Hybrid drive lower limb rehabilitation training system and control method thereof

Abstract

The present disclosure provides a hybrid-driven lower limb rehabilitation training system and a control method thereof. The method includes: determining a target interaction force factor based on the human-machine interaction force between the target training part and the exoskeleton robot; determining a target muscle fatigue factor based on the electromyographic signal of the target training part; determining a stimulation ratio based on the target interaction force factor and the target muscle fatigue factor, wherein the stimulation ratio is characterized as the ratio of the target stimulation output torque of the electrical stimulation module in the target training torque; determining a target motor output torque of the motor module and a target electrical stimulation signal of the electrical stimulation module based on the stimulation ratio; and controlling the motor module and the electrical stimulation module to drive the target training part to move based on the target motor output torque and the target electrical stimulation signal, so that the target training part is at the target training torque. The hybrid-driven lower limb rehabilitation training system includes an exoskeleton robot, a motor module, an electrical stimulation module, and a control unit.

Description

Technical Field

[0001] The present disclosure relates to the field of exoskeleton robot rehabilitation, and in particular to a control method for a hybrid-driven lower limb rehabilitation training system and a hybrid-driven lower limb rehabilitation training system. Background Art

[0002] The lower limb rehabilitation training system assists the rehabilitation therapist and the patient in lower limb rehabilitation training through exoskeleton robots and functional electrical stimulation. The exoskeleton robot can provide effective external support for the patient, assist the patient's limb training, and improve the rehabilitation training effect. At the same time, functional electrical stimulation is used to stimulate the patient's skeletal muscles to contract through low-frequency weak current pulses, thereby generating the desired movement and performing active rehabilitation.

[0003] However, when rehabilitation therapists or patients use the lower limb rehabilitation training system based on functional electrical stimulation and motor hybrid drive for rehabilitation training, there are problems such as insufficient system control accuracy and easy to cause muscle fatigue. Summary of the invention

[0004] In order to at least partially overcome the technical defects of at least one or other inventions mentioned above, at least one embodiment of the present disclosure provides a control method for a hybrid-driven lower limb rehabilitation training system and a hybrid-driven lower limb rehabilitation training system, which can improve the rehabilitation training effect of patients.

[0005] In view of this, an embodiment of the present disclosure provides a control method for a hybrid-driven lower limb rehabilitation training system, the hybrid-driven lower limb rehabilitation training system comprising an exoskeleton robot, a motor module and an electrical stimulation module, characterized in that the method comprises: determining a target interaction force factor based on a human-machine interaction force between a target training part and the exoskeleton robot, wherein the human-machine interaction force is generated when the motor module drives the exoskeleton robot to drive the target training part to move; determining a target muscle fatigue factor based on an electromyographic signal of the target training part; determining a stimulation ratio based on the target interaction force factor and the target muscle fatigue factor, wherein the stimulation ratio is characterized by the ratio of the target stimulation output torque of the electrical stimulation module in the target training torque; determining a target motor output torque of the motor module and a target electrical stimulation signal of the electrical stimulation module based on the stimulation ratio; and controlling the motor module and the electrical stimulation module to drive the target training part to move based on the target motor output torque and the target electrical stimulation signal, so that the target training part is at the target training torque.

[0006] Optionally, determining the target interaction force factor based on the human-computer interaction force of the target training part includes: when the human-computer interaction force is greater than the interaction force threshold, determining the target interaction force factor based on the sum of the numerical value of the current interaction force factor and a first preset value; when the human-computer interaction force is less than or equal to the interaction force threshold, determining the current interaction force factor as the target interaction force factor.

[0007] Optionally, the determination of the target muscle fatigue factor based on the electromyographic signal of the target training part includes: obtaining the average median frequency of the electromyographic signal at the current moment, wherein the average median frequency represents the average value of multiple median frequencies, and the multiple median frequencies include the median frequency of the electromyographic signal at the current moment and the median frequencies of the electromyographic signals at multiple historical moments before the current moment; when the average median frequency is less than the current first baseline value, determining the current muscle fatigue factor as the target muscle fatigue factor; when the average median frequency is greater than the current first baseline value, setting the current The median frequency at the moment is the target first baseline value; when the average median frequency is less than the target first baseline value, and the ratio of the absolute value of the difference between the average median frequency and the target first baseline value to the target first baseline value is greater than the second baseline value, the target muscle fatigue factor is obtained based on the sum of the value of the current muscle fatigue factor and the second preset value; when the average median frequency is less than the target first baseline value, and the ratio of the absolute value of the difference between the average median frequency and the target first baseline value to the target first baseline value is less than or equal to the second baseline value, the current muscle fatigue factor is determined to be the target muscle fatigue factor.

[0008] Optionally, determining the stimulation proportion based on the target interaction force factor and the target muscle fatigue factor includes: acquiring a training factor based on the target interaction force factor and the target muscle fatigue factor; and determining the stimulation proportion based on a mapping relationship and the training factor.

[0009] Optionally, determining the target motor output torque of the motor module based on the stimulation ratio includes: determining the target stimulation output torque of the electrical stimulation module based on the stimulation ratio and the target training torque; determining the target motor output torque based on the target stimulation output torque and the target training torque.

[0010] Optionally, determining the target electrical stimulation signal based on the stimulation ratio includes: determining the muscle activation degree of the target training part based on the target stimulation output torque and the joint angle of the target training part; and determining the target electrical stimulation signal based on the muscle activation degree.

[0011] The disclosed embodiment also provides a hybrid-driven lower limb rehabilitation training system, comprising: an exoskeleton robot, configured to support a patient to be trained; a motor module, connected to the exoskeleton robot, the motor module being configured to drive the exoskeleton robot to move, so as to drive the target training part of the patient to move; an electrical stimulation module, disposed on the exoskeleton robot, the electrical stimulation module being configured to electrically stimulate the muscles of the target training part to drive the target training part to move; a control unit, connected to the motor module and the electrical stimulation module, the control unit being configured to use the above-mentioned method to respectively control the motor module and the electrical stimulation module to drive the target training part to move, so that the target training part is at the target training torque.

[0012] Optionally, the exoskeleton robot includes a thigh structure, a calf structure, an ankle structure and connecting joints, and the control unit includes: a feedback subunit connected to the ankle structure, the feedback subunit is configured to obtain motion information of the ankle structure, and the control unit obtains the patient's gait phase information based on the motion information.

[0013] Optionally, the motor module includes: a force sensor, which is arranged at the target training part, and the force sensor is configured to obtain the human-machine interaction force between the target training part and the exoskeleton robot.

[0014] Optionally, the hybrid-drive lower limb rehabilitation training system also includes: a balance measurement module, which is arranged on the exoskeleton robot, and the balance measurement module is configured to detect the posture of the exoskeleton robot; a locking device, which is arranged on the exoskeleton robot, and when the inclination angle of the exoskeleton robot exceeds an angle threshold, the control unit controls the locking device to perform a locking operation.

[0015] According to the embodiment of the present disclosure, the target interaction force factor and the target muscle fatigue factor can be determined by obtaining the current human-machine interaction force and electromyographic signal, and the proportion of the target stimulation output torque in the target training torque can be adjusted based on the target interaction force factor and the target muscle fatigue factor. Thus, the target motor output torque of the motor module and the target electrical stimulation signal of the electrical stimulation module can be controlled while meeting the target training torque, which can adapt to the motor abilities of different patients, alleviate muscle fatigue caused by continuous electrical stimulation, and thus improve the rehabilitation training effect of patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 An exemplary system architecture that can be applied to a control method for a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0017] Figure 2A flow chart of a control method for a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0018] Figure 3 A block diagram of a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0019] Figure 4 A front view of a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0020] Figure 5 A side view of a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0021] Figure 6 A block diagram of an electronic device for a control method of a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0022] In the above drawings, the meanings of the reference numerals are as follows:

[0023] 300. Hybrid drive lower limb rehabilitation training system;

[0024] 310. Exoskeleton robot;

[0025] 311. Thigh structure;

[0026] 312. Calf structure;

[0027] 313. Foot and ankle structure;

[0028] 314, connecting joints;

[0029] 315. Waist structure;

[0030] 3151, slide rail;

[0031] 3152, driving device;

[0032] 316. Hip structure;

[0033] 3161, L-shaped plate;

[0034] 317. Leg length adjustment device;

[0035] 320, motor module;

[0036] 330, electrical stimulation module;

[0037] 340. Control Unit

[0038] 350. Locking device. DETAILED DESCRIPTION

[0039] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0040] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0041] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0042] In the case of using expressions such as "at least one of A, B, and C, etc.", it should generally be interpreted in accordance with the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.). In the case of using expressions such as "at least one of A, B, or C, etc.", it should generally be interpreted in accordance with the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B, or C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0043] Figure 1 An exemplary system architecture that can be applied to a control method for a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0044] It should be noted that Figure 1The examples shown are only examples of system architectures to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but do not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios. For example, in another embodiment, an exemplary system architecture that can be applied to a control method for a hybrid-driven lower limb rehabilitation training system may include a terminal device, but the terminal device may not need to interact with a server to implement the control method for a hybrid-driven lower limb rehabilitation training system provided by the embodiments of the present disclosure.

[0045] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a hybrid-driven lower limb rehabilitation training system 101, a terminal device 102, a network 103, and a server 104. The network 103 is used to provide a medium for a communication link between the hybrid-driven lower limb rehabilitation training system 101, the terminal device 102, and the server 104. The network 103 may include various connection types, such as wired and / or wireless communication links, etc.

[0046] The user can use the hybrid drive lower limb rehabilitation training system 101 and the terminal device 102 to interact with the server 104 through the network 103 to receive or send messages, etc. The hybrid drive lower limb rehabilitation training system 101 can be a device for driving the patient to move, etc. (only for example). Various communication client applications can be installed on the terminal device 102, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients and / or social platform software, etc. (only for example).

[0047] The terminal device 102 may be any electronic device having a display screen and supporting web browsing, including but not limited to a television, a tablet computer, a laptop computer, a desktop computer, and the like.

[0048] Server 104 can be any type of server that provides various services. For example, server 104 can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services (Virtual Private Server). Server 104 can also be a server of a distributed system, or a server combined with a blockchain.

[0049] It should be noted that the control method for the hybrid-driven lower limb rehabilitation training system provided in the embodiment of the present disclosure can generally be executed by the hybrid-driven lower limb rehabilitation training system 101 or the terminal device 102 .

[0050] Alternatively, the control method for the hybrid drive lower limb rehabilitation training system provided in the embodiment of the present disclosure may also be generally executed by the server 104. The control method for the hybrid drive lower limb rehabilitation training system provided in the embodiment of the present disclosure may also be executed by a server or server cluster that is different from the server 104 and can communicate with the hybrid drive lower limb rehabilitation training system 101, the terminal device 102 and / or the server 104. It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of image acquisition devices, terminal devices, networks and servers may be provided according to the implementation requirements.

[0051] It should be noted that the sequence numbers of the operations in the following method are only used as representations of the operations for the purpose of description, and should not be regarded as representing the execution order of the operations. Unless explicitly stated, the method does not need to be executed completely in the order shown.

[0052] Figure 2 A flow chart of a control method for a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0053] like Figure 2 As shown, an embodiment of the present disclosure provides a control method for a hybrid drive lower limb rehabilitation training system. The hybrid drive lower limb rehabilitation training system includes an exoskeleton robot, a motor module and an electrical stimulation module. The method 200 includes performing operations S210 to S250.

[0054] In operation S210, a target interaction force factor is determined based on the human-machine interaction force between the target training part and the exoskeleton robot.

[0055] In operation S220, a target muscle fatigue factor is determined based on the myoelectric signal of the target training part.

[0056] In operation S230 , a stimulation ratio is determined based on the target interaction force factor and the target muscle fatigue factor.

[0057] In operation S240 , a target motor output torque of the motor module and a target electrical stimulation signal of the electrical stimulation module are determined based on the stimulation ratio.

[0058] In operation S250, the motor module and the electrical stimulation module are respectively controlled to drive the target training part to move based on the target motor output torque and the target electrical stimulation signal, so that the target training part is at the target training torque.

[0059] According to the disclosed embodiment, the human-machine interaction force can be generated when the motor module drives the exoskeleton robot to drive the target training part to move, that is, the force exerted by the exoskeleton robot on the target training part. The target training part can be the patient's left thigh, left calf, right thigh, right calf or hip joint, and the training part can be a single part or multiple parts.

[0060] According to the embodiment of the present disclosure, the myoelectric signal may be a physiological electrical signal generated by the muscles of the target training part when the electrical stimulation module electrically stimulates the target training part to move. The electrical stimulation module may drive the target training part to move by electrically stimulating the muscles of the target training part.

[0061] According to an embodiment of the present disclosure, the muscles of the target training site may include the tibialis anterior, gastrocnemius, biceps femoris and quadriceps femoris of the ankle joint.

[0062] Furthermore, when the patient is controlled to enter the swing phase, only the anterior tibialis muscle of the ankle joint is activated; when the patient is controlled to enter the stance phase, only the gastrocnemius muscle is activated; when the patient is controlled to enter the swing phase, only the biceps femoris is activated; when the patient is controlled to enter the end of the swing phase and the middle of the stance phase, only the quadriceps femoris is activated. This activation method can stimulate the muscles more accurately, avoid the muscles being in an activated state all the time, thereby reducing muscle fatigue, and avoid unnecessary electrical stimulation from interfering with the lower limb movement, causing deviations between the actual movement trajectory and the planned movement trajectory line.

[0063] According to the disclosed embodiment, the rehabilitation therapist can plan the motion trajectory of the target part according to the patient's physical condition. The torque trajectory can be fitted based on the motion trajectory. The target training torque can be characterized as the torque corresponding to a certain moment in the torque trajectory.

[0064] According to an embodiment of the present disclosure, the stimulation ratio may be characterized as the ratio of the target stimulation output torque of the electrical stimulation module to the target training torque.

[0065] According to the embodiment of the present disclosure, during the functional electrical stimulation process, that is, when the electrical stimulation module is used to stimulate the movement of the target training part with a target electrical stimulation signal, the movement torque of the target training part can reach the target stimulation output torque.

[0066] According to the embodiment of the present disclosure, during the motor driving process, that is, when the motor module is used to drive the target training part to move with the target motor output torque, the movement torque of the target training part can reach the target motor output torque.

[0067] According to an embodiment of the present disclosure, the target training torque may include a target stimulation output torque and a target motor output torque. The target interaction force factor and the target muscle fatigue factor can be determined by obtaining the current human-computer interaction force and electromyographic signal, and the proportion of the target stimulation output torque in the target training torque can be adjusted based on the target interaction force factor and the target muscle fatigue factor. That is, functional electrical stimulation and motor drive can be organically integrated to optimize the human-computer interaction loop, realize hybrid complementary control, promote the recovery of limb motor function and somatic sensory function, and improve the level of limb function rehabilitation.

[0068] According to the embodiments of the present disclosure, the motion information of the target training part can be recorded in real time to adjust the target motor output torque and the target electrical stimulation signal, and a multi-dimensional quantitative gait assessment can be performed based on the real-time recorded motion information to provide a reference for the patient's subsequent rehabilitation training.

[0069] According to the embodiment of the present disclosure, the target interaction force factor and the target muscle fatigue factor can be determined by obtaining the current human-machine interaction force and electromyographic signal, and the proportion of the target stimulation output torque in the target training torque can be adjusted based on the target interaction force factor and the target muscle fatigue factor. Thus, the target motor output torque of the motor module and the target electrical stimulation signal of the electrical stimulation module can be controlled while meeting the target training torque, which can adapt to the motor abilities of different patients, alleviate muscle fatigue caused by continuous electrical stimulation, and thus improve the rehabilitation training effect of patients.

[0070] In some embodiments, based on the human-computer interaction force of the target training part, determining the target interaction force factor includes: when the human-computer interaction force is greater than the interaction force threshold, obtaining the target interaction force factor based on the sum of the value of the current interaction force factor and the third preset value. When the human-computer interaction force is less than or equal to the interaction force threshold, determining the current interaction force factor as the target interaction force factor.

[0071] According to an embodiment of the present disclosure, the interaction force threshold and the first preset value can be set by a rehabilitation therapist or a patient according to the patient's physical condition. When it is detected that the human-computer interaction force is greater than the interaction force threshold, the target interaction force factor can be determined as the sum of the current interaction force factor and the first preset value. That is, the target interaction force factor can be a value updated in real time. The target interaction force factor at the current moment can be the current interaction force factor at the next moment. The initial value of the current interaction force factor can be zero. The first preset value can be 0.1. The interaction force threshold can be a variable value, which can be updated according to the patient's motion state. The target interaction force factor can be the current interaction force factor at the next moment.

[0072] In some embodiments, based on the electromyographic signal of the target training part, determining the target muscle fatigue factor includes: obtaining the average median frequency of the electromyographic signal at the current moment. The average median frequency can represent the average value of multiple median frequencies. The multiple median frequencies can include the median frequency of the electromyographic signal at the current moment and the median frequencies of the electromyographic signals at multiple historical moments before the current moment.

[0073] In the case where the average median frequency is less than the current first baseline value, the current muscle fatigue factor is determined to be the target muscle fatigue factor. In the case where the average median frequency is greater than the current first baseline value, the median frequency at the current moment is set as the target first baseline value. In the case where the average median frequency is less than the target first baseline value, and the ratio of the absolute value of the difference between the average median frequency and the target first baseline value to the target first baseline value is greater than the second baseline value, the target muscle fatigue factor is obtained based on the sum of the value of the current muscle fatigue factor and the second preset value. In the case where the average median frequency is less than the target first baseline value, and the ratio of the absolute value of the difference between the average median frequency and the target first baseline value to the target first baseline value is greater than the second baseline value, the target muscle fatigue factor is the sum of the value of the current muscle fatigue factor and the second preset value. In the case where the average median frequency is less than the target first baseline value, and the ratio of the absolute value of the difference between the average median frequency and the target first baseline value to the target first baseline value is less than or equal to the second baseline value, the current muscle fatigue factor is determined to be the target muscle fatigue factor.

[0074] The current first baseline value may be a changing value. The target first baseline value at the current moment may be the current first baseline value at the next moment. The initial value of the current first baseline value and the initial value of the second baseline value may be set by a doctor or a patient according to the patient's physical condition. The second baseline value may be 0.05. The target muscle fatigue factor may be a value updated in real time. The target muscle fatigue factor at the current moment may be the current muscle fatigue factor at the next moment. The initial value of the current muscle fatigue factor may be zero.

[0075] According to the embodiment of the present disclosure, the median frequency can characterize the patient's muscle fatigue level, and the median frequency MF can be expressed as the following formula (1).

[0076]

[0077] Where, M = 1024, P j is the amplitude of the frequency spectrum. By acquiring multiple segments of the patient's electromyographic signals, the frequency curve of the electromyographic signals can be obtained, and the amplitude of the frequency curve can be represented as the amplitude of the frequency spectrum.

[0078] According to the embodiment of the present disclosure, by setting the electromyographic signal sliding window, obtaining the median frequency of the preset length, calculating the average value of the median frequency of the preset length, when the average value is greater than the current first baseline, the average value can be the current first baseline value, that is, the updated first baseline value. For example, a 1000ms electromyographic signal sliding window is set, the overlap width can be 0ms, and after obtaining 5 median frequencies, the average value of the 5 median frequencies is calculated. When the average value is greater than the current first baseline, the average value can be the current first baseline value.

[0079] In some embodiments, determining the stimulation ratio based on the target interaction force factor and the target muscle fatigue factor includes: acquiring a training factor based on the target interaction force factor and the target muscle fatigue factor, and determining the stimulation ratio based on the mapping relationship and the training factor.

[0080] According to the embodiment of the present disclosure, the sum of the target interaction force factor and the target muscle fatigue factor can be expressed as a training factor. The mapping relationship between the training factor and the stimulation ratio can be shown as formula (2).

[0081]

[0082] Among them, a can be expressed as the stimulus ratio. F It can be expressed as the target interaction factor. Q M It can be expressed as a target muscle fatigue factor.

[0083] In some embodiments, determining the target motor output torque of the motor module based on the stimulation ratio includes: determining the target stimulation output torque of the electrical stimulation module based on the stimulation ratio and the target training torque. Determining the target motor output torque based on the target stimulation output torque and the target training torque.

[0084] According to the embodiment of the present disclosure, the stimulation ratio and the target stimulation output torque may be in direct proportion to each other. The relationship between the stimulation ratio and the target stimulation output torque may be as shown in formula (3).

[0085] τ FES =aτ (3).

[0086] Among them, τ FES It can be expressed as the target stimulation output torque. τ can be expressed as the target training torque. a can be expressed as the stimulation ratio.

[0087] According to the embodiment of the present disclosure, the target stimulation output torque and the target motor output torque may be inversely proportional to each other. The relationship between the target stimulation output torque and the target motor output torque may be as shown in formula (4).

[0088] τ motor =(1-a)τ=τ-τ FES(4).

[0089] Among them, τ FES It can be expressed as the target stimulation output torque. τ can be expressed as the target training torque. a can be expressed as the stimulation ratio. τ motor It can be expressed as the target motor output torque.

[0090] According to the embodiment of the present disclosure, at the initial moment, Q F =Q M =0, a=0.5.

[0091] In some embodiments, determining the target electrical stimulation signal based on the stimulation ratio includes: determining the muscle activation degree of the target training part based on the target stimulation output torque and the joint angle of the target training part. Determining the target electrical stimulation signal based on the muscle activation degree.

[0092] According to the embodiment of the present disclosure, the degree of muscle activation and the target stimulation output torque may be proportional. Further, the relationship between the degree of muscle activation, the target stimulation output torque and the joint angle may be as shown in formula (5).

[0093] τ FES =Q M ·(c 2 θ 2 +c 1 θ+c 0 )·I (5).

[0094] Among them, τ FES It can be expressed as the target stimulus output torque. Q M It can be expressed as the target muscle fatigue factor. θ can represent the angle of the corresponding joint in the patient's target training part. 0 、c 1 、c 2 is a constant that can be measured and adjusted according to the joint position and the patient's physical condition. 0 =64, c 1 =17, c 2 = -33. I can be expressed as the degree of muscle activation, and the range of I is [0,1]. Different electrical stimulation signals correspond to different degrees of muscle activation, that is, there is a one-to-one correspondence between the electrical stimulation signal and the degree of muscle activation. The correspondence between the electrical stimulation signal and the degree of muscle activation can be obtained from previously recorded data.

[0095] Figure 3 A block diagram of a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown.

[0096] like Figure 3As shown, the embodiment of the present disclosure provides a hybrid drive lower limb rehabilitation training system. The hybrid drive lower limb rehabilitation training system 300 includes an exoskeleton robot 310, a motor module 320, an electrical stimulation module 330 and a control unit 340. The exoskeleton robot can be used to support the patient to be trained. The motor module is connected to the exoskeleton robot, and the motor module can be used to drive the exoskeleton robot to move, so as to drive the target training part of the patient to move. The electrical stimulation module is arranged on the exoskeleton robot, and the electrical stimulation module can be used to electrically stimulate the muscles of the target training part to drive the target training part to move. The control unit is connected to the motor module and the electrical stimulation module, and the control unit can be used to control the motor module and the electrical stimulation module to drive the target training part to move respectively using the above method, so that the target training part is at the target training torque. The control unit can have a hybrid control calculation function to process the multi-modal signals it receives, and can control the motor module and the electrical stimulation module more stably. Specifically, the control unit can adopt distributed control logic, and a microprocessor can be used to alleviate the calculation and operation load of the control unit.

[0097] Figure 4 A front view of an exoskeleton robot according to an embodiment of the present disclosure is schematically shown. Figure 5 A side view of an exoskeleton robot according to an embodiment of the present disclosure is schematically shown.

[0098] like Figure 4 and Figure 5As shown, in some embodiments, the exoskeleton robot 310 includes a thigh structure 311, a calf structure 312, an ankle structure 313, and a plurality of connection joints 314. The control unit 340 may include a feedback subunit. The feedback subunit may be connected to the ankle structure 313. The feedback subunit may be used to obtain motion information of the ankle structure 313, and obtain gait phase information of the patient based on the motion information. A plantar pressure sensor may be provided on the ankle structure 313, and when the patient is in the standing phase, the feedback subunit may determine the gait phase information of the patient through the pressure information fed back by the plantar pressure sensor. When the patient is in the swing phase, an inertial measurement device can be set on the ankle structure 313, and the feedback subunit can judge the gait phase information through the acceleration and angular velocity fed back by the inertial measurement device, so as to activate the muscles of the target training part in stages based on the gait phase information, that is, to activate the anterior tibialis muscle of the ankle joint during the period when the patient enters the swing phase, to activate the gastrocnemius muscle during the period when the patient enters the stance phase, to activate the biceps femoris during the period when the patient enters the swing phase, and to activate the quadriceps femoris during the period when the patient enters the end of the swing phase and the middle of the stance phase. The control unit 340 can also include a digital-to-analog conversion subunit. The digital-to-analog conversion subunit can pre-process and extract features of the acceleration and angular velocity fed back by the inertial measurement device of the pressure information fed back by the plantar pressure sensor, and transmit the processed information to the feedback subunit. The feedback subunit can judge the gait phase information based on the information.

[0099] Further, the connecting joint 314 connected between the calf structure 312 and the ankle structure 313 can be characterized as a mechanical ankle joint. The calf structure 312 can be made of a metal plate. The linkage between the calf structure 312, the ankle structure 313 and the connecting joint 314 can complete dorsiflexion and plantar flexion movements. Adjustment springs (not shown in the figure) can be installed on both sides of the mechanical ankle joint to absorb and release the potential energy of the mechanical ankle joint during gait, and assist the mechanical ankle joint in dorsiflexion and plantar flexion. The plantar pressure sensor can be an 8-lead pressure film sensor. The inertial measurement device can be a 6-axis inertial measurement unit. The thigh structure 311, the calf structure 312, and the ankle structure 313 can simulate the thigh, calf and foot of the patient respectively. The 8-lead pressure film sensors can be respectively arranged on the big toe, the first metatarsal head, the third metatarsal head, the fifth metatarsal head, the outer side of the arch, the rear side of the heel, the inner side of the heel and the outer side of the heel of the ankle structure 313.

[0100] In some embodiments, the motor module 320 may include a force sensor. The force sensor is disposed at the target training part. The force sensor may be used to obtain the human-machine interaction force between the target training part and the exoskeleton robot 310.

[0101] In some embodiments, the hybrid drive lower limb rehabilitation training system 300 also includes a balance measurement module and a locking device 350. The balance measurement module is arranged on the exoskeleton robot 310, and the balance measurement module (not shown in the figure) can be used to detect the posture of the exoskeleton robot 310. The locking device 350 is arranged on the exoskeleton robot 310. When the inclination angle of the exoskeleton robot 310 exceeds the angle threshold, the control unit 340 controls the locking device 350 to perform a locking operation, thereby preventing the patient from falling. Specifically, the balance measurement module may include an inertial sensor and a feature processing chip to detect and evaluate the posture and stability of the exoskeleton robot 310. The locking device 350 may be an electromagnetic brake device. The joint is controlled to be in a moving or stationary state by powering on or off, thereby locking or releasing the exoskeleton robot 310.

[0102] According to an embodiment of the present disclosure, the hybrid drive lower limb rehabilitation training system 300 may also be provided with a backpack. The backpack can be used to place the control unit 340, the battery management module and the mobile power supply. The battery management module can be used to manage the mobile power supply, such as charging and warning the mobile power supply. A battery compartment door may be left on the side of the backpack to facilitate the replacement of the mobile power supply. The mobile power supply may be a lithium battery. The mobile power supply can be placed on the bottom layer of the backpack to improve weight distribution and enhance wearing comfort. A battery compartment door may be left on the side of the backpack to facilitate the replacement of the mobile power supply. The side of the backpack close to the patient's back may be provided with fabric cushioning and double-sided shoulder straps to facilitate the patient's wearing and improve wearing comfort.

[0103] According to the embodiment of the present disclosure, the exoskeleton robot 310 can be roughly symmetrical. The exoskeleton robot 310 can also include a waist structure 315 and a hip structure 316. The hip structure 316 includes two L-shaped plates 3161. The two L-shaped plates 3161 can be respectively arranged on both sides of the waist structure 315. A slide rail and a drive device 3152 can be arranged on the waist structure 315. The control unit 340 can make the two L-shaped plates 3161 approach or move away along the slide rail by adjusting the drive device 3152, thereby adjusting the width of the hip structure 316. The drive device 3152 can be a turbine screw motor, and the turbine screw motor and the L-shaped plate 3161 can be threadedly connected. By adjusting the width of the hip structure 316, the hip width of different patients can be adapted to enhance the patient's wearing experience and auxiliary effect. The thigh structure 311 can include two thigh plates, which are respectively arranged on both sides of the hip structure 316 through the connecting joint 314. The thigh plate can be a metal plate. The calf structure 312 may include two calf plates, which are respectively arranged on both sides of the thigh structure 311 through the connection joints 314. The calf plate may be a metal plate. The thigh plate and the calf plate may be slidably connected.

[0104] According to the disclosed embodiment, the exoskeleton robot 310 may further include a plurality of leg length adjustment devices 317. The leg length adjustment devices 317 may be respectively arranged on the thigh board and the calf board. The leg length adjustment devices 317 may adjust the length of the thigh board and the calf board, thereby adjusting the length of the exoskeleton robot 310 to accommodate patients with different leg lengths. Each leg length adjustment device 317 may include a stepper motor, a linear displacement sensor, and a locking mechanism. The control unit 340 may adjust the length of the exoskeleton robot 310 by driving the stepper motor, and detect the length of the exoskeleton robot 310 by the linear displacement sensor. When it is determined that the length of the exoskeleton robot 310 reaches a preset length, the locking mechanism may lock the thigh board and the calf board, and fix the length of the thigh board and the calf board. The leg length adjustment device 317 may adopt a conventional adjustment method.

[0105] According to an embodiment of the present disclosure, in order to reduce the overall weight of the exoskeleton robot 310, the thigh structure 311, the calf structure 312, the ankle structure 313, the waist structure 315 and the hip structure 316 can be made of high-strength magnesium alloy and aluminum alloy materials. Further, other alloys or polymer materials can also be used. The exoskeleton robot 310 can also include a shell, which can be used to be set on the thigh structure 311, the calf structure 312, the ankle structure 313, the waist structure 315 and the hip structure 316 to improve the comfort of the patient during training. The shell of the exoskeleton robot 310 can be made of 3D printing materials through 3D printing technology. The interior of the exoskeleton robot 310 can be provided with auxiliary structural parts for supporting parts. The auxiliary structural parts can be made of high-strength magnesium alloy and aluminum alloy materials.

[0106] According to an embodiment of the present disclosure, each connection joint 314 may include a motor, a reducer, a torque sensor, a current detection device, a temperature detection device and an encoder. The control unit 340 may include a joint control subunit. The joint control subunit can drive the motor to rotate to drive the calf and / or thigh to move. The reducer can increase the output torque of the motor and reduce the speed of the motor output. The current detection device and the temperature detection device can detect the temperature of the motor when it moves. The torque sensor can detect the output torque and speed of the motor. The encoder can calculate the rotation angle and speed of the connection joint 314. The joint control subunit can control the motion state of the connection joint 314 in real time according to the rotation angle and speed of the connection joint 314.

[0107] According to the embodiment of the present disclosure, the electrical stimulation module 330 can simultaneously complete the electromyographic signal acquisition and the functional electrical stimulation operation. The electrical stimulation module 330 can drive the target training part to move by electrically stimulating the muscles of the target training part. Furthermore, the primary and secondary dual channels can be used to acquire electromyographic signals. For example, within T seconds of applying electrical stimulation, the secondary channel is used to acquire electromyographic signals. After T seconds, the electromyographic signal is switched to the primary channel again and it is determined whether the signal is saturated. The above process is repeated until normal acquisition is achieved, thereby avoiding the stimulation artifacts generated by the electrical stimulation from affecting the acquisition of the electromyographic signal. T can be 100ms.

[0108] According to the embodiment of the present disclosure, the thigh structure 311, the calf structure 312, the ankle structure 313, the waist structure 315 and the hip structure 316 can be provided with straps on both sides to facilitate the patient to wear. The electrical stimulation module 330 is used for the electrode stickers of electrical stimulation, which are respectively pasted on the tibialis anterior, gastrocnemius, biceps femoris and quadriceps femoris of the left and right legs of the patient, and the pasting position can also be set according to the training needs of the patient. The hybrid drive lower limb rehabilitation training system 300 also includes an interactive device. The interactive device may include a touch display screen and a button. The rehabilitation therapist or the patient can use the control unit 340 to adjust the width of the hip structure 316, the length of the thigh structure 311 and the length of the calf structure 312 through the interactive device to monitor the operating state of the exoskeleton and the movement state of the wearer. The rehabilitation therapist or the patient can use the control unit 340 through the interactive device to set the walking assistance parameters required by the patient. The walking assistance parameters may include parameters such as step length, step speed, torque of each motor, waveform, amplitude, and width of the lead electrical stimulation turned on by electrical stimulation. Furthermore, when conducting rehabilitation walking assistance training, the control unit 340 fits the torque trajectory according to the set walking assistance parameters, and determines the patient's gait phase based on the plantar motion information, the acceleration and angular velocity of the inertial measurement device, the torque and speed of the motor, the rotation angle and speed of the connecting joint 314, the posture of the exoskeleton robot 310 and other information, and determines the target motor output torque and target electrical stimulation signal required by the motor module 320 and the electrical stimulation module 330 based on the human-computer interaction force and electromyographic signal.

[0109] Figure 6 A block diagram of an electronic device for a control method of a hybrid-driven lower limb rehabilitation training system according to an embodiment of the present disclosure is schematically shown. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0110] like Figure 6As shown, the electronic device 600 according to an embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0111] In RAM 603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM 602 and RAM 603 are connected to each other through bus 604. Processor 601 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 602 and / or RAM 603. It should be noted that the program can also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in one or more memories.

[0112] According to an embodiment of the present disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The system 600 may further include one or more of the following components connected to the I / O interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a speaker, etc., such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc.; a storage portion 608 including a hard disk, etc.; a communication portion 609 including a network interface card, such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0113] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0114] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0115] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0116] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 602 and / or the RAM 603 described above and / or one or more memories other than the ROM 602 and the RAM 603 .

[0117] The embodiments of the present disclosure also include a computer program product, which includes a computer program, and the computer program contains program code for executing the method provided by the embodiments of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the above method provided by the embodiments of the present disclosure.

[0118] When the computer program is executed by the processor 601, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0119] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0120] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level procedures and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, Python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0121] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0122] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A hybrid drive lower limb rehabilitation training system, comprising: an exoskeleton robot configured to support a patient to be trained; A motor module connected to the exoskeleton robot, the motor module being configured to drive the exoskeleton robot to move so as to drive the target training part of the patient to move; An electrical stimulation module is provided on the exoskeleton robot, and is configured to electrically stimulate the muscles of the target training part to drive the target training part to move; A control unit is connected to the motor module and the electrical stimulation module, and the control unit is configured as follows: Determine a target interaction force factor based on the human-machine interaction force between the target training part and the exoskeleton robot at the current moment, wherein the human-machine interaction force is generated when the motor module drives the exoskeleton robot to drive the target training part to move; Determine the target muscle fatigue factor based on the average median frequency of the electromyographic signal of the target training part at the current moment, wherein the average median frequency represents the average value of multiple median frequencies, and the multiple median frequencies include the median frequency of the electromyographic signal at the current moment and the median frequencies of the electromyographic signals at multiple historical moments before the current moment; Determine a stimulation proportion based on the target interaction force factor and the target muscle fatigue factor, wherein the stimulation proportion is characterized by the proportion of the target stimulation output torque of the electrical stimulation module in the target training torque, wherein the target training torque corresponds to the torque in the torque trajectory line; Determine the target motor output torque of the motor module and the target electrical stimulation signal of the electrical stimulation module based on the stimulation proportion; Based on the target motor output torque and the target electrical stimulation signal, the motor module and the electrical stimulation module are respectively controlled to drive the target training part to move, so that the target training part is at the target training torque.

2. The hybrid drive lower limb rehabilitation training system according to claim 1, characterized in that: The determining of the target interaction force factor based on the human-machine interaction force between the target training part and the exoskeleton robot at the current moment includes: In the case where the human-computer interaction force is greater than the interaction force threshold, determining the target interaction force factor based on the sum of the value of the current interaction force factor and the first preset value; When the human-computer interaction force is less than or equal to the interaction force threshold, the current interaction force factor is determined as the target interaction force factor.

3. The hybrid drive lower limb rehabilitation training system according to claim 1, characterized in that: Determining the target muscle fatigue factor based on the average median frequency of the electromyographic signal of the target training part at the current moment includes: When the average median frequency is less than the current first baseline value, determining the current muscle fatigue factor as the target muscle fatigue factor; When the average median frequency is greater than the current first baseline value, the median frequency at the current moment is set as the target first baseline value; When the average median frequency is less than the target first baseline value, and the ratio of the absolute value of the difference between the average median frequency and the target first baseline value to the target first baseline value is greater than the second baseline value, the target muscle fatigue factor is obtained based on the sum of the value of the current muscle fatigue factor and the second preset value; When the average median frequency is less than the target first baseline value, and the ratio of the absolute value of the difference between the average median frequency and the target first baseline value to the target first baseline value is less than or equal to the second baseline value, the current muscle fatigue factor is determined to be the target muscle fatigue factor.

4. The hybrid drive lower limb rehabilitation training system according to claim 1, characterized in that: The determining of the stimulation proportion based on the target interaction force factor and the target muscle fatigue factor comprises: Acquire a training factor based on the target interaction force factor and the target muscle fatigue factor; Based on the mapping relationship and the training factor, the stimulation ratio is determined.

5. The hybrid drive lower limb rehabilitation training system according to claim 1, characterized in that: Determining the target motor output torque of the motor module based on the stimulation ratio includes: Determining a target stimulation output torque of the electrical stimulation module based on the stimulation proportion and the target training torque; The target motor output torque is determined based on the target stimulation output torque and the target training torque.

6. The hybrid drive lower limb rehabilitation training system according to claim 5, characterized in that: The determining the target electrical stimulation signal based on the stimulation proportion comprises: Determining the muscle activation degree of the target training part based on the target stimulation output torque and the joint angle of the target training part; The target electrical stimulation signal is determined based on the muscle activation level.

7. The hybrid drive lower limb rehabilitation training system according to claim 1, characterized in that: The exoskeleton robot comprises a thigh structure, a calf structure, an ankle structure and a connecting joint, and the control unit comprises: A feedback subunit is connected to the ankle structure, and the feedback subunit is configured to obtain motion information of the ankle structure, and the control unit obtains gait phase information of the patient based on the motion information.

8. The hybrid drive lower limb rehabilitation training system according to claim 1, characterized in that: The motor module comprises: A force sensor is arranged at the target training part, and the force sensor is configured to obtain the human-machine interaction force between the target training part and the exoskeleton robot.

9. The hybrid drive lower limb rehabilitation training system according to claim 1, characterized in that: Also includes: A balance measurement module, disposed on the exoskeleton robot, and configured to detect the posture of the exoskeleton robot; The locking device is arranged on the exoskeleton robot. When the tilt angle of the exoskeleton robot exceeds an angle threshold, the control unit controls the locking device to perform a locking operation.

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