JP2006345990A - System for estimation of muscle activity - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a system for extracting an estimated value of the quantity of activity of muscles or the quantity of movement of lower limbs of a user doing exercise without giving physical restraint or pain to the user or without local restraint. <P>SOLUTION: The system is characterized by a pressure sensor disposed in such a position as can measure the pressure generated in a specific region of the sole of the user and a processor for extracting the quantity of activity of one or a plurality of muscles or the quantity of movement of the lower limbs based on the output from the pressure sensor. The processor extracts the quantity of activity of the muscles based preferably on the output from the pressure sensor and the previously computed correlation coefficient between the output and the quantity of activity of the muscles or the quantity of movement of the lower limbs. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a muscle activity estimation system for estimating the amount of muscle activity or the amount of movement of a lower limb based on pressure generated on the sole of a foot during walking or the like.

  In order to prevent an increase in bedridden elderly people in an aging society, it is said that it is effective to stimulate muscle functions, particularly muscle groups on the rear surface of the thigh, and suppress the decrease in muscle tissue mass and strength. In recent years, there have been actual reports that Parkinson's disease and cognitive symptoms have improved after a month of walking, walking, stretching, etc. for about a month. For those who do not have special training, walking is the most effective activity that stimulates the lower body muscles in daily life, but a simple means to determine how much stimulation is being applied to the muscles Never before.

  As a conventional method of grasping the amount of muscle activity, a method using an electromyogram that can electrically grasp the amount of muscle activity from the outside is common. Hereinafter, conventional electromyogram measurement will be described with reference to FIG. This figure shows the example which measured the myoelectric potential change amount when force was applied to the muscle. This figure is described in Non-Patent Document 1. In the figure, the horizontal axis corresponds to time. a shows the time change of the applied force. b shows the state of potential change of the intramuscular electromyogram at that time, and c shows the state of potential change of the surface electromyogram. It can be seen that the electromyogram amplitude increases as the force increases. Therefore, by measuring the electromyogram, it is possible to estimate the amount of muscle activity from the amplitude value.

On the other hand, in an exercise program such as rehabilitation, it is common to determine whether a body is moving according to an exercise prescription with the eyes of an expert such as a doctor or a trainer. At that time, it is a common practice to visually feed back the current state to the subject using a method of continuous shooting using television, video, or a strobe, or leave it as a record.
Kaneko Park, Tetsuo Fukunaga, “Science Fundamentals of Biomechanics”, Kyorin Shoin, October 1, 2004, 1st edition, 1st edition, p. 445

  The method for measuring the amount of muscle activity using the above electromyogram directly measures the action potential generated from the muscle, and can estimate the amount of muscle activity from the measured potential. However, myoelectric potential measurement requires a dedicated and expensive measuring instrument, and there is a problem that it is difficult to use it on a daily basis economically and locally. In addition, it is necessary to wear a large number of electrodes on the body at the time of measurement, and the subject's body is restrained, which may lead to physical and mental pain. Furthermore, when measuring an intramuscular electromyogram, it is necessary to pierce the subject's muscle with a needle-like electrode, which may lead to further physical pain of the subject. Further, in this case, only qualified persons such as doctors can insert the electrodes into the subject, so that there is a problem that there is a great restriction on the place of implementation.

  Visual judgment of the above-mentioned body movements and muscle activity can be done by using video equipment that can be used on a daily basis, but it is a dedicated place for installing video equipment. Is needed. In addition, there is a restriction that it is necessary to have specialized knowledge and experience to judge how much the line is used from the acquired video information at the shooting site or at a remote place.

  The present invention has been made in view of the above problems, and the amount of activity of the user's muscles and movement of the lower limbs during exercise without causing restraint to the user, pain to the user, restriction on the place of use, etc. The problem is to provide a system capable of estimating the quantity.

  In the present invention (first invention), the pressure generated on the sole of the foot when the user performs exercise such as walking, the rectus femoris, the anterior tibialis, the gastrocnemius, the hamstring, etc., which are important in stretching and rehabilitation Pressure based on the new knowledge that it has a strong correlation with the amount of exercise of multiple muscles, and the pressure placed at a position where the pressure generated at a specific part of the user's sole can be measured A muscle activity estimation system comprising: a sensor; and a processing device for deriving an activity amount of one or a plurality of muscles based on an output of the pressure sensor.

  As the pressure sensor in the present invention, an arbitrary type of sensor capable of measuring the pressure generated on the sole when walking, such as a sensor using a strain gauge or a piezoelectric element, is used. Sensors, preferably by embedding such pressure sensors in the soles or insoles of shoes or sandals worn by the user, so that when the user performs exercises such as walking, The resulting pressure is detected.

  Here, by using a plurality of the pressure sensors, it is possible to detect the pressure at a plurality of parts of the user's sole, and by using the pressure detection data at the plurality of parts, more muscles can be detected. The momentum can be derived or the accuracy of the derived value can be increased.

  The processing apparatus in the present invention can derive the amount of muscle activity based on the output from the pressure sensor and the correlation coefficient obtained in advance for the output and the amount of muscle activity, and particularly preferably, The amount of muscle activity is derived based on the integral value of the output within a predetermined time and the correlation coefficient obtained in advance for the integral value and the amount of muscle activity.

  The present invention may include a display device for displaying an output of a pressure sensor or a muscle activity amount derived based on the output, in which case the user can detect a muscle activity amount, for example, It is possible to perform exercises such as walking while monitoring the amount of activity of rectus femoris, anterior tibial muscle, gastrocnemius, hamstring, etc., which are important in stretching and rehabilitation.

  Further, the present invention (second invention) is based on a new finding that the pressure generated on the sole during walking has a strong correlation with the amount of movement of the lower limbs. A muscle sensor comprising: a pressure sensor arranged at a position capable of measuring a pressure generated in a specific part of a sole of the foot; and a processing device for deriving a movement amount of a lower limb based on an output of the pressure sensor. It is an estimation system.

  In the present invention, a sensor similar to that described above for the first invention can be used in the same manner, and a plurality of pressure sensors are used to provide a plurality of sensors on the sole of the user, as in the first invention. By measuring the pressure of the part, the amount of movement of the user's lower limb can be derived more accurately, or the amount of movement of more parts of the user's lower limb can be derived.

  The processing device in the present invention can derive the amount of movement of the lower limb based on an output from the pressure sensor and a correlation coefficient obtained in advance for the output and the amount of movement of the lower limb, and is particularly preferable. The amount of movement of the lower limb is derived based on the integrated value of the output within a predetermined time and the correlation value obtained in advance for the integrated value and the amount of movement of the lower limb.

  In the present invention, it is also possible to determine whether or not the movement of the user's lower limb is included in a predetermined category for the movement of the lower limb based on the amount of movement of the lower limb derived by the present invention. is there.

  For example, it is possible to discriminate whether or not the amount of movement of the lower limb derived by the present invention belongs to that category by using the movement of the lower limb desired in a desirable mode during exercise such as walking as a category. It is. It is also possible to determine a plurality of categories for the movement of the lower limbs and determine which category the movement of the user's lower limbs is included.

  Further, by providing a display device for displaying the result of the determination made in this way, whether or not the user's own lower limb movement is included in a predetermined category (for example, the lower limb movement is It is possible to exercise while monitoring whether or not the desired movement is achieved.

  In the present invention, it is also possible to generate image data for visually displaying the movement of the user's lower limb based on the derived amount of movement of the lower limb, and display the image data on the display device. With this, the user can exercise while visually monitoring the movement of his / her lower limbs.

  A display device for displaying sensor output, muscle activity, amount of movement of the lower limb, the result of determination of the movement of the lower limb, or image data for visually displaying the movement of the lower limb can be attached to the arm or the like. A portable display device is particularly preferable.

  In addition, the muscle activity estimation system of the present invention provides image data for visually displaying the sensor output, the amount of muscle activity, the amount of movement of the lower limbs, the result of discrimination of the movement of the lower limbs and / or the movement of the lower limbs. It is possible to further provide a communication means for transferring data, which makes it possible to transmit data useful for management and analysis of training and rehabilitation to specialists such as doctors and trainers at remote locations.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is an explanatory diagram showing a configuration of a muscle activity estimation system 10 according to an embodiment of the present invention, and FIG. 2 is a pressure sensor arranged on shoes 11a and 11b worn by a user in the muscle activity estimation system 10. FIG. 3 is an explanatory diagram showing the arrangement of P _{1 to} P ₄ , and FIG. 3 is a system configuration diagram of the muscle activity estimation system 10.

Figure 11a, 11b are shoes to a portion of the sole pressure sensors _P 1 to P ₄ are embedded, pressure sensors _P 1 to P _4, as shown in FIG. 2, the thumb portion, the thumb portion, It arrange | positions in the position which can measure the pressure which generate | occur | produces on the sole of the user H in four places, an outer part and a buttocks. The pressure values measured by the pressure sensors P _{1 to} P ₄ are transmitted as electric signals to the terminal 12 attached to the user's arm. The transmission method may be wired or wireless.

  As shown in FIG. 3, the terminal 12 includes a processing unit 12a including a CPU and a storage device, and a display unit 12b (for example, a liquid crystal monitor and a lamp) for visually displaying data.

Data such as correlation coefficients β _pi and ε _{i to be} described later are recorded in the storage device of the processing means 12a. The processing means 12a is based on these data and signals from the pressure sensors P _{1 to} P _4. The amount of activity y _i of the user's muscle (for example, rectus femoris, anterior tibialis, gastrocnemius, hamstring, etc.) is derived and displayed on the display means 12b. The display may be performed such that the derived activity amount y _i is in the form of a numerical value, a graph, or the like, and is performed in the form of blinking of a lamp or the like when the activity amount of a specific muscle is greater than or less than a predetermined value. Also good.

Terminal 12 further includes a communication unit 12c, the activity amount of said muscle derived based on the pressure value or which measure the pressure sensor P ₁ to P ₄ to the data processing unit 13, which is remotely located It can be transmitted.

  The data processing unit 13 transmits / receives data to / from the processing unit 13a including a CPU and a storage device, a display device 13b for visually displaying data, an input unit 13c such as a keyboard, and the terminal 12. For example, a doctor or a trainer analyzes, manages, or stores data from the terminal 12, or transmits a message input from the input means 13c to the terminal 12, and displays the display means. 12b can be displayed.

Next, an exemplary method for deriving the correlation coefficients β _pi and ε _i recorded in the processing means 12a of the muscle activity estimation system 10 and the muscle activity amount using the correlation coefficients β _pi and ε _i will be described.

FIG. 4 shows the walking of the user H measured by the pressure sensors P ₁ (thumb part), P ₂ , (mother finger part) P ₃ (outer part), and P ₄ (buttock part) of the muscle activity estimation system 10. Fig. 5 (a) to 5 (d) show the measured values of the pressure generated on the sole of the user H. Fig. 5 (a) to (d) show the myoelectric potentials of the hamstring, rectus femoris, gastrocnemius, and anterior tibial muscles. The result measured using a myoelectric potential measuring device is shown. In addition, the horizontal axis | shaft of FIG. 4, FIG. 5 (a)-(d) is time.

ここでｘ_ｐ（ｐ＝１〜４）は、所定時間毎の各圧力センサーＰ_１〜Ｐ_４の出力の積分値であり、添字のｉは筋肉の種類（大腿直筋、前脛骨筋、腓腹筋、ハムストリング）毎に振られた符号である。 Here, the time interval d from the rising part of the output of the pressure sensor P ₄ arranged on either the left or right collar part to the next rising part is taken as one period, and each pressure sensor P ₁ to an integral value x ₁ ~x ₄ of the output of P ₄ and explanatory variables, the regression coefficients by performing multiple regression analysis as objective variable integration value of the absolute value of the measured the myoelectric potentials of the muscles by the myoelectric potential measuring device β _pi and ε _i can be obtained, and from the regression coefficient and the data obtained from the pressure sensors P _{1 to} P ₄ , the predicted value y _i of each muscle activity is derived by the following equation (1). can do.

Here, x _p (p = 1 to 4) is an integrated value of the outputs of the pressure sensors P _{1 to} P ₄ every predetermined time, and the subscript i is a muscle type (stratus thigh muscle, anterior tibialis muscle, gastrocnemius muscle) , A hamstring).

In a combination of muscles (stratus thigh muscle, anterior tibialis muscle, gastrocnemius muscle, hamstring) for estimating the amount of activity and the placement of the pressure sensors P _{1 to} P ₄ , the integrated values x _{1 to} x ₄ and these muscles are used. Therefore, an extremely high correlation coefficient such as 0.7 to 0.95 can be obtained between the activity amounts of the muscles. Therefore, the muscle activity estimation system 10 in this embodiment estimates the activity amount of each muscle with extremely high accuracy. It can be said that it is possible.

  Subsequently, a muscle activity estimation system 20 according to another embodiment of the present invention will be described.

The muscle activity estimation system 20, the processing unit 12a will derive the motion amount of the lower limbs of the user based on the output of the pressure sensor P ₁ to P _4, to display information about the amount of motion of the leg on the display unit 12b, Alternatively, it has the same configuration as the muscle activity estimation system 10 except that it is transmitted to the data processing unit 13.

ここでｘ_ｐ（ｐ＝１〜４）は、所定時間毎の各圧力センサーＰ_１〜Ｐ_４の出力の積分値であり、添字のｉは筋肉の種類（大腿直筋、前脛骨筋、腓腹筋、ハムストリング）毎に振られた符号である。 That is, in this muscle activity estimation system 20, the regression coefficients β ′ _pi and ε ′ _i for deriving the amount of movement of the lower limb from the output values of the pressure sensors P _{1 to} P ₄ are recorded in the processing means 12a of the terminal 12. Then, the processing means 12a derives the movement amount y ′ _i of the lower limb according to the following equation (2).

Here, x _p (p = 1 to 4) is an integrated value of the outputs of the pressure sensors P _{1 to} P ₄ every predetermined time, and the subscript i is a muscle type (stratus thigh muscle, anterior tibialis muscle, gastrocnemius muscle) , A hamstring).

Further, the regression coefficients β ′ _pi and ε ′ _i can be obtained based on data obtained from a measurement system using a motion capture system (VICOM 8 manufactured by VICOM) shown in FIG. 6, for example.

  The motion capture system is a system that measures human motion, converts it into digital data, and captures it. In this measurement system, 12 motion cameras 14 arranged in a circle as shown in FIG. The amount of movement of the lower limbs of the user H based on the three-dimensional position coordinates of each marker obtained by taking an image of the user H wearing the marker M on each part of the body shown in FIG. The measured value is derived. The measurement value of the amount of movement of the lower limb is derived for each image frame output from the motion camera 14 every 1/30 seconds.

Also, the user H in the measuring system, shoe 11a the pressure sensor P ₁ to P ₄ is attached to the position shown in FIG. 2, 11b are fitted with the pressure generated in the sole of the user H It can measure at the same time.

  FIG. 7 is an explanatory diagram showing an example of a measurement value of the amount of movement of the lower limb obtained by the measurement system. In the example shown in the figure, the knee portion of the shin portion when the user H is walking is centered. The time transition of the rotation angle is shown. In the figure, “Shin X”, “Shin Y”, and “Shin Z” are rotation angles in the horizontal direction, the walking direction, and the vertical direction, respectively.

In accordance with the derivation frequency of the measurement value of the amount of movement of the lower limbs, the integrated values x _{1 to} x ₄ every 1/30 seconds of the outputs of the pressure sensors P _{1 to} P ₄ are used as explanatory variables, and every 1/30 seconds. The regression coefficients β ′ _pi and ε ′ _i are obtained by performing multiple regression analysis using the measured value of the amount of movement of the lower limbs of the user H derived in (1) as an objective variable.

In FIG. 8, the measured value obtained by the above measurement system for the rotation angle of the shin portion in the walking direction is the estimated value y ′ _i derived from the equation (2) or an approximation of this estimated value y ′ _i . It is shown in contrast to a multinomial curve, and it can be seen from this figure that the estimated value y ′ _i (or its approximate curve) derived by the muscle activity estimation system 20 according to this embodiment is extremely accurate.

The amount of movement y ′ _i of the lower limb derived by the processing means 12a in this way can be displayed on the display means 12b or 13b in various ways.

FIG. 9 is an explanatory diagram showing an example of a display mode of the amount of movement y ′ _i of the lower limb on the display unit 12b or 13b.

The illustrated example shows an example of image data obtained by applying the amount of movement y ′ _i of each part of the lower limb derived by the processing means 12a to the bone model, and the muscle activity estimation system 20 of the present invention is shown in FIG. In this manner, the manner of movement of the lower limb can be visually displayed.

  Further, the muscle activity estimation system 20 of the present invention can execute a discriminant analysis on a certain category related to a predetermined lower limb movement and display the result on the display means 12b or 13b.

  Hereinafter, the evaluation result performed about the discriminant analysis whether the user's H walk is contained in the category of a good walk is demonstrated.

A walk in which the back is naturally stretched and a foot is carried in a rolling manner is generally considered to be a good walk, and here, such a walk is defined as “good walk (category)”. In addition, walking in the rolling mode is the following operation.
・ Extend your knees straight and land from the heel.
・ After the landing, move the center of gravity around the arch and move it to the base of the thumb and toes.
・ Kick the ground lightly with your toes.

ただし、ｉは歩行態様についてのカテゴリ（ｉ＝１の場合は「良い歩行」、ｉ＝２の場合は「良い歩行」以外の態様での歩行）であり、ｐ＝１〜４は圧力センサーＰ_１〜Ｐ_４に対応し、ｊはフレーム番号（モーションカメラ１４から出力される画像フレーム毎に振られた番号）である。 With the measurement system shown in FIG. 6, the measured value (Z _1j ) of the amount of movement of the lower limbs (for example, the rotation angle of the shin portion) when the subject performs the walking motion in a mode according to the above “good walking”, and at this time The output (x _p1j ) of the pressure sensors P _{1 to} P _{4 and} the amount of movement of the lower limbs (for example, the rotation angle of the shin portion) when the subject is performing a walking motion in a mode that does not follow the “good walking”. The measured value (Z _2j ) and the outputs (x _p2j ) of the pressure sensors P _{1 to} P ₄ at this time are measured. In the following formulas (3) to (5), under the condition of “S _b / S _w = maximum” The discrimination coefficient _ap was derived.

However, i is a category regarding walking modes (“good walking” when i = 1, walking in modes other than “good walking” when i = 2), and p = 1 to 4 are pressure sensors P. corresponding to ₁ to P _4, j is the frame number (numbers swung for each image frame output from the motion camera 14).

Using _ap derived as described above, the outputs (x _11j) of the pressure sensors P _{1 to} P ₄ when the subject performs a walking motion in a mode that follows “good walking” or a walking motion in a mode that does not follow this. ˜x _11j ) into the above formula (3), Z _ij obtained by substituting for a positive value or a negative value depends on the category of “good walking” and walking other than “good walking”. As a result of the discriminant analysis into the category, the ratio of discriminating the walking motion in the mode according to the “good walking” to the “good walking” category is 82.8%, and the walking category other than “good walking” is discriminated. The ratio is 17.8%, and the ratio of discriminating the walking motion in a mode that does not follow “good walking” into the category of “good walking” is 12.8%, and discriminating into the walking category other than “good walking” The percentage was 87.2%.

  As mentioned above, although this invention was demonstrated based on some embodiment, this invention is not limited by these embodiment.

  For example, in the above embodiment, the amount of muscle activity and the amount of movement of the lower limbs based on the outputs of four pressure sensors arranged at positions where the sole pressure generated at the thumb, thumb, outer, and hips can be detected. However, the number and arrangement of the pressure sensors in the above embodiment are merely exemplary, and three or less or five or more pressure sensors are described. It is also possible to use a pressure sensor arranged at a position different from the above embodiment.

  In the above-described embodiment, the amount of muscle activity or the amount of movement of the lower limb is derived based only on the output of the pressure sensor that detects the pressure generated on the sole, or the movement of the lower limb is determined in some category. As described above, the output of the pressure sensor is used in combination with other measurement data such as the output of a myoelectric potential measuring device that measures the myoelectric potential of the user at one or more locations to determine the amount of muscle activity and the amount of movement of the lower limbs. It is also possible to derive or discriminate the movement of the lower limbs into some category.

  The present invention can be used for medical equipment, rehabilitation assistance equipment, training assistance equipment, etc. used in specialized institutions for medical treatment, rehabilitation, training, etc., and individual users can exercise such as jogging and walking. It can be used as a health promotion aid used when performing.

Explanatory drawing which shows the structure of the muscle activity estimation system which concerns on one Embodiment of this invention. Explanatory drawing which shows arrangement | positioning of the pressure sensor in the muscle activity estimation system which concerns on one Embodiment of this invention. The system block diagram of the muscle activity estimation system which concerns on one Embodiment of this invention. Explanatory drawing which shows the output from the pressure sensor of the muscle activity estimation system which concerns on one Embodiment of this invention. Explanatory drawing which shows the myoelectric potential measured by the myoelectric potential measuring device. Explanatory drawing which shows the example measurement system used for derivation | leading-out of a regression coefficient. Explanatory drawing which shows an example of the measured value of the amount of movements of the lower limbs obtained from the measurement system shown in FIG. Explanatory drawing which shows the measured value of the amount of movement of the lower limb obtained from the measuring system shown in FIG. 5 in contrast with the estimated value derived | led-out by the muscle activity estimation system of this invention, and its approximated polynomial curve. Explanatory drawing which shows an example of the display mode of the amount of movements of the leg on a display means. Explanatory drawing which shows an example of the measurement data measured by a myoelectric potential meter.

Explanation of symbols

10 Muscle activity estimation system 20 Muscle activity estimation system 11a, 11b shoe 12 terminal 12 processing unit 12a processor 12b display device 12c communicating means 13 the data processing unit 13a processor 13d communicating means 13c input means 13b display device _P 1 to P ₄ pressure sensor

Claims (11)

  A pressure sensor disposed at a position where pressure generated in a specific part of a user's sole can be measured, and a processing device for deriving one or a plurality of muscle activity amounts based on an output of the pressure sensor. A muscle activity estimation system characterized by   The muscle activity estimation system according to claim 1, wherein a plurality of the pressure sensors are arranged to measure pressures at a plurality of sites on a user's sole.   The said processing apparatus derives the activity amount of the said muscle based on the output from the said pressure sensor, and the correlation coefficient previously calculated | required about the said output and the activity amount of a muscle. The muscle activity estimation system described in 1.   The muscle activity estimation system according to any one of claims 1 to 3, further comprising a display device for displaying an output of the pressure sensor or an amount of activity of the muscle.   A pressure sensor arranged at a position where a pressure generated at a specific part of a user's sole can be measured, and a processing device for deriving a movement amount of the lower limb based on an output of the pressure sensor. Muscle activity estimation system.   The muscle activity estimation system according to claim 5, wherein a plurality of the pressure sensors are arranged to measure pressures at a plurality of sites on a user's sole.   The processing device derives the amount of movement of the lower limb based on an output from the pressure sensor and a correlation coefficient obtained in advance for the output and the amount of movement of the lower limb. The muscle activity estimation system described in 1.   The processing device determines whether or not the movement of the user's lower limb is included in a specific category predetermined for the movement of the lower limb based on the amount of movement of the lower limb. Item 8. The muscle activity estimation system according to any one of Items 5 to 7.   The muscle activity estimation system according to claim 8, further comprising a display device for displaying the amount of movement of the lower limb or the result of the discrimination. The processing device further generates image data for visually displaying the movement of the user's lower limb based on the amount of movement of the lower limb,
The muscle activity estimation system according to any one of claims 5 to 7, further comprising a display device for displaying the image data. The communication device for transferring the output of the pressure sensor, the amount of activity of the muscle, the amount of movement of the lower limbs, the result of the discrimination, or the image data to a remote place. The muscle activity estimation system according to one item.

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