JP2010193936A - Muscle rigidity degree quantitative evaluation apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an apparatus for measuring the muscle rigidity of a subject while applying passive upper limb bending motion, the same method as a clinically used measuring method, to the subject, and quantitatively evaluating the result of measurement especially on the gear-like rigidity. <P>SOLUTION: The apparatus includes: a motion means utilizing a stepping motor with an increased motion torque for passively applying the upper-limb bending motion to the subject by using a gear box directly connected to an arm having a means for fixing the upper limb at the elbow joint and the wrist; a myogenic potential measuring means for measuring the myogenic potential; and a forearm position measuring means for measuring the position of the forearm by a position convertor with a displacement cable. An analysis value is computed on the digital data obtained by downloading biological information on the myogenic potential, and the muscle rigidity is quantitatively evaluated based on the computed data of the analysis value. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

The present invention relates to an apparatus for analyzing human upper limb movements, and relates to a muscular rigidity quantitative evaluation apparatus for performing quantitative evaluation by flexing and stretching the upper limb dynamically.

Muscle stiffness is a phenomenon in which muscle tone increases when joints of the limbs are flexed and stretched dynamically. For example, in patients with Parkinson's disease, gear-like stiffness that shows intermittent resistance is observed. This muscular stiffness was caused by the resistance felt when the upper extremity was stretched or bent at the elbow or the wrist was rotated by the examiner who was a doctor against subjects who had relaxed their upper limbs in a daily state. Based on the resistance felt at times, it is subjectively rated on a five-point scale. In Unified Parkinson's Disease Rating Scale (UPDRS) often used in clinical diagnosis, 0 points when there is no muscle rigidity, 1 point that can be induced by minor or mirror movements or other movements, mild to moderate It is evaluated as 2 points when there is rigidity, 3 points when the joint movement is normal, but 4 points when there is significant rigidity and the joint movement is limited. The UPDRS evaluation is subjective, and an apparatus that objectively and quantitatively evaluates the degree of muscular rigidity is required to ensure the universality of the evaluation.

Parkinson's disease is a typical neurodegenerative disease mainly characterized by movement disorders. In addition to muscle stiffness, movement disorders such as resting tremors, immobility, and posture maintenance disorders are observed. Methods for evaluating the severity of such movement disorders include Hoehn-Yahr severity classification and UPDRS, and both methods are based on the subjectivity of doctors. Objective and quantitative evaluation of movement disorders to determine the clinical severity of Parkinson's disease is very important for clinical diagnosis and response to pharmacotherapy. Evaluation methods and quantitative evaluation devices have been proposed.

For example, Patent Document 1 proposes a method of performing an exercise operation based on an audio signal based on an image signal supplied according to a program and performing an exercise evaluation based on the reaction time or operation time of the exercise. Although this method can be measured relatively easily, it does not directly correspond to the UPDRS and Hoehn-Yahr severity classifications that are commonly used clinically.

Further, Patent Document 2 exemplifies a device that measures a resistance felt when an upper limb is stretched or bent at an elbow using a method similar to a clinical UPDRS evaluation method. This device attempts to distinguish subjects with muscle stiffness by recording and displaying torque corresponding to the time course of the flexion and extension angle position, but it cannot detect gear-like stiffness seen in Parkinson's disease patients.

Non-Patent Document 1 proposes a method for quantifying finger taps, which is one of evaluation methods included in UPDRS, but muscular rigidity is not quantified.

In Non-Patent Document 2, muscle stiffness is evaluated based on frequency analysis of a surface electromyogram obtained from the upper arm, but no quantification method is proposed.

Non-Patent Document 3 exemplifies a device that quantitatively evaluates muscular rigidity based on an analysis value of a surface electromyogram obtained from the upper arm using a method similar to a clinical UPDRS evaluation method. However, the illustrated device may cause unexpected movement due to malfunction of the control device and may cause injury to the subject. In addition, there are few measurement examples, and in order to objectively and quantitatively evaluate movement disorders, it is unclear what the value of the window function used for moving average should be, and a quantitative evaluation method based on frequency analysis is also exemplified It has not been.

JP 2004-57357 A JP-A-56-151023

Akihiko Kandoori, et al. , Neuroscience Research, Vol. 49,2004, pp 253-260 L. J. et al. Findley, et al. , Journal of neurology, Neurosurgery, and Psychiatry, Vol. 44, 1981, pp 534-546 D. Wright, et al. , Conference processings IEEE Engineering and Biological Society, Vol. 1, 2008, pp 2825-2827

The present invention has been made in view of the above-mentioned circumstances, and its purpose is to perform muscle stiffness while giving a subject the passive movement of the upper limb, which is the same method as the measurement method used in UPDRS. An object of the present invention is to provide an apparatus for measuring and particularly quantitatively evaluating the measurement result of gear-like stiffness. In addition, the evaluation device must incorporate a safety device to prevent the subject from making excessive movements due to malfunction. Still another object of the present invention is to provide an apparatus for quantitatively evaluating the degree of muscle rigidity that can be used for diagnosis, early diagnosis, severity evaluation, drug efficacy evaluation, surgical treatment effect determination, and the like, particularly for diseases involving muscle rigidity such as Parkinson's disease. The purpose is to provide.

The present invention provides a subject with flexing motion of the upper limb by using a stepping motor having increased operating torque using a gear box directly connected to an arm having means for fixing the upper limb with an elbow joint and a wrist. Digital data obtained by taking in biological information on myoelectric potential, comprising operating means, myoelectric potential measuring means for measuring myoelectric potential, and forearm position measuring means for measuring the forearm position with a position converter using a displacement cable An apparatus for quantitatively evaluating the degree of stiffness of muscles characterized by calculating an analysis value and performing quantitative evaluation of muscle stiffness based on the calculated data of the analysis value.

One example of the analysis value is a moving average process using a window function for the absolute value of myoelectric potential for one measurement extracted from digital data obtained by taking myoelectric potential obtained from a plurality of measurements. Single moving average electromyogram is calculated, average electromyogram is calculated from the average value of the calculated multiple single moving average electromyograms, and the average muscle is calculated from the integrated value of the calculated average electromyogram Calculating the electrogram integral value, and calculating the single moving average electromyogram deviation integral value from the integral value of the absolute value of the difference between the single moving average electromyogram and the average electromyogram for one measurement. Calculate the single moving average electromyogram deviation ratio, which is the ratio of the single moving average electromyogram deviation integrated value to the EMG integral value, and obtain the single moving average electromyogram deviation ratio obtained from multiple measurements. Is the average value.

As for the window function used for the moving average process, it is preferable to use a function in which only the window function time is 1 and others are 0, and the window function time is 10 ms to 20 ms.

Another example of the analysis value is to perform fast Fourier transform on the absolute value of digital data obtained by taking in myoelectric potential obtained from multiple measurements, and to calculate the frequency power for the result of the fast Fourier transform processing. Calculate a spectrum, calculate an average frequency power spectrum, which is an average value of frequency power spectra obtained from a plurality of measurements, and integrate each of the non-specific frequency band component and the specific frequency band component of the average frequency power spectrum. And the ratio of the integral value of the specific frequency frequency band component to the integral value of the non-specific frequency component.

It is preferable to use a 2-20 Hz component of a power spectrum as the non-specific frequency band component and a 6-9 Hz component as the specific frequency band component.

According to the muscular rigidity evaluation method of the present invention, the severity of symptoms can be objectively and quantitatively ensured universality of evaluation and can be easily used for diagnosis. It is also useful for diagnosis of diseases with muscle rigidity such as Parkinson's disease, early diagnosis, severity evaluation, drug efficacy evaluation, and surgical treatment effect determination.

It is a figure which shows the muscular solidity quantitative evaluation apparatus of the state which fixed the upper limb with the elbow joint and the wrist. It is a figure which shows the muscular solidity quantitative evaluation apparatus of the state except the means to fix a wrist. It is a rear view of a muscular rigidity degree quantitative evaluation apparatus. It is the figure which showed the position of the electromyogram and arm which were measured at the time of the bending motion of a healthy test subject. It is the figure which showed the single measurement electromyogram measured at the time of bending movement of a Parkinson's disease patient, the single moving average electromyogram which performed the moving average process, and the average electromyogram. It is the figure which showed the area | region of the integral value of an average electromyogram. It is the figure which showed the area | region which integrates the absolute value of the difference of a single measurement moving average electromyogram and an average electromyogram. It is the figure which showed the result of the frequency analysis at the time of bending operation | movement of a Parkinson's disease patient. It is the figure which showed the area | region of the non-specific frequency band and the specific frequency band. It is the figure which showed the position of the electromyogram and arm which were measured at the time of bending operation | movement of a Parkinson's disease patient. It is a figure which shows the result of having changed the window function time of a moving average process, and calculating the evaluation value of the muscular rigidity by a moving average. It is the figure which showed the result of the frequency analysis at the time of a bending motion of a healthy test subject. It is a figure which shows the result of having calculated the evaluation value of the muscular rigidity by a frequency analysis about a Parkinson's disease patient and a healthy test subject.

Embodiments of the muscular stiffness measurement apparatus according to the present invention will be described in detail below with reference to the drawings.

FIG. 1 shows a stepping motor having an increased operating torque using a gear box 2 directly connected to an arm 4 having means 7 for fixing an upper limb composed of an upper arm 11 and a forearm 12 with an elbow joint and means 10 for fixing with an wrist. 1 shows an operation means for dynamically applying an upper limb bending motion to a subject using 1. Protective equipment such as roller skates can be used to fix the elbow joint and wrist. FIG. 2 shows a state in which the protector of the roller skate, which is a means 7 for fixing the wrist, is removed. The wrist fixture metal fitting 6 for fixing the protective equipment and the wrist fixture metal fitting 6 are attached to the arm 4. A fixing metal fitting 5 for fixing to is shown. FIG. 3 is a view showing an operating means for giving an upper limb bending action from the side opposite to FIG.

When a stepping motor was used alone without using a gear box, sufficient force to move the forearm could not be obtained, but by using the gear box 2 having a torque of 30 N · m, Parkinson It was possible to flex all upper limbs of 10 subjects including sick patients.

By connecting a control device connected to the stepping motor 1 to a computer and creating an operation program, the position of the forearm can be easily set. By using a stepping motor equipped with an angle detector, it is possible to control the position of the forearm and measure the position of the forearm. However, if the control device and the computer are connected using a serial interface, the position cannot be measured simultaneously with the position control if the communication speed is low. In addition, when measuring the position using a stepping motor, the control device may malfunction, causing the forearm to move to the wrong position, which may cause injury to the subject, especially when using high-torque operating means. There was sex. Therefore, it was understood that the position of the forearm must be acquired in several ways.

As a means for detecting the position of the arm 4, a position converter 8 that measures the length of the displacement cable 9 can be used. One end of the displacement cable 9 is fixed to the arm 4 and its length changes according to the bending motion of the upper limb. The position converter 8 is attached so that the length of the displacement cable 9 is the shortest in the state where the upper limb is extended, and the length of the displacement cable 9 is increased as the upper limb is bent. The position transducer 8 always places the displacement cable 9 in a tensioned state using an internal spring, and measures the rotation angle of the cylinder around which the displacement cable 9 is wound by using an angle detector. 9 is a device for measuring the length of 9. An example of such a position transducer is a position transducer manufactured by SpaceAge Control.

The position converter 8 converts the length of the displacement cable 9 into a resistance value proportional to the length, and a voltage proportional to the length of the displacement cable 9 can be obtained by applying a voltage from the outside. By converting this voltage into digital data using an analog-digital converter, the position of the arm 4 can be recorded in the computer.

By recording a voltage proportional to the length of the displacement cable 9 with a plurality of devices, an unexpected movement of the arm 4 caused by a malfunction of the control device can be prevented.

For example, if the voltage recorded in a safety device different from the control device is equal to or higher than a certain voltage or less than a certain voltage, the forearm is moved to an unreasonable position. Therefore, if a stop signal is sent from the safety device and the power supplied to the stepping motor 1 is cut off, unexpected movement of the arm 4 can be prevented and injury to the subject can be prevented.

A surface electromyogram can be used as a measuring means for measuring myoelectric potential. Since it is easy to apply a surface electrode for electromyogram measurement, it is easy to obtain an electromyogram of the biceps that contracts during flexion. Other electromyograms such as head muscles may be used. As the surface electrode, various types of electrodes capable of measuring a surface electromyogram such as a silver-silver chloride electrode can be used. The potential measured at the surface electrode is amplified by an amplifier and converted into digital data using an analog-digital converter, whereby the myoelectric potential is taken into the computer. The sampling frequency in the analog-digital converter needs to be at least 100 Hz, but it is desirable to use a high sampling frequency as long as the performance of the analog-digital converter allows. The Delsys parallel bar surface electrode with a built-in first-stage amplifier is a useful surface electrode with less noise, and the Delsys Bagnoli-2 EMG System can be used as a signal amplifier.

The subject's elbow joint and wrist are fixed to the device for quantitatively evaluating muscle stiffness, and a surface electromyogram is attached to the upper arm. Since the signal noise is large immediately after the surface electromyogram is pasted, it takes time to stabilize the measurement signal for about 5 to 15 minutes while measuring the surface electromyogram.

In order to determine the motion range of the upper limb bending motion, the arm 4 is manually moved, and the extension position where the upper limb is extended is measured and recorded by the position converter 8. Further, the arm 4 is manually moved to measure and record the bending position where the upper limb is bent. The range of motion of the upper limb bending motion is between this extended position and the bent position.

The movement speed of the bending movement can be arbitrarily determined within a range that does not burden the subject, but the bending / extension movement is performed once in 2 seconds so that the speed is almost the same as the measurement method used in the clinic by the doctor. It is desirable to set to repeat.

Since the electromyogram measurement potential varies depending on how the surface electrode is applied and the subject, it is desirable to standardize the electromyogram measurement potential. As a standardization method, an electromyogram potential standardization method can be used in which an electromyogram at rest when the upper limb is not moving is measured for about 20 seconds and standardized based on an average value and variance of the electromyogram at rest. Specifically, it is a method of standardization by subtracting the average value of the resting electromyogram from the electromyogram during flexion measured during the flexion motion of the upper limb and dividing by the variance of the resting electromyogram.

FIG. 4 illustrates an electromyogram and the position of the arm 4 when a surface electrode is attached to a healthy subject and the bending is performed. Subjects were instructed to relax their upper limbs and not perform active movements during movement. The electromyogram shows the absolute value after standardization by the above method. With respect to the position of the arm 4 measured by the position converter, the values are converted so that they are 0 when extended and 1 when bent. It can be seen that in healthy subjects, the electromyogram potential during flexion is small and the potential does not vary.

An electromyogram at the time of a plurality of bending motions is obtained by performing an upper limb bending motion at least 10 times for one subject.

In order to perform quantitative evaluation of muscular rigidity for digital data obtained by taking in biological information related to myoelectric potential obtained from multiple measurements, it is necessary to calculate an analysis value thereof.

The measured electromyogram during flexion has many high-frequency components and is difficult to quantitatively evaluate as it is, so the high-frequency components are removed using a low-frequency filter. As one of the low frequency filters, moving average processing using a window function can be used. The window function is a function in which, for example, the window function time is 1 only and the others are 0. The electromyogram at the time of flexion movement measured at the time of bending-extension-flexion movement is regarded as a single measurement electromyogram, and the window function time is shifted by performing convolution integration of the single measurement electromyogram and the window function. A single moving average electromyogram subjected to the averaging process is obtained.

The thin dotted line in FIG. 5 is a single measurement electromyogram of the biceps brachii when the upper limb flexion motion is given to a Parkinson's disease patient. The thick broken line is a single moving average electromyogram obtained by subjecting the biceps electromyogram to a moving average process with a window function time of 10 ms, and the thick solid line is obtained from 10 flexion-extension / bending operations. It is the average electromyogram which calculated the single moving average electromyogram which performed the moving average process for each of several single measurement electromyograms by the window function time of 10 ms, and calculated the average value of 10 times of measured values. . In the figure, the most bent position is 0 second, and the electromyogram during the extension of the upper limb is shown up to 0.5 seconds. In patients with Parkinson's disease, a marked increase in electromyogram accompanying muscle rigidity is observed in about 100 to 150 ms, and the period is remarkably observed in a single moving average electromyogram subjected to moving average processing.

In order to quantitatively evaluate the enhancement of the electromyogram accompanying the muscular rigidity, which is noticeable in the single moving average electromyogram in FIG. 5, the single moving average electromyogram and the average muscle with respect to the integrated value of the average electromyogram A single moving average electromyogram deviation ratio, which is a ratio of integral values of absolute values of electrogram differences, was calculated. The area indicated by the hatched area in FIG. 6 is the average electromyogram integrated value, which is the integrated value of the average electromyogram, and the area indicated by the hatched area in FIG. 7 is the single moving average electromyogram and the average muscle. It is a moving average electromyogram deviation integral value that is an integral value of an absolute value of an electrogram difference. If the single moving average electromyogram deviation ratio, which is the ratio of the moving average electromyogram deviation integrated value to the average electromyogram, is calculated, the greater the single moving average electromyogram deviation ratio, the greater the muscle stiffness. It shows that. Ten single moving average electromyogram deviation ratios are obtained from ten measurements, and the average value of the single moving average electromyogram deviation ratios is used as an evaluation value of muscle stiffness by the moving average of the subject. be able to.

When calculating the average value of multiple measurements, it is desirable to exclude measurements that include obvious external noise in the electromyogram. In the example of FIG. 5, the calculation method has been described for the measurement data for 0.5 seconds, but actually, the evaluation value is obtained by measuring the electromyogram of the entire operation of flexion-extension-flexion over about 2 seconds as one measurement. It is desirable to calculate

In order to perform quantitative evaluation of muscular rigidity, in addition to the evaluation value of muscular rigidity obtained from the moving average value, a method of quantitative evaluation by applying a frequency analysis method can be used.

The thin dotted line in FIG. 8 shows the absolute value of the electromyogram of the biceps brachii when the upper limb flexion motion is given to a patient with Parkinson's disease, and the calculated frequency power spectrum is superimposed on multiple measurements. It is a thing. The solid line shows the average value of the frequency power spectrum obtained from multiple measurements. In Parkinson's disease patients, a prominent peak associated with muscle stiffness is seen around 8 Hz.

In order to quantitatively evaluate the peak due to muscle stiffness observed in the frequency analysis of FIG. 8, an average value of the frequency power spectrum obtained from a plurality of measurements is calculated, and the non-specific frequency band of the average frequency power spectrum is calculated. The integration is performed for the component data and the specific frequency band component data, respectively, and the ratio of the integration value of the specific frequency frequency band component to the integration value for the non-specific frequency component is calculated.

The solid line in FIG. 9 indicates the average value of the frequency power spectrum obtained from a plurality of measurements. When a frequency component of 2-20 Hz is used as the non-specific frequency band and a frequency component of 6-9 Hz is used as the specific frequency band, the ratio of the integral value of the lower right oblique line region to the integral value of the lower left oblique line region is the frequency. It becomes an evaluation value of muscle stiffness by analysis. It shows that muscle stiffness is increased as the evaluation value of muscle stiffness by frequency analysis is larger.

Among multiple measurements, the evaluation value of muscle stiffness by frequency analysis is calculated for one measurement, and the evaluation value of multiple measurements may be averaged to obtain the evaluation value of the subject. It is simpler to calculate an average value of the obtained frequency power spectrum and calculate an evaluation value of muscular rigidity by frequency analysis from the average frequency power spectrum with less errors.

Next, the method of the present invention will be described in more detail with reference to examples.

1, 2, and 3 are applied to nine Parkinson's disease patients and one healthy person, and the above-mentioned moving average evaluation values and frequency analysis are performed. Based on the evaluation value of muscular rigidity, it was investigated whether quantitative evaluation of muscular rigidity was possible.

FIG. 4 shows an electromyogram when the surface electrode is applied to a healthy subject and the bending motion is performed, and the position of the arm 4. FIG. 10 shows an electromyogram measured for one subject of Parkinson's disease patient. And the positions of the arms 4 are illustrated. Subjects were instructed to relax their upper limbs during movement and not to move actively. The electromyogram showed the absolute value after standardizing by the electromyogram potential standardization method. For the position of the arm 4 measured by the position converter, the values are converted and shown so that 0 is when extended and 1 when bent. In healthy subjects, the potential of the electromyogram during flexion is small, and there is no variation in potential. On the other hand, patients with Parkinson's disease have markedly increased myoelectric potential and myoelectric potential variation associated with muscle stiffness.

FIG. 11 shows the result of calculating the evaluation value of muscle stiffness by moving average while changing the window function time of moving average processing. The black square points are the evaluation values calculated from 9 Parkinson's disease patients, and the white triangle points are the evaluation values calculated from healthy subjects. White circles are the results of a similar evaluation performed on a random time series. The evaluation value of muscle stiffness by moving average is large in Parkinson's disease patients and small in healthy subjects. This difference is particularly noticeable when the moving average window time is 10 ms to 20 ms. In addition, the value calculated from the random time series is as small as the value of the healthy subject, and the evaluation value of muscle stiffness by moving average indicates that it is an appropriate quantitative evaluation method of muscle stiffness.

The thin dotted line in FIG. 8 shows the frequency power spectrum calculated for the absolute value of the electromyogram of the biceps brachii when the upper limb flexion motion is given to a patient with Parkinson's disease, with multiple measurements repeated. The solid line shows the average value of the frequency power spectrum obtained from multiple measurements. Similarly, FIG. 12 shows the frequency power spectrum of a plurality of measurements for healthy subjects as a thin dotted line and the average value as a solid line. In Parkinson's disease patients, a prominent peak associated with muscle stiffness is seen around 8 Hz, whereas healthy subjects have a generally small power spectrum value and no prominent peak.

FIG. 13 shows the result of calculating an evaluation value of muscle stiffness by frequency analysis for Parkinson's disease patients and healthy subjects. White triangle points are evaluation values calculated from nine Parkinson's disease patients, and black circle points are evaluation values calculated from healthy subjects. In the power spectrum for white noise with no remarkable peak, the evaluation value of muscle stiffness by frequency analysis theoretically shows about 0.17 from the area ratio. In healthy subjects, it was about 0.17, and in Parkinson's disease patients, it was about 0.19 or more. Although there is variation compared to the evaluation value of muscle stiffness by moving average, it shows that the evaluation value of muscle stiffness by frequency analysis can be used as a quantitative evaluation method of muscle stiffness.

Nine Parkinson's disease patients measured in the present example were mostly patients with mild symptoms, and it was difficult to recognize muscle rigidity in a subjective evaluation conducted by a doctor. A quantitative evaluation value can be calculated even for a patient with such mild symptoms, and the fact that a difference from a healthy subject is detected is considered to indicate the usefulness of the evaluation apparatus. According to the muscle stiffness evaluation method of the present invention, it was considered that early diagnosis of diseases associated with muscle stiffness such as Parkinson's disease is possible.

1 stepping motor, 2 gear box, 3 arm fixture, 4 arm, 5 fixture, 6 wrist fixture, 7 elbow joint fixture, 8 position transducer, 9 displacement cable, 10 wrist fixture, 11 upper arm, 12 Forearm

Claims (5)

        An operation means for increasing the operation torque using a gear box directly connected to an arm provided with means for fixing the upper limb with an elbow joint and a wrist, and using a stepping motor to give the subject an upper limb flexion motion, Equipped with a myoelectric potential measuring means for measuring myoelectric potential and a forearm position measuring means for measuring the forearm position with a displacement cable by means of a displacement cable, and calculating an analysis value for digital data obtained by taking biological information about myoelectric potential Then, the muscular rigidity degree quantitative evaluation apparatus characterized in that the muscular rigidity is quantitatively evaluated based on the calculated data of the analysis value.       The analysis value is a single movement obtained by moving average processing using a window function for the absolute value of myoelectric potential for one measurement extracted from digital data obtained by taking in myoelectric potential obtained from a plurality of measurements. Calculate the average electromyogram, calculate the average electromyogram from the average value of the calculated multiple single moving average electromyograms, and calculate the average electromyogram integration value from the calculated average electromyogram integration value Calculate the single moving average electromyogram deviation integrated value from the integral value of the absolute value of the difference between the single moving average electromyogram and the average electromyogram for one measurement, and calculate the average electromyogram integration Calculate the single moving average electromyogram deviation ratio, which is the ratio of the single moving average electromyogram deviation integrated value to the value, and use the average value of the single moving average electromyogram deviation ratio obtained from multiple measurements. The apparatus for quantitatively evaluating the degree of muscular rigidity according to claim 1.       The muscle function according to claim 2, wherein the window function used in the moving average process is a function in which only the window function time is 1 and the others are 0, and the window function time is 10 ms to 20 ms. Shrinkage quantitative evaluation device.       Analytical values are subjected to fast Fourier transform on the absolute value of digital data obtained by capturing myoelectric potentials obtained from multiple measurements, and frequency power spectra are calculated for the results of the fast Fourier transforms. An average frequency power spectrum that is an average value of the frequency power spectrum obtained from the measurement is calculated, integration is performed for the non-specific frequency band component and the specific frequency band component of the average frequency power spectrum, and the non-specific frequency component is integrated. The muscular rigidity quantitative evaluation apparatus according to claim 1, which is a ratio of an integrated value of a specific frequency frequency band component to an integrated value of.       The apparatus for quantitatively evaluating muscle stiffness according to claim 4, wherein a 2-20 Hz component of a power spectrum is used as the non-specific frequency band component, and a 6-9 Hz component is used as the specific frequency band component.

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