KR101317817B1 - EMG feedback-based active training system for rehabilitation exercise - Google Patents

Abstract

The present invention relates to an active upper limb rehabilitation training system based on EMG feedback that drives an exercise machine in consideration of the will of the patient. More specifically, the elbow joint is actively trained using the brachial electromyography signal, thereby rehabilitation of hemiplegic patients. The present invention relates to an active upper limb rehabilitation training system based on EMG feedback.
Active upper limb rehabilitation training system based on EMG feedback of the present invention, EMG detection unit for detecting the EMG from the biceps of the upper arm; A control unit that uses the detected EMG signal x, wherein a is a real number of 0.8 to 1.2, b is a real number of 0.4 to 1.2, and obtains a motor torque y by y = axb to generate a motor control signal. ; A motor driven by a motor control signal of the control unit and mounted to a hinge-coupled portion between the upper arm exoskeleton for mounting the upper arm and the lower arm skeleton for mounting the lower arm, such that the elbow joint can bend / shuck; It is characterized by including.

Description

EMG feedback-based active training system for rehabilitation exercise

 The present invention relates to an active upper limb rehabilitation training system based on EMG feedback that drives an exercise machine in consideration of the will of the patient. More specifically, the elbow joint is actively trained using the brachial electromyography signal, thereby rehabilitation of hemiplegic patients. The present invention relates to an active upper limb rehabilitation training system based on EMG feedback.

Stiffness occurs after damage to the central nervous system caused by cardiovascular diseases such as stroke. Stiffness requires regular and continuous movement because joint deformation is inevitable if left untreated. In particular, stiffness can be alleviated through regular stretching or passive movement within the range of motion (RoM).

Rehabilitation stretching allows the therapist to manually move the patient's joints to prevent deformation of the joint, thereby maintaining the current range of motion or improving the limited range of motion.

Physical therapy in domestic rehabilitation hospitals is limited within 1 hour once a day, and both the therapist and the patient have a high economic, time, and physical burden in one treatment, and maintain and improve the recovery state after treatment. Continuous exercise therapy is urgently needed. To this end, robot rehabilitation training aimed at task-oriented repetitive training has been introduced and applied.

 Representative examples include computer-based isokinetic dynamometers, continuous passive motion (CPM), and feedback-controlled and programmed stretching.

However, due to its high price and large volume, isokinetic dynamometers are currently only used in certain facilities and are mainly used for clinical evaluation of patients rather than for rehabilitation purposes.

Continuous manual exercise equipment is difficult to repetitive training, and the results have been reported that there is no significant effect in the recovery of the function of the patient. In general, the force sensor used in the robotic training system is effective in measuring the components of applied force / torque and moment, but has a disadvantage in that it is difficult to directly observe or reflect the microscopic muscle movement or the patient's will.

 Recently, in order to enhance the effect of exercise treatment using robots in robotic training systems, active training systems that drive devices by reflecting the patient's intention beyond passive treatment methods, that is, stretching devices based on biosignal feedback, have been studied.

Active training system reflects one's willingness in training, so training effect is greater than passive rehabilitation, and re-education effect of nerve and muscle can be expected.

The present invention provides an upper limb training system capable of active training of the elbow joint using the EMG signal.

The problem to be solved by the present invention, active upper extremity rehabilitation training with a robotic exoskeleton is controlled by the EMG signal of the upper arm and made to be able to exercise the elbow joint bending / shock within 1 degree of freedom, 0 ~ 120 degree range To provide a system.

Another object of the present invention is to provide an active upper extremity rehabilitation training system is made to measure the elbow joint angle by mounting a variable resistor on the rotation axis of the robotic exoskeleton, at the same time detect the EMG signal and the angle data.

Another problem to be solved by the present invention is to estimate the elbow joint torque on the basis of the EMG signal at the maximum voluntary contraction of the patient, and the constant velocity motion only when the estimated elbow joint torque reaches a certain level or more. It is possible to provide an active upper extremity rehabilitation training system that can be configured to be able to set the exercise intensity arbitrarily according to the patient.

In addition, the active upper limb rehabilitation training system of the present invention is to provide an active upper limb rehabilitation training system that brings more effective therapeutic effect by inducing active exercise reflecting the will of the patient.

Active upper limb rehabilitation training system based on EMG feedback of the present invention, EMG detection unit for detecting the EMG from the biceps of the upper arm; By using the detected EMG signal x, a is a real number of 0.8 to 1.2, b is a real number of 0.4 to 1.2, and the motor torque y is obtained by y = ax ^b to generate a motor control signal. A motor driven by a motor control signal of the controller, mounted on a hinged portion between the upper arm exoskeleton for mounting the upper arm and the lower arm skeleton for mounting the lower arm, such that the elbow joint can bend / shuck It characterized by including.

In addition, EMG feedback-based active upper extremity rehabilitation training system of the present invention, EMG detection unit for detecting the EMG from the triceps of the upper arm; By using the detected EMG signal x, a real number of -0.8 to -1.2, b is a real number of 0.4 to 1.2, and the motor torque y is y = ax ^b. A control unit for obtaining a motor control signal; A motor driven by a motor control signal of the control unit and mounted to a hinge-coupled portion between the upper arm exoskeleton for mounting the upper arm and the lower arm skeleton for mounting the lower arm, such that the elbow joint can bend / shuck; It is characterized by including.

In addition, the EMG-based active upper extremity rehabilitation training system of the present invention, the brachial exoskeleton including a brachial rest, and the upper arm rest fixing portion mounted to the left and right sides of the upper arm rest; A lower armrest holder and a lower armrest control member are provided on both left and right sides of the lower armrest holder, wherein the lower armrest adjusting part includes a hole for adjusting a through hole, and a lower footrest stator positioned on the outside of the lower footrest moves along the adjustment head. By being fixed, the lower exoskeleton made to be adjustable in length; The upper arm rest fixing unit and the lower arm rest adjusting unit are hinged on the left and right sides of the upper arm rest, respectively, the hinge coupling of one side of the joint portion is mounted motor; A sensor rotation angle detection unit mounted to a rotation shaft of the motor and including a rotation angle sensor detecting an angle signal; Characterized in that it comprises a.

In addition, the present invention, the EMG detection unit for detecting the EMG, the control unit for generating a motor control signal in accordance with the output signal of the EMG detection unit, by driving the motor by the motor control signal received from the control unit bending / braking motion of the elbow joint In the EMG-based active upper extremity rehabilitation training system having a robotic exoskeleton configured to enable the control, the control unit estimates elbow joint torque based on the EMG signal at the maximum voluntary contraction, and the elbow joint torque It characterized in that it is made to differentially control the exercise intensity.

The EMG detector is composed of two or three differential electrodes.

The motor is a motor having a torque of 25 Nm or more.

The motor is equipped with a gearhead with a damping ratio of 230: 1.

The rotation angle measuring sensor is a potentiometer.

The lower eye exoskeleton further includes a belt for tying the lower eye.

The joint part is made to be capable of movement within 1 degree of freedom, 0 degrees to 120 degrees.

In addition, the method of driving an active upper limb rehabilitation training system based on EMG feedback of the present invention detects an EMG signal at the maximum voluntary contraction (MVC) of a patient and estimates elbow joint torque based on the detected EMG signal. Joint movement range setting step of setting a range of motion (Rom); An exercise intensity target value setting step of reading a user set exercise intensity target value (threshold) input by the patient; A motor excitation determining step of initializing a motor if the joint movement range set in the joint movement range setting step is greater than the preset constant velocity joint motion reference value and the user set exercise intensity target value is within the set joint movement range; It detects EMG signals of patients who are exercising as the motor is driven, and detects angle signals by the rotation angle measuring sensor mounted on the rotating shaft of the motor, and receives and stores EMG signals and angle signals. Signal detection step; If the EMG signal detected in the signal detection step during exercise is greater than or equal to the exercise intensity target value, the motor torque according to the EMG signal is estimated to generate a motor control signal, transmit it to the motor, and return to the signal detection step during exercise. Determining whether or not to update the signal.

The elbow joint torque (y) in the joint movement range setting step is y = ax ^b with respect to the EMG signal (x) at the maximum voluntary contraction. (However, in the case of the EMG signal at the maximum voluntary contraction of the biceps, a is a real number from 0.8 to 1.2, b is a real number from 0.4 to 1.2, and the EMG signal at the maximum voluntary contraction of the triceps. a is a real number of -0.8 to -1.2 and b is a real number of 0.4 to 1.2).

In the step of determining whether to update the motor control signal, the estimation of the motor torque y according to the EMG signal x is y = ax ^b (where a is a real number of 0.8 to 1.2 when b is an EMG signal of the biceps. A real number of 0.4 to 1.2, and a MG signal x, where a is a real number of -0.8 to -1.2 and b is a real number of 0.4 to 1.2.

When the elbow joint torque is equal to or greater than a predetermined constant joint motion reference value, the robotic exoskeleton is configured to perform constant velocity joint motion.

According to the active upper extremity rehabilitation training system of the present invention, an active upper limb having a robotic exoskeleton, which is controlled by an EMG signal of the upper arm and is capable of exercising the elbow joint's bending / knuckle within 1 degree of freedom and 0 to 120 degrees. As a rehabilitation training system, it is inexpensive, capable of exercising without time constraints, and has a small volume, so that it is economically, temporally and spatially light.

In addition, the active upper extremity rehabilitation training system of the present invention is made to measure the elbow joint angle by mounting a variable resistor on the rotation axis of the robotic exoskeleton, it is made to detect the EMG signal and the angle data at the same time, more precise control and inspection is possible Do.

In addition, the active upper limb rehabilitation training system of the present invention estimates the elbow joint torque based on the EMG signal at the maximum voluntary contraction of the patient, and is constant velocity motion only when the estimated elbow joint torque reaches a predetermined level or more. It is made to be possible, made the exercise intensity can be set arbitrarily according to the patient, customized control and customized training is possible.

In addition, the active upper extremity rehabilitation training system of the present invention, by inducing active exercise that reflects the will of the patient brings a more effective therapeutic effect.

1 is an explanatory diagram schematically illustrating an active upper limb rehabilitation training system based on EMG feedback according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a configuration of an active upper limb rehabilitation training system based on EMG feedback of FIG. 1.
3 is a perspective view of the robotic exoskeleton of FIG. 1.
4 is an exploded view of the exoskeleton of FIG.
5 is an example of a driving flowchart of the controller of FIG. 1.
6 shows the relationship between the EMG signal and the torque value of a normal person as an experimental result for estimating the EMG signal and the elbow joint torque.
7 shows the relationship between EMG signals and torque values in hemiplegic patients as experimental results for estimating EMG signals and elbow joint torques.
Figure 8 is an example of the results of applying the active upper extremity rehabilitation training system of the present invention to a normal person.
Figure 9 is an example of the results of applying the active upper extremity rehabilitation training system of the present invention to hemiplegic patients.

Hereinafter, the configuration and manufacturing method of an active upper limb rehabilitation training system based on EMG feedback according to an embodiment of the present invention will be described in detail.

1 is an explanatory diagram schematically illustrating an active upper limb rehabilitation training system based on EMG feedback according to an embodiment of the present invention, Figure 2 is a block for explaining the configuration of the active upper limb rehabilitation training system based on EMG feedback of Figure 1 Road, EMG detection unit 100, rotation angle detection unit 140, A / D conversion unit 180, control unit 200, motor 300, robotic exoskeleton unit 400, output unit 500, memory unit 550.

The EMG detector 100 includes at least one EMG electrode 10 and an EMG signal preprocessor 20 to detect and preprocess EMG to the A / D converter 180.

The EMG electrode 10 detects EMG from the muscles of the upper arm and can use a plurality of electrodes. As the EMG electrode 10, two or three differential electrodes may be used, and the EMG of the brachial biceps (BB) or the brachial triceps (TB) may be detected.

The EMG signal preprocessor 20 amplifies the EMG detected from the EMG electrode 10 in the EMG signal preprocessor and removes noise. The EMG signal preprocessor 20 may attenuate the EMG signal detected by the EMG electrode 10 times and full-wave rectification to remove noise with a 2 Hz secondary Butterworth low pass filter.

The rotation angle detector 140 is pre-processed by the rotation angle measurement sensor 150 mounted on the rotating shaft of the motor 300 detects the joint angle, and removes the noise of the joint angle signal from the angle signal preprocessing unit 160, A / D conversion unit 180 to transmit. The angle signal preprocessing unit 160 may be a 5 Hz secondary Butterworth low pass filter.

The controller 200 generates a motor control signal by arithmetic processing from the signal received from the EMG detector 100 and transmits the generated motor control signal to the motor 300. The motor control signal estimates the elbow joint torque based on the EMG signal at the maximum voluntary contraction, and differentially controls the exercise intensity according to the elbow joint torque, that is, differentially controls the motor. In addition, it receives the joint angle detected from the rotation angle measurement sensor mounted on the motor 300, and transmits the output EMG signal detected by the joint angle and the EMG detector 100 to the output unit 500, the memory The data is transmitted to the unit 550 and stored.

The motor 300 has a rotating shaft connected to one side of the joint portion 440 of the robotic exoskeleton 400, and is driven by a motor control signal received from the controller 200. In the present invention, a preliminary experiment was performed through a normal person to select a motor. The maximum elbow torque obtained through the normal person was 25 Nm, and a motor capable of generating more torque was selected. In the present invention, the motor 300 may be configured to satisfy a torque range by mounting a gear head having a damping ratio of 230: 1. The motor 300 may use a motor voltage of 24V, a speed of 33 rpm, and a torque of 29 Nm.

The rotation axis of the motor 300 is equipped with a rotation angle measurement sensor for measuring the elbow joint angle, and in some cases the rotation angle measurement sensor may be a potentiometer.

The robotic exoskeleton 400 is a means for assisting the movement of the joint by mounting the arm, and includes a brachial exoskeleton 410, a joint 440, and a lower exoskeleton 470.

The upper arm exoskeleton 410 is a cradle of the upper arm for stably raising the upper arm, the joint portion 440 is located on one side. The upper arm exoskeleton 410 may be made to mount the upper arm in a state placed on the table or the like.

Joint portion 440 is located between the upper arm exoskeleton 410 and the lower exoskeleton 470, the rotation axis of the motor 300 is mounted on at least one side, the arm folded by the drive of the motor 300 This is done to make it possible. The upper arm exoskeleton 410 and the lower exoskeleton 470 are hinged, but the rotational axis of the motor 300 is mounted on one side of the hinged portion, the lower exoskeleton 470 may be moved by the motor. .

The lower eye exoskeleton 470 is mounted on one side of the joint 440 as a cradle of the lower arm. The lower exoskeleton portion 470 further includes a belt for tying the lower eye.

The output unit 500 outputs the joint angle and the EMG signal received from the control unit 200.

3 is a perspective view of the robotic exoskeleton of FIG. 1, and FIG. 4 is an exploded view of the exoskeleton of FIG. 1.

Robotic exoskeleton 400 for the rehabilitation of the elbow joint in the active upper extremity rehabilitation training system of the present invention to implement a degree of freedom, 1 degree of freedom, 0 degrees to 120 degrees It is made to be able to exercise.

The robotic exoskeleton 400 includes a brachial exoskeleton 410 and a lower exoskeleton 470, and the brachial exoskeleton 410 is a support plate 415, a brachial brace 420, and a brachial brace fixed part 425. It includes.

The supporting plate 415 is in contact with the upper surface of the table or the like when the robotic exoskeleton 400 is placed on the upper surface of the table or the like.

The upper arm rest 420 is a means for mounting the upper arm, to fix the upper arm rest 420 to the upper surface of the support plate 415.

The upper arm rest fixing portion 425 is hinged and coupled to the lower restraint adjusting portion 480 to be made to fold and lift the elbow, such that the upper arm rest 420 is positioned and fixed on the support plate 415, left and right, It is fixedly mounted to the left and right sides of the upper arm rest 420 or the support plate 415. One side of the left and right arm rest fixing unit 425 has an upper arm rotating shaft hole for insertion and mounting of the rotating shaft of the motor, the motor fixing part 320 is mounted on the outer side of the upper arm rotating side hole, the inner lower shaft rotation shaft The lower supporter adjustment unit 480 having a hole is mounted, and the rotation shaft of the motor is inserted into the upper arm rotation shaft hole and the lower eye rotation shaft hole, and the motor 300 is fixedly mounted to the motor fixing part 320. One side of the left and right arm rest fixing unit 425 is provided with an upper arm hinge rod hole, the lower arm hinge rod adjustment portion 480 having a lower arm hinge rod hole inside the upper arm hinge rod hole is mounted on the upper arm hinge rod hole and the lower arm hinge ball hole. Hinge rod 325 is inserted, it is made to tighten the screw by opening the bushing on the outside of the upper arm hinge rod hole.

The lower eye exoskeleton 470 includes a lower eye rest 475, and a lower eye rest adjuster 480.

The lower eye rest 475 is a means for mounting the lower arm, which is mounted between two lower eye rest adjusters 480, and the lower eye rest stator 482 located on the left and right sides of the lower eye rest 475 is a lower eye rest adjuster. 480 is made to adjust and fix in accordance with the length of the eye of the user on the main 485. In some cases, the bottom supporter stator 482 is made of a male screw shape, and a plurality of grooves are provided on the outer left and right sides of the lower supporter 475, and the groove is made of a female screw shape so as to be fixedly mounted in a groove at a desired position. Can be. In addition, after the arm is mounted on the lower eye rest 475, the lower eye rest 475 and the belt 484 for tying the arm may be further provided.

The lower eye rest adjustment unit 480 has one end fixed to the inner side of the upper arm rest fixing unit 425, and one of the lower eye rest adjustment units 480 includes a lower eye rotation shaft hole, and the upper arm rotation shaft hole of the motor 300. The rotating shaft is inserted, the other one of the lower eye rest adjustment unit 480 is provided with a lower arm hinge rod hole, the hinge rod 325 is inserted together with the upper arm hinge rod hole.

Upper arm rest fixing part 425, the lower eye rest adjusting unit 480, the motor 300, the hinge rod 325 forms a joint portion 440.

5 is an example of a driving flowchart of the controller of FIG. 1.

In the step of setting the range of motion, the EMG signal is detected during the maximum voluntary contraction (MVC) of the user (trainer, patient), and the range of motion is estimated by estimating the elbow joint torque based on the detected EMG signal. RoM) is set (S100).

The elbow joint torque y is estimated by y = ax ^b for the EMG signal x at the maximum voluntary contraction.

Here, in the case of the EMG signal x at the maximum voluntary contraction of the biceps, a is a real number of 0.8 to 1.2, and b is a real number of 0.4 to 1.2. In the case of the EMG signal x at the maximum voluntary contraction of the triceps, a is a real number of -0.8 to -1.2, and b is a real number of 0.4 to 1.2.

In step S110 of setting the intensity target value, the user sets the exercise intensity target value (threshold, threshold) input by the user (trainer, patient) (S110).

In the step of determining whether the motor is excited, the joint movement range set in the joint movement range setting step (S100) is greater than the preset constant velocity joint motion reference value (stored before shipment in some cases), and the user set exercise intensity target value is set. It is determined whether it is within the operating range (S120), and if so, the motor is initialized to generate a motor control signal, which is transmitted to the motor 300 to drive the motor. Otherwise, the operation returns to the joint operating range setting step (S100).

In the step of detecting a signal during exercise, as the motor 300 is excited, the user performs exercise. At this time, the detected EMG signal and the rotation angle signal are received (S130) and stored in the memory unit 550 and output unit 500. And outputs (S140).

In the step of determining whether the motor control signal is updated, it is determined whether the detected EMG signal is greater than or equal to the exercise intensity target value (S150). If not, the process returns to the signal detection step (S130) during exercise without updating the motor control signal.

In the step of updating the motor control signal, if the detected EMG signal is greater than or equal to the exercise intensity target value, the motor torque (y) by the input EMG signal (x) is obtained by the above y = ax ^b to generate a motor control signal. Transmission to the motor 300 and returns to the signal detection step (S130) during exercise (S160).

Next, an experiment for establishing an equation for estimating the EMG signal and the elbow joint torque and the result will be described.

Based on the EMG signal and torque data at the maximum voluntary contraction of the biceps and triceps obtained from five normal and one hemiplegic patients, the regression analysis was performed with a power function (y = ax ^b ). Got

6 is an experimental result for estimating the EMG signal and the elbow joint torque, and shows the relationship between the EMG signal and the torque value of a normal person, and FIG. 7 is an experimental result for estimating the EMG signal and the elbow joint torque. The relationship of the torque value is shown.

Fig. 6 (a) is the y-function calculated from the EMG of the biceps of a normal person and y = 0.9789x ^0.5699 , and Fig. 6 (b) is the y-function obtained from the EMG of the triceps of a normal person y = -1.0792x ^0.5873 . .

FIG. 7 (a) is y = 1.034x ^0.9301 , which is obtained from EMG of the biceps muscle of hemiplegic patients, and FIG. 7 (b) is y = -0.997x, which is obtained from EMG of the triceps muscle of hemiplegic patients. ^1.172 .

Next, an experiment to which the active upper limb rehabilitation training system of the present invention is applied will be described.

The system was applied to five healthy subjects (age 24 ± 1 years, height 171 ± 4 cm, weight 67 ± 6 kg) and hemiplegic patients (age 19, height 172 cm, weight 82 kg). Evaluated. Patients who participated in the study had mild hemiplegia symptoms that the muscle limbs noticeably increased but limbs easily flexed according to a clinical expert's muscle tone assessment. Threshold values were set at 10% (0.1) and 50% (0.5) of the maximum torque the subject could generate. The range of motion was set at 0 ° ~ 120 ° and the elbow joint torque predicted from the biceps EMG signal of the wearer was tested at the preset threshold.

Figure 8 is an example of the result of applying the active upper extremity rehabilitation training system of the present invention to a normal person, Figure 9 is an example of the result of applying the active upper extremity rehabilitation training system of the present invention to hemiplegic patients.

Fig. 8 shows the elbow joint angle, biceps and triceps signals when the active upper extremity rehabilitation training system of the present invention is applied to a normal person, and a target exercise intensity value (threshold value). The x-axis is the training time frame and the y-axis is the EMG signal value normalized from 0 to 1 for threshold setting.

FIG. 8A is a system operation screen when 10% (0.1) of the test subject's maximum torque is set as a threshold value. The elbow joint angle increased (bended) when an EMG signal above the threshold was obtained.

Figure 8 (b) shows the operation screen when the threshold value is 50% (0.5). EMG signals from the biceps were measured, but the elbow joint angles could not be observed because they were below the threshold. The elbow joint angle rose momentarily in the range where the EMG signal was measured above the threshold.

Fig. 9 shows the elbow joint angle, biceps and triceps signals when the active upper extremity rehabilitation training system of the present invention is applied to a hemiplegic patient, and a set target intensity value (threshold value). Patients were also evaluated by setting the same threshold range as normal subjects.

FIG. 9A is a system operation screen when the threshold value is set to 10% (0.1) of the torque that the hemiplegic patient can maximize. The elbow joint angle increased (bending) from the point at which the EMG signal of the biceps was above the threshold value, which was the same as that of the normal person. 9B is a screen when the threshold value is 50% (0.5). EMG signals of the biceps were measured as in normal people, but the elbow joint angle did not change until the threshold value was exceeded, and the elbow joint angle increased for a while when the EMG signal was measured above the threshold value.

Therefore, the active upper extremity rehabilitation training system of the present invention is an active upper extremity training system for active training of stiffness hemiplegic patients, it can be confirmed that it is applicable to normal people and patients through the experiment.

Only when the magnitude of the EMG signal measured in the elbow muscle exceeds the preset threshold level, the motor is driven to enable elbow constant velocity motion. It was confirmed that the developed system plays the role of an active training system that reflects the patient's will. Even if the patient's stiffness is severe and weak EMG signals are acquired, training can be performed by setting the threshold value from the lowest ability value of the patient. This is expected to help patients recover more effectively than manual training by allowing them to adjust their muscle strength to reflect their will.

The active upper limb rehabilitation training system of the present invention is a conventional continuous passive exercise therapy apparatus that does not consider the severity of symptoms in that the subject's movement range is specified by the torque information converted from the EMG signal, and the patient does not require excessive exercise. There is a difference. In addition, since the physical condition or mood, which has a great influence on the exercise treatment, is reflected in the subject's willingness to exercise, the intensity of the training can be adjusted, and thus the performance improvement is high unlike the therapist's randomized treatment termination. Therefore, by inducing active exercise that reflects the will of the patient, it brings a more effective therapeutic effect than the conventional passive therapy. Since the present invention operates on the subject's muscle strength, continuous training can put fatigue and burden on the subject. Therefore, a combination of rest and training can be intrigued by the subject.

It is to be understood that the present invention is not limited by what has been described above and illustrated in the drawings, and those skilled in the art will recognize that many modifications and variations are possible within the scope of the following claims.

10: EMG electrode 20: EMG signal preprocessor
100: EMG detector 140: Rotation angle detector
150: rotation angle measurement sensor 160: angle signal preprocessor
180: A / D conversion unit 200: control unit
300: motor 320: motor fixing part
325 hinge rod 400 robotic exoskeleton
410: upper arm exoskeleton 415: support plate
420: upper arm rest 425: upper arm rest fixing portion
440: joint 470: lower extremity exoskeleton
475: Haan cradle 480: Haan cradle adjustment unit
482: bottom support stator 484: belt
485: mainly for adjustment 500: output
550: memory

Claims (15)

EMG detection unit for detecting EMG from the biceps of the upper arm;
By using the detected EMG signal x, a is a real number of 0.8 to 1.2, b is a real number of 0.4 to 1.2, and the motor torque y is
y = ax ^b
A control unit for obtaining a motor control signal;
A motor driven by a motor control signal of the control unit and mounted to a hinge-coupled portion between the upper arm exoskeleton for mounting the upper arm and the lower arm skeleton for mounting the lower arm, such that the elbow joint can bend / bounce;
Active upper limb rehabilitation training system based on EMG feedback comprising a. An EMG detector for detecting EMG from the triceps of the upper arm;
Using the detected EMG signal x, a real number of -0.8 to -1.2, b is a real number of 0.4 to 1.2, and the motor torque y is
y = ax ^b
A control unit for obtaining a motor control signal;
A motor driven by a motor control signal of the control unit and mounted to a hinge-coupled portion between the upper arm exoskeleton for mounting the upper arm and the lower arm skeleton for mounting the lower arm, such that the elbow joint can bend / bounce;
Active upper limb rehabilitation training system based on EMG feedback comprising a. A brachial exoskeleton including a brachial rest, and a brachial rest fixing part mounted on left and right sides of the brachial rest;
A lower armrest holder and a lower armrest control member are provided on both left and right sides of the lower armrest holder, wherein the lower armrest adjusting part includes a hole for adjusting a through hole, and a lower footrest stator positioned on the outside of the lower footrest moves along the adjustment head. By being fixed, the lower exoskeleton made to be adjustable in length;
The upper arm rest fixing part and the lower arm rest fixing part are on the left and right sides of the upper arm rest respectively.
Hinge coupled, but the hinge coupling portion of one side of the joint portion is mounted motor;
A sensor rotation angle detection unit mounted to a rotation shaft of the motor and including a rotation angle sensor detecting an angle signal;
Active upper limb rehabilitation training system based on EMG feedback comprising a. The method of claim 3,
EMG detection unit for detecting the EMG of the upper arm;
A controller configured to generate a motor control signal using the detected EMG signal and to receive an angle signal from the rotation angle detector;
Active upper limb rehabilitation training system based on EMG feedback further comprising a. 5. The method of claim 4,
The robotic exoskeleton includes the brachial exoskeleton, the articulation, and the lower exoskeleton, and is configured to bend / shape the elbow joint by driving a motor according to a motor control signal received from the controller.
The control unit
Estimate elbow joint torque based on EMG signal at maximum voluntary contraction,
EMG feedback-based active upper extremity rehabilitation training system, characterized in that made to differentially control the exercise intensity according to the elbow joint torque. The method according to any one of claims 1, 2, 4 and 5,
The electromyography detection unit active upper limb rehabilitation training system, characterized in that consisting of two or three differential electrodes. The method according to any one of claims 1 to 5,
EMG feedback-based active upper limb rehabilitation training system, characterized in that the motor having a torque of 25 Nm or more. The method according to any one of claims 1 to 5,
EMG feedback-based active upper limb rehabilitation training system, characterized in that the motor is equipped with a gear head having a damping ratio of 230: 1. The method of claim 3,
The rotation angle measuring sensor is an electromyographic feedback-based active upper limb rehabilitation training system, characterized in that the potentiometer (potentiometer). The method of claim 3,
The lower extremity exoskeleton is EMG feedback-based active upper rehabilitation training system further comprises a belt for tying the lower eye. The method of claim 3,
EMG feedback-based active upper extremity rehabilitation training system, characterized in that the joint is made to be able to exercise within a degree of freedom, 0 degrees to 120 degrees. Detecting an EMG signal during a maximum voluntary contraction (MVC) of the patient, and arranging a range of motion (RoM) by estimating elbow joint torque based on the detected EMG signal;
An exercise intensity target value setting step of reading a user set exercise intensity target value (threshold) input by the patient;
A motor excitation determining step of initializing a motor if the joint movement range set in the joint movement range setting step is greater than the preset constant velocity joint motion reference value and the user set exercise intensity target value is within the set joint movement range;
It detects EMG signals of patients who are exercising as the motor is driven, and detects angle signals by the rotation angle measuring sensor mounted on the rotating shaft of the motor, and receives and stores EMG signals and angle signals. Signal detection step;
If the EMG signal detected in the signal detection step during exercise is greater than or equal to the exercise intensity target value, the motor torque according to the EMG signal is estimated to generate a motor control signal, transmit it to the motor, and return to the signal detection step during exercise. Determining whether the signal is updated;
A method of driving an active upper limb rehabilitation training system based on EMG feedback, comprising a. The method of claim 12,
The elbow joint torque (y) in the step of setting the range of motion of the joint relative to the EMG signal (x) at the maximum voluntary contraction
y = ax ^b
(However, in the case of the EMG signal at the maximum voluntary contraction of the biceps, a is a real number from 0.8 to 1.2, b is a real number from 0.4 to 1.2, and the EMG signal at the maximum voluntary contraction of the triceps. a is a real number between -0.8 and -1.2 and b is a real number between 0.4 and 1.2)
A method of driving an active upper limb rehabilitation training system based on EMG feedback, characterized in that obtained by. The method of claim 12,
In the determining whether the motor control signal is updated, the estimation of the motor torque y according to the EMG signal x is
y = ax ^b
However, in the case of the EMG signal of the biceps, a is a real number of 0.8 to 1.2, b is a real number of 0.4 to 1.2, and in the case of the EMG signal of the triceps, a is a real number of -0.8 to -1.2 and b is 0.4 To a real number of 1.2)
A method of driving an active upper limb rehabilitation training system based on EMG feedback, characterized in that obtained by. The method of claim 5,
EMG feedback-based active upper limb rehabilitation training system, characterized in that the robotic exoskeleton is made to perform a constant joint motion when the elbow joint torque is equal to or more than a predetermined constant joint joint reference value.

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