JP5332292B2 - Walking analysis and exercise menu suggestion system - Google Patents

Description

  The present invention relates to a walking analysis and exercise menu suggestion system for obtaining a walking ability of a subject and proposing an appropriate exercise menu based on the obtained ability.

  Declining athletic ability is an urgent problem for the elderly, and there is a great demand for maintaining walking ability by carrying out appropriate exercise menus on a daily basis. In addition, in rehabilitation facilities, in order to improve the motor function of subjects whose walking ability has temporarily declined due to illness or accident, the subject's walking ability is requested and a preferable exercise menu is proposed for functional recovery. Yes. Measurement of walking ability and proposal of exercise menus are generally performed by skilled professional measurers and rehabilitation instructors. When proposing an exercise menu, it is necessary to make the exercise purpose, exercise content, and intensity appropriate so that no adverse effects such as falls occur.

  As described above, for example, there is a fall prevention guidance support system disclosed in Patent Document 1 as a system that obtains the walking ability of a subject and proposes an appropriate exercise menu that matches the walking ability or the fall risk. The system of Patent Document 1 measures foot pressure distribution data during a walking motion of a subject using a measuring instrument generally called a mattress-type pressure-sensitive walking analyzer, extracts features from the image processing data, and falls. The degree of danger is judged and a walking training instruction screen is displayed.

In addition, the fall prevention guidance support device disclosed in Patent Document 2 has the largest walking data from the state in which the subject walks a predetermined straight distance with maximum effort, and the subject has both legs aligned to the largest leg. Maximum step length data when the opposite leg is aligned to the side, and the subject ascends without raising the platform at the specified height without lifting the hand, and then stands straight on the platform and then descends to the other side The step-lifting data determined as to whether or not it can be input is input from the input unit as a fall avoidance ability evaluation value. Then, the control unit evaluates the fall avoidance ability evaluation value and decides the guidance items, creates a balance chart for guidance on fall prevention, creates an aging graph, and prints out the balance chart and the aging graph. It is supposed to be. Furthermore, the storage unit is configured to store a fall avoidance capability reference value file, a guidance item selection file, a measurement history file, and an average value data file.
JP 2002-345786 A JP 2006-102462 A

  In the technique disclosed in Patent Document 1, when the pedestrian naturally walks about 3 to 5 steps on the mattress, the pressure sensor below the mattress detects the foot pressure, and the system walks based on the image time series data. Analyzing the walking motion of the person. In addition, the numerical data obtained is the ratio between the stride and the step (distance between the reference points of the left and right feet in the direction orthogonal to the walking direction), and the ratio between the pedestrian's foot load and the pressure area. Yes, the risk of falling is calculated based on these numerical data. Furthermore, a graph in which these numerical values and the actual walking pattern of the pedestrian and the ideal pattern are superimposed is displayed as a walking training instruction screen. However, these numerical values and graphs are abstract, and it is difficult for an inexperienced instructor to instruct based on the walking training instruction screen. Moreover, the measuring equipment is long and expensive, and the measuring operation is difficult. Further, it is troublesome to input the data obtained by the measuring equipment into the system again, and there is a risk of an input error or data loss.

  On the other hand, as a conventional method for measuring the stride, a simple method for measuring the interval between footprints by walking on a dry floor with water on the feet is performed. Although this method has a low equipment cost, it takes a lot of time for measurement operation and data recording and storage.

  In the technique of Patent Document 2, the ability to avoid falls is calculated from the measurement results when the subject performs each measurement item of “10m full power walking”, “maximum one step width”, “following leg walking”, and “40 cm step up / down”. I am evaluating. However, since it is necessary to perform many measurement items and obtain a large number of indices, it has been a burden on both the subject and the measurer. In addition, when the subject's walking ability is reduced, there are some measurement items that make it difficult to obtain measurement accuracy or make the implementation itself difficult. For example, in the case of a subject who may fall, place one foot on the left or right on a 5cm wide cloth tape affixed to the floor, and take a posture where the foot of the other foot is in contact with the toe of the foot. Then, “next leg walking”, in which this is continued alternately and counting the number of steps made in succession, may not provide measurement accuracy. In addition, “40cm step up / down”, which determines whether it is possible to climb the 40cm step without climbing the hand, and to get down to the other side after standing upright with both legs on the stand, ensures the safety of the subject. It may not be possible to implement.

  Conventionally, only an index indicating the total walking ability of both the left and right feet or an index obtained individually for the left and right feet has been used. In other words, the index indicating the ratio of the walking ability of the left and right feet or the degree of symmetry was not used. This left-right symmetry index is effective as a judgment material when determining a fall risk and proposing an exercise menu.

  The present invention has been made in view of the current situation as described above, and measures walking motion that can be performed on a daily basis by a subject to detect walking ability including a symmetry index, to prevent falls and exercise. Provided is a gait analysis and exercise menu suggestion system that can propose exercise menus for improving functions and has a simple configuration and easy and inexpensive measurement operation and data management.

  The present inventors have already filed an application in Japanese Patent Application No. 2007-077735 for a system that proposes an exercise menu by determining walking risk by measuring walking ability that can be performed on a daily basis to determine walking ability. Then, earnest study was advanced, and it was conceived that an index indicating the ratio or the degree of symmetry of the walking ability of the left and right feet is effective as an index of walking ability, and the present invention in which the applied system was improved was completed.

That is, the walking analysis and exercise menu suggestion system of the present invention that solves the above-mentioned problem is a walking ability detection means for determining walking ability by measuring a walking motion of a subject, and discriminating a fall risk of the subject from the obtained walking ability. A fall risk discriminating means, an exercise menu suggesting means for proposing a fall prevention menu and an exercise menu for improving the locomotor function in accordance with the walking ability or the fall risk of the previous period, and the exercise menu and the walking ability and the fall A walking analysis and exercise menu suggestion system having notification means for notifying at least one of the risks, wherein the walking ability detection means is symmetric for obtaining an index indicating a left / right stride ratio representing a ratio of a left leg stride length and a right leg stride length The walking motion that is the target of the symmetry detecting means includes a sex detecting means, and is Characterized in that it is a walking operation of the constant distance or intermediate portion except for the fixed number of steps and end.

  The walking analysis and exercise menu suggestion system of the present invention can be composed of walking ability detection means including symmetry detection means, fall risk determination means, exercise menu suggestion means, and notification means. Each means can be realized by, for example, a personal computer and its peripheral devices and software. The symmetry detecting means can be realized by software as a part of the walking ability detecting means. Needless to say, “determining walking ability” means obtaining an index such as walking speed and stride indicating the level of walking ability by quantitatively quantifying.

The indicator of walking ability required by the symmetry detection means is a left / right stride ratio that represents a ratio between the left foot stride and the right foot stride. For example, when the left foot stride length L when the left foot is stepped on and the right foot stride length R when the right foot is stepped on, the left / right stride ratio X is obtained by the following equation.
X = L / (L + R): R / (L + R)
If the left / right stride ratio X = 50: 50, it can be said that the left and right stride are equal. The symmetry index including the left / right stride ratio can be used as a reference when determining the fall risk. In addition, when selecting an exercise menu, it is possible to propose different exercise types and different exercise intensities on the left and right. Furthermore, the left-right symmetry index is considered to be effective for finding potential illnesses and injuries on either foot and for comparative evaluation of the degree of walking ability improvement.

X = L / (L + R): R / (L + R)
If the left / right stride ratio X = 50: 50, it can be said that the left and right stride are equal. The symmetry index including the left / right stride ratio can be used as a reference when determining the fall risk. In addition, when selecting an exercise menu, it is possible to propose different exercise types and different exercise intensities on the left and right. Furthermore, the left-right symmetry index is considered to be effective for finding potential illnesses and injuries on either foot and for comparative evaluation of the degree of walking ability improvement.

  The walking motion targeted by the symmetry detection means may be a walking motion at an intermediate portion excluding each predetermined distance at the beginning and end of the walking motion at a predetermined distance.

  Further, the walking motion targeted by the symmetry detecting means may be a walking motion at an intermediate portion excluding a fixed number of steps at the beginning and end of the walking motion at a predetermined distance.

  Furthermore, it is preferable that the left / right stride ratio is obtained using an average left foot stride and an average right foot stride obtained from a plurality of left foot stride and right foot stride, respectively.

  There is no restriction on the form of the walking motion of the subject targeted by the symmetry detection means, but it is a condition that the steps of the left and right feet, which are the premise for obtaining the right / left step ratio, can be obtained. If the walking motion of the middle part excluding each fixed distance at the beginning and the end of the walking motion of a predetermined distance is targeted, the irregular walking motion at the beginning and the end of walking is deleted, and only the stable walking motion in the middle The accuracy of the left / right stride ratio is improved. In addition, if the walking motion of the intermediate portion excluding the fixed number of steps at the beginning and the end of the walking motion of a predetermined distance is targeted, only the stable walking motion in the middle can be targeted and the step length is obtained. In addition, the complexity of performing fraction processing of less than one step is eliminated. When the middle stable walking motion is a plurality of left and right steps, the left and right stride ratios can be obtained from the average left foot stride and the average right foot stride obtained by calculating an average value for each of the left and right.

  It is preferable that the walking motion is a single walking mode in which the subject walks at a normal speed only in a normal walking motion, or a two-walking mode in which the subject walks at full power and the normal walking motion.

  The form of the walking motion can be a one-walking mode with only a normal walking motion in which the subject walks at a normal speed, and a two-walking mode can be added by adding a full-strength walking motion in which the subject walks at full power. Measurement and data processing can be easily performed in the case of the one walking form, and in the case of the two walking form, the types of indicators of walking ability can be increased and the fall risk determination accuracy can be improved.

  The walking ability detection means includes acceleration measuring means that is attached to the waist of the subject and measures acceleration during walking motion, and walking ability estimation means that estimates the walking ability based on the measured acceleration. Is preferred.

  The walking ability detection means can be composed of acceleration measurement means and walking ability estimation means. The acceleration measuring means is attached to the subject's waist and measures the acceleration during the walking motion. The acceleration measuring means can be configured to continuously measure at least the acceleration in the front-rear direction of the waist of the subject, that is, the walking direction. Moreover, you may make it measure continuously the acceleration of 3 directions including an up-down direction and a left-right direction.

  The walking ability estimation means is a means for estimating a walking ability index such as a walking speed, a stride, and a left / right stride ratio from the measured acceleration data. A correlation estimation formula can be used for this estimation. More specifically, an indicator of walking ability is measured using a standard measuring instrument for a large number of preliminary subjects in advance, and accelerations in three directions are simultaneously measured. Then, a correlation analysis between the walking ability index and the acceleration is performed to confirm that there is a correlation, and a correlation estimation expression that represents the walking ability index as a function of acceleration is obtained. Thereafter, when the acceleration is measured for the subject and the actually measured acceleration value is substituted into the correlation estimation formula, the indicator of the walking ability of the subject can be estimated.

  As another method for obtaining the stride by the walking ability estimating means, mathematical integration can be used. In other words, the walking speed can be obtained by integrating the measured acceleration with the initial position of the position at the start of walking and zero speed, and the walking distance can be obtained by performing another integral calculation. Furthermore, the feature point of the acceleration change and the walking motion can be associated with each other, the one-step time required for one step can be obtained, and the stride can be obtained from the walking speed and the one-step time.

  The walking ability detecting means may obtain at least one of walking speed, stride, pace, knee extension force, ankle dorsiflexion force in addition to the left / right stride ratio.

  The walking ability detecting means including the symmetry detecting means may obtain at least one of walking speed, stride, pace, knee extension force, ankle dorsiflexion force as well as the left / right stride ratio as an indicator of walking ability. Good. Of the above indices, the stride has already been obtained in the process of obtaining the left / right stride ratio. Other indices can be obtained by the same method as the correlation estimation equation for obtaining the above-mentioned stride. By increasing the index of walking ability, it is possible to improve the determination accuracy of the fall risk described later, and to further optimize the proposed exercise menu.

  The fall risk discriminating means can discriminate the magnitude of the fall risk from the obtained walking ability level. For example, the risk of falling can be determined as one of four stages of danger of falling, attention to falling, attention to whispering, and no problem (goodness).

  The exercise menu suggesting unit may hold the exercise menu for each of a plurality of exercise purposes, and select and propose the exercise menu that matches the obtained walking ability or the fall risk.

  It is preferable to prepare a large number of exercise menus from intense exercise to light exercise, and also consider the number of exercises and the execution time. The exercise menu proposing means can be configured to hold all these exercise menus and select and propose an exercise menu that matches the required walking ability or risk of falling.

  Further, the exercise menu proposing means holds a symmetry improving exercise menu whose purpose of exercise is to improve symmetry, and selects and proposes the symmetry improving exercise menu that matches the obtained left / right stride ratio. Is preferred.

  For subjects whose left / right walking ability is not symmetric, prepare a dedicated symmetry-enhancing exercise menu for the purpose of exercise to improve symmetry, hold it in the exercise menu suggestion means, A symmetry enhancement exercise menu that matches the ratio can be selected and proposed.

  The notification means notifies the exercise menu and at least one of the walking ability and the risk of falling. As the notification means, for example, a display of a personal computer can be used, and necessary information including an exercise menu can be displayed and notified to a subject or a rehabilitation instructor. As the notification means, the output printer may be used to print and notify necessary information, and other information notification media may be used.

  The notification means may notify a time series change of at least one of the walking ability and the fall risk.

  For a subject who repeatedly uses the system, the notification means can notify the time series change of at least one of walking ability and fall risk. Then, it is convenient because the state of change in walking ability and the effect of the exercise menu performed can be easily confirmed.

  A part or all of the walking ability detection unit, the fall risk determination unit, the exercise menu suggestion unit, and the notification unit may be coupled by a wired communication unit or a wireless communication unit.

  By combining each means with a communication means, the system of the present invention can be used even from a remote location. Also, data can be managed centrally, eliminating the need for re-input, and there is no worry of input mistakes or data loss, which is efficient.

In the walking analysis and exercise menu suggestion system of the present invention, it is possible to obtain an index of the right / left stride ratio effective for the fall risk determination and the exercise menu suggestion only by measuring the walking motion of the subject, in addition, the predetermined distance Since only the middle stable walking motion is targeted, the accuracy of the left / right stride ratio is improved and the practical performance is enhanced. Furthermore, the index of the left / right stride ratio is effective for finding potential diseases and injuries and for comparative evaluation of the degree of functional recovery of the left and right feet.

  Further, in the aspect having the acceleration measuring means, it is only necessary to measure the waist acceleration during the walking motion of the subject, so that the burden on the subject and the measurer is larger than the conventional method that requires many measurement items. The apparatus configuration is simple and inexpensive.

  Furthermore, in a mode in which the respective means are coupled by the communication means, data can be managed in a centralized manner, and there is no need for re-input, and there is no fear of input mistakes or data loss, which is efficient.

  The best mode for carrying out the present invention will be described with reference to FIGS. FIG. 1 is a functional block diagram illustrating a walking analysis and exercise menu suggestion system 100 according to an embodiment of the present invention. As shown in the figure, the system 100 according to the embodiment includes a walking ability detection unit 1, a fall risk determination unit 2, an exercise menu suggestion unit 3, and a notification unit 4. The walking ability detection means 1 includes an acceleration measurement means 5 and a walking ability estimation means 6, and the walking ability estimation means 6 includes a symmetry detection means 7.

  The acceleration measuring means 5 is a means for measuring the waist acceleration during the walking motion of the subject, the walking ability estimating means 6 is a means for estimating an indicator of walking ability from the waist acceleration, and the symmetry detecting means 7 is a right and left from the waist acceleration. It is a means for estimating the stride ratio. Moreover, the fall risk discriminating means 2 is a means for discriminating the fall risk from the walking ability. The exercise menu suggesting means 3 is a means for selecting and proposing an appropriate one from a large number of exercise menus stored in the database 8 with reference to walking ability and fall risk. The notification means 4 is means for notifying the subject and the rehabilitation instructor of walking ability, fall risk, exercise menu to be selected and proposed.

  Each of the means 1 to 7 is realized by hardware including an accelerometer, a computer, and peripheral devices, and software executed on the computer. FIG. 2 is a hardware configuration diagram illustrating an actual configuration of the system 100 according to the embodiment. The system 100 of this embodiment includes an accelerometer 10 that measures walking motion, a computing unit 20 that estimates the walking ability of a subject, determines a fall risk, and selects and proposes an exercise menu, a time measuring unit 30 that measures walking time, and the like. The display unit 40 that notifies walking ability, the risk of falling, and the exercise menu, and the recording unit 50 that stores various types of information are actually configured.

  The accelerometer 10 corresponds to the acceleration measuring means 5 and is attached to the waist when the subject is walking to detect acceleration. The accelerometer 10 includes a walking direction, that is, an X-direction acceleration detection unit 12 in the front-rear direction, a Y-direction acceleration detection unit 14 in the left-right direction, and a Z-direction acceleration detection unit 16 in the up-down direction. Each of the detection units 12, 14, and 16 is integrated, and can detect all of the longitudinal acceleration, the lateral acceleration, and the vertical acceleration. The accelerations in the three directions are output to the calculation unit 20 as independent longitudinal acceleration signals, lateral acceleration signals, and vertical acceleration signals.

  As the accelerometer 10, a generally known acceleration sensor can be used. For example, a triaxial acceleration sensor using a piezoelectric element, a capacitance type triaxial acceleration sensor, or the like can be used. In the case of a triaxial acceleration sensor, the longitudinal acceleration detection unit 12, the lateral acceleration detection unit 14, and the vertical acceleration detection unit 16 can be a single detection element. Alternatively, a uniaxial or biaxial acceleration sensor may be used in combination.

  The arithmetic unit 20 includes an A / D converter 22, a CPU 24 as an arithmetic device, and a ROM 26 and a RAM 28 as storage devices. The A / D converter 22 converts the analog acceleration signal input from the accelerometer 10 into a digital acceleration signal. The digital acceleration signal output from the A / D converter 22 is temporarily stored in the RAM 28, and predetermined processing is performed by the CPU 24. For example, the digital acceleration signal is processed together with the time information input from the time measuring unit 30 and stored in the RAM 28 as a time change waveform for several steps of walking motion.

  The ROM 26 stores software corresponding to the walking ability estimation means 6. That is, software for obtaining the walking ability by extracting the start time and end time of a specific walking motion and a specific period from the time change waveform of the acceleration signal in three directions stored in the RAM 28 is stored. Further, the ROM 26 also stores software corresponding to the other means 2, 3, 4. These software programs are executed as needed.

  Next, the walking motion will be described with reference to FIG. FIG. 3 is a diagram illustrating a time-varying waveform of a walking motion and a corresponding acceleration signal. Walking refers to alternately swinging left and right feet forward. A leg that touches the ground and supports weight is called a stance leg, and a leg that swings forward from the ground is called a free leg. In each of the left and right legs, there is a stance phase in which the foot is attached to the ground and a swing phase in which the foot is separated from the ground. A period in which both feet are in the stance phase simultaneously is a both-leg support period A, and a period in which only one leg is in the stance phase is a single-leg support period B.

  The stance phase starts when the heel of the foot that has become a free leg is in contact with the ground (heel contact), and the bottom of the foot is in contact with the ground substantially along the toe (ground). The bottom of the foot), the state where the bottom of the foot is in contact with the floor surface, the state where the heel part is separated from the floor surface (the heel-off ground), and the toes (toes) are separated from the floor surface. End in a state of leaving (toe away). Accordingly, the stance phase is from the heel grounding to the toe-seated ground, and the free leg phase is from the heel-landing to the heel grounding.

  The specific walking motion indicates any one of the heel contact operation, the sole contact operation, the toe-off operation and the like shown in FIG. The heel contact operation is an operation in which the heel of one foot is in contact with the ground, the sole contact operation is an operation in which the entire sole of the one foot is grounded, and the toe release operation is performed by the foot apex of the other foot. Is the action.

  Next, the walking ability estimation means 6 will be described. The walking ability estimation means 6 includes a period extraction means, an estimated index calculation means, and a walking ability calculation means implemented by software. The period extracting means extracts a point in time when the above specific walking motion starts and ends, and a specific period that continues. The estimated index calculation means calculates the estimated index based on the extracted acceleration in the three directions within the specified period. The estimated index is a parameter that mediates the relationship between acceleration and walking ability. The walking ability calculation means calculates the walking ability from the estimated index using a relationship (for example, a relational expression) between the estimated index and the walking ability stored in the ROM 26. A part of the walking ability calculating means is a symmetry detecting means 7 for calculating the right / left stride ratio.

  The fall risk discriminating means 2 is also realized by software, and the fall risk is discriminated based on the calculated walking ability. At the time of determination, the correspondence relationship between the level of walking ability obtained in advance and stored in the ROM 26 and the multi-step fall risk is used.

  Similarly, the exercise menu proposing means 3 is also realized by software, and selects and proposes an appropriate exercise menu with reference to at least one of walking ability and fall risk. In selecting and proposing, the correspondence between the walking ability and the risk of falling and the many exercise menus which are obtained in advance and stored in the ROM 26 is used.

  The walking ability estimated as described above, the determined fall risk and the proposed exercise menu can be temporarily stored in the RAM 28, and can be stored in the recording unit 50 automatically or by operation.

  The display unit 40 corresponding to the notification unit 4 displays the walking ability, the fall risk, and the exercise menu automatically or by operation. Note that an unillustrated input unit for inputting subject information and the like is provided, and the display unit 40 also displays information such as the subject and date. In addition, past measurement results stored in the recording unit 50 are also displayed. Furthermore, an output printer (not shown) that prints out the result as a notification means 4 is also provided.

  Next, the operation and action of the walking analysis and exercise menu suggestion system 100 according to the embodiment configured as described above will be described. FIG. 4 is a flowchart illustrating the operation and operation of the system 100 according to the embodiment.

  In FIG. 4, first, as a measurement preparation, the accelerometer 10 is attached to the waist of the subject. (Step S1). Next, acceleration is measured in conjunction with the walking motion of the subject. The acceleration signals in the three directions of the waist detected by the accelerometer 10 are digitally converted by the A / D converter 22 and temporarily stored in the RAM 28 (step S2). Next, the CPU 24 creates a time-varying waveform of acceleration in three directions (step 3).

  At this time, the test subject's walking motion is a normal walking and full power walking. Further, the predetermined distance of the walking motion is measured as 16 m, and the CPU 24 treats the walking motion of the intermediate portion excluding 4 steps each of the start and end of walking as effective data. Since the walking distance of 4 steps generally corresponds to about 3 m, the walking ability is obtained by using a stable walking motion of about 10 m as effective data. Alternatively, the measurement may be performed with a walking motion of 16 m, and the CPU 10 may treat the walking motion of 10 m in the middle portion excluding 3 m at the beginning and the end of walking as valid data. In this case, the fraction less than one step at both ends of 10 m can be handled by deleting, for example. From 10 m of effective data, effective stride data of about 6 to 7 steps on the left and right can be obtained. As another alternative, measurement is performed with a walking motion of 11 m, and the CPU 24 treats the walking motion of approximately 5 m in the middle portion excluding 4 steps at the beginning and the end of walking or 3 m at each end as valid data. Good. In this alternative method, effective stride data of about three steps on the left and right is obtained.

  Subsequent to step 3, the CPU 24 determines the time point and the specific period when the specific walking motion is performed from the time change of the acceleration signal by the software of the period detection means (step S4). Specifically, (1) the time point at which the acceleration signal reaches a peak value is detected by differentiating the acceleration signal with respect to time, or (2) one acceleration selected from longitudinal acceleration, vertical acceleration, and lateral acceleration. Attention is paid to the detection of a point of time when the signal changes from positive to negative or from negative to positive, or (3) a point of time when the acceleration reaches a certain predetermined ratio with respect to the peak value of the acceleration signal. These detected time points are the time points when a specific walking motion starts or ends.

  A criterion for determining which of the methods (1) to (3) is used can be stored in the ROM 26 in advance and can be automatically selected at the time of execution. In addition, the ROM 26 can also set which direction of acceleration is selected by the method (2) or what a predetermined ratio is to be selected by the method (3). Furthermore, among the methods (1) to (3), the most appropriate method may be selected as needed, or a method in which these methods are appropriately combined may be employed.

  As an example, a description will be given of the flow of starboard contact detection criterion software by the method (2). A negative peak with large longitudinal acceleration is detected (step S401), and a minimum point of longitudinal acceleration immediately before the negative peak is detected (step S402). Next, it is determined whether or not there is a point where the lateral acceleration changes from positive to negative between the negative peak and the minimum point (step S403). When the point at which the lateral acceleration changes from positive to negative is within the above range, the change point is determined as the point of (right) heel contact operation (step S404). If the point at which the lateral acceleration changes from positive to negative is not within the above range, the minimum point is determined as the time point of the (right) heel contact operation (step S405). Note that the above description is a determination on (right) heel contact, and when (left) heel contact is determined, in step S403, the lateral acceleration is changed from negative to positive between the negative peak and the minimum point. What is necessary is just to determine whether there exists a point to change.

  Subsequent to step 4, the determined specific time point and specific period of the specific walking motion are stored in the RAM 28 (step S5). Next, the CPU 24 calculates an estimated index during a specific period of a specific walking motion by software of the estimated index calculation means. (Step S6).

  As an example, a flow of software for calculating an estimation index V1 described later will be described. A point in time when the longitudinal acceleration changes from positive to negative is detected (step S601), and then a point in time when the longitudinal acceleration changes from negative to positive is detected (step S602). Further, a one-step time that is a time from the time when the one foot is touched to the other foot is calculated (step S603). The two detected time points and the calculated one-step time are substituted into a calculation formula described later to calculate the estimated index V1 (step S604).

  In this embodiment, seven estimated indices V1 to V7 are calculated, and the CPU 24 stores the calculated estimated indices in the RAM 28 (step S7). Next, the CPU 24 calculates the walking ability by the software of the walking ability calculation means. Specifically, when calculating the walking speed and the stride as the walking ability, the CPU 24 substitutes each estimated index calculated in the walking speed calculation formula and the stride calculation formula stored in the ROM 26 (step S8). Since each index of the walking ability is calculated for each step of the effective walking motion, the average value, the maximum value, and the minimum value of the left and right feet during the walking motion are obtained. The knee extension force and ankle dorsiflexion force can be calculated in the same manner.

  Next, the CPU 24 uses the calculated average left foot stride length L and average right foot stride length R to obtain the left / right stride ratio X by the following equation (step S9).

Left / right stride ratio X = L / (L + R): R / (L + R)
The calculated walking speed, stride, and left / right stride ratio are temporarily stored in the RAM 28, and stored in the recording unit 50 automatically or by operation (step S10). Thus, the operation for obtaining the walking ability is completed.

  Subsequently, the name, age, height, weight, and gender are input as subject information. (Step S11). Next, the stored walking speed, stride, and left / right stride ratio data are read again. These data may be measured by another measuring device and input separately (step S12). Using the read walking speed and stride, the pace is calculated by the following equation (step S13).

Step (step / min) = walking speed (m / sec) ÷ step length (m) × 60
Next, the fall risk of the subject is determined based on the list of FIGS. 5 and 6 based on the combination of the walking speed, the stride, and the gait values obtained. (Step S14). FIG. 5 is a list for determining a fall risk based on measurement data in a normal walking form. As shown in the table, the walking speed is 0.69 (m / sec) or less, 1.5 (m / sec) or more, and the interval between them is divided into multiple stages, the stride is 0.49 (m) or less, and 0. 8 (m) or more and the interval between them are divided into many stages, and the pace is divided into two stages of 90 (step / min) or less and 91 (step / min) or more. And the fall risk is discriminated by the combination of each stage. For example, when the walking speed is 0.69 (m / sec) or less and the step length is 0.49 (m) or less (step / min) or less, it is determined that “there is a risk of falling”. If the walking speed is 1.5 (m / sec) or higher, the step length is 0.8 (m) or higher, and the butterfly 91 (step / min) is higher, it is determined that there is no problem.

  FIG. 6 is a list for determining the risk of falls based on the measurement data in the full power walking mode, and the boundary values between the stages are different from those in the normal walking mode. In these two lists, the risk of falling is divided into four stages: danger of falling, attention to falling, attention to whispering, and no problem. The boundary values between the illustrated steps can be appropriately set according to the physique, age, sex, walking form (normal walking, full power walking), etc. of the subject.

  The determined fall risk is temporarily stored in the RAM 28 and further stored in the recording unit 50 automatically or by operation. (Step S15).

  In this embodiment, the right / left stride ratio is not directly used for the fall risk determination. However, if the right / left stride ratio is not balanced, the fall risk increases, and this can be quantitatively evaluated and reflected in the fall risk discrimination. For example, the list of FIG. 5 and FIG. Risks can be added in stages.

  Next, on the basis of the determined fall risk, an appropriate selection for fall prevention and improvement of exercise function is selected from a pre-stored exercise menu (step 16). At this time, the exercise menu can be selected with reference to not only the fall risk but also the walking ability. For example, when the left / right stride ratio of the subject is not balanced, an exercise menu suitable for an exercise purpose for improving the balance function can be recommended, the exercise type can be changed left and right, and the exercise intensity can be changed left and right.

  As described above, the CPU 24 calculates an index of walking ability, determines a fall risk, and selects an exercise menu. Finally, the CPU 24 displays the exercise menu together with other information on the display unit 40 and notifies it (step S17). Other information includes walking ability, fall risk, subject information, etc., and includes past data. These pieces of information may be selected and displayed by operation, or all information may be automatically displayed. Further, the exercise menu desired by the subject can be selected, and the details of the selected exercise menu can be displayed.

  Next, details of a method for calculating the walking speed and the stride using the estimated index will be described. First, the reasons for selecting the seven estimated indexes V1 to V7 used when calculating the walking speed and the stride and the calculation formulas will be described.

  (Estimated index V1) Although the forward speed, that is, the walking speed can be calculated to some extent by integrating the longitudinal acceleration, the influence of the integration error is large and there is a problem in the estimation accuracy. Therefore, I thought as follows. Walking motion is a repetition of acceleration and deceleration operations. When you look at the ratio of the time to accelerate (acceleration time) and the time to decelerate (deceleration time), the longer the time to accelerate, the faster the walking Therefore, the ratio of the deceleration time in one step time can be used as an estimation index. In this case, the deceleration time corresponds to the time from the point at which the maximum speed is obtained in the front-rear direction (referred to as the front-rear maximum speed position) to the point at which the minimum speed in the front-rear direction (referred to as the front-rear minimum speed position). Therefore, the estimated index V1 is determined by the following calculation formula.

Estimated index V1 = Time from the front and rear maximum speed position to the front and rear minimum speed position / step time Acceleration is a derivative of speed. Therefore, in FIG. 3, the point where the front and rear speeds are maximum is where the acceleration crosses the time axis from positive to negative, and the point where the front and rear speeds are minimum is where the acceleration crosses the time axis from negative to positive. Therefore, “the time from the maximum speed position to the minimum speed position” is “the time when the longitudinal acceleration becomes negative to positive“ − ”the time when positive and negative becomes positive”.

  Here, in order to confirm the correlation between the estimated index V1 and the walking speed, a correlation analysis was performed using data measured by a large number of preliminary subjects. That is, the X-axis is the estimated index V1, the Y-axis is (walking speed / height), and the data of the preliminary subjects are plotted to create a correlation graph. The walking speed on the Y axis is an actual measurement value measured using a three-dimensional motion analysis system different from the present embodiment. Moreover, in order to reduce and standardize the influence of individual differences, a value obtained by dividing walking speed by height was used. In this correlation graph, the smaller the rate of deceleration time in one step time, the larger the value obtained by dividing the walking speed by the height, and there is a negative correlation between the estimated index V1 and the value obtained by dividing the walking speed by the height. Admitted. Note that the normalization by dividing the walking speed and the stride by the height is performed in common for the other estimated indexes V2 to V7.

  (Estimated index V2) When a large positive acceleration occurs, a large negative acceleration occurs. When the walking speed is fast, the acceleration change is considered large. Therefore, the negative longitudinal acceleration indicating deceleration during the one-step period was considered to reflect the walking speed.

  When the acceleration change is large, the energy consumption increases. Since the estimated index V1 and the walking speed are correlated as described above, it can be seen that when the walking speed is high, the time spent for the acceleration operation becomes longer in one step time. In other words, when large braking (negative acceleration) occurs, it is considered that the acceleration time was long. This is considered to be walking such that the energy consumption does not increase as much as possible, and it is considered that the normal walking is based on the assumption that the movement is performed with the minimum energy consumption. Therefore, the estimated index V2 is obtained by the following calculation formula.

Estimated index V2 = Integral value of the longitudinal acceleration / integration period time from the point at which the longitudinal acceleration changes from positive to negative to the point from negative to positive
"The integrated value of the longitudinal acceleration from the point at which the longitudinal acceleration changes from positive to negative to the point at which it changes from negative to positive" means the longitudinal acceleration in the period representing the "time from the maximum speed position to the minimum speed position" of the estimated index V1 Is a value obtained by integrating over time. That is, the estimated index V2 is a value obtained by dividing the integral value by the integration period time, and means an average deceleration during the deceleration operation. Further, when a correlation analysis between the estimated index V2 and (walking speed / height) was performed, a negative correlation was found between them.

  (Estimated index V3) The body center of gravity during walking repeatedly moves up and down. The position of the center of gravity of the body is lowest when the heel is touched, and is highest when the body is in an upright state (mid stance). After the middle stage of stance, when the foot is swung forward, the center of gravity of the body moves downward and becomes the lowest point when the heel touches.

  Therefore, the upward acceleration generated when the center of gravity moves upward, the upward deceleration acceleration generated when the upward moving speed is decelerated, and the downward acceleration generated when the center of gravity moves downward also reflect the walking speed. it is conceivable that. Since the upward acceleration is considered to be caused by vibration due to the impact at the time of ground contact, attention was paid to the upward deceleration acceleration and downward acceleration, which are considered to be less affected by the vibration due to external force.

  The middle stance phase appears after the toes leave. Therefore, we thought that the negative acceleration in the vertical acceleration after the toe-off shows the vertical deceleration acceleration just before the middle stance and the downward acceleration of the body center of gravity by swinging the foot forward. The positive vertical acceleration immediately before the heel contact was considered to be an acceleration for decelerating the downward speed to mitigate the impact force at the heel contact. This operation of impact relaxation can be said to be based on the assumption that muscle load at the time of saddle contact (braking period) can be reduced and energy consumption is suppressed. The sum of absolute values of both integral values considered to reflect the walking speed was used as the estimated index V3.

Estimated index V3 = | Deceleration amount of upper speed / period time | + | Deceleration amount of lower speed / period speed |
The “deceleration amount of the upward speed” indicates a time integral value of the vertical acceleration over a period from the tip of the foot to the point where the vertical acceleration changes from negative to positive. Therefore, | the amount of deceleration of the upward speed / period time | means the absolute value of the average deceleration in the vertical direction in this specific period. Further, the “deceleration amount of the downward speed” indicates a time integration value of the vertical acceleration with a specific period from the point at which the vertical acceleration changes from negative to positive to the heel contact. Therefore, | the amount of deceleration of the downward speed / period time | means the absolute value of the average acceleration in the vertical direction during this specific period. Further, when a correlation analysis between the estimated index V3 and (walking speed / height) was performed, a positive correlation was found between the two.

(Estimated index V4)
Estimated index V4 = (integration of longitudinal acceleration from right [left] 踵 contact to left [right] 踵 contact, difference between maximum speed and minimum speed) / (time from maximum front and rear speed position to minimum front and rear speed position) / Step time)
Here, when a correlation analysis was performed between the estimated index V4 and (walking speed / height), a positive correlation was found between the two.

  (Estimated index V5) Next, integrate the longitudinal acceleration from the right foot apex in the first acceleration phase to the late right stance phase (the point where the vertical acceleration changes from negative to positive after the foot apex) and before and after the right stance phase The speed was set as an estimated index V5 of walking speed (similarly, the longitudinal speed at the late stage of the left stance can also be used).

Estimated index V5 = Integral value of longitudinal acceleration from right [left] toe separation to right [left] late stance Here, when a correlation analysis between estimated index V5 and (walking speed / height) was performed, There was a positive correlation between them.

  (Estimated index V6) Next, the speed calculated by integrating the vertical acceleration from the initial stage of stance (the first point at which the vertical acceleration changes from positive to negative after the point of foot separation) to the late stage of stance and the other leg from the late stage of stance. The magnitude of the sum of the speeds calculated by integrating the vertical acceleration until the ground contact of the heel was set as the estimated index V6.

Estimated index V6 = | the sum of the integrated value of the vertical acceleration from the initial stance phase of one foot to the late stance phase and the integrated value of the vertical acceleration from the late stance phase of one foot to just before the heel contact of the other foot When a correlation analysis between the estimated index V6 and (walking speed / height) was performed, a positive correlation was found between the two.

(Estimated index V7)
Estimated index V7 = estimated index V6 / estimated index V1
Here, when a correlation analysis between the estimated index 7 and (walking speed / height) was performed, a positive correlation was found between the two.

  Next, a walking speed estimation formula for determining the walking speed using the estimation indexes V1 to V7 will be described. The walking speed estimation formula can be expressed by a linear function obtained by multiplying any one estimated index by a coefficient based on the result of the correlation analysis. In addition, in order to improve the accuracy, multiple regression analysis can be performed to obtain an estimation formula using a plurality of estimation indices. An example of an estimation formula using the estimation indexes V1 to V3 is shown below.

Estimated walking speed = 0.249 × V1−0.091 × V2 + 0.049 × V3 + 0.269
The estimated walking speed was calculated by substituting the estimated indices V1 to V3 calculated from the measurement data of the preliminary subject into the above estimation formula, and the correlation with the actually measured walking speed was confirmed. That is, when a correlation graph in which the measurement data of the preliminary subjects were plotted with the X axis as (estimated walking speed / height) and the Y axis as (actual walking speed / height) was created, a high positive correlation was recognized.

  Further, when the estimation indexes V4 to V7 were used, the following estimation formula was obtained.

Estimated walking speed = 0.18 × V4 + 0.56 × V5 + 0.69 × V6-0.15 × V7 + 0.38
Even in this estimation formula, a high positive correlation was observed.

  Next, a stride estimation formula for obtaining a stride can be expressed by a formula obtained by multiplying one or a plurality of estimation indices by a coefficient and a constant, similarly to the walking speed estimation formula. For example, when the estimation indexes V4, V6, and V7 are used, the following estimation formula is obtained.

Estimated stride = 0.11 × V4 + 0.27 × V6-0.06 × V7 + 0.24
Estimated strides were calculated by substituting the estimated indices V4, V6, and V7 calculated from the measurement data of the preliminary subjects into the above estimation formula, and the correlation with the actually measured stride was confirmed. That is, when a correlation graph in which the measurement data of the preliminary subject was plotted with the X axis as (estimated stride / height) and the Y axis as (actual stride / height) was created, a high positive correlation was recognized.

  As explained above, by performing correlation analysis and obtaining the estimation index calculation formula, the walking speed estimation formula, and the stride estimation formula, it becomes clear that the walking speed and stride can be accurately estimated only by measuring the acceleration. It was.

  It should be noted that another estimation formula can be used for the stride. For details, see Japanese Patent Application No. 2007-077735, which is an earlier application. In addition, the estimation formulas for estimating the knee extension force and the ankle dorsiflexion force are also described in detail in the previous application, and will be omitted.

  Next, examples of display screens for walking ability, fall risk and exercise menu displayed on the display unit 40 will be described with reference to FIGS.

  FIG. 7 is an example of a display screen for walking ability. “Walking analysis” is displayed as the title of the screen in the upper left corner of the display screen. Displayable contents are displayed in symbols and words from the center of the upper stage of the screen to the right side. As shown in the figure, “registrant list”, “analysis result”, “advice”, “exercise selection”, “exercise menu”, “end”, and “print” are displayed, and only the “analysis result” currently displayed is highlighted. It is displayed. Under the title at the top of the screen, the subject's name, gender, age, height, and weight are displayed. The display content in the upper part of the screen is common to other display screens. In the middle of the screen, the obtained walking speed and stride during normal walking and full power walking are displayed together with past data. In addition, the average value data of subjects of the same age is displayed on the right side as a reference. At the bottom of the screen, the time-series changes in walking ability from the past to the present are displayed in a graph. By displaying the average value data of the same age and the time-series changes of the walking ability of the subject, it is possible to encourage the subject's willingness to improve the athletic ability.

  FIG. 8 is an enlarged view of the time-series change graph of walking ability displayed in FIG. 7, where (1) is the walking speed, (2) is the average stride, (3) is the left / right stride and left / right stride ratio. Show. Each graph shows three times of time-series changes from left to right, and all of them illustrate that the walking ability has been improved by rising to the right. (1) In (2), the upper broken line indicates full power walking, and the lower bent line indicates normal walking. In (3), the left / right stride ratio is numerically displayed, and it can be seen that the latest data on the right side is 50:50 and the symmetry is satisfied.

  FIG. 9 is an example of a display screen of the tipping risk and advice with “advice” displayed in the title. The fall risk is displayed in chronological order on the left side of the middle of the screen, and the walking speed and stride during full power walking and normal walking are displayed on the right side of the middle of the screen as squares. Makes intuitive understanding easy. In the lower part of the screen, advice on selecting an exercise menu according to the fall risk is displayed.

  FIG. 10 is an example of an exercise menu proposal display screen with “Exercise Selection” displayed in the title. In FIG. 10, an exercise menu when the fall risk is determined to be “no problem (good)” is displayed. A plurality of exercise menus are proposed for each exercise purpose, and an illustration and an exercise item name are displayed. As shown in the figure, exercise objectives are broadly divided into physical fitness improvement and walking motion improvement, physical fitness improvement is subdivided into flexibility improvement, lower limb muscle strength enhancement, balance function improvement and agility improvement, and walking motion improvement is stepping improvement・ It is subdivided into walking posture improvement. A total of 18 exercise menus have been proposed for a total of 6 exercise purposes. The subject and the rehabilitation instructor can select a desired exercise menu on this screen.

  When the exercise menu is selected on the exercise menu suggestion screen in FIG. 10, another screen for explaining the details of the exercise menu is opened. FIG. 11 is another screen for explaining the details of the exercise menu, and illustrates one-leg swing balance exercise for improving the balance function among the physical strength improvements. On this screen, the exercise menu implementation guidelines and precautions are displayed with illustrations and texts, and the number of exercises and the execution time are also displayed, so that the amount of exercise can be known.

  1 and 2 can be used to print out the display screens of FIGS. 7 to 11 on paper. Furthermore, it is possible to print out an execution plan for the selected exercise menu and a recording sheet. FIG. 12 is an example of a weekly calendar that also serves as an exercise menu execution plan and a recording sheet. This calendar contains the exercise menu you have selected, and you can write your work for one week and self-evaluate your achievement. There is also a monthly calendar that is longer than the weekly calendar. The subject can print out these calendars and take them home for use.

  As described above, according to the walking analysis and exercise menu suggestion system 100 of the embodiment, it is possible to accurately estimate the walking ability index such as the walking speed and the stride only by measuring the waist acceleration during the walking motion. it can. Measurement of acceleration can be performed in a short time with a simple operation using simple equipment, and no specialized knowledge is required. Therefore, the burden on the subject and the measurer is small.

  Further, in the present embodiment, the right / left stride ratio can be obtained and used for discrimination of the fall risk and the proposal of the exercise menu, and the practical performance has been improved. The left / right stride ratio is also effective for finding potential illnesses and injuries, and for comparative evaluation of the degree of functional recovery of the left and right feet.

  In addition, after calculating | requiring a knee extension force and a dorsiflexion force, the test subject's present walking age can also be calculated. Specifically, the ROM 26 stores in advance a relational expression between the strength of knee extension force or dorsiflexion force and walking age, and the calculated knee extension force and dorsiflexion force are substituted into the relationship, thereby walking. Age can be calculated. The determined walking age can be stored and displayed in the same manner as other indicators of walking ability. In addition, the present invention can be applied in various ways.

It is a functional block diagram explaining the walk analysis and exercise menu suggestion system of the Example of this invention. It is a hardware block diagram explaining the actual structure of the system of the Example of FIG. It is a figure which shows a time change waveform of walking motion and a corresponding acceleration signal. FIG. 3 is a flowchart illustrating the operation and operation of the system of the embodiment of FIGS. 1 and 2. In the Example of FIG.1 and FIG.2, it is a list which discriminate | determines a fall risk based on the measurement data in a normal walking form. In the Example of FIG.1 and FIG.2, it is a list which discriminate | determines a fall risk based on the measurement data in a full power walking form. It is an example of the display screen of the walking ability displayed on a display part. FIG. 7 is an enlarged graph of time-series changes in walking ability displayed in FIG. 7, (1) shows walking speed, (2) shows average stride, and (3) shows left and right stride and left / right stride ratio. It is an example of the display screen of the fall risk and advice displayed on the display unit. It is an example of the display screen of the exercise menu proposal displayed on a display part. It is an example of another screen explaining the detail of the exercise menu opened from the display screen of FIG. It is an example of a weekly calendar that is printed out by an output printer and serves as both an execution plan and a recording sheet.

Explanation of symbols

100: Walking analysis and exercise menu suggestion system 1: Walking ability detection means 2: Fall risk determination means 3: Exercise menu suggestion means 4: Notification means 5: Acceleration measurement means 6: Walking ability estimation means 7: Symmetry detection means 10: Accelerometer (acceleration measuring means)
20: arithmetic unit 22: A / D converter 24: CPU 26: ROM 28: RAM
30: Time measuring unit 40: Display unit 50: Recording unit

Claims (9)

Walking ability detection means for determining walking ability by measuring the walking motion of the subject, fall risk judgment means for judging the subject's fall risk from the obtained walking ability, and fall prevention in accordance with the walking ability or the previous fall risk And an exercise menu proposing means for proposing an exercise menu for improving the motor function, and a notification means for notifying the exercise menu and notifying at least one of the walking ability and the fall risk. A system,
The walking ability detecting means includes symmetry detecting means for obtaining an index indicating a left / right stride ratio representing a ratio of a left foot stride and a right foot stride,
The walking motion targeted by the symmetry detection means is a walking motion of a middle portion excluding each constant distance or each predetermined number of steps from the beginning and end of the walking motion of a predetermined distance, and Exercise menu suggestion system. The walking analysis and exercise menu suggestion system according to claim 1 , wherein the left / right stride ratio is obtained by using an average left foot stride and an average right foot stride obtained from a plurality of left foot stride and right foot stride, respectively. The walking action, the subject 1 walking form of normal walking only to walk at a normal speed or claim 1 or 2 subjects is 2 walking form of best walking and the normal walking action of walking with full force, The walking analysis and exercise menu suggestion system described in 1. The walking ability detecting means, claim having an acceleration measuring means for measuring acceleration in the walking motion is attached to the waist of the subject, the walking ability estimating means for estimating the walking ability based on the measured acceleration, a The walking analysis and exercise menu suggestion system according to any one of claims 1 to 3 . The walking ability detecting means, in addition to the left and right step length ratio, walking speed, stride, pace, knee extension strength, ankle back屈力, as claimed in claim 1 for determining at least one Walking analysis and exercise menu suggestion system. The exercise menu offering means each holding the motion menu for a plurality of kinetic purposes, any claims 1 to 5, proposes to select the motion menu that fits the walking ability or the risk of falls obtained walking analysis and motion menus proposed system according to an item or. The exercise menu proposed means to claim 6 symmetry improving retain the symmetry improving exercise menu to said movement purposes, we propose to select the symmetry improves exercise menu that fits the left and right step length ratio obtained The described walking analysis and exercise menu suggestion system. The gait analysis and exercise menu suggestion system according to any one of claims 1 to 7, wherein the notification means notifies a time-series change of at least one of the walking ability and the fall risk. The walking ability detecting means, the fall risk determination means, said motion menu offering means, and some or all of the mutual announcement means any of the preceding claims linked by wired communication means or wireless communication means walking analysis and motion menus proposed system according to an item or.