CN104666047A - Double-side mirror image rehabilitation system based on biological information sensing - Google Patents

Abstract

The present invention is a double-sided image rehabilitation system based on biological information perception. One end of the somatosensory device is connected to the healthy side limb to collect the motion signal of the healthy side limb; the other end is connected to the computer through the USB bus, and the collected healthy side limb's motion The signal is sent to the computer; the motor driver is connected to the computer through the CAN bus to receive the motion control command sent by the computer; the other end is connected to the motor, and the received motion control command is converted into a corresponding current signal, which is sent to the motor to drive the motor Rotate; the motor is arranged at the kinematic joint of the mechanical arm, and when the motor rotates, it drives the connecting rod of the mechanical arm to move; the limb on the affected side is placed in the mechanical arm, and the connecting rod on the mechanical arm drives the limb on the affected side to perform rehabilitation exercises. The invention can realize the rehabilitation of the active motor function of the hemiplegic patient, and mobilize the function of the healthy limb of the hemiplegic patient to assist the affected side to carry out rehabilitation training.

Description

Bilateral mirror rehabilitation system based on biological information perception

technical field

The invention relates to a novel medical rehabilitation field for hemiplegia patients, in particular to a bilateral mirror image rehabilitation system based on biological information perception.

Background technique

Cerebral apoplexy (also known as cerebral apoplexy) is a kind of acute cerebral blood circulation disorder caused by the stenosis, occlusion or rupture of intracerebral arteries caused by predisposing factors, clinically manifested as symptoms and signs of transient or permanent brain dysfunction. Cerebral apoplexy is a clinical common disease and frequently-occurring disease. Its fatality rate and disability rate are very high. It constitutes the three major fatal diseases in most countries together with heart disease and malignant tumors. It seriously endangers human health and life safety and brings great harm to patients. Great physical and mental pain, a heavy burden on the family and society. In developed countries, stroke has become the main factor of people's acquired disability. In my country, there are 2 million stroke patients every year. With the continuous improvement of medical conditions and treatment technology, the mortality rate of stroke patients has been significantly reduced, but among the 7 million surviving stroke patients, 4.5 million patients have lost their basic labor ability and self-care ability to varying degrees , its morbidity rate is as high as 75% or more among survivors. Motor dysfunction is the most common manifestation of stroke patients, and about 2/3 of stroke patients have dysfunction of one upper limb. The upper limb motor function plays a vital role in people's daily life and work. It can not only complete simple upper limb movements such as pushing, pulling, grasping, and lifting, but also perform some complex and delicate hand operations. Therefore, if the upper limb encounters Dysfunction will seriously affect the patient's ability to take care of themselves and reduce their independence in life.

After more than ten years of development, a variety of rehabilitation techniques have emerged for the upper limb motor dysfunction of stroke hemiplegia. However, many studies have shown that traditional rehabilitation techniques are not very effective in recovering motor function after stroke. We now realize that all rehabilitation methods are aimed at regaining control of movement. The functional changes of the motor cortex depend on the amount of activity experienced by the limbs and their own experience of movement. The effect of rehabilitation treatment is related to the neuromuscular system stimulated by voluntary movement. The greater the intensity of post-stroke rehabilitation, the more conducive to the recovery of motor function.

The traditional hemiplegia rehabilitation treatment method is mainly that the hemiplegia patients use the affected limbs to repeatedly complete a single training movement with the help of multiple therapists. Since each rehabilitation training requires the cooperation of two to three doctors to ensure the safety of the training, so as not to cause the patient to be injured again during the rehabilitation exercise, the rehabilitation cost is relatively expensive, which brings huge economic pressure to the patient's family , Many patients also gave up treatment because of this, missed the best time for postoperative recovery, and left great regrets. Secondly, repeating a single training method is likely to make the patient feel bored and feel tired, thereby reducing the effect of treatment and failing to achieve the expected rehabilitation goals.

The development of robotics and its combination with clinical rehabilitation medicine provides a good solution to the current shortage of rehabilitation physicians. Robot rehabilitation has the following advantages that make it very suitable for rehabilitation training of limb patients: a) the robot is suitable for long-term reciprocating motion and meets the needs of rehabilitation training; b) the robot can flexibly control the force exerted on the patient; c) The robot can accurately and repeatedly generate the required training force. The above characteristics have made medical rehabilitation robots develop rapidly in recent years.

However, the current medical rehabilitation robots need to be improved in the following aspects:

The patient's active participation is low: most rehabilitation systems only drive the affected side of the patient to perform rehabilitation, moving according to the established trajectory, and the patient belongs to the passive movement mode;

New concept of rehabilitation: Bilateral movement is a movement pattern in which the limbs on both sides perform common time and space. Bilateral mirror training has a positive effect on both hemispheres, which is very beneficial to the rehabilitation of patients. However, the existing rehabilitation system generally drives the affected side of the patient to move unilaterally;

Safety issues: The motion control of rehabilitation equipment does not incorporate the characteristics of the flexibility of human limbs, which makes the patient's rehabilitation training operation stiff and easy to cause permanent damage to the patient's limbs;

Compliance issues: the rehabilitation process does not take into account the patient's pain perception, and the patient's compliance is poor;

Objective evaluation of rehabilitation: The rehabilitation system lacks objective evaluation standards for rehabilitation effects.

Contents of the invention

Aiming at the deficiencies of the prior art, the present invention provides a bilateral mirror image rehabilitation system based on biological information perception, which realizes the active motor function rehabilitation of hemiplegic patients, and mobilizes the functions of the healthy limbs of hemiplegic patients to assist the affected side in rehabilitation training.

The technical scheme that the present invention adopts for realizing the above object is:

A bilateral mirror rehabilitation system based on biological information perception. One end of the somatosensory device is connected to the healthy limb to collect motion signals of the healthy limb, and the other end is connected to the computer through the USB bus to send the collected motion signals of the healthy limb to computer;

The motor driver is connected to the computer through the CAN bus to receive the motion control commands sent by the computer; the other end is connected to the motor to convert the received motion control commands into corresponding current signals and send them to the motor to drive the motor to rotate;

The motor is arranged at the kinematic joint of the mechanical arm, and when the motor rotates, it drives the connecting rod of the mechanical arm to move;

The limb on the affected side is placed in the mechanical arm, and the connecting rod on the mechanical arm drives the limb on the affected side to carry out rehabilitation exercises.

A torque sensor is provided at the kinematic joint of the mechanical arm to measure the torque information of the joint shaft;

One end of the data acquisition card is connected to the torque sensor for collecting torque information;

The other end of the data acquisition card is connected to the computer, and the collected torque information is sent to the computer.

The torque sensor is a strain type torque measuring element.

The limb on the affected side is connected to one end of the electromyographic signal acquisition device for collecting the electromyographic signal on the limb on the affected side;

The other end of the electromyographic signal collection device is connected to a computer for sending the collected signals to the computer.

The myoelectric signal acquisition device includes a myoelectric electrode, a signal amplifier and a data acquisition box connected in sequence; wherein the myoelectric electrode is connected to the affected limb for receiving the signal of the affected limb and converting the signal of the affected limb Send to the signal amplifier, the signal amplifier sends the processed signal to the data acquisition box, and the data acquisition box sends the collected signal to the computer.

Also included is a dementia brake control button held by a rehabilitation therapist.

The dementia brake control button is connected with the embedded real-time system, and is used for the rehabilitation therapist to control and safely stop the rehabilitation training process in case of accident or emergency.

The somatosensory device is a device that uses infrared measurement technology to realize the acquisition of 3D scene depth information.

The virtual reality scene display device is worn on the patient's head and is connected with a computer to display the virtual reality scene generated by the computer in front of the patient's eyes to form visual feedback for the patient's rehabilitation training.

The present invention has the following beneficial effects and advantages:

1. Improve the participation of patients in rehabilitation training. Patients' rehabilitation training is no longer based on fixed training movements, but also based on common daily life behaviors, which improves the efficiency of rehabilitation;

2. Based on the theory of mirror movement rehabilitation, further effectively improve the efficiency of patient rehabilitation;

3. The use of robotic arms to drive patients to recover frees the physical labor of rehabilitation therapists, allowing rehabilitation therapists to concentrate on the arrangement of rehabilitation courses and the design of rehabilitation training tasks, and optimize the rehabilitation effect of patients;

4. A variety of sensors are installed on the rehabilitation equipment, which can reliably and quantitatively measure various parameters in the process of patient rehabilitation training, and facilitate effective evaluation of the patient's rehabilitation effect. Based on this evaluation, different patients can be proposed different Rehabilitation training requirements, to achieve the purpose of individual treatment.

Description of drawings

Fig. 1 is a functional block diagram of the bilateral mirror image rehabilitation system of the present invention;

Fig. 2 is the functional block diagram of myoelectric signal acquisition device of the present invention;

Fig. 3 is the block diagram of the control system based on force and position hybrid control according to the present invention;

Fig. 4 is a schematic diagram of the exoskeleton upper limb rehabilitation mechanical arm according to the present invention, in which 1 is the degree of freedom of abduction and adduction of the shoulder joint, 2 is the degree of freedom of lifting and lowering the shoulder joint, and 3 is the degree of freedom of bending the elbow joint.

Detailed ways

The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

As shown in Fig. 1, it is a functional block diagram of the bilateral mirror image rehabilitation system according to the present invention, which includes the following main parts: somatosensory equipment limb motion state acquisition, real-time 3D virtual reality scene generated by computer, DC motor driver, upper limb exoskeleton rehabilitation Robotic arm, sensor for measuring joint torque of the robotic arm, surface electromyography signal acquisition system, emergency stop button for emergency situations, data acquisition card for collecting system sensor data, motion control software running on the embedded real-time system, fusion Algorithms for motion control of rehabilitation manipulators based on force and position information. The somatosensory device collects the movements of the patient's healthy limbs, converts them into kinematic parameters, and transmits them to the computer.

The computer receives the motion state of the healthy side of the patient and judges whether the state is in a safe state space. If it is in a safe state space, it sends a control command to the motion control algorithm to drive the exoskeleton rehabilitation robotic arm to drive the affected limb of the patient to complete the mirror movement. ; If the state is not in the safe state space, an alarm will be sent to the patient through the virtual reality scene, indicating that the rehabilitation training action deviates from the norm and needs to be readjusted. The computer runs the virtual reality scene generation software, uses the 3D graphics engine to drive the human simulation model based on the bone skin technology, and presents the scene to the patients receiving rehabilitation training from the first-person perspective; the human body model in this scene imitates the patient Actions made, and complete a series of pre-designed computer-generated virtual tasks, including grasping and moving objects, and completing a specified action sequence. The computer-generated real-time 3D virtual reality scene provided by the present invention is characterized in that: using three-dimensional modeling software, using bone skin animation technology to establish a highly simulated human body computer three-dimensional model, and realizing the three-dimensional graphic engine driving the model by computer programming to realize the human body Motion simulation, and display the virtual scene to the patients receiving rehabilitation training through the graphic display, so as to realize the visual feedback of the patient's rehabilitation process. And a series of training actions that need to be completed in upper limb rehabilitation training are designed, and provided to patients to choose and complete corresponding training in the form of game tasks with the help of virtual reality scenes.

As shown in Figure 4, it is a schematic diagram of the exoskeleton upper limb rehabilitation mechanical arm according to the present invention. The exoskeleton mechanical arm is equipped with at least three degrees of freedom, including the degree of freedom of shoulder joint lifting and hem down 1, and the degree of freedom of shoulder joint abduction and adduction 2. Elbow joint bending degree of freedom 3, wherein the elbow joint bending degree of freedom can be in the same plane or in two perpendicular planes with the shoulder joint lifting and lowering degree of freedom under the condition of adjusting the installation position of the forearm robotic arm. And each degree of freedom is driven by a DC motor.

The invention provides a set of patch type torque sensors for measuring the output torque of exoskeleton manipulator joints, using strain type torque measuring elements, sticking the elements on the joints where the joints are deformed by torque, and adopting the distribution method of full bridge strain element distribution And the measurement circuit, use a passive filter to filter the original signal output by the sensor to weaken the interference, use a high-precision instrument amplifier to amplify the filtered weak stress signal to the amplitude range received by the data acquisition card, and convert the amplified sensor The analog signal is connected to the data acquisition card for analog-to-digital conversion.

The surface mount electrode is composed of a viscous adhesive layer and three electrode contacts; the three electrode contacts are respectively a signal reference ground and two differential signal input terminals; the patch electrode is connected to the signal acquisition box through a shielded wire, The signal acquisition box is connected with the computer through the data bus to realize the acquisition and recording of the electromyographic signal data. Using the collected surface electromyographic signal data, the current upper limb joint motion angle can be estimated by using its signal characteristics. At the same time, the surface electromyography signal can be used to estimate muscle spasm, stop rehabilitation training when it is predicted that the spasm will occur, and judge the pain degree of the patient according to the surface electromyography signal information, and stop rehabilitation training when pain occurs.

Bilateral mirror image rehabilitation system based on biological information perception can be used for upper limb function recovery of patients with upper limb dysfunction, including limb motion perception equipment based on somatosensory equipment, real-time 3D virtual reality scenes generated by computers, DC motor drivers, upper limb exoskeleton rehabilitation machinery Arm, robotic arm joint torque measurement sensor, surface electromyography signal acquisition system, emergency stop and auxiliary buttons for handling emergency and specified events, data acquisition card for collecting system sensor data, motion control software, fusion force and position information The motion control algorithm of the rehabilitation robotic arm; the somatosensory device collects the depth information and color image information of the scene, estimates the patient's current motion state based on the human skeleton model and predicts the patient's next possible motion state; the computer 3D real-time virtual reality The scene generates the mirror visual simulation required for patient rehabilitation, and at the same time guides the actions required for patient rehabilitation in a task-based manner; the upper limb rehabilitation robotic arm includes an upper limb exoskeleton body and a DC motor that provides power; the DC motor driver The DC motor is connected with the DC motor through the power line and the signal line, and connected with the computer through the data bus; the DC motor is provided with a digital Hall sensor and a photoelectric encoder. The motion control algorithm of the manipulator integrates force and position information, and according to the movement state of the patient's limbs collected by the somatosensory device, the control command is sent to the DC motor driver through the data bus on the computer side, and then the DC motor driver controls the upper limb exoskeleton. The patient's limbs have completed rehabilitation training.

As shown in Figure 2, it is the functional block diagram of the myoelectric signal acquisition device of the present invention, and the surface electromyography signal acquisition system includes an electromyography electrode, a signal amplifier, and a data acquisition box; wherein the electromyography electrode is connected to the affected limb for Receive the signal of the affected limb, and send the signal of the affected limb to the signal amplifier, and the signal amplifier sends the processed signal to the data acquisition box, and the data acquisition box sends the collected signal to the computer.

The limb motion sensing device based on the somatosensory device provided by the present invention uses infrared measurement technology to realize the depth information collection of 3D scenes, and uses visible light sensors to realize the color image collection of the scene; after fusing and calibrating the depth information and color information, the scene can be obtained The three-dimensional coordinates of any point in space; combined with the human skeleton model, the three-dimensional coordinates in the x, y, and z directions of the wrist, elbow, and shoulder joints of the human upper limb can be obtained; the joint motion angle can be estimated by using the space coordinates of the joint points according to the following steps:

Define the coordinates of the shoulder joint as (x1, y1, z1), the coordinates of the elbow joint as (x2, y2, z2), and the coordinates of the wrist joint as (x3, y3, z3)

The up and down swing angle of the shoulder joint is

${\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arccos</span>}\frac{{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}{\sqrt{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}$

The angle of abduction and adduction of the shoulder joint is

${\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arccos</span>}\frac{{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}{\sqrt{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}$

The elbow flexion angle is

$\mathrm{<span\; class="notranslate">\; AB</span>}<span\; class="notranslate">\; =</span>\sqrt{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}$

$\mathrm{<span\; class="notranslate">\; BC</span>}<span\; class="notranslate">\; =</span>\sqrt{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}$

$\mathrm{<span\; class="notranslate">\; AC</span>}<span\; class="notranslate">\; =</span>\sqrt{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}$

${\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arccos</span>}\frac{{\mathrm{<span\; class="notranslate">\; AB</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; BC</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; AC</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \&CenterDot;</span>\mathrm{<span\; class="notranslate">\; AB</span>}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; BC</span>}}$

As shown in Figure 3, it is a block diagram of the control system based on force and position hybrid control according to the present invention. The signal collected by the torque sensor is used for force/position hybrid control of the exoskeleton manipulator, and the torque sensor adopts a patch-based strain The sensor indirectly measures the output torque of the connecting rod by measuring the bending strain of the connecting rod. The torque information is kinematically decoupled and converted into a given movement deviation signal for each degree of freedom, which is used to control the exoskeleton arm. Movement, so that the moment of direct contact between the patient and the robotic arm is integrated into the closed-loop control of the robotic arm to realize the compliance of the control of the robotic arm to the contact force between the human and the robotic arm. This control algorithm makes the patient comfortable during rehabilitation training sex and security.

The surface electromyographic signal is input into the acquisition box through the electrodes pasted on the skin surface for collection, and the computer reads the collected electromyographic signal to analyze the current movement angle of the patient's arm joints and determine whether the movement range is in a safe movement state space , and give alarms to incorrect and dangerous motion states. At the same time, the EMG signal can be used to judge the pain of the patient's affected arm. When the patient's affected arm moves in a safe space but the patient's pain is detected, an alarm will be given and the current rehabilitation training process will be stopped. EMG signals reflect the activity of human muscles, so the characteristics of EMG signals are also used to evaluate the rehabilitation effect of patients after a period of rehabilitation treatment, and provide guidance and basis for rationally arranging treatment plans.

Claims (9)

1. A bilateral mirror image rehabilitation system based on biological information perception, characterized in that: One end of the somatosensory device is connected to the healthy limb to collect the motion signal of the healthy limb, and the other end is connected to the computer through the USB bus, and the collected motion signal of the healthy limb is sent to the computer; The motor driver is connected to the computer through the CAN bus to receive the motion control commands sent by the computer; the other end is connected to the motor to convert the received motion control commands into corresponding current signals and send them to the motor to drive the motor to rotate; The motor is arranged at the kinematic joint of the mechanical arm, and when the motor rotates, it drives the connecting rod of the mechanical arm to move; The limb on the affected side is placed in the mechanical arm, and the connecting rod on the mechanical arm drives the limb on the affected side to carry out rehabilitation exercises. 2. the bilateral mirror image rehabilitation system based on biological information perception according to claim 1, is characterized in that: A torque sensor is provided at the kinematic joint of the mechanical arm to measure the torque information of the joint shaft; One end of the data acquisition card is connected to the torque sensor for collecting torque information; The other end of the data acquisition card is connected to the computer, and the collected torque information is sent to the computer. 3. The bilateral mirror image rehabilitation system based on biological information perception according to claim 2, characterized in that: the torque sensor is a strain type torque measuring element. 4. the bilateral mirror image rehabilitation system based on biological information perception according to claim 1, is characterized in that: The limb on the affected side is connected to one end of the electromyographic signal acquisition device for collecting the electromyographic signal on the limb on the affected side; The other end of the electromyographic signal collection device is connected to a computer for sending the collected signals to the computer. 5. the bilateral mirror image rehabilitation system based on biological information perception according to claim 4, is characterized in that: The myoelectric signal acquisition device includes a myoelectric electrode, a signal amplifier and a data acquisition box connected in sequence; wherein the myoelectric electrode is connected to the affected limb for receiving the signal of the affected limb and converting the signal of the affected limb Send to the signal amplifier, the signal amplifier sends the processed signal to the data acquisition box, and the data acquisition box sends the collected signal to the computer. 6. The bilateral mirror image rehabilitation system based on biological information perception according to claim 1, further comprising a brake control button for deafness held by the rehabilitation therapist. 7. The bilateral mirror image rehabilitation system based on biological information perception according to claim 6, characterized in that: the dementia brake control button is connected with the embedded real-time system, and is used for rehabilitation treatment in case of accident or emergency The teacher controls the safe stop of the rehabilitation training process. 8. The bilateral mirror image rehabilitation system based on biological information perception according to claim 1, characterized in that: the somatosensory device is a device that uses infrared measurement technology to realize the acquisition of 3D scene depth information. 9. The bilateral mirror rehabilitation system based on biological information perception according to claim 1, characterized in that: the virtual reality scene display device is worn on the patient's head and connected to a computer to display the virtual reality scene generated by the computer The visual feedback of the patient's rehabilitation training is formed in front of the patient's eyes.