Double-upper-limb rehabilitation training management system

Abstract

The invention discloses a double-upper-limb rehabilitation training management system which comprises a training management system, and the training management system comprises an intelligent rehabilitation platform, a modeling DFM platform, a bionic robot platform and a robot structure platform. Effective evaluation is carried out through a movement route of the system before training, a corresponding PNF upper limb training track is planned based on the functional level and the seat height posture of a patient, training imitating therapist skills is carried out, excitation and inhibition of main prime mover muscles and antagonistic muscles of the upper limb of the uninjured side of the patient are detected through surface myoelectricity, and the result serves as a normal standard. Myoelectricity detection is carried out on prime mover muscles and antagonistic muscles of the upper limb of the affected side, the effects of promoting excitation of the prime mover muscles and inhibiting the antagonistic muscles are carried out according to the state presented in the motion trail, and the excitation of the prime mover muscles is mainly promoted at the positions of muscle abdomens and muscle tendons in a tapping stimulation mode in an intermediate frequency therapeutic apparatus.

Description

Technical Field

[0001] The present invention relates to the technical field of rehabilitation training, and in particular to a double upper limb rehabilitation training management system. Background Art

[0002] The rehabilitation of upper limb motor function and hand function is the key and difficulty for the prognosis of stroke patients. Its rehabilitation treatment emphasizes diversity and comprehensiveness. It should not only focus on the rehabilitation training of motor function, but also pay attention to appropriate sensory input stimulation. Proprioceptive neuromuscular facilitation therapy stretching training can produce continuous motor sensation and proprioceptive stimulation. It is simple and easy to operate. It can be used as an important means of upper limb functional rehabilitation for hemiplegic stroke patients. The rehabilitation of hemiplegic stroke patients should be aimed at enhancing the function of the affected limb. The characteristics of PNF stretching training are analyzed, especially based on the physiological characteristics of neuromuscular. During the training process, a large number of receptors are stimulated to excite, thereby strengthening muscle activity and promoting the improvement of limb functional movement.

[0003] Using the upper limb PNF training model, the patient took the supine position, and the rehabilitation therapist sat on the patient's waist. First, the passive training movement of upper limb extension-adduction-internal rotation was performed. Then the therapist grasped the patient's affected hand with one hand and grasped the patient's affected upper arm with the other hand. After that, the patient changed to a seat and repeated the above training movements. After 20 days of treatment, the upper limb function and hand function were significantly improved compared with conventional rehabilitation. On the basis of thermosensitive moxibustion, proprioceptive neuromuscular promotion therapy was performed on patients with spastic hemiplegia of the upper limbs due to stroke: the patient's upper limbs were trained in flexion-adduction-external rotation mode, flexion-abduction-external rotation mode, and then switched to extension-abduction-internal rotation mode training, and finally to extension-adduction-internal rotation mode, 30 minutes / time, 6 times / week, and 1 consecutive treatment. The results showed that proprioceptive neuromuscular promotion therapy combined with thermosensitive moxibustion in patients with upper limb spastic hemiplegia after stroke can effectively improve the patient's muscle spasm and promote the recovery of the patient's upper limb motor function, while promoting the reconstruction of proprioception and the brain's neuromotor center signals, effectively correcting the patient's abnormal movement pattern and restoring blood rheology indicators. In the treatment of active, assisted and passive movements of conventional manual rehabilitation, Bobath technique, rood technique, and upper limb muscle strength training combined with PNF stretching technique can be used: according to the patient's muscle strength and muscle tension, the affected upper limb is moved from one side flexion mode to the opposite side extension mode or from the opposite side flexion mode to the other side extension mode, diagonal spiral, and reciprocating motion. During the operation, the rhythm of movement should be stabilized, and both contraction and relaxation should be taken into account. Appropriate visual, auditory and tactile stimulation should be given during the exercise. Treatment should be given once a day, and home training should be continued as required after treatment. The results showed that after one month, the Brunnstrom assessment of the upper limbs of the patients in the PNF technology group found that more patients had decreased abnormal muscle tension in the upper limbs and dissociated movements. The upper limb motor function score was also better than that of the control group. PNF technology is effective in treating spastic hemiplegia of the upper limbs after stroke, and can effectively improve the motor function of the upper limbs and improve the ability of daily living activities.

[0004] However, the traditional PNF upper limb training model has the following disadvantages:

[0005] The traditional PNF technology upper limb training model has been confirmed by scholars to have a therapeutic effect on the rehabilitation of upper limb function in stroke patients, and based on the therapeutic effect of PNF technology in stroke, corresponding training courses have been established for standardized learning; but because the number of therapists is too far from the number of stroke patients who need rehabilitation, there is a shortage of therapists, and the levels of therapists are uneven, the level of PNF technology will also affect the rehabilitation effect of patients, and the rehabilitation training of stroke patients is based on the theory of motor relearning, and the lower limb function is better than the upper limb function. Part of the reason is that the number of lower limb training sessions of patients is far more than that of upper limbs, and the rehabilitation of upper limbs and the patients' needs for upper limb rehabilitation are worse than those of lower limbs, and the content of upper limb rehabilitation training is shorter than that of lower limb training. The number of patients who receive PNF training is relatively small, the recovery process is slow, patients are easily bored after long-term training, and the labor cost is high. However, in PNF technology, when the therapist assists the patient with assisted active movements with both hands, he can very intuitively feel the degree of participation of the patient's upper limb muscles, and provide supplementary assistance and verbal encouragement based on the patient's active participation. He also guides the patient to participate in multiple degrees of freedom of the three joints of the shoulder, elbow, and wrist upper limbs, and the guided movements are all movements that normal people can complete in life. However, when the patient contracts autonomously, due to the stroke, the patient's ability of autonomous contraction is poor, and abnormal contraction of the antagonist muscles and the emergence of compensatory functions are also very easy to occur during training. The therapist cannot take into account both the promotion of contraction of the agonist muscles and the inhibition of the antagonist. Summary of the invention

[0006] The purpose of the present invention is to provide a bilateral upper limb rehabilitation training management system to solve the problem that the traditional PNF technology upper limb training mode proposed in the above background technology has been confirmed by scholars to have a therapeutic effect on the rehabilitation of upper limb function of stroke patients, and based on the therapeutic effect of PNF technology in stroke, corresponding training courses have been conducted for standardized learning; but since the number of therapists is too far from the number of stroke patients who need rehabilitation, there is a shortage of therapists, and the levels of therapists are uneven, the level of PNF technology techniques will also affect the rehabilitation effect of patients, and the rehabilitation training of stroke patients is the theory of motor relearning, and the lower limb function is better than the upper limb function rehabilitation, partly because the number of training times of patients' lower limbs is far more than that of upper limbs, and the rehabilitation of upper limbs and the patients' needs for upper limb rehabilitation are poorer than those of lower limbs. Some of them, the rehabilitation training content of the upper limbs is less than that of the lower limbs, the recovery process is slower, patients are easily bored after long-term training, the labor cost is high, etc. However, in PNF technology, when the therapist assists the patient with assisted active movements with both hands, he can very intuitively feel the degree of participation of the patient's upper limb muscles, give supplementary assistance and verbal encouragement according to the degree of active participation of the patient, and guide the patient to participate in multiple degrees of freedom of the three joints of the shoulder, elbow and wrist upper limbs. The guided movements are all movements that normal people can complete in life. However, when the patient contracts autonomously, due to the stroke, the ability of autonomous contraction is poor, the antagonist muscles contract abnormally, and compensatory function is also very easy to occur during training. The therapist cannot take into account the problem of promoting contraction of the agonist muscles and inhibiting the antagonist.

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a dual upper limb rehabilitation training management system, comprising a training management system, the training management system comprising an intelligent rehabilitation platform, a modeling DFM platform, a bionic robot platform and a robot structure platform, the intelligent rehabilitation platform comprising a movement pattern module, a muscle state evaluation module, a manipulation force conduction module, an evaluation integration module, a treatment module and a verbal encouragement module, the movement pattern module evaluates the movement trajectory - movement pattern activities based on the spiral / diagonal form of the PNF upper limb, the muscle state evaluation module after the patient's healthy hand is held by the bionic robot dual mechanical upper limb using the PNF manipulation, and moves according to the original PNF movement trajectory in the system, according to the changes in the three joint angles of the shoulder, elbow and wrist joints of the upper limb, the contraction of the normal corresponding prime mover muscle group, the inhibition of the antagonist and the duration of muscle contraction maintenance and relaxation maintenance are detected, the system plans a normal muscle state as a normal standard, and then the therapist uses the PNF upper limb technology to guide the patient's affected upper limb to move under the seat, according to the changes in the three joint angles of the shoulder, elbow and wrist joints of the affected upper limb, the detection The contraction of the corresponding prime mover muscle group, the inhibition of the antagonist, and the duration of muscle contraction and relaxation are measured. The system evaluates the muscle status before treatment as the baseline level. The technology is implemented by: Athos sportswear, MC sensor, surface electromyography, Finnish Mbody3 muscle activity detection and comprehensive human analysis technology support for sports performance, manual force conduction module. When the therapist uses PNF upper limb manipulation to guide the healthy upper limb of the stroke patient to perform diagonal spiral movement, the therapist senses the patient's active movement and force conduction through the tactile receptors on the skin, and gives appropriate resistance or assistance guidance according to the patient's active feedback, and takes the stress feedback of the healthy side of the patient as the normal standard, and takes the assistance given to the patient by the therapist through touch as the minimum intensity during treatment, and takes the resistance as the maximum intensity during treatment; When the PNF upper limb manipulation is used to guide the stroke patient's affected upper limb to perform diagonal spiral movement, the therapist senses the patient's active movement and force conduction through the tactile receptors, and gives appropriate resistance or assistance guidance according to the patient's active feedback, and takes the stress feedback of the affected side of the patient as the baseline level;Flexible pressure sensors and electronic skin tactile sensor technology support, the evaluation integration module uses the motion trajectory of the stroke patient's normal upper limb under the bionic robot technique, as well as the activation, contraction, relaxation, and continuous muscle function status of each prime mover and antagonist muscle group at each moment of the movement, and the patient's active feedback as the normal standard after systematic analysis, and uses the motion trajectory of the stroke patient's affected upper limb under the bionic robot technique, as well as the activation, contraction, relaxation, and continuous muscle function status of each prime mover and antagonist muscle group at each moment of the movement, and the patient's active feedback as the baseline after systematic analysis, thus conducting advanced training design based on the patient's range of motion of each joint involved in the motion trajectory, the level of participation of each muscle group, and the degree of participation in active motion, and the motion trajectory of the treatment module The output should avoid repetitiveness and dullness, and jointly predict the joints and muscles affected by the next movement trajectory. Combined with the bionic robot receiving flexible pressure information, it is targeted, easy to understand, simple, and will amplify the patient's slow and weak active participation through the system to encourage the patient to continue to maintain active movement information, and output encouraging and interesting game design. In each sequence of the movement trajectory of the affected upper limb muscle group, according to the evaluation data, the prime mover muscle belly and tendon are squeezed and tapped mechanical stimulation at the corresponding sequence, thereby promoting the contraction of the muscles around the joints. The verbal encouragement module is set by the system according to the game and according to the patient's active movement participation. According to the patient's participation level, different encouraging words and volumes are used to encourage the patient to continue to maintain the best state. ;

[0008] As a preferred technical solution of the present invention, the movement pattern module includes a flexion, adduction and external rotation submodule, an extension, abduction and internal rotation submodule, a flexion, abduction and external rotation submodule and an extension, adduction and internal rotation submodule. The flexion, adduction and external rotation submodule presses the upper serratus anterior muscle and the trapezius muscle of the scapula forward and downward, the upper pectoralis major, the anterior deltoid muscle, and the biceps brachii on the shoulder joint flex, adduct and externally rotate, the elbow joint is extended, the forearm is supinated, the wrist joint is flexed, the fingers are flexed and lateralized, the thumb is flexed and adducted, the extension, abduction and internal rotation submodule presses the scapula backward and downward, and the shoulder joint is extended. Abduction, abduction and internal rotation, elbow extension, forearm pronation, ulnar extension of wrist, extension and ulnar deviation of fingers, abduction and extension of thumb palm, flexion, abduction and external rotation submodule scapula posterior elevation, shoulder flexion, abduction and internal rotation, elbow extension, forearm supination, lateral extension of wrist, extension and lateral deviation of fingers, extension and abduction of thumb, extension, adduction and internal rotation submodule scapula forward and downward pressure, shoulder extension, adduction and internal rotation, elbow extension, forearm pronation, ulnar flexion of wrist, flexion and ulnar deviation of fingers, flexion and adduction of thumb palm.

[0009] As a preferred technical solution of the present invention, the muscle state assessment module includes an Athos sportswear submodule, an MC sensor submodule, a surface electromyography submodule and a muscle activity detection submodule.

[0010] As a preferred technical solution of the present invention, the manipulation force conduction module includes a flexible pressure sensor sub-module and an electronic skin tactile sensor sub-module. The electronic skin tactile receptors and flexible strain pressure sensors are installed in both hands of the bionic robot according to the patient's tactile feedback and strain pressure.

[0011] As a preferred technical solution of the present invention, the modeling DFM platform includes a structural database, a shell design module and a power design module. The various functions of each component of the structural database are stored in the database. The shell design module uses elastic tensor materials to pre-calculate the functions of many structures. For example, the directional Young's modulus represents the stiffness in the loading direction. The user selects the function parameters of the corresponding structure to automatically generate many geometrically effective structures. The user inputs motion simulation in the power design module to generate a dynamic structure.

[0012] As a preferred technical solution of the present invention, the bionic robot platform includes a three-dimensional model design module, a bionic robot module, a somatosensory interactive screen module, a background data analysis module and a therapeutic intervention controller. The three-dimensional model design module designs the bionic robot double-arm functions that meet the present invention on the three-dimensional model: the soft arm directly designs functions on the three-dimensional model, the bionic robot module has shoulder, elbow, wrist, and finger joints, and the shoulder has flexion, extension, adduction, abduction, internal rotation, and external rotation functions, the elbow joint has flexion, extension, pronation, and supination functions, the wrist joint has dorsiflexion, dorsiextension, ulnar deviation, radial deviation and rotation functions; the four finger joints have flexion and extension functions, and the thumb joint has abduction, adduction, flexion, and extension functions; and completes the compound movements of the four joint levels of the shoulder, elbow, wrist, and fingers, and calculates according to the length of the patient's upper limbs. The upper arm length is suitable for bionic robot treatment; the somatosensory interactive screen module will display the interaction situation intuitively on the large screen; the background data analysis module will enter the system based on the PNF technique of both upper limbs' motion trajectory, and install the electronic skin tactile receptors and flexible strain pressure sensors into the bionic robot's hands. According to the patient's tactile feedback and strain pressure, it will provide matching power guidance or resistance guidance for data analysis; the treatment intervention controller will detect the excitement / inhibition of the main prime movers and antagonist muscles of the patient's healthy upper limb through surface electromyography. As the normal standard, it will perform electromyography on the prime movers and antagonist muscles of the affected upper limb, and promote the excitement of the prime movers and the inhibition of the antagonist muscles according to the status presented in the motion trajectory. The excitement of the prime movers is mainly promoted through the tapping stimulation mode of the medium frequency therapeutic device at the muscle belly / tendon.

[0013] As a preferred technical solution of the present invention, the robot structure platform includes a multi-joint motion module, an artificial muscle simulation module and a human skin-mimicking module. The multi-joint motion module performs multi-joint motion and is scalable. The seat is located on the affected side of the patient. According to the patient's sitting posture and arm length, the bionic robot's dual mechanical upper limbs cooperate with the stroke patient's affected upper limb to complete the PNF upper limb flexion-adduction-external rotation mode to the flexion-abduction-external rotation mode, and the extension-abduction-internal rotation mode is converted to the extension-adduction-internal rotation mode; the dual arms of the artificial muscle simulation module are currently designed based on the skeletal muscle-tendon structure concept. Guided by this, we have developed a highly skeletal muscle-mimicking flexible actuator, called a muscle-tendon system-mimicking flexible actuator, which can imitate the contraction and expansion of human muscles. At the same time, through the bionics research on the morphology and anatomy of the human hand, we have obtained the key structural parameters of the human hand and the distribution of muscles, and designed flexible finger actuators and humanoid dexterous hands. The human skin module bionic hand has human skin-mimicking tactile receptors with high sensitivity, which can evaluate the wrist / finger movement participation of the patient's affected upper limb during active movement. It also has flexible strain sensors, which provide assistance and appropriate resistance to the affected hand through bilateral bionic manipulators.

[0014] Compared with the prior art, the beneficial effects of the present invention are: a double upper limb manipulation training and rehabilitation intelligent system guided by PNF upper limb manipulation technology, an effective assessment of the system's movement route before training, and planning of the corresponding PNF upper limb training trajectory based on the patient's functional level and seat height and posture, to perform therapist-like manipulation training. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a schematic diagram of the architecture of the training management system of the present invention;

[0016] Figure 2 Schematic diagram of the architecture of the intelligent rehabilitation platform of the present invention;

[0017] Figure 3 is a schematic diagram of the architecture of the motion mode module of the present invention;

[0018] Figure 4 It is a schematic diagram of the architecture of the DFM platform capable of modeling in the present invention;

[0019] Figure 5 This is a schematic diagram of the architecture of the bionic robot platform of the present invention;

[0020] Figure 6 is a schematic diagram of the architecture of the muscle state assessment module of the present invention;

[0021] Figure 7 It is a schematic diagram of the structure of the mana transmission module of the present invention;

[0022] Figure 8 It is a schematic diagram of the architecture of the robot structure platform of the present invention.

[0023] In the figure: 1. Training management system; 2. Intelligent rehabilitation platform; 21. Movement mode module; 211. Flexion, adduction and external rotation submodule; 212. Extension, abduction and internal rotation submodule; 213. Flexion, abduction and external rotation submodule; 214. Extension, adduction and internal rotation submodule; 22. Muscle state assessment module; 221. Athos sportswear submodule; 222. MC sensor submodule; 223. Surface electromyography submodule; 224. Muscle activity detection submodule; 23. Hand force transmission module; 231. Flexible pressure sensor submodule; 232. Electronic skin Tactile sensor submodule; 24. Evaluation and integration module; 25. Treatment module; 26. Verbal encouragement module; 3. Modeling DFM platform; 31. Structural database; 32. Shell design module; 33. Power design module; 4. Bionic robot platform; 41. Three-dimensional model design module; 42. Bionic robot module; 43. Somatosensory interactive screen module; 44. Background data analysis module; 45. Treatment intervention controller; 5. Robot structure platform; 51. Multi-joint motion module; 52. Artificial muscle simulation module; 53. Human skin simulation module. DETAILED DESCRIPTION

[0024] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1-8The present invention provides a double upper limb rehabilitation training management system, including a training management system 1, the training management system 1 includes an intelligent rehabilitation platform 2, a modeling DFM platform 3, a bionic robot platform 4 and a robot structure platform 5, the intelligent rehabilitation platform 2 includes a movement pattern module 21, a muscle state evaluation module 22, a manipulation force conduction module 23, an evaluation integration module 24, a treatment module 25 and a verbal encouragement module 26, the movement pattern module 21 evaluates the movement trajectory--the movement pattern activity based on the spiral / diagonal form of the PNF upper limb, the muscle state evaluation module 22 evaluates the movement trajectory of the patient's healthy hand after the bionic robot double mechanical upper limb is grasped using the PNF manipulation, and when the patient's healthy hand moves according to the original PNF movement trajectory in the system, the contraction of the normal corresponding prime mover muscle group, the inhibition of the antagonist, and the duration of muscle contraction maintenance and relaxation maintenance are detected according to the changes in the three joint angles of the shoulder, elbow and wrist joints of the upper limb, and the normal muscle state is planned by the system as a normal standard, and then the therapist uses the PNF upper limb technology to guide the patient's affected upper limb to move under the seat, and the affected upper limb is based on the changes in the three joint angles of the shoulder, elbow and wrist joints of the upper limb. , detect the contraction of the corresponding prime mover muscle group, the inhibition of the antagonist, and the duration of muscle contraction and relaxation. The system evaluates the muscle status level before treatment as the baseline level. Its technical implementation: Athos sportswear, MC sensor, surface electromyography, Finnish Mbody3 muscle activity detection and comprehensive human analysis technology support for sports performance, manual force conduction module 23. When the therapist uses PNF upper limb manipulation to guide the healthy upper limb of the stroke patient to perform diagonal spiral movement, the therapist senses the patient's active movement and force conduction through the tactile receptors on the skin, and gives appropriate resistance or assistance guidance according to the patient's active feedback, taking the stress feedback of the patient's healthy side as the normal standard, taking the assistance given to the patient by the therapist through touch as the minimum intensity during treatment, and taking the resistance as the maximum intensity during treatment; when the PNF upper limb manipulation is used to guide the stroke patient's affected upper limb to perform diagonal spiral movement, the therapist senses the patient's active movement and force conduction through the tactile receptors, and gives appropriate resistance or assistance guidance according to the patient's active feedback, and taking the stress feedback of the patient's affected side as the baseline level;Flexible pressure sensors and electronic skin tactile sensor technology support, the evaluation integration module 24 takes the motion trajectory of the stroke patient's normal upper limb in the bionic robot technique, as well as the activation, contraction, relaxation, and continuous muscle function status of each prime mover and antagonist muscle group in each time sequence of the movement, and the patient's active feedback as the normal standard after systematic analysis, and takes the motion trajectory of the stroke patient's affected upper limb in the bionic robot technique, as well as the activation, contraction, relaxation, and continuous muscle function status of each prime mover / antagonist muscle group in each time sequence of the movement, and the patient's active feedback as the baseline after systematic analysis, thus conducting advanced training design based on the patient's range of motion of each joint involved in the motion trajectory, the level of participation of each muscle group, and the degree of participation in active movement, the treatment module 25 motion trajectory The output of the trajectory should avoid repetitiveness and dullness, and jointly predict the joints and muscles affected by the next movement trajectory. Combined with the bionic robot receiving flexible pressure information, it is targeted, easy to understand, simple, and the patient's slow and weak active participation is amplified by the system to encourage the patient to continue to maintain active movement information, and output encouraging and interesting game design. In each time sequence of the movement trajectory of the affected upper limb muscle group, according to the evaluation data, the prime mover muscle belly and tendon are squeezed and tapped mechanical stimulation at the corresponding time sequence, thereby promoting the contraction of the muscles around the joints. The verbal encouragement module 26 is set by the system according to the game and according to the patient's active movement participation, according to the patient's participation level, through different encouraging words and volumes to encourage the patient to continue to maintain the best state. ;

[0026] The movement pattern module 21 includes a flexion, adduction and external rotation submodule 211, an extension, abduction and internal rotation submodule 212, a flexion, abduction and external rotation submodule 213 and an extension, adduction and internal rotation submodule 214. The flexion, adduction and external rotation submodule 211 presses the upper serratus anterior and trapezius muscles of the scapula forward and downward, flexes, adducts and externally rotates the upper pectoralis major, the anterior deltoid muscle and the biceps brachii on the shoulder joint, extends the elbow joint, supinates the forearm, flexes the wrist joint laterally, flexes and deviates the fingers, flexes and adducts the thumb, and the extension, abduction and internal rotation submodule 212 presses the scapula backward and downward, and extends the shoulder joint. , abduction and internal rotation, elbow extension, forearm pronation, ulnar extension of wrist, finger extension, ulnar deviation, abduction and extension of thumb palm, flexion, abduction and external rotation submodule 213 scapula is lifted up and down, shoulder flexion, abduction and internal rotation, elbow extension, forearm supination, wrist lateral extension, finger extension and lateral deviation, thumb extension and abduction, extension, adduction and internal rotation submodule 214 scapula is pressed forward and downward, shoulder extension, adduction and internal rotation, elbow extension, forearm pronation, ulnar flexion of wrist, finger flexion and ulnar deviation, thumb flexion and adduction.

[0027] The muscle state assessment module 22 includes an Athos sportswear submodule 221 , an MC sensor submodule 222 , a surface electromyography submodule 223 and a muscle activity detection submodule 224 .

[0028] The hand force transmission module 23 includes a flexible pressure sensor submodule 231 and an electronic skin tactile sensor submodule 232. The electronic skin tactile receptors and flexible strain pressure sensors are installed in both hands of the bionic robot according to the patient's tactile feedback and strain pressure.

[0029] The modeling DFM platform includes a structural database 31, a shell design module 32 and a power design module 33. The various functions of each component of the structural database 31 are stored in the database. The shell design module 32 uses elastic tensor materials to pre-calculate the functions of many structures. For example, the directional Young's modulus represents the stiffness in the loading direction. The user selects the function parameters of the corresponding structure to automatically generate many geometrically effective structures. The user inputs motion simulation in the power design module 33 to generate a dynamic structure.

[0030] The bionic robot platform 4 includes a three-dimensional model design module 41, a bionic robot module 42, a somatosensory interactive screen module 43, a background data analysis module 44 and a treatment intervention controller 45. The three-dimensional model design module 41 designs the bionic robot double-arm functions that meet the present invention on the three-dimensional model: the soft arm directly designs functions on the three-dimensional model, the bionic robot module 42 has shoulder, elbow, wrist, and finger joints, and the shoulder has flexion, extension, adduction, abduction, internal rotation, and external rotation functions; the elbow joint has flexion, extension, pronation, and supination functions; the wrist joint has dorsiflexion, dorsiextension, ulnar deviation, radial deviation and rotation functions; the four finger joints have flexion and extension functions, and the thumb joint has abduction, adduction, flexion, and extension functions; and completes the compound movements of the four joint levels of the shoulder, elbow, wrist, and fingers, and calculates the bionic functions according to the length of the patient's upper limbs. Appropriate upper arm length during robot treatment; the somatosensory interactive screen module 43 displays the interaction situation intuitively on the large screen; the background data analysis module 44 enters the motion trajectory of both upper limbs based on the PNF technique into the system, and installs the electronic skin tactile receptors and flexible strain pressure sensors into the hands of the bionic robot, and gives matching power guidance or resistance guidance for data analysis according to the patient's tactile feedback and strain pressure; the treatment intervention controller 45 detects the excitement / inhibition of the main prime movers and antagonist muscles of the patient's healthy upper limb through surface electromyography, and performs electromyography detection on the prime movers and antagonist muscles of the affected upper limb as the normal standard, and promotes the excitement of the prime movers and the inhibition of the antagonist muscles according to the status presented in the motion trajectory. The excitement of the prime movers is mainly promoted through the tapping stimulation mode of the medium frequency therapeutic device at the muscle belly / tendon.

[0031] The robot structure platform 5 includes a multi-joint motion module 51, an artificial muscle simulation module 52 and a human skin simulation module 53. The multi-joint motion module 51 performs multi-joint motion and is retractable. The seat is located on the affected side of the patient. According to the patient's sitting posture and arm length, the bionic robot's dual mechanical upper limbs cooperate with the stroke patient's affected upper limb to complete the PNF upper limb flexion-adduction-external rotation mode to flexion-abduction-external rotation mode, and the extension-abduction-internal rotation mode is converted to extension-adduction-internal rotation mode; the artificial muscle simulation module 52 arms are currently designed based on the skeletal muscle-tendon structure concept. The highly skeletal muscle-mimicking flexible actuator developed is called the muscle-tendon system flexible actuator, and has the ability to imitate the contraction and expansion of human muscles. At the same time, through the bionics research on the morphology and anatomy of the human hand, the key structural parameters of the human hand and the distribution of muscles are obtained, and flexible finger actuators and humanoid dexterous hands are designed; the human skin module 53 bionic hand has human skin-mimicking tactile receptors with high sensitivity, which can evaluate the wrist / finger movement participation of the patient's affected upper limb during active movement. At the same time, it has a flexible strain sensor, which provides assistance and appropriate resistance to the affected hand through the bilateral bionic manipulator.

[0032] In the present invention, the multi-joint motion module 51 performs multi-joint motion and scalability, and the seat is located on the affected side of the patient. According to the patient's sitting posture and arm length, the bionic robot's dual mechanical upper limbs cooperate with the stroke patient's affected upper limb to complete the PNF upper limb flexion-adduction-external rotation mode to the flexion-abduction-external rotation mode, and the extension-abduction-internal rotation mode is converted to the extension-adduction-internal rotation mode; the artificial muscle simulation module 52 arms currently adopt a highly skeletal muscle-like flexible driver developed with the skeletal muscle-tendon structure concept as the design guide, called a muscle-tendon system flexible driver, and has the function of imitating the contraction and expansion of human muscles, and at the same time, by adjusting the shape of the human hand The bionics research on morphology and anatomy obtains the key structural parameters of the human hand and the distribution of muscles, designs flexible finger actuators and humanoid dexterous hands; the bionic hand of the human skin module 53 has tactile receptors that imitate human skin and has high sensitivity. It evaluates the wrist / finger movement participation when the patient's affected upper limb actively moves. It also has flexible strain sensors, which provide assistance and appropriate resistance to the affected hand through bilateral bionic manipulators. For the computational design method of advanced functional products, direct functional modeling (DFM) has been developed, a new design technology and an advanced manufacturing process. By using DFM, designers design functions directly on the three-dimensional model, so each component Various functions are embedded in the final product, and the product can be popped up without assembly. In addition, the structural database 31 for direct functional modeling uses methods such as elastic modulus to pre-calculate the functions of many structures. The user selects the function parameters of the corresponding structure, and the algorithm will automatically generate many topological and geometrically valid structures. In the design of the shell, a large number of structures and functions are collected and stored; for effective dynamic design, DFM not only provides a design method for lightweight structures, but also a dynamic design method. The user inputs motion simulation, and DFM uses them to generate functional structures. It also designs kinematic tactile applications and many elastic applications based on the original product. Based on the design, the functions of the bionic robot's two arms that meet the present invention are designed on the three-dimensional model: when the soft arm is directly designed on the three-dimensional model, it must have shoulder, elbow, wrist, and finger joints, and the shoulder has the functions of flexion, extension, adduction, abduction, internal rotation, and external rotation; the elbow joint has the functions of flexion, extension, pronation, and supination; the wrist joint has the functions of dorsiflexion, dorsiextension, ulnar deviation, radial deviation, and rotation; the four finger joints have the functions of flexion and extension, and the thumb joint has the functions of abduction, adduction, flexion, and extension; and the compound movements at the four joint levels of the shoulder, elbow, wrist, and finger are completed, and according to the length of the patient's upper limbs, the appropriate upper arm length for bionic robot treatment is calculated;Based on effective power settings, the PNF technique-based upper limb motion trajectory is recorded into the system, and the electronic skin tactile receptors and flexible strain pressure sensors are installed in the bionic robot hands. According to the patient's tactile feedback and strain pressure, matching power guidance or resistance guidance is given. The excitement and inhibition of the main prime movers and antagonist muscles of the patient's healthy upper limb are detected by surface electromyography. As a normal standard, the prime movers and antagonist muscles of the affected upper limb are tested for electromyography, and the prime movers and antagonists are promoted according to the state presented in the motion trajectory. The excitement of the prime movers is mainly promoted by the tapping stimulation mode in the medium frequency therapeutic instrument on the muscle belly and tendon. ;

[0033] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A double upper limb rehabilitation training management system, comprising a training management system (1), characterized in that: The training management system (1) comprises an intelligent rehabilitation platform (2), a modeling DFM platform (3), a bionic robot platform (4) and a robot structure platform (5), and the intelligent rehabilitation platform (2) comprises a movement pattern module (21), a muscle state assessment module (22), a manual force transmission module (23), an assessment integration module (24), a treatment module (25) and a verbal encouragement module (26).

2. The upper limb rehabilitation training management system according to claim 1, characterized in that: The movement pattern module (21) comprises a flexion, adduction and external rotation submodule (211), an extension, abduction and internal rotation submodule (212), a flexion, abduction and external rotation submodule (213) and an extension, adduction and internal rotation submodule (214).

3. The upper limb rehabilitation training management system according to claim 1, characterized in that: The muscle state assessment module (22) comprises an Athos sportswear submodule (221), an MC sensor submodule (222), a surface electromyography submodule (223) and a muscle activity detection submodule (224).

4. The upper limb rehabilitation training management system according to claim 1, characterized in that: The hand force transmission module (23) comprises a flexible pressure sensor submodule (231) and an electronic skin tactile sensor submodule (232).

5. The upper limb rehabilitation training management system according to claim 1, characterized in that: The modeling DFM platform (3) includes a structure database (31), a shell design module (32) and a power design module (33).

6. The upper limb rehabilitation training management system according to claim 1, characterized in that: The bionic robot platform (4) comprises a three-dimensional model design module (41), a bionic robot module (42), a body sensing interactive screen module (43), a background data analysis module (44) and a treatment intervention controller (45).

7. The upper limb rehabilitation training management system according to claim 1, characterized in that: The robot structure platform (5) comprises a multi-joint motion module (51), an artificial muscle simulation module (52) and a human skin simulation module (53).

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