Feedback-type efficiency-enhanced electrical stimulation method and device

Abstract

The invention provides a feedback-type efficiency-enhanced electrical stimulation method and device. The method comprises the following steps: acquiring voice feedback information and muscle force state feedback information of electrical stimulation operation of a living body; based on the voice feedback information and the muscle force state feedback information, determining a subjective and objective intensity actual value corresponding to the organism electrical stimulation operation; and determining a target adjustment value of the electrical stimulation intensity of the organism electrical stimulation operation based on the subjective and objective intensity actual value and a subjective and objective intensity expected value corresponding to the organism electrical stimulation operation. According to the technical scheme, the intelligent level and accuracy of electrical stimulation intensity adjustment are improved.

Description

[Technical Field]

[0001] This application relates to the field of electrical stimulation training optimization technology, and in particular to a feedback-based efficacy-enhancing electrical stimulation method and device. [Background Technology]

[0002] Currently, athletes and rehabilitation patients often require electrical stimulation devices to provide electrical stimulation to help them improve muscle strength. Most electrical stimulation devices can provide multiple levels of electrical stimulation intensity, each corresponding to a fixed intensity. Athletes or rehabilitation patients can choose the appropriate level based on their own needs or tolerance level.

[0003] However, this method of selecting intensity levels results in overly uniform electrical stimulation for athletes or rehabilitation patients, making it impossible to tailor the stimulation to their individual needs or tolerance levels. To address this, related technologies propose setting adjustable values ​​for each intensity level of the electrical stimulation device, allowing adjustments based on real-time active evaluations from athletes or rehabilitation patients. However, this adjustment method heavily relies on human experience; setting it too high can cause overstimulation and even harm, while setting it too low requires further adjustments, incurring excessive time costs, both of which hinder the smooth and efficient conduct of electrical stimulation training.

[0004] Therefore, how to reasonably optimize the intensity of electrical stimulation in electrical stimulation training has become an urgent technical problem to be solved. [Summary of the Invention]

[0005] This application provides a feedback-based efficacy-enhancing electrical stimulation method and apparatus, aiming to solve the technical problem in related technologies where inaccurate adjustment of electrical stimulation intensity leads to difficulty in meeting the high efficiency requirements of electrical stimulation training.

[0006] In a first aspect, embodiments of this application provide a feedback-based efficacy-enhancing electrical stimulation method, comprising:

[0007] Acquire voice feedback and muscle strength feedback information from bio-electrical stimulation operations;

[0008] Based on the voice feedback information and the muscle strength status feedback information, the actual subjective and objective intensity values ​​corresponding to the bio-electric stimulation operation are determined.

[0009] Based on the actual subjective and objective intensity values ​​and the expected subjective and objective intensity values ​​corresponding to the biological electrical stimulation operation, the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation is determined.

[0010] Optionally, in one embodiment of this application, acquiring the voice feedback information and muscle strength status feedback information of the bio-electrical stimulation operation includes:

[0011] Real-time voice information is periodically collected after the start of the bio-electrostimulation operation.

[0012] Detect whether the real-time voice information contains a target keyword that matches a preset electrical stimulation intensity feedback keyword;

[0013] If the real-time voice information contains the target keyword, the voice evaluation value corresponding to the target keyword is determined as the voice feedback information of the bio-electrostimulation operation.

[0014] In one embodiment of this application, optionally, the acquisition of voice feedback information and muscle strength status feedback information of bio-electrical stimulation operation further includes:

[0015] Extract the response features of the electrical stimulation object of the biological electrical stimulation operation, wherein the response features include integrated electromyography value, root mean square value, waveform length, information entropy, median frequency and average power frequency;

[0016] Based on the response characteristics and a preset support vector machine regression algorithm, the muscle strength state value of the electrically stimulated object is determined as feedback information on the muscle strength state of the biological body during electrical stimulation.

[0017] In one embodiment of this application, optionally, determining the actual subjective and objective intensity value corresponding to the bio-electrical stimulation operation based on the voice feedback information and the muscle strength state feedback information includes:

[0018] The ratio of the voice evaluation value to a preset evaluation expectation value is obtained as a subjective feature; and

[0019] The ratio of the muscle strength state value to the preset expected muscle strength state value is obtained as an objective feature;

[0020] Based on the current weights of the subjective and objective features, a weighted summation is performed on the subjective and objective features to obtain the actual subjective and objective intensity values ​​corresponding to the bio-electrostimulation operation.

[0021] Optionally, in one embodiment of this application, before performing a weighted summation on the subjective features and the objective features, the method further includes:

[0022] For multiple historical electrical stimulation operations

[0023] The first proportion of historical electrical stimulation operations that match the voice evaluation value with the preset evaluation expectation value is determined;

[0024] The current weight of the subjective feature is set by the preset weight of the subjective feature and the average of the first proportion; and

[0025] The second proportion of historical electrical stimulation operations that match the muscle strength state value with the preset muscle strength state expectation value is determined;

[0026] The average of the preset weight of the objective feature and the second proportion is set as the current weight of the objective feature.

[0027] In one embodiment of this application, optionally, determining the target adjustment value of the electrical stimulation intensity of the bio-electrical stimulation operation based on the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the bio-electrical stimulation operation includes:

[0028] Based on the actual values ​​of subjective and objective intensity and the expected values ​​of subjective and objective intensity corresponding to the bio-electro-stimulation operation, the subjective and objective intensity error and the rate of change of subjective and objective intensity error corresponding to the bio-electro-stimulation operation are determined.

[0029] Based on the subjective and objective intensity error and the rate of change of the subjective and objective intensity error, the incremental stimulation amplitude of the biological electrical stimulation operation is retrieved from the preset fuzzy control lookup table.

[0030] Based on the stimulus amplitude increment, the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation is determined.

[0031] In one embodiment of this application, optionally, determining the target adjustment value of the electrical stimulation intensity of the bio-electro-stimulation operation based on the stimulation amplitude increment includes:

[0032] Based on the stimulation amplitude increment hit by the bio-electro-stimulation operation and the membership degree of the fuzzy control rule corresponding to the stimulation amplitude increment, the target adjustment value of the electro-stimulation intensity of the bio-electro-stimulation operation is determined, wherein...

[0033]

[0034] u represents the target adjustment value of the electrical stimulation intensity of the bio-electro-stimulation operation, n is the number of stimulation amplitude increments hit by the bio-electro-stimulation operation, and y i v is the amplitude increment of the i-th stimulus. i Let be the membership degree of the fuzzy control rule corresponding to the amplitude increment of the i-th stimulus.

[0035] In one embodiment of this application, optionally, determining the target adjustment value of the electrical stimulation intensity of the bio-electrical stimulation operation based on the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the bio-electrical stimulation operation includes:

[0036] Determine the difference between the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the bio-electrostimulation operation;

[0037] Obtain a first mapping value of the difference in the voice feedback dimension and a second mapping value in the muscle strength state feedback dimension, wherein the first mapping value is the product of the subjective feature and the difference, and the second mapping value is the product of the objective feature and the difference;

[0038] Based on the first mapping value and the second mapping value, the degree of difference between the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the bio-electrostimulation operation is determined;

[0039] Determine the preset range of differences to which the difference belongs;

[0040] The preset adjustment value corresponding to the preset difference range is set as the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation.

[0041] Secondly, embodiments of this application provide a feedback-type efficacy-enhancing electrical stimulation device, comprising:

[0042] The initial information acquisition unit is used to acquire voice feedback information and muscle strength status feedback information of the bio-body electrical stimulation operation;

[0043] The subjective and objective intensity determination unit is used to determine the actual value of the subjective and objective intensity corresponding to the bio-electrical stimulation operation based on the voice feedback information and the muscle strength state feedback information.

[0044] The adjustment value determination unit is used to determine the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation based on the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the biological electrical stimulation operation.

[0045] Optionally, in one embodiment of this application, the initial information acquisition unit includes:

[0046] The voice feedback information acquisition unit is used to periodically collect real-time voice information after the start of the bio-electrostimulation operation, and detect whether the real-time voice information contains a target keyword that matches a preset electrostimulation intensity feedback keyword. If the real-time voice information contains the target keyword, the voice evaluation value corresponding to the target keyword is determined as the voice feedback information of the bio-electrostimulation operation.

[0047] Optionally, in one embodiment of this application, the initial information acquisition unit includes:

[0048] The muscle strength state feedback information acquisition unit is used to extract the response features of the electrically stimulated object in the bio-electrical stimulation operation. The response features include integrated electromyography value, root mean square value, waveform length, information entropy, median frequency, and average power frequency. Based on the response features and a preset support vector machine regression algorithm, the muscle strength state value of the electrically stimulated object is determined as the muscle strength state feedback information of the bio-electrical stimulation operation.

[0049] Optionally, in one embodiment of this application, the subjective / objective intensity determination unit includes:

[0050] The first feature acquisition unit is used to acquire the ratio of the voice evaluation value to the preset evaluation expectation value as a subjective feature;

[0051] The second feature acquisition unit is used to acquire the ratio of the muscle strength state value to the preset muscle strength state expected value as an objective feature;

[0052] The calculation unit is used to perform a weighted summation of the subjective features and the objective features based on their respective current weights, to obtain the actual subjective and objective intensity values ​​corresponding to the bio-electrostimulation operation.

[0053] Optionally, in one embodiment of this application, the subjective / objective intensity determination unit further includes:

[0054] The weight acquisition unit is used to, before performing weighted summation on the subjective features and the objective features, determine, for multiple historical electrical stimulation operations, a first proportion of historical electrical stimulation operations in which the voice evaluation value matches a preset evaluation expectation value, and set the current weight of the subjective feature by the average of the preset weight of the subjective feature and the first proportion; and to determine a second proportion of historical electrical stimulation operations in which the muscle strength state value matches a preset muscle strength state expectation value, and set the current weight of the objective feature by the average of the preset weight of the objective feature and the second proportion.

[0055] Optionally, in one embodiment of this application, the adjustment value determination unit includes:

[0056] An error calculation unit is used to determine the subjective and objective intensity error and the rate of change of subjective and objective intensity error corresponding to the biological electrical stimulation operation based on the actual value of subjective and objective intensity and the expected value of subjective and objective intensity corresponding to the biological electrical stimulation operation.

[0057] The stimulation amplitude increment retrieval unit is used to retrieve the stimulation amplitude increment hit by the bio-electro-stimulation operation from a preset fuzzy control lookup table based on the subjective and objective intensity error and the rate of change of the subjective and objective intensity error.

[0058] The first execution unit is used to determine the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation based on the stimulation amplitude increment.

[0059] Optionally, in one embodiment of this application, the execution unit is specifically used for:

[0060] Based on the stimulation amplitude increment hit by the bio-electro-stimulation operation and the membership degree of the fuzzy control rule corresponding to the stimulation amplitude increment, the target adjustment value of the electro-stimulation intensity of the bio-electro-stimulation operation is determined, wherein...

[0061]

[0062] u represents the target adjustment value of the electrical stimulation intensity of the bio-electro-stimulation operation, n is the number of stimulation amplitude increments hit by the bio-electro-stimulation operation, and y i v is the amplitude increment of the i-th stimulus. i Let be the membership degree of the fuzzy control rule corresponding to the amplitude increment of the i-th stimulus.

[0063] Optionally, in one embodiment of this application, the adjustment value determination unit includes:

[0064] The difference determination unit is used to determine the difference between the actual value of the subjective and objective intensity and the expected value of the subjective and objective intensity corresponding to the bio-electrostimulation operation;

[0065] A mapping value acquisition unit is used to acquire a first mapping value of the difference in the voice feedback dimension and a second mapping value in the muscle strength state feedback dimension, wherein the first mapping value is the product of the subjective feature and the difference, and the second mapping value is the product of the objective feature and the difference;

[0066] The difference calculation unit is used to determine the difference between the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the bio-electrostimulation operation based on the first mapping value and the second mapping value.

[0067] A difference range determination unit is used to determine the preset difference range to which the difference belongs;

[0068] The second execution unit is used to set the preset adjustment value corresponding to the preset difference range as the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation.

[0069] Thirdly, embodiments of this application provide a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform the method described in the first aspect above.

[0070] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions for performing the method described in the first aspect above.

[0071] The above technical solution addresses the technical problem of inaccurate electrical stimulation intensity adjustment in related technologies, which hinders the achievement of high efficiency in electrical stimulation training. It determines the adjustment value of the electrical stimulation intensity based on the subjective and objective intensity reflected by the trainee's real-time voice feedback and actual muscle strength state. In other words, it adjusts the electrical stimulation intensity based on the actual subjective and objective intensity values ​​corresponding to the trainee's real-time perception and actual muscle strength state, ensuring that the adjusted electrical stimulation intensity achieves the desired subjective and objective intensity. This replaces the uncertainty of manual adjustment of electrical stimulation intensity and comprehensively considers the trainee's real-time perception and actual muscle strength state, avoiding the problem of inaccurate electrical stimulation intensity adjustment due to considering only a single condition, thus improving the intelligence and accuracy of electrical stimulation intensity adjustment. [Attached Image Description]

[0072] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0073] Figure 1 A flowchart of a feedback-based efficacy-enhancing electrical stimulation method according to an embodiment of this application is shown;

[0074] Figure 2 A schematic diagram of a feedback-based efficacy-enhancing electrical stimulation method according to another embodiment of this application is shown;

[0075] Figure 3 It shows Figure 2 Structure diagram of a fuzzy controller;

[0076] Figure 4 A block diagram of a computer device according to one embodiment of this application is shown;

[0077] Figure 5 A block diagram of a computer device according to another embodiment of this application is shown.

Detailed Implementation Methods

[0078] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0079] Figure 1 A flowchart of a feedback-based efficacy-enhancing electrical stimulation method according to an embodiment of this application is shown.

[0080] like Figure 1 As shown, a feedback-based efficacy-enhancing electrical stimulation method according to an embodiment of this application includes:

[0081] Step 102: Obtain the voice feedback information and muscle strength status feedback information of the bio-electrical stimulation operation.

[0082] Bio-electrostimulation is performed by an electrical stimulation device to apply electrical stimulation to a training subject in order to improve muscle strength at the site of the applied electrical stimulation. The training subject mentioned here includes, but is not limited to, athletes, rehabilitation patients, or any organism that needs to improve muscle strength.

[0083] The voice feedback information is the voice content of the training subject's real-time evaluation of the bioelectric stimulation operation. Optionally, the voice feedback information can be obtained in the following ways.

[0084] First, real-time speech information is periodically acquired after the start of the bio-electrical stimulation operation. Periodic acquisition here refers to performing real-time speech acquisition within a specified and continuous time period. For example, starting from the start of the bio-electrical stimulation operation, the real-time speech acquisition operation is performed cyclically every 3 minutes. Of course, the 3-minute period mentioned here is merely an example; in actual scenarios, the time period for acquiring real-time speech information can be any length that meets the needs of actual electrical stimulation training.

[0085] The specified feedback duration refers to the recording time after the termination of the bio-electrical stimulation operation. During this recording time, real-time feedback information from the training subject is collected for automatic adjustment of the electrical stimulation intensity.

[0086] Optionally, a prompt will be issued when the specified feedback duration begins, such as a voice prompt or an indicator light prompt, so that the trainee is aware of it.

[0087] Next, it is detected whether the real-time voice information contains a target keyword that matches the preset electrical stimulation intensity feedback keyword.

[0088] The preset electrical stimulation intensity feedback keywords reflect the level of electrical stimulation intensity. If the real-time voice information contains a target keyword that matches the preset electrical stimulation intensity feedback keywords, then the target keyword reflects the level of electrical stimulation intensity recognized by the training subject. Therefore, if the real-time voice information contains the target keyword, the voice evaluation value corresponding to the target keyword is determined as the voice feedback information for the bio-electrical stimulation operation.

[0089] Muscle strength feedback information reflects the actual response of the muscles in the body parts of the trainee to electrical stimulation. The process of collecting muscle strength feedback information is as follows.

[0090] First, the response characteristics of the electrical stimulation object of the biological electrical stimulation operation are extracted, wherein the response characteristics include, but are not limited to, one or more of the following: integrated electromyography (iEMG), root mean square (RMS), waveform length (WL), information entropy (SE), median frequency (MF), and average power frequency (MPF).

[0091] Next, based on the response features and a preset support vector machine regression algorithm, the muscle strength state value of the electrically stimulated object is determined as feedback information on the muscle strength state of the organism during electrical stimulation. The support vector machine regression algorithm is used to locate the overall situation of an object through partial features. In the current scenario, the support vector machine regression algorithm can determine the muscle strength state value of the electrically stimulated object (i.e., the body part of the training object receiving electrical stimulation) based on the integrated electromyographic value and median frequency corresponding to the training object's performance in response to the current electrical stimulation.

[0092] Step 104: Based on the voice feedback information and the muscle strength status feedback information, determine the actual subjective and objective intensity values ​​corresponding to the bio-electrical stimulation operation.

[0093] The voice feedback information and the muscle strength status feedback information reflect the trainee's perception of the bioelectric stimulation operation in the trainee's sensory dimension and the trainee's actual physical response characteristics dimension, respectively. Therefore, the actual subjective and objective intensity values ​​corresponding to the bioelectric stimulation operation can be determined based on the information of the former subjective evaluation dimension and the latter objective evaluation dimension.

[0094] In one possible design, step 104 specifically includes: obtaining the ratio of the voice evaluation value to a preset evaluation expectation value as a subjective feature; and obtaining the ratio of the muscle strength state value to a preset muscle strength state expectation value as an objective feature; and performing a weighted summation on the subjective feature and the objective feature based on their respective current weights to obtain the actual subjective and objective intensity values ​​corresponding to the bio-electrical stimulation operation.

[0095] In other words, the features of the training object's perception dimension are abstracted into the ratio of the voice evaluation value to the preset evaluation expectation value, and the features of the training object's actual bodily response dimension are abstracted into the ratio of the muscle strength state value to the preset muscle strength state expectation value. The two ratios are then weighted and summed to obtain the final actual subjective and objective intensity values.

[0096] Optionally, the sum of the current weight of the subjective feature and the current weight of the objective feature is 1.

[0097] In one possible design, before performing a weighted summation on the subjective and objective features, it is necessary to obtain their current weights, which can be done in the following way.

[0098] For multiple historical electrical stimulation operations, a first proportion of historical electrical stimulation operations whose voice evaluation values ​​match preset evaluation expectations is determined, and the current weight of the subjective feature is set by the average of the preset weights of the subjective features and the first proportion. Similarly, a second proportion of historical electrical stimulation operations whose muscle strength values ​​match preset muscle strength expectations is determined, and the current weight of the objective feature is set by the average of the preset weights of the objective features and the second proportion.

[0099] Therefore, the first proportion reflects the contribution of speech evaluation values ​​to the electrical stimulation intensity adjustment results in historical data, while the preset weight reflects the expected contribution of speech evaluation values ​​to the electrical stimulation intensity adjustment results. The current weight of subjective features is the average of the two, indicating that the weight of subjective features is jointly determined by the contribution of their corresponding features in historical data and the expected level of sharing. The second proportion reflects the contribution of muscle strength values ​​to the electrical stimulation intensity adjustment results in historical data, while the preset weight reflects the expected contribution of muscle strength values ​​to the electrical stimulation intensity adjustment results. The current weight of objective features is the average of the two, indicating that the weight of objective features is jointly determined by the contribution level of their corresponding features in historical data and the expected level of sharing.

[0100] This allows for the determination of current weights that more accurately reflect the contribution levels of subjective and objective characteristics. This facilitates the more accurate calculation of the actual values ​​of subjective and objective intensity based on these current weights, thereby improving the accuracy of subsequent electrical stimulation intensity regulation.

[0101] Step 106: Based on the actual subjective and objective intensity values ​​and the expected subjective and objective intensity values ​​corresponding to the biological electrical stimulation operation, determine the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation.

[0102] The actual subjective and objective intensity values ​​reflect the actual contributions of the speech evaluation value and muscle strength status value to the adjustment result of the electrical stimulation intensity, while the expected subjective and objective intensity values ​​reflect the intensity that the current biological electrical stimulation operation should achieve when the expected level of muscle strength improvement is reached. The difference between the two reflects the gap between the current electrical stimulation intensity and the actual required electrical stimulation intensity. Therefore, the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation can be determined based on the difference between the two.

[0103] The above technical solution determines the adjustment value of the electrical stimulation intensity for bio-stimulation based on the subjective and objective intensity reflected by the real-time feedback of the trainee's voice and the trainee's actual muscle strength state. In other words, it adjusts the electrical stimulation intensity according to the actual subjective and objective intensity values ​​corresponding to the trainee's real-time perception and actual muscle strength state, so that the adjusted electrical stimulation intensity brings the desired subjective and objective intensity. This replaces the uncertainty of manual adjustment of electrical stimulation intensity, and comprehensively considers the trainee's real-time perception and actual muscle strength state, avoiding the problem of inaccurate electrical stimulation intensity adjustment due to considering only a single condition, thus improving the intelligence and accuracy of electrical stimulation intensity adjustment.

[0104] Figure 2 A schematic diagram of a feedback-based efficacy-enhancing electrical stimulation method according to another embodiment of this application is shown.

[0105] like Figure 2 As shown, on the one hand, the electrical stimulation device collects the surface electromyography information of the training subjects through multiple channels, extracts features such as integral electromyography value and median frequency from it, uses them for support vector machine regression algorithm, and finally outputs muscle strength state value as muscle strength state feedback information.

[0106] On the other hand, the trainees provide voice input to the electrical stimulation device, which then uses a voice-intensity sensory recognition model to determine the trainees' evaluation of the electrical stimulation intensity. Specifically, six input voice feedback messages, ranging from 0 to 5, can be set, where "0" corresponds to no sensation, "1" to just a slight sensation, "2" to a relatively strong sensation, "3" to a comfortable sensation, "4" to pain, and "5" to relatively strong pain.

[0107] Next, the voice feedback information and muscle strength feedback information are comprehensively quantified subjectively and objectively. The method of comprehensive quantification includes: obtaining the ratio of the voice evaluation value to the preset evaluation expectation value as a subjective feature; and obtaining the ratio of the muscle strength value to the preset muscle strength expectation value as an objective feature; based on the current weights of the subjective feature and the objective feature, the subjective feature and the objective feature are weighted and summed to obtain the actual subjective and objective intensity values ​​corresponding to the bio-electric stimulation operation.

[0108] Furthermore, by performing fuzzy learning processing on the actual values ​​and expected values ​​of subjective and objective intensity using a fuzzy controller, a target adjustment value for the electrical stimulation intensity is obtained. The required stimulation intensity is then generated according to this target adjustment value and sent to the electrical stimulator, which applies electrical stimulation to the training subject's body according to this stimulation intensity.

[0109] like Figure 3 As shown, in the fuzzy controller, firstly, based on the actual values ​​of subjective and objective intensity y... r The subjective and objective intensity expectation y corresponding to the bio-electrical stimulation operation k The subjective and objective intensity error e and the rate of change Δe of the subjective and objective intensity error corresponding to the electrical stimulation operation on the organism were determined.

[0110] Next, the precise values ​​of the subjective and objective intensity error e and the rate of change of the subjective and objective intensity error Δe are fuzzified into fuzzy values. Then, the decision logic in the knowledge base, i.e., the preset fuzzy control lookup table, is called to determine the stimulus amplitude increment corresponding to the fuzzy value. Finally, the stimulus amplitude increment is defuzzified into a precise value, which is used as the target adjustment value.

[0111] At this point, the original electrical stimulation intensity is corrected using the target adjustment value.

[0112] The preset fuzzy control query table is shown in Table 1 below.

[0113] Table 1

[0114]

[0115] Specifically, based on the subjective and objective intensity error and the rate of change of the subjective and objective intensity error, the incremental stimulation amplitude of the bio-electrostimulation operation can be retrieved from a preset fuzzy control lookup table. It should be noted that the subjective and objective intensity error and the rate of change of the subjective and objective intensity error in the preset fuzzy control lookup table shown in Table 1 are only one example. In actual scenarios, the subjective and objective intensity error and the rate of change of the subjective and objective intensity error in the preset fuzzy control lookup table can be any other possible values, and are not limited to this example.

[0116] Furthermore, based on the stimulus amplitude increment, a target adjustment value for the electrical stimulation intensity of the biological electrical stimulation operation is determined.

[0117] Specifically, the target adjustment value is calculated as follows: based on the stimulus amplitude increment hit by the bio-electrical stimulation operation and the membership degree of the fuzzy control rule corresponding to the stimulus amplitude increment, the target adjustment value of the electrical stimulation intensity of the bio-electrical stimulation operation is determined, wherein...

[0118]

[0119] u represents the target adjustment value of the electrical stimulation intensity of the bio-electro-stimulation operation, n is the number of stimulation amplitude increments hit by the bio-electro-stimulation operation, and y i v is the amplitude increment of the i-th stimulus. i Let be the membership degree of the fuzzy control rule corresponding to the amplitude increment of the i-th stimulus.

[0120] This allows for the acquisition of accurate target adjustment values, thereby improving the accuracy of electrical stimulation intensity regulation.

[0121] exist Figure 1 Based on the illustrated embodiment, in addition to using a fuzzy controller to determine the target adjustment value, another design can be used to calculate the target adjustment value.

[0122] Specifically, firstly, the difference between the actual value of the subjective and objective intensity and the expected value of the subjective and objective intensity corresponding to the bio-electrical stimulation operation is determined. This difference reflects the difference between the actual effect and the expected effect of the electrical stimulation training.

[0123] Next, the first mapping value of the difference in the voice feedback dimension and the second mapping value in the muscle strength status feedback dimension are obtained.

[0124] The first mapping value is the product of the subjective feature and the difference, reflecting the level of performance of the difference between the actual and expected effects of electrical stimulation training in the dimension of the trainee's speech evaluation. The second mapping value is the product of the objective feature and the difference, reflecting the level of performance of the difference between the actual and expected effects of electrical stimulation training in the dimension of the trainee's muscle strength response.

[0125] Furthermore, based on the first mapping value and the second mapping value, the degree of difference between the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the bio-electrical stimulation operation is determined. This degree of difference reflects the comprehensive performance level of the difference between the actual effect and the expected effect of electrical stimulation training in the two dimensions of the training subject's speech evaluation and muscle strength response.

[0126] Optionally, the difference is a weighted average of the first mapping value and the second mapping value, wherein the weight of the first mapping value is the same as the current weight of the subjective feature, and the weight of the second mapping value is the same as the current weight of the objective feature.

[0127] Finally, a preset range of differences is determined, and a preset adjustment value corresponding to the preset range of differences is set as the target adjustment value for the electrical stimulation intensity of the bio-electrostimulation operation. In other words, the difference can be divided into multiple ranges, and a preset adjustment value adapted to the actual needs of each range can be set.

[0128] Therefore, by combining the differences between the actual and expected effects of electrical stimulation training at different dimensions, the target adjustment value required for electrical stimulation intensity can be accurately calculated, thus improving the accuracy of electrical stimulation intensity adjustment.

[0129] This application provides a feedback-type efficacy-enhancing electrical stimulation device, comprising:

[0130] The initial information acquisition unit is used to acquire voice feedback information and muscle strength status feedback information of the bio-body electrical stimulation operation;

[0131] The subjective and objective intensity determination unit is used to determine the actual value of the subjective and objective intensity corresponding to the bio-electrical stimulation operation based on the voice feedback information and the muscle strength state feedback information.

[0132] The adjustment value determination unit is used to determine the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation based on the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the biological electrical stimulation operation.

[0133] Optionally, in one embodiment of this application, the initial information acquisition unit includes:

[0134] The voice feedback information acquisition unit is used to periodically collect real-time voice information after the start of the bio-electrostimulation operation, and detect whether the real-time voice information contains a target keyword that matches a preset electrostimulation intensity feedback keyword. If the real-time voice information contains the target keyword, the voice evaluation value corresponding to the target keyword is determined as the voice feedback information of the bio-electrostimulation operation.

[0135] Optionally, in one embodiment of this application, the initial information acquisition unit includes:

[0136] The muscle strength state feedback information acquisition unit is used to extract the response features of the electrically stimulated object in the bio-electrical stimulation operation. The response features include integrated electromyography value, root mean square value, waveform length, information entropy, median frequency, and average power frequency. Based on the response features and a preset support vector machine regression algorithm, the muscle strength state value of the electrically stimulated object is determined as the muscle strength state feedback information of the bio-electrical stimulation operation.

[0137] Optionally, in one embodiment of this application, the subjective / objective intensity determination unit includes:

[0138] The first feature acquisition unit is used to acquire the ratio of the voice evaluation value to the preset evaluation expectation value as a subjective feature;

[0139] The second feature acquisition unit is used to acquire the ratio of the muscle strength state value to the preset muscle strength state expected value as an objective feature;

[0140] The calculation unit is used to perform a weighted summation of the subjective features and the objective features based on their respective current weights, to obtain the actual subjective and objective intensity values ​​corresponding to the bio-electrostimulation operation.

[0141] Optionally, in one embodiment of this application, the subjective / objective intensity determination unit further includes:

[0142] The weight acquisition unit is used to, before performing weighted summation on the subjective features and the objective features, determine, for multiple historical electrical stimulation operations, a first proportion of historical electrical stimulation operations in which the voice evaluation value matches a preset evaluation expectation value, and set the current weight of the subjective feature by the average of the preset weight of the subjective feature and the first proportion; and to determine a second proportion of historical electrical stimulation operations in which the muscle strength state value matches a preset muscle strength state expectation value, and set the current weight of the objective feature by the average of the preset weight of the objective feature and the second proportion.

[0143] Optionally, in one embodiment of this application, the adjustment value determination unit includes:

[0144] An error calculation unit is used to determine the subjective and objective intensity error and the rate of change of subjective and objective intensity error corresponding to the biological electrical stimulation operation based on the actual value of subjective and objective intensity and the expected value of subjective and objective intensity corresponding to the biological electrical stimulation operation.

[0145] The stimulation amplitude increment retrieval unit is used to retrieve the stimulation amplitude increment hit by the bio-electro-stimulation operation from a preset fuzzy control lookup table based on the subjective and objective intensity error and the rate of change of the subjective and objective intensity error.

[0146] The first execution unit is used to determine the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation based on the stimulation amplitude increment.

[0147] Optionally, in one embodiment of this application, the execution unit is specifically used for:

[0148] Based on the stimulation amplitude increment hit by the bio-electro-stimulation operation and the membership degree of the fuzzy control rule corresponding to the stimulation amplitude increment, the target adjustment value of the electro-stimulation intensity of the bio-electro-stimulation operation is determined, wherein...

[0149]

[0150] u represents the target adjustment value of the electrical stimulation intensity of the bio-electro-stimulation operation, n is the number of stimulation amplitude increments hit by the bio-electro-stimulation operation, and y i v is the amplitude increment of the i-th stimulus.i Let be the membership degree of the fuzzy control rule corresponding to the amplitude increment of the i-th stimulus.

[0151] Optionally, in one embodiment of this application, the adjustment value determination unit includes:

[0152] The difference determination unit is used to determine the difference between the actual value of the subjective and objective intensity and the expected value of the subjective and objective intensity corresponding to the bio-electrostimulation operation;

[0153] A mapping value acquisition unit is used to acquire a first mapping value of the difference in the voice feedback dimension and a second mapping value in the muscle strength state feedback dimension, wherein the first mapping value is the product of the subjective feature and the difference, and the second mapping value is the product of the objective feature and the difference;

[0154] The difference calculation unit is used to determine the difference between the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the bio-electrostimulation operation based on the first mapping value and the second mapping value.

[0155] A difference range determination unit is used to determine the preset difference range to which the difference belongs;

[0156] The second execution unit is used to set the preset adjustment value corresponding to the preset difference range as the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation.

[0157] The device uses the solution described in any one of the above embodiments, and therefore has all the above-mentioned technical effects, which will not be repeated here.

[0158] In another embodiment, this application provides a computer device, which may be a server, and its internal structure diagram may be as follows. Figure 4 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it can implement the methods described in any of the above embodiments.

[0159] In one embodiment, this application also provides a computer device, which can be a client, and its internal structure diagram can be as follows: Figure 5As shown, the computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it can implement the methods described in any of the above embodiments.

[0160] Any of the computer devices described in the embodiments of this application exist in various forms, including but not limited to:

[0161] (1) Mobile communication devices: These devices are characterized by their mobile communication capabilities and primarily aim to provide voice and data communication. These terminals include: smartphones (e.g., iPhones), multimedia phones, feature phones, and low-end phones, etc.

[0162] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, possessing computing and processing capabilities, and generally also have mobile internet access features. These terminals include PDAs, MIDs, and UMPCs, such as the iPad.

[0163] (3) Portable entertainment devices: These devices can display and play multimedia content. This category includes: audio and video players (such as iPods), handheld game consoles, e-books, as well as smart toys, wearable devices, and portable car navigation devices.

[0164] (4) Server: A device that provides computing services. The components of a server include a processor, hard disk, memory, system bus, etc. Servers are similar to general computer architectures, but because they need to provide highly reliable services, they have higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0165] (5) Other electronic devices with data interaction functions.

[0166] Additionally, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which are used to perform the following steps:

[0167] Acquire voice feedback and muscle strength feedback information from bio-electrical stimulation operations;

[0168] Based on the voice feedback information and the muscle strength status feedback information, the actual subjective and objective intensity values ​​corresponding to the bio-electric stimulation operation are determined.

[0169] Based on the actual subjective and objective intensity values ​​and the expected subjective and objective intensity values ​​corresponding to the biological electrical stimulation operation, the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation is determined.

[0170] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0171] The technical solution of this application has been described in detail above with reference to the accompanying drawings. This technical solution allows for the determination of the adjustment value of the electrical stimulation intensity for bio-stimulation based on the subjective and objective intensity reflected by the real-time feedback of the trainee's voice and the trainee's actual muscle strength state. In other words, the electrical stimulation intensity is adjusted according to the actual value of the subjective and objective intensity corresponding to the trainee's real-time perception and actual muscle strength state, ensuring that the adjusted electrical stimulation intensity brings the desired subjective and objective intensity. This replaces the uncertainty of manual adjustment of electrical stimulation intensity and comprehensively considers the trainee's real-time perception and actual muscle strength state, avoiding the problem of inaccurate electrical stimulation intensity adjustment due to considering only a single condition, thus improving the intelligence and accuracy of electrical stimulation intensity adjustment.

[0172] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0173] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0174] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0175] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in a combination of hardware and software functional units.

[0176] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0177] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A feedback-based efficacy-enhancing electrical stimulation method, characterized in that, include: Acquire voice feedback and muscle strength feedback information from bio-electrical stimulation operations; Based on the voice feedback information and the muscle strength status feedback information, the actual subjective and objective intensity values ​​corresponding to the bio-electric stimulation operation are determined. Based on the actual subjective and objective intensity values ​​and the expected subjective and objective intensity values ​​corresponding to the biological electrical stimulation operation, the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation is determined.

2. The feedback-based efficacy-enhancing electrical stimulation method according to claim 1, characterized in that, The acquisition of voice feedback information and muscle strength status feedback information of bio-electrical stimulation operation includes: Real-time voice information is periodically collected after the start of the bio-electrostimulation operation. Detect whether the real-time voice information contains a target keyword that matches a preset electrical stimulation intensity feedback keyword; If the real-time voice information contains the target keyword, the voice evaluation value corresponding to the target keyword is determined as the voice feedback information of the bio-electrostimulation operation.

3. The feedback-based efficacy-enhancing electrical stimulation method according to claim 2, characterized in that, The acquisition of voice feedback information and muscle strength status feedback information from bio-electrical stimulation operations also includes: Extract the response features of the electrical stimulation object of the biological electrical stimulation operation, wherein the response features include integrated electromyography value, root mean square value, waveform length, information entropy, median frequency and average power frequency; Based on the response characteristics and a preset support vector machine regression algorithm, the muscle strength state value of the electrically stimulated object is determined as feedback information on the muscle strength state of the biological body during electrical stimulation.

4. The feedback-based efficacy-enhancing electrical stimulation method according to claim 3, characterized in that, The step of determining the actual subjective and objective intensity values ​​corresponding to the bio-electrical stimulation operation based on the voice feedback information and the muscle strength status feedback information includes: The ratio of the voice evaluation value to a preset evaluation expectation value is obtained as a subjective feature; and The ratio of the muscle strength state value to the preset expected muscle strength state value is obtained as an objective feature; Based on the current weights of the subjective and objective features, a weighted summation is performed on the subjective and objective features to obtain the actual subjective and objective intensity values ​​corresponding to the bio-electrostimulation operation.

5. The feedback-based efficacy-enhancing electrical stimulation method according to claim 4, characterized in that, Before performing a weighted summation on the subjective features and the objective features, the process also includes: For multiple historical electrical stimulation operations The first proportion of historical electrical stimulation operations that match the voice evaluation value with the preset evaluation expectation value is determined; The current weight of the subjective feature is set by the preset weight of the subjective feature and the average of the first proportion; and The second proportion of historical electrical stimulation operations that match the muscle strength state value with the preset muscle strength state expectation value is determined; The average of the preset weight of the objective feature and the second proportion is set as the current weight of the objective feature.

6. The feedback-based efficacy-enhancing electrical stimulation method according to any one of claims 1 to 5, characterized in that, The process of determining the target adjustment value of the electrical stimulation intensity of the bio-organic electrical stimulation operation based on the actual subjective and objective intensity values ​​and the expected subjective and objective intensity values ​​corresponding to the bio-organic electrical stimulation operation includes: Based on the actual values ​​of subjective and objective intensity and the expected values ​​of subjective and objective intensity corresponding to the bio-electro-stimulation operation, the subjective and objective intensity error and the rate of change of subjective and objective intensity error corresponding to the bio-electro-stimulation operation are determined. Based on the subjective and objective intensity error and the rate of change of the subjective and objective intensity error, the incremental stimulation amplitude of the biological electrical stimulation operation is retrieved from the preset fuzzy control lookup table. Based on the stimulus amplitude increment, a target adjustment value for the electrical stimulation intensity of the biological electrical stimulation operation is determined.

7. The feedback-based efficacy-enhancing electrical stimulation method according to claim 6, characterized in that, The step of determining the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation based on the stimulation amplitude increment includes: Based on the stimulation amplitude increment hit by the bio-electro-stimulation operation and the membership degree of the fuzzy control rule corresponding to the stimulation amplitude increment, the target adjustment value of the electro-stimulation intensity of the bio-electro-stimulation operation is determined, wherein... u represents the target adjustment value of the electrical stimulation intensity of the bio-electro-stimulation operation, n is the number of stimulation amplitude increments hit by the bio-electro-stimulation operation, and y i v is the amplitude increment of the i-th stimulus. i Let be the membership degree of the fuzzy control rule corresponding to the amplitude increment of the i-th stimulus.

8. The feedback-based efficacy-enhancing electrical stimulation method according to claim 4, characterized in that, The process of determining the target adjustment value of the electrical stimulation intensity of the bio-organic electrical stimulation operation based on the actual subjective and objective intensity values ​​and the expected subjective and objective intensity values ​​corresponding to the bio-organic electrical stimulation operation includes: Determine the difference between the actual value of the subjective and objective intensity and the expected value of the subjective and objective intensity corresponding to the bio-electrostimulation operation; Obtain a first mapping value of the difference in the voice feedback dimension and a second mapping value in the muscle strength state feedback dimension, wherein the first mapping value is the product of the subjective feature and the difference, and the second mapping value is the product of the objective feature and the difference; Based on the first mapping value and the second mapping value, the degree of difference between the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the bio-electrostimulation operation is determined; Determine the preset range of differences to which the difference belongs; The preset adjustment value corresponding to the preset difference range is set as the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation.

9. A feedback-type efficacy-enhancing electrical stimulation device, characterized in that, include: The initial information acquisition unit is used to acquire voice feedback information and muscle strength status feedback information of the bio-body electrical stimulation operation; The subjective and objective intensity determination unit is used to determine the actual value of the subjective and objective intensity corresponding to the bio-electrical stimulation operation based on the voice feedback information and the muscle strength state feedback information. The adjustment value determination unit is used to determine the target adjustment value of the electrical stimulation intensity of the biological electrical stimulation operation based on the actual subjective and objective intensity value and the expected subjective and objective intensity value corresponding to the biological electrical stimulation operation.

10. A computer device, characterized in that, include: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, the instructions being configured to cause the processor to perform the method according to any one of claims 1 to 8.

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