JP5071822B2 - Physical state detection device, detection method thereof, and detection program - Google Patents

Physical state detection device, detection method thereof, and detection program Download PDF

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JP5071822B2
JP5071822B2 JP2010113174A JP2010113174A JP5071822B2 JP 5071822 B2 JP5071822 B2 JP 5071822B2 JP 2010113174 A JP2010113174 A JP 2010113174A JP 2010113174 A JP2010113174 A JP 2010113174A JP 5071822 B2 JP5071822 B2 JP 5071822B2
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acceleration vector
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克典 松岡
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独立行政法人産業技術総合研究所
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  The present invention relates to a body state detection apparatus, a detection method, and a detection program for detecting a walking state or posture of a person in daily life or work using a triaxial acceleration sensor.

  Conventionally, various methods have been proposed in which an acceleration sensor is attached to the body, a change in the gravitational acceleration direction is obtained from a change in the output signal of the acceleration sensor due to a change in the posture of the body, and a body posture is detected. For example, the following Non-Patent Document 1 proposes a method of detecting walking, stair climbing and the like by a combination of an acceleration sensor and an angular velocity sensor.

  Further, in Patent Document 1 below, by measuring the direct current component of the output signal of the acceleration sensor while a person is not operating, the inclination angle of the acceleration sensor (specifically, a pacemaker with a built-in acceleration sensor) is measured. A body motion detecting device capable of obtaining the angle of elevation and the angle of deviation is disclosed.

Japanese Patent Laid-Open No. 11-42220

Koki and Kurata, Personal Positioning Method Based on Walking Motion Analysis Using Inertial Sensors and Wearable Cameras, IEICE Technical Report, PRMU2003-260, pp.25-30, 2004

  However, in the conventional method, accurate measurement requires that the acceleration sensor is accurately attached to the direction of gravitational acceleration when attached to the body, but this is not easy.

  In Patent Document 1, the initial inclination angle of the acceleration sensor can be obtained, but a complicated process of measuring the direct current component of the output signal of the acceleration sensor in a non-operating state is necessary.

  Furthermore, even if the acceleration sensor can be correctly attached, if the attachment direction of the acceleration sensor may change from the initial direction due to a change in the body condition after attachment, the gravitational acceleration direction is set in advance. In the method of setting, there is a problem that the body state cannot be detected correctly.

  SUMMARY OF THE INVENTION An object of the present invention is to solve the above-mentioned problems, and does not depend on the mounting direction of the acceleration sensor, and can detect a body state such as a walking state and a posture inclination with high accuracy, and a detection method thereof. And providing a detection program.

  The object of the present invention is achieved by the following means.

That is, a body state detection device (1) according to the present invention includes a triaxial acceleration sensor worn on the body, and data collection means for collecting acceleration vector data output from the triaxial acceleration sensor at a predetermined sampling interval. And a processing means, wherein the processing means detects the walking state of the body using the acceleration vector data continuously collected, and uses the continuous acceleration vector data within the period of the walking state. Determine the gravitational acceleration vector and body axis, and calculate the absolute value of each acceleration vector, the average value of these absolute values, the standard deviation, and the periodicity with respect to the acceleration vector data collected continuously. When the deviation is within a predetermined range and the periodicity is greater than a predetermined value, the walking state is determined.

  Further, the physical condition detection device (2) according to the present invention is the principal component analysis for the acceleration vector data in the period in which the processing means is determined to be the walking state in the physical condition detection device (1). The first principal component, the second principal component, and the third principal component are used as the body axis.

  Further, in the body state detection device (3) according to the present invention, in the body state detection device (2), the processing unit obtains an average acceleration vector from the acceleration vector data as a target of the principal component analysis, The direction of the first principal component close to the average acceleration vector is determined as a direction directly below the body, and the forward direction of the body is determined according to the time change of the component of the second principal component direction of the acceleration vector data. The direction of the third principal component orthogonal to the right downward direction and the forward direction in the right-handed system is determined as the right lateral direction of the body.

  Further, the body state detection device (4) according to the present invention is the body state detection device (3), wherein the processing means is positive in one direction of the second main component in determining the body forward direction. Assuming that the time component of the second principal component direction of the acceleration vector data is similar to the whole or a part of a sawtooth wave having a slowly decreasing portion, the second principal component When one direction is determined as a forward direction of the body, and the time change of the component in the second principal component direction of the acceleration vector data is similar to all or part of a sawtooth wave having a slowly increasing portion, A direction opposite to the one direction of the second main component is determined as a body advance direction.

  Further, in the physical condition detection device (5) according to the present invention, in the physical condition detection device (3) or (4), the processing means obtains an average acceleration vector of the acceleration vector data, and the average acceleration vector And an angle formed with each of the directly downward direction, the forward direction, and the right lateral direction is obtained as an inclination angle of the body wearing the acceleration sensor.

  The body condition detection method (1) according to the present invention includes a first step of collecting acceleration vector data at a predetermined sampling interval using a three-axis acceleration sensor attached to the body, A second step of detecting a walking state of the body using acceleration vector data; and a third step of determining a gravitational acceleration vector and a body axis using continuous acceleration vector data within a period of the walking state. The second step calculates the absolute value of each acceleration vector, the average value of these absolute values, the standard deviation, and the periodicity with respect to the acceleration vector data collected continuously; And a fifth step of determining the walking state when the standard deviation is within a predetermined range and the periodicity is greater than a predetermined value. It is.

  Further, the body state detection method (2) according to the present invention is based on the acceleration vector data in the period in which the fifth step is determined to be the walking state in the body state detection method (1). Analysis is performed, and the method includes a sixth step in which the first principal component, the second principal component, and the third principal component are the body axes.

In addition, in the body state detection method (3) according to the present invention, in the body state detection method (2), the fifth step obtains an average acceleration vector from the acceleration vector data as a target of the principal component analysis. , A seventh step of determining the direction of the first principal component close to the average acceleration vector as a direction directly below the body, and a time change of the component of the second principal component direction of the acceleration vector data, An eighth step of determining a forward direction; and a ninth step of determining a direction of the third principal component orthogonal to the right-down direction and the forward direction as a right-hand direction of the body. It is said.

  Further, in the body state detection method (4) according to the present invention, in the body state detection method (3), the eighth step assumes that one direction of the second principal component is a positive direction, and the acceleration When the time change of the component in the second principal component direction of the vector data is similar to the whole or a part of the sawtooth wave having a gently decreasing portion, the one direction of the second principal component is set as the body advance direction. And the time change of the component in the second principal component direction of the acceleration vector data is similar to the whole or a part of a sawtooth wave having a slowly increasing portion, the one of the second principal components. It is characterized by the step of determining the direction opposite to the direction as the forward direction of the body.

  In addition, in the body state detection method (5) according to the present invention, in the body state detection method (3) or (4), the third step includes a tenth step of obtaining an average acceleration vector of the acceleration vector data; And an eleventh step of obtaining an average acceleration vector and an angle formed by each of the right-down direction, the forward direction, and the right-side direction to obtain a tilt angle of a body wearing the acceleration sensor. Yes.

  In addition, the body condition detection program (1) according to the present invention uses the three-axis acceleration sensor in a body condition detection apparatus including a three-axis acceleration sensor attached to the body, a data collection unit, and a processing unit. A first function for collecting acceleration vector data at a predetermined sampling interval, a second function for detecting the walking state of the body using the acceleration vector data continuously collected, and within a period of the walking state And a third function for determining a gravitational acceleration vector and a body axis using the continuous acceleration vector data, wherein the second function is the absolute value of each acceleration vector with respect to the continuously collected acceleration vector data. A fourth function for calculating a value, an average value of these absolute values, a standard deviation, and a periodicity, and the standard deviation is within a predetermined range, and the periodicity is a predetermined value When Ri large, is characterized in that it comprises a fifth function for determining that the walking state.

  Further, the body condition detection program (2) according to the present invention is based on the acceleration vector data during the period in which the fifth function is determined to be the walking state in the body condition detection program (1). An analysis is performed, and a sixth function having the first principal component, the second principal component, and the third principal component as the body axis is included.

  Further, in the body condition detection program (3) according to the present invention, in the body condition detection program (4), the fifth function obtains an average acceleration vector from the acceleration vector data that is the target of the principal component analysis. , According to a seventh function for determining the direction of the first principal component close to the average acceleration vector as a direction directly below the body, and a time change of the component of the second principal component direction of the acceleration vector data. And an eighth function for determining a forward direction, and a ninth function for determining the direction of the third principal component orthogonal to the right-down direction and the forward direction as a right-hand direction of the body. It is said.

In the body condition detection program (4) according to the present invention, in the body condition detection program (3), the eighth function assumes that one direction of the second principal component is a positive direction, and the acceleration When the time change of the component in the second principal component direction of the vector data is similar to the whole or a part of the sawtooth wave having a gently decreasing portion, the one direction of the second principal component is set as the body advance direction. And the time change of the component in the second principal component direction of the acceleration vector data is similar to the whole or a part of a sawtooth wave having a slowly increasing portion, the one of the second principal components. It is characterized by the function of determining the direction opposite to the direction as the body's forward direction.

  Further, the body condition detection program (5) according to the present invention is the body function detection program (3) or (4), wherein the third function is a tenth function for obtaining an average acceleration vector of the acceleration vector data. And an eleventh function for determining an angle formed between the average acceleration vector and each of the right-down direction, the forward direction, and the right-side direction to obtain a tilt angle of a body wearing the acceleration sensor. Yes.

  According to the present invention, it is not necessary to make a pre-adjustment such as accurately mounting the triaxial acceleration sensor before calibration or calibrating the mounting direction, and also when the mounting direction of the acceleration sensor changes during the measurement. It is possible to accurately detect a physical state such as a walking state and a posture inclination.

  In particular, the direction of the average acceleration vector calculated from the acceleration data of the period detected as the walking state is used as the direction of the gravitational acceleration as a reference for obtaining the body inclination angle, thereby accurately calculating the body inclination angle. be able to.

  In addition, the principal component analysis is performed on the acceleration data in the walking state, and the positive direction of the body axis is considered by considering the relationship between the first principal component and the average acceleration vector and the temporal change pattern of the acceleration component in the second principal component direction. Can be determined with high accuracy. By using this body axis, the posture can be determined by accurately calculating the tilt angle of the body.

1 is a block diagram showing a schematic configuration of a body state detection device according to an embodiment of the present invention. It is a wave form diagram which shows an example of the acceleration data of 1 axis direction. It is a flowchart which shows the detection process of the highly accurate body posture by the body state detection apparatus which concerns on embodiment of this invention. It is a figure which shows the relationship between the axis | shaft of an acceleration sensor, a body axis, and a gravitational acceleration direction, (a) shows the relationship between the XYZ axis | shaft of an acceleration sensor in a walking state, and a body axis, (b) is the state which bent forward. It is a figure which shows a body inclination angle. It is a figure explaining the method of determining a forward direction from the acceleration component of a 2nd main component direction. It is a figure which shows an example of the result of having applied the detection function of the highly accurate body posture by the body state detection apparatus which concerns on embodiment of this invention.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, embodiments of the invention will be described with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a schematic configuration of a body state detection device according to an embodiment of the present invention. The body state detection apparatus according to the present embodiment samples a triaxial acceleration sensor (hereinafter referred to as an acceleration sensor) 1 attached to a human body and an analog output signal of the acceleration sensor 1 at a predetermined time interval. A data sampling unit 2 that performs D conversion and outputs a digital signal, a recording unit 3 that records a digital signal from the data sampling unit 2, a memory unit 4, and a processing unit 5 that controls these units are provided. For example, when the acceleration sensor 1 is attached to the lower back of a human body and receives an external force, the acceleration sensor 1 is an analog corresponding to the acceleration in each of three orthogonal axes (X axis, Y axis, Z axis) set in advance in the acceleration sensor 1. A signal (such as a voltage) is output from three corresponding output terminals (not shown).

Under the control of the processing unit 5, the data sampling unit 2 samples each analog signal output from the acceleration sensor 1 at a predetermined sampling interval Δt, performs A / D conversion, and converts the digital acceleration data (g x , (g y , g z ) are output in the order of collection. In the following description, unless otherwise specified, the acceleration data means three-dimensional vector data (g x , g y , g z ). The output acceleration data is recorded in the recording unit 3 in time series. In addition to the control of each unit, the processing unit 5 performs acceleration processing recorded in the recording unit 3 as a target, and executes a walking state detection process, which will be described later, using the memory unit 4 as a work area.

  Hereinafter, the function of the body state detection device according to the present embodiment will be specifically described.

  FIG. 2 shows an example of recorded acceleration data. In FIG. 2, the vertical axis represents the uniaxial component of acceleration data, and the horizontal axis represents time. In the following description, the processing performed by the processing unit 5 will be described unless otherwise specified. Further, in the processing at each step, the processing unit 5 appropriately reads acceleration data from the recording unit 3 to the memory unit 4, performs calculation using a predetermined area of the memory unit 4 as a work area, and records the result as appropriate. It will be recorded in part 3.

(Highly accurate body posture detection function)
In the method of using the number of times that the absolute value of acceleration | g | i exceeds the average acceleration value g AV for detecting the walking state, the walking speed may affect the detection accuracy. In addition, the method cannot detect the inclination angle of the body as an inclination angle with respect to each of the front, lower, and side directions of the body, for example, it cannot determine whether the front is all or whether it is inclined sideways. . In order to improve these points and detect the body posture more accurately, the stable walking state is detected, the body axis in this state is obtained, and the body axis and the average acceleration vector obtained by the acceleration sensor are formed. The angle is determined as the body tilt angle. This will be specifically described below.

  FIG. 3 is a flowchart showing a highly accurate body posture detection process by the body state detection apparatus shown in FIG.

In step S31, initialization is performed. Evaluation time width T 1 , shift time width ΔT 1
T 1 ≦ T 1 ), and a predetermined value is set for the sampling interval Δt. Further, “0” is set to the repetition counter k, and “0” is set to all the flags flag (j) (j is an integer value of 0 or more). As will be described later, since the acceleration data to be processed once is determined from all the time-series acceleration data while shifting by the shift time width ΔT 1 along the time axis, the flag flag ( j) is provided. In addition, an inclination angle calculation time T 3 (<T 1 ) and reference values σ still , σ walk , ν walk , σ w0 , σ w1 , ν w0 , and σ shock to be described later are set.

In step S32, acceleration data (g xi , g yi , g zi ) (i = k to k + N 1 −1) during the evaluation time width T 1 is read from the beginning of the acceleration data recorded in time series. Evaluation acceleration data number N 1 for every time width T 1 is calculated by T 1 / Δt.

In step S33, the absolute value | g | i = (g xi 2 + g yi 2 + g zi ) of each acceleration data (g xi , g yi , g zi ) (i = k to k + N 1 −1) read out in step S32. 2 ) Calculate 1/2 , calculate the average value g av and standard deviation σ thereof, and further calculate the periodicity ν of the temporal variation of the absolute value | g | i of the acceleration data. The reason for obtaining the periodicity ν is to detect a stable walking state, and processing described later is performed based on the characteristics of this state.

The periodicity ν of the acceleration data absolute value | g | i that is the time series data of the time interval Δt in the evaluation time width T 1 can be obtained using a known technique. For example, | g | i the Fourier transform, depending on the degree peak broadening of the resulting frequency spectrum, it is possible to determine the periodicity [nu. Further, a frequency distribution of time intervals in which | g | i exceeds the average value g av is obtained, and the ratio of the maximum value of the cumulative frequency in the predetermined time width ΔTc to the total number in the frequency distribution is also defined as the periodicity ν. Good.

In step S34, it is determined whether it is a walking state using the standard deviation (sigma) and periodicity (nu) calculated | required by step S33. Specifically, if σ still ≦ σ ≦ σ walk and ν> ν walk , it is determined that the user is in the walking state, and the process proceeds to step S35. Otherwise, it is determined that the user is not in the walking state, and the process proceeds to step S38. . σ still , σ walk , and ν walk are reference values set in the initial setting in step S31.

In step S35, it is determined whether or not the walking state is stable under conditions stricter than those in step S34. That is, if σ w0 ≦ σ ≦ σ w1 and ν> ν w0 , it is determined that the walking state is stable, and the process proceeds to step S36. Otherwise, it is determined that the walking state is not stable and the process proceeds to step S39. To do. Here, σ stillw0 , σ w1 ≦ σ walk , and ν walkw0 .

In step S36, principal component analysis is performed on the acceleration data (g xi , g yi , g zi ) (i = k to k + N 1 −1) read out in step S32 to obtain a body axis. In a stable walking state, there is a characteristic that the same posture is maintained by the same person with respect to the direction of gravity. Therefore, the first to third principal components obtained by principal component analysis on the acceleration vector in a stable walking state are taken as body axes. That is, the first to third principal components are respectively the vertical direction (gravity acceleration direction), the front-rear direction, and the horizontal direction of the body during walking.

In step S37, from the fluctuation of the acceleration component in the body axis (first to third principal components) direction obtained in step S36, the direction directly below the body, the forward direction (forward direction), and the right lateral direction ((( a) see) is recorded and recorded in the recording unit 3. When the first to third principal components obtained in step S36 are used as body axes, there are two directions in the positive direction of each axis. In other words, the positive and negative directions of the body axis cannot be uniquely determined only by principal component analysis. Therefore, first, the average acceleration vector of the walking state is obtained, and the direction of the first principal component close to the direction of the average acceleration vector is determined as the direction directly below the body. Next, an acceleration component in the second principal component direction is obtained with one direction of the second principal component as a provisional positive direction, and the front-rear direction of the body is determined based on the time change pattern of the obtained acceleration component. Specifically, as shown in FIG. 5, the similarity between two sawtooth waveforms that are symmetrical with respect to the time axis is determined. One of the two sawtooth waves increases slowly after decreasing gently, and then decreases gently again (for example, the waveform indicated as “forward component” in FIG. 5), and the other increases sharply after increasing slowly. After that, it gradually increases again (for example, a waveform indicated as “reverse forward direction component” in FIG. 5). The middle waveform in FIG. 5 is the acceleration component in the second principal component direction, which is a waveform similar to the “forward component”, so that the positive direction of the second principal component is the forward direction (forward direction) of the body. decide. On the other hand, when the acceleration component in the two principal components direction is similar to the sawtooth wave in the reverse advance direction component, the negative direction of the second principal component is determined as the forward direction (forward direction) of the body. Finally, the direction of the third principal component close to the direction orthogonal to the determined right-down direction and the forward direction in the right hand system is determined as the right lateral direction of the body. Note that the similarity may be calculated using a known matching technique. For example, the degree of similarity may be determined by obtaining a correlation between the waveform of the acceleration component in the second principal component direction and a sawtooth waveform as a determination reference. Also, as a method of determining the similarity to the sawtooth wave, paying attention to the difference in feature quantity (for example, differential coefficient) of two sawtooth waveforms symmetric with respect to the time axis, the same feature regarding the waveform of the acceleration component in the second principal component direction A quantity (differential coefficient) may be calculated and used for determination. Also, instead of the similarity with the whole sawtooth wave (including the feature amount), a part of the sawtooth wave, for example, a rapidly changing part of acceleration due to kicking of the foot or a part where the acceleration gradually decreases The similarity (including the feature amount) may be used as a criterion for determination.

In step S38, the body state other than the walking state is determined using the standard deviation σ and the periodicity ν calculated in step S33. Specifically, σ walk <σ ≦ σ shock and ν> ν walk
If it is "running state", if σ <σ still , "still state", if σ> σ shock , "impact state" such as falling, and if neither of these states nor walking state Is determined as “other state”.

In step S39, when the determination result in physical condition in step S38 is other than "impact state", the acceleration vector of the average calculated for each tilt angle calculation time T 3, reads the information of the body axis from the recording unit 3 The angle (body inclination angle) formed by the average acceleration vector and the body axis is obtained. That is, as shown in FIG. 4B, three angles θ, φ, and γ that the average acceleration vector forms with each body axis (directly downward direction, forward direction, and right lateral direction) are obtained. Here, posture determination can also be performed from the obtained θ. For example, in step S31, the reference values θ 0 , θ 1 , and θ 2 are initially set. If θ 0 <θ ≦ θ 1 , “inclination is small”, and if θ 1 <θ ≦ θ 2 is “inclining” If θ ≧ θ 2 , it is determined that “the inclination is large”.

In step S40, it is determined whether or not the acceleration data to be processed remains N 1 (corresponding to the evaluation time width T 1 ) or more, and the process proceeds to step S41 until Δk (Δk = ΔT 1 / Δt) is added as a new counter k, and the above steps S32 to S39 are repeated.

  As described above, the body axis can be accurately determined from the acceleration data in the stable walking state, and then the body inclination angle can be accurately determined as the angle formed by the determined body axis and the average acceleration vector. it can.

  Depending on the acceleration data to be processed, the process in step S39 may be performed without performing the processes in steps S36 and S37. In that case, a meaningful body tilt angle is not calculated because the body axis has not been determined. Therefore, a flag indicating whether or not the body axis has been calculated is provided, the state of the flag is determined in step S39, and if the body axis has not been calculated, the processing in step S39 described above may not be executed. . Alternatively, in the initial setting in step S31, an initial value in the body axis direction may be set. Furthermore, if the calculation result of the body tilt angle during a period when the body axis is not determined is excluded, the initial value in the body axis direction may not be set.

FIG. 6 shows a result of an experiment in which this function is applied to measured acceleration data. Four similar types of acceleration sensors are mounted on the front, back, left, and right of the human body without special positioning, walking, sitting on a chair, bending in the front direction, looking from the right, looking left A series of operations for peeping through were performed, acceleration data output from each acceleration sensor was recorded, and a series of processing shown in FIG. 3 was executed on this data. Evaluation time width T 1 = 5 (seconds), tilt angle calculation time T 3 = 1 (seconds). FIG. 6 shows data related to acceleration sensors attached to the front side, the left side, the rear side, and the right side from the top. The signal waveform of each stage shown as “(a) 3-axis acceleration information” on the left side of FIG. 6 represents the XYZ-axis acceleration components acquired from the acceleration sensor, and is shown as “(b) body inclination angle” on the right side. The signal waveforms represent body inclination angles θ, φ, γ (actually, θ, φ-90, γ-90) calculated using the determined body axis. A part of the body inclination angle is added numerically. Comparing the data of each stage of body tilt angle, this function can obtain almost equal body tilt angle regardless of the mounting position and mounting direction of the acceleration sensor on the body, and seated and bent into the front It can be seen that the peep from the right and the peep from the left can be identified.

  In the above description, the body state detection apparatus having the configuration shown in FIG. 1 has been described. However, the present invention is not limited to this, and various changes and expansions can be made.

  In addition, all the components shown in FIG. 1 may be incorporated into one unit, and the unit may be attached to the body. The acceleration sensor and the data collection unit may be incorporated into one unit, and only that unit is attached to the body. May be. In the former case, the processing result may be wirelessly transmitted to another processing apparatus by wireless communication, for example. In the latter case, the digital data output from the data collection unit may be wirelessly transmitted to the recording unit by wireless communication, for example.

  Further, the processing shown in FIG. 3 can be executed with various changes such as changing the order of the steps. For example, in FIG. 3, the walking state detection process in step S34 may be included in step S38. In that case, the high periodicity detection process of step S35 is first performed.

  Further, the direction of the body axis is not limited to the downward direction, the forward direction, and the right lateral direction, and may be the opposite direction or a left-handed axis.

In the above-described walking state detection function, the flag flag (j) at time t + T 1 is determined using acceleration data within the evaluation time width T 1 (time t to t + T 1 ). However, the present invention is not limited to this. , Flag flag (j) at an arbitrary time t + τ in the section from t to t + T 1 may be determined. Here, τ <T 1 . In that case, when the shift time width ΔT 1 is taken into consideration, the determined flag flag (j) is maintained during the time t + τ to t + τ + ΔT 1 . For example, τ = T 1/2 .

  Various methods can be used to detect periodicity. For example, with respect to acceleration data for each predetermined period, absolute value frequency analysis may be performed by Fourier transform or the like, and a walking state or a stable walking state may be determined based on a ratio of frequency components included. Moreover, you may perform a frequency analysis for every component instead of the absolute value of acceleration data.

  In the above-described high-accuracy body posture detection function, the case of processing acceleration data recorded in advance in the recording unit has been described. However, the processing may be performed in real time in parallel with data collection. In that case, for example, the process of step S31 of FIG. 9 may be a process of collecting a predetermined number of acceleration data.

1 3-axis acceleration sensor 2 Data collection unit 3 Recording unit 4 Memory unit 5 Processing unit

Claims (15)

  1. A three-axis acceleration sensor worn on the body;
    Data collection means for collecting acceleration vector data output from the three-axis acceleration sensor at a predetermined sampling interval;
    Processing means,
    The processing means is
    Using the acceleration vector data collected continuously, detecting the walking state of the body,
    Determining a gravitational acceleration vector and a body axis using continuous acceleration vector data within a period detected as the walking state;
    For the acceleration vector data collected continuously , calculate the absolute value of each acceleration vector , and further calculate the average value, standard deviation and periodicity of these absolute values,
    The body state detection device, wherein the walking state is determined when the standard deviation is within a predetermined range and the periodicity is larger than a predetermined value.
  2. The processing means is
    2. The principal component analysis is performed on the acceleration vector data for the period determined to be the walking state, and the first principal component, the second principal component, and the third principal component are used as the body axis. The body condition detection apparatus as described in 2.
  3. The processing means is
    An average acceleration vector is obtained from the acceleration vector data as the target of the principal component analysis,
    Determining the direction of the first principal component close to the average acceleration vector as a direction directly below the body;
    According to the time change of the component of the second principal component direction of the acceleration vector data, determine the body forward direction,
    The body state detection device according to claim 2, wherein a direction of the third principal component orthogonal to the right-down direction and the forward direction in a right-handed system is determined as a right lateral direction of the body.
  4. In the determination of the body advance direction, the processing means,
    Assuming that one direction of the second principal component is a positive direction, the time variation of the component of the second principal component direction of the acceleration vector data is similar to all or part of a sawtooth wave having a gradually decreasing portion. In the case, the one direction of the second principal component is determined as a body forward direction, and a sawtooth wave having a portion in which the time change of the component in the second principal component direction of the acceleration vector data gradually increases. 4. The body state detection device according to claim 3, wherein a direction opposite to the one direction of the second principal component is determined as a body advance direction when the whole or part is similar.
  5. The processing means is
    Obtaining an average acceleration vector of the acceleration vector data;
    4. An angle formed by the average acceleration vector and each of the directly downward direction, the forward direction, and the right lateral direction is obtained as an inclination angle of a body wearing the three-axis acceleration sensor. 4. The body state detection device according to 4.
  6. A first step of collecting acceleration vector data at a predetermined sampling interval using a three-axis acceleration sensor mounted on the body;
    A second step of detecting the walking state of the body using the acceleration vector data collected continuously;
    A third step of determining a gravitational acceleration vector and a body axis using continuous acceleration vector data within a period detected as the walking state,
    The second step includes
    A fourth step of calculating an absolute value of each acceleration vector with respect to the acceleration vector data collected continuously , and further calculating an average value, a standard deviation and a periodicity of these absolute values;
    And a fifth step of determining the walking state when the standard deviation is within a predetermined range and the periodicity is greater than a predetermined value.
  7. The fifth step includes
    A sixth step of performing a principal component analysis on the acceleration vector data for the period determined to be the walking state and using the first principal component, the second principal component, and the third principal component as the body axis. The body state detection method according to claim 6.
  8. The fifth step includes
    A seventh step of determining an average acceleration vector from the acceleration vector data to be subjected to the principal component analysis, and determining a direction of the first principal component close to the average acceleration vector as a direction directly below the body;
    An eighth step of determining a forward direction of the body in accordance with a time change of the component of the second principal component direction of the acceleration vector data;
    The body state according to claim 7, further comprising a ninth step of determining the direction of the third principal component orthogonal to the right downward direction and the forward direction in the right hand system as a right lateral direction of the body. Detection method.
  9. The eighth step includes
    Assuming that one direction of the second principal component is a positive direction, the time variation of the component of the second principal component direction of the acceleration vector data is similar to all or part of a sawtooth wave having a gradually decreasing portion. In the case, the one direction of the second principal component is determined as a body forward direction, and a sawtooth wave having a portion in which the time change of the component in the second principal component direction of the acceleration vector data gradually increases. 9. The body condition detection method according to claim 8, wherein when the whole or part of the body is similar, the direction opposite to the one direction of the second principal component is determined as a body advance direction. .
  10. The third step includes
    A tenth step of obtaining an average acceleration vector of the acceleration vector data;
    An eleventh step including obtaining an average acceleration vector and an angle formed by each of the right-down direction, the forward direction, and the right-side direction to obtain a tilt angle of a body wearing the three-axis acceleration sensor. The body condition detection method according to claim 8 or 9.
  11. A body state detection device comprising a three-axis acceleration sensor attached to the body, data collection means, and processing means,
    A first function for collecting acceleration vector data at a predetermined sampling interval using the three-axis acceleration sensor;
    A second function for detecting the walking state of the body using the acceleration vector data collected continuously;
    A third function of determining a gravitational acceleration vector and a body axis using continuous acceleration vector data within a period detected as the walking state;
    The second function is
    A fourth function for calculating an absolute value of each acceleration vector with respect to the acceleration vector data collected continuously , and further calculating an average value, standard deviation and periodicity of these absolute values;
    A body condition detection program comprising: a fifth function for determining the walking state when the standard deviation is within a predetermined range and the periodicity is greater than a predetermined value.
  12. The fifth function is
    It includes a sixth function that performs principal component analysis on the acceleration vector data in the period determined to be the walking state and uses the first principal component, the second principal component, and the third principal component as the body axis. The body condition detection program according to claim 11.
  13. The fifth function is
    A seventh function for obtaining an average acceleration vector from the acceleration vector data to be subjected to the principal component analysis, and determining a direction of the first principal component close to the average acceleration vector as a direction directly below the body;
    An eighth function for determining a forward direction of the body according to a time change of the component of the second principal component direction of the acceleration vector data;
    The physical state according to claim 12, further comprising a ninth function for determining the direction of the third principal component orthogonal to the right downward direction and the forward direction in the right-handed system as the right lateral direction of the body. Detection program.
  14. The eighth function is
    Assuming that one direction of the second principal component is a positive direction, the time variation of the component of the second principal component direction of the acceleration vector data is similar to all or part of a sawtooth wave having a gradually decreasing portion. In the case, the one direction of the second principal component is determined as a body forward direction, and a sawtooth wave having a portion in which the time change of the component in the second principal component direction of the acceleration vector data gradually increases. The body condition detection program according to claim 13, which has a function of determining a direction opposite to the one direction of the second principal component as a body advance direction when similar to the whole or a part. .
  15. The third function is
    A tenth function for obtaining an average acceleration vector of the acceleration vector data;
    And an eleventh function for determining an angle formed by each of the average acceleration vector and each of the right-down direction, the forward direction, and the right-side direction, and setting the inclination angle of the body wearing the three-axis acceleration sensor. The body condition detection program according to claim 13 or 14.
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