KR101618186B1 - A rehabilitation robot control system and control method based on brain-machine interface - Google Patents

Abstract

The present invention relates to a brain-machine interface-based rehabilitation robot control system, and more particularly, to a brain-machine interface-based rehabilitation robot control system that enables a rehabilitation robot to effectively move to a target point intended by a user.
According to an aspect of the present invention, there is provided a mobile communication terminal comprising: a signal management unit for receiving an electromagnetic signal from a specific region of the brain and extracting characteristics relating to a moving target point of a specific body region from the electromagnetic signal; A movement information management unit connected to the signal management unit and generating and managing a locus or path point for the robot to be associated with the specific body part to reach the movement target point; And a control unit for receiving the guidance signal of the robot from the movement information management unit and controlling the movement of the robot, wherein the movement information management unit determines whether the robot has departed from a path or a path point for reaching the movement target point And generating an induction signal for correcting a position of the rehabilitation robot, and a controller for controlling the rehabilitation robot based on the brain-machine interface.

Description

Technical Field [0001] The present invention relates to a brain-machine interface-based rehabilitation robot control system and a control method thereof,

The present invention relates to a brain-machine interface-based rehabilitation robot control system, and more particularly, to a brain-machine interface-based rehabilitation robot control system that enables a rehabilitation robot to effectively move to a target point intended by a user.

Rehabilitation treatment includes a series of treatment procedures that are performed for the functional recovery of the injured area when the body is damaged due to an accident or the like in addition to the disease caused by the aged.

 Therefore, for patients suffering from an accident or impairment of body function due to stroke, traumatic brain injury, or cerebral palsy, or weakening of strength due to aging, or physical disability caused by various adult diseases, some or all of the damaged body function is recovered Long-term, systematic physical rehabilitation treatment should be provided by specialists such as doctors and physical therapists.

In addition, rehabilitation training information of rehabilitation patients can be stored in a separate database during rehabilitation treatment process, and rehabilitation training can be performed more systematically.

However, physicians and physiotherapists must repeatedly generate information for rehabilitation training. In order to perform rehabilitation training safely and repeatedly, physicians and physical therapists need physical effort, time and proficiency.

In order to overcome these limitations, gait assist devices are being developed that provide mechanical support to lower (lower) rehabilitation exercises, for example, gait training, and to assist the movement of the upper body (upper body) Upper limb rehabilitation devices are being developed.

In particular, robots have been recently developed for such rehabilitation, and Korean Patent Laid-Open No. 10-2012-0057081 discloses such rehabilitation robots.

Some of these rehabilitation robots are driven by the interpreted brain signals, and researches claiming that these robots exhibit excellent rehabilitation effects are being reported recently.

In this rehabilitation robot, when the motion of the upper limb estimated from the brain signal is directly applied to the robot, there arises a problem that the robot arm can not reach the intended destination due to the position difference between the human arm and the robot arm. If the robot is driven after the brain signal reaches its destination, there is a disadvantage that the time delay becomes inevitable.

 In addition, the conventional rehabilitation robot may have difficulty in performing tasks such as precisely capturing a specific object due to the noise and signal analysis ability of the brain electrode sensor, and in many cases, it is still practicing extremely simple motion in many cases.

The present invention relates to a brain-machine interface-based rehabilitation robot control system which enables a rehabilitation robot to effectively follow a user's brain signal and move to a desired position by a user, And a control method.

According to an aspect of the present invention, there is provided a mobile communication terminal comprising: a signal management unit for receiving an electromagnetic signal from a specific region of the brain and extracting characteristics relating to a moving target point of a specific body region from the electromagnetic signal;

A movement information management unit connected to the signal management unit and generating and managing a locus or path point for the robot to be associated with the specific body part to reach the movement target point;

And a control unit for receiving the guidance signal of the robot from the movement information management unit and controlling the movement of the robot,

Wherein the movement information management unit is provided to determine whether the robot has departed from a trajectory or a path point for reaching the movement target point and generate an induction signal for correcting the position accordingly. And provides an interface-based rehabilitation robot control system.

The signal managing unit includes: a signal receiving unit for receiving an electromagnetic signal from the brain;

A signal processor for filtering the electromagnetic signal; And a feature extraction unit for extracting, from the signal processing unit, a position of a moving target point of a specific body part and a velocity and a position characteristic of the specific body part.

Wherein the movement information management unit comprises: An operation unit for calculating a position of the moving target point and a continuous trajectory or a plurality of intermittent path points that can reach the position of the moving target point based on the feature extracted by the feature extracting unit; A characteristic extracting unit for measuring the characteristic;

And an induction signal generator for generating an operation induction signal of the robot based on the information of the operation unit and the characteristic extractor.

Wherein the calculation unit determines whether the current position of the robot has deviated from the locus or the route point based on the position of the robot received from the characteristic measurement unit,

And the induction signal generator generates an induction signal for correcting the position when the path or the path point is deviated.

Wherein the characteristic extracting unit measures the position or speed of the robot through an encoder or an acceleration sensor or a gyroscope or a sensor unit outside the robot, which is provided in the robot and encodes the state of the driving motor.

The sensor unit may include a camera unit.

According to another aspect of the present invention, there is provided an apparatus for analyzing a subject, comprising: a signal management unit for receiving an electromagnetic signal from a specific region of the brain and extracting characteristics of the estimated position by estimating a current position of a specific body part intended by the user; A movement information management unit connected to the signal management unit and generating and managing information for reaching a current position of the estimated specific body part; And a control unit for receiving the guidance signal of the robot from the movement information management unit and controlling the motion of the robot, wherein the movement information management unit, when the robot is away from the current position of the estimated specific body part by a predetermined distance or more, And a controller for generating an induction signal for correcting a position of the body-part to track a specific body part in real time.

The present invention also provides a method comprising: receiving an electromagnetic signal from a specific region of the brain; Processing the received signal and extracting information on a moving target point of a specific body part based on the received signal; Calculating a movement trajectory of the robot on the basis of the extracted moving target point and the position of the current robot and generating an induction signal corresponding to the movement trajectory, generating a control command to operate the robot according to the induction signal, The controller receives the information about the position and speed of the robot in real time to determine whether or not the position of the robot deviates from the provided movement trajectory and generates a control signal for position correction so that the robot can return to the movement trajectory The method comprising the steps of:

The movement trajectory may be implemented as a continuous line or as a plurality of path points spaced apart from each other.

The induction signal is implemented by a trajectory tracking induction method or a path point induction method.

The real-time reception of the information on the position and speed of the robot is performed by an encoder or an acceleration sensor or a gyroscope provided in the robot and encoding the state of the driving motor or a sensor unit implemented by a camera provided outside the robot do.

The present invention also provides a method comprising: receiving an electromagnetic signal from a specific region of the brain; Processing the received signal, estimating a current position of a specific body part intended by the user based on the received signal, and extracting information on the current position; Calculating a movement locus of the robot on the basis of the estimated position of the extracted specific body part and the position of the current robot and generating an induction signal corresponding thereto; Generating a control command so that the robot is operated according to the induction signal; The controller receives the information about the position and the speed of the robot in real time and determines whether or not the position of the robot is separated from the current position of the estimated specific body part by a predetermined distance or more. And generating a control signal for correcting the position of the robot so as to be able to track the robot in real time. The present invention also provides a control method of a brain-machine interface based rehabilitation robot.

According to the present invention, an electromagnetic signal emitted from a user's brain is analyzed to recognize a target position intended by a user, and a movement trajectory corresponding to the target position is extracted. Then, the movement trajectory of the robot is calculated, The movement of the matching robot can be realized.

Particularly, when calculating the movement trajectory of the robot and reflecting it to the actual operation, by using the path point guidance method or the trajectory tracking method used for calculating and guiding the movement trajectory of the air vehicle such as a missile or an airplane, I can reach it effectively.

Particularly, by real-time measurement of the robot's movement, position, speed, and the like, and when the robot deviates from the predetermined movement locus, a control command for returning to the locus of movement is issued, .

In addition, if the position of the robot is different from the position of the finger of a person estimated from the brain signal, the robot tracks the position of the finger and corrects the position thereof, thereby realizing the position control of the robot in accordance with the user's intention.

1 is a block diagram of a brain-machine interface-based rehabilitation robot control system according to the present invention.
2 is a block diagram of a PID controller as an embodiment applicable to a controller according to the present invention.
3 (a) is a schematic view showing a route point guidance method implemented by the present invention.
FIG. 3 (b) is a schematic diagram showing a trajectory tracking guidance method implemented by the invention.
FIG. 4 illustrates a locus of a finger of a person, which is estimated by analyzing a user's brain signal, and a locus of movement of the robot that tracks the finger in real time.
5 and 6 are flowcharts of a control method according to the present invention.

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

Electromagnetic signals (MEG, EEG) occur in areas where the human brain functions to control the movement of a specific part of the body. By analyzing this signal, you can figure out what the person wants to do and where they want to go.

The signal is filtered to obtain a specific frequency band of the EEG, which can then be predicted by the data of the acceleration sensor and multiple linear regression.

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a robot control system based on a brain-machine interface, and its configuration is as shown in FIG.

That is, the signal management unit 100 connected to the brain B, the movement information management unit 200 connected to the signal management unit 100, the control unit 300, the robot 400, and the sensor unit 500 . The specific structure and role of these are as follows.

The signal management unit 100 receives an electromagnetic signal from the brain and extracts characteristics relating to a moving target point of a specific body part (e.g., upper limb) from the electromagnetic signal.

Meanwhile, the signal management unit 100 may perform not only the moving target point but also a function of determining the human brain signal and tracking the position of the fingertip the user intends.

The specific structure of the signal management unit 100 includes a signal receiving unit 110 for receiving electromagnetic signals from the brain, a specific frequency band of an EEG by filtering the received electromagnetic signals, And a signal processing unit 120 for processing the signal.

The signal management unit 100 detects a position of a moving target point of a specific body part, a direction of a body part to be moved, a velocity characteristic, or a position of a current intended body (fingertip) from a signal processed by the signal processing unit 120 And a feature extraction unit 130 for extracting and extracting the feature extraction unit.

The signal management unit 100 can grasp and estimate the intention and the intention of the movement based on the analysis of the user's brain wave.

When the intention of the user is grasped by the signal management unit 100, the information is transmitted to the movement information management unit 200.

The movement information management unit 200 includes a characteristic measurement unit 210, an operation unit 220, and an induction signal generation unit 230.

The characteristic measuring unit 210 can measure the speed and current position of the robot based on information transmitted from the acceleration sensor 430, the gyroscope 440, and the encoder 420 provided in the robot 400 have.

The calculating unit 220 calculates the coordinates of the moving target point based on the current state of the robot 400 measured by the characteristic measuring unit 210 and the intention target, direction, and speed of the user extracted by the feature extracting unit 130 At the same time, the movement locus is calculated.

The movement locus calculated by the calculation unit 220 may be a continuous linear / non-linear locus, or may be a locus realized by a plurality of spaced-apart path points.

The trajectory is obtained through a plurality of route points, and the route guidance is referred to as "Waypoint Guidance." The continuous trajectory is obtained and the guidance is accordingly referred to as "Trajectory Tracking Guidance".

The induction signal generating unit 230 generates information on the initial robot position (initial position and velocity) measured by the characteristic measuring unit 210 and the path point trajectory or the continuous trajectory calculated through the calculating unit 220, So that an induction signal is generated.

The calculation unit 220 may calculate the current state of the robot 400 based on the current state of the robot 400 measured by the characteristic measurement unit 210 and the current position of the user's body part (e.g., fingertip) estimated by the feature extraction unit 130, The distance difference between the current position of the robot 400 and the estimated current position of the user's body part can be calculated.

When the distance between the current position of the robot 400 and the estimated current position of the user's body part is equal to or greater than a predetermined distance (for example, 40 mm), the robot 400 calculates the estimated current position The movement locus of the robot 400 can be calculated.

The movement locus calculated by the calculation unit 220 may be a continuous linear / non-linear locus, or may be a locus realized by a plurality of spaced-apart path points.

The induction signal generator 230 calculates the initial robot characteristic (initial position and speed) information measured by the characteristic measuring unit 210 and the calculated information through the calculating unit 220 so that the robot 400 real- It is possible to generate an induction signal that allows the estimated position to be tracked.

The control unit 300 receives the induction signal and controls the robot 400.

The controller 300 is preferably configured as a PID controller, but the present invention is not limited thereto. Accordingly, it is robust to disturbance, the response speed can be improved, and the operating error can be remarkably reduced.

The configuration of the controller 300 implemented by the PID controller is as shown in FIG.

P controller 310, I controller 320, and D controller 330 are connected in parallel with each other.

The P controller 310 functions to reduce the error, the I controller 320 contributes to the disturbance robustness, and the D controller 330 contributes to increase the response speed.

Besides the PID control method, a linear quadratic regulator (LQR) control method, which is a linear optimal control method, can also be used.

1, the robot 400 includes a frame (not shown) for forming an outer appearance thereof, a driving unit 410 for driving the frames, an acceleration sensor 430 for measuring the acceleration of the robot 400, A gyroscope 440 capable of measuring information, and the like.

The position of the robot 400 can be known by the acceleration sensor 430 and the rotation state of the end point of the robot can be known by the gyroscope 440. [

The robot 400 further includes an encoder 410. The encoder 420 serves to encode the information of the driving unit 410 constituted by the driving motor.

The acceleration sensor 430 or the gyroscope 440 or the encoded information is transmitted to the movement information management unit 200, the control unit 300 and the sensor unit 500 to be described later and is used to correct the locus of the robot 400 .

The sensor unit 500 is for measuring the current state of the robot 400 from the outside, and is preferably implemented by an infrared camera, a general camera, or the like.

The information secured by the sensor unit 500 is transmitted to the movement information management unit 200 and the control unit 300 so that they can be used to correct the locus of the robot 400. [

The information shot by the sensor unit 500 is information obtained by grasping the current state of the robot, the target position, the target object, and the external influences in real time, and the result can be converted into the coordinate value by the sensor unit 500.

Accordingly, when the sensor unit 500 is a camera, the accurate position and external influence of the target object can be reflected in the induction signal through the coordinate transformation matrix between the camera and the robot.

Fig. 3 shows that a movement locus is set when a user's intended target point is set and the robot knows the initial position of the robot.

In particular, it is assumed that there is an obstacle between the starting point and the target point.

Fig. 3 (a) shows a case where the route point guidance is performed. In this case, the path from the start point to the target point is not implemented as a continuous line in the operation unit 220 (see FIG. 1) and the induction signal generation unit 230 (see FIG. 1) but is implemented as a plurality of intermediate path points spaced from each other .

Fig. 3 (b) shows the case of performing the trajectory following guidance. In this case, the calculation unit 220 and the induction signal generator 230 implement a path from the starting point to the target point as a continuous line.

Figs. 3 (a) and 3 (b) illustrate a control method in which a trajectory between them is estimated or set when the intended target point is determined at the current point, and the robot can follow the trajectory.

This control method is called GN & C (Guidance, Navigation, & Control) method.

FIG. 4 is a diagram for explaining a case where a control method for enabling a robot to track real time of a position of a fingertip of a person at that time, instead of following an estimated complete trajectory to a target point as shown in FIG. 3, And the position of the robot is changed.

The solid line shows the connection of the estimated finger position change, and the line connecting the points is the change of the position of the robot.

Here, when the position of the robot and the position of the estimated finger of the person (the position estimated by analyzing the brain signal) are different by 40 mm or more, the robot can track the position of the finger detected from the human brain signal.

This is a guideline command generated by applying a special guiding law. In this case, the robot can track and follow the human arm in real time when the position of the estimated human hand is different.

Guidance Law is a type of Guidance Command used to track and follow a moving object such as a missile. Typical examples are Velocity Pursuit Guidance, Line- of-sight Guidance, and Proportional Navigation Guidance.

FIG. 4 is a graph showing a result of real-time tracking of a position of a human hand estimated by a robot using velocity tracking guidance (Velocity Pursuit Guidance) when the estimated position of the human hand is different by 40 mm.

Figures 5 and 6 illustrate operations according to the present invention.

First, when an electromagnetic signal of the brain is received at the signal receiving unit (S501), the signal processing unit processes the electromagnetic signal (S502).

That is, the signal is processed through a filtering process and a polynomial regression method, and the position of the moving target point of the specific body part (e.g., arm) and the direction and speed characteristics of the body part to be moved are extracted through the feature extracting part (S503 ).

When the intention of the user is thus grasped, this information is transmitted to the movement information management unit.

The movement information management unit recognizes the current speed and current position state of the robot and also calculates the coordinates of the movement target point based on the intention target, direction and speed of the user extracted from the feature extraction unit, And calculates a movement trajectory to be different.

At this time, the movement locus may be a continuous locus in the form of a continuous line (S504), or may be a locus set by a plurality of spaced-apart path points (S505).

Based on this, the induction signal generator generates an induction signal to the controller (S506).

When the control unit issues a driving command to the robot based on the received induction signal, the robot moves along the received movement trajectory (S507).

On the other hand, due to disturbance or noise, the position of the robot can be displaced from a locus that is supposed to move originally.

The position of the robot is recognized in real time by the characteristic measurement unit, the control unit, and the sensor unit.

In step S508, it is determined whether the position of the robot deviates from the predetermined movement locus in step S508. In this case, a control signal for correcting the current position is generated in step S601. The control signal is generated by the induction signal generator and transmitted to the robot through the controller.

In this case, the robot can return to the predetermined movement trajectory. If it is determined that the robot has reached the target point, the robot repeats the above process until the robot reaches the target position, so that the robot can move to the position intended by the user (S602).

On the other hand, instead of calculating the coordinates of the movement target point, coordinates of a point intended to be able to estimate the position of the current fingertip the user intended can be calculated.

Then, the estimated finger end position is compared with the current robot position, and when the difference between the two positions is greater than a predetermined distance (e.g., 40 mm), the robot can track the estimated finger tip in real time It is also possible.

100: signal management unit 110: signal reception unit
120: signal processor 130: feature extractor
200: movement information management unit 210: characteristic extraction unit
220: operation unit 230: induction signal generator
300: control unit 400: robot
410: Driving unit 420: Encoder
430: Acceleration sensor 440: Gyroscope
500:

Claims (12)

delete delete delete delete delete delete A signal management unit for receiving an electromagnetic signal from a specific region of the brain and extracting characteristics of the estimated position by estimating a current position of a specific body part intended by the user;
A movement information management unit connected to the signal management unit and generating and managing information for reaching a current position of the estimated specific body part;
And a control unit for receiving the guidance signal of the robot from the movement information management unit and controlling the movement of the robot,
The movement information management unit is configured to generate an induction signal for position correction that can track the estimated specific body part in real time when the robot is away from the estimated current position of the specific body part by a predetermined distance or more Wherein the robot-machine-based rehabilitation robot control system is a brain-machine interface-based rehabilitation robot control system. delete delete delete delete Receiving an electromagnetic signal from a specific region of the brain;
Processing the received signal, estimating a current position of a specific body part intended by the user based on the received signal, and extracting information on the current position;
Calculating a movement locus of the robot on the basis of the estimated position of the extracted specific body part and the position of the current robot and generating an induction signal corresponding thereto;
Generating a control command so that the robot is operated according to the induction signal;
The controller receives the information about the position and the speed of the robot in real time and determines whether or not the position of the robot is separated from the current position of the estimated specific body part by a predetermined distance or more. And generating a control signal for correcting the position of the robot so as to track the robot in real time.

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