JP5303712B2 - Lower limb coordination evaluation system - Google Patents

Description

  The present invention relates to a lower limb coordination evaluation system capable of evaluating a fall risk of an elderly person or the like.

  If an elderly person or a person with sports disabilities falls while walking, the possibility of developing a serious injury from a decline in physical ability centered on muscle strength increases. Therefore, it is considered that it is very important to recognize each fall risk in advance.

  In general, falls are considered to be closely related to dynamic balance ability and lower limb strength, so dynamic balance ability and lower limb strength are often used as risk indicators related to fall risk. . Therefore, various methods for measuring dynamic balance and lower limb muscle strength have been proposed.

For example, a method has been proposed that uses a portable three-dimensional acceleration sensor to detect a decrease in the lower limb from pelvic acceleration during normal walking and the dorsiflexion force of the human body (Patent Document 1).
However, the peak of pelvic acceleration varies greatly depending on the walking state, and the aging change of dorsiflexion force varies greatly between individuals, so when considering the range of motion of the joint, we measure the decline of the lower limbs from pelvic acceleration and dorsiflexion force There is a fear that you can not.

  Therefore, the present inventors have found that the acceleration generated in the body during walking or exercising is closely related to the risk index, and by measuring the acceleration generated on the toe by wearing an acceleration sensor on the toe, the inversion A method for risk assessment is proposed.

2007-125368 gazette

The 66th Annual Meeting of the Japanese Society of Public Health (2008)

  However, since the technique described in Non-Patent Document 1 cannot objectively determine the risk index used when evaluating the risk of falls, there is a problem that it is difficult to evaluate the fall risk with high accuracy. is there.

  The present invention has been made in view of the above problems, and further improves the above invention, and can objectively determine the risk index used for the evaluation of the fall risk, thereby accurately evaluating the fall risk. It is an object to provide a lower limb coordination evaluation system that can be used.

The above problem is solved by the following means.
The invention according to claim 1 of the present application is an acceleration measuring means that is attached to a predetermined part of a human body and measures acceleration generated in the vertical direction, the left-right direction, and / or the front-rear direction during walking or exercise of the predetermined part. , on the basis of the measured acceleration, vertical predetermined portion, the lateral direction and / or a calculation detecting means for calculating a statistic related to the acceleration with respect to the front-rear direction respectively, statistics related to the calculated acceleration ROC for the amount; used to evaluate the risk of falls by performing (receiver operating characteristic receiver operating characteristic) analysis extracts the statistics to set the cut-off value associated with statistics that the extracted as a risk index A lower limb cooperation evaluation system comprising: setting means.

The invention according to claim 2 of the present application is the lower limb cooperation evaluation system according to claim 1 , further comprising an evaluation unit that evaluates a fall risk of the subject based on the set risk index.

The invention according to claim 3 of the present application is the lower limb coordination evaluation system according to claim 1 or 2, wherein the predetermined parts where the acceleration measuring means is installed are the left and right toe parts, the left and right knee joint parts, and the waist part.

In the invention according to claim 4 of the present application, as the calculating means, the absolute value of the acceleration generated during the walking motion or the motion motion is integrated over a certain time when the walking motion or the motion motion is performed, and the integrated value is obtained. by dividing the fixed time walking or movement operation is performed to calculate the statistics related to the acceleration, a lower limb coordinated evaluation system according to any of claims 1 to 3.

  According to the invention of claim 1 of the present application, it is possible to extract a statistic suitable for the evaluation of the fall risk from the measurement direction of the part to which the acceleration measuring means is attached, and to extract information related to the extracted statistic. It can be set as an index. As a result, an objective risk index can be set, and a highly accurate fall risk evaluation can be performed.

Furthermore , according to the invention according to claim 1 of the present application, it is possible to extract a statistic suitable for evaluation of a fall risk using ROC analysis, and the statistic can be used as a risk index. Can be extracted.

According to the invention of claim 2 of the present application, it is possible to evaluate a subject's fall risk using the set risk index.

According to the invention of claim 3 of the present application, the acceleration generated in the up-down direction, the left-right direction, and / or the front-rear direction during walking of the left and right toe parts, the left and right knee joint parts, and the waist part during walking or exercise is measured. It is possible to perform measurement with higher accuracy.

According to the invention according to claim 4 of the present application, the absolute value of the acceleration generated during the walking motion or the motion motion is integrated over a certain time during which the walking motion or the motion motion is performed, and the integrated value is integrated into the walking motion or By dividing by the time at which the exercise motion was performed, the statistics related to acceleration can be calculated.

  As a result, the acceleration generated during a certain period of time during which the walking motion or the motion motion is performed can be averaged, so that measurement using effective statistics can be performed.

It is the figure which showed the whole structure of the leg cooperation evaluation system which concerns on one Embodiment of this invention. (a) is a diagram showing the measurement direction of the acceleration sensor 2e attached to the waist, and (b) is a diagram showing the measurement directions of the acceleration sensors 2d and 2b attached to the right knee joint part and the right toe part. is there It is the figure which showed the block diagram of a data logger and a leg cooperation evaluation apparatus. It is the figure which showed an example of the screen displayed on a display part. It is the figure which showed an example of acceleration waveform data. (a), (b) is the figure which showed an example of the constituent number according to age and the gender of the subject who measures when extracting a risk index. It is the figure which showed an example of the life function ability parameter | index questionnaire. It is the figure which showed an example of the fall risk assessment questionnaire. It is the figure which showed the result of having performed the screening test | inspection with respect to the test subject based on the questionnaire result of a life function ability parameter | index. It is a continuation of FIG. It is a continuation of FIG. It is a continuation of FIG. It is a continuation of FIG. It is the figure which showed the ROC curve. It is the figure which showed the result of having performed the screening test | inspection with respect to the test subject based on the result of FRT. It is a continuation of FIG. It is a continuation of FIG. FIG. 17 is a continuation of FIG. It is a continuation of FIG. It is the figure which showed the result of having performed the screening test | inspection with respect to the test subject based on the result of the fall risk assessment. It is a continuation of FIG. It is a continuation of FIG. It is a continuation of FIG. It is a continuation of FIG. It is the figure which showed the result of having performed the screening test | inspection with respect to the said test subject based on the result of a leg muscular strength. FIG. 26 is a continuation of FIG. 25. FIG. 27 is a continuation of FIG. 26. FIG. 28 is a continuation of FIG. 27. FIG. 29 is a continuation of FIG. 28. It is the figure which showed an example of the test subject data table which measured with respect to five test subjects using the leg cooperation evaluation system, and showed the measurement result. Huh It is an example of the handbill which notifies a test subject the result of having determined the fall risk based on the measurement result. It is the flowchart which showed operation | movement of the leg cooperation evaluation apparatus. It is the flowchart which showed the operation | movement of the data logger.

  Embodiments of the present invention will be described with reference to the drawings. In addition, embodiment shown below is only one form which actualized this invention, and does not limit the technical scope of this invention.

  In the present embodiment, first, a statistic used for a subject's fall risk evaluation is extracted, and a risk index closely related to the fall is set. Therefore, we measure the acceleration of each part for multiple subjects, calculate the average acceleration for each part, and extract the optimal statistic for use in the evaluation of fall risk from the average acceleration for each part. Then, a cutoff value related to the statistical quantity extracted thereafter is set as a risk index.

  Then, the fall risk of each subject is evaluated based on the set risk index. In the present embodiment, the subject is allowed to walk for 8 seconds in a straight line, the average of accelerations generated during that time is calculated, and based on this, statistics are extracted, fall risk is evaluated, and the like.

  Hereinafter, an overall configuration of the lower limb coordination evaluation system, a method for setting a risk index used for evaluating a subject's fall risk, and a method for evaluating a fall risk based on the risk index will be described.

[Overall system configuration]
First, the overall configuration of the lower limb cooperation evaluation system will be described.
FIG. 1 is a diagram showing an overall configuration of a lower limb cooperation evaluation system according to an embodiment of the present invention.
The lower limb coordination evaluation system 1 includes acceleration sensors 2a, 2b, 2c, 2d and 2e, a data logger 3, a lower limb coordination evaluation apparatus 4, a WEB camera 5 and the like as shown in the figure. The evaluation device 4 is connected with a USB cable 6.

Acceleration sensors 2a, 2b, 2c, 2d and 2e are used as acceleration measurement means, and are attached to the left toe, right toe, left knee joint, right knee joint and waist as shown in the figure, while walking Or the acceleration which arises in the up-down direction of the said site | part in motion, the left-right direction, and the front-back direction is measured.
The acceleration sensors 2a, 2b, 2c, 2d and 2e have built-in amplifier circuits, full-wave rectifier circuits, smoothing circuits and converters (all not shown), and the measured acceleration, which is an analog signal, is After being amplified and converted into direct current by a full-wave rectifier circuit and a smoothing circuit, it is converted into a digital signal by a converter. In the following description, the digital signal is referred to as acceleration data, and the acceleration data refers to data including an acceleration waveform.

  The data logger 3 captures acceleration data from the acceleration sensors 2a, 2b, 2c, 2d and 2e, and transmits the captured acceleration data to the lower limb coordination evaluation device 4 through a communication means such as Bluetooth. In response to the measurement start instruction and measurement end instruction from, the acceleration sensors 2a, 2b, 2c, 2d and 2e are controlled to start and stop measurement.

  The lower limb coordination evaluation device 4 calculates the average acceleration, which is a statistic related to acceleration, based on the acceleration data from the data logger 3, evaluates the fall risk, and outputs the evaluation result. .

  The WEB camera 5 is an electronic camera having a pixel number of 640 × 480 pixels, and can be connected to the lower limb cooperation evaluation device 4 according to the USB standard and output captured image data of a moving image. In this embodiment, as described above, the subject walks for 8 seconds in a straight line, and the walking state is photographed.

Next, the places where the acceleration sensors 2a, 2b, 2c, 2d, and 2e are attached to the body and the measurement directions will be described.
As described above, the acceleration sensors 2a, 2b, 2c, 2d and 2e are attached to the left toe part, the right toe part, the left knee joint part, the right knee joint part and the waist part, respectively. Measure the acceleration that occurs in the longitudinal direction.

  2 (a) shows the measurement direction of the acceleration sensor 2e attached to the waist, and FIG. 2 (b) shows the measurement direction of the acceleration sensors 2b and 2d attached to the right toe part and the right knee joint part. FIG.

  The acceleration sensor 2e attached to the waist measures the acceleration in the up-down direction (UD), the left-right direction (LR), and the front-rear direction (F-B) generated during walking or exercise. Further, the acceleration sensor 2b attached to the right toe portion measures the acceleration in the up-down direction (UD), the left-right direction (LR), and the front-rear direction (FB) generated during walking or exercise. .

  Further, the acceleration sensor 2d is mounted at a position 2 cm above the right knee joint, and is generated in the up-down direction (UD), left-right direction (LR), and front-back direction (FB) generated during walking or exercise. Measure acceleration. Note that the measurement directions of the acceleration sensors 2a and 2c attached to the left toe portion and the left knee joint portion are the same as in the case of the right foot, so a detailed description thereof is omitted here.

Next, the circuit configuration of the data logger 3 and the lower limb cooperation evaluation device 4 will be described with reference to FIG.
As shown in the drawing, the data logger 3 includes a control unit 3a, a signal capturing unit 3b, a RAM 3c, a communication unit 3d, and the like.

The control unit 3a comprehensively controls the entire data logger 3, and controls the acceleration sensors 2a, 2b, 2c, 2d, and 2e based on an instruction from the lower limb cooperation evaluation device 4.
The signal capturing unit 3b captures acceleration data from the acceleration sensors 2a, 2b, 2c, 2d, and 2e.

The RAM 3c temporarily stores acceleration data and the like captured by the signal capturing unit 3c.
The communication unit 3d transmits acceleration data to the lower limb cooperation evaluation device 4, and receives a measurement start instruction and a measurement end instruction from the lower limb cooperation evaluation device 4.

  As shown in FIG. 3, the lower limb cooperation evaluation device 4 includes a control unit 4a, a RAM 4b, a ROM 4c, a USB interface (USB I / F) 4d, a communication unit 4e, a processing unit 4f, a data storage unit 4g, a printing unit 4h, and an input unit. 4i, a display unit 4j, and the like.

  The control unit 4a performs overall control of the lower limb coordination evaluation device 4 as well as extraction of statistics used for evaluation of fall risk by performing statistical analysis processing (ROC analysis), and relates to the extracted statistics The cut-off value to be used is set as a risk index, and the risk of falling is evaluated. The details will be described later.

The RAM 4b temporarily stores moving images taken by the WEB camera 5, acceleration data from the data logger 3, and the like. In the RAM 4b, under the control of the control unit 4a, the transmitted acceleration data and the moving image taken by the WEB camera 5 are synchronized and displayed on the acceleration waveform data display screen 41j (shown below). The acceleration waveform and the moving image displayed on the moving image display screen 42j (shown below) are synchronized.
The ROM 4c stores programs executed by the control unit 4a and the like.

  The USB interface (USB I / F) 4d is connected to the WEB camera 5 via the USB cable 6, and takes in a moving image shot by the WEB camera 5.

  The communication unit 4e transmits / receives data to / from the data logger 3.

  The processing unit 4f is used as first calculation means, extracts acceleration data from the RAM 4b, and calculates the average of accelerations generated in the vertical direction, the horizontal direction, and the front-rear direction for each part where the acceleration sensor is mounted. The average acceleration is calculated by performing absolute value integration on the acceleration generated during the measurement time (8 seconds) and dividing by the measurement time as shown in FIG.

  The data storage unit 4g is a video taken by the WEB camera 5, waveform data of acceleration of each part, risk index, a result of questionnaire on vital function ability preliminarily input by a measurer, a measurement result of lower limb muscle strength, etc. Also save below).

The printing unit 4h prints the calculated data and the like.
The input unit 4i is composed of a keyboard, a mouse, and the like, and inputs a measurement start instruction and a measurement end instruction from the user, and also inputs a subject's name, age, and the like.

  The display unit 4j is a display or the like, and displays data input from the input unit 4i, measurement results, age of the subject, moving images taken by the WEB camera 5, and the like.

FIG. 4 is a diagram illustrating an example of a screen displayed on the display unit 4j.
As shown in the figure, the display unit 4j includes a subject data display screen 40j, an acceleration waveform data display screen 41j, a moving image display screen 42j, an instruction input screen 43j, and the like.

The subject data display screen 40j displays the name, age, and sex of the subject.
The acceleration waveform data display screen 41j displays a waveform of acceleration generated in the waist, left toe part, right toe part, right knee joint part, and left knee joint part when the subject walks or exercises.

FIG. 5 is a diagram showing an example of an acceleration waveform displayed on the acceleration waveform data display screen 41j. The horizontal axis represents measurement time (s) and the vertical axis represents acceleration (m / s ² ). ing.
The moving image display screen 42j displays a moving image shot by the WEB camera 5.

  The instruction input screen 43j includes a measurement start button 430j, a measurement end button 431j, a print button 432j, a playback button 433j, an analysis button 434j, a save button 435j, a system setting button 436j, a system end button 437j, and the like.

The measurement start button 430j is selected when a measurement start instruction is issued from the measurer.
The measurement end button 431j is selected when a measurement end instruction is issued from the measurer.

The print button 432j is selected when printing measurement data, measurement results, and the like.
The playback button 433j is selected when playing back a moving image or acceleration waveform.

  The analysis button 434j is selected when calculating an average acceleration, evaluating a fall risk, or the like based on the acceleration data transmitted from the data logger 3.

  The save button 435j is selected when the moving image, acceleration waveform data, average acceleration, and the like taken by the WEB camera 5 are saved in the data saving unit 4g.

The system setting button 436j is selected when setting the input method of the subject's name, age, and gender from the input unit 4i and various function settings.
The system end 437j is selected when the operation of the lower limb cooperation evaluation system 1 is ended.

[Risk index setting method]
Next, a statistical amount extraction method and a risk index setting method used in evaluating the subject's fall risk will be described.
For the risk index, basic data are collected by measuring the vital function ability index questionnaire, fall risk assessment questionnaire, FRT (Function Reach Test), and lower extremity muscle strength shown below for a plurality of subjects. It is set by performing a statistical analysis process (ROC analysis) based on the data and the measured acceleration value of each part. It should be noted that statistics and risk indices used when evaluating the fall risk are extracted and set for the vital function ability index, the fall risk assessment, the FRT, and the lower limb strength.

(basic data)
First, the vital function ability index, fall risk assessment, FRT and lower limb muscle strength used as basic data will be described.

  A table 6a shown in FIG. 6 shows an example of the number of constituents by age and gender of subjects who perform the vital function ability index questionnaire, the fall risk assessment questionnaire, and the FRT measurement. Thus, a total of 278 men, 129 men and 149 women, were included. The table 6b shows an example of the number of subjects by gender and age of subjects who measure the muscle strength of the lower limbs. In the present embodiment, as shown in the figure, a total of 232 boys (110 boys and 122 girls) are shown. Name was targeted.

  Table 7 shows the results of questionnaire on the functional function ability index and the fall risk assessment, FRT (Function Reach Test) and lower limb muscle strength measurement results of the subjects.

As shown in the table 9 of FIG. 7, the vital function ability index 7a is a questionnaire conducted on a subject related to basic actions necessary for daily life actions such as meals, excretion, detachable clothes, bathing, moving and waking up. The result is quantified and used to measure the physical activity ability and the degree of disability of the subject.
In this embodiment, subjects with less than 13 points are classified as a high risk group and subjects with 13 points or more are classified as a low risk group based on the questionnaire results.

  The high risk group is a group of subjects who are considered to have a high risk of falling, and the low risk group is a group of subjects who are considered to have a low risk of falling. These values are determined based on the experience of the measurer. In addition, the numerical value used as a standard for classifying into the high risk group or the low risk group is set in advance by the measurer and stored in the data storage unit 4g. When data such as questionnaire results or measurement values is input, it is automatically set. It is classified as either a high risk group or a low risk group.

  The fall risk assessment 7b is obtained by conducting a questionnaire as shown in the table 10 of FIG. Note that. In the present embodiment, subjects having 10 points or less are classified as a high risk group and subjects having 11 points or more are classified as a low risk group based on the questionnaire results.

  FRT (Function Reach Test) 7c is a measurement of the distance at which a fingertip can be stretched forward without falling from a standing position. In this embodiment, subjects of 15 cm or less are subject to a high risk group, and subjects exceeding 15 cm are regarded as a low risk. Classify as a group.

  The lower limb strength 7d is obtained by measuring the lower limb strength using a lower limb strength measurement device or the like for the subject. In the present embodiment, subjects whose lower limb muscle strength is less than 15 kg are classified as a high risk group, and subjects whose lower limb muscle strength is 15 kg or more are classified as a low risk group.

(Measurement value of acceleration)
Next, based on the basic data and the transmitted acceleration data, a statistic extraction method and a risk index setting method used for the fall risk evaluation will be described. As described above, the statistics and risk index used for the evaluation of the fall risk are extracted and set for the vital function ability index, the fall risk assessment, the FRT, and the lower limb muscle strength.
FIG. 9 to FIG. 29 show the results obtained by measuring the acceleration of each part using the acceleration sensors 2a, 2b, 2c, 2d and 2e for the subject, and the results of the age and the average acceleration. It is the figure which represented by the graph of the relationship and performed the screening test | inspection based on the said questionnaire result and a measurement result. The horizontal axis represents age (years), and the vertical axis (logarithmic axis) represents average acceleration (m / s ² ). 9 to 29, the average acceleration is simply expressed as acceleration.

[Functional function ability index]
First, a method for extracting a statistic relating to a vital function capability index and a method for setting a risk index will be described.
FIG. 9 to FIG. 13 are diagrams showing the results of a screening test performed on subjects based on the vital function ability index questionnaire results.
The subjects classified into the high risk group are indicated by ●, and the subjects classified into the low risk group are indicated by ○.

  9 (a), 9 (b), and 9 (c) are the distribution diagrams of the waist front, back, left and right, and waist top and bottom, respectively, and FIG. 10 (a), (b), and (c) are the right knee joint front and back, right FIG. 11 (a), (b), and (c) show the distribution diagrams of the right and left knees and the right and right toes, respectively.

  12 (a), 12 (b), and 12 (c) are distribution diagrams of the left and right knee joints, the left and right knee joints, and the left and right knee joints, respectively, and FIGS. 13 (a), 13 (b), and (c). ) Respectively show left and right toe front, left toe left and right and left toe up and down distribution maps.

  14 (a) and 14 (b) are the waist front and back, waist left and right, waist top and bottom, right knee joint front and back, right knee joint left and right, right knee joint top and bottom, right toe front and back, right toe left and right, right toe top and bottom, left knee joint. By extracting the statistics used for risk assessment from the front and back, left and right knee joints, left and right joints up and down, left toe front and back, left toe left and right and left toe up and down, by changing the cutoff value of acceleration (average acceleration) It is the graph (ROC curve) which performed the ROC (receiver operating characteristic) analysis and showed the result.

  In the figure, the vertical axis represents sensitivity (%), and the horizontal axis represents 100-specificity (%). Here, the extracted statistic is a statistic corresponding to the ROC curve at the shortest distance from the point of (sensitivity, 100−specificity) = (100,0). The cut-off value set as the risk index is set to an acceleration corresponding to the coordinates on the ROC curve forming the shortest distance from the point. In order to set the risk index, the distribution of the population is determined in consideration.

  As shown in FIG. 14, the curve that satisfies the above condition is a curve “before and after the left toe”, and thus the average acceleration measurement values before and after the left toe are extracted as a statistic when performing a fall risk assessment. In this case, the cutoff value is 0.6. Also, since ROC analysis is a known technique, a detailed description thereof is omitted here.

[FRT]
Next, a risk index setting method for FRT will be described.
FIG. 15 to FIG. 19 are diagrams showing the results of the screening test performed on the subject based on the measurement results of FRT. Indicates the subjects classified into the high risk group by FRT, respectively. The vertical axis represents acceleration (m / s ² ), and the horizontal axis represents age (years).

  15 (a), 15 (b), and 15 (c) are distribution diagrams of the waist front, back, left and right, and waist top and bottom, respectively, and FIG. 16 (a), (b), and (c) are the front and back right knee joints and the right FIG. 17 (a), (b), and (c) show distribution diagrams of the right and left knees, right and left and right toe verticals, respectively.

  18 (a), (b), and (c) are distribution diagrams of the left and right knee joints before and after, the left and right knee joints, and the left and right knee joints, respectively, and FIGS. 19 (a), (b), and (c). ) Respectively show left and right toe front, left toe left and right and left toe up and down distribution maps.

  For these, ROC analysis is performed in the same manner as described above, and statistics used for evaluation of the fall risk are extracted. In this case, the average acceleration measurement value “before and after the right knee joint” is extracted as a statistic when the fall risk is evaluated. Note that the cutoff value set as the risk index in this case is 0.6.

[Fall risk assessment]
Next, the setting method of the risk index regarding the fall risk assessment will be described.
FIG. 20 to FIG. 24 are diagrams showing the results of the screening test performed on the subject based on the fall risk assessment questionnaire results, and the circles shown in the figures are classified into low risk groups in the fall risk assessment. The subject indicates the subject classified into the high risk group by the fall risk assessment. The vertical axis represents acceleration (m / s ² ), and the horizontal axis represents age (years).

  20 (a), (b), and (c) are distribution diagrams of the waist front, back, left and right, and waist top and bottom, respectively, and (a), (b), and (c) of FIG. FIG. 22 (a), (b), and (c) show the distribution diagrams of the right and left knees, the right and left toes, and the right and left toes, respectively.

  23A, 23B, and 23C are distribution diagrams of the left and right knee joints, the left and right knee joints, and the left and right knee joints, respectively. ) Respectively show left and right toe front, left toe left and right and left toe up and down distribution maps.

  For these, ROC analysis is performed in the same manner as described above, and statistics used for evaluation of the fall risk are extracted. In this case, the average acceleration measurement value of “waist up and down” is extracted as a statistic when the fall risk is evaluated. Note that the cutoff value set as the risk index is 0.5.

[Lower limb strength]
Finally, a method for setting a risk index related to lower limb muscle strength will be described.
FIG. 25 to FIG. 29 are diagrams showing the results of a screening test performed on the above subjects based on the measurement results of the lower limb muscle strength, and “◯” shown in the figure is classified into a low-risk group in which the lower limb muscle strength is less than 15 kg. The ● indicates the subjects classified into the high risk group whose lower limb muscle strength is 15 kg or more. The vertical axis represents acceleration (m / s ² ), and the horizontal axis represents age (years).

  25 (a), (b), and (c) are the waist front, back, left and right, and waist top and bottom distribution maps, respectively, and FIG. 26 (a), (b), and (c) are the right knee joint front and back, right FIGS. 27A, 27B, and 27C are distribution diagrams of the right and left knees, right and left knees, and right and left toes, respectively. .

  28 (a), (b), and (c) are distribution diagrams of the front and rear of the left knee joint, the left and right knee joints, and the upper and lower left knee joints, respectively (a), (b), and (c) of FIG. ) Is a diagram showing distribution diagrams of the left toe front and back, the left toe left and right and the left toe up and down, respectively.

  For these, ROC analysis is performed in the same manner as described above to extract statistics used for evaluation of the fall risk. In this case, the average acceleration measurement value “before and after the right toe” is extracted as a statistic when the fall risk evaluation is performed. The cut-off value set as the risk index is 0.7.

  As described above, the statistics used for the fall risk evaluation are extracted for each of the vital function ability index, the fall risk assessment, the FRT, and the lower limb muscle strength, and the risk index is set. In addition, each statistic and the numerical value of the risk index are stored in the data storage unit 4g.

[Falling risk evaluation method]
Next, a method for evaluating a fall risk for each subject will be described. The statistic used in the fall risk assessment is the statistic extracted by the above method, that is, “left and right toe before and after”, “right and left knee joint before and after”, “waist up and down” and “right toe before and after”, The risk index is set as described above.
First, a life function ability index questionnaire and a fall risk assessment are performed on the subject in the same manner as described above, and FRT and lower limb muscle strength are measured. Next, as shown in FIG. 2, an acceleration sensor is attached to each part of the body, and an average acceleration for each part is calculated by having a straight walk for 8 seconds.

FIG. 30 shows an example of the subject data table 15 showing the results of questionnaires and measurements on five subjects (A, B, C, D, E, F) by the above method. FIG.
As shown in the figure, it consists of subject information 15a, measurement / questionnaire result 15b, average acceleration measurement value 15c, criterion 15d, and total score 15e.

  The subject information 15a is for identifying the subject, and is composed of a subject number, sex, and age that are uniquely assigned to the subject. In the gender, “1” represents male and “2” represents female.

  The measurement / questionnaire result 15b represents the result of the questionnaire on fall risk assessment and vital function ability index performed on the subject, and the measurement result of FRT and lower limb muscle strength.

  The average acceleration measurement value 15c represents an average acceleration obtained by measuring accelerations before and after the right knee joint, before and after the left toe, up and down the waist, and before and after the right toe using an acceleration sensor.

  Criteria 15d is a score assigned by comparing the cut-off values before and after the right knee joint set as the risk index, before and after the left toe, before and after the waist and the right toe and the average acceleration of the subject. . That is, the cutoff value is compared with the average acceleration measurement value described in the average acceleration measurement value 15c. If the average acceleration measurement value is larger than the cutoff value, “1” is indicated. If the average acceleration measurement value is smaller than the cutoff value, “0” is indicated. Are assigned respectively.

  For example, the average acceleration measurement value before and after the right knee joint of subject number A is 0.58, while the cutoff value before and after the set right knee joint is 0.5. In this case, since the average acceleration measurement value is larger, “1” is assigned. The average acceleration before and after the right knee joint of subject number B is 0.48, which is smaller than the cutoff value, so “0” is assigned.

  Hereinafter, by comparing the average acceleration measurement value before and after the left toe, the average acceleration measurement value of the upper and lower hips, the average acceleration measurement value before and after the right toe and the average acceleration measurement before and after the right knee joint, and the respective cut-off values. 1 "or" 0 "is assigned respectively.

As described above, the total score 15e of the assigned points is an evaluation of the subject's fall risk.
Here, for example, when the measurer thinks that the fall risk is high when the total score is 1 point or less, the fact that the fall risk is high is displayed on the display unit 4j for the subject whose total score is 1 point or less. Set to print from the printing unit 4h. And when showing the measurement result of the subject A whose total score is 1 point or less, while displaying or / and printing that the fall risk is high, the handbill shown in FIG. Prompt.

  As described above, when the risk of falling is high, it is possible to call the subject to prevent falling. In addition, since an optimal risk index is extracted from the measurement result at each part by ROC analysis, it is possible to prevent falls with high accuracy.

(Falling risk assessment flowchart)
Next, operation | movement of the leg cooperation evaluation apparatus 4 at the time of evaluating a test subject's fall risk is demonstrated, referring the flowchart shown in FIG. This operation is realized by the control unit 4a executing a program stored in the ROM 4c or the like.

  System setting button 436j is selected, communication module address setting, data and video synchronization condition setting, waist, right knee, right toe, left knee and left toe acceleration waveform display setting, subject name, gender, etc. The system setting such as the input setting is performed, and it is determined whether or not the system setting is completed (step S10). When the data display screen 40j is selected, subject data such as the subject's name, age, and sex can be input. Further, an instruction to the effect that the system setting is completed is made by selecting a “setting completed” button (not shown).

If the system setting has not been completed (NO in step S10), the input is still performed, and the system setting is completed.
On the other hand, when the system setting is completed (YES in step S10), the measurement start button 430j is selected to determine whether or not a measurement start instruction has been issued (step S12).

  If no measurement start instruction is given (NO in step S12), the process waits until there is a measurement start instruction. On the other hand, when measurement start button 430j is selected and measurement start is instructed (YES in step S12), in order to start measurement from acceleration sensors 2a, 2b, 2c, 2d and 2e, via communication unit 4e An instruction to start measurement is transmitted to the data logger 3 (step S14).

  Imaging of the subject from the WEB camera 5 is started (step S16), moving image capturing is started (step S18), reception of acceleration data from the data logger 3 is started (step S20), and the acceleration data and the moving image are synchronized. Processing is performed (step S22), and the synchronized acceleration data and moving image are temporarily stored in the RAM 4b.

Next, a moving image and an acceleration waveform are respectively displayed on the moving image display screen 42j and the acceleration waveform display screen 41j (step S24), and whether or not the measurement end button 431j is selected and the measurement end is instructed by the measurer. A determination is made (step S26).
When the end instruction is not given (NO in step 26), the process returns to step S18, and the capturing of moving images, the reception of acceleration data, and the like are continued.

On the other hand, if an end instruction has been given (YES in step S26), the display of the acceleration data is received, the video is captured, and the video and acceleration waveforms displayed on the video display screen 42j and the acceleration waveform display screen 41j are terminated. The end instruction is transmitted to the data logger 3 via the communication unit 4e (step S28).
Next, the save button 435j is selected, and it is determined whether or not an instruction to save acceleration data or the like has been given (step S30).
If there is no save instruction (NO in step S30), the process returns to step S10 to change the system settings and perform re-measurement. The instruction not to save is made by selecting a “reset” button (not shown).

On the other hand, when a storage instruction is given (YES in step S30), the moving image, the transmitted acceleration data, and the like are stored in the data storage unit 4g (step S32).
At this time, when the playback button 433j is selected, a moving image or an acceleration waveform is played back.
It is determined whether or not the analysis button 434j is selected and an instruction for calculating the average acceleration is given (step S34).

If not instructed (NO in step S34), the process returns to step 10. An instruction not to calculate the average acceleration is made by selecting a “reset” button (not shown).
On the other hand, when the analysis button 434j is selected (YES in step S34), the average acceleration is calculated from the received acceleration data (step S36), and falls using the risk index stored in advance in the data storage unit 4g. The risk is evaluated (step S38), and the subject data table 15 shown in FIG. 30 is created (step S40).

  It is determined whether or not the print button 432j has been selected and a print instruction has been issued (step S42).

If no print instruction has been given (NO in step S42), the process returns to step S10 in order to measure a new subject. Note that an instruction not to print is performed by selecting a “reset” button (not shown).
On the other hand, if a print instruction is issued (YES in step S42), the subject data table 15 is printed (step S44), and it is determined whether the system end button 437j is selected and an end instruction is issued (step S46). .

If the system termination instruction has not been given (NO in step S46), the process returns to step S10 to measure a new subject. The instruction not to end is performed by selecting a “reset” button (not shown).
On the other hand, if the system end button 437j is selected and an end instruction is issued (YES in step S46), an end instruction is transmitted to the data logger 3 to end the system.

  Next, the operation of the data logger 3 will be described with reference to the flowchart shown in FIG. This operation is realized by the control unit 3a executing a program stored in a ROM (not shown).

  It is determined whether or not an instruction to start measurement is given from the lower limb coordination evaluation device 4 (step S60). If there is no instruction (NO in step S60), the process waits until there is an instruction.

On the other hand, when an instruction to start measurement is given (YES in step S60), measurement of each part is started from the acceleration sensors 2a, 2b, 2c, 2d and 2e (step S62).
Next, acceleration data is acquired from the acceleration sensors 2a, 2b, 2c, 2d, and 2e via the signal acquisition unit 3c (step S64), temporarily stored in the RAM 3c, and then generated for transmission acceleration data (step S66). .

Next, the transmission acceleration data is transmitted to the lower limb cooperation evaluation device 4 (step S68), and it is determined whether or not there is an instruction to end the measurement from the lower limb cooperation evaluation device 4 (step S70).
If there is no end instruction (NO in step S70), the process returns to step 64, and acceleration data is captured.

  On the other hand, when an end instruction is received from the lower limb cooperation evaluation device 4 (YES in step S70), the control unit 3a ends the measurement of the acceleration sensors 2a, 2b, 2c, 2d, and 2e.

As described above, the acceleration sensors 2a, 2b, 2c, 2d, and 2e measure the acceleration generated in the vertical direction, the horizontal direction, and the longitudinal direction of the left and right toe parts, the left and right knee joint parts, and the waist part. Is calculated, an optimal statistic is extracted for each part using ROC analysis, and a cutoff value related to the statistic is set as a risk index.
As a result, an objective risk index can be set, and a highly accurate fall risk evaluation can be performed.

  From the measured acceleration statistics of each part, statistics are extracted by taking into account vital function ability index, fall risk assessment, FRT and lower limb muscle strength that have been generally used as an index for preventing falls. Risk indicators are set. As a result, since various conventional methods for preventing falls can be taken in, it is possible to evaluate the fall risk with higher accuracy than the conventional measurement method.

  In the present embodiment, the average acceleration is calculated in the lower limb cooperation evaluation device 4, but the present invention is not limited to this. For example, the data logger 3 uses acceleration sensors 2a, 2b, 2c, 2d, and 2e. The average acceleration, which is a statistic related to acceleration, may be automatically calculated and used based on the smoothed voltage value after full-wave rectification after the acceleration signal is amplified.

  In this embodiment, all of the acceleration measurement values of 278 subjects (232 in the lower limb muscle strength) are used when extracting the risk index. However, the present invention is not limited to this. For example, the maximum value of the measurement values It is also possible to use only the remaining measured values with the minimum value removed. Thereby, for example, an abnormal value of measurement caused by malfunction of the acceleration sensor or the like is removed, and a risk index can be extracted with higher accuracy.

  The present invention can be used for the risk assessment of falls of the elderly and the physically handicapped.

1 ... Lower limb coordination evaluation system
2a, 2b, 2c, 2d, 2e ... Acceleration sensor 3 ... Data logger 4 ... Lower limb coordination evaluation device

Claims (4)

An acceleration measuring means that is mounted on a predetermined part of the human body and measures acceleration generated in the vertical direction, the left-right direction, and / or the front-rear direction during walking or exercise of the predetermined part;
Based on the measured acceleration, vertical predetermined portion, a calculation detecting means for calculating a statistic related to the acceleration with respect to the horizontal direction and / or longitudinal direction, respectively,
ROC against statistics related to the calculated acceleration; extract statistics used for evaluation of falling risk by performing (receiver operating Characteristic Receiver Operating Characteristic) analysis, associated with the statistical amount of the extracted And a setting means for setting a cut-off value as a risk index. The lower limb cooperation evaluation system according to claim 1 , further comprising an evaluation unit that evaluates a subject's fall risk based on the set risk index. It said predetermined portion of installing the acceleration measurement means, the left and right toe, a right and left knee joint and lumbar, leg coordination evaluation system according to claim 1 or 2. The calculation means integrates the absolute value of the acceleration generated during the walking operation or the exercise operation over a certain time during which the walking operation or the exercise operation is performed, and the integrated value is subjected to the walking operation or the exercise operation. The lower limbs cooperative evaluation system according to any one of claims 1 to 3 , wherein a statistic related to acceleration is calculated by dividing by a predetermined time.

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