An audio production method and terminal based on EEG nonlinear dynamics analysis

Abstract

The present invention discloses an audio production method and terminal based on electroencephalogram (EEG) nonlinear dynamics analysis, which obtain a EEG signal set; calculate multiple phase synchronization intensities corresponding to the EEG signal set, and calculate the main frequency of the EEG signal based on the multiple phase synchronization intensities; obtain a changed EEG signal set according to the main frequency of the EEG signal, and screen a target main frequency from the main frequencies of the EEG signal according to the changed EEG signal set; perform EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio. Since the target main frequency is the main frequency that can induce EEG changes, the basic audio is obtained based on the target main frequency. The basic audio can be used to induce specific EEG frequencies, which can stimulate brain neurons in a direction, thereby improving the emotional soothing and regulating effects of the audio.

Description

Technical Field

[0001] The present invention relates to the technical field of audio production, and in particular to an audio production method and terminal based on electroencephalogram (EEG) nonlinear dynamics analysis. Background Art

[0002] Current audio production often uses a mixture of natural music and relaxing music. The music produced in this way is not very effective in soothing and regulating emotions. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide an audio production method and terminal based on EEG nonlinear dynamics analysis, which can improve the emotion soothing and regulating effects of audio.

[0004] In order to solve the above technical problems, a technical solution adopted by the present invention is:

[0005] An audio production method based on EEG nonlinear dynamics analysis, comprising the steps of:

[0006] Obtaining a brainwave signal set;

[0007] Calculating a plurality of phase synchronization strengths corresponding to the brain wave signal set, and calculating a main frequency of the brain wave signal based on the plurality of phase synchronization strengths;

[0008] Acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set;

[0009] Based on the target main frequency, an electroencephalogram nonlinear dynamics analysis is performed to obtain a basic audio frequency.

[0010] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0011] An audio production terminal based on electroencephalogram (EEG) nonlinear dynamics analysis includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0012] Obtaining a brainwave signal set;

[0013] Calculating a plurality of phase synchronization strengths corresponding to the brain wave signal set, and calculating a main frequency of the brain wave signal based on the plurality of phase synchronization strengths;

[0014] Acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set;

[0015] Based on the target main frequency, an electroencephalogram nonlinear dynamics analysis is performed to obtain a basic audio frequency.

[0016] The beneficial effects of the present invention are: calculating multiple phase synchronization intensities corresponding to the acquired brainwave signal set, and calculating the main frequency of the brainwave signal based on the multiple phase synchronization intensities, obtaining the changed brainwave signal set according to the main frequency of the brainwave signal, and screening the target main frequency from the changed brainwave signal set, performing brainwave nonlinear dynamic analysis based on the target main frequency, and obtaining basic audio. Since the target main frequency is the main frequency that can induce brainwave changes, the basic audio is obtained based on the target main frequency. The basic audio can be used to induce specific brainwave frequencies, which can stimulate brain neurons in a direction, thereby improving the emotional soothing and regulation effects of the audio. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flowchart of the steps of an audio production method based on EEG nonlinear dynamics analysis according to an embodiment of the present invention;

[0018] Figure 2 This is a structural diagram of an audio production terminal based on EEG nonlinear dynamics analysis according to an embodiment of the present invention;

[0019] Figure 3 This is a composition ratio table of nonlinear dynamic audio in the audio production method based on EEG nonlinear dynamic analysis according to an embodiment of the present invention;

[0020] Figure 4 Schematic diagram of brain wave signals in an audio production method based on nonlinear dynamic analysis of brain waves according to an embodiment of the present invention;

[0021] Figure 5 This is a graph showing the synchronization index of brain wave signals in an audio production method based on nonlinear dynamic analysis of brain wave signals according to an embodiment of the present invention;

[0022] Figure 6 This is an energy spectrum of brain wave analysis in the audio production method based on nonlinear dynamic analysis of brain waves in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0024] Please refer to Figure 1 The embodiment of the present invention provides an audio production method based on EEG nonlinear dynamics analysis, comprising the steps of:

[0025] Obtaining a brainwave signal set;

[0026] Calculating a plurality of phase synchronization strengths corresponding to the brain wave signal set, and calculating a main frequency of the brain wave signal based on the plurality of phase synchronization strengths;

[0027] Acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set;

[0028] Based on the target main frequency, an electroencephalogram nonlinear dynamics analysis is performed to obtain a basic audio frequency.

[0029] From the above description, it can be seen that the beneficial effects of the present invention are: calculating multiple phase synchronization intensities corresponding to the acquired brainwave signal set, and calculating the main frequency of the brainwave signal based on the multiple phase synchronization intensities, obtaining the changed brainwave signal set according to the main frequency of the brainwave signal, and screening the target main frequency from the changed brainwave signal set based on the target main frequency, performing EEG nonlinear dynamics analysis based on the target main frequency, and obtaining basic audio. Since the target main frequency is the main frequency that can induce brainwave changes, the basic audio is obtained based on the target main frequency. The basic audio can induce specific brainwave frequencies, which can stimulate brain neurons in a direction, thereby improving the emotional soothing and regulation effects of the audio.

[0030] Furthermore, the brainwave signal set includes multi-channel brainwave signals;

[0031] The step of calculating a plurality of phase synchronization strengths corresponding to the brainwave signal set and calculating the main frequency of the brainwave signal based on the plurality of phase synchronization strengths includes:

[0032] performing a Hilbert transform on the multi-channel brain wave signal to obtain a transformed brain wave signal;

[0033] Calculating the phase synchronization strength corresponding to every two adjacent transformed brain wave signals to obtain a plurality of phase synchronization strengths;

[0034] determining a highest phase synchronization strength from among the plurality of phase synchronization strengths;

[0035] The main frequency of the brain wave signal is calculated according to the brain wave signal corresponding to the highest phase synchronization intensity.

[0036] From the above description, it can be seen that the multi-channel brainwave signal is Hilbert transformed to obtain the transformed brainwave signal, and the phase synchronization strength corresponding to every two adjacent transformed brainwave signals is calculated. The highest phase synchronization strength is determined from multiple phase synchronization strengths, and the main frequency of the brainwave signal is calculated based on the brainwave signal corresponding to the highest phase synchronization strength. The highest phase synchronization strength indicates that the corresponding brainwave signal has a high correlation. Taking the brainwave signal with a high correlation to calculate the main frequency can ensure the accuracy of subsequent audio production, thereby improving the emotional soothing and regulation effect of the audio.

[0037] Furthermore, the transformed brain wave signal for:

[0038]

[0039] H[x(t)]=a(t)e iФ(t) ;

[0040] Where H[] represents Hilbert transform, x(t) represents the multi-channel EEG signal, a(t) represents the instantaneous amplitude, e iФ(t) Represents the complex phase.

[0041] As can be seen from the above description, using Hilbert transform to describe the envelope, instantaneous frequency and instantaneous phase of amplitude modulation or phase modulation can make subsequent analysis of phase synchronization strength easier.

[0042] Furthermore, acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set includes:

[0043] Determining a frequency multiplication corresponding to a main frequency of the brain wave signal;

[0044] Mixing the frequency multiplication with a first preset noise to obtain a mixed frequency multiplication;

[0045] Acquire a changed brainwave signal set according to the mixed frequency multiplication, and select a target main frequency from the main frequencies of the brainwave signals according to the changed brainwave signal set;

[0046] The performing of EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio includes:

[0047] Obtaining a brainwave analysis energy spectrum according to the changed brainwave signal set;

[0048] The duration and magnitude of the target main frequency are adjusted according to the brain wave analysis energy spectrum to obtain basic audio.

[0049] From the above description, it can be seen that the determined frequency multiplication corresponding to the main frequency of the brainwave signal is mixed with the first preset noise, and the changed brainwave signal set is obtained according to the mixed frequency multiplication, and the target main frequency is screened out according to the changed brainwave signal set, and the brainwave analysis energy spectrum is obtained according to the changed brainwave signal set, and the duration and size of the target main frequency are adjusted according to it to obtain the basic audio. By applying the nonlinear dynamic sub-harmonic frequency theory, the basic audio is produced based on the inducible target main frequency. The basic audio serves as the basis for the subsequent generation of nonlinear dynamic audio, so that the nonlinear dynamic audio can stimulate brainwave energy, reduce brainwave energy, and make brain neurons directional, so as to achieve the purpose of emotional relief and regulation.

[0050] Furthermore, performing EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio includes:

[0051] Brownian noise or pink noise is added to the basic audio to perform chaotic encryption to obtain nonlinear dynamic audio.

[0052] From the above description, we can see that the initial audio is added with Brownian noise or pink noise for chaotic encryption to produce nonlinear dynamic audio. Brownian noise has more low-frequency components and sounds deeper, similar to the sound of the seaside. Pink noise can better simulate the influence of environmental noise, similar to the sound of rain. Brownian noise or pink noise further enhances the emotional soothing and adjustment effects of the audio.

[0053] Please refer to Figure 2 , an audio production terminal based on EEG nonlinear dynamics analysis, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0054] Obtaining a brainwave signal set;

[0055] Calculating a plurality of phase synchronization strengths corresponding to the brain wave signal set, and calculating a main frequency of the brain wave signal based on the plurality of phase synchronization strengths;

[0056] Acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set;

[0057] Based on the target main frequency, an electroencephalogram nonlinear dynamics analysis is performed to obtain a basic audio frequency.

[0058] From the above description, it can be seen that the beneficial effects of the present invention are: calculating multiple phase synchronization intensities corresponding to the acquired brainwave signal set, and calculating the main frequency of the brainwave signal based on the multiple phase synchronization intensities, obtaining the changed brainwave signal set according to the main frequency of the brainwave signal, and screening the target main frequency from the changed brainwave signal set based on the target main frequency, performing EEG nonlinear dynamics analysis based on the target main frequency, and obtaining basic audio. Since the target main frequency is the main frequency that can induce brainwave changes, the basic audio is obtained based on the target main frequency. The basic audio can induce specific brainwave frequencies, which can stimulate brain neurons in a direction, thereby improving the emotional soothing and regulation effects of the audio.

[0059] Furthermore, the brainwave signal set includes multi-channel brainwave signals;

[0060] The step of calculating a plurality of phase synchronization strengths corresponding to the brainwave signal set and calculating the main frequency of the brainwave signal based on the plurality of phase synchronization strengths includes:

[0061] performing a Hilbert transform on the multi-channel brain wave signal to obtain a transformed brain wave signal;

[0062] Calculating the phase synchronization strength corresponding to every two adjacent transformed brain wave signals to obtain a plurality of phase synchronization strengths;

[0063] determining a highest phase synchronization strength from among the plurality of phase synchronization strengths;

[0064] The main frequency of the brain wave signal is calculated according to the brain wave signal corresponding to the highest phase synchronization intensity.

[0065] From the above description, it can be seen that the multi-channel brainwave signal is Hilbert transformed to obtain the transformed brainwave signal, and the phase synchronization strength corresponding to every two adjacent transformed brainwave signals is calculated. The highest phase synchronization strength is determined from multiple phase synchronization strengths, and the main frequency of the brainwave signal is calculated based on the brainwave signal corresponding to the highest phase synchronization strength. The highest phase synchronization strength indicates that the corresponding brainwave signal has a high correlation. Taking the brainwave signal with a high correlation to calculate the main frequency can ensure the accuracy of subsequent audio production, thereby improving the emotional soothing and regulation effect of the audio.

[0066] Furthermore, the transformed brain wave signal for:

[0067]

[0068] H[x(t)]=a(t)e iФ(t) ;

[0069] Where H[] represents Hilbert transform, x(t) represents the multi-channel EEG signal, a(t) represents the instantaneous amplitude, e iΦ(t) Represents the complex phase.

[0070] As can be seen from the above description, using Hilbert transform to describe the envelope, instantaneous frequency and instantaneous phase of amplitude modulation or phase modulation can make subsequent analysis of phase synchronization strength easier.

[0071] Furthermore, acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set includes:

[0072] Determining a frequency multiplication corresponding to a main frequency of the brain wave signal;

[0073] Mixing the frequency multiplication with a first preset noise to obtain a mixed frequency multiplication;

[0074] Acquire a changed brainwave signal set according to the mixed frequency multiplication, and select a target main frequency from the main frequencies of the brainwave signals according to the changed brainwave signal set;

[0075] The performing of EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio includes:

[0076] Obtaining a brainwave analysis energy spectrum according to the changed brainwave signal set;

[0077] The duration and magnitude of the target main frequency are adjusted according to the brain wave analysis energy spectrum to obtain basic audio.

[0078] From the above description, it can be seen that the determined frequency multiplication corresponding to the main frequency of the brainwave signal is mixed with the first preset noise, and the changed brainwave signal set is obtained according to the mixed frequency multiplication, and the target main frequency is screened out according to the changed brainwave signal set, and the brainwave analysis energy spectrum is obtained according to the changed brainwave signal set, and the duration and size of the target main frequency are adjusted according to it to obtain the basic audio. By applying the nonlinear dynamic sub-harmonic frequency theory, the basic audio is produced based on the inducible target main frequency. The basic audio serves as the basis for the subsequent generation of nonlinear dynamic audio, so that the nonlinear dynamic audio can stimulate brainwave energy, reduce brainwave energy, and make brain neurons directional, so as to achieve the purpose of emotional relief and regulation.

[0079] Furthermore, performing EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio includes:

[0080] Brownian noise or pink noise is added to the basic audio to perform chaotic encryption to obtain nonlinear dynamic audio.

[0081] From the above description, we can see that the initial audio is added with Brownian noise or pink noise for chaotic encryption to produce nonlinear dynamic audio. Brownian noise has more low-frequency components and sounds deeper, similar to the sound of the seaside. Pink noise can better simulate the influence of environmental noise, similar to the sound of rain. Brownian noise or pink noise further enhances the emotional soothing and adjustment effects of the audio.

[0082] The above-mentioned audio production method and terminal based on EEG nonlinear dynamics analysis of the present invention can be applied to the production of audio that soothes and regulates emotions. The following is an explanation through specific implementation methods:

[0083] Example 1

[0084] Please refer to Figure 1 、 Figure 3-Figure 6 , an audio production method based on EEG nonlinear dynamics analysis of this embodiment includes the steps of:

[0085] S1. Obtain brain wave signal set;

[0086] Wherein, the brain wave signal set includes multi-channel brain wave signals;

[0087] Specifically, an electroencephalogram (EEG) device was used to obtain 32 channels of EEG signals from the subjects at a sampling rate of 1000 points per second.

[0088] S2. Calculating multiple phase synchronization strengths corresponding to the brainwave signal set, and calculating the main frequency of the brainwave signal based on the multiple phase synchronization strengths, specifically including:

[0089] S21, performing Hilbert transform on the multi-channel brain wave signal to obtain a transformed brain wave signal;

[0090] Among them, the transformed brain wave signal for:

[0091]

[0092] H[x(t)]=a(t)e iΦ(t) ;

[0093] Where H[] represents Hilbert transform, x(t) represents the multi-channel EEG signal, a(t) represents the instantaneous amplitude, e iΦ(t) represents the complex phase;

[0094] S22, calculating the phase synchronization strength corresponding to every two adjacent transformed brain wave signals to obtain a plurality of phase synchronization strengths;

[0095] Specifically, the phase-lock ratio is set to 1:1, in which case the difference between the instantaneous phases is used as the relative phase;

[0096] The relative phase for:

[0097]

[0098] Where, represents the instantaneous phase of the transformed brainwave signal at time a, represents the instantaneous phase of the brain wave signal at time b, represents the transformed brain wave signal at time a, represents the transformed brain wave signal at time b, x b (t) represents the multi-channel brain wave signal at time b, x a (t) represents the multi-channel brain wave signal at time a;

[0099] The phase synchronization strength ρ is:

[0100]

[0101] Where H represents the conversion phase of the brain wave signal after the transformation, H max Indicates the maximum value in the conversion phase;

[0102] The phase synchronization strength is determined by the relative phase The converted H is further calculated;

[0103] ρ is in the range of [0, 1] and is equal to 1 only when the two signals fully meet the phase synchronization condition, and is equal to 0 when the phase synchronization condition is violated. This is used to analyze the phase synchronization between two EEG signals. The index is based on entropy, which is obtained by finding the probability of the relative phase φ of the i-th grid, and then obtaining the EEG signal synchronization index graph. Among them, when the phase difference between the two time series is accurate to 16 decimal places, it can be considered that the phase synchronization condition is fully met.

[0104] S23. Determine the highest phase synchronization strength from the multiple phase synchronization strengths;

[0105] S24, calculating the main frequency of the brain wave signal according to the brain wave signal corresponding to the highest phase synchronization intensity;

[0106] S3, obtaining a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set, specifically comprising:

[0107] S31, determining a frequency multiplication corresponding to the main frequency of the brain wave signal;

[0108] In an optional embodiment, the multiple frequencies corresponding to the main frequency of the brain wave signal are determined to be 10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 80 Hz, 90 Hz and 120 Hz,

[0109] S32, mixing the frequency multiplication with a first preset noise to obtain a mixed frequency multiplication;

[0110] Wherein, the first preset noise is white noise;

[0111] S33, obtaining a changed brainwave signal set according to the mixed frequency multiplication, and screening a target main frequency from the main frequencies of the brainwave signals according to the changed brainwave signal set;

[0112] In an optional embodiment, after playing the mixed frequency multiples to the subject, a changed brainwave signal set is obtained, and a frequency multiple that can stimulate brainwave changes is determined based on the changed brainwave signal set, and the main frequency of the brainwave signal corresponding to the frequency multiple is determined as the target main frequency;

[0113] S4. Performing EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio, specifically including:

[0114] S41, obtaining a brain wave analysis energy spectrum according to the changed brain wave signal set;

[0115] S42, adjusting the duration and magnitude of the target main frequency according to the brain wave analysis energy spectrum to obtain a basic audio frequency;

[0116] S5, adding Brownian noise or pink noise to the basic audio to perform chaotic encryption to obtain nonlinear dynamic audio;

[0117] Specifically, the basic audio is added with Brownian noise or pink noise to perform in-phase and anti-phase chaotic encryption to obtain nonlinear dynamic audio;

[0118] In an optional embodiment, as Figure 3 As shown in the table, the basic audio is added with Brown noise or pink noise and any music such as general light music and natural music for in-phase and anti-phase chaotic encryption according to the component ratio table to obtain nonlinear dynamic audio; natural music such as natural ocean waves, such as Figure 3 As shown, the generated nonlinear dynamic audio can be used to add interludes and set frequency bands with random intensity changes;

[0119] The in-phase and anti-phase chaotic encryption refers to the use of signals with opposite phases in the left and right ears simultaneously during chaotic encryption.

[0120] In an optional embodiment, the method further includes verifying the effect of the nonlinear dynamic audio:

[0121] Twenty male and female subjects aged 8-58 years were selected for the audio experiment;

[0122] The first stage is to wear headphones and rest silently for three minutes to obtain 32-channel brain wave signals, such as Figure 4 As shown, the 32-channel EEG signals of the first stage were used to produce nonlinear dynamic audio according to S1 to S5. After the production was completed, the nonlinear dynamic audio was used for the second stage of twelve minutes of audio stimulation, followed by the third stage of three minutes of silent rest.

[0123] According to the brain wave signals of the three stages, the brain wave signal synchronization index diagram of the left and right brain is obtained, such as Figure 5 As shown, the horizontal axis represents time, and the vertical axis represents the brain wave synchronization rate index factor, that is, the phase synchronization intensity. It can be seen that in the second stage ( Figure 5 During the third stage (275s~810s), the nonlinear dynamic audio stimulation increased the left and right brain synchronization rate index factor, and then decreased again when the stimulation stopped in the third stage, proving the stimulation efficacy of nonlinear dynamic audio.

[0124] The energy spectrum of brainwave analysis of the above three stages is obtained, such as Figure 6 As shown, the circle represents the brain, and the color from light to dark represents the brain wave energy from high to low. It can be seen that in the first stage (i.e. Figure 6 During the rest period (1), brainwave energy is very high, and in the second stage (i.e. Figure 6 The brainwave energy decreases and continues to maintain until the third stage (i.e. Figure 6 Rest 2) in the figure shows that the nonlinear dynamic audio of the present invention has a good effect of soothing and regulating emotions.

[0125] Example 2

[0126] Please refer to Figure 2 In this embodiment, an audio production terminal based on EEG nonlinear dynamics analysis includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, each step of the audio production method based on EEG nonlinear dynamics analysis in Example 1 is implemented.

[0127] In summary, the present invention provides an audio production method and terminal based on EEG nonlinear dynamics analysis, which performs Hilbert transform on multi-channel EEG signals to obtain transformed EEG signals; calculates the phase synchronization strength corresponding to every two adjacent transformed EEG signals to obtain multiple phase synchronization strengths; determines the highest phase synchronization strength from the multiple phase synchronization strengths; calculates the main frequency of the EEG signal based on the EEG signal corresponding to the highest phase synchronization strength, and calculates the main frequency using the EEG signal with high correlation, which can ensure the accuracy of subsequent audio production; obtains a changed EEG signal set based on the main frequency of the EEG signal, and filters a target main frequency from the main frequencies of the EEG signal based on the changed EEG signal set; performs EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio, adds Brownian noise or pink noise to the basic audio for chaotic encryption, and obtains nonlinear dynamic audio, which further enhances the emotional soothing and regulatory effects of the audio through Brownian noise or pink noise; utilizes the basic audio to induce specific EEG frequencies, which can stimulate brain neurons in a direction, thereby improving the emotional soothing and regulatory effects of the audio.

[0128] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An audio production method based on EEG nonlinear dynamics analysis, characterized in that: Including steps: Obtaining a brainwave signal set; Calculating a plurality of phase synchronization strengths corresponding to the brain wave signal set, and calculating a main frequency of the brain wave signal based on the plurality of phase synchronization strengths; Acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set; Performing EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio; The step of acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequency of the brainwave signal according to the changed brainwave signal set includes: Determining a frequency multiplication corresponding to a main frequency of the brain wave signal; Mixing the frequency multiplication with a first preset noise to obtain a mixed frequency multiplication; Acquire a changed brainwave signal set according to the mixed frequency multiplication, and select a target main frequency from the main frequencies of the brainwave signals according to the changed brainwave signal set; The performing of EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio includes: Obtaining a brainwave analysis energy spectrum according to the changed brainwave signal set; The duration and magnitude of the target main frequency are adjusted according to the brain wave analysis energy spectrum to obtain basic audio.

2. The audio production method based on EEG nonlinear dynamics analysis according to claim 1, characterized in that: The brainwave signal set includes multi-channel brainwave signals; The step of calculating a plurality of phase synchronization strengths corresponding to the brainwave signal set and calculating the main frequency of the brainwave signal based on the plurality of phase synchronization strengths includes: performing a Hilbert transform on the multi-channel brain wave signal to obtain a transformed brain wave signal; Calculating the phase synchronization strength corresponding to every two adjacent transformed brain wave signals to obtain a plurality of phase synchronization strengths; determining a highest phase synchronization strength from among the plurality of phase synchronization strengths; The main frequency of the brain wave signal is calculated according to the brain wave signal corresponding to the highest phase synchronization intensity.

3. The audio production method based on EEG nonlinear dynamics analysis according to claim 2, characterized in that: The transformed brain wave signal for: ； ； Wherein, H[] represents Hilbert transform, x(t) represents the multi-channel EEG signal, a(t) represents the instantaneous amplitude, Represents the complex phase.

4. The audio production method based on EEG nonlinear dynamics analysis according to claim 1, characterized in that: The performing of EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio includes: Brownian noise or pink noise is added to the basic audio to perform chaotic encryption to obtain nonlinear dynamic audio.

5. An audio production terminal based on EEG nonlinear dynamics analysis, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: Obtaining a brainwave signal set; Calculating a plurality of phase synchronization strengths corresponding to the brain wave signal set, and calculating a main frequency of the brain wave signal based on the plurality of phase synchronization strengths; Acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequencies of the brainwave signal according to the changed brainwave signal set; Performing EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio; The step of acquiring a changed brainwave signal set according to the main frequency of the brainwave signal, and screening a target main frequency from the main frequency of the brainwave signal according to the changed brainwave signal set includes: Determining a frequency multiplication corresponding to a main frequency of the brain wave signal; Mixing the frequency multiplication with a first preset noise to obtain a mixed frequency multiplication; Acquire a changed brainwave signal set according to the mixed frequency multiplication, and select a target main frequency from the main frequencies of the brainwave signals according to the changed brainwave signal set; The performing of EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio includes: Obtaining a brainwave analysis energy spectrum according to the changed brainwave signal set; The duration and magnitude of the target main frequency are adjusted according to the brain wave analysis energy spectrum to obtain basic audio.

6. The audio production terminal based on EEG nonlinear dynamics analysis according to claim 5, characterized in that: The brainwave signal set includes multi-channel brainwave signals; The step of calculating a plurality of phase synchronization strengths corresponding to the brainwave signal set and calculating the main frequency of the brainwave signal based on the plurality of phase synchronization strengths includes: performing a Hilbert transform on the multi-channel brain wave signal to obtain a transformed brain wave signal; Calculating the phase synchronization strength corresponding to every two adjacent transformed brain wave signals to obtain a plurality of phase synchronization strengths; determining a highest phase synchronization strength from among the plurality of phase synchronization strengths; The main frequency of the brain wave signal is calculated according to the brain wave signal corresponding to the highest phase synchronization intensity.

7. The audio production terminal based on EEG nonlinear dynamics analysis according to claim 6, characterized in that: The transformed brain wave signal for: ； ； Wherein, H[] represents Hilbert transform, x(t) represents the multi-channel EEG signal, a(t) represents the instantaneous amplitude, Represents the complex phase.

8. The audio production terminal based on EEG nonlinear dynamics analysis according to claim 5, characterized in that: The performing of EEG nonlinear dynamics analysis based on the target main frequency to obtain basic audio includes: Brownian noise or pink noise is added to the basic audio to perform chaotic encryption to obtain nonlinear dynamic audio.

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