Coordinated control system for spinal cord stimulation devices and rehabilitation system

Abstract

The embodiment of the application relates to the technical field of medical devices, and discloses a synergic control system of a spinal cord stimulation device and a rehabilitation system, the synergic control system comprising: a muscle strength determination module for determining a muscle strength level; a mode selection module for determining a current control mode; a first synergic control module for generating a first control instruction and a second control instruction in a first mode; the first control instruction instructing the spinal cord stimulation device to activate an agonist muscle group to generate an auxiliary contraction force; the second control instruction instructing an exoskeleton to be in an active driving mode; a second synergic control module for generating a third control instruction and a fourth control instruction in a second mode; the third control instruction instructing the spinal cord stimulation device to maintain a muscle activation level of the agonist muscle group; the fourth control instruction instructing the exoskeleton to be in a support weight-reducing mode; and an instruction output module for sending the first control instruction and the third control instruction to the spinal cord stimulation device and sending the second control instruction and the fourth control instruction to the exoskeleton.

Description

Technical Field

[0001] This application relates to the field of medical device technology, and more specifically, to a collaborative control system and rehabilitation system for a spinal cord stimulation device. Background Technology

[0002] Spinal cord injury, stroke, and other diseases often lead to motor dysfunction, manifested as decreased or lost strength in voluntary muscle groups. Implantable spinal cord stimulation is currently an important active intervention method. It uses spinal electrodes of a spinal cord stimulation device to output sequential pulses, activate the motor neuron pool, and induce muscle contraction to drive joint movement.

[0003] However, for patients with severely insufficient residual muscle strength, the weak contractile force induced by spinal cord stimulation devices is insufficient to overcome the gravity and inertia of the limbs, thus failing to form effective joint movement, resulting in poor rehabilitation outcomes. Summary of the Invention

[0004] This application provides a collaborative control system and rehabilitation system for a spinal cord stimulation device to solve the problem that the rehabilitation effect of spinal cord stimulation devices is poor when used for rehabilitation treatment in the prior art.

[0005] According to a first aspect of the embodiments of this application, a collaborative control system for a spinal cord stimulation device is provided, the collaborative control system for the spinal cord stimulation device comprising: The muscle strength determination module is used to determine the muscle strength level of the agonist muscle groups involved in the target joint movement of an object. The mode selection module is used to determine whether the current control mode is a first mode or a second mode based on the muscle strength level; the muscle strength level in the first mode is lower than the muscle strength level in the second mode. A first collaborative control module is used to generate a first control command and a second control command based on the motion intention of the object in the first mode; the first control command is used to instruct the spinal cord stimulation device to output a first electrical stimulation signal to activate the active muscle group to generate an auxiliary contractile force; the second control command is used to instruct the exoskeleton worn by the object to be in an active drive mode. The second collaborative control module is used to generate a third control command and a fourth control command based on the muscle activation level of the active muscle group in the second mode; the third control command is used to instruct the spinal cord stimulation device to output a second electrical stimulation signal to maintain the muscle activation level of the active muscle group; the fourth control command is used to instruct the exoskeleton to be in a support weight reduction mode. The instruction output module is used to send the first control instruction and the third control instruction to the spinal cord stimulation device, and to send the second control instruction and the fourth control instruction to the exoskeleton.

[0006] Optionally, the collaborative control system further includes: The mode switching management module is used to control the driving force provided by the exoskeleton to decrease by a preset step size during the switching process when the current control mode is switched from the first mode to the second mode, and to control the signal strength of the electrical stimulation signal output by the spinal cord stimulation device to be maintained or adjusted adaptively during the switching process, until the muscle strength level of the active muscle group reaches a preset standard, and then switch to the second mode.

[0007] Optionally, the mode switching management module is further configured to: When the current control mode switches from the first mode to the second mode, the assist torque of the exoskeleton is reduced according to the first ramp function, and the signal strength of the electrical stimulation signal output by the spinal cord stimulation device is kept constant or increased according to the second ramp function. When the muscle strength level of the active muscle group is detected to reach a preset standard, the current control mode is switched to the second mode.

[0008] Optionally, the instruction output module is further configured to: When outputting the first control command and the second control command, the output time of the first control command is earlier than the output time of the second control command, and the time difference between the two output times is equal to the target duration; The target duration is equal to the physiological response time when the muscle contraction force induced by electrical stimulation reaches a predetermined threshold.

[0009] Optionally, the first collaborative control module is used to: By decoding the object's electroencephalogram (EEG) signals, the movement intention was identified as stepping with the left leg, stepping with the right leg, standing up, or stopping. Based on the identified movement intention, the electrical stimulation sequence corresponding to the gait phase is determined; The first control command is generated based on the electrical stimulation sequence corresponding to the gait phase.

[0010] Optionally, the second collaborative control module is used to generate the third control command through the following steps: The deviation between the characteristic values ​​of the electromyographic signals of the active muscle group and the target characteristic values ​​within the current time window is calculated in real time. Based on a preset deviation mapping table, the stimulus adjustment amount corresponding to the deviation is determined; wherein, the preset deviation mapping table includes the mapping relationship between different deviations and different stimulus adjustment amounts. Based on the stimulation adjustment amount corresponding to the deviation, the third control command is generated so that after the spinal cord stimulation device executes the third control command, the characteristic value of the electromyographic signal of the active muscle group tends to the target characteristic value, or remains within a preset range containing the target characteristic value.

[0011] Optionally, the collaborative control system further includes: an update module, used for: In the second mode, the number of times the object successfully completes the target action within the first time period is monitored; If the number of times is greater than or equal to the number of times threshold, the target feature value is automatically increased; wherein the increased target feature value is greater than the original target feature value.

[0012] Optionally, the update module is further configured to: Monitor the frequency or rate of change in muscle strength level of the subject successfully completing the target action during the second time period; The number of repetitions threshold is dynamically adjusted based on the rate of change of frequency or the rate of change of muscle strength.

[0013] Optionally, the fourth control command is used to instruct the exoskeleton to reduce joint impedance to a preset resistance value when it is in the support and weight reduction mode, so that the exoskeleton can act as a motion follower to provide an auxiliary force to drive the target joint movement.

[0014] According to a second aspect of the present application, a rehabilitation system is provided, the rehabilitation system comprising: an exoskeleton, a spinal cord stimulation device, and a collaborative control system as described in the first aspect; the exoskeleton and the spinal cord stimulation device are respectively communicatively connected to the collaborative control system. The spinal cord stimulation device is used for: Receive the first control command and / or the third control command sent by the cooperative control system; The first electrical stimulation signal is output according to the first control command to activate the active muscle group to generate auxiliary contractile force; The second electrical stimulation signal is output according to the third control command to maintain the muscle activation level of the active muscle group; The exoskeleton is used for: Receive the second control command and / or the fourth control command sent by the cooperative control system; According to the second control command, the exoskeleton is controlled to be in active drive mode; According to the fourth control command, the exoskeleton is controlled to be in a support and weight reduction mode.

[0015] The beneficial effects of the technical solutions provided in this application are: In this embodiment, spinal cord stimulation and mechanical synergy are integrated, and the synergy mode can be automatically switched according to the muscle strength level. When the muscle strength is severely insufficient, the spinal cord electrical stimulation and exoskeleton active assistance can be triggered simultaneously by the intention to move, forming a synergistic drive of neural stimulation and mechanical force, restoring the patient's active intention to move. After the muscle strength reaches a certain level, the electrical stimulation is adjusted according to electromyographic feedback and the exoskeleton provides weight-reduction support, enabling the patient to complete the movement in a near-natural way of muscle exertion. This effectively avoids the treatment deficiency or over-assistance caused by a single mode and greatly enhances the rehabilitation effect. Attached Figure Description

[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A schematic diagram of the implementation environment of the collaborative control system provided in the embodiments of this application; Figure 2 A schematic diagram of the structure of a collaborative control system for a spinal cord stimulation device provided in this application embodiment; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] The embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the embodiments described below with reference to the accompanying drawings are exemplary descriptions for explaining the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions of the embodiments of this application.

[0018] Those skilled in the art will understand that, unless otherwise stated, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the terms “comprising” and “including” as used in the embodiments of this application mean that the corresponding feature can be implemented as the presented feature, information, data, step, operation, element, and / or component, but do not exclude implementation as other features, information, data, step, operation, element, component, and / or combinations thereof supported by the art. It should be understood that when we say that an element is “connected” or “coupled” to another element, the one element can be directly connected or coupled to the other element, or it can mean that the one element and the other element establish a connection relationship through an intermediate element. Furthermore, “connected” or “coupled” as used herein can include wireless connection or wireless coupling. The term “multiple” refers to two or more; therefore, in the embodiments of this application, “multiple” may also be understood as “at least two.” The term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / ", unless otherwise specified, generally indicates that the related objects before and after it are in an "or" relationship.

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0020] To facilitate understanding of the technical solution of this application, the following terms will be introduced.

[0021] Electroencephalogram (EEG) signals are formed by summing the postsynaptic potentials that occur synchronously among a large number of neurons during brain activity. It records the electrical wave changes during brain activity and is a comprehensive reflection of the electrophysiological activity of brain nerve cells on the surface of the cerebral cortex or scalp; it can also be called an electroencephalogram or brainwave. In this application, EEG signals can be used to decode the motor intentions of an object.

[0022] Electromyography (EMG) is the sum of action potentials generated by muscle fibers during muscle contraction, both temporally and spatially. It reflects characteristics such as muscle activation state and contraction strength. In this application, EMG signals can be used to assess the muscle activation level of agonist muscle groups and serve as one of the bases for determining muscle strength.

[0023] Muscle strength level refers to the magnitude of force or degree of muscle activation currently generated by the agonist muscle groups involved in the movement of a target joint. Muscle strength level can be quantified by analyzing characteristic parameters such as the amplitude and frequency of electromyographic signals, or it can be comprehensively assessed in conjunction with the subject's motor performance or other physiological signals. In this application, based on the level of muscle strength, either a first mode or a second mode is selected to achieve coordinated control between the spinal cord stimulation device and the exoskeleton.

[0024] A spinal cord stimulation device is a device that delivers electrical stimulation signals to specific segments of the spinal cord via implantation or non-implantation. This device releases pulsed currents with specific parameters to the dorsal or ventral side of the spinal cord through a pre-set electrode array to activate neural pathways in the target muscle group, thereby inducing or enhancing muscle contraction, or maintaining the muscle's activated state.

[0025] An exoskeleton is a wearable mechanical device that mimics the structure of a human limb, typically consisting of a drive unit, a support structure, and sensors. An exoskeleton can operate in different drive modes, providing active driving force, auxiliary force, or support force for the joint movement of the subject. In this application, the exoskeleton operates in an active drive mode in the first mode, responding to a second control command to drive or assist the movement of the subject's limbs; in the second mode, it operates in a support and weight reduction mode, responding to a fourth control command to provide support and gravity compensation for the subject's limbs.

[0026] In the field of spinal cord injury rehabilitation, to assist patients in rebuilding lower limb motor function, related technologies typically involve either exoskeletons or implantable spinal cord stimulation systems (the aforementioned spinal cord stimulation devices). Exoskeletons utilize motors positioned at the hip and knee joints to drive the patient's limbs to perform movements such as stepping and sitting up, following a pre-set gait trajectory. Their primary purpose is to provide mechanical support and driving force to compensate for the loss of voluntary muscle strength. Spinal cord stimulation, on the other hand, applies sequential electrical pulses to specific segments of the lumbosacral spinal cord via an electrode array implanted in the epidural space. This activates the motor neuron pool, inducing rhythmic contractions of the lower limb muscles, focusing on utilizing residual neural pathways to generate a certain degree of active muscle involvement. These two approaches are independent in terms of interface and control, and are used separately for passive motor assistance or neural activation training.

[0027] However, this separate approach becomes ill-suited to situations where patients' residual muscle strength fluctuates significantly during rehabilitation. For patients whose manual muscle strength tests show agonist muscle strength below grade 2, while spinal cord stimulation alone can induce muscle contraction, the resulting joint torque is usually too small to enable the lower limbs to complete full functional movements such as leg raises or extensions. Conversely, when using an exoskeleton to forcibly move the limb along a fixed trajectory, the patient's weak electrical activity attempting to exert force is difficult for the system to recognize and utilize, preventing the active movement intention from participating in the control process and thus inhibiting opportunities for neuromuscular joint training. For patients whose muscle strength has recovered to grade 3 or higher, maintaining strong active drive from the exoskeleton or a fixed output intensity of electrical stimulation masks the patient's gradually increasing ability to exert force, making it difficult for the patient to naturally perceive the correspondence between force output and movement results, thus delaying the smooth transition to voluntary movement. During the continuous rehabilitation cycle of the same patient, they will experience two states: severe muscle weakness and gradual recovery of muscle strength. The fixed control architecture in related technologies cannot meet the needs for assistive force and nerve stimulation in both states at the same time in the same system. If only one of them is used, the rehabilitation effect will inevitably be very poor.

[0028] To address the aforementioned issues, this disclosure provides a collaborative control system. First, a muscle strength determination module and a mode selection module assess the exertion capacity of the active muscle groups in real time, establishing a decision-making basis for the automatic switching of subsequent control strategies. In the first mode, the first collaborative control module simultaneously converts the motor intent decoded by the EEG into a first control command for the spinal cord stimulation device and a second control command for the exoskeleton. The command output module controls the precise timing coordination of these two commands, allowing the weak contractile force induced by electrical stimulation to superimpose with the active driving force provided by the exoskeleton at the joint, solving the problem that existing single methods cannot generate effective joint movement when muscle strength is extremely low. As muscle strength increases and mode switching is triggered, the mode switching management module can use a ramp function to control the smooth withdrawal of the exoskeleton assistance while maintaining or enhancing the electrical stimulation output, ensuring a smooth switching process. The system eliminates the sensation of impact and falls, resolving safety and comfort issues arising from sudden mode changes. Upon entering the second mode, the second collaborative control module uses real-time electromyography signals as a closed-loop feedback source to generate a third control command that dynamically adjusts the intensity of electrical stimulation, and a fourth control command that switches the exoskeleton to a support-weight-reduction mode. This allows patients to complete movements primarily using their own muscle strength in a near-natural biomechanical environment. Simultaneously, the update module automatically adjusts the target feature value based on the number of successful movements, forming a progressive rehabilitation loop of "training → achieving the target → incremental improvement." Ultimately, throughout the entire rehabilitation cycle, the system can automatically match the optimal stimulation-assistance synergy strategy based on real-time changes in the patient's muscle strength without manual intervention, smoothly transitioning from "fully assisted initiation" to "autonomous force-driven dominance." This effectively avoids the problems of insufficient treatment or excessive assistance caused by a single mode, significantly improving rehabilitation effects and training efficiency.

[0029] Figure 1 This is a schematic diagram of the implementation environment of a collaborative control system provided in an embodiment of this application.

[0030] The implementation environment includes the hardware environment for an adaptive and coordinated control system for spinal cord injury rehabilitation. The hardware components include a wearable exoskeleton 101, an implantable spinal cord stimulation device 102, a signal acquisition device 103, and a coordinated control device 104. The exoskeleton 101 is worn on the affected limb via a fixation strap and joint actuators, capable of outputting driving torque or providing weight-reducing support at joints such as the hip and knee. The spinal cord stimulation device includes an electrode array and a pulse generator implanted in the epidural space to output electrical stimulation signals to specific spinal cord segments to induce contraction of agonist muscle groups. The signal acquisition device 103 includes electroencephalogram (EEG) signal acquisition electrodes and electromyography (EMG) signal acquisition electrodes.

[0031] The collaborative control device 104 establishes communication connections with the exoskeleton 101, the spinal cord stimulation device, and the signal acquisition device 103. The collaborative control device 104 receives EEG and EMG data from the signal acquisition device 103 via wired or wireless means. After performing signal processing and control logic operations internally, it sends a first type of instruction to the spinal cord stimulation device to control the electrical stimulation output and a second type of instruction to the exoskeleton 101 to control the joint drive mode. The first type of instruction includes instructions for generating activation-type electrical stimulation and instructions for adjusting the electrical stimulation to maintain muscle activation levels. The second type of instruction includes instructions for the exoskeleton 101 to actively provide driving force and instructions for the exoskeleton 101 to provide support and weight reduction.

[0032] When the subject's muscle strength is low, the collaborative control device 104 generates commands based on the motor intention in the EEG signals and transmits them to the spinal stimulation device and exoskeleton 101, causing them to synchronize movements and form a synergistic driving force. After the subject's muscle strength partially recovers, the collaborative control device 104 switches to using EMG signals as the primary feedback source, outputting adjustment commands to the spinal stimulation device to maintain the target muscle activation level, while simultaneously outputting commands to the exoskeleton 101 to put it into a low-impedance following state, providing only weight loss assistance. The signal acquisition device 103 continuously acquires EEG and EMG signals in real time, forming the data foundation for closed-loop control.

[0033] like Figure 2 As shown in the figure, this application provides a collaborative control system for a spinal cord stimulation device, including: The muscle strength determination module 201 is used to determine the muscle strength level of the agonist muscle group for the target joint movement of the object.

[0034] The target population includes patients with spinal cord injuries, strokes, and other conditions that often lead to motor dysfunction, such as paraplegia. Target joints include lower limb joints, such as the hip and knee joints. Muscle strength is an indicator that measures the maximum force that the agonist muscle groups can currently generate. For example, muscle strength can be used to accurately assess the degree of paralysis and recovery stage in paraplegic patients.

[0035] In some embodiments, the muscle strength determination module 201 can extract quantitative indicators to characterize muscle strength levels by performing time-domain analysis on the surface electromyography signals of the active muscle groups involved in the target joint movement.

[0036] Optionally, the muscle strength determination module 201 can calculate the root mean square (RMS) value of the electromyographic signal of the agonist muscle group moving the target joint within a preset time window, as a quantitative indicator of muscle strength level. The RMS value can be considered the effective value of the electromyographic signal discharge; its magnitude is determined by the amplitude change of the electromyographic signal and can reflect the current muscle strength and movement speed trend to a certain extent. A larger value indicates stronger contractile force of the agonist muscle group, thus serving as a quantitative indicator of muscle strength level. The preset time window can be set according to actual needs, for example, it can be set to 200 milliseconds, 400 milliseconds, or 800 milliseconds.

[0037] Optionally, the muscle strength determination module 201 can calculate the integrated electromyographic (EMG) value of the active muscle group moving the target joint within a preset time window, as a supplementary quantitative indicator of muscle strength level. The integrated EMG value reflects the cumulative effect of the EMG signal over time. The larger the integrated EMG value, the greater the total electrical activity of the muscle per unit time, and the higher the corresponding muscle strength level. Conversely, the smaller the integrated EMG value, the lower the muscle strength level.

[0038] In some embodiments, the muscle strength determination module 201 can also perform frequency domain analysis on the surface electromyography signals of the active muscle group moving the target joint and extract frequency domain feature parameters to assist in assessing muscle strength level.

[0039] Optionally, the muscle strength determination module 201 can calculate the median frequency (MF) or mean power frequency (MPF) of the electromyographic signal of the agonist muscle group as an auxiliary assessment indicator of muscle strength level. The median frequency is the frequency value corresponding to dividing the power spectrum area into two equal parts, and the mean power frequency is the weighted average of all frequency components in the power spectrum. When muscles are fatigued or muscle strength decreases, the power spectrum of the electromyographic signal usually shifts to the left, and the median frequency and mean power frequency decrease accordingly. Therefore, the median frequency and mean power frequency can serve as auxiliary reference indicators of muscle strength level.

[0040] In some embodiments, the muscle strength determination module 201 can also acquire the muscle strength grading results assessed by Manual Muscle Testing (MMT) as a quantitative indicator of muscle strength level. For example, Manual Muscle Testing uses a six-level grading system from 0 to 5, and the specific meanings of each level are as follows: Grade 0: No muscle contraction; Grade 1: There is slight muscle contraction, but it cannot cause joint movement; Level 2: Able to perform full range of motion of joints while on a weight-loss basis; Level 3: Able to perform full range of motion against gravity, but unable to resist resistance; Level 4: Can resist gravity and some resistance to motion; Level 5: Can resist gravity and completely resist resistance motion.

[0041] For example, when the manual muscle strength assessment is 0 to 2, it can be judged as a low level of muscle strength (corresponding to the first mode); when the manual muscle strength assessment is 3 or above, it can be judged as a high level of muscle strength (corresponding to the second mode).

[0042] In some embodiments, the muscle strength level of the object can also be configured directly through an external device. For example, after a professional assesses the object's muscle strength level, the assessment result is transmitted to the muscle strength determination module 201 using a terminal device. The muscle strength determination module 201 can then use the received assessment result as the object's muscle strength level, thus eliminating the need to perform the muscle strength level assessment step locally.

[0043] The mode selection module 202 is used to determine whether the current control mode is the first mode or the second mode based on the muscle strength level; the muscle strength level in the first mode is lower than the muscle strength level in the second mode.

[0044] In some embodiments, the mode selection module 202 can compare the muscle strength level determined by the muscle strength determination module 201 with a preset threshold. When the muscle strength level is less than or equal to the preset threshold, the object is determined to be in a state of severe muscle weakness, and the first mode is selected, i.e., the current mode is determined to be the first mode; otherwise, the second mode is selected. The preset threshold can be flexibly set according to needs and is not limited here. For different muscle strength level quantification indicators, the preset threshold is the standard value corresponding to the indicator. For example, when the muscle strength level quantification indicator includes the root mean square value within a preset time window, the preset threshold can be set as: the root mean square value calculated in real time reaches or exceeds 70% of the target value, wherein the target value is a predetermined reference benchmark value. As another example, when the muscle strength level quantification indicator adopts the results of manual muscle strength assessment, the preset threshold can be set as: the manual muscle strength assessment reaches level 3 or above.

[0045] In some embodiments, the mode selection module is dynamically set by the physician according to the rehabilitation progress. The mode selection module 202 is connected to the first collaborative control module 203 and the second collaborative control module 204, respectively. For example, the mode selection module 202 can output a control signal to either the first collaborative control module 203 or the second collaborative control module 204, ensuring that only one of the collaborative control modules is active at any given time. This mode selection based on muscle strength level avoids undertreatment or over-assistance caused by prolonged use of a fixed mode.

[0046] The first collaborative control module 203 is used to generate a first control command and a second control command based on the object's motion intention in a first mode; the first control command is used to instruct the spinal cord stimulation device to output a first electrical stimulation signal to activate the active muscle group to generate an auxiliary contractile force; the second control command is used to instruct the exoskeleton worn by the object to be in an active drive mode.

[0047] Motor intentions can be obtained by decoding electroencephalogram (EEG) signals. The first collaborative control module 203 can be configured with a decoding algorithm that can identify motor intentions such as stepping or standing up from EEG signals. After obtaining the motor intention, the first collaborative control module 203 can call a pre-stored electrical stimulation sequence template to generate a first control command. This first control command may include the timing, pulse width, amplitude, and targeted electrode channel of the stimulation pulse to induce auxiliary contractile force in the agonist muscle groups.

[0048] The first collaborative control module 203 generates a second control command based on the same motion intention. This second control command can be used to control the drive mode of the exoskeleton, for example, by adjusting the drive mode, controlling the hip and knee joint actuators to output a predetermined assist torque.

[0049] It is worth noting that in the first mode, the weak muscle force induced by electrical stimulation and the mechanical force provided by the exoskeleton are generated synchronously in time, forming a neuromechanical synergistic driving force that helps the subject initiate and complete the target action. The exoskeleton operating in active drive mode provides the main or all of the power required for the subject's movement.

[0050] The second collaborative control module 204 is used to generate a third control command and a fourth control command based on the muscle activation level of the active muscle group in the second mode; the third control command is used to instruct the spinal cord stimulation device to output a second electrical stimulation signal to maintain the muscle activation level of the active muscle group; the fourth control command is used to instruct the exoskeleton to be in a support weight reduction mode.

[0051] The muscle activation level can be a feature value extracted from the real-time electromyographic signal of the agonist muscle group, such as a window RMS value updated in 50-millisecond increments. The second collaborative control module 204 compares the deviation between this feature value and a preset target feature value, and generates a third control command to adjust the electrical stimulation intensity according to preset control rules. This third control command can specifically be a command to adjust the amplitude of the stimulation current or the pulse width, so that the electromyographic feature value tends to and remains within the desired range. Maintaining the muscle activation level of the agonist muscle group can be achieved by keeping the muscle activation level of the agonist muscle group within a preset range.

[0052] After the subject's muscle strength partially recovers, the control feedback source is switched from electroencephalogram (EEG) signals to electromyogram (EMG) signals, allowing the electrical stimulation to automatically adapt to the real-time state of the muscles. This enables the subject to perform repetitive movement training at a stable neuromuscular activation level. Simultaneously, the fourth control command generated by the second collaborative control module 204 switches the exoskeleton to a support and weight reduction mode, compensating only for the weight of the affected limb without excessively interfering with the movement.

[0053] The instruction output module 205 is used to send the first control instruction and the third control instruction to the spinal cord stimulation device, and to send the second control instruction and the fourth control instruction to the exoskeleton.

[0054] The command output module 205 may include at least one interface for sending data to the spinal cord stimulation device and at least one interface for sending data to the exoskeleton. These interfaces may be wired serial ports, Bluetooth wireless links, or wireless LAN connections. During the transmission process, the command output module 205 can perform data packaging and transmission timing management of control commands to ensure that the control commands reliably reach the corresponding execution device at the physical level.

[0055] In this embodiment, spinal cord stimulation and mechanical synergy are integrated, and the synergy mode can be automatically switched according to the muscle strength level. When the muscle strength is severely insufficient, the spinal cord electrical stimulation and exoskeleton active assistance can be triggered simultaneously by the intention to move, forming a synergistic drive of neural stimulation and mechanical force, restoring the patient's active intention to move. After the muscle strength reaches a certain level, the electrical stimulation is adjusted according to electromyographic feedback and the exoskeleton provides weight-reduction support, enabling the patient to complete the movement in a near-natural way of muscle exertion. This effectively avoids the treatment deficiency or over-assistance caused by a single mode and greatly enhances the rehabilitation effect.

[0056] To further optimize the smoothness of the mode switching process and reduce the safety risks associated with switching, in some embodiments of this application, the cooperative control system further includes: The mode switching management module is used to control the exoskeleton to reduce the driving force provided by the exoskeleton according to a preset step size when switching from the first mode to the second mode, and to control the signal strength of the electrical stimulation signal output by the spinal cord stimulation device to be maintained or adjusted during the switching process, until the muscle strength level of the active muscle group reaches the preset standard, and then switch to the second mode.

[0057] It should be noted that the switch from the first mode to the second mode indicates that the subject's muscle strength has recovered to a certain extent. Since the spinal cord stimulation device and exoskeleton operate significantly differently in the two modes, to avoid an overly abrupt switch that could introduce safety risks, this embodiment will implement transition control during the switch. For example, in the first mode, the exoskeleton provides the primary power for the subject's movement. If the switch to the second mode is abruptly interrupted in a short time, with the exoskeleton only used for weight reduction, safety issues may arise because the subject may not be able to adapt quickly enough.

[0058] The preset step size can be a pre-set reasonable step size. Each time the preset step size is reduced, the impact on the object is small and the safety is high. For example, the preset step size can be 5% to 10% of the current driving torque. That is, the driving force output by the exoskeleton is gradually reduced. Each reduction step size can be set to 5% to 10% of the initial driving torque, and the object is paused for hundreds of milliseconds after each reduction to evaluate the object's adaptation status.

[0059] While adjusting the driving force output by the exoskeleton, the output signal intensity of the spinal cord stimulation device can remain unchanged from the value before switching, or be positively fine-tuned based on small fluctuations in the electromyographic signal, thereby continuously maintaining muscle activation. When it is confirmed that the muscle strength level of the active muscle group has reached the preset standard—for example, the electromyographic RMS value remains above 70% of the target value when performing movements independently without the assistance of the exoskeleton—then it fully switches to the second mode.

[0060] It is worth noting that the preset standard is a standard value predetermined based on the quantitative indicators of muscle strength level. Among them, the quantitative indicators of muscle strength level include, but are not limited to, the root mean square value within the preset time window, the integrated electromyography value within the preset time window, the median frequency of the electromyography signal of the active muscle group, the average power frequency of the electromyography signal of the active muscle group, and the muscle strength grading results in the above embodiments, which will not be elaborated here.

[0061] For different quantitative indicators of muscle strength, the preset standard is the standard value corresponding to that indicator. For example, when the quantitative indicator of muscle strength includes the root mean square value within a preset time window, the preset standard can be set as follows: the root mean square value calculated in real time reaches or exceeds 70% of the target value, wherein the target value is a predetermined reference benchmark value.

[0062] When the quantitative indicator of muscle strength level uses the integrated electromyography (EMG) value within a preset time window, the preset standard can be similarly set as follows: the currently calculated integrated EMG value reaches or exceeds 70% of the target value. Here, the target value is the integrated EMG value recorded when the subject's active muscle groups undergo maximum voluntary contraction in a healthy state, or the expected integrated EMG value set by the system.

[0063] When the quantitative index of muscle strength level is median frequency or average power frequency, the preset standard can be set as follows: the median frequency or average power frequency calculated in real time reaches or exceeds a certain percentage of the target value (such as 85% or 90%), or recovers to a certain range of the corresponding frequency domain characteristic value of the object in a healthy state.

[0064] When the quantitative indicator of muscle strength level is the result of manual muscle strength assessment, the preset standard can be set as: a manual muscle strength assessment of level 3 or above. According to the aforementioned manual muscle strength assessment standard, level 3 indicates that the muscles can complete the full range of motion of the joint against gravity, indicating that the subject has the basic ability to perform functional movements independently under weight reduction conditions, and can meet the prerequisite for entering the second mode.

[0065] In this embodiment of the application, a smooth switching process is set during the mode switching process, which can avoid the feeling of falling or muscle spasms that may be caused by the sudden removal of the auxiliary force of the exoskeleton, so that the patient can smoothly transition to the movement mode dominated by active muscle force.

[0066] In some embodiments of this application, the mode switching management module is further configured to: When the current control mode switches from the first mode to the second mode, the assist torque of the exoskeleton is reduced according to the first ramp function, and the signal strength of the electrical stimulation signal output by the spinal cord stimulation device remains unchanged or increases according to the second ramp function. When the muscle strength level of the active muscle group is detected to reach the preset standard, the current control mode is switched to the second mode.

[0067] It should be noted that the first ramp function can be a decreasing function that linearly reduces the current assist torque to a predetermined threshold (e.g., zero) within a transition time, which can be any set value between 3 and 8 seconds. By controlling the exoskeleton to precisely reduce force according to the first ramp function, the rate of withdrawal of the mechanical support is deterministic and controllable.

[0068] The second ramp function can be an incremental function that slowly increases the intensity of the electrical stimulation signal from its maintenance value during the transition process. The magnitude of this increase can be dynamically calculated based on the muscle strength increase gap. When the electrical stimulation intensity remains constant, the subject's muscle strength will bear an increasing amount of motion load at a constant activation level. At the end of the transition period, if the muscle strength level reaches the preset standard, the mode completely switches, and the exoskeleton immediately enters the support and weight reduction mode.

[0069] Understandably, the above-mentioned ramp function can be replaced by an exponential decay function or an S-curve function.

[0070] In this embodiment, the ramp control strategy makes the timing of the assisted retreat and electrical stimulation coordination deterministic, avoiding motion jitter caused by control command response delay.

[0071] To ensure that the muscle contraction force induced by spinal cord electrical stimulation and the exoskeleton driving force can be effectively superimposed to form the maximum resultant force in the first mode, in some embodiments of this application, the instruction output module is further used for: When outputting the first control command and the second control command, the output time of the first control command is earlier than the output time of the second control command, and the time difference between the two output times is equal to the target duration; wherein, the target duration is equal to the physiological response time when the muscle contraction force induced by electrical stimulation reaches a predetermined threshold.

[0072] It should be noted that the target duration can be pre-calibrated by applying test electrical stimulation to the subject individually and simultaneously measuring the muscle strength rise curve, for example, by taking the average of the time required for muscle strength to rise from the baseline value to the predetermined threshold.

[0073] In some embodiments, the instruction output module may have an internal delay buffer. After issuing the first control command, the second control command is buffered for a target duration before being sent to the exoskeleton. Therefore, when the exoskeleton begins to output assist torque, the muscle contraction force induced by electrical stimulation has already begun to rise after the delay, and the mechanical force is precisely superimposed on the active contraction force. This feedforward timing coupling setting greatly improves the success rate of action initiation and prevents the patient's residual neural pathways from being suppressed due to premature exoskeleton intervention or the assistance from being ineffective due to premature intervention.

[0074] In some embodiments, the target duration can be recalibrated based on changes in the individual's neural conduction velocity and stored in the patient record for system retrieval.

[0075] In some embodiments of this application, the first collaborative control module is used for: By decoding the subject's electroencephalogram (EEG) signals, the movement intention can be identified as stepping with the left leg, stepping with the right leg, standing up, or stopping. Based on the identified movement intention, the electrical stimulation sequence corresponding to the gait phase is determined; The first control command is generated based on the electrical stimulation sequence corresponding to the gait phase.

[0076] It should be noted that EEG decoding can first pass the EEG signal through multi-channel spatial filtering to extract motion-related potentials or event-related desynchronization features, and then use a trained classifier to map the feature vectors into discrete intention categories. These intention categories include: stepping with the left leg, stepping with the right leg, standing up, and stopping.

[0077] Upon recognizing a movement intention, such as "stepping with the left leg," the first collaborative control module retrieves the electrical stimulation sequence template corresponding to the left leg stepping phase from memory. This template defines which stimulation electrodes should output pulses with what parameters at what time, forming a muscle activation sequence consistent with the actual left leg stepping action. The first control command is then assembled into a data packet containing stimulation channels, amplitudes, and trigger times based on the template.

[0078] In this embodiment, by using a method of mapping each type of intention to a specific stimulation template, the patient's active intention can be accurately converted into a spinal cord stimulation pattern with biomechanical significance, thereby improving the coordination and efficiency of lower limb movements. Optionally, a second control command can also be generated synchronously, sharing the same motion intention calculation result with the exoskeleton as needed.

[0079] In some embodiments of this application, the second collaborative control module is used to generate a third control command through the following steps: Calculate in real time the deviation between the characteristic values ​​of the electromyographic signals of the active muscle groups and the target characteristic values ​​of the signals within the current time window; Based on a pre-defined deviation mapping table, the stimulus adjustment amount corresponding to the deviation is determined; wherein the pre-defined deviation mapping table includes the mapping relationship between different deviations and different stimulus adjustment amounts. Based on the stimulation adjustment amount corresponding to the deviation, a third control command is generated so that after the spinal cord stimulation device executes the third control command, the characteristic value of the electromyographic signal of the active muscle group tends to the target characteristic value, or is maintained within a preset range containing the target characteristic value.

[0080] It should be noted that the feature value can reflect the muscle activation level of the agonist muscle group. For example, the feature value can be the root mean square value of the electromyographic signal, but it is not limited to this. The preset interval can be a small range of values ​​with the target feature value as the median. For example, the minimum value of the preset interval can be 90% of the target feature value, and the maximum value of the preset interval can be 110% of the target feature value. Alternatively, the minimum value of the preset interval can be 95% of the target feature value, and the maximum value of the preset interval can be 105% of the target feature value.

[0081] The target feature value is the expected value or target value, which can be dynamically determined based on the object's current muscle activation level.

[0082] The preset deviation mapping table can be constructed during the system setup phase. In some embodiments, the preset deviation mapping table can be generated through calibration.

[0083] For example, when the absolute value of the deviation is within 5%, the stimulus adjustment can be zero; when the absolute value of the deviation is between 5% and 20%, a small stimulus adjustment corresponds to (e.g., increasing or decreasing the stimulus current amplitude by 0.2 mA); when the absolute value of the deviation is greater than 20%, a large stimulus adjustment corresponds to (e.g., increasing or decreasing the stimulus current amplitude by 0.5 mA or more). Optionally, a fuzzy logic rule set can replace the preset deviation mapping table.

[0084] In some embodiments, the third control command generated based on the stimulation adjustment amount changes the degree of stimulation released during the execution of the spinal cord stimulation device, thereby affecting the electromyographic signals of the active muscle group, so that the characteristic values ​​of the electromyographic signals will tend to the target characteristic values, so as to reduce the deviation corresponding to the stimulation adjustment amount.

[0085] For example, if the current calculated deviation is less than 5% of the target feature value, then the corresponding stimulation parameter adjustment is to increase by 3%. After the third control command is generated, the spinal cord stimulation device executes the third control command, and the intensity of the released electrical stimulation will also increase by 3%. As a result, the feature value of the electromyographic signal of the active muscle group will rise, and the deviation calculated again will shrink, that is, the feature value of the electromyographic signal will tend to the target feature value.

[0086] In this embodiment, by continuously outputting third control commands based on deviation mapping, the system can automatically increase the intensity of electrical stimulation when muscle fatigue leads to a decrease in electromyographic characteristic values, and automatically reduce the stimulation when the muscle is overexcited, maintaining the muscle activation level within a preset target window. This effectively avoids muscle overexertion caused by excessive stimulation or movement failure caused by insufficient stimulation.

[0087] In some embodiments of this application, the cooperative control system further includes: an update module, used for: In the second mode, the number of times the target object successfully completes the target action within the first time period is monitored; If the number of occurrences is greater than or equal to the threshold, the target feature value is automatically increased.

[0088] It should be noted that the first time period can be a pre-set time window, such as one hour, one day, or one week. The completion status of the target action can be determined by angle sensors configured at the joints and motion trajectory data on the exoskeleton. The target action can be at least one pre-set action, such as a stepping action or a standing action.

[0089] In some embodiments, a target action can be counted as completed when the knee joint extension angle reaches a preset range and the electromyographic characteristic value remains within the target range.

[0090] The number of times threshold can be a pre-set small value, for example, the number of times threshold can be 8 times. In some embodiments, once the update module detects that the number of times has reached the threshold, it automatically increases the current target feature value by a fixed percentage, such as 5%, and sends the new target feature value to the second collaborative control module 204 as the updated control benchmark.

[0091] In this embodiment, while continuously consolidating the subject's existing abilities, higher demands are gradually placed on muscle output, prompting the subject's nervous system to further readapt and strengthen. This not only improves the rehabilitation effect but also reduces the burden of manually adjusting target feature values.

[0092] To accommodate differences in recovery rates among different patients and prevent the target feature value adjustment rate from becoming disconnected from individual conditions, in some embodiments of this application, the update module is further configured to: The frequency or rate of change in muscle strength level of the monitored subjects successfully completing the target action during the second time period; The number of repetitions threshold is dynamically adjusted based on the rate of change in frequency or the rate of change in muscle strength.

[0093] It should be noted that the second time period can be a pre-set time window, such as one hour, one day, or one week.

[0094] Understandably, if the success rate of the target movement is high or the muscle strength level shows a rapid upward trend during the second time period, the system can lower the original repetition threshold, for example, from 8 repetitions to 5 repetitions, to reduce the dwell time in completing the repetitive movement and thus increase the difficulty of rehabilitation training more quickly. Conversely, if the frequency decreases or the muscle strength level changes slowly, the system can increase the repetition threshold, giving the patient a longer consolidation period.

[0095] In this embodiment, the mechanism of dynamically adjusting the threshold of repetitions allows the rehabilitation process to closely match the patient's actual neuromuscular plasticity, thereby improving the efficiency and safety of rehabilitation training.

[0096] In some embodiments of this application, a fourth control command is used to instruct the exoskeleton to reduce joint impedance to a preset resistance value when it is in a support weight reduction mode, so that the exoskeleton can act as a motion follower to provide an auxiliary force to drive the target joint movement.

[0097] It should be noted that in the second mode, in order to ensure that the exoskeleton provides support and weight reduction without interfering with the patient's intention to move actively, the fourth control command has a specific mode of operation.

[0098] In this embodiment, the reduction of joint impedance can be achieved by adjusting the exoskeleton's actuator controller, for example by setting the joint torque command to zero, or by setting the position gain to zero while retaining only a very low velocity damping term.

[0099] The preset resistance value can correspond to a minimum torque value that is sufficient to offset the patient's leg weight, so that when the patient actively exerts force, the exoskeleton introduces almost no additional resistance and simply follows along, and the patient only feels a light-load exercise environment after weight reduction.

[0100] As an example, taking hip flexion as an example, assuming the subject weighs 70kg, with the lower limb accounting for approximately 16% of the body weight, or about 11.2kg, the center of this mass is located at approximately 40% of the thigh length. If the thigh length is 0.45m, then in a horizontal position, the gravitational torque in the hip flexion direction is approximately 11.2kg × 9.8m / s² × 0.45m × 40% ≈ 19.8Nm. Setting this calculated value as the preset resistance value, the exoskeleton in this mode controls the upper limit of the joint resistance torque to around 19.8Nm, which precisely offsets the leg's own weight. This ensures that when the subject actively flexes the hip, the exoskeleton will neither hinder the movement due to excessive resistance nor reduce the subject's autonomous force application space due to excessive assistance.

[0101] In this embodiment, the exoskeleton will not resist the torque generated by the patient due to mechanical inertia or friction, thereby enabling the patient to use their own muscle strength to complete the full range of motion of the joint in a near-natural manner.

[0102] Based on the same principle as the collaborative control system shown in the embodiments of this application, the embodiments of this application also provide a rehabilitation system, which includes: an exoskeleton, a spinal cord stimulation device, and the collaborative control system as shown in the above embodiments; the exoskeleton and the spinal cord stimulation device are respectively communicatively connected to the collaborative control system; Spinal cord stimulation devices are used for: Receive the first and / or third control commands sent by the collaborative control system; The first electrical stimulation signal is output according to the first control command to activate the active muscle group to generate auxiliary contractile force; The second electrical stimulation signal is output according to the third control command to maintain the muscle activation level of the active muscle group; Exoskeletons are used for: Receive second and / or fourth control commands sent by the coordinated control system; According to the second control command, control the exoskeleton to be in active drive mode; According to the fourth control command, the exoskeleton is controlled to be in a support and weight reduction mode.

[0103] In some embodiments of this application, the rehabilitation system further includes: a data acquisition module communicatively connected to the collaborative control system; The data acquisition module is used to collect the subject's electroencephalogram (EEG) and electromyogram (EMG) signals.

[0104] In this embodiment, spinal cord stimulation and mechanical synergy are integrated, and the synergy mode can be automatically switched according to the muscle strength level. When the muscle strength is severely insufficient, the spinal cord electrical stimulation and exoskeleton active assistance can be triggered simultaneously by the intention to move, forming a synergistic drive of neural stimulation and mechanical force, restoring the patient's active intention to move. After the muscle strength reaches a certain level, the electrical stimulation is adjusted according to electromyographic feedback and the exoskeleton provides weight-reduction support, enabling the patient to complete the movement in a near-natural way of muscle exertion. This effectively avoids the treatment deficiency or over-assistance caused by a single mode and greatly enhances the rehabilitation effect.

[0105] For ease of understanding, a specific example is given below to illustrate the rehabilitation system or collaborative control system provided in the embodiments of this application.

[0106] Paraplegic patient A needs to wear an exoskeleton and spinal cord stimulation device during rehabilitation training, and both devices are connected to the collaborative control system.

[0107] At the start of rehabilitation training, the patient dons the exoskeleton, with the EEG cap and surface electromyography (EMG) electrodes attached to their scalp and other voluntary muscle groups. The muscle strength determination module first assesses the current muscle strength level of the voluntary muscle groups. For example, it calculates the root mean square (RMS) value of the EMG signal within a 400-millisecond sliding time window. The calculation shows that this RMS value is only 15% of the baseline value recorded during the patient's maximum voluntary contraction before the injury. The mode selection module compares this value with a preset threshold of 20%, determines that the current muscle strength level is below the preset threshold, and then outputs a logic switching signal to enable the first collaborative control module, and the system enters the first mode.

[0108] In the first mode, when patient A expresses the intention to "step with the left leg," the EEG cap in the data acquisition module captures the electrical potential changes in the brain regions related to scalp movement in real time and transmits the EEG signals to the first collaborative control module, thereby decoding the movement intention as "stepping with the left leg." Upon recognizing this movement intention, the first collaborative control module retrieves an electrical stimulation sequence template corresponding to the phase of the left-leg stepping gait from its memory. Based on this electrical stimulation sequence template, the first collaborative control module generates a first control command, which specifies in detail the current amplitude and triggering sequence of each stimulation channel to activate the active muscle groups and generate auxiliary contractile force. Simultaneously, according to the same movement intention, the first collaborative control module generates a second control command, which specifies the assist torque curves that the exoskeleton's hip and knee joint actuators should output, so that the exoskeleton is in active drive mode.

[0109] After a period of rehabilitation training, the muscle strength determination module continuously monitored the root mean square (RMS) electromyography (EMG) values ​​of patient A's voluntary muscle groups, showing an upward trend. During a particular rehabilitation session, the muscle strength determination module calculated that the muscle strength level had reached 25% of the maximum voluntary contraction baseline, exceeding the preset threshold. Based on this, the mode selection module determined that it should switch to the second mode and triggered the mode switching management module to run. At the start of the switching process, the mode switching management module controlled the exoskeleton's assist torque to linearly decrease from its current value to zero according to a first ramp function lasting 5 seconds. Simultaneously, the signal strength output by the spinal cord stimulation device maintained the current amplitude unchanged from before the switch. Patient A felt the support force of the exoskeleton gradually weaken, but his muscles were still continuously activated by electrical stimulation, and he began to mobilize more and more of his residual muscle strength to drive his legs. At the end of the ramp descent period, the muscle strength determination module detected that, without the active assistance of the exoskeleton, the RMS value of patient A's voluntary knee extension remained stably above 75% of the target value, reaching the preset standard. The system completely switched to the second mode, and the mode switching management module handed over control to the second collaborative control module.

[0110] Upon entering the second mode, the second collaborative control module switches to closed-loop control based on real-time electromyographic feedback. The second collaborative control module calculates the root mean square value of the electromyographic signal within the current 400-millisecond time window as a feature value and compares it with a preset target feature value to calculate the deviation. For example, when a negative deviation is detected and its absolute value is between 5% and 20%, a preset deviation mapping table is consulted, indicating that the stimulation current amplitude should be increased by 0.2 milliamperes. Based on this, the second collaborative control module generates a third control command and sends it to the spinal cord stimulation device, instructing it to increase the current amplitude output to the corresponding electrode channel by 0.2 milliamperes. This adjustment causes the subsequently acquired electromyographic feature values ​​to rise and approach the target feature value, maintaining the muscle activation level within the allowable range. Simultaneously, the second collaborative control module generates a fourth control command and sends it to the exoskeleton. The exoskeleton becomes a motion follower, no longer actively outputting driving torque, but only providing weight-reduction support.

[0111] In addition, during the second training mode, the update module runs continuously in the background. It monitors patient A's movement performance using joint angle sensors and exoskeleton motion trajectories. When patient A successfully extends their knee to the target angle eight consecutive times in the last ten movement cycles, with the electromyographic (EMG) characteristic value consistently remaining within the target range, the update module automatically increases the target characteristic value by 5% and sends the new target to the second collaborative control module. Subsequently, the second collaborative control module uses a higher expected value as a benchmark for feedback adjustment, gradually increasing the proportion of voluntary force exerted by patient A. Furthermore, the update module continuously analyzes the rate of change in the frequency of patient A's successful completion of the target movement. If it detects a significant increase in the completion frequency and a rapid upward trend in muscle strength, the update module automatically and dynamically reduces the threshold for successful completion from eight to five, accelerating the pace of training difficulty increase and more actively matching the patient's recovery rate.

[0112] In this embodiment, the system seamlessly senses the patient's functional state transition from complete inability to initiate movement to partial recovery of muscle strength, and automatically switches between two distinct strategies: neuro-mechanical synergistic drive and active muscle strength training. This ensures that the treatment intensity is always precisely matched to the patient's real-time capabilities. During the mode transition period, the patient does not experience a sudden loss of mechanical support, movement is smooth and continuous, and psychological safety is enhanced. As the target feature value is automatically increased, the rehabilitation training remains challenging, avoiding a plateau effect and accelerating the process of neuromuscular function reconstruction.

[0113] Based on the same principles as the methods shown in the embodiments of this application, the embodiments of this application also provide an electronic device that includes the collaborative control system provided in the above embodiments.

[0114] In an alternative embodiment, an electronic device, such as Figure 3 As shown, Figure 3 The illustrated electronic device 3000 includes a processor 3001 and a memory 3003. The processor 3001 and the memory 3003 are connected, for example, via a bus 3002. Optionally, the electronic device 3000 may further include a transceiver 3004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 3004 is not limited to one type, and the structure of the electronic device 3000 does not constitute a limitation on the embodiments of this application.

[0115] Processor 3001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 3001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0116] Bus 3002 may include a pathway for transmitting information between the aforementioned components. Bus 3002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 3002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0117] The memory 3003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, other magnetic storage devices, or any other medium capable of carrying or storing computer programs and capable of being read by a computer, without limitation herein.

[0118] The memory 3003 stores computer programs that execute embodiments of this application, and the processor 3001 controls their execution. The processor 3001 executes the computer programs stored in the memory 3003 to implement the processing procedures shown in the aforementioned embodiments of the cooperative control system.

[0119] The terms "first," "second," "third," "fourth," "1," "2," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in a sequence other than that shown in the illustrations or text descriptions.

[0120] It should be understood that although arrows indicate various operation steps in the flowcharts of this application's embodiments, the order in which these steps are implemented is not limited to the order indicated by the arrows. Unless explicitly stated herein, in some implementation scenarios of this application's embodiments, the implementation steps in each flowchart can be executed in other orders as required. Furthermore, some or all steps in each flowchart, based on the actual implementation scenario, may include multiple sub-steps or multiple stages. Some or all of these sub-steps or stages can be executed at the same time, and each sub-step or stage can also be executed at different times. In scenarios where execution times differ, the execution order of these sub-steps or stages can be flexibly configured according to requirements, and this application's embodiments do not limit this.

[0121] The above description is only an optional implementation method for some implementation scenarios of this application. It should be noted that for those skilled in the art, other similar implementation methods based on the technical concept of this application without departing from the technical concept of this application also fall within the protection scope of the embodiments of this application.

Claims

1. A collaborative control system for a spinal cord stimulation device, characterized in that, include: The muscle strength determination module is used to determine the muscle strength level of the agonist muscle groups involved in the target joint movement of an object. The mode selection module is used to determine whether the current control mode is a first mode or a second mode based on the muscle strength level; the muscle strength level in the first mode is lower than the muscle strength level in the second mode. The first collaborative control module is used to generate a first control command and a second control command based on the motion intention of the object in the first mode; the first control command is used to instruct the spinal cord stimulation device to output a first electrical stimulation signal to activate the active muscle group to generate an auxiliary contractile force. The second control command is used to instruct the exoskeleton worn by the object to be in active drive mode; The second collaborative control module is used to generate a third control command and a fourth control command based on the muscle activation level of the active muscle group in the second mode; the third control command is used to instruct the spinal cord stimulation device to output a second electrical stimulation signal to maintain the muscle activation level of the active muscle group; the fourth control command is used to instruct the exoskeleton to be in a support weight reduction mode. The instruction output module is used to send the first control instruction and the third control instruction to the spinal cord stimulation device, and to send the second control instruction and the fourth control instruction to the exoskeleton.

2. The collaborative control system according to claim 1, characterized in that, The collaborative control system also includes: The mode switching management module is used to control the driving force provided by the exoskeleton to decrease by a preset step size during the switching process when the current control mode is switched from the first mode to the second mode, and to control the signal strength of the electrical stimulation signal output by the spinal cord stimulation device to be maintained or adjusted adaptively during the switching process, until the muscle strength level of the active muscle group reaches a preset standard, and then switch to the second mode.

3. The collaborative control system according to claim 2, characterized in that, The mode switching management module is also used for: When the current control mode switches from the first mode to the second mode, the assist torque of the exoskeleton is reduced according to the first ramp function, and the signal strength of the electrical stimulation signal output by the spinal cord stimulation device is kept constant or increased according to the second ramp function. When the muscle strength level of the active muscle group is detected to reach a preset standard, the current control mode is switched to the second mode.

4. The collaborative control system according to claim 1, characterized in that, The instruction output module is also used for: When outputting the first control command and the second control command, the output time of the first control command is earlier than the output time of the second control command, and the time difference between the two output times is equal to the target duration; The target duration is equal to the physiological response time when the muscle contraction force induced by electrical stimulation reaches a predetermined threshold.

5. The collaborative control system according to claim 1, characterized in that, The first collaborative control module is used for: By decoding the object's electroencephalogram (EEG) signals, the movement intention was identified as stepping with the left leg, stepping with the right leg, standing up, or stopping. Based on the identified movement intention, the electrical stimulation sequence corresponding to the gait phase is determined; The first control command is generated based on the electrical stimulation sequence corresponding to the gait phase.

6. The collaborative control system according to claim 1, characterized in that, The second collaborative control module is used to generate the third control command through the following steps: The deviation between the characteristic values ​​of the electromyographic signals of the active muscle group and the target characteristic values ​​within the current time window is calculated in real time. Based on a preset deviation mapping table, the stimulus adjustment amount corresponding to the deviation is determined; wherein, the preset deviation mapping table includes the mapping relationship between different deviations and different stimulus adjustment amounts. Based on the stimulation adjustment amount corresponding to the deviation, the third control command is generated so that after the spinal cord stimulation device executes the third control command, the characteristic value of the electromyographic signal of the active muscle group tends to the target characteristic value, or remains within a preset range containing the target characteristic value.

7. The collaborative control system according to claim 6, characterized in that, The collaborative control system further includes: an update module, used for: In the second mode, the number of times the object successfully completes the target action within the first time period is monitored; If the number of occurrences is greater than or equal to the threshold, the target feature value is automatically increased.

8. The collaborative control system according to claim 7, characterized in that, The update module is also used for: Monitor the frequency or rate of change in muscle strength level of the subject successfully completing the target action during the second time period; The number of repetitions threshold is dynamically adjusted based on the rate of change of frequency or the rate of change of muscle strength.

9. The collaborative control system according to claim 1, characterized in that, The fourth control command is used to instruct the exoskeleton to reduce joint impedance to a preset resistance value when it is in the support and weight reduction mode, so that the exoskeleton can act as a motion follower to provide an auxiliary force to drive the target joint movement.

10. A rehabilitation system, characterized in that, The rehabilitation system includes: an exoskeleton, a spinal cord stimulation device, and a collaborative control system as described in any one of claims 1 to 9; the exoskeleton and the spinal cord stimulation device are respectively communicatively connected to the collaborative control system. The spinal cord stimulation device is used for: Receive the first control command and / or the third control command sent by the cooperative control system; The first electrical stimulation signal is output according to the first control command to activate the active muscle group to generate auxiliary contractile force; The second electrical stimulation signal is output according to the third control command to maintain the muscle activation level of the active muscle group; The exoskeleton is used for: Receive the second control command and / or the fourth control command sent by the cooperative control system; According to the second control command, the exoskeleton is controlled to be in active drive mode; According to the fourth control command, the exoskeleton is controlled to be in a support and weight reduction mode.

11. The rehabilitation system according to claim 10, characterized in that, The rehabilitation system further includes: a data acquisition module that is communicatively connected to the collaborative control system; The data acquisition module is used to acquire the electroencephalogram (EEG) and electromyogram (EMG) signals of the subject.

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