristics based on the step period. As shown in FIG. 1, the acceleration detection value has a peak in addition to the frequency corresponding to the step frequency, and these components hinder processing. Therefore, the subsequent processing can be facilitated by performing filter processing that passes the step frequency and does not pass other peaks. However, since the step frequency changes according to the exercise state (specifically, the user's walking / running pitch), it is preferable to change the characteristics of the filter following the change of the exercise state. Note that pass / non-pass of the filter may be determined by a cutoff frequency. In the case of a band pass filter, a pass band having an upper limit value and a lower limit value as cutoff frequencies can be set, and frequencies included in the pass band can be defined as pass and other frequencies can be defined as non-pass.

  Further, the state detection apparatus 100 may include a distance information calculation unit 170 that calculates a distance of travel or walking based on the stride estimated by the stride estimation unit 160 as illustrated in FIG.

  Thereby, it becomes possible to calculate the moving distance of the user based on the estimated stride. For example, if the stride is estimated for each step, the sum of the stride may be obtained. If the step length per step is estimated for each M step due to factors such as the average acceleration being calculated for each M step (M is an integer of 2 or more), the product of the calculated step length and M The movement distance can be obtained by taking

  Further, the state detection device 100 may include a determination unit 150 that determines whether the user's exercise state is a running state or a walking state based on the acceleration detection value. Then, the distance information calculation unit 170 calculates the distance information based on the stride estimated by the stride estimation unit 160 when it is determined as the running state. Further, when it is determined as a walking state, distance information is calculated based on a predetermined stride.

  Here, the determination by the determination unit 150 is not limited to the determination that the vehicle is in either the running state or the walking state, and the determination may be that the third state is neither the traveling state nor the walking state.

  This makes it possible to change the stride used for calculating the distance information between the running state and the walking state. In the running state, the stride is assumed to fluctuate violently because the exercise is more intense than in the walking state. Therefore, in order to cope with such fluctuations, it is preferable to use the estimation result of the stride estimation unit 160 as the stride. On the other hand, since the walking state is a relatively gentle movement, the variation in the stride is small. Therefore, even if the distance information is calculated using a predetermined stride, it is considered that a problem does not easily occur. By doing so, it is not necessary to perform the stride estimation process when it is determined that the user is in the walking state, so that the processing load can be reduced.

  Further, the present embodiment described above may be applied to an electronic apparatus including the state detection device 100 described above.

  Thereby, it is possible to realize an electronic apparatus including the state detection device 100 as illustrated in FIG. Typically, the wristwatch type device described above can be considered as the electronic apparatus. As shown in FIG. 4, the wristwatch type device may include the display unit 40 in addition to the state detection device 100 and the acceleration sensor 10. In FIG. 4, the communication unit 30 is provided in consideration of communication with an external host computer. However, if communication is not performed (or frequency is low), basically all processing is performed in the wristwatch type device. be able to.

  Further, the present embodiment described above includes an acquisition unit 110 that acquires an acceleration detection value from the acceleration sensor 10, an average acceleration calculation unit 162 that calculates an average acceleration for a given period based on the acceleration detection value, and a reference You may come to the program which functions a computer as the reference | standard information acquisition part 164 which acquires an average acceleration and a reference | standard stride, and the stride estimation 160 which estimates a stride. At that time, the stride estimation unit 160 estimates the stride based on the ratio of the reference average acceleration to the average acceleration and the reference stride.

  As a result, the same processing as that of the state detection device 100 described above can be realized by a program. The program is recorded on an information storage medium. Here, as the information recording medium, various recording media readable by the system, such as an optical disk such as a DVD or a CD, a magneto-optical disk, a hard disk (HDD), a memory such as a nonvolatile memory or a RAM, can be assumed. For example, in the system of FIG. 13 (such as an electronic device including the processing unit 70 realized by a CPU, a GPU, or the like), the program is stored in the information storage medium 60 and is read and processed by the processing unit 70. Become. Further, when considering a system (for example, PC) separate from the acceleration sensor 10 worn by the user as a configuration excluding the acceleration sensor 10 from FIG. 13, the program is stored in the information storage medium 60 included in the system. It may be stored. In the case of a PC or the like, since it is generally not assumed that the user wears it, the sensor information is acquired by wireless communication or the like from the acceleration sensor 10 configured separately, and the sensor information is stored in the information storage medium 60. Processing is performed by the processing unit 70 (CPU or the like) based on the stored program.

  In addition, the present embodiment described above includes an acquisition unit 110 that acquires an acceleration detection value from the acceleration sensor 10, an average speed calculation unit that calculates an average speed for a given period based on the acceleration detection value, and a reference average You may apply to the state detection apparatus 100 containing the reference | standard information acquisition part 164 which acquires a speed | rate and a reference | standard stride, and the stride estimation 160 which estimates a stride. The stride estimation unit 160 estimates the stride based on the ratio between the reference average speed and the average speed and the reference stride.

  In addition, the present embodiment described above includes an acquisition unit 110 that acquires an acceleration detection value from the acceleration sensor 10, an average speed calculation unit that calculates an average speed for a given period based on the acceleration detection value, and a reference average The present invention may be applied to a program that causes a computer to function as a reference information acquisition unit 164 that acquires a speed and a reference stride, and a stride estimation 160 that estimates a stride. The stride estimation unit 160 estimates the stride based on the ratio between the reference average speed and the average speed and the reference stride.

  This makes it possible to perform processing based on the average speed, not the average acceleration. Specifically, it corresponds to the above formulas (13) to (16). Since the contents of the other processes are the same as when the average acceleration is used, detailed description thereof is omitted. The same applies to the case where the program is stored in the information storage medium 60 shown in FIG. 13 when applied to the program.

  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 configuration and operation of the state detection device are not limited to those described in this embodiment, and various modifications can be made.

10 acceleration sensor, 20 storage unit, 30 communication unit, 40 display unit, 50 operation unit,
60 information storage medium, 70 processing unit, 100 state detection device, 110 acquisition unit,
120 filter processing unit, 130 control unit, 140 step detection unit,
142 step cycle information detection unit, 144 step count unit, 150 determination unit,
160 stride length estimation unit, 162 average acceleration calculation unit, 164 reference information acquisition unit,
166 Reference average acceleration calculation unit, 168 Reference stride calculation unit, 170 Distance information calculation unit

Claims (16)

An acquisition unit for acquiring an acceleration detection value from the acceleration sensor;
Based on the acceleration detection value, an average acceleration calculation unit that calculates an average acceleration for each given period;
A reference information acquisition unit for acquiring a reference average acceleration and a reference stride;
A stride estimation unit that estimates a stride based on a ratio of the average acceleration to the reference average acceleration and the reference stride;
A state detection device comprising: In claim 1,
Including a step detector,
The reference information acquisition unit
The state detection apparatus that acquires the reference stride based on input distance information and the number of steps detected by the step detection unit in a reference information acquisition period. In claim 2,
The reference information acquisition unit
The state detection apparatus that acquires the reference average acceleration based on the average acceleration acquired in the reference information acquisition period and the number of steps. In claim 2 or 3,
The stride estimation unit
When the reference average acceleration is NA, the reference step length is NS, the coefficient is C, and the average acceleration acquired at a given timing is An, the step length Sn corresponding to the timing at which the average acceleration An is acquired Is obtained by Sn = C × (An / NA) × NS. In any of claims 2 to 4,
The state detection apparatus, wherein the input distance information is user input information or external data. In any of claims 2 to 5,
The reference information acquisition unit
Based on the average acceleration in the signal value acquisition period and the number of steps detected in the signal value acquisition period, a reference average acceleration candidate is obtained,
When a reference information acquisition instruction is given, the reference average acceleration candidate is acquired as the reference average acceleration in association with the reference stride during the signal value acquisition period. In claim 6,
The reference information acquisition unit
In the reference information acquisition instruction, the state detection device is configured to acquire reference distance information of the running or the walking in the signal value acquisition period. In claim 7,
The state detection apparatus, wherein the reference distance information is user input information or external data. In any of claims 2 to 8,
The average acceleration calculation unit
The state detection apparatus, wherein the average acceleration is calculated for each given period set based on a timing at which a step is detected by the step detection unit. In claim 9,
A filter processing unit that performs band-pass filter processing on the acceleration detection value;
A control unit that changes a filter characteristic of the bandpass filter processing in the filter processing unit;
Including
The step detector is
Step period information is detected based on the acceleration detection value after the bandpass filter processing,
The controller is
A state detection apparatus that adaptively changes the filter characteristics of the bandpass filter processing based on the step period information detected by the step detection unit. In any one of Claims 1 thru | or 10.
A state detection apparatus comprising: a distance information calculation unit that calculates distance information of running or walking based on the stride estimated by the stride estimation unit. In claim 11,
A determination unit that determines whether the vehicle is in a running state or a walking state based on the acceleration detection value;
The distance information calculation unit
If the determination unit determines that the vehicle is in the running state, the distance information is calculated based on the stride estimated by the stride estimation unit, and the determination unit determines that the user is in the walking state. In the case, the distance detection device calculates the distance information based on a predetermined stride. An acquisition unit for acquiring an acceleration detection value from the acceleration sensor;
Based on the acceleration detection value, an average speed calculation unit that calculates an average speed for each given period;
A reference information acquisition unit for acquiring a reference average speed and a reference stride;
A stride estimation unit that estimates a stride based on a ratio of the average speed to the reference average speed and the reference stride;
A state detection device comprising:   An electronic apparatus comprising the state detection device according to claim 1. An acquisition unit for acquiring an acceleration detection value from the acceleration sensor;
Based on the acceleration detection value, an average acceleration calculation unit that calculates an average acceleration for each given period;
A reference information acquisition unit for acquiring a reference average acceleration and a reference stride;
As a stride estimation unit that estimates a stride based on the ratio of the average acceleration to the reference average acceleration and the reference stride,
A program characterized by operating a computer. An acquisition unit for acquiring an acceleration detection value from the acceleration sensor;
Based on the acceleration detection value, an average speed calculation unit that calculates an average speed for each given period;
A reference information acquisition unit for acquiring a reference average speed and a reference stride;
As a stride estimation unit that estimates a stride based on the ratio of the average speed to the reference average speed and the reference stride,
A program characterized by operating a computer.

Images