JP4504071B2 - Body motion analysis device - Google Patents

Description

  The present invention relates to a body motion analysis device that performs analysis on posture and motion based on physical features extracted during human exercise, and more particularly, a body motion analysis device used for a walking function test in a rehabilitation system or a sports training system, etc. About.

  In the background of the arrival of an aging society in recent years, devices and treatment methods for restoring lower limb functions of elderly people and patients with lower limb diseases have attracted attention. In particular, quantitatively grasping the degree of recovery (or deterioration) of lower limb function in artificial joint patients, osteoarthritis patients, and the like has become one of the important issues. Have been proposed (see, for example, Patent Documents 1 to 3).

  The “body feature point detection device and body motion analysis device” of Patent Document 1 performs motion analysis based on motion characteristics of each body part collected by photographing body motion. In the “motion analysis apparatus” of Patent Document 2, the magnetism of the magnetized portion formed on the magnetic recording medium is detected by a magnetic sensor linked to the moving body to quantitatively measure the momentum. Furthermore, in “Kinematic analysis method and apparatus thereof” in Patent Document 3, a moving object is photographed with a bright mark on a part of the body, and the kinematic analysis is performed based on the locus of the mark.

  Moreover, in general, a fall accident that causes bedridden and is a concern for elderly people is basically caused by a decrease in posture maintenance ability. And this fall of posture maintenance ability appears notably at the time of walking. For example, when posture retention ability declines, elderly people have reduced walking speed and shortened stride, and further compensated for ensuring stability by extending the distance between the left and right sides of both feet (hereinafter referred to as stance). Take action.

Therefore, it is necessary to measure the stance during walking, but a general technique for analyzing the motion of the human body is a center of gravity shake meter. A feature of this technique is that a load detection plate for detecting the load of the subject is installed on a horizontal floor, and the subject moves on the load detection plate to perform motion analysis of the center of gravity (see, for example, Patent Document 4). ).
Japanese Patent Laid-Open No. 10-111940 Japanese Patent Laid-Open No. 5-180861 Japanese Patent Laid-Open No. 5-274434 Japanese Patent No. 2760472

  However, in the technique using the image analysis methods of Patent Documents 1 to 3 described above, the amount of data to be handled is enormous and redundant. There is a problem that there are very few opportunities to be utilized in the field of restricted rehabilitation and sports training.

  In the case of the technique disclosed in Patent Document 4, measurement of the movement (trajectory) of the human body must be carried out by the subject on the load detection plate. The area in which the exercise is performed, the type of movement, the posture, and the like are determined. Since it is necessary to limit, there is a problem that it is troublesome for a subject and a measurer (for example, a medical staff or a caregiver) and cannot measure the walking state.

The present invention has been made in view of the above problems, while relaxing the restriction of the time of measurement, provides a motion analysis equipment capable of quantitatively analyzed with respect to a short time and at low cost human posture and movement For the purpose.

In order to achieve the above object, a body motion analysis apparatus according to the present invention is a body motion analysis apparatus for analyzing a person's walking function, and includes accelerations in the front-rear direction and left-and-right direction that accompany a person's motion. Acceleration detecting means for detecting at least one of the acceleration and the acceleration in the vertical direction over time, and a frequency analysis for generating a frequency spectrum based on the detected temporal change in the longitudinal acceleration. And a frequency specifying unit for specifying the frequency of the maximum power from the generated frequency spectrum, and a logarithmic value calculating unit for calculating a common logarithm value from the maximum power of the specified frequency spectrum. Walking function amount calculation that calculates the stride during walking by applying the calculated common logarithmic value to the acceleration analysis means and the approximate expression obtained in advance And means.

Here, the body motion analysis device according to the present invention is a body motion analysis device for analyzing a person's walking function, and includes a longitudinal acceleration, a lateral acceleration, and a vertical motion that occur in association with a human motion. An acceleration detector that detects at least one of the accelerations over time; a frequency analyzer that generates a frequency spectrum based on the detected temporal change in the lateral acceleration; In addition, the frequency corresponding to the maximum value is specified from the frequency spectrum, the frequency specifying unit for specifying the lowest frequency excluding 0 Hz from the frequency spectrum, and the common logarithm value from the peak value of the specified frequency spectrum. By applying the calculated common logarithmic value to an acceleration analysis means including a logarithmic value calculating unit to calculate and an approximate expression obtained in advance, Kicking may be configured to include a walking function calculating means for calculating a stance.

The body motion analysis apparatus according to the present invention is a body motion analysis apparatus for analyzing a human walking function, and includes longitudinal acceleration, lateral acceleration, and vertical acceleration generated by a human motion. Acceleration detecting means for detecting at least one acceleration over time, a frequency analysis unit for generating a frequency spectrum based on the detected temporal change of the acceleration, and the generated frequency spectrum Detected using a frequency specifying unit that specifies a frequency corresponding to the maximum value from among, a period calculating unit that calculates an integration period using the specified frequency, and the detected lateral acceleration Acceleration analysis means comprising a leg specifying unit that specifies which leg on the left and right is caused by the longitudinal acceleration, and the specified integration period is specified. A speed calculator that calculates the speed of the left leg and the right leg by integrating acceleration in the front-rear direction related to the leg, and a speed ratio calculator that calculates the ratio of the speed of the left and right legs based on the calculated speed And a walking function amount calculating means.

The body motion analysis apparatus according to the present invention is a body motion analysis apparatus for analyzing a human walking function, and includes longitudinal acceleration, lateral acceleration, and vertical acceleration generated by a human motion. An acceleration detecting means for detecting at least one acceleration over time, a spectrum generating section for generating a frequency spectrum from the detected curve representing the acceleration in the front-rear direction, and A maximum spectrum specifying unit that specifies the maximum spectral component from among the above, a logarithmic value calculating unit that calculates a common logarithm value from the peak value of the specified maximum spectral component, and an approximate expression obtained in advance as the calculation A stride calculation unit that calculates a stride by applying the common logarithm value, and a walking period is calculated based on the detected acceleration in the left-right direction. An acceleration analyzing unit and a walking period calculating unit for, on the basis of the walking cycle and extracted the stride length, and may be configured to include a walking function calculating means for calculating a walking speed.

The body motion analysis apparatus according to the present invention is a body motion analysis apparatus for analyzing a human walking function, and includes longitudinal acceleration, lateral acceleration, and vertical acceleration generated by a human motion. An acceleration detecting means for detecting at least one acceleration over time, a zero-cross point specifying unit for specifying a zero-cross point in a curve representing the detected lateral acceleration, and the specified at least A walking cycle calculation unit that calculates a walking cycle from two zero cross points, a spectrum generation unit that generates a frequency spectrum from the detected curve representing acceleration in the front-rear direction, and a maximum spectrum among the generated frequency spectra A common logarithmic value from the peak value of the specified maximum spectrum component and the maximum spectrum specifying part for specifying the component. A calculated logarithmic value calculating unit; a stride calculating unit that calculates a stride by applying the calculated common logarithmic value to an approximate expression obtained in advance; and walking based on the detected lateral acceleration A structure provided with the acceleration analysis means provided with the walking period calculation part which calculates a period, and the walking function-amount calculation means which calculates walking speed based on the extracted said stride and the said walking period may be sufficient.

According to the onset bright, measures acceleration of the longitudinal acceleration or lateral direction during walking by the acceleration sensor of the at least one axis, so quantitatively calculating the stride and walking speed out or the like based on the acceleration, artificial It is possible to quantitatively indicate the degree of recovery of motor function in joint patients and patients with lower limb diseases such as osteoarthritis in a short time and at low cost, and in the field of rehabilitation and sports training with restrictions on medical treatment time, labor, cost, etc. Is expected to be used in

  In addition, by presenting the current state of physical function such as walking of the subject to the subject, it becomes possible to share the problem awareness regarding the recovery situation between the medical staff and the subject, and to support the function recovery training more effectively Is possible.

Further, according to this onset bright, on little time limit measurement, it is possible to analyze a short time and inexpensively when walking stance.
Furthermore, according to this onset bright, on little time limit measurement, can be a short time and inexpensively detect the left-right difference of the feet in body movement, conveniently quantify the degree of functional recovery and deterioration It becomes.

Hereinafter, embodiments according to the present invention will be described in detail with reference to the drawings. In the following embodiments, the present invention will be described with reference to the drawings, but the present invention is not intended to be limited to these.
(Embodiment 1)
FIG. 1 is a schematic diagram of a body movement analysis system 100 in the present embodiment. The body motion analysis system 100 is a system that calculates a stride, a walking speed, and the like based on acceleration data acquired from a walking subject 1 and includes an acceleration detection device 10 and a body motion analysis device 20.

  The acceleration detection device 10 measures acceleration generated by the subject 1 walking with a built-in acceleration sensor, and the data is wireless (for example, a communication method based on Bluetooth (registered trademark of “The Bluetooth SIG Inc.”)). ) Is transmitted to the body motion analysis device 20 and is used by being fixed to a part of the body of the subject 1 (for example, a patient with lower limb dysfunction). In the following, it is a case where the acceleration detection device 10 is mounted on the right waist of the subject 1, and the longitudinal or lateral acceleration generated by the walking of the subject 1 is measured, and the walking speed is determined based on the measured acceleration. An example of calculation will be described.

  The body motion analysis device 20 has a function of a general personal computer, receives acceleration data transmitted from the acceleration detection device 10 by a communication method or the like according to the bluetooth, and based on the acceleration data, It has a function to calculate the stride and walking speed.

  FIG. 2 is a diagram showing the relationship between the mounting position of the acceleration detection device according to the present invention and the coordinate axes of the acceleration sensor. In addition, the relationship between the mounting position of the acceleration detection apparatus described below and the coordinate axis of the acceleration sensor is not limited to the present embodiment, and is common to the following second to fourth embodiments. As shown in FIG. 2, the acceleration detection device 10 is fixed to the right waist of the subject 1 by, for example, a belt-like wearing tool 5. Further, in the present invention, when measuring the acceleration accompanying walking of the subject 1, the left-right direction is the X-axis direction (the right direction is the “positive direction”), and the front-rear direction is the Y-axis direction (the front direction is “positive”. Direction ”).

  FIG. 3 is a block diagram showing functional configurations of the acceleration detection device 10 and the body motion analysis device 20. As shown in FIG. 3, the acceleration detection device 10 includes an acceleration information detection unit 11 and a wireless communication control unit 12. On the other hand, the body motion analysis apparatus 20 includes a wireless communication control unit 21, a walking speed detection unit 22, a display unit 23, and a storage unit 24. First, the acceleration detection device 10 will be described.

The acceleration information detection unit 11 measures the acceleration in the front-rear direction (or the left-right direction) generated by the activity of the subject 1 using an IC-type acceleration sensor (for example, one that can measure biaxial acceleration). Information representing this acceleration (hereinafter referred to as “acceleration data”) is transmitted to the wireless communication control unit 12. More specifically, for example, for a predetermined time (for example, 10 seconds), the longitudinal acceleration in walking of the subject 1 is monitored, and the maximum acceleration is ± 2 G (1 G = 9.8 [m / s ² ]). A corresponding voltage change is sampled at a sampling frequency of 125 Hz and a quantization bit number of 16 bits to perform A / D conversion, and the A / D converted acceleration data is transmitted to the wireless communication control unit 12.

  The wireless communication control unit 12 is, for example, a CPU including a ROM, a RAM, and the like that stores a control program and the like, and controls the entire acceleration detection device 10. Furthermore, the wireless communication control unit 12 transmits the acceleration data measured by the acceleration information detection unit 11 to the body motion analysis device 20 by, for example, the communication method based on the bluetooth.

Next, the body motion analysis device 20 will be described.
Similar to the wireless communication control unit 12 in the acceleration detection device 10, the wireless communication control unit 21 is a CPU including a ROM, a RAM, and the like that store a control program and the like, and controls the entire body motion analysis device 20. Further, the wireless communication control unit 21 receives the acceleration data transmitted from the acceleration detection device 10 by, for example, the communication method based on the bluetooth, and transmits it to the walking speed detection unit 22.

The walking speed detection unit 22 calculates a stride and a walking cycle based on the received acceleration data, and calculates a walking speed from the stride and the walking cycle.
The display unit 23 is a display device including a liquid crystal panel, for example, and information on the posture and movement of the subject 1 (for example, a measurement value regarding walking speed and a state in which the function has been recovered) and advice according to an instruction from the wireless communication control unit 21. Display information etc. for

  The storage unit 24 is a storage device made of, for example, a RAM or a fixed disk, and stores information representing acceleration received from the acceleration detection device 10 and information representing walking speed calculated by the walking speed detection unit 22. (Hereinafter referred to as “walking speed data”).

Here, a method for calculating the walking speed from the acceleration data will be described in detail with reference to FIGS.
FIG. 4 is an example showing the correspondence between leg movement and acceleration change in the walking function test of the subject as time elapses. A curve 41 in FIG. 4 is a diagram illustrating a change in acceleration in the left-right direction when the subject 1 performs the walking function test. On the other hand, a curve 42 is a diagram showing a change in acceleration in the front-rear direction when the walking function test is performed. As described in FIG. 2 above, “rightward” is defined as the positive direction for the acceleration in the left-right direction, and “forward” is defined as the positive direction for the acceleration in the front-rear direction. In this embodiment, the definition of walking speed in the following equation (1) is used.

Walking speed = (walking cycle) x (step length) (1)
Here, the “walking cycle” in the above equation (1) is the average cycle (for example, T (i) −T (i−1) [sec) of the curve 42 in FIG. ] Is the average of 10 cycles). In this case, in the curve 42, two adjacent points that are zero-crossed in the process of changing from a negative value to a positive value are used.

  Further, with respect to the “step length” in the above equation (1), for example, a power spectrum is obtained by Fourier transforming the acceleration / deceleration curve 42 measured in the above 10 cycles, and the peak value (this is expressed as “ The common logarithm of “frequency power” is calculated.

  FIG. 5 is a diagram schematically showing a frequency spectrum related to the curve 42. In FIG. The example shown in FIG. 5 shows an example (curve 501 to curve 504) in which the frequency power is maximum when the frequency is “1” (that is, the time required for one step is 1 second). Common logarithm values are shown. Therefore, in the case of the curve 504 in FIG. 5, there are 8 steps per second.

  FIG. 6 is an example showing the relationship between the common logarithm of frequency power and the stride calculated experimentally. As shown in FIG. 6, the common logarithm of the maximum frequency power and the stride are in a proportional relationship. The following equation (2) is derived based on the curve 601 in FIG. 6 (where the unit of stride is [cm]).

Step length = 143 × (common logarithm of maximum frequency power) −271 (2)
In the above relationship, one curve can be defined for each individual (thus, when there are three subjects, three curves can be defined as curves 601 to 603).

As apparent from the above description, the “walking speed” can be calculated by substituting the “step length” calculated by the above equation (2) into the above equation (1).
Next, the operation of the body motion analysis apparatus 20 configured as described above will be described.
FIG. 7 is a flowchart showing a process flow of the body motion analysis apparatus 20.

  First, the wireless communication control unit 21 receives acceleration data transmitted from the acceleration detection device 10 (S701: Yes), and calculates a walking cycle based on the acceleration data (S702). Next, when the received acceleration data is in the left-right direction (S703: Yes), the wireless communication control unit 21 doubles the calculated walking cycle value (S704). Further, the wireless communication control unit 21 estimates the stride based on the received acceleration data (S705), and calculates the walking speed from the walking cycle and the stride (S706).

Here, an effective application example of the body motion analysis system 100 will be described.
FIG. 8 is a display example when the latest measured value of the stride or walking speed is compared with the previous measured value on the display unit 23.

  Furthermore, FIG. 9 is an example displaying changes in physical motor functions related to the subject 1, and is a graph showing changes in walking speed during postoperative rehabilitation recovery for patients undergoing hip replacement surgery. In the example of FIG. 9, the first measurement is started from the fifth day after the operation, and the subsequent walking speed change rate when the first measurement value is 100 is associated with the elapsed days after the operation. FIG. As can be seen from the example of FIG. 9, the display unit 23 also has a totaling function every 10 days.

  As described above, by using the body motion analysis system 100 according to the present embodiment, the stride based on the acceleration measured by at least one axis (front-rear direction, left-right direction, etc.) acceleration sensor attached to the subject, Since the walking cycle and walking speed can be calculated, body motion analysis can be realized in a short time and at low cost in a rehabilitation system or a sports training system.

  In the first embodiment, “front” is defined as a positive direction in the longitudinal acceleration and “right” is defined as a positive direction in the lateral acceleration. However, the present invention is not limited to this. Alternatively, the sign of each acceleration value may be defined by other definitions. Moreover, in the said embodiment, although the Example which shows required information on the display part 23 was shown, it is not limited to this, For example, it notifies by audio | voice or stimulation by vibration etc. Notification may be made by flashing light.

  Further, in the above embodiment, as shown in FIG. 4, it is configured to detect the longitudinal acceleration, and the walking cycle, step length and walking speed are calculated based on the detected acceleration, but based on the lateral acceleration. Thus, the walking cycle may be obtained, and the stride may be calculated from the longitudinal acceleration. However, it should be noted that the walking cycle in that case is “½” of the walking cycle calculated based on the acceleration in the front-rear direction.

  In the above-described embodiment, an example in which acceleration data is transmitted from the acceleration detection device 10 to the body motion analysis device 20 using short-distance wireless communication has been described. However, the acceleration detection device is included in one device. 10 and the body motion analysis device 20 may be configured to have all the functions.

  Furthermore, in the above-described embodiment, an example in which acceleration is measured during walking by the subject has been described. However, the present invention is not limited to acceleration due to walking, and the subject is allowed to perform other exercises having periodicity and the acceleration. May be used to analyze the motor function of the subject.

(Embodiment 2)
In the first embodiment, the body motion analysis system that calculates the stride, the walking speed, and the like based on the acceleration data acquired from the walking subject 1 has been described. However, in the present embodiment, the acquired acceleration data is also used. A body motion analysis system for calculating a stance (left / right leg opening) during walking will be described.

  FIG. 10 is a block diagram illustrating functional configurations of the acceleration detection device 10 and the body motion analysis device 30 in the body motion analysis system 200 according to the present embodiment. In the following description, the same functional configuration as that of body motion analysis system 100 in the first embodiment is denoted by the same reference numeral, and the description thereof is omitted.

  The acceleration detection device 10 measures the acceleration in at least one direction among the front-rear direction, the left-right direction, and the up-down (vertical) direction with respect to the subject 1 and wirelessly controls a signal corresponding to the acceleration (hereinafter referred to as acceleration data). To the unit 12.

  The body motion analysis device 30 is a device that calculates a stance during walking based on measured acceleration data, and includes a wireless communication control unit 21, a motion analysis unit 31, a display unit 23, and a storage unit 24.

  The motion analysis unit 31 is a department having a function corresponding to the walking speed detection unit 22 in the first embodiment, and performs a waveform analysis on the acceleration data received from the wireless communication control unit 21 at a predetermined time interval. It has.

  FIG. 11 is a block diagram illustrating a functional configuration of the motion analysis unit 31. As shown in FIG. 11, the motion analysis unit 31 includes a frequency analysis unit 32, a maximum value detection unit 33, a maximum value frequency detection unit 34, a minimum frequency detection unit 35, an array storage unit 36, and an evaluation unit 37.

  The frequency analysis unit 32 performs frequency analysis on the acceleration data received from the wireless communication control unit 21. The local maximum detector 33 detects the local maximum value of the power from the power spectrum input from the frequency analyzer 32. The local maximum frequency detector 34 detects a frequency corresponding to the local maximum detected by the local maximum detector 33. The lowest frequency detector 35 detects the lowest frequency excluding 0 Hz from the frequencies extracted by the local maximum frequency detector 34. The array storage unit 36 stores an array including the lowest frequency, the maximum value corresponding to the lowest frequency, and the measurement date and time. The evaluation unit 37 reads out data at the designated date and time from the data stored in the array storage unit 36 and outputs the data to the wireless communication control unit 21.

Here, the function of the motion analysis unit 31 will be described in detail using acceleration data in the horizontal direction.
FIG. 12 is an example of time-series data of acceleration in the left-right direction during walking in the walking test performed on the subject 1. In FIG. 12, the horizontal axis represents time [sec], and the vertical axis represents acceleration. In the case of FIG. 12, the acceleration data is collected at a sampling rate of 125 Hz for 10 seconds of walking.

  First, the frequency analysis unit 32 performs frequency analysis on the acceleration data received via the wireless communication control unit 21 and generates a power spectrum thereof. Next, the maximum value detection unit 33 specifies one or more envelopes with respect to the power spectrum generated from the acceleration data, and detects a maximum value for each specified envelope.

Subsequently, the maximum value frequency detection unit 34 detects the frequency of the waveform having the detected maximum value.
FIG. 13 is a diagram illustrating an example of a power spectrum generated in the frequency analysis unit 32. In FIG. 13, the horizontal axis represents frequency [Hz] and the vertical axis represents power. A to F in FIG. 13 indicate spectra that are detected by the maximum value detection unit 33 and indicate respective local maximum values in a plurality of convex portions represented by envelopes, and a to f are local maximum values. The frequency corresponding to each maximum value specified by the frequency detector 34 is shown.

  Next, the lowest frequency detection unit 35 extracts the lowest frequency excluding 0 Hz from the frequencies a to f. In the example of FIG. 13, it corresponds to a. Thereafter, the array storage unit 36 associates the lowest frequency specified as described above and the maximum value corresponding to the lowest frequency (corresponding to A in FIG. 13) with the date on which they are measured. And save it as sequence data.

  Subsequently, the evaluation unit 37 reads the sequence data accumulated in the sequence storage unit 36 in accordance with the instruction received from the subject 1 or its caregiver. Then, data for displaying the maximum value for the lowest frequency for each day in a graph is transmitted to the wireless communication control unit 21. The wireless communication control unit 21 instructs the display unit 23 to perform display based on the data received from the evaluation unit 37.

  FIG. 14 is a diagram illustrating an example of a relationship between a walking stance and a stance evaluation index indicating a power value at the lowest frequency specified using a power spectrum of a lateral acceleration waveform collected by changing a stance during walking. is there. In FIG. 14, the horizontal axis represents the walking stance [cm], and the vertical axis represents the stance evaluation index in which the maximum value is expressed in common logarithm. FIG. 14 shows that there is a linear relationship between the stance during walking and the maximum value.

  FIG. 15 shows an example of a change in stance obtained by the walking test, created using the relationship shown in FIG. In FIG. 15, the horizontal axis indicates the date of the walking test, and the vertical axis indicates the walking stance evaluation index.

In FIG. 15, the walking stance in the left-right direction is shortened as the date progresses, and the degree of motor function recovery of the lower limb dysfunction patient (subject 1) can be grasped quantitatively.
Next, the operation of the body motion analysis system 200 configured as described above will be described. FIG. 16 is a flowchart showing a process flow of the body motion analysis system 200.

  First, when the frequency analysis unit 32 receives acceleration data from the wireless communication control unit 21 (S1601), the frequency analysis is performed on the acceleration data (S1602), and the result is output to the maximum value detection unit 33. .

  Next, the maximum value detection unit 33 detects the maximum value of power from the power spectrum input from the frequency analysis unit 32 (S1603). As a result, the local maximum frequency detector 34 detects the frequency corresponding to the local maximum detected by the local maximum detector 33 (S1604).

  Further, the lowest frequency detection unit 35 detects the lowest frequency excluding 0 Hz from the frequencies detected by the local maximum frequency detection unit 34 (S1605). Then, the array storage unit 36 stores an array including the lowest frequency, the maximum value corresponding to the lowest frequency, and the measurement date and time thereof.

The evaluation unit 37 reads out data at the designated date and time from the data stored in the array storage unit 36 and outputs the data to the wireless communication control unit 21 (S1606).
As described above, the body motion analysis system 200 according to the present embodiment makes it possible to compare the state of motor function recovery of lower limb dysfunction patients on a daily basis.

(Embodiment 3)
In the first embodiment, the body motion analysis system that calculates the stride, the walking speed, and the like based on the acceleration data acquired from the walking subject 1 has been described. In the present embodiment, the walking is performed based on the difference in acceleration. A physical motion analysis system that quantifies the degree of functional recovery will be described.

FIG. 17 is a block diagram illustrating functional configurations of the acceleration detection device 10 and the body motion analysis device 20 in the body motion analysis system 300 according to the present embodiment.
The body motion analysis system 300 includes an acceleration detection device 10 and a body motion analysis device 40, and the acceleration detection device 10 measures accelerations caused by movement of the subject 1 due to left and right feet. This system quantifies the degree of recovery of walking function based on the difference in measured acceleration. In the following description, it is assumed that the subject 1 walks as an example of the exercise of the subject 1, and the acceleration detection device 10 measures the acceleration when the subject 1 walks. In addition, the same reference numerals are given to the same functional configurations as those of the body motion analysis system 100 in the first embodiment, and the description thereof is omitted.

  The body motion analysis device 40 has a function of a general personal computer, receives acceleration data transmitted from the acceleration detection device 10 by a communication method or the like based on the bluetooth, and based on the acceleration data, Has a function to quantify the degree of recovery.

As illustrated in FIG. 17, the body motion analysis device 40 includes a wireless communication control unit 21, a left / right difference determination unit 43, a display unit 23, and a storage unit 24.
The left / right difference determination unit 43 is a processing unit that performs numerical calculation based on the acceleration data received from the wireless communication control unit 21, and calculates a left / right difference determination point that represents a difference in acceleration in the front-rear direction caused by the left and right legs. . More specifically, the left / right difference determination unit 43 determines the leg to be accelerated during walking from the left / right acceleration data, and the acceleration data attributed to the left foot and the acceleration data attributed to the right foot from the acceleration data in the front / rear direction. And the left-right difference determination point is calculated as the ratio of the accelerations or the difference between the accelerations.

  The display unit 23 is a display device including, for example, a liquid crystal panel, and displays the left / right difference determination points calculated by the left / right difference determination unit 43 in accordance with a control instruction from the wireless communication control unit 21.

  The storage unit 24 is a storage device including, for example, a RAM or a fixed disk, and includes an input / output interface for exchanging data with the wireless communication control unit 21. Further, the storage unit 24 stores the acceleration data and the left / right difference determination point calculated by the left / right difference determination unit 43 in association with the subject 1 and the measurement date / time according to an instruction from the wireless communication control unit 21.

  FIG. 18 is a diagram for explaining the processing contents in the left / right difference determination unit 43, and is a diagram showing a correspondence relationship between the leg travel of the subject 1 and acceleration data in the left / right and up / down directions. As shown in FIG. 18, the upper part shows the acceleration in the left-right direction when the subject 1 walks, and the lower part shows the acceleration in the front-rear direction. As described above, in the present embodiment, the forward direction is defined as the positive direction for the longitudinal acceleration information, and the right direction is defined as the positive direction for the lateral acceleration information.

The present embodiment is characterized in that the degree of recovery of the subject 1 is quantified. Therefore, the difference in speed between the left and right legs is defined as a ratio (percentage) of the speed of the non-healthy leg with respect to the speed of the healthy leg, with the difference between the left and right legs as a determination point. That is,
[Left / right difference judgment point]
= [Speed by non-healthy leg] / [Speed by normal leg] x 100 (3)
Expressed by

  As shown in FIG. 18, the speed in the front-rear direction caused by the left and right legs is defined as a value obtained by integrating the positive part of the acceleration in the front-rear direction along the time axis. It is defined in the interval from the time when the acceleration becomes positive to the time when it becomes negative. However, when only the acceleration in the front-rear direction is referenced, it is impossible to determine whether the acceleration is due to the left or right leg, even if the presence or absence of the acceleration can be determined. Therefore, in the present embodiment, this problem is solved using acceleration in the left-right direction.

  In other words, the left / right movement of the leg is strongly involved in fluctuations in the acceleration in the left / right direction, and the left / right acceleration when the left leg is grounded is deviated in the positive direction and the right foot is grounded. Since the acceleration in the left and right direction is deviated in the negative direction, the acceleration in the front and rear direction can be calculated by referring to the acceleration data in the left and right direction when calculating the speed in the front and rear direction due to the left and right legs. It is possible to determine whether the leg is left or right.

  As described above, in the present embodiment, when calculating the velocity due to the left and right legs, the right leg is grounded and positive when the acceleration in the left-right direction at the start of integration is negative. In some cases, a certain relationship is used in which the left leg is grounded.

  In the integration period, as in the case of the first embodiment, a frequency spectrum is generated based on a temporal change in measured acceleration, and a frequency spectrum having a maximum value is generated from the generated frequency spectrum. Identify. Further, the frequency of the specified frequency spectrum is specified, and the half period of the specified frequency is set as the integration period.

Next, the operation of the body motion analysis system 100 configured as described above will be described. FIG. 19 is a flowchart showing a process flow of the body motion analysis system 300.
First, when acceleration data is collected in the acceleration information detection unit 11 (S1), the left / right difference determination unit 43 calculates a speed (S2). Further, the left / right difference determination unit 43 calculates a left / right difference determination point based on the calculated speed (S3), and the display unit 23 displays the calculated left / right difference determination point (S4).

  More specifically, the acceleration information in the front-rear direction and the acceleration information in the left-right direction, which are simultaneously measured within a predetermined time interval, are input (S1), and the integration value for each integration interval is input to the input acceleration information. Is calculated and held.

  Furthermore, by referring to the sign of acceleration in the left-right direction at the start of integration, a label indicating which of the integration values corresponds to the left or right leg is assigned to each integration value. The integrated values distributed to the left and right legs in this way are averaged to calculate the speed by the healthy leg and the speed by the non-healthy leg (S2).

  At this time, in the body motion analysis apparatus according to the present embodiment, in advance, information that either the left or right leg is a non-healthy leg and the other leg is a non-healthy leg is retained, and finally The left-right difference determination point defined by the above equation (3) is generated.

If both legs are non-healthy legs, the one with the higher acceleration is regarded as a healthy leg. The same applies to the case where it is difficult to distinguish the left and right legs.
Further, the left / right difference determination point generated in the left / right difference determination step (S3) is output to the storage unit 24 of the body motion analysis apparatus according to the present embodiment (S4).

FIG. 20 is an example in which the degree of recovery of the body movement function of the subject 1 displayed on the display unit 23 is quantitatively displayed, and is a display example of the left-right difference determination point calculated by the above equation (3).
In the present embodiment, the positive direction in the lateral acceleration is “right” and the positive direction in the longitudinal acceleration is “front”. However, other directions may be used. It is sufficient if the code can be specified by.

In the above-described embodiment, an example in which the display unit 23 is configured by a display device including a liquid crystal panel or the like has been described. Or the like.
(Embodiment 4)
In the third embodiment, the system for quantifying the degree of recovery of the walking function based on the difference in acceleration caused by the walking of the subject has been described. However, in the present embodiment, the exercise of the subject is further added to the system. A system having a function capable of automatically determining whether or not is walking will be described.

  FIG. 21 is a block diagram showing a functional configuration of body motion analysis system 400 in the present embodiment. As shown in FIG. 21, the body motion analysis system 400 includes an acceleration detection device 10 and a body motion analysis device 45. In the following description, the same functional configuration as that of body motion analysis system 100 in the first embodiment is denoted by the same reference numeral, and the description thereof is omitted.

  The body motion analysis device 45 has a function of a general personal computer and determines whether or not the subject's motion is walking based on the acceleration data transmitted from the acceleration detection device 10. It has a function of quantifying the degree of recovery of the subject based on the data, and includes a wireless communication control unit 26, a left / right difference determination unit 43, a display unit 23, a storage unit 24, and a walking detection unit 27.

  In addition to the function of the wireless communication control unit 21 in the first embodiment, when the wireless communication control unit 26 receives a notification from the walking detection unit 27 that the exercise of the subject 1 is walking, the wireless communication control unit 26 Instructs to calculate the difference judgment point.

The walking detection unit 27 automatically determines whether or not the walking is based on the input vertical acceleration data, and notifies the wireless communication control unit 26 of the determination result.
FIG. 22 is a part of a waveform showing a change in acceleration in the vertical direction when the subject 1 is walking, which is referred to when the walking detector 27 determines the walking.

In general, when walking, a reaction force from the floor (or the ground) is generated rhythmically with the grounding of the legs. FIG. 22 shows the change in the floor reaction force.
Therefore, the walking detection unit 27 determines “walking” when any of the following conditions is satisfied. That is,
(Condition 1):
“In the acceleration in the vertical direction for a specified time (for example, 160 [msec]), a change of“ maximum → minimum → maximum ”occurs, and the amplitude between the maximum value and the minimum value (or between the minimum value and the maximum value) (In the case of FIG. 22, the amplitude between A and B or between B and C) is a specified value (for example, 0.15 G) or more, and the maximum value and the minimum value (or the minimum value and the maximum value). When the value of the midpoint (D or E in the case of FIG. 22) falls within a specified range (for example, 0.5G to 1.5G) "
(Condition 2):
“When condition 1 occurs more than the specified number of times (for example, 5 times) in a predetermined time (for example, 2 seconds), and the posture of the subject at that time is standing”
These two conditions.

  The walking determination in the walking detector 27 is performed after the acceleration data is acquired and before the speed is calculated (“input of acceleration information (S1)” in FIG. 19 in the third embodiment and “speed calculation (S2)”. ) ”).

  As described above, according to the body motion analysis system in the present embodiment, the three-dimensional acceleration data at the time of walking of the subject 1 is collected, it is determined whether or not the walking is based on these acceleration data, and further the walking The degree of functional recovery can be quantified.

  Note that the body movement analysis device 45 of the second embodiment can be connected to a terminal (for example, a personal computer) at a remote medical facility via a network such as the Internet.

  FIG. 23 is a diagram showing a state in which the body motion analysis device 45 in the subject house 2 and the terminal 29 of the medical facility 4 are connected via the network 3 as described above. As shown in FIG. 23, by connecting the body motion analysis device 45 and the terminal 29 via the network 3, it is possible to share information regarding the degree of recovery of the subject 1 between both devices.

  FIG. 24 is a diagram illustrating a change in the left-right difference determination point of the subject 1 displayed on the monitor (not shown) of the terminal 29 described above. As described above, the staff of the medical facility can grasp the recovery status of the subject 1 while staying at a remote place, and can give appropriate advice and the like.

  FIG. 24 is an example of displaying information related to the body movement function of the subject 1 displayed via the communication line on the display unit 23 provided in the terminal 29 of the medical facility. This is a graph of past left / right difference judgment points in the number of days later.

  Thus, it becomes possible to support the progress management of functional recovery by quantitatively showing the recovery of the body movement function of the subject to the medical staff. In addition, the degree of functional recovery can be shared with patients at home by using communication lines.

  As described above, the body motion analysis system 400 according to the present embodiment can automatically detect walking and can support autonomous function recovery training by presenting the subject's body motion function to the subject. .

  In addition, in the said Embodiment 1-4, the Example which the acceleration detection apparatus 10 fixes to the test subject's 1 waist part right side was demonstrated. This is because it is preferable to use the trunk of the human body rather than the hands and feet when determining the change in the walking stance of the human body in the left-right direction. Furthermore, the waist part closer to the center of gravity of the human body is more preferable.

  In the first to fourth embodiments, the acceleration data is collected at a sampling rate of 125 Hz. However, the sampling rate is a rate at which an acceleration waveform included in the frequency band of at least 0 to 20 Hz is obtained. I just need it.

  Furthermore, although Embodiments 1 to 4 show examples in which exercise analysis is performed for walking, it can also be applied to determination of whether or not walking is beautiful from the relationship of height, weight, and the like. It can also be applied to the analysis of running methods such as jogging and marathon, and can be used to study efficient driving methods.

  In the fourth embodiment, the predetermined time in the condition 2 is “2 seconds”, but this value is set to an arbitrary value according to the condition of the subject 1 and the like.

  As described above, the body motion analysis system and the body motion analysis device of the present invention can be applied as a rehabilitation system, a sports training device, a terminal device in a rehabilitation facility, a communication terminal in an elderly house, and the like.

1 is a schematic diagram of a body movement analysis system in Embodiment 1. FIG. It is a figure which shows the relationship between the mounting position of the acceleration detection apparatus in this invention, and the coordinate axis of an acceleration sensor. FIG. 2 is a block diagram illustrating functional configurations of an acceleration detection device and a body motion analysis device according to Embodiment 1. It is an example which showed correspondence with leg change and change of acceleration in a subject's walking function test over time. It is the figure which showed typically the frequency spectrum regarding the acceleration curve of the front-back direction. It is an example which shows the relationship between the common logarithm of frequency power and step length calculated experimentally. It is a flowchart which shows the flow of a process of a body movement analyzer. It is a display example at the time of comparing the latest measured value of the stride and the walking speed with the previous measured value on the display unit. It is an example which displayed the change of the body movement function regarding a test subject. It is a block diagram which shows each function structure of the acceleration detection apparatus in Embodiment 2, and a body movement analysis apparatus. It is a block diagram which shows the function structure of a motion analysis part. It is an example of the time series data of the acceleration of the left-right direction at the time of the walk in the walk test implemented by the test subject. It is a figure which shows an example of the power spectrum produced | generated in the frequency analysis part. It is a figure which shows an example of the relationship between the stance evaluation index which shows the power value in the lowest frequency, and a walking stance. It is an example which shows the mode of the change of the stance obtained by the walk test. 6 is a flowchart showing a flow of processing of the body movement analysis system in the second embodiment. FIG. 10 is a block diagram illustrating functional configurations of an acceleration detection device and a body motion analysis device according to Embodiment 3. It is the figure which showed the correspondence of a test subject's leg movement and the acceleration data of the left-right direction and the up-down direction. 10 is a flowchart showing a process flow of the body movement analysis system in the third embodiment. It is an example of a display of a right-and-left difference judging point about a subject. FIG. 10 is a block diagram showing a functional configuration of a body movement analysis system in a fourth embodiment. It is a part of the waveform which shows the change of the acceleration of the up-down direction at the time of a test subject's walk referred at the time of a walk determination in a walk detection part. It is the figure which showed a mode that the body movement analysis apparatus in a test subject's house and the terminal of a medical facility were connected via the network. It is a figure which shows the mode of the change of the subject's left-right difference determination point displayed on the terminal of a remote place.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Test subject 2 Test subject's house 3 Network 4 Medical facility 5 Wearing tool 10 Acceleration detection apparatus 11 Acceleration information detection part 12 Wireless communication control part 20 Physical motion analysis apparatus 21 Wireless communication control part 22 Walking speed detection part 23 Display part 24 Accumulation part 26 Wireless Communication control unit 27 Walking detection unit 29 Terminal 30 Body motion analysis device 31 Motion analysis unit 32 Frequency analysis unit 33 Maximum value detection unit 34 Maximum value frequency detection unit 35 Minimum frequency detection unit 36 Array storage unit 37 Evaluation unit 40 Body motion analysis device 43 Left-right difference determination unit 45 Physical motion analysis device 100 Physical motion analysis system 200 Physical motion analysis system 300 Physical motion analysis system 400 Physical motion analysis system

Claims (5)

A body movement analysis device for analyzing a human walking function,
Acceleration detecting means for detecting at least one of the acceleration in the front-rear direction, the acceleration in the left-right direction, and the acceleration in the up-down direction caused by the movement of the person over time;
Based on the detected temporal change in the longitudinal acceleration, a frequency analysis unit that generates a frequency spectrum, and a frequency specifying unit that specifies a frequency of the maximum power from the generated frequency spectrum are specified. An acceleration analysis means comprising a logarithmic value calculation unit for calculating a common logarithm value from the maximum power of the frequency spectrum;
A body motion analysis apparatus comprising: a walking function amount calculating unit that calculates a stride during walking by applying the calculated common logarithmic value to an approximate expression obtained in advance. A body movement analysis device for analyzing a human walking function,
Acceleration detecting means for detecting at least one of the acceleration in the front-rear direction, the acceleration in the left-right direction, and the acceleration in the up-down direction caused by the movement of the person over time;
Based on the detected temporal change in the lateral acceleration, a frequency analysis unit that generates a frequency spectrum, a frequency corresponding to the maximum value is identified from the generated frequency spectrum, and further, An acceleration analyzing means comprising a frequency specifying unit for specifying the lowest frequency excluding 0 Hz, and a logarithmic value calculating unit for calculating a common logarithm value from the peak value of the specified frequency spectrum;
A body motion analysis device comprising: a walking function amount calculating means for calculating a stance during walking by applying the calculated common logarithmic value to an approximate expression obtained in advance. A body movement analysis device for analyzing a human walking function,
Acceleration detecting means for detecting at least one of the acceleration in the front-rear direction, the acceleration in the left-right direction, and the acceleration in the up-down direction caused by the movement of the person over time;
Based on the detected temporal change of the acceleration, a frequency analysis unit that generates a frequency spectrum, a frequency specifying unit that specifies a frequency corresponding to a maximum value from the generated frequency spectrum, and the specified A period calculation unit that calculates an integration period using a frequency, and a leg specification unit that specifies which leg on the left and right of the detected longitudinal acceleration is caused by using the detected acceleration in the left and right direction An acceleration analysis means comprising:
For the calculated integration period, a speed calculation unit that calculates the speed of the left leg and the right leg by integrating the acceleration in the front-rear direction related to the specified leg, and based on the calculated speed, A walking function amount calculating means comprising a speed ratio calculating unit for calculating a rate of leg speed;
A body motion analysis device comprising: A body movement analysis device for analyzing a human walking function,
Acceleration detecting means for detecting at least one of the acceleration in the front-rear direction, the acceleration in the left-right direction, and the acceleration in the up-down direction caused by the movement of the person over time;
A spectrum generation unit that generates a frequency spectrum from the detected curve representing acceleration in the front-rear direction, a maximum spectrum specification unit that specifies a maximum spectral component from the generated frequency spectrum, and the specified maximum A logarithmic value calculation unit that calculates a common logarithm value from a peak value of a spectrum component, a stride calculation unit that calculates a stride by applying the calculated common logarithm value to an approximate expression obtained in advance, and An acceleration analysis means comprising: a walking cycle calculating unit that calculates a walking cycle based on the acceleration in the left-right direction;
A walking function amount calculating means for calculating a walking speed based on the extracted stride and the walking cycle;
A body motion analysis device comprising: A body movement analysis device for analyzing a human walking function,
Acceleration detecting means for detecting at least one of the acceleration in the front-rear direction, the acceleration in the left-right direction, and the acceleration in the up-down direction caused by the movement of the person over time;
A zero-cross point identifying unit that identifies a zero-cross point in the detected curve representing the acceleration in the left-right direction; a walking cycle calculation unit that calculates a walking cycle from the identified at least two zero-cross points; A spectrum generating unit that generates a frequency spectrum from a curve representing acceleration in a direction; a maximum spectrum specifying unit that specifies a maximum spectral component from the generated frequency spectrum; and a peak value of the specified maximum spectral component A logarithmic value calculation unit that calculates a common logarithm value from the above, a stride calculation unit that calculates a stride by applying the calculated common logarithm value to an approximate expression obtained in advance, and the detected left-right direction An acceleration analysis means comprising: a walking cycle calculation unit that calculates a walking cycle based on acceleration;
A walking function amount calculating means for calculating a walking speed based on the extracted stride and the walking cycle;
A body motion analysis device comprising:

Images