Multi-frequency signal generation method and device for collaborative muscle recovery, equipment and storage medium

Abstract

The invention relates to the technical field of signal processing, and provides a multi-frequency signal generation method and device for cooperatively recovering nerve and muscle tissues, equipment and a storage medium. The multi-frequency signal generation method for synergistically recovering nerve and muscular tissues comprises the following steps: matching at least two electrical stimulation signals with different frequencies according to a current state and a recovery demand of a target muscle; according to the electromyographic signals fed back in real time, the intensity and duration of the matched frequency signals are adjusted, and a composite multi-frequency signal sequence is generated; determining a recovery stage of the target muscle according to the reaction characteristics of the target muscle; and dynamically adjusting parameters of each frequency signal in the multi-frequency signal sequence according to the recovery stage. Combination and synergistic effects of multi-frequency signals can be adjusted according to muscle recovery requirements and different recovery stages, and the muscle recovery effect is improved.

Description

Technical Field

[0001] The present invention relates to the field of signal processing technology, and in particular to a method, device, equipment and storage medium for generating a multi-frequency signal for coordinated muscle recovery. Background Art

[0002] Muscle rehabilitation is a key means of treating muscle atrophy, weakness and motor dysfunction. Traditional electrical stimulation technology has been widely used in the field of rehabilitation to promote muscle contraction, increase muscle strength and improve blood circulation. However, existing electrical stimulation treatment methods are mostly single-frequency current stimulation, and usually use a fixed frequency to electrically stimulate muscles, which may not fully meet the needs of different muscle groups at different recovery stages, resulting in limited treatment effects. Modern rehabilitation medicine research shows that muscle recovery not only depends on the adjustment of the stimulation frequency, but is also closely related to the dynamic changes of the stimulation frequency and the synergistic effect of different frequencies. Different frequency combinations can produce different stimulation effects on muscles at different time periods, thereby accelerating the recovery process. The existing technology lacks a technical means that can flexibly generate multi-frequency signals according to different stages of muscle recovery to synergize to improve the effect of muscle rehabilitation. Summary of the invention

[0003] In view of this, the embodiments of the present application provide a multi-frequency signal generation method, device, equipment and storage medium for collaborative muscle recovery, which can adjust the combination and synergy of multi-frequency signals according to the muscle recovery needs and different recovery stages, thereby improving the muscle rehabilitation effect.

[0004] In a first aspect, an embodiment of the present application provides a method for generating a multi-frequency signal for collaborative muscle recovery, comprising: matching at least two electrical stimulation signals of different frequencies according to the current state and recovery requirements of the target muscle; adjusting the intensity and duration of each matched frequency signal according to real-time feedback of the electromyographic signal to generate a composite multi-frequency signal sequence; determining the recovery stage of the target muscle according to the reaction characteristics of the target muscle; and dynamically adjusting the parameters of each frequency signal in the multi-frequency signal sequence according to the recovery stage.

[0005] In the second aspect, an embodiment of the present application provides a multi-frequency signal generating device for collaborative muscle recovery, comprising: a matching module for matching at least two electrical stimulation signals of different frequencies according to the current state and recovery requirements of the target muscle; a generating module for adjusting the intensity and duration of each matched frequency signal according to the real-time feedback electromyographic signal to generate a composite multi-frequency signal sequence; a determining module for determining the recovery stage of the target muscle according to the reaction characteristics of the target muscle; and an adjusting module for dynamically adjusting the parameters of each frequency signal in the multi-frequency signal sequence according to the recovery stage.

[0006] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0007] Memory and processing modules;

[0008] The memory is used to store computer programs;

[0009] The processing module is used to execute the computer program and implement the steps of the multi-frequency signal generation method for collaborative muscle recovery as described in the first aspect above when executing the computer program.

[0010] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program;

[0011] When the computer program is executed by one or more processing modules, the one or more processing modules execute the steps of the multi-frequency signal generation method for coordinated muscle recovery according to the first aspect above.

[0012] The embodiments of the present application provide a method, device, equipment and storage medium for generating a multi-frequency signal for collaborative muscle recovery, wherein the method for generating a multi-frequency signal for collaborative muscle recovery includes: matching at least two electrical stimulation signals of different frequencies according to the current state and recovery requirements of the target muscle; adjusting the intensity and duration of each matched frequency signal according to the real-time feedback electromyographic signal to generate a composite multi-frequency signal sequence; determining the recovery stage of the target muscle according to the reaction characteristics of the target muscle; and dynamically adjusting the parameters of each frequency signal in the multi-frequency signal sequence according to the recovery stage. The combination and synergy of the multi-frequency signals can be adjusted according to the recovery requirements and different recovery stages of the muscles to improve the muscle rehabilitation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0014] Figure 1 A schematic diagram of a flow chart of a method for generating a multi-frequency signal for collaborative muscle recovery provided in an embodiment of the present application;

[0015] Figure 2 Provided in the embodiments of this application Figure 1 Schematic diagram of the specific implementation process of S102;

[0016] Figure 3 A schematic diagram of the structure of a multi-frequency signal generating device for collaborative muscle recovery provided in an embodiment of the present application;

[0017] Figure 4A schematic block diagram of a multi-frequency signal generating device for collaborative muscle recovery provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0020] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0021] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0022] The technical solution provided by this application will be described in detail below with reference to the accompanying drawings.

[0023] See also Figure 1 , Figure 1 The flowchart of the multi-frequency signal generation method for collaborative muscle recovery provided in the embodiment of the present application is shown in FIG. The multi-frequency signal generation method for collaborative muscle recovery provided in the embodiment of the present application is implemented by a multi-frequency signal generation device for collaborative muscle recovery. The embodiment of the present application does not impose any limitation on the multi-frequency signal generation device for collaborative muscle recovery. Specifically, Figure 1 As shown, the method for generating a multi-frequency signal for collaborative muscle recovery includes steps S101 to S104. The details are as follows:

[0024] S101: Match at least two electrical stimulation signals of different frequencies according to the current state and recovery requirements of the target muscle.

[0025] In the present application, the state of the target muscle includes the degree of fatigue, and the recovery demand includes improving the performance of the muscle. Electrical stimulation signals of different frequencies can be used to activate different types of muscle fibers, thereby improving the performance of the muscle and promoting its recovery. Common electrical stimulation signal frequencies include low-frequency electrical stimulation signals for stimulating slow muscle fibers and high-frequency electrical stimulation signals for stimulating fast muscle fibers. Specifically, if the degree of fatigue of the target muscle is high and the recovery demand is for muscles that require long-term recovery, it is necessary to match at least two low-frequency electrical stimulation signals of different frequencies to promote muscle recovery and endurance improvement and reduce fatigue; if the degree of fatigue of the target muscle is low and the recovery demand is to improve muscle performance, it is necessary to match at least two high-frequency electrical stimulation signals of different frequencies to increase the explosiveness and strength of the muscle.

[0026] S102: According to the real-time feedback electromyographic signal, the intensity and duration of each matched frequency signal are adjusted to generate a composite multi-frequency signal sequence.

[0027] In the present application, the active state of the target muscle is captured according to the electromyographic signal of real-time feedback, and these electromyographic signals can reflect the activation degree (such as muscle contraction degree) of the target muscle, and the intensity and duration of each frequency signal matched are adjusted according to the activation degree of the target muscle, and each frequency signal after adjustment is superimposed into a composite signal sequence. The superposition of these frequency signals can make the electrical stimulation signal stimulate the target muscle at different times and intensities, and then achieve the best adjustment to the muscle state. Specifically, the composite multi-frequency signal sequence can be a composite waveform formed by the electrical stimulation signal of multiple frequencies according to a certain timing and intensity superposition, and the goal is to improve the recovery of the muscle, increase the endurance of the muscle, or adjust the activation state of the muscle through these composite multi-frequency signal sequences.

[0028] For example, Figure 2 As shown, Figure 2 Provided in the embodiments of this application Figure 1 The specific implementation flow diagram of S102 is shown in FIG. Figure 2 It can be seen that S102 includes:

[0029] S1021: Acquire the characteristic value of the electromyographic signal fed back in real time, determine the intensity adjustment factor of each frequency signal, and adjust the intensity of each frequency signal according to each intensity adjustment factor.

[0030] The intensity adjustment factor is expressed as:

[0031] Among them, E max is the maximum value of the EMG signal activation level, k1 is the intensity proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

[0032] S1022: Analyze the activity pattern of the real-time feedback electromyographic signal, determine the time adjustment factor of each frequency signal, and adjust the duration of each frequency signal according to each time adjustment factor.

[0033] The time adjustment factor is expressed as:

[0034] Among them, E max is the maximum value of the EMG signal activation level, k2 is the time proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

[0035] S1023: Superimpose the adjusted frequency signals to obtain a composite multi-frequency signal sequence.

[0036] The above-mentioned method dynamically adjusts the electrical stimulation signal according to the real-time state and needs of the muscles to ensure the optimal combination of the intensity, duration and frequency of the electrical stimulation signal, thereby improving the effect of electrical stimulation and promoting muscle recovery or improving its performance.

[0037] S103: Determine the recovery phase of the target muscle according to the response characteristics of the target muscle.

[0038] In the process of electrical muscle stimulation based on the above-mentioned composite multi-frequency signal sequence, the current recovery stage of the target muscle is further determined according to the response characteristics of the target muscle, so as to adjust the parameters of the signal to achieve more accurate stimulation and improve the muscle recovery effect.

[0039] In the present application, the reaction characteristics include frequency characteristics. According to the reaction characteristics of the target muscle, the recovery stage of the target muscle is determined, including: acquiring the electromyographic signal of the target muscle, performing spectral analysis on the electromyographic signal to obtain the frequency characteristics of the target muscle, and determining the recovery stage of the target muscle according to the frequency characteristics.

[0040] In the present application, the judgment of the recovery stage mainly depends on the frequency characteristics, which include intermediate frequency, average frequency or peak frequency. The recovery stage of the target muscle includes early recovery stage, mid-term recovery stage and late recovery stage; the recovery stage of the target muscle is determined according to the frequency characteristics, including: if the frequency characteristic is greater than or equal to the first preset frequency threshold, it is determined that the target muscle is in the early recovery stage; if the frequency characteristic is less than the first preset frequency threshold and greater than the second preset frequency threshold, it is determined that the target muscle is in the mid-term recovery stage; if the frequency characteristic is less than or equal to the second preset frequency threshold, it is determined that the target muscle is in the late recovery stage.

[0041] S104: Dynamically adjust the parameters of each frequency signal in the multi-frequency signal sequence according to the recovery stage.

[0042] The muscle recovery stage is related to the frequency distribution, the amplitude of each frequency, and the phase relationship between each frequency signal. For example, in the early recovery stage, a lower frequency stimulation signal is usually required, while in the late recovery stage, a high frequency signal can be increased to improve the recovery effect. For another example, in the early recovery stage, the amplitude is small to avoid overstimulation; in the late recovery stage, the amplitude can be increased to provide stronger stimulation to help the muscle increase strength. The adjustment of the phase generally affects the synchronization of the signal and the interaction between the signals. In different recovery stages, it is necessary to optimize the muscle response by adjusting the phase relationship between the signals.

[0043] In the present application, the parameters of each frequency signal include: the frequency distribution of the signal, the amplitude of each frequency signal, and the phase relationship between each frequency signal.

[0044] Exemplarily, the frequency distribution adjustment process of the signal is expressed as: in, is the preset reference frequency, α is an adjustment parameter used to control the amplitude of frequency change, R(t) is the recovery stage function, which is dynamically adjusted according to the recovery progress. In the early stage, R(t) is small, in the middle stage, R(t) gradually increases, and in the late stage, R(t) reaches a larger value. i represents the i-th signal.

[0045] The amplitude adjustment process of each frequency signal is expressed as: in, is the preset reference amplitude, and β is the adjustment parameter used to control the amplitude adjustment.

[0046] The phase relationship adjustment process between the frequency signals is expressed as: in, is the preset reference phase, and γ is an adjustment parameter used to control the amplitude of phase change.

[0047] According to the recovery stage, the parameters of each frequency signal in the multi-frequency signal sequence are dynamically adjusted, which can be comprehensively expressed as:

[0048] By combining and adjusting frequency, amplitude and phase, the parameters of the multi-frequency signal sequence are dynamically changed to optimize the muscle recovery process.

[0049] Through the above analysis, it can be known that the multi-frequency signal generation method for collaborative muscle recovery provided by the embodiment of the present application includes: matching at least two electrical stimulation signals of different frequencies according to the current state and recovery requirements of the target muscle; adjusting the intensity and duration of each matched frequency signal according to the real-time feedback electromyographic signal to generate a composite multi-frequency signal sequence; determining the recovery stage of the target muscle according to the reaction characteristics of the target muscle; and dynamically adjusting the parameters of each frequency signal in the multi-frequency signal sequence according to the recovery stage. It is possible to adjust the combination and synergy of multi-frequency signals according to the recovery requirements and different recovery stages of the muscle to improve the muscle rehabilitation effect.

[0050] See also Figure 3 As shown, Figure 3 This is a schematic diagram of the structure of a multi-frequency signal generating device for collaborative muscle recovery provided in an embodiment of the present application. Figure 3 It can be seen that the multi-frequency signal generating device 300 for collaborative muscle recovery provided in the embodiment of the present application includes:

[0051] A matching module 310, for matching at least two electrical stimulation signals of different frequencies according to the current state and recovery requirements of the target muscle;

[0052] The generating module 320 is used to adjust the intensity and duration of each matched frequency signal according to the real-time feedback electromyographic signal to generate a composite multi-frequency signal sequence;

[0053] A determination module 330, for determining a recovery stage of the target muscle according to the reaction characteristics of the target muscle;

[0054] The adjustment module 340 is used to dynamically adjust the parameters of each frequency signal in the multi-frequency signal sequence according to the recovery stage.

[0055] In one embodiment, the generating module 320 includes:

[0056] The first adjustment unit is used to obtain the characteristic value of the electromyographic signal fed back in real time, determine the intensity adjustment factor of each frequency signal, and adjust the intensity of each frequency signal according to each intensity adjustment factor;

[0057] The second adjustment unit is used to analyze the activity pattern of the real-time feedback electromyographic signal, determine the time adjustment factor of each frequency signal, and adjust the duration of each frequency signal according to each time adjustment factor;

[0058] The obtaining unit is used to superimpose the adjusted frequency signals to obtain a composite multi-frequency signal sequence.

[0059] In one embodiment, the intensity adjustment factor is expressed as:

[0060] Among them, E maxis the maximum value of the EMG signal activation level, k1 is the intensity proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

[0061] In one embodiment, the time adjustment factor is expressed as:

[0062] Among them, E max is the maximum value of the EMG signal activation level, k2 is the time proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

[0063] In one embodiment, the determination module 330 is specifically configured to:

[0064] The electromyographic signal of the target muscle is acquired, and the frequency spectrum of the electromyographic signal is analyzed to obtain the frequency characteristics of the target muscle, and the recovery stage of the target muscle is determined according to the frequency characteristics.

[0065] In one embodiment, the frequency feature includes an intermediate frequency, an average frequency or a peak frequency, and the recovery stage of the target muscle includes an early recovery stage, a mid-term recovery stage and a late recovery stage; the determination module 330 includes:

[0066] a first determining unit, configured to determine that the target muscle is in an early recovery stage if the frequency characteristic is greater than or equal to a first preset frequency threshold;

[0067] a second determination unit, configured to determine that the target muscle is in a mid-term recovery stage if the frequency characteristic is less than a first preset frequency threshold and greater than a second preset frequency threshold;

[0068] The third determination unit is used to determine that the target muscle is in a late recovery stage if the frequency characteristic is less than or equal to a second preset frequency threshold.

[0069] In one embodiment, the parameters of each frequency signal include: frequency distribution of the signal, amplitude of each frequency signal, and phase relationship between each frequency signal.

[0070] It should be noted that the specific implementation process of the above modules or units can refer to the specific implementation process of each step in the previous method embodiment, which will not be repeated here.

[0071] See also Figure 4 As shown, Figure 4 A schematic block diagram of a multi-frequency signal generating device for collaborative muscle recovery provided in an embodiment of the present application.

[0072] Exemplarily, the multi-frequency signal generating device 400 for coordinated muscle recovery includes a processing module 410 and a memory 420 .

[0073] Exemplarily, the processing module 410 and the memory 420 are connected via a bus 430 , and the bus 430 is, for example, an I2C (Inter-integrated Circuit) bus.

[0074] Specifically, the processing module 410 may be a micro-controller unit (MCU), a central processing unit (CPU) or a digital signal processing module (DSP).

[0075] Specifically, the memory 420 may be a Flash chip, a read-only memory (ROM) disk, an optical disk, a USB flash drive, or a mobile hard disk.

[0076] The processing module 410 is used to run the computer program stored in the memory 420, and implement the steps of the multi-frequency signal generation method for collaborative muscle recovery when executing the computer program.

[0077] Exemplarily, the processing module 410 is used to run a computer program stored in the memory 420, and implement the following steps when executing the computer program:

[0078] Matching at least two electrical stimulation signals of different frequencies according to the current state and recovery needs of the target muscles;

[0079] According to the real-time feedback of electromyographic signals, the intensity and duration of each matching frequency signal are adjusted to generate a composite multi-frequency signal sequence;

[0080] Determine the recovery phase of the target muscle based on its response characteristics;

[0081] According to the recovery stage, the parameters of each frequency signal in the multi-frequency signal sequence are dynamically adjusted.

[0082] In one embodiment, the intensity and duration of each matched frequency signal are adjusted according to the real-time feedback electromyographic signal to generate a composite multi-frequency signal sequence, including:

[0083] Acquire the characteristic value of the electromyographic signal fed back in real time, determine the intensity adjustment factor of each frequency signal, and adjust the intensity of each frequency signal according to each intensity adjustment factor;

[0084] Analyze the activity pattern of the real-time feedback electromyographic signal, determine the time adjustment factor of each frequency signal, and adjust the duration of each frequency signal according to each time adjustment factor;

[0085] The adjusted frequency signals are superimposed to obtain a composite multi-frequency signal sequence.

[0086] In one embodiment, the intensity adjustment factor is expressed as:

[0087] Among them, E max is the maximum value of the EMG signal activation level, k1 is the intensity proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

[0088] In one embodiment, the time adjustment factor is expressed as:

[0089] Among them, E max is the maximum value of the EMG signal activation level, k2 is the time proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

[0090] In one embodiment, the response characteristic includes a frequency characteristic, and determining the recovery stage of the target muscle according to the response characteristic of the target muscle includes:

[0091] The electromyographic signal of the target muscle is acquired, and the spectrum analysis of the electromyographic signal is performed to obtain the frequency characteristics of the target muscle, and the recovery stage of the target muscle is determined according to the frequency characteristics.

[0092] In one embodiment, the frequency characteristics include a medium frequency, an average frequency or a peak frequency, and the recovery stage of the target muscle includes an early recovery stage, a mid-term recovery stage and a late recovery stage; determining the recovery stage of the target muscle according to the frequency characteristics includes:

[0093] If the frequency characteristic is greater than or equal to a first preset frequency threshold, determining that the target muscle is in an early recovery stage;

[0094] If the frequency characteristic is less than the first preset frequency threshold and greater than the second preset frequency threshold, it is determined that the target muscle is in the mid-term recovery stage;

[0095] If the frequency characteristic is less than or equal to the second preset frequency threshold, it is determined that the target muscle is in a late recovery stage.

[0096] In one embodiment, the parameters of each frequency signal include: frequency distribution of the signal, amplitude of each frequency signal, and phase relationship between each frequency signal.

[0097] The specific principles and implementation methods of the multi-frequency signal generation device for collaborative muscle restoration provided in the embodiment of the present application are similar to those of the multi-frequency signal generation method for collaborative muscle restoration in the aforementioned embodiment, and will not be repeated here.

[0098] The embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by the processing module, the processing module implements the following steps:

[0099] Matching at least two electrical stimulation signals of different frequencies according to the current state and recovery needs of the target muscles;

[0100] According to the real-time feedback of electromyographic signals, the intensity and duration of each matching frequency signal are adjusted to generate a composite multi-frequency signal sequence;

[0101] Determine the recovery phase of the target muscle based on its response characteristics;

[0102] According to the recovery stage, the parameters of each frequency signal in the multi-frequency signal sequence are dynamically adjusted.

[0103] In one embodiment, the intensity and duration of each matched frequency signal are adjusted according to the real-time feedback electromyographic signal to generate a composite multi-frequency signal sequence, including:

[0104] Acquire the characteristic value of the electromyographic signal fed back in real time, determine the intensity adjustment factor of each frequency signal, and adjust the intensity of each frequency signal according to each intensity adjustment factor;

[0105] Analyze the activity pattern of the real-time feedback electromyographic signal, determine the time adjustment factor of each frequency signal, and adjust the duration of each frequency signal according to each time adjustment factor;

[0106] The adjusted frequency signals are superimposed to obtain a composite multi-frequency signal sequence.

[0107] In one embodiment, the intensity adjustment factor is expressed as:

[0108] Among them, E max is the maximum value of the EMG signal activation level, k1 is the intensity proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

[0109] In one embodiment, the time adjustment factor is expressed as:

[0110] Among them, E max is the maximum value of the EMG signal activation level, k2 is the time proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

[0111] In one embodiment, the response characteristic includes a frequency characteristic, and determining the recovery stage of the target muscle according to the response characteristic of the target muscle includes:

[0112] The electromyographic signal of the target muscle is acquired, and the spectrum analysis of the electromyographic signal is performed to obtain the frequency characteristics of the target muscle, and the recovery stage of the target muscle is determined according to the frequency characteristics.

[0113] In one embodiment, the frequency characteristics include a medium frequency, an average frequency or a peak frequency, and the recovery stage of the target muscle includes an early recovery stage, a mid-term recovery stage and a late recovery stage; determining the recovery stage of the target muscle according to the frequency characteristics includes:

[0114] If the frequency characteristic is greater than or equal to a first preset frequency threshold, determining that the target muscle is in an early recovery stage;

[0115] If the frequency characteristic is less than the first preset frequency threshold and greater than the second preset frequency threshold, it is determined that the target muscle is in the mid-term recovery stage;

[0116] If the frequency characteristic is less than or equal to the second preset frequency threshold, it is determined that the target muscle is in a late recovery stage.

[0117] In one embodiment, the parameters of each frequency signal include: frequency distribution of the signal, amplitude of each frequency signal, and phase relationship between each frequency signal.

[0118] The computer-readable storage medium may be an internal storage unit of the multi-frequency signal generating device for collaborative muscle restoration in the aforementioned embodiment, such as a hard disk or memory of the multi-frequency signal generating device for collaborative muscle restoration. The computer-readable storage medium may also be an external storage device of the multi-frequency signal generating device for collaborative muscle restoration, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc., equipped on the multi-frequency signal generating device for collaborative muscle restoration.

[0119] It should be understood that the terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0120] It will also be understood that the term "and / or" used in this application and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0121] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for generating a multi-frequency signal for collaborative muscle recovery, characterized in that: include: Matching at least two electrical stimulation signals of different frequencies according to the current state and recovery needs of the target muscles; According to the real-time feedback of electromyographic signals, the intensity and duration of each matching frequency signal are adjusted to generate a composite multi-frequency signal sequence; Determining the recovery phase of the target muscle according to the reaction characteristics of the target muscle; According to the recovery stage, the parameters of each frequency signal in the multi-frequency signal sequence are dynamically adjusted.

2. The method for generating a multi-frequency signal for collaborative muscle recovery according to claim 1, characterized in that: The method of adjusting the intensity and duration of each frequency signal matched according to the real-time feedback electromyographic signal to generate a composite multi-frequency signal sequence includes: Acquire the characteristic value of the electromyographic signal fed back in real time, determine the intensity adjustment factor of each frequency signal, and adjust the intensity of each frequency signal according to each intensity adjustment factor; Analyze the activity pattern of the electromyographic signal fed back in real time, determine the time adjustment factor of each frequency signal, and adjust the duration of each frequency signal according to each time adjustment factor; The adjusted frequency signals are superimposed to obtain the composite multi-frequency signal sequence.

3. The method for generating a multi-frequency signal for collaborative muscle recovery according to claim 2, characterized in that: The intensity adjustment factor is expressed as: Among them, E max is the maximum value of the EMG signal activation level, k1 is the intensity proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

4. The method for generating a multi-frequency signal for collaborative muscle recovery according to claim 2, characterized in that: The time adjustment factor is expressed as: Among them, E max is the maximum value of the EMG signal activation level, k2 is the time proportional coefficient, and E(t) is the characteristic value of the EMG signal at time t.

5. The method for generating a multi-frequency signal for collaborative muscle recovery according to claim 1, characterized in that: The reaction characteristic includes a frequency characteristic, and determining the recovery stage of the target muscle according to the reaction characteristic of the target muscle includes: The electromyographic signal of the target muscle is acquired, and a spectrum analysis is performed on the electromyographic signal to obtain a frequency characteristic of the target muscle, and the recovery stage of the target muscle is determined according to the frequency characteristic.

6. The method for generating a multi-frequency signal for collaborative muscle recovery according to claim 5, characterized in that: The frequency characteristics include a medium frequency, an average frequency or a peak frequency, and the recovery stage of the target muscle includes an early recovery stage, a mid-term recovery stage and a late recovery stage; and determining the recovery stage of the target muscle according to the frequency characteristics includes: If the frequency characteristic is greater than or equal to a first preset frequency threshold, determining that the target muscle is in the early recovery stage; If the frequency characteristic is less than the first preset frequency threshold and greater than the second preset frequency threshold, it is determined that the target muscle is in the mid-term recovery stage; If the frequency characteristic is less than or equal to the second preset frequency threshold, it is determined that the target muscle is in the late recovery stage.

7. The method for generating a multi-frequency signal for collaborative muscle recovery according to claim 1, characterized in that: The parameters of each frequency signal include: frequency distribution of the signal, amplitude of each frequency signal and phase relationship between each frequency signal.

8. A multi-frequency signal generating device for coordinated muscle recovery, characterized in that: include: A matching module, for matching at least two electrical stimulation signals of different frequencies according to the current state and recovery requirements of the target muscle; A generation module is used to adjust the intensity and duration of each matching frequency signal according to the real-time feedback electromyographic signal to generate a composite multi-frequency signal sequence; A determination module, used for determining the recovery phase of the target muscle according to the response characteristics of the target muscle; The adjustment module is used to dynamically adjust the parameters of each frequency signal in the multi-frequency signal sequence according to the recovery stage.

9. An electronic device, characterized in that: include: Memory and processing modules; The memory is used to store computer programs; The processing module is used to execute the computer program and implement the steps of the multi-frequency signal generation method for collaborative muscle recovery as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer readable storage medium stores a computer program; When the computer program is executed by one or more processing modules, the one or more processing modules execute the steps of the multi-frequency signal generation method for collaborative muscle recovery as described in any one of claims 1 to 7.

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