KR20160022002A - Warning system for real-time muscle fatigue and a method for measuring the real-time muscle fatigue for the same - Google Patents

Abstract

The present invention relates to a warning system for muscle fatigue, and a method for measuring muscle fatigue for the same. The warning system for muscle fatigue comprises a muscle fatigue measurement unit, a wireless transceiver unit, an imaging device, and a muscle fatigue analysis unit. The muscle fatigue measurement unit is mounted on the body of a user to measure a muscle fatigue signal. The wireless transceiver unit wirelessly transmits and receives the muscle fatigue signal. The imaging device shows a condition of the body to the user. The muscle fatigue analysis unit receives and analyzes the muscle fatigue signal, and warns the user if a muscle fatigue value is higher than or equal to a prescribed value.

Description

TECHNICAL FIELD [0001] The present invention relates to a warning system and a method for measuring muscle fatigue of the muscle,

The present invention relates to an alopecia warning system and a method for measuring a muscle fatigue thereof. More particularly, the present invention relates to an alopecia alert system which alerts the user to prevent excessive use of muscles by measuring and analyzing muscle fatigue in real time using an EMG sensor And a method for measuring muscle fatigue therefor.

Recently, I have been enjoying various physical activities such as fitness training, judo, boxing, water skiing, etc. in terms of interest in leisure activities and management of health care and body shape. In addition, athletes and physical workers who use muscle excessively may have excessive muscle strength, which may result in accumulation of muscle fatigue, resulting in temporary muscle weakness resulting in injuries or industrial accidents during exercise. And, if you use excessive muscle due to hobby activities and leave the fatigued muscle without appropriate measures, it will develop into musculoskeletal chronic disease.

As described above, the degree of muscle fatigue is not only a problem of simple muscle damage but also a problem associated with life. Therefore, it is important to check muscle fatigue at all times and measure and prevent muscle fatigue in real time so as not to interfere with work or hobbies. In order to measure the existing muscle fatigue, it is necessary to measure the change in the concentration of lactic acid in the blood or to measure the change in the frequency range of the EMG from the high frequency band to the low frequency band due to the decrease of the conduction velocity of the muscle fiber. However, the measurement method using the change in the concentration of lactic acid requires a blood sample, is invasive, has a slow reaction rate, and the frequency-based method is non-invasive, but the accuracy with conventional frequency analysis is very low.

Usually, muscle fatigue can be judged from the frequency range of the electromyogram signal measured by sensing the skin surface movement (muscle activity potential) of the human muscle and the degree of spread of the electromyogram signal. Here, the EMG refers to a wave form obtained by deriving the action potential change that occurs simultaneously with the contraction of the skeletal muscle, and the spectrum refers to an electromagnetic wave or other wave that is obtained by sorting the wavelength components by a spectroscope. On the other hand, it is difficult to measure and measure muscle fatigue in real time because the existing muscle fatigue measuring method takes a long time to calculate the numerical value of muscle fatigue.

In this regard, Korean Patent Application No. 1998-0011384 discloses an invention capable of accurately measuring the muscle fatigue through an efficient analysis of the spectrum of an EMG signal using an AR modeling technique. Korean Patent No. 10-1040109 discloses a technique Discloses an invention in which a living body signal that is reacted by a human body when tilted is measured and analyzed to utilize it as data for evaluating the ride quality of a train. However, the techniques disclosed above can be used to measure accurate muscle fatigue or to utilize measurement of muscle fatness as data However, it does not provide a technique to prevent muscle damage by warning the user by measuring muscle fatigue in real time.

Therefore, it is necessary to develop a system that feeds back the state of the muscles used by real-time measuring and analyzing the muscle fatigue of the people using the muscle in real time with the increase of the hobby activity and the safety of physical labor.

SUMMARY OF THE INVENTION Accordingly, the present invention has been made in view of the above problems, and it is an object of the present invention to provide a muscle fatigue warning system that measures the muscle fatigue in real time and feeds back the state of muscles using a small EMG sensor .

It is another object of the present invention to provide a method for measuring a muscle fatigue degree for the fatigue fatigue warning system.

According to another aspect of the present invention, there is provided an alopecia warning system comprising an electromyogram measuring unit, a wireless transceiver unit, a video apparatus, and an EMG analyzing unit. Wherein the EMG measuring unit is mounted on a user's body to measure an EMG signal and the wireless transceiver wirelessly transmits and receives the EMG signal and the imaging device indicates the state of the user to the user, And warns the user when a numerical value exceeding a predetermined value is also displayed.

In one embodiment, the EMG measuring unit may include an EMG sensor attached to the muscles of the body to measure the EMG signal and having an alarm function.

In one embodiment, the electromyogram sensor includes an operational amplifier, a high-pass filter, and a low-pass filter, the operational amplifier amplifies the EMG signal, the high-pass filter filters a high-frequency band of the EMG signal, The low-pass filter can filter the low-frequency band of the EMG signal.

In one embodiment, the wireless transceiver may transmit the EMG signal having passed through the high-pass filter and the low-pass filter to the EMG analyzer.

In one embodiment, the EMG analyzing unit receives the EMG signal, and when the EMG signal that has passed through the low-pass filter is larger than a certain level of the EMG signal that has passed through the high-pass filter and the value of the muscle fatigue is low And may transmit an alarm signal to the wireless transceiver.

In one embodiment, the electromyogram measuring unit may receive the alarm signal from the wireless transceiver unit and transmit the alarm signal to the electromyogram sensor.

In one embodiment, the EMG analyzing unit may transmit analysis information of the EMG signal including the degree of muscle weakness to the wireless transceiver unit to the wireless transceiver unit in real time.

In one embodiment, the imaging device may receive the analysis information from the wireless transceiver and display the change in state of the myocardial infarction to the user in real time.

According to another aspect of the present invention, there is provided a method for measuring a muscle fatigue degree, comprising the steps of measuring an EMG signal from an EMG sensor attached to a user, measuring a first EMG signal separated from the EMG signal by a low- Passing a second electromyogram signal separated from the electromyogram signal through a high-pass filter, analyzing the first and second electromyogram signals to analyze the numerical value of the myoepithelia, And warning the user if the number is less than the threshold value.

According to the embodiments of the present invention, the EMG sensor attached to the user transmits the EMG signal measured in real time to the EMG analyzing unit through the EMG measuring unit and the wireless transceiver, and the EMG analyzing unit analyzes the EMG signal The calculation of the muscle fatigue can be performed in a short time, and the muscle fatigue state can be informed to the user in real time by calculating the muscle fatigue value in a short time.

In addition, the EMG sensor is attached to various parts of the body so that it does not interfere with movement, and when the numerical value of muscle fatigue is lower than a predetermined value including an alarm function, the user is prevented from using the muscle by light, sound or vibration So that damage to the muscles can be prevented from occurring.

In addition, the user can visually check the numerical value and the change state of the muscle fatigue transmitted in real time through the smartphone or the monitor during the exercise or work, and by analyzing the numerical value of the muscle fatigue by returning home after exercise or work, The efficiency can be increased.

In addition, since the muscle fatigue measuring method can be easily calculated through the first EMG signal and the second EMG signal passed through the high pass filter and the low pass filter in comparison with the conventional muscle fatness measuring methods, Or muscle sores can also tell you the numbers.

FIG. 1 is a block diagram showing an alveolar fatigue warning system according to an embodiment of the present invention. FIG.
2 is a block diagram showing a circuit structure of the electromyogram sensor of Fig.
FIG. 3 is a flow chart illustrating a method of measuring a muscle fatigue level for the fatigue fatigue warning system of FIG. 1. FIG.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the invention are shown. While the present invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments. It is to be understood, however, that the invention is not intended to be limited to the particular forms disclosed, but on the contrary, is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention. Like reference numerals are used for like elements in describing each drawing. The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the term "comprises" or "comprising ", etc. is intended to specify that there is a stated feature, figure, step, operation, component, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

 Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing an alveolar fatigue warning system according to an embodiment of the present invention. FIG.

Referring to FIG. 1, the muscle fatigue warning system 10 includes an EMG measuring unit 100, a wireless transceiver 200, an EMG analyzing unit 300, and a video device 400.

The electromyogram measuring unit 100 includes an electromyogram sensor 110.

The EMG measuring unit 100 receives the EMG signal through the EMG sensor 110 attached to the muscles of the user. The electromyogram sensor 110 is attached to legs or arms of a user who uses muscles such as working or exercising from the outside through a band or the like, and measures the EMG signal every second or minute according to the setting. Various sensors such as a force measuring sensor, an angle measuring sensor, a tilt sensor, an electrocardiograph sensor, a respiration sensor, a pressure sensor, and a foot switch sensor can be used together with the electromyogram sensor 110 have.

Here, the EMG signal is an electrical signal generated along the muscle fiber from the muscle surface by the movement of the body, the size of which is usually less than 10 mV, the frequency range is less than 500 Hz and the needle is directly inserted into the muscle, Is a signal to be measured. The electromyogram sensor 110 uses surface electromyography to measure an electrode by attaching an electrode to the skin surface. Therefore, the electromyogram sensor 110 is attached to a part of the body where the user frequently uses the muscle, and the electromyogram signal generated per second is measured in real time.

The EMG signal is transmitted to the wireless transceiver 200 through wireless communication. The wireless communication method includes a telemetry method. The telemetry scheme is a non-contact bi-directional transmission scheme, and the structure transmits the EMG signal generated by the EMG sensor 110 and the EMG sensor 110 attached to moving muscles to a stationary amplifier connected in a line .

More particularly, the telemetry is divided into a transmitter and a receiver. The transmitter includes an encoder for converting the EMG signal into a format convenient for transmission, and a modulator for exchanging the EMG signal with a modulated signal suitable for transmission And a telemetry transmitter that converts the electromyogram signal into an electric signal and outputs the electric signal in the form of a radio wave of the public. The receiving unit represents the wireless transceiver 200, and is composed of an antenna, a radio frequency amplifier, and a demodulator for extracting the original EMG signal from the modulated EMG signal.

Accordingly, the EMG measuring unit 100 receives the EMG signal from the EMG sensor 110 and transmits the EMG signal to the WTRU 200 through the transmitting unit of the telemetry in real time.

The wireless transceiver 200 receives the EMG signal and transmits the data of the EMG signal to the EMG analyzer 300. The wireless transceiver 200 may be located in a workplace or a home where the user is working together with the EMG analyzer 300. The user may return to the workplace or home after work or exercise to monitor the EMG There is a merit that it is possible to evaluate the exercise intensity and the work intensity by checking the change of the signal and plan for the improved work and the exercise efficiency.

The EMG analyzing unit 300 receives the EMG signal and measures the degree of muscle fatness represented by the EMG signal. In general, when the muscle fatigue is high, the concentration of lactic acid in the blood increases, but it is difficult to measure in real time because the blood sample is the necessary invasive method. In addition, when the muscle fatigue is high, the frequency range of the EMG shifts from the high frequency band to the low frequency band due to the decrease in the conduction velocity of the muscle fiber, which is non-invasive but has a disadvantage in that the accuracy of the conventional frequency analysis is very low.

Therefore, the present invention analyzes the EMG signal in real time using a filter-based muscle fatness measurement method which is more accurate and can be applied in real time than a conventional frequency analysis which will be described later. When the muscle wave intensity is high, To the electromyogram sensor 110 through the controller 200 to warn the user.

Meanwhile, the video device 400 includes a smart phone that the user always carries, a monitor located in the health club, a small monitor mounted on the bicycle, and smart glasses displaying various kinds of information in glasses. Therefore, the muscle fatness information evaluated by the EMG analyzing unit 300 and the force measuring sensor, the angle measuring sensor, the tilt sensor, the electrocardiogram sensor, the breathing sensor, the pressure sensor, and the walking switch, Sensors, and the like, and transmits the analyzed body information to the video device 400 through the wireless transceiver 200. FIG. The information can be transmitted in real time even when the degree of muscle weakness is low, so that a change in the physical condition of the user can be monitored, and the change in various physical information as well as the myopathy can be checked.

2 is a block diagram showing a circuit structure of the electromyogram sensor of Fig.

2, the electromyogram sensor 110 includes an operational amplifier 112, a high-pass filter 113, a low-pass filter 114, and a voltage converter 115.

The electromyogram sensor 110 is attached to a part of the body where the muscles mainly used by the user during work or exercise are located. It can be attached to various parts including the arms, thighs, calves, chest, abdomen and ankle. It is made in small size and strong in adhesion, so that it is not likely to be detached during work or exercise by the user and is not inconvenient to move.

And a minute muscle activity potential that occurs in the muscles due to work or exercise is detected. For example, when the user attaches the EMG sensor 110 to the thigh and rides a bicycle, the user uses the muscle of the thigh, and the minute muscle activity potential generated in the thigh muscle is transmitted through the EMG sensor 110 Transmitted to the electromyogram analyzer 300 through the wireless transceiver 200 and analyzed for the state of the thigh muscles including the degree of muscle weakness to be displayed on the video device 400 used by the user . When the muscle fatigue degree is high or dangerous, a warning is given through the electromyogram sensor 110.

The operational amplifier 112 is a DC-coupled high gain voltage amplifier having one differential input and usually one single output. One of the operational amplifiers 112 generates an output voltage that is usually several hundreds to several thousands times larger than the voltage difference between its input terminals. Thus, the operational amplifier 112 is formed for amplification of minute muscle activity potentials. In addition, the operational amplifier 112 is advantageous in that band-pass filters for removing noise can be designed.

The high pass filter 113 and the low pass filter 114 are designed together with the operational amplifier 112 and the EMG signal amplified by the operational amplifier 112 is supplied to the high pass filter 113, Pass filter 114, respectively. The electromyogram signal passing through the high-pass filter 113 passes through the high-pass filter 113 and passes only a signal having a frequency higher than a predetermined level. The EMG signal removes gentle fluctuations in a high frequency, Only the above-mentioned frequency signals are detected. The electromyogram signal passing through the low-pass filter 114 passes through the low-pass filter 114 so that only a low-frequency signal of a certain level passes through the low-pass filter 114, And detects only a frequency signal of a predetermined level or more which changes abruptly.

The EMG signal passing through the high pass filter 113 and the low pass filter 114 passes through the voltage converter 115 and moves to the electromyogram analyzer 300 through the wireless transceiver 200 . The EMG analyzing unit 300 analyzes the EMG signal that has arrived through the high and low pass filters 113 and 114 using a real time empirical analysis method to measure the fatigue of the user.

In this case, existing methods for measuring the muscle fatness include a method using a median frequency and a mean frequency, a Fourier transform and a discrete wavelet transform. The method using the median frequency and the median frequency is generally performed by measuring and analyzing a change in the power spectrum of the electromyography. This is because, unlike the real-time muscle fatigue analysis method, It exhibits low sensitivity under exercise.

Although the Fourier transform and discrete wavelet transform methods are relatively accurate, there is a disadvantage in that it is difficult to measure the degree of muscle fatigue in real time in a large amount of calculation in analyzing the muscle fatigue degree.

[Equation 1]

The first equation is related to the Fourier transform for measuring the _muscle fatigue (FI _nsm5 ), and it takes a long time to calculate the fatigue degree through the first equation.

&Quot; (2) "

The second equation is a mathematical expression for measuring the degree of mynor (WIRE51) through the discrete wavelet transform, and it takes a long time to calculate the degree of myopia in real time like the Fourier transform.

&Quot; (3) "

On the other hand, the equation (3) as the equation in which the geunpiro of how the present application is also used for the analysis method, S _HPF (i) denotes the EMG signal that has passed through the high-pass filter _{(113), S lPF (i} ) Pass filter 114. The low-pass filter 114 receives the EMG signal. The high-pass filter 113 passes only a signal of a frequency higher than a specific frequency of the EMG signal passing through the high-pass filter 113 and reduces noise. The low-pass filter 114 low- 114 of the electromyogram signal and reduces the noise.

Furthermore, since in the equation (3) the geunpiro Fig value (FI value) is low, the more indicates that the geunpiro increased to decrease the strength, a low frequency band of the EMG signal is increased if the geunpiro Increases the S _HPF (i ) Decreases, the S _lPF (i) increases, and the _muscle fatigue degree value decreases to the contrary.

 Therefore, the muscle fatigue analysis method according to the present invention measures the muscle fatigue of the user in real time in a short time by using only the simple operation compared with the method using the Fourier transform and the method of analyzing the muscle fatness using the discrete wavelet transform There is an advantage to be able to do.

Table 1 shows the results of the muscle fatigue analysis using the Fourier transform and the discrete wavelet transform and the results of the muscle fatigue analysis method.

The right rectus femoris is one of the muscles formed on the front of the thigh and the metatarsophalas is located at the lower end of the back side of the rectus femur. The outside light side is located outside the back side of the rectus femoris, The biceps triceps are located behind the biceps biceps, and the tibialis anterior muscle represents the muscle located at the anterior part of the knee.

In the experimental environment, six types of isotonic exercises are performed to measure the fatigue of the muscles. The isotonic movement refers to all the exercises for lifting the weight equipment to bring about a change in the muscles. In order to measure the degree of muscle fatigue for each muscle, a set consisting of ten joint movements and two minutes of rest at the location of the muscle is run five times to analyze the muscle fatigue.

[Table 1]

The muscle fatigue results of the muscles measured using the Fourier transform and the muscle fatigue results of the muscles measured using the fatigue measuring method (FI _hlrOPT ) of the present invention are compared with each other, Of the results of the femoral rectus to the tibialis anterior to the tibial rectus to the tibialis ankle using the Fourier transform and the discrete wavelet transform method, similar.

This means that the muscle fatigue analysis method exhibits the same change as that of the muscle fatness measured using the conventional Fourier transform and the discrete wavelet transform. Therefore, the EMG analyzing unit 300 for analyzing the EMG signal by the muscle fatigue analyzing method analyzes the EMG signal in real time, and can alert the user when the muscle fatigue of the user reaches a dangerous level .

FIG. 3 is a flow chart illustrating a method of measuring a muscle fatigue level for the fatigue fatigue warning system of FIG. 1. FIG.

The muscle fatness measurement method is substantially the same as the above-described muscle fatness measurement method of the fatness alert system 10 described with reference to Figs. 1 and 2 except for the first EMG signal and the second EMG signal. Use numbers and omit duplicate descriptions.

3, the EMG sensor 110 measures EMG signals of muscles attached to the body of the user and is divided into the high-pass filter 113 and the low-pass filter 114 (Step S101).

The first electromyogram signal passes through the low pass filter 114 and passes through only a signal of a frequency lower than a specific frequency while noise is removed. At this time, as the muscular fatigue increases, the frequency region of the first EMG signal is shifted to the low frequency band, and when the signal passes through the low-pass filter 114, the EMG signal exhibits a high EMG signal (Step S102).

 The second electromyogram signal passes through the high pass filter 113, and noise is removed, and only a signal having a frequency higher than a specific frequency is passed. At this time, the frequency of the second EMG signal is shifted to the low frequency band due to the increase of muscular fatigue. When the second EMG signal passes through the high pass filter 113, the second EMG signal is transmitted to the low pass filter 114 1 < / RTI > electromyogram signal (step S103).

The magnitude of the first electromyogram signal having passed through the low pass filter 114 is greater than a predetermined magnitude of the magnitude of the second electromyogram signal having passed through the high pass filter 113, The EMG analyzing unit 300 transmits an alarm signal to the EMG sensor 110 and the imaging device 400 through the wireless transceiver 200 in step S104.

If the muscle fatigue value (FI value) is not less than a predetermined value, the EMG analyzing unit 300 transmits the analyzed muscle fatigue degree to the imaging device 400 through the wireless transceiver 200 in real time Step S104).

The electromyogram sensor 110 and the imaging device 400 receive the alarm signal at the wireless transceiver 200 and warn the user (step S105). According to the embodiments of the present invention, the electromyogram sensor 110 attached to the user transmits the electromyogram signal measured in real time through the electromyogram measuring unit 100 and the wireless transceiver 200 The EMG analysis unit 300 calculates the muscle fatigue level in a short time using a muscle fatness measurement method that can be calculated in a shorter time than the conventional calculation method of the muscle fatigue frequency, There is also an advantage that the user can be informed about the condition of muscle weakness.

In addition, the electromyogram sensor 110 is attached to various parts of the body so that it does not interfere with movement, and includes an alarm function. When the muscle fatigue level is lowered below a predetermined value, So that it is possible to prevent muscle damage from occurring.

In addition, the user can visually confirm the numerical value and the change state of the muscle fatigue transmitted through the smartphone or the monitor in real time during exercise or work, and after returning home after exercise or work, the muscle fatigue can be analyzed through numerical analysis The efficiency of the work can be improved.

In addition, the muscle fatness measurement method is a simple calculation using a first EMG signal and a second EMG signal that have passed through the high-pass filter 113 and the low-pass filter 114 in comparison with existing muscle fatness measurement methods It is possible to inform the user of the alarm signal or the value of the muscle fatigue in real time.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the present invention as defined by the following claims. It can be understood that it is possible.

The anti-fatigue warning system and the method for measuring fatigue for it in accordance with the present invention have industrial applicability that can be used in homes, health clubs and work places.

10: Muscle fatigue warning system 100: EMG measuring unit
110: EMG sensor 112: operational amplifier
113: high-pass filter 114: low-pass filter
115: voltage converter 200: wireless transmitting /
300: EMG analysis unit 400:

Claims (9)

An EMG measuring unit mounted on the user's body for measuring an EMG signal;
A wireless transmission / reception unit wirelessly transmitting / receiving the EMG signal;
A video device that displays a state of muscle fatigue to the user; And
And an EMG analyzer for receiving and analyzing the EMG signal,
A warning system that alerts the user if a number of muscle fatigue above a certain level appears. The apparatus according to claim 1, wherein the electromyogram measuring unit comprises:
And an electromyogram sensor attached to the muscles of the body for measuring the EMG signal and having an alarm function. 3. The method of claim 2,
Wherein the electromyogram sensor comprises:
An operational amplifier (OP Amp) for amplifying the EMG signal;
A high-pass filter for filtering a high-frequency band of the EMG signal; And
And a low-pass filter for filtering a low-frequency band of the EMG signal. The method of claim 3,
The wireless transmitting /
And the EMG signal transmitted through the high-pass filter and the low-pass filter is transmitted to the EMG analyzer. [5] The apparatus of claim 4,
And an alarm signal is transmitted to the radio transceiver when the electromyogram signal received by the electromyogram signal and passed through the low-pass filter is higher than a certain level of the electromyogram signal passing through the high-pass filter and the value of the muscle- Wherein said at least one of said at least two of said at least two of said at least two of said at least one of 6. The apparatus according to claim 5,
Receives the alarm signal from the wireless transceiver and transmits the alarm signal to the electromyogram sensor. [5] The apparatus of claim 4,
And transmits the analysis information of the EMG signal including the muscle fatigue value to the wireless transceiver unit to the wireless transceiver unit in real time. 8. The apparatus according to claim 7,
Receiving the analysis information from the wireless transceiver and displaying the state change of the muscle fatigue state to the user in real time. Measuring an EMG signal from an EMG sensor attached to a user;
Passing a first electromyogram signal separated from the electromyogram signal through a low-pass filter;
Passing a second electromyogram signal separated from the electromyogram signal through a high-pass filter;
Analyzing the first and second EMG signals and analyzing the myoepithelial level; And
And alerting the user if the muscle fatigue level is less than a predetermined value.

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