Nerve regulation and control method based on chronic tinnitus sound stimulation and related equipment

Abstract

The invention discloses a nerve regulation and control method based on chronic tinnitus sound stimulation and related equipment, and the method comprises the steps: carrying out tinnitus sound threshold detection, and generating a comfortable tinnitus sound template; the tinnitus state of the patient is tested based on the comfortable tinnitus sound template, and neural state feedback parameters are obtained; performing chronic stimulation pretreatment on the neural state feedback parameters; a chronic tinnitus sound neural network is constructed, the chronic tinnitus sound stimulation process of the patient is simulated in combination with the neural state feedback parameters after chronic stimulation preprocessing, and the optimal stimulation statistics and correction parameters are obtained; correcting and debugging the comfortable tinnitus sound template to obtain a chronic tinnitus sound treatment template; the chronic tinnitus sound treatment template is adopted to carry out chronic tinnitus sound stimulation treatment on a patient, and the treatment effect is verified. According to the invention, tinnitus treatment is carried out on patients by adopting chronic tinnitus sound stimulation, actual nerve states of different patients are effectively matched, the treatment effect is better, the treatment experience is better, and the method has a wider medical prospect.

Description

Technical Field

[0001] The present invention relates to the field of neural regulation technology, and in particular to a neural regulation method based on chronic tinnitus sound stimulation and related equipment. Background Art

[0002] With the development of social economy, the aging problem in my country is becoming more and more serious, the competition in all walks of life is intensifying, and the pressure of social life is increasing dramatically. People are under too much psychological pressure, which causes mental anxiety, depression, irritability and other related negative emotions, which in turn lead to physical health problems such as insomnia, illness, tinnitus, etc., which not only cause great harm to the body and mind, but also seriously affect the quality of life. Such health problems have gradually become one of the issues of concern to all sectors of society.

[0003] In order to deal with such health problems, when traditional medical treatments are ineffective, more and more people are beginning to seek non-traditional medical methods, such as long-term tinnitus treatment, which has a certain therapeutic effect. However, current tinnitus treatments usually generate universal biological natural sound noises, and each patient's nervous system perceives tinnitus differently. In the case of illness, certain areas of the brain have abnormal activities in tinnitus perception and emotion. The emotional disorders caused by their activation will lead to poor therapeutic effects of universal tinnitus treatments, and the actual treatment experience of patients during treatment is also unsatisfactory. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides a neural regulation method and related equipment based on chronic tinnitus sound stimulation, which uses chronic tinnitus sound stimulation to treat tinnitus in patients, effectively matching the actual neural states of different patients, achieving better treatment effects and better treatment experience, and having broader medical prospects.

[0005] The present invention provides a neural regulation method based on chronic tinnitus sound stimulation, the method comprising:

[0006] Conduct tinnitus sound threshold test on the patient and generate a comfortable tinnitus sound template for the patient;

[0007] Testing the patient's tinnitus state based on the comfortable tinnitus sound template to obtain the patient's neural state feedback parameters in the tinnitus state;

[0008] Performing chronic stimulation preprocessing on the neural state feedback parameters to obtain the neural state feedback parameters after chronic stimulation preprocessing;

[0009] Constructing a chronic tinnitus sound neural network, simulating the patient's chronic tinnitus sound stimulation process based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after the chronic stimulation preprocessing, and obtaining the optimal stimulation statistics and correction parameters;

[0010] Modify and debug the comfortable tinnitus sound template based on the correction parameters to obtain a chronic tinnitus sound treatment template;

[0011] The chronic tinnitus sound treatment template is used to perform chronic tinnitus sound stimulation treatment on the patient based on the optimal stimulation statistics, and the treatment effect is verified after the treatment is completed.

[0012] Furthermore, the step of detecting the tinnitus sound threshold of the patient and generating a comfortable tinnitus sound template for the patient includes:

[0013] Conduct tinnitus threshold testing on patients to obtain the tinnitus comfort threshold range of patients;

[0014] Randomly generate a number of tinnitus sound templates within the tinnitus sound comfort threshold range, provide the tinnitus sound templates to the patient for experience, and obtain the patient's comfort feedback;

[0015] The tinnitus sound template with the highest patient comfort level is selected as the comfortable tinnitus sound template.

[0016] Further, the patient's tinnitus state is tested based on the comfortable tinnitus sound template, and the neural state feedback parameters of the patient in the tinnitus state are obtained, including:

[0017] The comfortable tinnitus sound template is played based on an audio playback device, and cyclic periodic stimulation is performed in combination with a tinnitus stimulation electrode device to collect the patient's neural power spectrum coefficients;

[0018] Performing Gaussian fitting processing on the neural power spectrum coefficient to generate a Gaussian fitting vector value of the neural power spectrum coefficient;

[0019] A neural power spectrum curve graph is depicted based on the Gaussian fitting vector value of the neural power spectrum coefficient, and a neural state feedback parameter of the patient is obtained according to the neural power spectrum curve graph.

[0020] Furthermore, the tinnitus stimulation electrode device is provided with more than 64 electrodes.

[0021] Furthermore, performing chronic stimulation preprocessing on the neural state feedback parameters to obtain the neural state feedback parameters after chronic stimulation preprocessing includes:

[0022] Proportionally stretching the neural state feedback parameter and periodically inserting an interval amount to generate a first preprocessed neural state feedback parameter;

[0023] Referring to the electrode setting orientation of the tinnitus stimulation electrode device, performing a standardized zero reference process on the first preprocessed neural state feedback parameter to obtain a second preprocessed neural state feedback parameter;

[0024] Extracting a portion of the second preprocessed neural state feedback parameter based on a preset optimal coverage principle to generate a third preprocessed neural state feedback parameter;

[0025] Perform periodic component extraction on the neural state feedback parameters after the third preprocessing to obtain the neural state feedback parameters after chronic stimulation preprocessing.

[0026] Further, referring to the electrode setting position of the tinnitus stimulation electrode device, performing standardization and zeroing reference processing on the first preprocessed neural state feedback parameter to obtain the second preprocessed neural state feedback parameter includes:

[0027] Acquire the setting positions of all electrodes of the tinnitus stimulation electrode device, and specify the relative positions of the reference electrode and other electrodes except the reference electrode relative to the reference electrode;

[0028] Setting the electrode setting amount of the reference electrode as the electrode stimulation reference amount, and correspondingly generating electrode stimulation relative amounts of other electrodes relative to the electrode stimulation reference amount;

[0029] The electrode stimulation reference amount and the electrode stimulation relative amount are filtered to generate a second preprocessed neural state feedback parameter.

[0030] Furthermore, the chronic tinnitus sound neural network is constructed, and based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after the chronic stimulation preprocessing, the chronic tinnitus sound stimulation process of the patient is simulated to obtain the optimal stimulation statistics and correction parameters, including:

[0031] Constructing a blank tinnitus sound neural network based on the standard coherence principle, and presetting a chronic rate index for the blank tinnitus sound neural network to generate a chronic tinnitus sound neural network;

[0032] Inputting the neural state feedback parameters after the chronic stimulation preprocessing into the chronic tinnitus sound neural network, and calculating the autospectral density of each parameter and the cross-spectral density between each other;

[0033] Analyze the autospectral density and the cross-spectral density based on the clustering method to calculate the optimal stimulation statistics of the patient's chronic tinnitus sound stimulation process;

[0034] The correlation rank value of the optimal stimulation statistic is calculated, and the correlation rank value is compared with the standardized rank value to obtain a correction parameter.

[0035] The present invention also provides a neural regulation system based on chronic tinnitus sound stimulation, the neural regulation system based on chronic tinnitus sound stimulation is used to implement the above-mentioned neural regulation method based on chronic tinnitus sound stimulation, the system comprises:

[0036] A tinnitus sound threshold detection module, which is used to detect the tinnitus sound threshold of the patient and generate a comfortable tinnitus sound template for the patient;

[0037] A neural state testing module, the neural state testing module is used to test the patient's tinnitus state based on the comfortable tinnitus sound template, and obtain the patient's neural state feedback parameters in the tinnitus state;

[0038] A chronic stimulation preprocessing module, the chronic stimulation preprocessing module is used to perform chronic stimulation preprocessing on the neural state feedback parameters to obtain the neural state feedback parameters after chronic stimulation preprocessing;

[0039] A chronic tinnitus sound stimulation simulation module, which is used to construct a chronic tinnitus sound neural network, simulate the patient's chronic tinnitus sound stimulation process based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after the chronic stimulation preprocessing, and obtain the optimal stimulation statistics and correction parameters;

[0040] A correction and debugging module, wherein the correction and debugging module is used to correct and debug the comfortable tinnitus sound template based on the correction parameters to obtain a chronic tinnitus sound treatment template;

[0041] A treatment verification module is used to use the chronic tinnitus sound treatment template to perform chronic tinnitus sound stimulation treatment on the patient based on the optimal stimulation statistics, and to verify the treatment effect after the treatment is completed.

[0042] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned neural regulation method based on chronic tinnitus sound stimulation.

[0043] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned neural regulation method based on chronic tinnitus sound stimulation is implemented.

[0044] The present invention provides a neural regulation method and related equipment based on chronic tinnitus sound stimulation, which uses chronic tinnitus sound stimulation to treat tinnitus in patients. First, the tinnitus sound threshold of the patient is detected, and the comfortable tinnitus sound template that is most suitable for the patient is selected with full consideration of the patient's treatment experience; the neural power spectrum coefficient is processed by Gaussian fitting to obtain the neural state feedback parameter, and the stimulation sensitive point information represented by the peak of the neural power spectrum is further obtained to obtain the neural state feedback parameter, which can fully reflect the state of the patient in the tinnitus state and provide a basis for the subsequent corresponding matching of the best stimulation statistics and correction parameters; the reference potential is processed by standardized zero reference processing, and the chronic tinnitus sound neural network is constructed to obtain the best stimulation statistics and correction parameters, which effectively improves the accuracy of electroencephalogram signal processing, effectively simulates the change process of the electroencephalogram signal of the patient during stimulation treatment, thereby generating the best stimulation statistics and correction parameters, and optimizing the actual stimulation treatment effect. The present invention effectively matches the actual neural state of different patients, has better treatment effect, better treatment experience, and has a broader medical prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 is a flow chart of the neural regulation method based on chronic tinnitus sound stimulation in Embodiment 1 of the present invention;

[0047] Figure 2 is a flow chart of tinnitus threshold detection in Embodiment 1 of the present invention;

[0048] Figure 3 is a flow chart of obtaining neural state feedback parameters in Embodiment 1 of the present invention;

[0049] Figure 4 is a flow chart of chronic stimulation pretreatment in Example 1 of the present invention;

[0050] Figure 5 is a flow chart of obtaining the neural state feedback parameter after the second preprocessing in the first embodiment of the present invention;

[0051] Figure 6 is a flow chart of obtaining the best stimulation statistics and correction parameters in the first embodiment of the present invention;

[0052] Figure 7 This is a diagram of the architecture of a neural regulation system based on chronic tinnitus sound stimulation in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In the present invention, it should be understood that terms such as "include" or "have" are intended to indicate the existence of features, numbers, steps, behaviors, components, parts or a combination thereof disclosed in the specification, and are not intended to exclude the possibility that one or more other features, numbers, steps, behaviors, components, parts or a combination thereof exist or are added.

[0055] It should also be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0056] Embodiment 1

[0057] Embodiment 1 of the present invention provides a neural regulation method based on chronic tinnitus sound stimulation, the method comprising: performing tinnitus sound threshold detection on a patient and generating a comfortable tinnitus sound template for the patient; testing the tinnitus state of the patient based on the comfortable tinnitus sound template to obtain neural state feedback parameters of the patient in the tinnitus state; performing chronic stimulation preprocessing on the neural state feedback parameters to obtain neural state feedback parameters after chronic stimulation preprocessing; constructing a chronic tinnitus sound neural network, simulating the chronic tinnitus sound stimulation process of the patient based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after chronic stimulation preprocessing to obtain optimal stimulation statistics and correction parameters; correcting and debugging the comfortable tinnitus sound template based on the correction parameters to obtain a chronic tinnitus sound treatment template; performing chronic tinnitus sound stimulation treatment on the patient based on the optimal stimulation statistics using the chronic tinnitus sound treatment template, and verifying the treatment effect after the treatment is completed.

[0058] In an optional implementation of this embodiment, Figure 1 As shown, Figure 1 The flowchart of the neural regulation method based on chronic tinnitus sound stimulation in the first embodiment of the present invention is shown, which includes the following steps:

[0059] S101, performing tinnitus sound threshold detection on the patient, and generating a comfortable tinnitus sound template for the patient;

[0060] In an optional implementation of this embodiment, Figure 2 As shown, Figure 2The flowchart of tinnitus threshold detection in the first embodiment of the present invention is shown, including the following steps:

[0061] S201, performing tinnitus threshold detection on the patient to obtain the tinnitus comfort threshold range of the patient;

[0062] In an optional implementation of this embodiment, an octave-band tinnitus threshold test is performed on the patient to obtain a comfort threshold curve of the patient in several tinnitus threshold ranges, and the tinnitus comfort threshold range of the patient is extracted through the several comfort threshold curves.

[0063] Specifically, the total range of tinnitus sound thresholds that can be distinguished as tinnitus sound by humans is subdivided into several octave bands. After performing octave band tinnitus sound threshold detection on the patient, the comfort threshold in the tinnitus sound threshold range corresponding to the several octave bands can be obtained, and the comfort threshold is portrayed as a comfort threshold curve. All the portrayed comfort threshold curves are compared to obtain the average change rate value between different comfort thresholds, and the comfort threshold range with a relatively gentle average change rate value is selected as the patient's tinnitus sound comfort threshold range.

[0064] It should be noted that when more octaves are subdivided, the patient's comfort threshold result is more precise, but the detection time is longer, which is not good for the patient's treatment experience. However, if fewer octaves are subdivided, it will lead to poor accuracy and poor treatment effect. Here, it is adjusted according to the actual situation. In this embodiment, the total range of tinnitus threshold that can be distinguished as tinnitus by humans is subdivided into 12 octaves, and each octave is 1 / 12 octave. While taking into account the patient's treatment experience, the accuracy is also high to ensure the subsequent treatment effect.

[0065] S202, randomly generating a number of tinnitus sound templates within the tinnitus sound comfort threshold range, providing the tinnitus sound templates to the patient for experience, and obtaining the patient's comfort feedback;

[0066] In an optional implementation of the present embodiment, a number of tinnitus sound templates within the tinnitus sound comfort threshold range are randomly generated, and the tinnitus templates are evenly distributed within the tinnitus sound comfort threshold range. After the order of the tinnitus sound templates is disrupted, they are provided to patients for experience to obtain comfort feedback from the patients.

[0067] Specifically, the patient's comfort feedback includes the patient's comfort level, preference level, and acceptability level for the tinnitus sound template.

[0068] It should be noted that the frequency and amplitude of the randomly generated tinnitus sound template are the same as the frequency and amplitude of the patient in the tinnitus state.

[0069] S203. Select the tinnitus sound template with the highest patient comfort level as the comfortable tinnitus sound template.

[0070] In an optional implementation of this embodiment, after integrating the comfort feedback of the patient corresponding to each tinnitus template in step S202, a comfort score is set, and the tinnitus sound template with the highest comfort score is selected as the comfortable tinnitus sound template.

[0071] Here, we first test the patient's tinnitus sound threshold, fully consider the patient's treatment experience, and select the most suitable comfortable tinnitus sound template for the patient.

[0072] S102, testing the patient's tinnitus state based on the comfortable tinnitus sound template to obtain the patient's neural state feedback parameters in the tinnitus state;

[0073] In an optional implementation of this embodiment, Figure 3 As shown, Figure 3 The flowchart of obtaining neural state feedback parameters in the first embodiment of the present invention is shown, including the following steps:

[0074] S301, playing the comfortable tinnitus sound template based on an audio playback device, and performing cyclical stimulation in combination with a tinnitus stimulation electrode device to collect the patient's neural power spectrum coefficients;

[0075] In an optional implementation of this embodiment, the comfortable tinnitus sound template is played based on an audio playback device, and a tinnitus stimulation electrode device worn on the patient's head is used for cyclic periodic stimulation, and the patient's neural power spectrum coefficients are collected through the sensor of the tinnitus stimulation electrode device.

[0076] Specifically, sample values ​​of different segments at the frequency of the comfortable tinnitus sound template are collected, and the calculation formula of the neural power spectrum coefficient includes:

[0077]

[0078] Where P(f) is the neural power spectrum coefficient, N is the number of segments, M is the sample value in each segment, m(k) is the sample value at time k, and w(ik) is the lth sample value of the window function in the i-th segment.

[0079] In an optional implementation of this embodiment, the audio playback device may be a power amplifier device, or a left and right dual-channel sound amplification headphone device, or a bone conduction headphone device.

[0080] In an optional implementation of this embodiment, the tinnitus stimulation electrode device is provided with 64 or more electrodes.

[0081] Specifically, the tinnitus stimulation electrode device here can be collected using an ASA-Lab amplifier, including 64 electrodes, and the electrode layout is placed according to the 10 / 20 international electrode placement standard.

[0082] S302, performing Gaussian fitting processing on the neural power spectrum coefficient to generate a Gaussian fitting vector value of the neural power spectrum coefficient;

[0083] In an optional implementation of this embodiment, Gaussian fitting is performed on the neural power spectrum coefficients obtained in step S301 to generate Gaussian fitting vector values ​​of the neural power spectrum coefficients.

[0084] Specifically, the non-periodic component in the neural power spectrum coefficient P(f) is split, each oscillation peak in the non-periodic component is modeled using a Gaussian function and then fitted to generate a Gaussian fitting vector value of the neural power spectrum coefficient. The calculation formula includes:

[0085]

[0086] p n = z - log (q + f χ);

[0087]

[0088] In the formula, is the Gaussian fitting vector value, p n is the non-periodic component, a n is the Gaussian component, z is the band offset, q is the bending function used for the non-periodic component, f is the periodic frequency, χ is the exponent, c is the center frequency, and δ is the Gaussian standard deviation.

[0089] It should be noted that the initial values ​​of the band offset z and the index x can be obtained from the slopes of the center frequency point of the non-periodic component and the left and right endpoints.

[0090] S303, characterizing a neural power spectrum curve graph based on the Gaussian fitting vector value of the neural power spectrum coefficient, and obtaining the patient's neural state feedback parameters according to the neural power spectrum curve graph.

[0091] In an optional implementation of this embodiment, after the Gaussian fitting vector value of the neural power spectrum coefficient in step S302 is depicted as a neural power spectrum curve, each peak in the neural power spectrum curve is found through periodic oscillation, and the frequency point corresponding to the peak is determined. After each frequency point corresponding to a peak is extracted, periodic oscillation is performed again until all the frequency points corresponding to the peaks are extracted. After all the frequency points corresponding to the peaks are extracted, they are centrally fitted around the center frequency c to generate the patient's neural state feedback parameters.

[0092] Here, the neural power spectrum coefficients are processed by Gaussian fitting to obtain the neural state feedback parameters. The stimulation sensitive point information represented by the peak of the neural power spectrum is used to obtain the neural state feedback parameters, which can fully reflect the patient's state under tinnitus and provide a basis for the subsequent corresponding matching of the optimal stimulation statistics and correction parameters.

[0093] S103, performing chronic stimulation preprocessing on the neural state feedback parameters to obtain the neural state feedback parameters after chronic stimulation preprocessing;

[0094] In an optional implementation of this embodiment, Figure 4 As shown, Figure 4 The flowchart of chronic stimulation pretreatment in the first embodiment of the present invention is shown, which includes the following steps:

[0095] S401, proportionally stretching the neural state feedback parameter and periodically inserting an interval to generate a first preprocessed neural state feedback parameter;

[0096] In an optional implementation of the present embodiment, a number of fixed anchor points with the same intervals are set in the neural state feedback parameter, and the fixed anchor points are stretched to both ends by a certain proportion. After the stretching is completed, intervals are inserted at the fixed anchor points, and the length of each interval is the same. After the insertion is completed, the first preprocessed neural state feedback parameter is generated.

[0097] S402, referring to the electrode setting orientation of the tinnitus stimulation electrode device, performing a standardization and zeroing reference process on the first preprocessed neural state feedback parameter to obtain a second preprocessed neural state feedback parameter;

[0098] In an optional implementation of this embodiment, the standardized zero reference processing is a processing method applied to EEG signal processing. Since the essence of EEG signal is the voltage signal collected by the electrodes set on the scalp, and the essence of the voltage signal is the potential difference between different electrodes, it is necessary to set a reference electrode when processing the EEG signal after the collection is completed, and use the potential of the reference electrode as the reference potential. Therefore, the accuracy of the reference potential will directly affect the accuracy of EEG signal processing. The standardized zero reference processing used in this embodiment is a method that uses zero potential as the reference potential. Since it is zero potential, it will not affect the accuracy of EEG signal, and it is the most ideal processing method. However, since there is no absolute zero potential position on the human scalp, the reference potential setting close to zero potential can be achieved by using the reference electrode standardization technology.

[0099] In an optional implementation of this embodiment, Figure 5 As shown, Figure 5The flowchart of obtaining the neural state feedback parameter after the second preprocessing in the first embodiment of the present invention is shown, including the following steps:

[0100] S501, obtaining the setting positions of all electrodes of the tinnitus stimulation electrode device, and specifying the relative positions of a reference electrode and other electrodes except the reference electrode relative to the reference electrode;

[0101] In an optional implementation of this embodiment, all electrode setting positions of the tinnitus stimulation electrode device are obtained. In this embodiment, the setting positions of 64 electrodes are obtained, and a reference electrode standardization algorithm is used to specify the reference electrode, as well as the relative positions of other electrodes except the reference electrode relative to the reference electrode.

[0102] S502, setting the electrode setting amount of the reference electrode as the electrode stimulation reference amount, and correspondingly generating electrode stimulation relative amounts of other electrodes relative to the electrode stimulation reference amount;

[0103] In an optional implementation of this embodiment, the reference electrode is assumed to be the average reference electrode setting amount at a certain moment, that is, the electrode stimulation reference amount is V is the original potential, The average potential of all electrodes;

[0104] Furthermore, the scalp surface potential is represented as a matrix V″=DU, where the matrix V″(h×w) represents the w potential difference signal sampling records of h electrodes, D is the transfer matrix, and the matrix U(l×r) represents the r sampling values ​​of l neural sources;

[0105] Further, the electrode stimulation relative amount V of other electrodes relative to the electrode stimulation reference amount i =V′-tV″, where V i is the relative amount of electrode stimulation for the i-th other electrode.

[0106] Standardized zero reference processing is used here to improve the accuracy of EEG signal processing and effectively reduce the interference caused by the reference potential selection orientation.

[0107] S503: Filter the electrode stimulation reference amount and the electrode stimulation relative amount to generate a second preprocessed neural state feedback parameter.

[0108] In an optional implementation of this embodiment, after the processing of S502, the electrode stimulation reference amount and the electrode stimulation relative amount are filtered to a frequency band below 50 Hz.

[0109] S403, extracting a portion of the second preprocessed neural state feedback parameter based on a preset optimal coverage principle to generate a third preprocessed neural state feedback parameter;

[0110] In an optional implementation of the present embodiment, the most representative 18 electrodes covering the head are selected from the 64 electrodes based on a preset optimal coverage principle, and their corresponding electrode stimulation reference amounts and electrode stimulation relative amounts are extracted to generate a third preprocessed neural state feedback parameter.

[0111] Here, representative electrodes are extracted based on the preset optimal coverage principle, which can effectively reduce the impact of volume conduction between nodes when the tinnitus sound neural network is subsequently calculated.

[0112] S404, extracting periodic components of the neural state feedback parameters after the third preprocessing to obtain neural state feedback parameters after chronic stimulation preprocessing.

[0113] In an optional implementation of this embodiment, the periodic component spectrum in the power spectrum of the neural state feedback parameter after the third preprocessing is extracted, and by comparing the baseline and the correlation, data with the correlation reaching a threshold is obtained as the neural state feedback parameter after chronic stimulation preprocessing.

[0114] S104, constructing a chronic tinnitus sound neural network, simulating the patient's chronic tinnitus sound stimulation process based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after the chronic stimulation preprocessing, and obtaining the optimal stimulation statistics and correction parameters;

[0115] In an optional implementation of this embodiment, Figure 6 As shown, Figure 6 The flowchart of obtaining the optimal stimulation statistics and correction parameters in the first embodiment of the present invention is shown, including the following steps:

[0116] S601, constructing a blank tinnitus sound neural network based on the standard coherence principle, and presetting a chronic rate index for the blank tinnitus sound neural network to generate a chronic tinnitus sound neural network;

[0117] In an optional implementation of this embodiment, a blank tinnitus sound neural network is constructed based on the standard coherence principle. The blank tinnitus sound neural network is a computing network based on an EEG signal network as a basic framework and adapted to the characteristics of tinnitus sound.

[0118] Furthermore, a chronic rate index is preset in the blank tinnitus sound neural network to generate a chronic tinnitus sound neural network, and the expression of the chronic tinnitus sound neural network includes:

[0119]

[0120] In the formula, C xy (f) is the expression of the neural network of chronic tinnitus, specifically the configuration coherence, S xy(f) is the cross spectrum of x and y at frequency f, that is, the cross spectrum, A xx (f) is the autospectrum of x at frequency f, A yy (f) is the autospectrum of y at frequency f.

[0121] S602, inputting the neural state feedback parameters after the chronic stimulation preprocessing into the chronic tinnitus sound neural network, and calculating the autospectral density of each parameter and the cross-spectral density between them respectively;

[0122] In an optional implementation of this embodiment, the autospectral density is calculated by an autocorrelation function, and the expression includes:

[0123]

[0124] In the formula, A xx (f) is the autospectrum of x at frequency f, that is, the autospectral density of x, A yy (f) is the autospectrum of y at frequency f, that is, the autospectral density of y, which represents the power of x and y at frequency f, F xx (τ), F yy (τ) is the autocorrelation function.

[0125] In an optional implementation of this embodiment, the cross-spectral density is calculated by a cross-correlation function, and the expression includes:

[0126]

[0127] In the formula, S xy (f) is the cross-spectrum of x and y at frequency f, that is, the cross-spectral density, which represents the correlation between x and y at frequency f. xy (τ) is the cross-correlation function.

[0128] S603, analyzing the autospectral density and the cross-spectral density based on a clustering method, and calculating the optimal stimulation statistics of the patient's chronic tinnitus sound stimulation process;

[0129] In an optional implementation of this embodiment, the autospectral density and the cross-spectral density are analyzed based on a k-mean clustering algorithm to calculate the optimal stimulation statistics of the patient's chronic tinnitus sound stimulation process.

[0130] S604 , calculating the correlation rank value of the optimal stimulation statistic, comparing the correlation rank value with the standardized rank value, and obtaining a correction parameter.

[0131] In an optional implementation of this embodiment, the correlation rank value of the optimal stimulation statistic is calculated based on the Wilcoxon signed rank algorithm, and compared with the preset standardized rank value to obtain the rank difference value, and generate the corresponding correction parameter.

[0132] Here, by constructing a chronic tinnitus sound neural network to obtain the optimal stimulation statistics and correction parameters, the change process of the patient's EEG signal during stimulation treatment can be effectively simulated, thereby generating the optimal stimulation statistics and correction parameters and optimizing the actual stimulation treatment effect.

[0133] S105, modifying and debugging the comfortable tinnitus sound template based on the modification parameters to obtain a chronic tinnitus sound treatment template;

[0134] In an optional implementation of this embodiment, the comfortable tinnitus sound template is modified and debugged based on the correction function obtained in step S604 to obtain a chronic tinnitus sound treatment template.

[0135] S106: Perform chronic tinnitus sound stimulation treatment on the patient using the chronic tinnitus sound treatment template based on the optimal stimulation statistics, and verify the treatment effect after the treatment is completed.

[0136] In an optional implementation of this embodiment, based on the chronic tinnitus sound treatment template obtained in step S105, the course of chronic tinnitus sound stimulation treatment is determined according to the optimal stimulation statistics, and the chronic tinnitus sound stimulation treatment is performed according to the course.

[0137] In an optional implementation of this embodiment, after the treatment is completed, the treatment effect is verified and the chronic tinnitus sound treatment template with better treatment effect is stored.

[0138] In summary, the first embodiment of the present invention provides a neural regulation method based on chronic tinnitus sound stimulation, which uses chronic tinnitus sound stimulation to treat tinnitus in patients. First, the tinnitus sound threshold of the patient is detected, and the patient's treatment experience is fully considered to select the most suitable comfortable tinnitus sound template for the patient; the neural power spectrum coefficient is processed by Gaussian fitting to obtain the neural state feedback parameter, and the stimulation sensitive point information represented by the peak of the neural power spectrum is further obtained. The neural state feedback parameter can fully reflect the state of the patient in the tinnitus state and provide a basis for the subsequent corresponding matching of the optimal stimulation statistics and correction parameters; the reference potential is processed by standardized zero reference processing, and the chronic tinnitus sound neural network is constructed to obtain the optimal stimulation statistics and correction parameters, which effectively improves the accuracy of EEG signal processing, effectively simulates the change process of the patient's EEG signal during stimulation treatment, thereby generating the optimal stimulation statistics and correction parameters, and optimizing the actual stimulation treatment effect. The present invention effectively matches the actual neural state of different patients, has better treatment effect, better treatment experience, and has a broader medical prospect.

[0139] Embodiment 2

[0140] Embodiment 2 of the present invention provides a neural regulation system based on chronic tinnitus sound stimulation, and the neural regulation system based on chronic tinnitus sound stimulation is used to implement the neural regulation method based on chronic tinnitus sound stimulation described in Embodiment 1. The system includes a tinnitus sound threshold detection module, a neural state test module, a chronic stimulation preprocessing module, a chronic tinnitus sound stimulation simulation module, a correction and debugging module, and a treatment verification module.

[0141] In an optional implementation of this embodiment, as shown in the figure, the neural regulation system architecture based on chronic tinnitus sound stimulation in the second embodiment of the present invention is shown, including the following modules:

[0142] A tinnitus sound threshold detection module 10, wherein the tinnitus sound threshold detection module 10 is used to detect the tinnitus sound threshold of the patient and generate a comfortable tinnitus sound template for the patient;

[0143] A neural state testing module 20, the neural state testing module 20 is used to test the patient's tinnitus state based on the comfortable tinnitus sound template, and obtain the patient's neural state feedback parameters in the tinnitus state;

[0144] A chronic stimulation preprocessing module 30, wherein the chronic stimulation preprocessing module 30 is used to perform chronic stimulation preprocessing on the neural state feedback parameters to obtain the neural state feedback parameters after chronic stimulation preprocessing;

[0145] A chronic tinnitus sound stimulation simulation module 40, which is used to construct a chronic tinnitus sound neural network, simulate the patient's chronic tinnitus sound stimulation process based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after the chronic stimulation preprocessing, and obtain the best stimulation statistics and correction parameters;

[0146] A correction and debugging module 50, wherein the correction and debugging module 50 is used to correct and debug the comfortable tinnitus sound template based on the correction parameters to obtain a chronic tinnitus sound treatment template;

[0147] The treatment verification module 60 is used to use the chronic tinnitus sound treatment template to perform chronic tinnitus sound stimulation treatment on the patient based on the optimal stimulation statistics, and verify the treatment effect after the treatment is completed.

[0148] In summary, the second embodiment of the present invention provides a neural regulation system based on chronic tinnitus sound stimulation, which is used to implement the neural regulation method based on chronic tinnitus sound stimulation in the first embodiment, and the patient is treated for tinnitus by using chronic tinnitus sound stimulation. The patient is first tested for tinnitus sound threshold, and the comfortable tinnitus sound template that best suits the patient is selected taking into full consideration the patient's treatment experience; the neural power spectrum coefficient is processed by Gaussian fitting to obtain the neural state feedback parameter, and the neural state feedback parameter is obtained for the stimulation sensitive point information represented by the peak of the neural power spectrum, which can fully reflect the state of the patient in the tinnitus state and provide a basis for the subsequent corresponding matching of the optimal stimulation statistics and correction parameters; the reference potential is processed by standardized zero reference processing, and the chronic tinnitus sound neural network is constructed to obtain the optimal stimulation statistics and correction parameters, which effectively improves the accuracy of EEG signal processing, effectively simulates the change process of the patient's EEG signal during stimulation treatment, thereby generating the optimal stimulation statistics and correction parameters, and optimizing the actual stimulation treatment effect. The present invention effectively matches the actual neural state of different patients, has better treatment effect, better treatment experience, and has a broader medical prospect.

[0149] Embodiment 3

[0150] Embodiment 3 of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the neural regulation method based on chronic tinnitus sound stimulation described in Embodiment 1.

[0151] In summary, the third embodiment of the present invention provides an electronic device for executing the neural regulation method based on chronic tinnitus sound stimulation described in the first embodiment, using chronic tinnitus sound stimulation to treat tinnitus in patients, firstly performing tinnitus sound threshold detection on the patient, taking full account of the patient's treatment experience, and selecting the most suitable comfortable tinnitus sound template for the patient; obtaining neural state feedback parameters by Gaussian fitting processing of neural power spectrum coefficients, and then obtaining neural state feedback parameters for the stimulation sensitive point information represented by the peak of the neural power spectrum, which can fully reflect the state of the patient in the tinnitus state and provide a basis for the subsequent corresponding matching of the best stimulation statistics and correction parameters; using standardized zero reference processing to process the reference potential, and constructing a chronic tinnitus sound neural network to obtain the best stimulation statistics and correction parameters, effectively improving the accuracy of EEG signal processing, effectively simulating the change process of the patient's EEG signal during stimulation treatment, thereby generating the best stimulation statistics and correction parameters, and optimizing the actual stimulation treatment effect. The present invention effectively matches the actual neural state of different patients, has better treatment effect, better treatment experience, and has a broader medical prospect.

[0152] Embodiment 4

[0153] Embodiment 4 of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the neural regulation method based on chronic tinnitus sound stimulation described in Embodiment 1 is implemented.

[0154] In summary, the fourth embodiment of the present invention provides a computer-readable storage medium for executing the neural regulation method based on chronic tinnitus sound stimulation described in the first embodiment, using chronic tinnitus sound stimulation to treat tinnitus in patients, firstly performing tinnitus sound threshold detection on the patient, taking full account of the patient's treatment experience, and selecting the most suitable comfortable tinnitus sound template for the patient; obtaining neural state feedback parameters by Gaussian fitting processing of neural power spectrum coefficients, and obtaining neural state feedback parameters for the stimulation sensitive point information represented by the peak of the neural power spectrum, which can fully reflect the state of the patient in the tinnitus state and provide a basis for the subsequent corresponding matching of the best stimulation statistics and correction parameters; using standardized zero reference processing to process the reference potential, and constructing a chronic tinnitus sound neural network to obtain the best stimulation statistics and correction parameters, effectively improving the accuracy of EEG signal processing, effectively simulating the change process of the patient's EEG signal during stimulation treatment, thereby generating the best stimulation statistics and correction parameters, and optimizing the actual stimulation treatment effect. The present invention effectively matches the actual neural state of different patients, has better treatment effect, better treatment experience, and has a broader medical prospect.

[0155] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0156] In addition, the embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A neural regulation method based on chronic tinnitus sound stimulation, characterized in that: The method comprises: Conduct tinnitus sound threshold test on the patient and generate a comfortable tinnitus sound template for the patient; Testing the patient's tinnitus state based on the comfortable tinnitus sound template to obtain the patient's neural state feedback parameters in the tinnitus state; Performing chronic stimulation preprocessing on the neural state feedback parameters to obtain the neural state feedback parameters after chronic stimulation preprocessing; Constructing a chronic tinnitus sound neural network, simulating the patient's chronic tinnitus sound stimulation process based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after the chronic stimulation preprocessing, and obtaining the optimal stimulation statistics and correction parameters; Modify and debug the comfortable tinnitus sound template based on the correction parameters to obtain a chronic tinnitus sound treatment template; The chronic tinnitus sound treatment template is used to perform chronic tinnitus sound stimulation treatment on the patient based on the optimal stimulation statistics, and the treatment effect is verified after the treatment is completed.

2. The neural regulation method based on chronic tinnitus sound stimulation according to claim 1, characterized in that: The method of detecting the tinnitus sound threshold of the patient and generating a comfortable tinnitus sound template for the patient includes: Conduct tinnitus threshold testing on patients to obtain the tinnitus comfort threshold range of patients; Randomly generate a number of tinnitus sound templates within the tinnitus sound comfort threshold range, provide the tinnitus sound templates to the patient for experience, and obtain the patient's comfort feedback; The tinnitus sound template with the highest patient comfort level is selected as the comfortable tinnitus sound template.

3. The neural regulation method based on chronic tinnitus sound stimulation according to claim 1, characterized in that: Testing the patient's tinnitus state based on the comfortable tinnitus sound template and obtaining the patient's neural state feedback parameters in the tinnitus state includes: The comfortable tinnitus sound template is played based on an audio playback device, and cyclic periodic stimulation is performed in combination with a tinnitus stimulation electrode device to collect the patient's neural power spectrum coefficients; Performing Gaussian fitting processing on the neural power spectrum coefficient to generate a Gaussian fitting vector value of the neural power spectrum coefficient; A neural power spectrum curve graph is depicted based on the Gaussian fitting vector value of the neural power spectrum coefficient, and a neural state feedback parameter of the patient is obtained according to the neural power spectrum curve graph.

4. The neural regulation method based on chronic tinnitus sound stimulation according to claim 3, characterized in that: The number of electrodes provided in the tinnitus stimulation electrode device is more than 64.

5. The neural regulation method based on chronic tinnitus sound stimulation according to claim 3, characterized in that: The performing chronic stimulation preprocessing on the neural state feedback parameters to obtain the neural state feedback parameters after chronic stimulation preprocessing comprises: Proportionally stretching the neural state feedback parameter and periodically inserting an interval amount to generate a first preprocessed neural state feedback parameter; Referring to the electrode setting orientation of the tinnitus stimulation electrode device, performing a standardized zero reference process on the first preprocessed neural state feedback parameter to obtain a second preprocessed neural state feedback parameter; Extracting a portion of the second preprocessed neural state feedback parameter based on a preset optimal coverage principle to generate a third preprocessed neural state feedback parameter; Perform periodic component extraction on the neural state feedback parameters after the third preprocessing to obtain the neural state feedback parameters after chronic stimulation preprocessing.

6. The method for neural regulation based on chronic tinnitus sound stimulation according to claim 5, characterized in that: The step of referring to the electrode setting position of the tinnitus stimulation electrode device, performing standardization and zeroing reference processing on the first preprocessed neural state feedback parameter, and obtaining the second preprocessed neural state feedback parameter comprises: Acquire the setting positions of all electrodes of the tinnitus stimulation electrode device, and specify the relative positions of the reference electrode and other electrodes except the reference electrode relative to the reference electrode; Setting the electrode setting amount of the reference electrode as the electrode stimulation reference amount, and correspondingly generating the electrode stimulation relative amounts of other electrodes relative to the electrode stimulation reference amount; The electrode stimulation reference amount and the electrode stimulation relative amount are filtered to generate a second preprocessed neural state feedback parameter.

7. The method for neural regulation based on chronic tinnitus sound stimulation according to claim 1, characterized in that: The method of constructing a chronic tinnitus sound neural network, simulating the patient's chronic tinnitus sound stimulation process based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after the chronic stimulation preprocessing, and obtaining the optimal stimulation statistics and correction parameters includes: Constructing a blank tinnitus sound neural network based on the standard coherence principle, and presetting a chronic rate index for the blank tinnitus sound neural network to generate a chronic tinnitus sound neural network; Inputting the neural state feedback parameters after the chronic stimulation preprocessing into the chronic tinnitus sound neural network, and calculating the autospectral density of each parameter and the cross-spectral density between each other; Analyze the autospectral density and the cross-spectral density based on the clustering method to calculate the optimal stimulation statistics of the patient's chronic tinnitus sound stimulation process; The correlation rank value of the optimal stimulation statistic is calculated, and the correlation rank value is compared with the standardized rank value to obtain a correction parameter.

8. A neural regulation system based on chronic tinnitus sound stimulation, characterized in that: The neural regulation system based on chronic tinnitus sound stimulation is used to implement the neural regulation method based on chronic tinnitus sound stimulation according to any one of claims 1 to 7, and the system comprises: A tinnitus sound threshold detection module, which is used to detect the tinnitus sound threshold of the patient and generate a comfortable tinnitus sound template for the patient; A neural state testing module, the neural state testing module is used to test the patient's tinnitus state based on the comfortable tinnitus sound template, and obtain the patient's neural state feedback parameters in the tinnitus state; A chronic stimulation preprocessing module, the chronic stimulation preprocessing module is used to perform chronic stimulation preprocessing on the neural state feedback parameters to obtain the neural state feedback parameters after chronic stimulation preprocessing; A chronic tinnitus sound stimulation simulation module, which is used to construct a chronic tinnitus sound neural network, simulate the patient's chronic tinnitus sound stimulation process based on the chronic tinnitus sound neural network combined with the neural state feedback parameters after the chronic stimulation preprocessing, and obtain the optimal stimulation statistics and correction parameters; A correction and debugging module, wherein the correction and debugging module is used to correct and debug the comfortable tinnitus sound template based on the correction parameters to obtain a chronic tinnitus sound treatment template; A treatment verification module is used to use the chronic tinnitus sound treatment template to perform chronic tinnitus sound stimulation treatment on the patient based on the optimal stimulation statistics, and to verify the treatment effect after the treatment is completed.

9. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the neural regulation method based on chronic tinnitus sound stimulation according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the neural regulation method based on chronic tinnitus sound stimulation according to any one of claims 1 to 7 is implemented.

Images