Control Method, Device and System of an Electrical Stimulation Therapeutic Apparatus

Abstract

The present invention discloses a control method, device and system for an electrostimulation therapeutic apparatus. The control method of the electrostimulation therapeutic apparatus includes collecting electromyography data and flexion and extension angle data measured on a user's limb that vary with the sampling time points when the limb makes flexion and extension movements; determining the duration parameter, rising slope parameter and falling slope parameter of the electrostimulation signal according to the electromyography data and the flexion and extension angle data; and controlling the electrostimulation therapeutic apparatus to output an electrostimulation signal according to the duration parameter, rising slope parameter, falling slope parameter and maximum voltage peak value. In this application, on the basis of ensuring the effectiveness of the electrostimulation signal treatment, the parameters of the electrostimulation signal are automatically adjusted, that is, it is convenient for the electrostimulation therapeutic apparatus to be widely used in families or other environments, and the convenience of using the electrostimulation therapeutic apparatus is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electrostimulation therapy, and particularly to a control method, device, and system for an electrostimulation therapy instrument. Background Art

[0002] Electrostimulation therapy instruments can be applied to the rehabilitation training of upper and lower limb dysfunction caused by stroke; stroke can cause limb movement disorders, resulting in weakened limb regulation ability and inconvenient limb movement. Common diseases include hemiplegia. By sending electrostimulation signals to the limb parts of patients through the electrodes of the electrostimulation therapy instrument, the electrostimulation signals are used to stimulate the contraction and relaxation of the muscles of the patients' limbs, so as to realize the autonomous movement function training of the paralyzed limbs or the limbs with limited movement of the patients.

[0003] However, during the actual treatment process of the electrostimulation therapy instrument, medical staff need to adjust the parameters of the electrostimulation signals output by the electrostimulation therapy instrument to a reasonable range based on the actual situation of the patients; this requires that the patients must be in places with professional medical staff such as hospitals or nursing homes to carry out electrostimulation therapy, which brings great inconvenience to the electrostimulation therapy of the patients and is not conducive to the wide application of the electrostimulation therapy instrument. Summary of the Invention

[0004] The purpose of the present invention is to provide a control method, device, and system for an electrostimulation therapy instrument, which can realize the automatic adjustment of the parameters of the electrostimulation signals on the basis of ensuring the effectiveness of the electrostimulation signal treatment, that is, it can facilitate the wide application of the electrostimulation therapy instrument in families or other environments and improve the convenience of using the electrostimulation therapy instrument.

[0005] To solve the above technical problems, the present invention provides a control method for an electrostimulation therapy instrument, including:

[0006] Collecting the myoelectric data and flexion and extension angle data measured on the limb that change with the sampling time points when the limb of the user makes flexion and extension movements;

[0007] Determining the duration parameter, rising slope parameter, and falling slope parameter of the electrostimulation signal according to the myoelectric data and the flexion and extension angle data;

[0008] Controlling the electrostimulation therapy instrument to output electrostimulation signals according to the duration parameter, the rising slope parameter, the falling slope parameter, and the maximum voltage peak value.

[0009] In an optional embodiment of the present application, collecting the myoelectric data and flexion and extension angle data measured on the limb that change with the sampling time points when the limb of the user makes flexion and extension movements includes:

[0010] Collect the myoelectric data and the flexion and extension angle data corresponding to each sampling time point during at least two complete flexion and extension movements of the limb; wherein, one complete flexion and extension movement is a flexion and extension movement of the limb from the maximum flexion and extension angle to the minimum flexion and extension angle and then to the maximum flexion and extension angle.

[0011] Correspondingly, according to the myoelectric data and the flexion and extension angle data, determine the duration parameter, the rising slope parameter, and the falling slope parameter of the electrical stimulation signal, including:

[0012] According to the flexion and extension angle data changing with each sampling time point, determine the first starting moment and the first ending moment when the flexion and extension angle data is less than or equal to the set flexion and extension angle during one complete flexion and extension movement of the limb.

[0013] Use the time difference between the first ending moment and the first starting moment as the duration parameter.

[0014] According to the myoelectric data changing with each sampling time point, determine the second starting moment and the second ending moment when the myoelectric data is greater than the set myoelectric threshold during one complete flexion and extension movement of the limb.

[0015] Use the time difference between the first starting moment and the second starting moment as the rising duration, and perform a ratio operation on the maximum voltage peak value and the rising duration to obtain the rising slope parameter.

[0016] Use the time difference between the second ending moment and the first ending moment as the falling duration, and perform a ratio operation on the maximum voltage peak value and the falling duration to obtain the falling slope parameter.

[0017] In an optional embodiment of the present application, the process of determining the set myoelectric threshold includes:

[0018] According to the myoelectric data changing with each sampling time point, determine the maximum myoelectric data and the minimum myoelectric data during one complete flexion and extension movement of the limb.

[0019] According to the maximum myoelectric data, the minimum myoelectric data, and the myoelectric threshold formula: S0 = Smin + K(Smax - Smin), determine the set myoelectric threshold; wherein, S0 is the set myoelectric threshold, Smax and Smin are the maximum myoelectric data and the minimum myoelectric data respectively, K is a proportionality coefficient, and the value range of K is (0.5, 1).

[0020] In an optional embodiment of the present application, it further includes:

[0021] Based on the flexion and extension angle data of the limb in two consecutive complete flexion and extension movements, determine the time difference between the first end moment corresponding to the previous complete flexion and extension movement and the first start moment corresponding to the next complete flexion and extension movement as the interval time parameter between two adjacent output electrical stimulation signals.

[0022] In an alternative embodiment of the present application, when collecting the flexion and extension movements of the user's limb, after measuring the electromyogram data and flexion and extension angle data that vary with the sampling time points on the limb, it further includes:

[0023] Use the moving average filtering algorithm to perform filtering and smoothing processing on the electromyogram signal and the flexion and extension angle data that vary with the sampling time points respectively, to obtain the electromyogram data and the flexion and extension angle data after filtering and smoothing processing;

[0024] Correspondingly, determining the duration parameter, rising slope parameter, and falling slope parameter of the electrical stimulation signal according to the electromyogram data and the flexion and extension angle data includes:

[0025] Determine the duration parameter, rising slope parameter, and falling slope parameter of the electrical stimulation signal according to the electromyogram data and the flexion and extension angle data after filtering and smoothing processing.

[0026] In an alternative embodiment of the present application, using the time difference between the first end moment and the first start moment as the duration parameter includes:

[0027] Use the average value of the time differences between the first end moment and the first start moment corresponding to multiple complete flexion and extension movements of the limb as the duration parameter;

[0028] Use the time difference between the first start moment and the second start moment as the rising duration, including:

[0029] Use the average value of the time differences between the first start moment and the second start moment corresponding to multiple complete flexion and extension movements of the limb as the rising duration;

[0030] Use the time difference between the second end moment and the first end moment as the falling duration, including:

[0031] Use the average value of the time differences between the second end moment and the first end moment corresponding to multiple complete flexion and extension movements of the limb as the falling duration.

[0032] A control device for an electrical stimulation therapeutic apparatus, comprising:

[0033] A data acquisition module, configured to acquire the electromyography data and flexion and extension angle data of a limb changing with sampling time points when the limb of a user makes flexion and extension movements.

[0034] An analysis module, configured to determine the duration parameter, rising slope parameter, and falling slope parameter of the electrical stimulation signal according to the electromyography data and the flexion and extension angle data.

[0035] A signal output module, configured to control the electrical stimulation therapeutic apparatus to output an electrical stimulation signal according to the duration parameter, the rising slope parameter, the falling slope parameter, and the maximum voltage peak value.

[0036] A control system of an electrical stimulation therapeutic apparatus, comprising:

[0037] An electromyography sensor and a flexion and extension angle detector respectively configured to acquire the electromyography data and the flexion and extension angle data of a limb changing with sampling time points when the limb of a user makes flexion and extension movements;

[0038] An electrical stimulation therapeutic apparatus configured to output an electrical stimulation signal;

[0039] A processor connected to the electromyography sensor, the flexion and extension angle detector, and the electrical stimulation therapeutic apparatus, configured to execute the steps of the control method of the electrical stimulation therapeutic apparatus described in any one of the above.

[0040] In an optional embodiment of the present application, the flexion and extension angle detector is a camera device configured to acquire the flexion and extension images of the limb making flexion and extension movements;

[0041] The processor is configured to analyze and identify the flexion and extension images to determine the flexion and extension angle data.

[0042] In an optional embodiment of the present application, it further comprises a voice device connected to the processor, configured to prompt the user to make flexion and extension movements.

[0043] A control method, device, and system of an electrical stimulation therapeutic apparatus provided by the present invention. The control method of the electrical stimulation therapeutic apparatus includes acquiring the electromyography data and the flexion and extension angle data of a limb changing with sampling time points measured on the limb when the limb of a user makes flexion and extension movements; determining the duration parameter, rising slope parameter, and falling slope parameter of the electrical stimulation signal according to the electromyography data and the flexion and extension angle data; controlling the electrical stimulation therapeutic apparatus to output an electrical stimulation signal according to the duration parameter, the rising slope parameter, the falling slope parameter, and the maximum voltage peak value.

[0044] In this application, it is considered that when using an electro - stimulation therapeutic apparatus to perform electro - stimulation treatment on a user's limb, the parameters of the electro - stimulation signal need to be set based on the strength of the voluntary movement of the limb muscles. Therefore, in this application, the flexion - extension angle data and electromyogram (EMG) data during the flexion - extension movement of the limb are collected first. Obviously, the speed of the flexion - extension movement of the limb (which can be represented by the rate of change of the flexion - extension angle data) and the magnitude of the EMG data can both reflect to a certain extent the magnitude of the strength of the voluntary movement of the limb muscles. Thus, in this application, based on the EMG data and the corresponding flexion - extension angle data, parameters such as the duration parameter, rise - slope parameter, and fall - slope parameter of the electro - stimulation signal can be analyzed and determined. When performing electro - stimulation treatment on the limb, on the basis of ensuring the effectiveness of the electro - stimulation signal treatment, the automatic adjustment of the parameters of the electro - stimulation signal can be realized, which is convenient for the wide application of the electro - stimulation therapeutic apparatus in the family or other environments, and improves the convenience of using the electro - stimulation therapeutic apparatus. Brief Description of the Drawings

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0046] Figure 1 It is a schematic flow chart of the control method of the electro - stimulation therapeutic apparatus provided by the embodiment of this application;

[0047] Figure 2 It is a schematic diagram of a complete flexion - extension movement of the limb provided by the embodiment of this application;

[0048] Figure 3 It is a coordinate schematic diagram of the EMG data and the flexion - extension angle data changing with the sampling time during multiple consecutive complete flexion - extension movements provided by the embodiment of this application;

[0049] Figure 4 It is a schematic diagram of the change in the voltage peak value of the electro - stimulation signal provided by the embodiment of this application;

[0050] Figure 5 It is a structural block diagram of the control device of the electro - stimulation therapeutic apparatus provided by the embodiment of the present invention. Detailed Embodiments

[0051] The core of the present invention is to provide a control method, device, and system for an electro - stimulation therapeutic apparatus, which can improve the convenience of using the electro - stimulation therapeutic apparatus to a certain extent and is conducive to the wide application of the electro - stimulation therapeutic apparatus.

[0052] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0053] like Figures 1 to 4 As shown, Figure 1 A flow chart of a control method for an electrical stimulation therapeutic apparatus according to an embodiment of the present application; Figure 2 A schematic diagram of a limb performing a complete flexion and extension movement provided in an embodiment of the present application; Figure 3 A schematic diagram of coordinates showing changes in electromyographic data and flexion and extension angle data over sampling time during multiple consecutive complete flexion and extension movements provided in an embodiment of the present application; Figure 4 Schematic diagram of the voltage peak change of the electrical stimulation signal provided in the embodiment of the present application.

[0054] In a specific embodiment of the present application, a control method of the electrical stimulation therapeutic apparatus may include:

[0055] S11: Collecting myoelectric data and flexion and extension angle data measured on the user's limbs when the limbs perform flexion and extension movements, which change with sampling time points.

[0056] Reference Figure 2 , Figure 2 For the user's upper limbs from straight state to bent and contracted state and then to straight state, Figure 2 A complete set of flexion and extension movements of the middle and upper limbs is from a fully extended state to a fully fitted and contracted state between the upper arm and the forearm and then to a fully extended state.

[0057] It is understood that the electrical stimulation therapeutic device in this embodiment can be used to treat both the user's upper limbs and the user's lower limbs. When the user's upper limbs need to be treated, the user's complete set of flexion and extension movements can be from a fully straightened state to a fully bent and contracted state and then to a fully straightened state, or from a fully straightened state to a 90-degree bend between the thigh and calf and then to a fully straightened state. This application does not impose any specific restrictions on this.

[0058] like Figure 2 As shown, Figure 2The angle θ between the upper arm and the forearm is the flexion and extension angle of the limb; it is understandable that for the lower limbs, the flexion and extension angle should be the angle between the thigh and the calf; ideally, when the user's limb is in a fully extended state, the flexion and extension angle should be 180 degrees, and when the limb is in a fully bent and contracted state, the flexion and extension angle should be 0 degrees. However, in actual applications, the user's limbs may not be able to fully extend or fully bend and contract due to various reasons such as illness and muscle injury. Therefore, as the user completes a complete set of flexion and extension movements, the flexion and extension angle data collected should gradually change from the maximum angle to the minimum angle, and then from the minimum angle to the maximum angle; and the maximum angle may be less than 180 degrees or close to 180 degrees, and the minimum angle may be greater than 0 degrees or close to 0 degrees.

[0059] On this basis, in actual application, a myoelectric sensor can be fitted on a limb, and when the limb performs flexion and extension, the myoelectric data that changes with the limb movement can be collected. In addition, when the limb performs flexion and extension, the flexion and extension images of the limb movement can also be collected by a camera device, and then the flexion and extension images are subjected to image recognition analysis to determine the flexion and extension angle data during the limb movement process. The camera device can be a mobile phone, a tablet or an electronic device with a camera, or it can be a camera configured by the electrical stimulation therapeutic device itself, and this application is not specifically limited to this; for example, an APP software can be developed for the electrical stimulation therapeutic device in advance, and after the user's mobile phone logs in to the APP software, the user can turn on the mobile phone camera according to the instructions of the APP software and perform at least one group of flexion and extension movements. The mobile phone camera collects the flexion and extension images during the flexion and extension movement, and uploads them to the cloud platform server through the host computer. The cloud platform server performs recognition analysis on the flexion and extension images, thereby determining the flexion and extension angle data of the corresponding limb in each flexion and extension image. Of course, the electrical stimulation therapeutic device is equipped with a camera that can capture flexion and extension images, and the processor of the main control system in the electrical stimulation therapeutic device can also be used to directly analyze and identify the flexion and extension images to obtain the flexion and extension angle data of the user during the flexion and extension movement.

[0060] It is understood that the myoelectric sensor and camera device should respectively collect myoelectric data and flexion and extension images in real time when the user's limbs are flexing and extending. Therefore, as the limb flexion and extension movements change, each sampling time point should correspond to one piece of myoelectric data and one piece of flexion and extension angle data; both the myoelectric data and the flexion and extension angle data change with the changes in the flexion and extension movements. Furthermore, in order to ensure the reliability of the collected myoelectric data and flexion and extension angle data, in actual applications, the myoelectric data and flexion and extension angle data corresponding to multiple sets of complete flexion and extension movements should be collected by the user.

[0061] like Figure 3 As shown, Figure 3The curves showing the changes of EMG data and flexion / extension angle data with sampling time during consecutive complete flexion / extension movements are shown.

[0062] S12: Determine the duration parameter, rising slope parameter, and falling slope parameter of the electrical stimulation signal based on the EMG data and flexion / extension angle data.

[0063] It can be understood that for patients who need rehabilitation training, the state of the limb's flexion / extension movement can, to a certain extent, characterize the patient's limb's autonomous movement ability. For example, when the limb makes flexion / extension movements, both the change rate of the flexion / extension angle and the degree of muscle tension (which can be determined by the magnitude of the EMG data) can reflect the limb's autonomous movement ability to a certain extent. Thus, in this application, the EMG data and flexion / extension angle data can be used as reference bases to automatically analyze and determine the treatment parameters of the electrical stimulation signal suitable for the user. The treatment parameters of the electrical stimulation signal can include but are not limited to the duration parameter, rising slope parameter, and falling slope parameter.

[0064] As Figure 4 shown, Figure 4 is a schematic diagram of the change in the voltage peak value of the electrical stimulation signals output continuously twice by the electrical stimulation therapy device. The process of the electrical stimulation therapy device outputting each electrical stimulation signal includes a rising stage, a constant stage, and a falling stage. Among them, the electrical stimulation signal output by the electrode patch of the electrical stimulation therapy device is generally a sine wave signal or a square wave signal; in this embodiment, the voltage peak value of the electrical stimulation signal is also the voltage value corresponding to the peak or trough of each cycle of the electrical stimulation signal.

[0065] The rising stage of the electrical stimulation signal is also the stage where the voltage peak value of the electrical stimulation signal gradually increases from 0 to the maximum voltage peak value V0. The slope of the voltage peak value of the electrical stimulation signal increasing from 0 to the maximum voltage peak value V0 in this stage is also the rising slope.

[0066] When the voltage peak value of the electrical stimulation signal rises to the maximum voltage peak value V0, the electrical stimulation signal maintains this constant value of the maximum voltage peak value V0 and continuously outputs for a period of time, that is, the constant stage, and then starts to enter the falling stage, that is, the stage where the voltage peak value of the electrical stimulation signal gradually decreases from the maximum voltage peak value V0 to 0. The slope of the voltage peak value of the electrical stimulation signal decreasing from the maximum voltage peak value to 0 in this stage is also the falling slope.

[0067] Based on this, the parameters determined based on the above EMG data and flexion / extension angle data in this embodiment are also the rising slope parameter and falling slope parameter of each output of the electrical stimulation signal. In addition, it includes a duration parameter, which is the total duration of the rising stage, constant stage, and falling stage of the electrical stimulation signal.

[0068] Of course, in practical applications, based on the electromyography data and the flexion / extension angle data, the parameters of the electrical stimulation signal that can be further determined include the interval duration between two adjacent outputs of the electrical stimulation signal by the electrode patch; and as described above, the electrical stimulation signal can be a square wave signal, a sine wave signal, etc. Therefore, the frequency parameter, pulse width, and the above-mentioned maximum voltage peak parameter, etc. of the electrical stimulation signal can also be determined based on the electromyography data and the flexion / extension angle data. Of course, in this application, it is not excluded that only the duration parameter, rise slope parameter, and fall slope parameter, etc. of the electrical stimulation signal are determined based on the electromyography data and the flexion / extension angle data, while other parameters adopt default values; specific limitations are not made in this application in this regard.

[0069] In addition, there can be various different implementation manners for determining various parameters of the electrical stimulation signal based on the electromyography data and the flexion / extension angle data.

[0070] For example, a large amount of historical electromyography data and corresponding historical flexion / extension angle data are collected in advance, and the parameter data of the electrical stimulation signal with the best treatment effect corresponding to each group of historical electromyography data and the corresponding historical flexion / extension angle data are used as sample data. Through neural network training, the correlation between the electromyography data and the corresponding flexion / extension angle data and the parameter data of the electrical stimulation signal with the best treatment effect is learned and analyzed, and thus a neural network training model is determined; then, in practical applications, as long as the collected electromyography data and flexion / extension angle data are directly input into the neural network training model, the best parameter data of the electrical stimulation signal can be analyzed and determined.

[0071] Also for example, the historical flexion / extension angle data and each group of historical electromyography data can be analyzed in advance to construct a data table of the parameters of the electrical stimulation signal and the optimal parameter data corresponding to the electromyography data and the corresponding flexion / extension angle data; thus, in practical applications, the parameter data of the current electrical stimulation signal can be directly looked up based on the currently collected electromyography data and the corresponding flexion / extension angle data.

[0072] S13: Control the electrical stimulation therapeutic apparatus to output an electrical stimulation signal according to the duration parameter, rise slope parameter, fall slope parameter, and maximum voltage peak.

[0073] In summary, in this application, the flexion / extension angle data and EMG data during limb flexion / extension movements are collected first. Obviously, the speed of change of the flexion / extension angle data and the magnitude of the EMG data during limb flexion / extension movements can all reflect to a certain extent the magnitude of the voluntary movement force of the limb muscles. Therefore, in this application, based on the EMG data and the corresponding flexion / extension angle data, parameters such as the duration parameter, the rising slope parameter, and the falling slope parameter of the electrical stimulation signal can be analyzed and determined. Thus, when performing electrical stimulation treatment on the limb, on the basis of ensuring the effectiveness of the electrical stimulation signal treatment, the parameters of the electrical stimulation signal can be automatically adjusted, which is convenient for the wide application of the electrical stimulation therapeutic apparatus in the family or other environments and improves the convenience of using the electrical stimulation therapeutic apparatus.

[0074] Based on the above discussion, in an optional embodiment of this application, the process of the control method of the electrical stimulation therapeutic apparatus may include:

[0075] S21: Collect the EMG data and the flexion / extension angle data corresponding to each sampling time point during at least two complete flexion / extension movements of the limb.

[0076] Wherein, one complete flexion / extension movement is a flexion / extension movement of the limb from the maximum flexion / extension angle to the minimum flexion / extension angle and then back to the maximum flexion / extension angle.

[0077] It can be understood that during the continuous multiple complete flexion / extension movements of the limb, the collected EMG data and flexion / extension angle data may both be curves with obvious fluctuations, and due to various interference factors, there may be a large amount of noise in the curves of the EMG data and the flexion / extension angle data changing with time. Therefore, in order to avoid removing the noise interference in the EMG data and the flexion / extension angle data, after collecting the EMG data and the flexion / extension angle data, the EMG data and the flexion / extension angle data can be further subjected to filtering and smoothing processing respectively, specifically including:

[0078] Use the moving average filtering algorithm to perform filtering and smoothing processing on the EMG signal and the flexion / extension angle data changing with the sampling time point respectively, and obtain the EMG data and the flexion / extension angle data after filtering and smoothing processing.

[0079] Based on the principle of the moving average filtering algorithm, taking the moving window as 10 and the filtering and smoothing processing of the EMG data as an example, the EMG data after processing at the first sampling time point is equal to the average value of the EMG data collected at the first to the tenth sampling time points without processing; and the EMG data after processing at the second sampling time point is equal to the average value of the EMG data collected at the second to the eleventh sampling time points without processing; and so on, the EMG data at each sampling time point can be filtered in turn to obtain smoother EMG data. And for the flexion / extension angle data, a similar method can be used for processing. For this, it will not be repeated in this embodiment.

[0080] S22: Determine the first start time and the first end time at which the flexion / extension angle data is less than or equal to the set flexion / extension angle during a complete flexion / extension movement of the limb, based on the flexion / extension angle data that changes with each sampling time point.

[0081] As Figure 3 shown, after acquiring the flexion / extension angle data and the electromyogram data, the change curves of the flexion / extension angle data and the electromyogram data with respect to the sampling time can be respectively fitted.

[0082] In Figure 3 the illustrated embodiment, θ0 is the set flexion / extension angle; when the limb starts to bend and contract from the straight state, the flexion / extension angle data gradually decreases from the maximum flexion / extension angle θmax. When the flexion / extension angle data decreases to equal the set flexion / extension angle θ0, the corresponding sampling time point is also the first start time t1; as the limb continues to change completely, the flexion / extension angle data gradually decreases to the minimum flexion / extension angle θmin and then starts to gradually increase. When the flexion / extension angle data gradually increases to equal the set flexion / extension angle θ0, the corresponding sampling time point is also the first end time t2.

[0083] It can be understood that the set flexion / extension angle θ0 in this embodiment can be set based on the maximum flexion / extension angle θmax that the user can reach during the flexion / extension movement. This set flexion / extension angle θ0 can be 5 to 10 degrees smaller than the maximum flexion / extension angle θmax; for example, if the user's maximum flexion / extension angle θmax is 180 degrees, then this set flexion / extension angle θ0 can be between 175 degrees and 170 degrees; based on this set flexion / extension angle θ0, the time points when the limb starts and ends the flexion / extension movement can be more accurately identified.

[0084] In addition, as described above, after acquiring the flexion / extension angle data and the electromyogram data in multiple consecutive complete flexion / extension movements in this embodiment, the flexion / extension angle data and the electromyogram data can be further filtered and smoothed. Thus, in this embodiment, the first start time and the second start time can be determined based on the filtered and smoothed flexion / extension angle data.

[0085] S23: Use the time difference between the first end time and the first start time as the duration parameter.

[0086] Referring to Figure 3 , the duration parameter T0 in this embodiment is also equal to t2 - t1; referring to Figure 4 , the total duration of each output of the electrical stimulation therapeutic apparatus for the electrical stimulation signal is also the duration parameter T0.

[0087] It is understandable that the duration of a complete flexion and extension movement of the user's limb to a certain extent reflects the speed of the flexion and extension movement of the user's limb, that is, it can indirectly reflect the flexibility of the limb's voluntary movement. Obviously, the slower the speed of the user's limb for the flexion and extension movement, the worse the flexibility of the user's limb's voluntary movement, and the lower the sensitivity of its perception of the electrical stimulation signal. Therefore, during the actual physical therapy process, applying an electrical stimulation signal for a longer time can ensure the treatment effect to a certain extent. That is to say, the total duration of each output electrical stimulation signal should be proportional to the total duration of a complete flexion and extension movement of the limb. In this embodiment, the total duration of a complete flexion and extension movement of the limb is directly used as the duration parameter of each output electrical stimulation signal; however, in actual applications, the duration parameter of the electrical stimulation signal and the total duration of a complete flexion and extension movement of the limb can satisfy T0 = k(t2 - t1) + b; where k is the proportionality coefficient, b is a constant, and the magnitudes of k and b can be set by the staff based on actual work experience or determined through multiple experimental tests. In this regard, no specific restrictions are made in this embodiment.

[0088] In addition, as shown in FIG. 3, in this embodiment, the electromyography data and flexion and extension angle data of the user's limb during continuous completion of multiple complete flexion and extension movements are collected; obviously, for the flexion and extension angle data corresponding to each complete driving movement, the total duration of a complete flexion and extension movement of the limb can be determined. Therefore, in actual applications, the total durations corresponding to multiple complete flexion and extension movements of the limb can be averaged, and this average value is used as the total duration of a complete flexion and extension movement of the limb, and the time parameter is determined therefrom.

[0089] In addition, considering the situation that the user's limb is not adapted to start the flexion and extension movement, as well as the fatigue condition after multiple groups of flexion and extension movements, it is also possible to only select the total duration of a complete flexion and extension movement determined by the middle several complete flexion and extension movements among multiple groups of complete flexion and extension movements as the basis to determine the time parameter; for example, the flexion and extension angle data of 4 consecutive complete flexion and extension movements are collected in total; the flexion and extension angle data of the 2nd and 3rd complete flexion and extension movements are taken to determine the total durations of two complete flexion and extension movements respectively, and the average value of the total durations of the two complete flexion and extension movements is used as the finally determined total duration of a complete flexion and extension movement.

[0090] S24: According to the electromyography data that changes with each sampling time point, determine the second starting time and the second ending time when the electromyography data is greater than or equal to the set electromyography threshold during a complete flexion and extension movement of the limb.

[0091] It is understandable that the electromyography data in this step can also be the electromyography data after filtering and smoothing processing.

[0092] On this basis, referring toFigure 3 , in Figure 3 , S0 is the set EMG threshold; as the limb makes flexion and extension movements, the EMG data will increase as the limb gradually bends. Thus, when the limb starts to contract from the straight state (or the state of the maximum flexion and extension angle), the EMG data begins to gradually increase. When the EMG data increases to be equal to the set EMG threshold S0, the corresponding sampling time point is also the second starting time point t3; during the process when the limb bends to the minimum flexion and extension angle and then gradually straightens, the EMG data also gradually increases to the maximum value and then starts to decrease. When the EMG data decreases to be equal to the set EMG threshold S0, the corresponding sampling time point is also the second ending time point t4. Obviously, the time period between this second starting time point t3 and the second ending time point t4 is also the time period when the EMG data is greater than the set EMG threshold S0.

[0093] It should be noted that the set EMG threshold S0 in this embodiment can also be set according to the magnitude of the EMG value during the flexion and extension movement of the limb; optionally, the process of determining the set EMG threshold includes:

[0094] According to the EMG data that changes with each sampling time point, determine the maximum EMG data and the minimum EMG data in a complete flexion and extension movement of the limb;

[0095] According to the maximum EMG data, the minimum EMG data, and the EMG threshold formula: S0 = Smin + K(Smax - Smin), determine the set EMG threshold; where S0 is the set EMG threshold, Smax and Smin are the maximum EMG data and the minimum EMG data respectively, K is the proportionality coefficient, and the value range of K is (0.5, 1).

[0096] The EMG data in this embodiment is generally collected during the process of the limb continuously completing multiple complete flexion and extension movements. Therefore, for each complete set of flexion and extension movements, there should be a set of maximum EMG data and minimum EMG data; for this reason, in this embodiment, the average value of the maximum EMG data corresponding to multiple complete sets of flexion and extension movements can be used as the maximum EMG data in a complete flexion and extension movement, and the average value of the minimum EMG data corresponding to multiple complete sets of flexion and extension movements can be used as the minimum EMG data in a complete flexion and extension movement. Combining the above EMG threshold formula to obtain the set EMG threshold. In addition, for the proportionality coefficient K, the specific value can be 0.6, 0.7, 0.8, 0.9, etc., and there is no specific limitation in this application.

[0097] S25: Use the time difference between the first starting time point and the second starting time point as the rising duration, and perform a ratio operation on the maximum voltage peak value and the rising duration to obtain the rising slope parameter.

[0098] It can be understood that during a complete flexion and extension movement of a limb, when the electromyogram data is greater than the set electromyogram threshold, it indicates that the muscles on the limb have contracted to a relatively large extent. Moreover, the speed at which the limb changes from the extended state to the electromyogram data being greater than or equal to the set electromyogram threshold also reflects to a certain extent the speed of muscle contraction of the limb. For users with relatively slow muscle contraction of the limb, the fluctuation of the electrical stimulation signal should not be too fast. Therefore, in this embodiment, the time required for the electromyogram data to rise to be greater than or equal to the set electromyogram threshold is used as the rising time Tu, that is, Tu = t3 - t1, and the ratio between the maximum voltage peak V0 and this rising time Tu is used as the rising slope parameter of the electrical stimulation signal. It can be seen that in this embodiment, the rising speed of the electrical stimulation signal is proportional to the growth speed of the electromyogram data during the limb bending and contraction process, so as to ensure that the limb can better adapt to the change of the electrical stimulation signal.

[0099] In addition, the rising time Tu in this embodiment can also be the average value of the time differences between multiple sets of first starting times and second starting times determined based on the changes in electromyogram data in multiple sets of complete flexion and extension movements as the rising time Tu.

[0100] In addition, for the magnitude of the maximum voltage peak of the electrical stimulation signal, it can be set based on the experience of the staff or determined based on the corresponding maximum electromyogram data during the flexion and extension movement of the limb. In this regard, this application does not specifically limit it.

[0101] S26: Use the time difference between the second end time and the first end time as the falling time, and perform a ratio operation on the maximum voltage peak and the falling time to obtain the falling slope parameter.

[0102] Similar to the above rising slope parameter; during the process of the limb gradually extending from the bent and contracted state, it belongs to the process of the muscle gradually relaxing. Therefore, the falling time Td = t2 - t4 consumed during the process of the electromyogram data gradually decreasing from the set electromyogram threshold to the limb reaching the minimum flexion and extension angle also characterizes the speed of the muscle relaxing from being tightened to being relaxed. Thus, in this embodiment, the ratio between the maximum voltage peak and the falling time is used as the falling slope parameter of the electrical stimulation signal, that is, the falling speed of the electrical stimulation signal is determined based on the speed of muscle relaxation.

[0103] Similar to the above determination of the rising time Tu, the falling time in this embodiment can also be determined by averaging the time differences between the corresponding second end times and first end times in multiple sets of complete flexion and extension movements.

[0104] S27: Control the electrical stimulation therapeutic apparatus to output an electrical stimulation signal according to the duration parameter, the rising slope parameter, the falling slope parameter, and the maximum voltage peak.

[0105] As shown above, when the electro - stimulation therapy device outputs an electro - stimulation signal, in addition to setting the duration parameter, the rising slope parameter, and the falling slope parameter, it is also necessary to set the maximum voltage peak value of the electro - stimulation signal, the frequency of the electro - stimulation signal, and the pulse width, etc.; for the maximum voltage peak value, frequency, and pulse width of the electro - stimulation signal, default values can be adopted, or they can be set based on the electromyogram data.

[0106] In addition, as Figure 3 and Figure 4 shown, in another optional implementation manner of this embodiment, based on the flexion - extension angle data of the limb during continuous performance of multiple sets of complete flexion - extension actions, the time difference between the first end time corresponding to the previous complete flexion - extension action and the first start time corresponding to the next complete flexion - extension action in two adjacent complete flexion - extension actions can be used as the interval time parameter ∆T between two adjacent outputs of the electro - stimulation signal.

[0107] Next, the control device of the electro - stimulation therapy device provided by the embodiments of the present invention will be introduced. The control device of the electro - stimulation therapy device described below can be mutually corresponding and referred to with the control method of the electro - stimulation therapy device described above.

[0108] Figure 5 is the structural block diagram of the control device of the electro - stimulation therapy device provided by the embodiments of the present invention. Referring to Figure 5 the control device of the electro - stimulation therapy device in can include:

[0109] A data acquisition module 100, configured to acquire the electromyogram data and flexion - extension angle data of the limb changing with the sampling time points when the user's limb performs flexion - extension actions;

[0110] An analysis module 200, configured to determine the duration parameter, the rising slope parameter, and the falling slope parameter of the electro - stimulation signal according to the electromyogram data and the flexion - extension angle data;

[0111] A signal output module 300, configured to control the electro - stimulation therapy device to output an electro - stimulation signal according to the duration parameter, the rising slope parameter, the falling slope parameter, and the maximum voltage peak value.

[0112] In an optional embodiment of the present application, the data acquisition module 100 is specifically configured to acquire the electromyogram data and the flexion - extension angle data corresponding to each sampling time point during at least two complete flexion - extension actions of the limb; where one complete flexion - extension action is a flexion - extension action of the limb from the maximum flexion - extension angle to the minimum flexion - extension angle and then back to the maximum flexion - extension angle;

[0113] The analysis module 200 includes:

[0114] The first analysis unit is configured to determine, according to the flexion and extension angle data that varies with each sampling time point, a first starting time point and a first ending time point at which the flexion and extension angle data is less than or equal to a set flexion and extension angle during one complete flexion and extension movement of the limb;

[0115] The second analysis unit is configured to use the time difference between the first ending time point and the first starting time point as the duration parameter;

[0116] The third analysis unit is configured to determine, according to the electromyogram data that varies with each sampling time point, a second starting time point and a second ending time point at which the electromyogram data is greater than a set electromyogram threshold during one complete flexion and extension movement of the limb;

[0117] The fourth analysis unit is configured to use the time difference between the first starting time point and the second starting time point as the rising duration, and perform a ratio operation on the maximum voltage peak value and the rising duration to obtain the rising slope parameter;

[0118] The fifth analysis unit is configured to use the time difference between the second ending time point and the first ending time point as the falling duration, and perform a ratio operation on the maximum voltage peak value and the falling duration to obtain the falling slope parameter.

[0119] In an optional embodiment of the present application, it further includes a set threshold module, configured to determine the maximum electromyogram data and the minimum electromyogram data during one complete flexion and extension movement of the limb according to the electromyogram data that varies with each sampling time point; determine the set electromyogram threshold according to the maximum electromyogram data, the minimum electromyogram data, and the electromyogram threshold formula: S0 = Smin + K(Smax - Smin); where S0 is the set electromyogram threshold, Smax and Smin are the maximum electromyogram data and the minimum electromyogram data respectively, K is a proportionality coefficient, and the value range of K is (0.5, 1).

[0120] In an optional embodiment of the present application, the data analysis module 200 further includes determining, according to the flexion and extension angle data of the limb during two consecutive complete flexion and extension movements, the time difference between the first ending time point corresponding to the previous complete flexion and extension movement and the first starting time point corresponding to the next complete flexion and extension movement as the interval time parameter between two adjacent output electrical stimulation signals.

[0121] In an alternative embodiment of the present application, it further includes a filtering processing module, which is used to, after measuring the electromyogram data and flexion / extension angle data that vary with the sampling time points on the limb when collecting the flexion / extension movements of the user's limb, perform filtering and smoothing processing on the electromyogram signal and the flexion / extension angle data that vary with the sampling time points respectively by using a moving average filtering algorithm, so as to obtain the electromyogram data and the flexion / extension angle data after the filtering and smoothing processing;

[0122] Correspondingly, the data analysis module 200 is used to determine the duration parameter, rising slope parameter, and falling slope parameter of the electrical stimulation signal according to the electromyogram data and the flexion / extension angle data after the filtering and smoothing processing.

[0123] In an alternative embodiment of the present application, the second analysis unit is specifically used to take the average value of the time differences between the first end time and the first start time corresponding to multiple complete flexion / extension movements of the limb as the duration parameter;

[0124] The fourth analysis unit is specifically used to take the average value of the time differences between the first start time and the second start time corresponding to multiple complete flexion / extension movements of the limb as the rising duration;

[0125] The fifth analysis unit is specifically used to take the average value of the time differences between the second end time and the first end time corresponding to multiple complete flexion / extension movements of the limb as the falling duration.

[0126] The control device of the electrical stimulation therapeutic apparatus in this embodiment is used to implement the foregoing control method of the electrical stimulation therapeutic apparatus. Therefore, the specific implementation manners in the control device of the electrical stimulation therapeutic apparatus can be seen in the embodiment part of the control method of the electrical stimulation therapeutic apparatus in the foregoing text. Its specific implementation manners can be referred to the descriptions of the corresponding various part embodiments, and will not be elaborated here.

[0127] The present application also provides a control system of an electrical stimulation therapeutic apparatus, and the control system of the electrical stimulation therapeutic apparatus may include:

[0128] An electromyogram sensor and a flexion / extension angle detector respectively used to collect the electromyogram data and the flexion / extension angle data that vary with the sampling time points of the limb when the limb of the user makes flexion / extension movements;

[0129] An electrical stimulation therapeutic apparatus used to output an electrical stimulation signal;

[0130] And a processor connected to the electromyogram sensor, the flexion / extension angle detector, and the electrical stimulation therapeutic apparatus, and used to execute the steps of the control method of the electrical stimulation therapeutic apparatus as described in any one of the foregoing items.

[0131] Optionally, the flexion and extension angle detector in this embodiment may be an imaging device for collecting flexion and extension images of the limb during flexion and extension movements;

[0132] The processor is configured to analyze and recognize the flexion and extension images to determine the flexion and extension angle data.

[0133] Optionally, this embodiment further includes a voice device connected to the processor for prompting the user to perform flexion and extension movements.

[0134] The processor in this application may be a processor built into the main control system of the electrostimulation therapeutic instrument, or a processor in a cloud platform server or a user's mobile phone and other devices. There is no specific limitation in this application.

[0135] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes the inherent elements thereof. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element. In addition, the parts of the above technical solutions provided in the embodiments of this application that are consistent with the corresponding technical solutions in the prior art in terms of implementation principles are not described in detail to avoid excessive elaboration.

[0136] Specific examples are used in this article to elaborate on the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A control device for an electrostimulation therapeutic apparatus, characterized in that, Including: A data acquisition module, configured to acquire electromyogram data and flexion / extension angle data of a limb changing with sampling time points when the limb of a user makes flexion and extension movements; A data analysis module, configured to determine a duration parameter, a rising slope parameter, and a falling slope parameter of an electrical stimulation signal according to the electromyogram data and the flexion / extension angle data; A signal output module, configured to control the electrical stimulation therapeutic apparatus to output an electrical stimulation signal according to the duration parameter, the rising slope parameter, the falling slope parameter, and the maximum voltage peak value; The data acquisition module is specifically configured to acquire the electromyogram data and the flexion / extension angle data corresponding to each sampling time point during at least two complete flexion and extension movements of the limb; wherein, one complete flexion and extension movement is a flexion and extension movement of the limb from the maximum flexion / extension angle to the minimum flexion / extension angle and then back to the maximum flexion / extension angle; The data analysis module includes: A first analysis unit, configured to determine a first starting moment and a first ending moment corresponding to when the flexion / extension angle data is less than or equal to a set flexion / extension angle during one complete flexion and extension movement of the limb according to the flexion / extension angle data changing with each sampling time point; A second analysis unit, configured to use the time difference between the first ending moment and the first starting moment as the duration parameter; A third analysis unit, configured to determine a second starting moment and a second ending moment when the electromyogram data is greater than a set electromyogram threshold during one complete flexion and extension movement of the limb according to the electromyogram data changing with each sampling time point; A fourth analysis unit, configured to use the time difference between the first starting moment and the second starting moment as the rising duration, and perform a ratio operation on the maximum voltage peak value and the rising duration to obtain the rising slope parameter; A fifth analysis unit, configured to use the time difference between the second ending moment and the first ending moment as the falling duration, and perform a ratio operation on the maximum voltage peak value and the falling duration to obtain the falling slope parameter.

2. The control device of the electrical stimulation therapeutic apparatus according to claim 1, wherein It further includes a set threshold module, configured to determine the maximum electromyogram data and the minimum electromyogram data during one complete flexion and extension movement of the limb according to the electromyogram data changing with each sampling time point; and determine the set electromyogram threshold according to the maximum electromyogram data, the minimum electromyogram data, and the electromyogram threshold formula: S0 = Smin + K(Smax - Smin); wherein, S0 is the set electromyogram threshold, Smax and Smin are the maximum electromyogram data and the minimum electromyogram data respectively, K is a proportionality coefficient, and the value range of K is (0.5, 1).

3. The control device of the electrical stimulation therapeutic apparatus according to claim 1, wherein, The data analysis module further includes determining, according to the flexion / extension angle data of the limb during two consecutive complete flexion and extension movements, the time difference between the first ending moment corresponding to the previous complete flexion and extension movement and the first starting moment corresponding to the next complete flexion and extension movement as the interval time parameter between two adjacent output electrical stimulation signals.

4. The control device of the electrical stimulation therapeutic apparatus according to any one of claims 1 to 3, characterized in that It further includes a filtering processing module, which is configured to, after acquiring the electromyography data and the flexion and extension angle data that vary with the sampling time points measured on the limb when the user's limb makes flexion and extension movements, perform filtering and smoothing processing on the electromyography signal and the flexion and extension angle data that vary with the sampling time points respectively by using a moving average filtering algorithm, so as to obtain the filtered and smoothed electromyography data and the flexion and extension angle data; Correspondingly, the data analysis module is configured to determine the duration parameter, the rising slope parameter, and the falling slope parameter of the electrical stimulation signal according to the filtered and smoothed electromyography data and the flexion and extension angle data.

5. The control device of the electrical stimulation therapeutic apparatus according to claim 4, characterized in that, The second analysis unit is specifically configured to use the average value of the time differences between the first end time and the first start time corresponding to multiple complete flexion and extension movements of the limb as the duration parameter; The fourth analysis unit is specifically configured to use the average value of the time differences between the first start time and the second start time corresponding to multiple complete flexion and extension movements of the limb as the rising duration; The fifth analysis unit is specifically configured to use the average value of the time differences between the second end time and the first end time corresponding to multiple complete flexion and extension movements of the limb as the falling duration.

6. A control system of an electrostimulation therapeutic apparatus, characterized in that, It includes: An electromyography sensor and a flexion and extension angle detector respectively configured to acquire the electromyography data and the flexion and extension angle data that vary with the sampling time points of the limb when the user's limb makes flexion and extension movements; An electrical stimulation therapeutic apparatus configured to output an electrical stimulation signal; A processor connected to the electromyography sensor, the flexion and extension angle detector, and the electrical stimulation therapeutic apparatus, and configured to execute the steps of the control method of the electrical stimulation therapeutic apparatus; The steps of the control method of the electrical stimulation therapeutic apparatus include: Acquiring the electromyography data and the flexion and extension angle data that vary with the sampling time points measured on the limb when the user's limb makes flexion and extension movements; determining the duration parameter, the rising slope parameter, and the falling slope parameter of the electrical stimulation signal according to the electromyography data and the flexion and extension angle data; controlling the electrical stimulation therapeutic apparatus to output an electrical stimulation signal according to the duration parameter, the rising slope parameter, the falling slope parameter, and the maximum voltage peak value; Acquiring the electromyography data and the flexion and extension angle data that vary with the sampling time points measured on the limb when the user's limb makes flexion and extension movements includes: Acquiring the electromyography data and the flexion and extension angle data corresponding to each sampling time point during at least two complete flexion and extension movements of the limb; wherein, one complete flexion and extension movement is a flexion and extension movement of the limb from the maximum flexion and extension angle to the minimum flexion and extension angle and then to the maximum flexion and extension angle; Correspondingly, determining the duration parameter, the rising slope parameter, and the falling slope parameter of the electrical stimulation signal according to the electromyography data and the flexion and extension angle data includes: Determining, according to the flexion and extension angle data that vary with each sampling time point, the first start time and the first end time when the flexion and extension angle data is less than or equal to a set flexion and extension angle during one complete flexion and extension movement of the limb; Use the time difference between the first end time and the first start time as the duration parameter; According to the electromyography data that varies with each sampling time point, determine the second start time and the second end time when the electromyography data is greater than the set electromyography threshold during one complete flexion and extension movement of the limb; Use the time difference between the first start time and the second start time as the rising duration, and perform a ratio operation on the maximum voltage peak value and the rising duration to obtain the rising slope parameter; Use the time difference between the second end time and the first end time as the falling duration, and perform a ratio operation on the maximum voltage peak value and the falling duration to obtain the falling slope parameter.

7. The control system of the electrical stimulation therapeutic apparatus according to claim 6, wherein, The flexion and extension angle detector is a camera device for collecting flexion and extension images of the limb during flexion and extension movements; The processor is used to analyze and identify the flexion and extension images to determine the flexion and extension angle data.

8. The control system of the electrical stimulation therapeutic apparatus according to claim 6, characterized in that, It further includes a voice device connected to the processor for prompting the user to perform flexion and extension movements.

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