阅读说明：本技术 一种盆底训练设备及其参数设置方法 (Pelvic floor training device and parameter setting method thereof ) 是由 章鸿 伍浩 林建勋 于 2019-11-08 设计创作，主要内容包括：本发明提供一种盆底训练设备的参数设置方法,包括：获取盆底肌肉初始信息；根据所述盆底肌肉初始信息,确定与所述盆底肌肉初始信息相应的训练参数；以及获取根据所述训练参数执行盆底训练时的盆底肌肉实时信息,并根据所述盆底肌肉实时信息自适应调节所述训练参数。本发明还提供相应的盆底训练设备及非易失性存储介质。本发明实现了盆底训练设备执行盆底训练的个性化设置以及个性化训练的自动设置,保证盆底训练的安全性和训练效果。(The invention provides a parameter setting method of pelvic floor training equipment, which comprises the following steps: obtaining initial information of pelvic floor muscles; determining training parameters corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information; and acquiring real-time pelvic floor muscle information when the pelvic floor training is executed according to the training parameters, and adaptively adjusting the training parameters according to the real-time pelvic floor muscle information. The invention also provides corresponding pelvic floor training equipment and a nonvolatile storage medium. The invention realizes the personalized setting of the pelvic floor training device for carrying out the pelvic floor training and the automatic setting of the personalized training, and ensures the safety and the training effect of the pelvic floor training.)

1. A parameter setting method of pelvic floor training equipment is characterized by comprising the following steps:

obtaining initial information of pelvic floor muscles;

determining training parameters corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information; and

and acquiring real-time pelvic floor muscle information when pelvic floor training is executed according to the training parameters, and adaptively adjusting the training parameters according to the real-time pelvic floor muscle information.

2. The method of claim 1,

according to the pelvic floor muscle initial information, determining training parameters corresponding to the pelvic floor muscle initial information, wherein the training parameters comprise:

and determining a preset pelvic floor muscle state grade corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information, and determining training parameters corresponding to the pelvic floor muscle initial information according to the preset pelvic floor muscle state grade.

3. The method as recited in claim 2,

the pelvic floor muscle initial information comprises an average value of maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to multiple maximum random contractions;

the determining of the preset pelvic floor muscle state grade corresponding to the pelvic floor muscle initial information and then determining the training parameters corresponding to the pelvic floor muscle initial information according to the preset pelvic floor muscle state grade comprise:

and determining a preset pelvic floor muscle state grade to which the pelvic floor muscle initial information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal values, and further determining a training parameter corresponding to the pelvic floor muscle initial information, wherein the preset pelvic floor muscle state classification table records corresponding relations between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and the preset training parameter.

4. The method as recited in claim 2,

the pelvic floor muscle real-time information comprises time domain information of myoelectric signals when the pelvic floor muscles are in a contraction state;

the obtaining of the real-time information of the pelvic floor muscles during the pelvic floor training performed according to the training parameters comprises:

acquiring the average value of electromyographic signals of pelvic floor muscles in a contraction state every time when biofeedback training is executed;

if the average value appears for the continuous preset times and is smaller than the preset value, determining the fatigue state of the pelvic floor muscles;

the self-adaptive adjustment of the training parameters according to the real-time information of the pelvic floor muscles comprises the following steps:

performing at least one of modifying an action type, reducing a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to the pelvic floor muscle fatigue state.

5. The method as recited in claim 2,

the pelvic floor muscle real-time information comprises frequency domain information of myoelectric signals when the pelvic floor muscles are in a contraction state;

the obtaining of the real-time information of the pelvic floor muscles during the pelvic floor training performed according to the training parameters comprises:

acquiring the average power frequency of electromyographic signals of pelvic floor muscles in a contraction state each time when biofeedback training is executed;

if the average power frequency is less than the preset value after the continuous preset times, determining the fatigue state of the pelvic floor muscles;

the self-adaptive adjustment of the training parameters according to the real-time information of the pelvic floor muscles comprises the following steps:

performing at least one of modifying an action type, reducing a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to the pelvic floor muscle fatigue state.

6. The method as recited in claim 2,

the pelvic floor muscle initial information comprises an average value of maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to multiple maximum random contractions;

the obtaining of the real-time information of the pelvic floor muscles during the pelvic floor training performed according to the training parameters comprises:

acquiring the average value of the maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to multiple maximum random contractions every preset time;

determining a preset pelvic floor muscle state grade to which the pelvic floor muscle real-time information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal value;

the self-adaptive adjustment of the training parameters according to the real-time information of the pelvic floor muscles comprises the following steps:

determining preset training parameters corresponding to the pelvic floor muscle real-time information from a preset pelvic floor muscle state classification table according to the preset pelvic floor muscle state grade to which the pelvic floor muscle real-time information belongs, and adjusting the preset training parameters to be the training parameters;

and the preset pelvic floor muscle state classification table records the corresponding relation between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and preset training parameters.

7. The method as recited in claim 2,

the pelvic floor muscle initial information comprises an average value of pressure values of the pelvic floor muscles when the pelvic floor muscles are subjected to a plurality of maximum voluntary contractions;

the step of determining the preset pelvic floor muscle state grade corresponding to the pelvic floor muscle initial information, and then determining the training parameters corresponding to the pelvic floor muscle initial information according to the preset pelvic floor muscle state grade, comprises the steps of:

and determining a preset pelvic floor muscle state grade to which the pelvic floor muscle initial information belongs from a preset pelvic floor muscle pressure gauge according to the average value of the pressure values, and further determining a training parameter corresponding to the pelvic floor muscle initial information, wherein the preset pelvic floor muscle pressure gauge records corresponding relations between different pressure values representing different preset pelvic floor muscle state grades and preset training parameters, and the preset training parameters change along with the change of the pressure values.

8. The method as recited in claim 7,

the obtaining of the real-time information of the pelvic floor muscles during the pelvic floor training performed according to the training parameters comprises:

acquiring a pressure value of the pelvic floor muscle in a contraction state every time when pulse electrical stimulation training and/or biofeedback training is performed;

if the pressure value is smaller than the preset value after the continuous preset times, determining the state as the fatigue state of the pelvic floor muscles;

the self-adaptive adjustment of the training parameters according to the real-time information of the pelvic floor muscles comprises the following steps:

performing at least one of modifying an action type, reducing a training height, shortening a contraction time, extending a relaxation time, and stopping a training, and/or performing at least one of reducing a current frequency, a current intensity, shortening a stimulation time, extending a rest time, and stopping a training, according to a fatigue state of the pelvic floor muscles.

9. A pelvic floor training device, comprising a processor, a memory and a signal collector, the memory and the signal collector are respectively connected with the processor, the memory stores instructions, the signal collector is used for collecting pelvic floor muscle initial information and pelvic floor muscle real-time information, the instructions when executed cause the processor to:

acquiring initial information of pelvic floor muscles acquired by the signal acquisition unit;

determining training parameters corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information; and

and acquiring real-time pelvic floor muscle information acquired by the signal acquisition unit when pelvic floor training is performed according to the training parameters, and adaptively adjusting the training parameters according to the real-time pelvic floor muscle information.

10. The pelvic floor training apparatus of claim 9, wherein the processor is specifically configured to:

and determining a preset pelvic floor muscle state grade corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information, and determining training parameters corresponding to the pelvic floor muscle initial information according to the preset pelvic floor muscle state grade.

11. The pelvic floor training apparatus of claim 10,

the pelvic floor muscle initial information comprises an average value of maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to multiple maximum random contractions;

the processor is specifically configured to:

and determining a preset pelvic floor muscle state grade to which the pelvic floor muscle initial information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal values, and further determining a training parameter corresponding to the pelvic floor muscle initial information, wherein the preset pelvic floor muscle state classification table records corresponding relations between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and the preset training parameter.

12. The pelvic floor training apparatus of claim 10,

the pelvic floor muscle real-time information comprises time domain information of myoelectric signals when the pelvic floor muscles are in a contraction state;

the processor is specifically configured to:

acquiring the average value of electromyographic signals of pelvic floor muscles in a contraction state every time when biofeedback training is executed;

if the average value appears for the continuous preset times and is smaller than the preset value, determining the fatigue state of the pelvic floor muscles;

the processor is further specifically configured to:

performing at least one of modifying an action type, reducing a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to the pelvic floor muscle fatigue state.

13. The pelvic floor training apparatus of claim 10,

the pelvic floor muscle real-time information comprises frequency domain information of myoelectric signals when the pelvic floor muscles are in a contraction state;

the processor is specifically configured to:

acquiring the average power frequency of electromyographic signals of pelvic floor muscles in a contraction state each time when biofeedback training is executed;

if the average power frequency is less than the preset value after the continuous preset times, determining the fatigue state of the pelvic floor muscles;

the processor is further specifically configured to:

performing at least one of modifying an action type, reducing a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to the pelvic floor muscle fatigue state.

14. The pelvic floor training apparatus of claim 10,

the pelvic floor muscle initial information comprises an average value of maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to multiple maximum random contractions;

the processor is specifically configured to:

acquiring the average value of the maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to multiple maximum random contractions every preset time;

determining a preset pelvic floor muscle state grade to which the pelvic floor muscle real-time information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal value;

the self-adaptive adjustment of the training parameters according to the real-time information of the pelvic floor muscles comprises the following steps:

determining preset training parameters corresponding to the pelvic floor muscle real-time information from a preset pelvic floor muscle state classification table according to the preset pelvic floor muscle state grade to which the pelvic floor muscle real-time information belongs, and adjusting the preset training parameters to be the training parameters;

and the preset pelvic floor muscle state classification table records the corresponding relation between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and preset training parameters.

15. The pelvic floor training apparatus of claim 9,

the pelvic floor muscle initial information comprises an average value of pressure values of the pelvic floor muscles when the pelvic floor muscles are subjected to a plurality of maximum voluntary contractions;

the processor is specifically configured to:

and determining a preset pelvic floor muscle state grade to which the pelvic floor muscle initial information belongs from a preset pelvic floor muscle pressure gauge according to the average value of the pressure values, and further determining a training parameter corresponding to the pelvic floor muscle initial information, wherein the preset pelvic floor muscle pressure gauge records corresponding relations between different pressure values representing different preset pelvic floor muscle state grades and preset training parameters, and the preset training parameters change along with the change of the pressure values.

16. The pelvic floor training apparatus of claim 15,

the processor is specifically configured to:

acquiring a pressure value of the pelvic floor muscle in a contraction state every time when pulse electrical stimulation training and/or biofeedback training is performed;

if the pressure value is smaller than the preset value after the continuous preset times, determining the state as the fatigue state of the pelvic floor muscles;

the processor is further specifically configured to:

performing at least one of modifying an action type, reducing a training height, shortening a contraction time, extending a relaxation time, and stopping a training, and/or performing at least one of reducing a current frequency, a current intensity, shortening a stimulation time, extending a rest time, and stopping a training, according to a fatigue state of the pelvic floor muscles.

17. A non-volatile storage medium having stored thereon instructions that, when executed, cause the processor to perform the method of any one of claims 1-8.

Technical Field

The disclosed embodiments of the present invention relate to the technical field of pelvic floor rehabilitation, and more particularly, to a parameter setting method of a pelvic floor training apparatus, and a non-volatile storage medium.

Background

The pelvic floor rehabilitation is training aiming at pelvic floor dysfunction diseases such as urinary incontinence, organ prolapse and the like, is essentially the training of pelvic floor muscles, and follows the training principle of common skeletal muscles, namely different muscle states need different training strengths, the training strength is gradually improved from low to high along with the gradual improvement of the muscle states, and the training form is from simple action to complex action.

In order to ensure the safety and the high efficiency of training, different training intensity schemes need to be formulated for different pelvic floor muscle states. In addition, during the training process, the state of the pelvic floor muscles is also constantly changing, either improving or worsening, and may also deteriorate.

Therefore, real-time adjustment of the training intensity is required to set the personalized rehabilitation regimen according to the real-time status of the pelvic floor muscles. At present, the personalized scheme for pelvic floor rehabilitation mainly depends on rich experience of a mentor or a trainer, and the program needs to be manually set in real time. This not only increases the operation difficulty, more importantly, for many instructors or trainers who lack the experience of pelvic floor rehabilitation, the setting of personalized scheme can not be accomplished at all, thereby seriously affecting the safety and training effect of pelvic floor rehabilitation.

Disclosure of Invention

According to an embodiment of the invention, the invention provides a pelvic floor training device and a parameter setting method thereof, which aim to solve the problems.

According to a first aspect of the present invention, there is disclosed a method of setting parameters of an exemplary pelvic floor training apparatus, comprising: obtaining initial information of pelvic floor muscles; determining training parameters corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information; and acquiring real-time pelvic floor muscle information when the pelvic floor training is executed according to the training parameters, and adaptively adjusting the training parameters according to the real-time pelvic floor muscle information.

According to a second aspect of the present invention, an exemplary pelvic floor training apparatus is disclosed, comprising a processor, a memory and a signal collector, the memory and the signal collector being respectively connected to the processor, the memory storing instructions, the signal collector being configured to collect pelvic floor muscle initial information and pelvic floor muscle real-time information, the instructions, when executed, causing the processor to: acquiring initial information of pelvic floor muscles acquired by the signal acquisition unit; determining training parameters corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information; and acquiring real-time pelvic floor muscle information acquired by the signal acquisition unit when pelvic floor training is performed according to the training parameters, and adaptively adjusting the training parameters according to the real-time pelvic floor muscle information.

According to a third aspect of the invention, an exemplary non-volatile storage medium is disclosed that stores instructions that, when executed, cause the processor to perform the method of the first aspect.

The invention has the following beneficial effects: the pelvic floor training is performed according to the training parameters corresponding to the initial information of the pelvic floor muscles, and the training parameters are adaptively adjusted according to the real-time information of the pelvic floor muscles, so that the personalized setting of the pelvic floor training performed by the pelvic floor training equipment and the automatic setting of the personalized training are realized, and the safety and the training effect of the pelvic floor training are ensured.

Drawings

The invention will be further described with reference to the accompanying drawings and embodiments, in which:

fig. 1 is a flowchart of a parameter setting method of a pelvic floor training device according to an embodiment of the present invention.

Fig. 2 is a schematic structural diagram of a pelvic floor training device according to an embodiment of the invention.

Fig. 3 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.

Detailed Description

In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution of the present invention is further described in detail below with reference to the accompanying drawings and the detailed description.

Fig. 1 is a flowchart of a parameter setting method of a pelvic floor training apparatus according to an embodiment of the present invention. The method can be executed by the pelvic floor training device, and can also be executed by terminal equipment, such as a mobile terminal like a mobile phone, a computer and the like, and the pelvic floor training device can execute pelvic floor training to reflect the state of the pelvic floor muscles, and the method comprises the following steps:

step 110: and acquiring initial information of the pelvic floor muscles.

As described above, the pelvic floor training is essentially the training of the pelvic floor muscles, wherein the pelvic floor training includes the pulse electrical stimulation training and the biofeedback training. The pulse electrical stimulation training is to excite and contract pelvic floor nerve muscles through pulse current so as to improve the functional state of the pelvic floor muscles, and the biofeedback training is to collect myoelectric signals and/or pressure signals of the pelvic floor muscles in a resting state and a contracted state, feed the myoelectric signals and/or the pressure signals back to a patient and guide the patient to carry out the active training of the pelvic floor muscles.

The pelvic floor muscle initial information is information representing the state of pelvic floor muscles when the pelvic floor training device starts to perform pelvic floor training on the pelvic floor muscles.

Step 120: and determining training parameters corresponding to the initial information of the pelvic floor muscles according to the initial information of the pelvic floor muscles.

And according to the training parameters corresponding to the initial information of the pelvic floor muscles, the pelvic floor training equipment starts to execute pelvic floor training.

The training parameters corresponding to the initial information of the pelvic floor muscles may be preset, and the present invention is not limited thereto. The training parameters include pulsed electrical stimulation training parameters, such as stimulation frequency, stimulation pulse width, single cycle stimulation time, single cycle rest time, cycle number, and the like, and/or biofeedback training parameters, such as action type, resting height, contraction height, single cycle contraction time, single cycle relaxation time, cycle number, and the like.

Step 130: obtaining real-time information of the pelvic floor muscles when the pelvic floor training is executed according to the training parameters, and adaptively adjusting the training parameters according to the real-time information of the pelvic floor muscles.

The pelvic floor muscle real-time information refers to information representing the state of pelvic floor muscles in the process of performing pelvic floor training by pelvic floor training equipment.

In the process of executing the pelvic floor training, the training parameters for carrying out the pelvic floor training are adaptively adjusted according to the real-time information of the pelvic floor muscles, namely the training parameters are adaptively adjusted along with the execution of the pelvic floor training, so that the automatic setting of the personalized training is completed, and the safety and the training effect of the pelvic floor training are ensured.

In the embodiment, the pelvic floor training is performed according to the training parameters corresponding to the initial information of the pelvic floor muscles, and the training parameters are adaptively adjusted according to the real-time information of the pelvic floor muscles, so that the personalized setting of the pelvic floor training performed by the pelvic floor training equipment and the automatic setting of the personalized training are realized, and the safety and the training effect of the pelvic floor training are ensured.

In some embodiments, the step 120 comprises:

and determining a preset pelvic floor muscle state grade corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information, and determining a training parameter corresponding to the pelvic floor muscle initial information according to the preset pelvic floor muscle state grade.

In some embodiments, electromyographic signal data, e.g., a maximum electromyographic signal value, of the pelvic floor muscle at one Maximum Voluntary Contraction (MVC) may be measured by the electrodes.

The pelvic floor muscle initial information includes an average value of maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles perform n Maximum Voluntary Contractions (MVC). Wherein n is an integer greater than 1. Specifically, the pelvic floor muscles are subjected to n times of maximum random contractions to respectively obtain n maximum electromyographic signal values, and then the n maximum electromyographic signal values are subjected to mean value operation to obtainThe calculation formula for representing the initial information of the pelvic floor muscles is as follows:

wherein, X_maxRepresents the maximum electromyographic signal value measured by one maximum voluntary contraction of the pelvic floor muscles. In some examples, n is 3.

Further, in some embodiments, the determining, according to the pelvic floor muscle initial information, a preset pelvic floor muscle state level corresponding to the pelvic floor muscle initial information, and then determining, according to the preset pelvic floor muscle state level, a training parameter corresponding to the pelvic floor muscle initial information includes:

and determining the preset pelvic floor muscle state grade to which the pelvic floor muscle initial information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal value, and further determining the training parameters corresponding to the pelvic floor muscle initial information.

The preset pelvic floor muscle state classification table records corresponding relations between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and preset training parameters.

The preset pelvic floor muscle state classification table may be pre-established.

Specifically, the pelvic floor muscle state is divided into different levels, namely different preset pelvic floor muscle state levels, according to the normal value range of the myoelectric signals when the pelvic floor muscles are contracted maximally and randomly. For example, assuming that the normal value range of the electromyographic signals when the pelvic floor muscles perform the maximum voluntary contraction is 40-50uV, the electromyographic signal value range of 0-5uV is divided into a preset pelvic floor muscle state level 0, the electromyographic signal value range of 5-10uV is divided into a preset pelvic floor muscle state level 1, the electromyographic signal value range of 10-20uV is divided into a preset pelvic floor muscle state level 2, the electromyographic signal value range of 20-30uV is divided into a preset pelvic floor muscle state level 3, the electromyographic signal value range of 30-40uV is divided into a preset pelvic floor muscle state level 4, and the electromyographic signal value range above 40uV is divided into a preset pelvic floor muscle state level 5. Thus, each electromyographic signal value range represents a predetermined pelvic floor muscle state level.

Then, preset training parameters are configured for each preset pelvic floor muscle state grade, wherein the preset training parameters comprise pulse electrical stimulation training parameters and biofeedback training parameters. For example, preset pelvic floor muscle state level 0 is configured with preset training parameters a0, preset pelvic floor muscle state level 1 is configured with preset training parameters a1, and so on, and preset pelvic floor muscle state level 5 is configured with preset training parameters a 5. When the pelvic floor muscles are in the preset pelvic floor muscle state level 0, the pelvic floor muscles cannot be actively trained, the pelvic floor muscles are not suitable for biofeedback training and can only be trained by pulse electrical stimulation, and at the moment, the preset training parameters A0 only comprise pulse electrical stimulation training parameters, such as stimulation frequency, stimulation pulse width, single-cycle stimulation time, single-cycle rest time and cycle times. When the pelvic floor muscles are respectively in the preset pelvic floor muscle states of 1-5 levels, the pelvic floor muscles can be actively trained, and at the moment, the preset training parameters A1-A5 comprise different pulse electrical stimulation training parameters, such as stimulation frequency, stimulation pulse width, single-cycle stimulation time, single-cycle rest time, cycle times and the like, and/or different biofeedback training parameters, such as action types, resting heights, contraction heights, single-cycle contraction times, single-cycle relaxation times, cycle times and the like. Therefore, the preset pelvic floor muscle state classification table records the corresponding relation between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and preset training parameters.

In the embodiment, the corresponding relation between different myoelectric signal value ranges representing different preset pelvic floor muscle state grades and preset training parameters is recorded through the preset pelvic floor muscle state classification table, so that the pelvic floor muscle states are divided into different grades according to the pelvic floor muscle myoelectric signal value ranges, the adaptive preset pelvic floor rehabilitation parameters are set according to the different grades, the corresponding pelvic floor rehabilitation parameters of the pelvic floor muscle initial information are determined through the preset pelvic floor muscle state classification table, personalized setting is realized, and the implementation is convenient.

In some embodiments, the pelvic floor training comprises biofeedback training, and the pelvic floor muscle real-time information comprises time-domain information and/or frequency-domain information representative of electromyographic signals of the pelvic floor muscles in a contracted state when the pelvic floor training device performs the biofeedback training. The myoelectric signals of the pelvic floor muscles in a contraction state in the process of performing the biofeedback training are required to be acquired, and the myoelectric signals can be acquired by combining the electrodes with corresponding technologies.

In the process of executing the biofeedback training, the electromyographic signals of the pelvic floor muscles in the contraction state are analyzed, and the real-time information of the pelvic floor muscles is represented by the time domain information and/or the frequency domain information of the electromyographic signals. The time domain information of the electromyographic signals comprises the average value of the electromyographic signals and the like, and the frequency domain information comprises the median frequency, the average power frequency and the like.

In one example, the step 130 of obtaining real-time information of the pelvic floor muscles when performing the pelvic floor training according to the training parameters comprises: obtaining an average value of electromyographic signals of pelvic floor muscles in a contracted state each time when performing biofeedback training

If the average value appears for the continuous preset times mAnd if the value is less than the preset value k, determining the fatigue state of the pelvic floor muscles. That is, ifIt is determined as the fatigue state of the pelvic floor muscles.

In another example, in step 130, obtaining real-time information of pelvic floor muscles while performing pelvic floor training includes: obtaining the average power frequency M of the electromyographic signals of the pelvic floor muscles in the contraction state every time when carrying out the biofeedback training_n(n-1, 2,3 …). Wherein the mean power frequency M of the electromyographic signals of the pelvic floor muscles in the contracted state every time_nThe calculation formula of (a) is as follows:

wherein, fs (f) is myoelectric data of the pelvic floor muscle in a contraction state every time, and s (f) is a corresponding frequency range.

If the average power frequency M appears for a continuous preset number M_nAnd if the value is less than the preset value g, determining the fatigue state of the pelvic floor muscles. That is, if M₁<k，M₂<k，…M_m<And k, determining the fatigue state of the pelvic floor muscles.

In the above example, when the pelvic floor muscles are in a state of pelvic floor muscle fatigue during the course of performing biofeedback training, the corresponding training parameters need to be adaptively adjusted.

At this time, in step 130, adaptively adjusting the training parameters according to the real-time information of the pelvic floor muscles, including: performing at least one of modifying an action type, lowering a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to a fatigue state of pelvic floor muscles.

Further, in some embodiments, in step 130, obtaining real-time information of the pelvic floor muscles during the pelvic floor training performed according to the training parameters includes: firstly, acquiring the average value of the maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to n times of maximum random contractions every preset time. Wherein n is an integer greater than 1. The preset time may be 5 minutes. And then, determining the preset pelvic floor muscle state grade to which the real-time pelvic floor muscle information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal value.

The preset pelvic floor muscle state classification table records corresponding relations between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and preset training parameters. The specific establishment of the classification table of the preset pelvic floor muscle state is described in the above embodiments, and for brevity, will not be described herein again.

In step 130, adaptively adjusting training parameters according to the real-time information of the pelvic floor muscles, including: and determining preset training parameters corresponding to the real-time information of the pelvic floor muscles according to the preset pelvic floor muscle state grade to which the real-time information of the pelvic floor muscles belongs from a preset pelvic floor muscle state classification table, and adjusting the preset training parameters as the training parameters.

In this embodiment, the pelvic floor muscle real-time information and the preset pelvic floor muscle state class to which the pelvic floor muscle real-time information belongs are acquired at intervals of preset time, and then the corresponding preset training parameters are determined from the preset pelvic floor muscle state classification table to adjust the preset training parameters to perform pelvic floor training, so that the pelvic floor training is continuously performed, the personalized setting of the pelvic floor training performed by the pelvic floor training equipment and the automatic setting of the personalized training are realized, and the safety and the training effect of the pelvic floor training are ensured.

In some embodiments, the pressure values of the pelvic floor muscles may be measured by deploying the electrodes' balloons.

The pelvic floor muscle initial information includes an average value of pressure values of the pelvic floor muscles when the pelvic floor muscles make n maximum voluntary contractions. Wherein n is an integer greater than 1. Specifically, the pelvic floor muscles perform n maximum random contractions to respectively obtain n pressure values Y_nThen, for n pressure values Y_nDoing a mean value operation to obtainThe calculation formula for representing the initial information of the pelvic floor muscles is as follows:

wherein, Y_nThe pressure values obtained by one maximum voluntary contraction of the pelvic floor muscles are indicated. In some examples, n is 3.

Further, in some embodiments, the determining, according to the pelvic floor muscle initial information, a preset pelvic floor muscle state level corresponding to the pelvic floor muscle initial information, and then determining, according to the preset pelvic floor muscle state level, a training parameter corresponding to the pelvic floor muscle initial information includes:

and determining the preset pelvic floor muscle state grade to which the pelvic floor muscle initial information belongs from a preset pelvic floor muscle pressure gauge according to the average value of the pressure values, and further determining training parameters corresponding to the pelvic floor muscle initial information.

The preset pelvic floor muscle pressure meter records corresponding relations between different pressure values representing different preset pelvic floor muscle state grades and preset training parameters, and the preset training parameters change along with the change of the pressure values.

The preset pelvic floor muscle pressure gauge may be pre-established. The preset training parameters include pulse electrical stimulation training parameters, such as stimulation frequency, stimulation pulse width, single-cycle stimulation time, single-cycle rest time, cycle times and the like, and/or biofeedback training parameters, such as action type, rest height, contraction height, single-cycle contraction time, single-cycle relaxation time, cycle times and the like.

Specifically, the preset training parameter B0 corresponding to the pressure value Y0 is preset.

Subsequently, comparing the pressure value Y1-Ym with the pressure value Y0, and correspondingly changing the preset training parameter B0 according to the change between the pressure value Y1-Ym and the pressure value Y0 to respectively obtain a preset training parameter B1-Bm, wherein the change can be synchronous increase, synchronous decrease, equal proportion change, unequal proportion change, fixed number value change, non-fixed number value change and the like. For example, for each 2% increase in these pressure values Y1-Ym, the stimulation frequency is increased by 1Hz, the stimulation pulse width is decreased by 10us, and the other parameters are unchanged, as compared to the pressure value Y0. Therefore, the corresponding relation between different pressure values and the preset training parameters is recorded by the preset pelvic floor muscle pressure meter, the preset training parameters change along with the change of the pressure values, and the pressure values Y1-Ym represent different preset pelvic floor muscle state grades respectively.

In the embodiment, the corresponding relation between different pressure values representing different preset pelvic floor muscle state levels and preset training parameters is recorded through the preset pelvic floor muscle pressure meter, the preset training parameters change along with the change of the pressure values, the corresponding training parameters of the pelvic floor muscle initial information are determined through the preset pelvic floor muscle pressure meter, the personalized setting of the pelvic floor training executed by the pelvic floor training equipment and the automatic setting of the personalized training are realized, and the implementation is convenient.

In some embodiments, the pelvic floor training comprises pulsed electrical stimulation training and/or biofeedback training. The pelvic floor muscle real-time information comprises pressure values of the pelvic floor muscles in a contracted state when pulse electrical stimulation training and/or biofeedback training is performed. The pressure value of the pelvic floor muscle in a contraction state in the process of pulse electrical stimulation training and/or biofeedback training needs to be acquired, and the pressure value can be acquired by combining the corresponding acquisition technology with the electrode-equipped air bag.

In the process of executing pulse electrical stimulation training and/or biofeedback training, the pressure signals of the pelvic floor muscles in the contraction state are analyzed, and the real-time information of the pelvic floor muscles is represented through the values of the pressure signals of the pelvic floor muscles in the contraction state.

In one example, the step 130 of obtaining real-time information of the pelvic floor muscles when performing the pelvic floor training according to the training parameters comprises: acquiring a pressure value of the pelvic floor muscle in a contraction state every time when pulse electrical stimulation training and/or biofeedback training is performed; and if the pressure value is less than the preset value after the continuous preset times, determining the fatigue state of the pelvic floor muscles.

In this example, when the pelvic floor muscles are in a fatigue state during the pulse electrical stimulation training and/or the biofeedback training, the corresponding training parameters need to be adaptively adjusted.

At this time, in step 130, adaptively adjusting the training parameters according to the real-time information of the pelvic floor muscles, including: performing at least one of modifying an action type, reducing a training height, shortening a contraction time, extending a relaxation time, and stopping a training, and/or performing at least one of reducing a current frequency, a current intensity, shortening a stimulation time, extending a rest time, and stopping a training, according to a fatigue state of the pelvic floor muscles.

In another example, the step 130 of obtaining real-time information of the pelvic floor muscles when performing the pelvic floor training according to the training parameters and adaptively adjusting the training parameters according to the real-time information of the pelvic floor muscles includes: firstly, acquiring a pressure value of the pelvic floor muscles in a contraction state when the pelvic floor muscles are subjected to maximum random contraction every preset time. The preset time may be 5 minutes. And then, according to the pressure value, determining a preset training parameter corresponding to the real-time information of the pelvic floor muscles from a preset pelvic floor muscle pressure gauge so as to adjust the preset training parameter as the training parameter.

The preset pelvic floor muscle pressure meter records and records corresponding relations between different pressure values and preset training parameters, and the preset training parameters change along with the change of the pressure values. The preset pelvic floor muscle pressure gauge is established in detail in the description of the above embodiment, and is not described herein for brevity.

Fig. 2 is a schematic structural diagram of the pelvic floor training device according to the embodiment of the present invention. The pelvic floor training device 200 comprises a processor 210, a trainer 220, a memory 230 and a signal collector 240, wherein the trainer 220, the memory 230 and the signal collector 240 are connected with the processor 210.

The trainer 220 is used to perform pelvic floor training and includes a pulsed electrical stimulation training circuit and/or a biofeedback training circuit.

The memory 230 is used for storing the preset pelvic floor muscle state classification table and the preset pelvic floor muscle pressure table in the above-described embodiments. Memory 230 may include read-only memory and/or random access memory, etc., and provides instructions and data to processor 210. A portion of the memory 230 may also include non-volatile random access memory (NVRAM).

The signal collector 240 may include electrodes and/or air bags with electrodes configured to collect electromyographic signals and/or pressure values of pelvic floor muscles in a contracted state during performing the pulse electrical stimulation training and/or the biofeedback training, but the present invention is not limited thereto.

The memory 230 stores instructions that, when executed, enable the processor 210, via the trainer 220, the signal collector 240, to implement the parameter setting method of the pelvic floor training device provided in any one of the above embodiments of the invention, as well as any non-conflicting combinations. The details of the parameter setting method are described in the above embodiments, and will not be described here.

In particular, the processor 210 is configured to:

obtaining initial information of pelvic floor muscles;

determining training parameters corresponding to the initial information of the pelvic floor muscles according to the initial information of the pelvic floor muscles; and

obtaining real-time information of the pelvic floor muscles when the pelvic floor training is executed according to the training parameters, and adaptively adjusting the training parameters according to the real-time information of the pelvic floor muscles.

The processor 210 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 210. The processor 210 may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed.

In some embodiments, processor 210 is specifically configured to:

and determining a preset pelvic floor muscle state grade corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information, and determining a training parameter corresponding to the pelvic floor muscle initial information according to the preset pelvic floor muscle state grade.

In some embodiments, the pelvic floor muscle initial information includes an average of maximum electromyographic signal values produced by the pelvic floor muscles when the pelvic floor muscles make a plurality of maximum voluntary contractions. The processor 210 is specifically configured to:

and determining a preset pelvic floor muscle state grade to which the pelvic floor muscle initial information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal values, and further determining a training parameter corresponding to the pelvic floor muscle initial information, wherein the preset pelvic floor muscle state classification table records corresponding relations between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and the preset training parameter.

In some embodiments, the pelvic floor muscle real-time information includes time domain information of electromyographic signals of the pelvic floor muscles in a contracted state. The processor 210 is specifically configured to:

acquiring the average value of electromyographic signals of pelvic floor muscles in a contraction state every time when biofeedback training is executed;

if the average value of the continuous preset times is smaller than the preset value, determining that the pelvic floor muscle is in a fatigue state;

the processor 210 is further specifically configured to:

performing at least one of modifying an action type, lowering a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to a fatigue state of pelvic floor muscles.

In some embodiments, the pelvic floor muscle real-time information includes frequency domain information of electromyographic signals of the pelvic floor muscles in a contracted state. The processor 210 is specifically configured to:

acquiring the average power frequency of electromyographic signals of pelvic floor muscles in a contraction state each time when biofeedback training is executed;

if the average power frequency is less than the preset value after the continuous preset times, determining the fatigue state of the pelvic floor muscles;

the processor 210 is further specifically configured to:

performing at least one of modifying an action type, lowering a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to a fatigue state of pelvic floor muscles.

In some embodiments, the pelvic floor muscle initial information includes an average of maximum electromyographic signal values produced by the pelvic floor muscles when the pelvic floor muscles make a plurality of maximum voluntary contractions. The processor 210 is specifically configured to:

acquiring the average value of the maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to multiple maximum random contractions every preset time;

determining a preset pelvic floor muscle state grade to which the real-time pelvic floor muscle information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal values;

the self-adaptive adjustment of training parameters according to the real-time information of the pelvic floor muscles comprises the following steps:

determining preset training parameters corresponding to the real-time pelvic floor muscle information from a preset pelvic floor muscle state classification table according to the preset pelvic floor muscle state grade to which the real-time pelvic floor muscle information belongs, and adjusting the preset training parameters as the training parameters;

the preset pelvic floor muscle state classification table records corresponding relations between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and preset training parameters.

In some embodiments, the pelvic floor muscle initial information includes an average of pressure values of the pelvic floor muscles when the pelvic floor muscles make a plurality of maximum voluntary contractions.

The processor 210 is specifically configured to:

and determining training parameters corresponding to the initial information of the pelvic floor muscles from a preset pelvic floor muscle pressure gauge according to the average value of the pressure values, wherein the preset pelvic floor muscle pressure gauge records the corresponding relation between different pressure values and the preset training parameters, and the preset training parameters change along with the change of the pressure values.

In some embodiments, processor 210 is specifically configured to:

acquiring a pressure value of the pelvic floor muscle in a contraction state every time when pulse electrical stimulation training and/or biofeedback training is performed;

if the pressure value is smaller than the preset value after the continuous preset times, determining the state as the fatigue state of the pelvic floor muscles;

the processor 210 is further specifically configured to:

performing at least one of modifying an action type, reducing a training height, shortening a contraction time, extending a relaxation time, and stopping a training, and/or performing at least one of reducing a current frequency, a current intensity, shortening a stimulation time, extending a rest time, and stopping a training, according to a fatigue state of the pelvic floor muscles.

As shown in fig. 3, which is a schematic structural diagram of a terminal device according to an embodiment of the present invention, the terminal device 300 may be a mobile terminal such as a mobile phone, a computer, or the like, and is connected to a pelvic floor training device, such as the pelvic floor training device 200 according to the above embodiment, and the terminal device 300 is used as a control terminal of the pelvic floor training device.

The terminal device 300 includes a memory 310, a processor 320, and a communication circuit 330. The memory 310 is connected to the processor 320.

Memory 310 may include read-only memory and/or random access memory, etc., and provides instructions and data to processor 320. A portion of the memory 310 may also include non-volatile random access memory (NVRAM). The memory 310 stores instructions that, when executed, implement the method for setting parameters of a pelvic floor training device provided by any one of the above-described embodiments of the invention, and any non-conflicting combinations.

The communication circuit 330 is used for transmitting and receiving data, and is an interface for the terminal device 300 to communicate with an external device.

The processor 320 performs the parameter setting method of the pelvic floor training apparatus of the above-described embodiment of the present invention through the communication circuit 330. In particular, upon execution of the instructions in the memory 310, the processor 320 is configured to:

obtaining initial information of pelvic floor muscles;

determining training parameters corresponding to the initial information of the pelvic floor muscles according to the initial information of the pelvic floor muscles; and

obtaining real-time information of the pelvic floor muscles when the pelvic floor training is executed according to the training parameters, and adaptively adjusting the training parameters according to the real-time information of the pelvic floor muscles.

Processor 320 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 320. The processor 320 may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed.

In some embodiments, processor 320 is specifically configured to:

and determining a preset pelvic floor muscle state grade corresponding to the pelvic floor muscle initial information according to the pelvic floor muscle initial information, and determining a training parameter corresponding to the pelvic floor muscle initial information according to the preset pelvic floor muscle state grade.

In some embodiments, the pelvic floor muscle initial information includes an average of maximum electromyographic signal values produced by the pelvic floor muscles when the pelvic floor muscles make a plurality of maximum voluntary contractions. Processor 320 is specifically configured to:

and determining a preset pelvic floor muscle state grade to which the pelvic floor muscle initial information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal values, and further determining a training parameter corresponding to the pelvic floor muscle initial information, wherein the preset pelvic floor muscle state classification table records corresponding relations between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and the preset training parameter.

In some embodiments, the pelvic floor muscle real-time information includes time domain information of electromyographic signals of the pelvic floor muscles in a contracted state. Processor 320 is specifically configured to:

acquiring the average value of electromyographic signals of pelvic floor muscles in a contraction state every time when biofeedback training is executed;

if the average value of the continuous preset times is smaller than the preset value, determining that the pelvic floor muscle is in a fatigue state;

processor 320 is further specifically configured to:

performing at least one of modifying an action type, lowering a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to a fatigue state of pelvic floor muscles.

In some embodiments, the pelvic floor muscle real-time information includes frequency domain information of electromyographic signals of the pelvic floor muscles in a contracted state. Processor 320 is specifically configured to:

acquiring the average power frequency of electromyographic signals of pelvic floor muscles in a contraction state each time when biofeedback training is executed;

if the average power frequency is less than the preset value after the continuous preset times, determining the fatigue state of the pelvic floor muscles;

processor 320 is further specifically configured to:

performing at least one of modifying an action type, lowering a training height, shortening a contraction time, lengthening a relaxation time, and stopping training, according to a fatigue state of pelvic floor muscles.

In some embodiments, the pelvic floor muscle initial information includes an average of maximum electromyographic signal values produced by the pelvic floor muscles when the pelvic floor muscles make a plurality of maximum voluntary contractions. Processor 320 is specifically configured to:

acquiring the average value of the maximum electromyographic signal values generated by the pelvic floor muscles when the pelvic floor muscles are subjected to multiple maximum random contractions every preset time;

determining a preset pelvic floor muscle state grade to which the real-time pelvic floor muscle information belongs from a preset pelvic floor muscle state classification table according to the average value of the maximum electromyographic signal values;

the self-adaptive adjustment of training parameters according to the real-time information of the pelvic floor muscles comprises the following steps:

determining preset training parameters corresponding to the real-time pelvic floor muscle information from a preset pelvic floor muscle state classification table according to the preset pelvic floor muscle state grade to which the real-time pelvic floor muscle information belongs, and adjusting the preset training parameters as the training parameters;

the preset pelvic floor muscle state classification table records corresponding relations between different electromyographic signal value ranges representing different preset pelvic floor muscle state grades and preset training parameters.

In some embodiments, the pelvic floor muscle initial information includes an average of pressure values of the pelvic floor muscles when the pelvic floor muscles make a plurality of maximum voluntary contractions.

Processor 320 is specifically configured to:

and determining training parameters corresponding to the initial information of the pelvic floor muscles from a preset pelvic floor muscle pressure gauge according to the average value of the pressure values, wherein the preset pelvic floor muscle pressure gauge records the corresponding relation between different pressure values and the preset training parameters, and the preset training parameters change along with the change of the pressure values.

In some embodiments, processor 320 is specifically configured to:

acquiring a pressure value of the pelvic floor muscle in a contraction state every time when pulse electrical stimulation training and/or biofeedback training is performed;

if the pressure value is smaller than the preset value after the continuous preset times, determining the state as the fatigue state of the pelvic floor muscles;

processor 320 is further specifically configured to:

performing at least one of modifying an action type, reducing a training height, shortening a contraction time, extending a relaxation time, and stopping a training, and/or performing at least one of reducing a current frequency, a current intensity, shortening a stimulation time, extending a rest time, and stopping a training, according to a fatigue state of the pelvic floor muscles.

It will be apparent to those skilled in the art that many modifications and variations can be made in the apparatus and method while maintaining the teachings of the present disclosure. Accordingly, the above disclosure should be considered limited only by the scope of the following claims.