CN113546307A

CN113546307A - Motion adjustment device and method, electronic apparatus, and storage medium

Info

Publication number: CN113546307A
Application number: CN202110800718.9A
Authority: CN
Inventors: 张熹; 马伯志; 眭亚楠; 陆洋; 吕长泉; 李路明
Original assignee: Tsinghua University; Beijing Pins Medical Co Ltd
Current assignee: Tsinghua University; Beijing Pins Medical Co Ltd
Priority date: 2021-07-15
Filing date: 2021-07-15
Publication date: 2021-10-26

Abstract

The present disclosure relates to a motion adjusting device and method, an electronic device and a storage medium. The device includes: a signal processing component, a control component, an electrical stimulation component and an electrode, the signal processing component is used for generating parameter adjustment instructions according to the spinal cord electrical signal; the control component is used for adjusting the instructions according to the parameters, and determining the control parameters; The set control parameter sequence is used to determine the control parameters; the electrical stimulation component is used to generate electrical stimulation according to the control parameters; the electrodes are used to detect spinal cord electrical signals and/or output electrical stimulation. According to the motion adjustment device of the embodiment of the present disclosure, the electric signal of the spinal cord can be collected before the user performs the limb movement through the electrode disposed on the epidural of the spinal cord of the user, so as to determine the parameter adjustment instruction to generate the corresponding electric stimulation, which can reduce the The delay of electrical stimulation improves the accuracy of stimulation, thereby improving the accuracy of the user's movements.

Description

Motion adjustment device and method, electronic apparatus, and storage medium

Technical Field

The present disclosure relates to the field of electronic devices, and in particular, to a motion adjustment apparatus and method, an electronic device, and a storage medium.

Background

Data show that more than 500 million patients with spinal cord injury and more than 1300 million patients with stroke in China have similar diseases which can cause motor dysfunction of the patients, and serious patients can not walk independently or even can not walk with the help of auxiliary tools. Conventional rehabilitation therapies including physical therapy, task therapy, electrical stimulation therapy, instrumental adjuvant therapy, and the like have ceiling effects in which the therapeutic effect is unstable and the function is restored, that is, in the case of irreversible damage to the brain or spinal cord, it is almost impossible to restore to a non-diseased state by the treatment.

The motion signal of the patient is detected through the motion sensor and other devices to judge the motion intention of the patient, and the auxiliary device assists the motion of the patient, so that the patient can have certain motion capability to a certain extent, but the patient loses or is limited in motion capability, the accuracy of the motion intention judging mode based on the detected motion signal is ensured, and the process is that the motion intention is judged after the patient has certain limb movement, so that the assistance of the patient movement has certain time delay.

Disclosure of Invention

The present disclosure provides a motion adjustment apparatus and method, an electronic device, and a storage medium.

According to an aspect of the present disclosure, there is provided a movement adjustment device, the device including: the signal processing assembly is connected to the electrical stimulation assembly and used for receiving spinal cord electrical signals detected by the electrical stimulation assembly through the electrodes and generating parameter adjusting instructions according to the spinal cord electrical signals; the control component is connected to the signal processing component and used for: determining control parameters for controlling the electrical stimulation component according to the parameter adjusting instruction sent by the signal processing component; and/or determining control parameters for controlling the electrical stimulation component according to a preset control parameter time sequence; the electrical stimulation component is respectively connected to the control component and the electrode and is used for generating electrical stimulation according to the control parameters; the electrodes are disposed at a plurality of locations extradurally of the spinal cord of the user for detecting the spinal electrical signals and/or outputting the electrical stimulation.

In one possible implementation, the generating a parameter adjustment instruction according to the spinal cord electrical signal includes: performing feature extraction on the spinal cord electric signals to obtain signal features; determining a target posture and/or a target action of the user according to the signal characteristics; and generating the parameter adjusting instruction according to the target posture and/or the target action of the user.

In one possible implementation, the generating a parameter adjustment instruction according to the spinal cord electrical signal includes: preprocessing the spinal cord electric signals to obtain preprocessed spinal cord electric signals, wherein the preprocessing comprises amplification and/or adaptive filtering; and generating a parameter adjusting instruction according to the preprocessed spinal cord electric signals.

In one possible implementation, the processing to generate the parameter adjustment instructions according to the spinal electrical signals is implemented by a parameter adjustment model, and the signal processing component is further configured to: receiving a sample spinal cord electric signal detected by the electrode, processing the sample spinal cord electric signal through the parameter adjusting model, and generating a sample parameter adjusting instruction, so that the control component determines a sample control parameter according to the sample parameter adjusting instruction, and controls the electric stimulation component to generate electric stimulation; determining the model loss of the parameter adjustment model according to the motion and/or posture of the user under the action of the electric stimulation and the pose error between the target motion and/or target posture of the user; and training the parameter adjustment model according to the model loss.

In one possible implementation, the electrodes include flat plate electrodes and/or columnar electrodes.

In one possible implementation, the spinal electrical signals include spinal epidural evoked compound action potential signals and/or spinal epidural potential signals.

In one possible implementation, the control parameters include at least one of a point in time, a duration, an amplitude, a pulse width, and a frequency at which each electrode applies the electrical stimulation.

According to an aspect of the present disclosure, there is provided a motion adjustment method including: and generating a parameter adjusting instruction according to the spinal cord electric signals detected by the electrodes, enabling the control component to determine control parameters for controlling the electrical stimulation component according to the parameter adjusting instruction, and enabling the electrical stimulation component to generate electrical stimulation according to the control parameters so as to output the electrical stimulation through the electrodes.

In one possible implementation, the generating a parameter adjustment instruction includes: performing feature extraction on the spinal cord electric signals to obtain signal features; determining a target posture and/or a target action of the user according to the signal characteristics; and generating the parameter adjusting instruction according to the target posture and/or the target action of the user.

In one possible implementation, the generating a parameter adjustment instruction includes: preprocessing the spinal cord electric signals to obtain preprocessed spinal cord electric signals, wherein the preprocessing comprises amplification and/or adaptive filtering; and generating a parameter adjusting instruction according to the preprocessed spinal cord electric signals.

In a possible implementation manner, the process of generating the parameter adjustment instruction is implemented by a parameter adjustment model, and the method further includes: receiving a sample spinal cord electric signal detected by the electrode, processing the sample spinal cord electric signal through the parameter adjusting model, and generating a sample parameter adjusting instruction, so that the control component determines a sample control parameter according to the sample parameter adjusting instruction, and controls the electric stimulation component to generate electric stimulation; determining the model loss of the parameter adjustment model according to the motion and/or posture of the user under the action of the electric stimulation and the pose error between the target motion and/or target posture of the user; and training the parameter adjustment model according to the model loss.

According to an aspect of the present disclosure, there is provided an electronic device including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.

According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described method.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.

FIG. 1 shows a block diagram of a motion adjustment apparatus according to an embodiment of the present disclosure;

FIG. 2 shows a schematic view of an electrode according to an embodiment of the present disclosure;

FIG. 3 shows a schematic diagram of a pre-process according to an embodiment of the present disclosure;

FIG. 4 shows a flow diagram of training a parameter tuning model according to an embodiment of the present disclosure;

FIG. 5 shows a schematic diagram of an application of a motion adjustment apparatus according to an embodiment of the present disclosure;

FIG. 6 shows a block diagram of an electronic device according to an embodiment of the disclosure;

fig. 7 shows a block diagram of an electronic device according to an embodiment of the disclosure.

Detailed Description

Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.

Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.

Fig. 1 shows a block diagram of a movement adjustment device according to an embodiment of the present disclosure, which, as shown in fig. 1, includes: a signal processing component 11, a control component 12, an electrical stimulation component 13 and electrodes 14,

the signal processing component 11 is connected to the electrical stimulation component 13, and is configured to receive the spinal electrical signals detected by the electrical stimulation component 13 through the electrodes 14, and generate parameter adjustment instructions according to the spinal electrical signals;

the control component 12, connected to the signal processing component 11, is configured to:

determining control parameters for controlling the electrical stimulation component 13 according to the parameter adjusting instruction sent by the signal processing component 11; and/or

Determining a control parameter for controlling the electrical stimulation component 13 according to a preset control parameter time sequence;

the electrical stimulation component 13 is respectively connected to the control component 12 and the electrode 14, and is used for generating electrical stimulation according to the control parameters;

the electrodes 14 are disposed at various locations outside of the spinal epidural of the user for detecting the spinal electrical signals and/or outputting the electrical stimulation.

According to the motion adjusting device of the embodiment of the disclosure, the electrical signals of the spinal cord can be acquired before the user performs limb actions by the electrode arranged at the epidural part of the spinal cord of the user, so that the parameter adjusting instruction is determined, corresponding electrical stimulation is generated, the time delay of the electrical stimulation can be reduced, the stimulation accuracy is improved, and the action accuracy of the user is further improved.

In one possible implementation, during locomotion, such as walking, the gait cycle is generally divided into a support phase and a swing phase, wherein the swing phase accounts for about 40% of the time of the gait cycle and the support phase accounts for about 60% of the time of the gait cycle. The hip, knee and ankle joints respectively complete corresponding actions in a gait cycle to form a complete gait track. The hip joint flexion, knee joint flexion, ankle joint dorsiflexion and knee joint extension are required in the swing period; the support phase requires hip and knee extension to support the body weight.

In one possible implementation, for the above gait cycle, limb movements are primarily controlled by the lumbosacral segment of the spinal cord, respectively: the L1-L5 segment (lumbar segment), the S1 and the S2 segment (sacral segment) of the spinal cord.

In the example, in the gait cycle, the relevant 6 movements, the muscle groups involved in the movements and the spinal cord nerve root segment controlling each muscle group are: in the hip flexion movement, the participated muscle groups comprise psoas major, ilius, rectus femoris, brachypodium latus, spinal nerve root segments for controlling the movement of psoas major comprise L1, L2, L3 and L4 segments, spinal nerve root segments for controlling the movement of ilius comprise L1, L2, L3 and L4 segments, spinal nerve root segments for controlling the movement of rectus femoris comprise L2, L3 and L4 segments, spinal nerve root segments for controlling the movement of brachyparis brevis and longsystole comprise L2, L3 and L4 segments, and spinal nerve root segments for controlling the movement of tensor fasciae latus comprise L4, L5 and S1 segments; in hip extension action, the participating muscle groups comprise gluteus maximus, biceps femoris longhead, semimembranosus, semitendinosus and gluteus medius, the spinal nerve root segment for controlling gluteus maximus action comprises L5, S1 and S2 segments, the spinal nerve root segment for controlling biceps femoris longhead action comprises L5, S1 and S2 segments, the spinal nerve root segment for controlling semimembraneus action comprises L4, L5, S1 and S2 segments, the spinal nerve root segment for controlling semitendinosus action comprises L4, L5, S1 and S2 segments, and the spinal nerve root segment for controlling gluteus medius action comprises L4, L5 and S1 segments; in knee bending action, the participating muscle groups comprise semitendinosus, semimembranous muscle, biceps femoris longhead and gastrocnemius muscle, the spinal nerve root segment controlling semitendinosus action comprises L4, L5, S1 and S2 segments, the spinal nerve root segment controlling semimembranous muscle action comprises L4, L5, S1 and S2 segments, the spinal nerve root segment controlling biceps femoris longhead action comprises L5, S1 and S2 segments, and the spinal nerve root segment controlling gastrocnemius action comprises S1 and S2 segments; in knee extension, the muscle groups involved include the quadriceps femoris, and the spinal nerve root segments controlling the action of the quadriceps femoris comprise segments L2, L3 and L4; in flexion-ankle (dorsiflexion) action, the muscle groups involved include tibialis anterior, extensor hallucis longus, extensor digitorum longus, the spinal nerve root segment controlling the action of tibialis anterior comprises segments L4, L5, the spinal nerve root segment controlling the action of extensor digitorum longus comprises segments L5, S1, S2, the spinal nerve root segment controlling the action of extensor digitorum longus comprises segments L4, L5, S1, S2; in the ankle extending (plantarflexion) action, the participating muscle groups include gastrocnemius, flexor hallucis longus, tibialis posterior and flexor digitorum longus, the spinal nerve root segment controlling the gastrocnemius action includes segments S1 and S2, the spinal nerve root segment controlling the flexor hallucis action includes segments L5, S1 and S2, the spinal nerve root segment controlling the tibialis posterior action includes segments L5, S1 and S2, and the spinal nerve root segment controlling the flexor digitorum longus action includes segments L5, S1 and S2.

The 6 motions involved in the gait cycle, the muscle groups involved in the motions and the spinal cord nerve root segments controlling the muscle groups are listed above, and the list is merely exemplary, and the gait cycle may involve other motions, muscle groups and spinal cord nerve root segments, which are not listed here. The exercise process may include not only walking, but also other processes, such as standing up, running, jumping, etc., wherein the other processes involve movements, muscle groups, and spinal cord nerve root segments, not to be enumerated here.

In one possible implementation, taking the walking process described above as an example only, each simple action may involve multiple muscle groups, as well as multiple spinal cord nerve root segments that control the muscle groups. Therefore, if the user is a patient with spinal cord injury, stroke, or other diseases, and under the condition of spinal cord function loss or partial loss, external electrical stimulation needs to be performed on each spinal cord nerve root segment to activate the proprioceptive loop, induce the target muscle group to produce the required contraction, and further control each muscle group to complete the corresponding action.

In one possible implementation, to accurately apply the electrical stimulation to make the correct action, the intention of the user is confirmed, i.e., the target action and/or target posture of the user is confirmed, and then the corresponding electrical stimulation is applied to control the muscle group of the user to complete the corresponding action. The external sensor detects the motion signal of the user (for example, detects the velocity, acceleration, etc. of the limbs of the user), and since the detection time is after the motion of the user, the electrical stimulation is output after the processing such as the sensor detection and the processor calculation, etc., the motion delay is inevitably caused. And because the movement function of the user is damaged, an error may exist between the action signal and the real intention of the user, and further an error of outputting the electrical stimulation is caused, so that an error exists between the action made by the user and the real intention of the user.

In one possible implementation manner, in view of the above problems, spinal cord electrical signals may be acquired through electrodes disposed outside the spinal cord epidural of a user (e.g., a patient with impaired motor function), so as to acquire the intention of the user before signals transmitted by the brain reach the muscle group through the spinal cord, and then perform electrical stimulation, so as to accurately control the muscle group to perform actions corresponding to the real intention, and reduce action delay.

In a possible implementation manner, when the electrical stimulation component is controlled, a control parameter time sequence of the electrical stimulation control component can be established, and the electrical stimulation component is controlled through the control parameter time sequence, so that the electrical stimulation component generates electrical stimulation according to a preset time sequence, and each muscle group of a user can be controlled according to the time sequence to complete corresponding actions.

In one possible implementation manner, the electrical stimulation component may generate electrical stimulation based on the control parameters of the control component, and the control component may generate the control parameters according to the intention of the user to complete the control of the electrical stimulation component, so that the electrical stimulation component generates electrical stimulation according to the control parameter timing sequence corresponding to the control parameters, for example, the control parameters include at least one of a time point, a time length, an amplitude, a pulse width and a frequency of applying electrical stimulation to each electrode. The stimulation mode, the stimulation time, the amplitude, the pulse width, the electrode contact, the stimulation duration and the like of the electrical stimulation can be controlled through the control parameters, so that the electrical stimulation component generates electrical stimulation according to a time sequence, and the electrical stimulation is output by clicking. In an example, 1-16 stimulation time sequences can be set for the control component, and each stimulation time sequence can be independently provided with 1-4 sets of control parameters to respectively control each contact of the electrode, so that each contact of the electrode outputs electrical stimulation according to the time sequence corresponding to the control parameters to control the muscle group to complete actions. The control parameters may be set according to parameters such as the motion sequence, the motion intensity, etc. of the muscle groups participating in the motion, and may be repeatedly adjusted until the motion of the user coincides with the target motion under the electrical stimulation. In the example, 3-6 sets of stimulation timing sequences are typically required to perform different movements (flexion and extension of the hip, knee and ankle) during the gait cycle.

Fig. 2 shows a schematic diagram of an electrode according to an embodiment of the present disclosure, as shown in fig. 2, the electrode includes a plate electrode and/or a column electrode, etc., and the electrode may include 8, 16, 24 or 32 contacts, is placed outside the spinal epidural through a surgical implantation method, and covers the spinal nerve root segment controlling the motor function of the lower limb, so as to apply electrical stimulation to the corresponding spinal nerve root segment through each contact. The present disclosure does not limit the type of electrode.

In one possible implementation, the manner of application of the electrical stimulation may be determined based on two ways: one is to determine the actual intention of the user based on the intention of the user, for example, by analyzing the measured electrical spinal signals through the signal processing component, and setting control parameters based on the actual intention, for example, by using a machine learning model or the like, determining the actual intention of the user based on the collected electrical spinal signals, and outputting the control parameters, thereby applying electrical stimulation based on the control parameters. And secondly, the control component can independently generate the electrical stimulation, for example, various intentions and corresponding control parameters can be recorded during debugging, and after the signal processing component determines the intention of the user, the control component can call the recorded control parameters and apply the electrical stimulation according to the recorded control parameters without receiving the control of the signal processing component in real time. In the debugging process, parameters such as stimulation intensity, pulse width, contact point and the like can be gradually adjusted, so that actions of a user after receiving stimulation are in accordance with the intention of the user, the control parameters can be recorded, and when the same intention of the user is detected by a subsequent user, the control parameters can be directly called, and electrical stimulation is generated according to the time sequence of the control parameters.

In one possible implementation, both of the above-described ways of generating electrical stimulation require determining the true intent of the user, i.e., the user's target motion and/or target posture. In an example, the user's true intent may be determined by measuring Spinal electrical signals including Spinal Epidural induced Compound Action Potential signals (ECAP) and/or Spinal Epidural Potential Signals (SEP) by electrodes.

In an example, the electrodes may include multiple contacts, wherein the contacts from which ECAP signals are collected may be different from the contacts from which electrical stimulation is applied to the spinal cord. The ECAP signal is a compound action potential induced when spinal epidural electrical stimulation reaches a certain threshold, for example, a part of contacts may apply electrical stimulation, so that the spinal epidural generates the compound action potential, another part of contacts may collect the compound action potential, and a part of contacts may be included as a reference potential. For example, the contact for applying electrical stimulation may continue to apply electrical stimulation and collect ECAP signals via other free contacts and, after analysis by the signal processing component, may adjust the electrical stimulation by the contact for applying electrical stimulation in accordance with the control parameters to apply electrical stimulation that matches the user's intent such that the user performs an action consistent with his intent under electrical stimulation.

In one possible implementation, the SEP signal is a spontaneous electrical signal collected extradurally from the spinal cord to control the movement of the muscles of the lower extremities, which may be collected by a plurality of contacts of the electrode to determine the intention of the user, and after determining the intention, an electrical stimulus may be emitted by the corresponding contact, for example, if the SEP signal is detected at the spinal cord nerve root segment L1, L2, L3, L4 which controls the movement of the psoas major muscle, it may be determined that the muscle group of the user is about to move, the corresponding electrical stimulus may be applied to the contacts of the L1, L2, L3, L4 segments, and the contacts where the electrical stimulus is applied may be the same as or different from the contacts where the SEP signal is collected.

In one possible implementation, the electrical signal may be interfered by noise when the electrical spinal signal is acquired, so that the acquired electrical spinal signal may be preprocessed, and the parameter adjustment command may be determined according to the preprocessed electrical spinal signal. The generating of parameter adjustment instructions from the spinal cord electrical signals comprises: preprocessing the spinal cord electric signals to obtain preprocessed spinal cord electric signals, wherein the preprocessing comprises amplification and/or adaptive filtering; and generating a parameter adjusting instruction according to the preprocessed spinal cord electric signals.

Fig. 3 shows a schematic diagram of preprocessing according to an embodiment of the present disclosure, and as shown in fig. 3, taking an ECAP signal as an example, the ECAP signal acquired by the electrode may be amplified, and the amplified signal is still a noisy ECAP original signal. The noise in the ECAP signal can be reduced by adaptive filtering, for example, the signal of a noise source can be detected, and the signal of the noise source is filtered out from the ECAP original signal by an adaptive filtering algorithm, for example, the ECAP original signal and the signal of the noise source are subtracted, and the noise signal is filtered out by a minimum mean square error algorithm or a recursive least square algorithm, so as to obtain the preprocessed ECAP signal. And can determine the real intention of the user based on the preprocessed ECAP signals and generate parameter adjustment instructions. The SEP signal may also be preprocessed in the above or other ways, which are not described in detail herein.

In one possible implementation, after obtaining the pre-processed spinal electrical signals, the signals may be analyzed to determine the user's true intent to generate corresponding parameter adjustment instructions. The generating of parameter adjustment instructions from the spinal cord electrical signals comprises: performing feature extraction on the spinal cord electric signals to obtain signal features; determining a target posture and/or a target action of the user according to the signal characteristics; and generating the parameter adjusting instruction according to the target posture and/or the target action of the user.

In one possible implementation, the spinal cord electrical signals collected by each contact may be analyzed, for example, time domain analysis, frequency domain analysis, wavelet analysis, principal component analysis, and the like may be performed on a plurality of spinal cord electrical signals collected by processing, so as to determine signal characteristics, and then a target motion and/or a target posture used may be determined according to the signal characteristics. In an example, different contacts may correspond to different signal channels, and the timing characteristics may be obtained from a time domain analysis of each signal channel. The sequence of conduction of the brain's electrical signals, and thus the user's true intent, can then be determined from the timing characteristics (e.g., based on the sequence of conduction, the sequence of movement of the muscles, and thus the actions the user intends to perform). Further, parameter adjustment instructions may be generated based on the target pose and/or target motion of the user. For example, the parameter adjustment instruction may include an instruction for the control unit to call the recorded control parameter, or may include an instruction for directly adjusting the parameter of the control unit.

In a possible implementation manner, the above-mentioned process of generating the parameter adjustment instruction may be implemented by a parameter adjustment model, which is a machine learning model, such as a neural network model, a support vector machine model, a bayesian model, a decision tree model, etc., and the present disclosure does not limit the type of the parameter adjustment model.

In a possible implementation manner, the model can be written into the signal processing assembly, and when the electrode detects the electrical signal of the spinal cord, the model is directly input, and after the model performs operation and analysis, a parameter adjusting instruction is output to adjust the control parameter of the control assembly, so that the electrical stimulation assembly outputs accurate electrical stimulation.

In one possible implementation, the model may be trained prior to using the parameter tuning model. The signal processing component is further configured to: receiving a sample spinal cord electric signal detected by the electrode, processing the sample spinal cord electric signal through the parameter adjusting model, and generating a sample parameter adjusting instruction, so that the control component determines a sample control parameter according to the sample parameter adjusting instruction, and controls the electric stimulation component to generate electric stimulation; determining the model loss of the parameter adjustment model according to the motion and/or posture of the user under the action of the electric stimulation and the pose error between the target motion and/or target posture of the user; and training the parameter adjustment model according to the model loss.

Fig. 4 illustrates a flow chart for training a parameter adjustment model according to an embodiment of the present disclosure, as shown in fig. 4, sample spinal electrical signals, e.g., ECAP signals or SEP signals, may be acquired to the spinal cord at multiple stages via electrodes. The spinal cord electrical signal of the sample can be preprocessed to obtain the preprocessed spinal cord electrical signal of the sample.

In one possible implementation, a suitable machine learning model may be selected as the parameter adjustment model, for example, any one of a neural network model, a bayesian model, and the like may be selected, and the selection manner is not limited by the present disclosure. After the selection is completed, the pre-processed sample spinal cord electrical signals can be input into a parameter adjustment model. The parameter adjusting model can extract the characteristics of the spinal cord electric signals, and select and operate the extracted characteristics to output a sample signal adjusting instruction. And then the control component can generate control parameters based on the sample signal adjusting instructions, and the electrical stimulation component can generate electrical stimulation based on the control parameters, so that the spinal nerve root segments of the user can be stimulated through the electrodes to act.

In one possible implementation, the electrical stimulation generated under control of the sample signal conditioning instructions may not be an accurate electrical stimulation, and the motion made by the user may have a pose difference from its target motion and/or target pose. Model losses may be determined based on the pose differences (e.g., model losses determined from parameters such as muscle strength, limb angle, walking speed, etc.), and parameters of the parameter adjustment model may be adjusted in a direction that reduces the model losses, such that the parameter adjustment model generates more accurate sample parameter adjustment instructions, thereby reducing the pose differences.

In a possible implementation manner, the parameter adjustment model can be repeatedly trained through the steps, and the training hyper-parameters can be debugged to improve the training efficiency. For example, a hyper-parameter such as a learning rate may be debugged and a parameter of the parameter adjustment model may be adjusted at the hyper-parameter. After multiple times of training, the pose difference can be reduced to an acceptable level, and the trained parameter adjustment model is used for determining a parameter adjustment instruction. The accuracy of the electric stimulation generated under the control of the parameter adjusting instruction is improved, and the action and/or posture of the user under the electric stimulation action is consistent with or close to the real intention.

According to the motion adjusting device of the embodiment of the disclosure, the electrodes arranged outside the dura mater of the spinal cord of the user can be used for collecting spinal cord electric signals before the user performs limb actions, the spinal cord electric signals can be preprocessed, the preprocessed spinal cord electric signals are used for carrying out characteristic analysis, or the preprocessed spinal cord electric signals are input into a parameter adjusting network, so that parameter adjusting instructions are determined, corresponding electric stimulation is generated, the time delay of the electric stimulation can be reduced, the accuracy of the stimulation is improved, and the accuracy of the user actions is further improved.

Fig. 5 is a schematic diagram illustrating an application of the exercise regulation device according to the embodiment of the present disclosure, as shown in fig. 5, the signal processing component and the control component may be integrated, and the electrical stimulation component may be carried by the patient. The signal processing and control components may be integrated into the electrical stimulation component, in which case the spinal electrical signals (ECAP or SEP signals) collected by the electrodes may be transmitted to the electrical stimulation component and may be directly read by the signal processing component. If the above components are not integrated, they may be connected to each other by wired or wireless communication (e.g., bluetooth, rf, etc.).

In one possible implementation, ECAP signals or SEP signals of a plurality of spinal cord nerve root segments of the patient may be acquired by the electrodes and analyzed by the signal processing component to determine the intent of the patient, and then parameter adjustment instructions corresponding to the intent may be output. For example, signal features of the signals may be extracted, and a target posture and/or a target motion of the user may be determined based on the signal features, thereby generating corresponding parameter adjustment instructions. Alternatively, the parameter adjustment model may be written into the signal processing component, and the ECAP signal or the SEP signal may be input into the parameter adjustment model for operation to output the parameter adjustment command.

In one possible implementation, the control unit may determine the control parameters under the action of the parameter adjustment instructions, send the control parameters to the electrical stimulation component to generate electrical stimulation, and output the electrical stimulation through the electrodes to stimulate spinal nerve root segments of the patient so that the muscle groups of the patient make corresponding actions.

In one possible implementation, the movement adjustment device may adjust the parameters in real time based on the patient's intent and generate new electrical stimuli for the user to perform new actions. The real-time performance and accuracy of motion control can be improved, and the motion recovery effect is improved.

In one possible implementation, the present disclosure further provides a motion adjustment method, including: and generating a parameter adjusting instruction according to the spinal cord electric signals detected by the electrodes, enabling the control component to determine control parameters for controlling the electrical stimulation component according to the parameter adjusting instruction, and enabling the electrical stimulation component to generate electrical stimulation according to the control parameters so as to output the electrical stimulation through the electrodes.

It is understood that the above-mentioned method embodiments of the present disclosure can be combined with each other to form a combined embodiment without departing from the logic of the principle, which is limited by the space, and the detailed description of the present disclosure is omitted. Those skilled in the art will appreciate that in the above methods of the specific embodiments, the specific order of execution of the steps should be determined by their function and possibly their inherent logic.

In some embodiments, functions of or modules included in the apparatus provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.

Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the above-mentioned method. The computer readable storage medium may be a non-volatile computer readable storage medium.

An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.

The embodiments of the present disclosure also provide a computer program product, which includes computer readable code, and when the computer readable code runs on a device, a processor in the device executes instructions for implementing the image processing method provided in any one of the above embodiments.

The embodiments of the present disclosure also provide another computer program product for storing computer readable instructions, which when executed cause a computer to perform the operations of the image processing method provided in any of the above embodiments.

The electronic device may be provided as a terminal, server, or other form of device.

Fig. 6 illustrates a block diagram of an electronic device 800 in accordance with an embodiment of the disclosure. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like terminal.

Referring to fig. 6, electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.

The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense an edge of a touch or slide action, but also detect a duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 800 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the electronic device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a non-transitory computer-readable storage medium, such as the memory 804, is also provided that includes computer program instructions executable by the processor 820 of the electronic device 800 to perform the above-described methods.

Fig. 7 illustrates a block diagram of an electronic device 1900 in accordance with an embodiment of the disclosure. For example, the electronic device 1900 may be provided as a server. Referring to fig. 7, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.

The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output (I/O) interface 1958. The electronic device 1900 may operate based on an operating system, such as Windows Server, stored in memory 1932^TM，Mac OS X^TM，Unix^TM,Linux^TM，FreeBSD^TMOr the like.

In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the electronic device 1900 to perform the above-described methods.

The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.

The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.

The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.

The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).

Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The computer program product may be embodied in hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.

Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A motion regulating device, characterized in that the device comprises: a signal processing component, a control component, an electrical stimulation component and an electrode,

the signal processing component, connected to the electrical stimulation component, for receiving the spinal cord electrical signals detected by the electrical stimulation component through the electrodes, and generating parameter adjustment instructions according to the spinal cord electrical signals;

The control component, connected to the signal processing component, is used for:

determining control parameters for controlling the electrical stimulation component according to the parameter adjustment instructions sent by the signal processing component; and/or

determining the control parameters for controlling the electrical stimulation component according to the preset control parameter sequence;

The electrical stimulation component is connected to the control component and the electrode, respectively, for generating electrical stimulation according to the control parameter;

The electrodes are disposed at multiple locations on the spinal cord epidural of the user for detecting the spinal cord electrical signals and/or outputting the electrical stimulation.

2. The device according to claim 1, wherein the generating a parameter adjustment instruction according to the spinal cord electrical signal comprises:

Feature extraction is performed on the spinal cord electrical signal to obtain signal features;

Determine the target posture and/or target action of the user according to the signal characteristics;

The parameter adjustment instruction is generated according to the target posture and/or target action of the user.

3. The device according to claim 1, wherein the generating a parameter adjustment instruction according to the spinal cord electrical signal comprises:

Preprocessing the spinal cord electrical signal to obtain a preprocessed spinal cord electrical signal, the preprocessing including amplification and/or adaptive filtering;

According to the preprocessed spinal cord electrical signals, parameter adjustment instructions are generated.

4. The device according to claim 1, wherein the process of generating a parameter adjustment instruction according to the spinal cord electrical signal is realized by a parameter adjustment model,

The signal processing component is also used for:

Receive the sample spinal cord electrical signal detected by the electrode, process it through the parameter adjustment model, and generate a sample parameter adjustment instruction, so that the control component determines the sample control parameter according to the sample parameter adjustment instruction, and controls the electrical signal. The stimulation component generates electrical stimulation;

Determine the model loss of the parameter adjustment model according to the user's action and/or posture under the action of electrical stimulation and the pose error between the user's target action and/or target posture;

The parameter adjustment model is trained according to the model loss.

5. The device according to claim 1, wherein the electrodes comprise flat electrodes and/or columnar electrodes.

6. The device according to claim 1, wherein the spinal cord electrical signal comprises a spinal cord epidural evoked compound action potential signal and/or a spinal cord epidural potential signal.

7 . The device according to claim 1 , wherein the control parameters include at least one of a time point, duration, amplitude, pulse width and frequency when each electrode applies electrical stimulation. 8 .

8. A movement adjustment method, is characterized in that, comprises:

According to the spinal cord electrical signal detected by the electrode according to any one of claims 1-7, a parameter adjustment instruction is generated, so that the control component determines a control parameter for controlling the electrical stimulation component according to the parameter adjustment instruction, and makes the electrical stimulation The component generates electrical stimulation according to the control parameters to output the electrical stimulation through the electrodes.

9. An electronic device, characterized in that, comprising:

processor;

memory for storing processor-executable instructions;

wherein the processor is configured to invoke the memory-stored instructions to perform the method of claim 8 .

10. A computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions implement the method of claim 8 when executed by a processor.