KR20120094870A - System for measure of electromyogram by suit type electromyogram sensors and analisys method of rehabilitation using thereof - Google Patents

Abstract

PURPOSE: A system for measuring nonintrusive electromyogram and a method for analyzing rehabilitation state using the same are provided to calculate basic data for analyzing and managing health conditions using obtained bio-information. CONSTITUTION: Analog to digital converters(201,202) converts and latches bio-signals into digital signals by respectively receiving the bio-signals from each channel. Upper and lower limb electromyogram measuring units(130,140) respectively detect electromyographic signals at upper and lower limbs. A wireless reception unit(211) wirelessly receives each electromyographic signal detected from the upper and lower limb electromyogram measuring unit. An interface transformation unit(203) converts and outputs inputted each channel signal for matching with an external interface. A first microcontroller(204) calculates parameters for determining the movement, health condition, and sensibility recognition of a person to be tested.

Description

System for measure of Electromyogram by suit type Electromyogram sensors and Analisys Method of Rehabilitation using approximation

The present invention relates to a system for measuring unrestrained electromyography of a muscle assist system, and more particularly, electromyogram (ECG), electrocardiogram (ECG), etc. to shoulders and chests of a vest-type suit worn by a subject such as clothing. Equipped with a biosignal sensor including heart sound, skin temperature, and sensor, the EMG sensor is attached to the upper limb and lower limb of the subject, as well as the biosignal for analyzing the subject's health. The present invention relates to an unrestrained EMG measuring system for analyzing and determining the rehabilitation level using the measured EMG signals, and to a method for analyzing the rehabilitation state using the same. .

In general, the u-healthcare system is a health care and medical service that can be used anytime, anywhere by combining IT and health care services, and is a system for remotely managing diseases and maintaining and improving the health of the general public.

For this purpose, the biometric information acquisition device must be attached to or worn on the subject's body to obtain the biometric information more accurately from the subject, and to obtain the biometric information in an unbounded state.

That is, the biometric information acquisition apparatus according to the prior art mainly includes electrocardiogram (ECG), pulse wave (PPG), skin electrical resistance (GSR), skin temperature (SKT), body fat (BMI), electromyogram (EMG), muscle signal ( It is a device that acquires MMG) from sensors, and various types of restraint such as watch type, band type, direct body attachment type, suit type, etc. in order to continuously acquire biometric information without disturbing the subject's daily life. It is composed of a biological information acquisition device.

The non-binding biometric information acquisition device obtains biometric information from the subject's body, stores the obtained biosignal in a memory, or transmits the biosignal to an analysis / management system as a wireless signal, thereby analyzing the acquired biosignal. To diagnose or identify

However, the apparatus for obtaining unbound biometric information according to the related art is composed of a wristwatch type, a band type, a body directly attached type, a suit type, etc. according to the characteristics of the biometric information to be obtained, and according to the biometric information to be acquired. Since a type of an acquisition device is determined and a corresponding type of acquisition device must be used to acquire different biometric information, there is a problem in that a plurality of different biometric information acquisition devices must be worn in order to acquire various biometric information.

Accordingly, the present invention provides an electromyogram (ECG), electrocardiogram (ECG), heart sound, skin temperature, etc. in the shoulder and chest of a vest-type suit worn by a subject such as clothing to improve the problems of the prior art. Equipped with a bio-signal sensor including a sensor, the EMG sensor is attached to the upper limb and lower limb of the subject, as well as the bio-signal for analyzing the subject's health status. The purpose of the present invention is to provide an unbound EMG measurement system that allows the system to control the muscle assistance system based on this.

Another object of the present invention is to acquire and analyze the path data and the velocity data obtained through the EMG signal, the 3-axis acceleration and the gyro sensor measured in the EMG measurement unit mounted on the upper and lower parts of the subject measured in the unrestrained EMG measurement system The present invention provides a rehabilitation status analysis method using unrestrained EMG signal of muscle strength assistance system to determine rehabilitation status and rehabilitation status according to one result.

Unbounded EMG measurement system for achieving the object of the present invention is a number of EMG sensors, electrocardiogram sensors, ECG sensor, heart sound sensor and skin temperature sensor for obtaining EMG, electrocardiogram (ECG), heart sound, respiration and skin temperature from the subject An unconstrained EMG measurement system including a biosensor unit, comprising: an AD converter for receiving and receiving respective bio signals obtained from each of the EMG sensors, the ECG sensor, the sound sensor, and the skin temperature sensor for each channel into digital signals; Upper and lower EMG measuring units for detecting EMG signals in upper and lower arms of the examinee; A wireless receiver configured to wirelessly receive respective EMG signals detected by the upper and lower EMG measuring units; Interface conversion for collecting the bio-signals for each channel input through the AD converter and the wireless receiver, determining which channel the collected bio-signals are, and converting and outputting the input-channel signals for external interface matching. part; And a first microcontroller which removes noise of a biosignal input from the interface converter and analyzes each biosignal to calculate parameters for determining a subject's operation, health status, and emotion recognition. The biosensor unit is attached to the inside of the biosignal measurement chute that the subject can wear, and the upper and lower leg electroconductivity measuring unit is attached to the inside of the band that can be worn on the upper and lower parts of the subject.

The upper and lower EMG measuring unit is in contact with the arm of the subject EMG sensor for detecting an EMG signal; An amplifier for amplifying the detection signal of the EMG sensor to a predetermined level; A three-axis acceleration sensor and a three-axis gyro sensor for detecting the movement acceleration and the angular velocity signal of the subject; A second microcontroller that receives signals input from the amplifier, a three-axis accelerometer sensor, and a three-axis gyroscope sensor, converts them into digital data, processes the signals, and wirelessly transmits the signals; A power supply unit supplying power to each unit; And a charging port for charging the battery of the power supply unit.

The second microcontroller may include: a multiplexer configured to receive an operation signal input from the amplifier, a three-axis acceleration sensor, and a three-axis gyroscope sensor and multiplex the output signal; An AD converter for converting an EMG signal and an operation signal of the examinee output from the multiplexer into a digital signal; A register that stores the EMG and motion data of the subject converted from the AD converter for a predetermined time; A wireless interface unit for converting each data stored in the register to match the wireless interface; And a wireless transmitter for wirelessly transmitting the EMG and motion data output from the wireless interface unit.

Rehabilitation status analysis process using the unbound EMG measurement signal to achieve another object of the present invention is a first microcontroller received an EMG signal obtained through a plurality of EMG measurements attached to the upper and lower arms of the subject In the rehabilitation state analysis method using an unrestrained EMG signal to analyze the rehabilitation state of the subject by the EMG signal from the EMG measuring unit attached to the upper and lower parts of the subject as the subject performs a specified motion A first process of obtaining each; A second step of comparing the EMG signal with a previously stored reference EMG signal EMG_ref; And a third step of determining a degree of rehabilitation and a degree of distortion of the movement path according to the comparison result of the second step.

Rehabilitation status analysis process using the unbound EMG measurement signal to achieve another object of the present invention is the EMG signal measured by the EMG measurement unit attached to the upper and lower rehabilitation side of the subject, three-axis acceleration sensor and three In the rehabilitation state analysis method using an unbounded EMG signal to analyze the rehabilitation state of the subject by the first microcontroller received the upper and lower motion path and speed measured by the axis gyroscope sensor, the subject performs a specified motion A first step of acquiring an EMG signal from each of the EMG measurement units attached to the upper and lower parts of the subject according to the present invention; A second process of acquiring upper and lower motion paths and velocity data of the subject through the 3-axis acceleration and 3-axis gyroscope sensors; A third step of comparing each EMG signal (EMG) measured in the first step with a reference EMG signal; A fourth step of comparing the upper and lower motion path and velocity data of the examinee obtained in the second step with the reference motion path and velocity data; And a fifth step of determining a degree of rehabilitation and a path distortion of the subject according to the comparison result in the third and fourth steps.

The unconstrained EMG measuring device and rehabilitation state analysis method according to the present invention is a biosignal measuring suit when a biosignal measurement suit equipped with an electrocardiogram (EMG), an electrocardiogram (ECG), a heart sound and a skin temperature sensor is worn by a subject. It is possible to acquire a variety of biometric information at once by just wearing a, and to calculate the basic data for analyzing and managing the health condition at once by using the obtained biometric information, as well as the upper and lower arms of the subject The EMG sensor is attached to the arm controller of the muscle assisting system based on the input EMG signal.

In addition, by analyzing the EMG signal measured from the unrestrained EMG measurement device and the three-axis acceleration and path data obtained from the upper and lower limbs, and provides the result data of the analysis and determination of the rehabilitation state, the examinee performs rehabilitation by referring to this More effective rehabilitation is effective.

1 is a block diagram of a subject wearing an unrestrained electromyography measuring system according to the present invention,
FIG. 2 is a configuration diagram of a state in which the biosignal measuring suit of FIG. 1 is unfolded,
3 is a block diagram of the upper and lower arm EMG measurement device configured as a band type according to an embodiment of the present invention,
4 is a block diagram of the entire system of the unbound EMG measurement system according to the embodiment of the present invention,
FIG. 5 is a detailed block diagram of the second microcontroller in FIG. 3;
6 to 8 are flowcharts of a rehabilitation state analysis process using an unrestrained EMG signal according to an embodiment of the present invention.

With reference to the accompanying drawings with respect to the specific configuration and operation of the unbound EMG measurement system according to an embodiment of the present invention will be described in detail as follows.

1 is a block diagram of a state in which a subject wears the unrestrained EMG measurement system according to an exemplary embodiment of the present invention, and FIG. 2 is a block diagram of a state in which a biosignal measurement suit is unfolded and is configured in a vest form that a subject can wear A biosignal measurement chute 101 equipped with a plurality of sensors for measuring a biosignal of a subject, six electrocardiogram sensors 111 mounted on an inner surface of the biosignal measurement chute 101, and one three-point electrocardiogram sensor ( 112, one heart sound sensor 113, the skin temperature sensor 114 and the signal measured from each of the sensors (111 ~ 114) receives the signal processing and calculates various parameters for determining the health status of the subject Consists of a control board 200.

The bio-signal measuring suit 101 is to be worn by the examinee in the form of a vest, and configured in the upper, middle, and lower sizes for convenience of wearing, and to be used as a fixing member after wearing by an adhesive method such as Velcro.

The material is made in the form of a span to increase the adhesion to the subject's body to increase the detection efficiency of each sensor (111 ~ 114). In another embodiment, after injecting air into the biosignal measuring chute 101, a pneumatic chute configured to be in close contact with each of the sensors 111 to 114 to the subject's body is also possible.

The electrodes of the six electrocardiogram sensors 111 and the electrocardiogram sensor 114 are composed of fabric electrodes and carbon nanotube (CNT) electrodes to facilitate attachment to the biosignal measurement chute 101 and increase biosignal detection efficiency. .

On the other hand, the bio-signal measurement chute 101 is attached to a power supply battery (not shown) for power supply, as well as each sensor (111 ~ 114) and the control board 200, each of the sensor (111 ~ 114) ) Is attached to detect the vital signs from the chest, armpits, shoulders or back.

3 is a configuration diagram of an extended state of the upper and lower arm EMG measuring device configured as a band type according to an embodiment of the present invention, the upper and lower arm EMG measuring device is worn in the form of a band on the upper and lower arms of the subject The upper and lower leg electroconductivity measuring units 130 and 150 for detecting the EMG signals are respectively mounted in the upper and lower band bands 102 and 103.

That is, specific configurations of the upper and lower EMG measuring units 130 and 150 attached to the upper and lower bands 102 and 103 may include a sensor electrode 131 for detecting an EMG signal, and the sensor electrode 131. An amplifier 132 for amplifying the weak electric signal detected from the sensor, a three-axis acceleration sensor and a three-axis gyro sensor 133 for detecting the upper and lower motions of the subject, the amplifier 132 and the three-axis acceleration sensor, and A second microcontroller 140 for converting the signal input from the three-axis gyro sensor 133 into digital data, signal processing and wirelessly transmitting the power, and a power supply unit for supplying power to the units 131 to 133 and 140. 136); And a charging port 137 for charging the battery of the power supply unit.

Here, the second microcontroller 140 may be a wireless module capable of wireless communication such as Bluetooth, ZigBee, Nordic, etc., but preferably in the present invention, a one-chip in which the microcontroller and Nordic are combined. Consists of.

FIG. 5 is a detailed block diagram of the second microcontroller 140 in FIG. 3. The operation signal input from the EMG signal amplifier 132, the 3-axis acceleration sensor, and the 3-axis gyroscope sensor 133 is multiplexed and output. A multiplexer 141, an AD converter 142 for converting the EMG signal and an operation signal of the examinee output from the multiplexer 141 into a digital signal, an EMG of the examinee converted from the AD converter 142, and A register 143 that stores operation data for a predetermined time, a wireless interface unit 144 for converting each data stored in the register 143 to match a wireless interface, and the EMG output from the wireless interface unit 144 And a wireless transmitter 145 for wirelessly transmitting operation data to the wireless receiver 211 of the control board 200 in a Nordic manner.

4 is a block diagram of an unbounded EMG measuring system according to an exemplary embodiment of the present invention, wherein the control board 200 receives a radio transmission signal from the upper and lower EMG measuring units 130 and 150. 211, first and second AD converters 201 and 202 which receive the detection signals of the sensors 111 to 114, convert them into digital signals, and output the latches; and the AD converters 201 and 202. Collecting biometric data for each channel and upper and lower extremity EMG data from the wireless receiver 211, determining which channel data the collected biometric data is, and matching the data of each input channel with an external interface The interface converter 203 converts and outputs the noise, and removes the noise of the biometric data input from the interface converter 203, and analyzes each biosignal to determine parameters for health status and emotional recognition of the subject. Calculate and Recall Data of the first microcontroller 204 and the first microcontroller 204 or the interface converter 203 for calculating the motion and position data of the subject from the EMG data of the lower limbs and the EMG data of the chest and shoulders. It is composed of a muscle strength assistance system interface unit 205 for transmitting to the external device, and transmits the operation and position data of the subject to the Arm controller.

The weak signal sensed by each of the sensors 111 to 114 is composed of respective amplifiers 121 that amplify above a set level and transmit the first and second AD converters 201 and 202.

The first and second AD converters 201 and 202 are composed of eight input channels, respectively, and the first AD converter 201 is an EMG signal R_EMG1 to R_EMG6 of the EMG sensor 111 mounted on the right side. And, receiving the ECG signal ECG of the ECG sensor 112, the second AD converter 202 is the EMG signals (L_EMG1 ~ 6) of the EMG sensors 111 mounted on the left side, the heart sound sensor and skin temperature Receive sensor sound and temperature data.

Referring to the operation of the present invention configured as described above in more detail with reference to Figures 1 to 5 as follows.

First, the six electrocardiogram sensors 111, one three-point electrocardiogram sensor 112, one heart sound sensor 113, and one skin temperature sensor 114 mounted on the biosignal measurement chute 101 are examined. Each part of the body 100 detects the corresponding biosignal.

That is, the six electrocardiogram sensors 111 and one electrocardiogram sensor 112 detect electrical signals from positive and negative electrodes, and amplify them through the amplifiers 121 so as to amplify the first and second ADs. Input to the transducer 201, 202, the heart sensor 113 acquires the heartbeat sound of the subject 100 by using a microphone and converts and amplifies the electrical signal of a predetermined level to the second AD converter 202 ), The skin temperature sensor 114 detects the temperature from the armpit side of the subject 100, converts and amplifies the electrical signal into a predetermined level, and inputs the same to the second AD converter 202.

The first and second AD converters 201 and 202 configured of each of the eight channels convert the bio signals input through the respective channels into digital data, latch the setting time, and then, to the interface converter 203. Output

The interface converter 203 collects biometric data input from the first and second AD converters 201 and 202, determines which channel biometric data is present, and determines the first microcontroller 204 and muscle power. After converting for interface matching with the auxiliary system interface unit 205, the output is performed.

Meanwhile, the upper and lower leg EMG data detected by the upper and lower leg EMG measuring units 130 and 140 mounted in a band type on the upper and lower legs of the examinee 100 are transmitted to the control board 200 as wireless data. .

3 and 5, the upper and lower EMG measuring units 130 and 140 are mounted on inner surfaces of the upper and lower band bands 102 and 103, respectively, to contact respective EMG signals. The same configuration and action will be detected. Therefore, the operation of the upper limb electromyography unit 130 will be described in more detail with reference to an embodiment, and the detailed operation description of the lower limb electromyography measuring unit 140 will be described with reference to FIGS. 3 and 5.

That is, the upper limb EMG measuring unit 130 detects the EMG signal through the sensor electrode 131 in contact with the skin, amplifies the weak EMG signal through the amplifier 132 to a predetermined level, and then the second microcontroller 140. The second microcontroller by detecting a position, azimuth, angular velocity and acceleration signal in a three-axis (x, y, z) direction measured from a three-axis acceleration sensor and a three-axis gyro sensor 133 mounted in a band. Output to 140.

The second microcontroller 140 receives the signals sensed by the sensors 131 and 133 and multiplexes them in the multiplexer 141 to output them. Each sensor signal output through the multiplexer 141 is converted into a digital signal through the AD converter 142, stored through the register 143, and wireless data of the Nordic wireless type through the wireless interface matching unit 144. After conversion to the wireless transmission unit 145 via the wireless signal measurement chute 101 of the wireless receiver 211 is transmitted.

The first microcontroller 204 of the biosignal measurement chute 101 removes and analyzes the noise of the biometric data input from the interface converter 203 and analyzes the operation state, health state or emotion of the subject from the analyzed data. Various parameters for determining the state are calculated.

The electrocardiogram data (ECG) is analyzed to calculate important parameters that can determine the health status of the subject, such as minute respiratory rate, R-peak, RRI, and HR.

That is, the input ECG data removes noise having high frequency and low frequency components through low and high pass filters, performs first-order differential and square root calculations, and performs R-peak through an envelope detection algorithm. The RRI and pulse rate (HR) are calculated from the R-peak.

On the other hand, the input heart sound data can not only calculate the parameters for determining the heart state such as heart rate per minute through the analysis process after removing the noise, but also replace the heart sound data to calculate the parameter when noise occurs in the electrocardiogram data. do.

As described above, each parameter calculated by the first microcontroller 204 is a controller (not shown in the figure), a subject health diagnosis system or a subject stress analysis, an emotional state analysis, and the like of the muscle assisting apparatus through the external communication unit 205. It can be output as a basic data of the system.

On the other hand, the first microcontroller 204 is each of the EMG data, gyro data, angular velocity data and the bio-signal measurement suit from the upper and lower extremity EMG measuring unit 130, 150 input through the wireless receiver 211 The EMG signal from the EMG sensor 111 mounted on the 101 is analyzed to calculate the upper and lower position, the movement direction, and the speed of the subject, and then output to the muscle strength assistance system interface unit 205.

The muscle force assisting system interface unit 205 transmits the operation data such as the upper and lower legs of the subject, the motion direction and the velocity of the subject, to the arm controller of the muscle force assisting system, to provide.

6 is a flowchart of a rehabilitation state analysis process using an unrestrained EMG measurement signal according to an embodiment of the present invention. By analyzing the EMG signal and the reference EMG signal, the degree of movement of the upper and lower extremities of the subject is out of the normal range, and the degree of rehabilitation is determined accordingly.

To this end, first, the upper and lower EMG signals are measured for each motion of a plurality of normal persons, and average values and standard errors are calculated and stored as reference EMG signals ref_EMG1 to ref_EMG4.

The reference EMG signal is classified into various types such as age and gender which may affect the EMG signal, and in order to calculate a more accurate reference EMG signal, the EMG signals for each motion are measured and averaged, and are databased. The reference EMG signal suitable for the subject's condition is selected and used.

The subject wears each upper and lower limb band 102 and 103 on the upper and lower limbs of the rehabilitation side, and starts the rehabilitation exercise with the designated motion, and at the same time, the EMG measurement embedded in each upper and lower limb band 102 and 103 is performed. The EMG signals L_EMG1 to L_EMG4 are measured from the units 130 and 150. (S103) (S105)

The EMG signals L_EMG1 to L_EMG4 measured by the EMG measuring unit 130 and 150 are transmitted to the first microcontroller 204 of the biosignal measuring suit 101 worn by the examinee.

Here, the EMG signals L_EMG1 to L_EMG4 measured by the EMG measuring unit 130 and 150 are wirelessly transmitted to the EMG signal computer or an analysis device to be analyzed.

The EMG signals L_EMG1 to L_EMG4 measured by the EMG measuring unit 130 and 150 and the reference EMG signals ref_EMG1 to ref_EMG4 corresponding to the corresponding motions performed by the examinee are analyzed to determine rehabilitation state and rehabilitation degree. (S107) (S109)

That is, the distortion state of the subject's motion direction is calculated according to a result of comparing the change in the reference EMG signal according to each motion with the motion direction data extracted from the measured EMG signal of the subject.

The subject designates various motions for more accurate analysis, and comprehensively analyzes the result data obtained by repeating the processes (S103 to S109) for each motion, thereby more accurately analyzing the rehabilitation state and degree of the subject. .

The first microcontroller 204 provides the subject with the calculated distortion state analysis data for the motion direction of the subject, so that the first microcontroller 204 can refer to the rehabilitation movement of the upper and lower extremities during rehabilitation.

7 is a flowchart of a rehabilitation state analysis process using an unbound EMG measurement signal according to another embodiment of the present invention, which sets a reference EMG signal for analyzing a rehabilitation degree and a rehabilitation state of a subject. This is set by the EMG signals on the upper and lower extremities.

That is, before the subject measures the EMG signal of the upper and lower rehabilitation side, the upper and lower leg bands 102 and 103 are worn on the upper and lower extremities of the normal side, and the specified various motions are performed.

The upper and lower EMG signals R_EMG1 to R_EMG4 of the normal side for each motion of the examinee are converted into a reference EMG signal ref_EMG1 to ref_EMG4 and stored in a database (S121).

Wear the upper and lower bands 102 and 103 on the upper and lower rehabilitation side of the subject, and measure the rehabilitation side EMG signals L_EMG1 to L_EMG4 for each designated motion to set reference EMG signals ref_EMG1 to ref_EMG4. (S123) (S125)

A process of comparing and analyzing the reference EMG signals ref_EMG1 to ref_EMG4 and the measured rehabilitation side EMG signals L_EMG1 to L_EMG4 for each motion, and determining rehabilitation status and rehabilitation degree for each motion according to the result (S127) (S129). Is the same as the comparative analysis and determination process (S107) (S109) of FIG. 6 below, the detailed description will be referred to.

8 is a flowchart of a rehabilitation state analysis process using an unrestrained EMG measurement signal according to another embodiment of the present invention, in which an EMG measuring unit and a 3-axis acceleration / gyro sensor are mounted on upper and lower bands, respectively, By comparing and analyzing the motion path and speed of the upper and lower extremities with the reference data, more accurate rehabilitation and rehabilitation status can be determined.

First, reference EMG signals ref_EMG1 to ref_EMG4 and reference motion paths and speeds of various motions are set.

To this end, the EMG signals EMG1 to EMG4 of motions of a plurality of normal people are measured and calculated, and the average values are calculated and the reference motion path and speed settings are obtained from the three-axis acceleration and gyro sensor 133 for each motion of a plurality of normal people. Based on the three-axis acceleration and gyro signals ref_Accl1 and ref_Accl2 (ref_Gyro1 and ref_Gyro2) as reference data, reference path data and velocity data for each motion are calculated and set. (S141) (S143) (S145)

As another embodiment for calculating reference EMG signals (ref_EMG1 to ref_EMG4), reference path data, and velocity data, it is possible to obtain and set EMG signals for each motion, 3-axis acceleration, and gyro signal measured on the upper and lower sides of the subject. Do.

After setting the reference EMG signals ref_EMG1 to ref_EMG4, reference path data, and velocity data, the subject wears each band 102 and 103 on the upper and lower extremities of the rehabilitation side, and performs a rehabilitation exercise for each of the designated motions. Each of the EMG signals L_EMG1 to L_EMG4 is measured from the units 130 and 150, and at the same time, the three axis acceleration / gyro signals L_Accl1 and L_Gyro1 through the three-axis acceleration / gyro sensor 133 (L_Accl2 and L-Gyro2). (S147) (S149) (S151).

Here, each of the upper and lower bands 102 and 103 has two pairs of EMG electrodes 131 and 138 and one triaxial acceleration / gyro sensor 133 for measuring EMG signals. The EMG signals input from each of the upper and lower band bands 102 and 103 acquire all four channels of EMG signals (L_EMG1 to L_EMG4), and the three-axis acceleration / gyro signals are three-axis acceleration / gyro of two channels. The signals L_Accl1 and L_Gyro1 are acquired.

The motion direction for each motion is calculated using the obtained EMG signals, and the rehabilitation state and degree are determined by comparing the motion direction data calculated from the preset reference EMG signals ref_EMG1 to ref_EMG4. )

In addition, by using the measured three-axis acceleration / gyro signals (L_Accl1, L_Gyro1) (L_Accl2, L-Gyro2) measured in the upper and lower extremities of the subject to calculate the motion path and velocity of the upper and lower extremities, And comparing the speed with the reference path and the speed data from the set reference triaxial acceleration / gyro signal, and determining the rehabilitation degree and the rehabilitation state according to the difference (S155).

Here, the rehabilitation state calculates a difference value by comparing the calculated motion path and speed for each motion of the rehabilitation side with the reference motion path and speed for each motion, and analyzes the deviation from the calculated difference value and the set standard error range. As a result, the rehabilitation state and the degree of rehabilitation according to the direction of motion of the upper and lower extremities are provided to the examinee, so that the rehabilitation training is performed with reference to this.

In this way, the rehabilitation degree and the rehabilitation state according to the comparison result (S155) of the rehabilitation degree and rehabilitation state data according to the comparison result of the EMG signal (S153) and the three-axis acceleration / gyro data are combined more accurately and specific rehabilitation according to the specific direction of movement The condition and the degree of rehabilitation are determined and provided to the subject. (S157)

In addition, although specific embodiments of the present invention have been described and illustrated above, a method of measuring a direction of movement, a path, and a velocity data for measuring a rehabilitation state of the present invention may be variously modified according to a measurement position, a motion, and the like. And the method of determining the rehabilitation degree and state by combining the EMG signal and the three-axis acceleration / gyro signal is obvious that can be variously modified by those skilled in the art.

It should be understood, however, that such modified embodiments are not to be understood individually from the spirit and scope of the invention, and such modified embodiments are intended to be included within the scope of the appended claims.

100: test subject 101: biological signal measurement chute
102,103: Upper and lower band
111: EMG sensor 112: ECG sensor
113: heart sound sensor 114: skin temperature sensor
121, 132: amplifier 130,150: upper and lower EMG measuring unit
131,138: EMG sensor electrode 133: 3-axis acceleration / gyro sensor
136: battery 137: charging port
141: multiplexer 143: register
144: wireless interface matching unit 145: wireless transmission unit
200: control board 201,202,142: AD converter
203: Interface conversion unit 204, 140: First and second microcontroller
205: muscle support system interface unit
211: wireless receiver

Claims (14)

In an unconstrained EMG measuring system comprising a biosensor unit including a plurality of EMG sensors, an ECG sensor, a heart sound sensor, and a skin temperature sensor for acquiring EMG, electrocardiogram (ECG), heart sound, respiration, and skin temperature from a subject,
An AD converter which receives the bio signals obtained from each of the EMG sensor, the ECG sensor, the sound sensor, and the skin temperature sensor for each channel, and converts and latches them into digital signals;
Upper and lower EMG measuring units for detecting EMG signals in upper and lower arms of the examinee;
A wireless receiver configured to wirelessly receive respective EMG signals detected by the upper and lower EMG measuring units;
Interface conversion for collecting the bio-signals for each channel input through the AD converter and the wireless receiver, determining which channel the collected bio-signals are, and converting and outputting the input-channel signals for external interface matching. part;
And a first microcontroller which removes noise of the biosignal input from the interface converter and analyzes each biosignal to calculate parameters for determining a subject's operation, health status, and emotional recognition.
The biosensor unit is attached to the inside of the wearable bio-signal measurement chute, the upper and lower extremity EMG measuring unit is attached to the inside of the band that can be worn on the upper and lower legs of the subject. The method of claim 1,
The interface converter is six channels of each EMG sensor,
Unrestrained electromyography system, characterized in that for receiving the measurement signal sequentially from each one of the electrocardiogram sensor, heart sound sensor and skin temperature sensor. The method of claim 1,
The upper and lower EMG measuring unit is in contact with the arm of the subject EMG sensor for detecting an EMG signal;
An amplifier for amplifying the detection signal of the EMG sensor to a predetermined level;
A three-axis acceleration sensor and a three-axis gyro sensor for detecting the upper and lower position, the direction, the movement acceleration and the angular velocity signal of the subject;
A second microcontroller that receives signals input from the amplifier, a three-axis acceleration sensor, and a three-axis gyroscope sensor, converts the signals into digital data, and wirelessly transmits them by processing them;
A power supply unit supplying power to each unit;
Unrestrained electromyography system characterized in that it comprises a charging port for charging the battery of the power supply. The method of claim 3, wherein
The second microcontroller may include: a multiplexer configured to receive an operation signal input from the amplifier, a three-axis acceleration sensor, and a three-axis gyroscope sensor and multiplex the output signal;
An AD converter for converting an EMG signal and an operation signal of the examinee output from the multiplexer into a digital signal;
A register that stores the EMG and motion data of the subject converted from the AD converter for a predetermined time;
A wireless interface unit for converting each data stored in the register to match the wireless interface; And
And a wireless transmitter configured to wirelessly transmit the EMG and operation data output from the wireless interface unit. The method of claim 1,
The first microcontroller removes the noise of the EMG signal inputted from the wireless receiver and the interface converter, calculates motion data of the upper and lower arms of the subject through a signal processing process, and outputs the motion data to the muscle assist system interface unit.
And the muscle strength assistance system interface unit outputs muscle strength assistance system control data mounted on an arm of a subject based on upper and lower arm motion data inputted from the first microcontroller. In a rehabilitation state analysis method using an unconstrained EMG signal to analyze the rehabilitation state of the subject by the first microcontroller received an EMG signal obtained through a plurality of EMG signals attached to the upper and lower arms of the subject ,
A first step of acquiring an EMG signal (EMG) from each of the EMG measuring units attached to the upper and lower parts of the examinee as the examinee performs a designated motion;
A second step of comparing the EMG signal with a previously stored reference EMG signal EMG_ref; And
And a third step of determining a degree of rehabilitation and a distortion degree of a movement direction according to the comparison result of the second step. Rehabilitation state analysis method using an unbounded EMG measurement signal, characterized in that it comprises a. The method according to claim 6,
The reference EMG signal (EMG_ref) of the second process is based on the average value of the EMG measurement position of a normal person, using an unbound EMG measurement signal, characterized in that measured at the same position as the EMG measurement position of the subject Rehabilitation status analysis method. The method according to claim 6,
The reference EMG signal (EMG_ref) of the second process is based on the EMG signal measured on the upper and lower extremities of the subject as a reference value, the measurement position is measured at a position symmetrical with the measurement position of the upper and lower rehabilitation side Rehabilitation status analysis method using unbound EMG measurement signal. The method according to claim 6,
Rehabilitation status analysis method using the unrestrained EMG signal, characterized in that by performing the first to the third process for each motion to determine the degree of rehabilitation and direction distortion degree for each motion of the subject. The method according to claim 6,
The first microcontroller is mounted in a biosignal measurement chute of a subject;
Each of the EMG measuring parts is mounted on the upper and lower bands of the upper and lower arm bands which can be worn on the upper and lower arms of the subject;
EMG signal obtained by each EMG measuring unit for rehabilitation status analysis method using the unbound EMG signal, characterized in that the wireless transmission to the first microcontroller. The first microcontroller receives the EMG signal measured by the EMG measurement unit attached to the upper and lower extremities of the subject's rehabilitation, and the upper and lower motion paths and velocities measured by the 3-axis acceleration sensor and the 3-axis gyroscope sensor. In the rehabilitation state analysis method using the unbound EMG signal to analyze the rehabilitation state of the subject by
A first step of acquiring an EMG signal (EMG) from each of the EMG measuring units attached to the upper and lower parts of the examinee as the examinee performs a designated motion;
A second process of acquiring upper and lower motion paths and velocity data of the subject through the 3-axis acceleration and 3-axis gyroscope sensors;
A third step of comparing each EMG signal (EMG) measured in the first step with a reference EMG signal;
A fourth step of comparing the upper and lower motion path and speed data of the examinee obtained in the second step with the reference motion path and speed data;
And a fifth step of determining a rehabilitation degree and a path distortion degree of the examinee according to the result of comparing the EMG, the motion path, and the velocity data obtained in the second and third processes. Rehabilitation analysis method using the signal. The method of claim 11,
And the reference motion path and speed data in the third process are average values of path data and average values of speed data when a normal person performs the same motion. The method of claim 11,
The reference motion path and velocity data of the third process are motion paths and velocity data of the upper and lower extremities on which the subject performs the same motion, and the rehabilitation state analysis method using the unbound EMG measurement signal. The method of claim 11,
The first microcontroller is mounted in a biosignal measurement chute of a subject;
Each of the EMG measurement unit, the three-axis acceleration sensor and the gyro sensor is mounted on the inside of the upper and lower bands wearable in the form of a band on the upper and lower arms of the subject;
Analysis of the rehabilitation state using the unbound EMG signal, wherein the EMG signal, the 3-axis acceleration signal, and the gyro signal obtained by the EMG measuring unit, the 3-axis acceleration sensor, and the gyro sensor are wirelessly transmitted to the first microcontroller. Way.

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