A method, system and storage medium for preparing music to relieve depression based on electroencephalogram signals

Abstract

A system for preparing depression-relieving music based on EEG signals, comprising a database module for storing audition music; an EEG signal acquisition module for acquiring music EEG signals when a subject listens to any music in the database; and a signal processing module for preprocessing the EEG signals. A music production module for generating music based on processed EEG signals, the music production module comprising an editing band selection unit and a production unit; the editing band selection unit for selecting signals on the right side of the EEG signals, and the production unit for producing music based on the signals on the right side. The music of the present invention can effectively relieve depression.

Description

Technical Field

[0001] The present invention relates to the field of music production, and in particular to a method, system and storage medium for preparing music to relieve depression based on electroencephalogram signals. Background Art

[0002] Depression is a state of low mood and pessimism caused by the external environment or one's own psychology. Most depressive emotions caused by daily life and work can be relieved and eliminated after expression, but they will still affect normal study and work in the short term. Some people will gradually develop slow thinking, reduced and slow language and movements due to long-term low mood, lack of interest and loss of pleasure, and develop into depression. When depression is severe, patients will experience symptoms of mental illness such as hallucinations and delusions, and may even commit suicide in severe cases. At the same time, the current costs of psychological counseling and drug treatment for depression are relatively high.

[0003] Therefore, timely intervention in the early stages and promoting positive emotional recovery can not only quickly return to normal life, but also avoid developing depression and reduce treatment costs.

[0004] Music therapy is an effective means of psychotherapy. The treatment room uses various forms of music experience and the therapeutic relationship developed during the treatment process as the driving force of treatment to help patients experience emotions and feelings and guide patients to intervene and channel their emotions.

[0005] Since music therapy is a lower-level intervention method, it has a better effect on people with short-term and early-stage depression. However, there is currently no music library specifically for depression, and there are only a small number of recommended universal music tracks. Listening to limited music repeatedly can easily lead to "immunity", making it difficult to effectively adjust and relieve depressive emotions. Summary of the invention

[0006] The present invention provides a method for preparing depression-relieving music based on electroencephalogram signals, which can not only expand the music library for treating depression, but also effectively adjust and relieve depressive emotions.

[0007] A system for preparing music to relieve depression based on electroencephalogram signals, comprising:

[0008] A database module, which is used to store audition music;

[0009] An EEG signal acquisition module, which is used to acquire music EEG signals when the subject listens to any music in the database;

[0010] A signal processing module, which is used to pre-process the EEG signal;

[0011] A music production module, which is used to generate music based on the processed EEG signals;

[0012] Preferably, the music production module includes an editing band selection unit and a production unit; the editing band selection unit is used to select the signal on the right side of the EEG signal, and the production unit is used to produce music according to the signal on the right side.

[0013] According to the present invention, the system further comprises a denoising module, which is used to perform denoising on the synthesized music;

[0014] Preferably, the audition music includes pentatonic music, Mozart K448 and Bach BWV1050.

[0015] According to the present invention, the signal processing module performs preprocessing on the EEG signal including removing equipment interference and removing artifacts. The equipment interference includes interference from the EEG device and the transmission line itself. Equipment interference removal is achieved by removing limit drift, removing power frequency interference and bandpass filtering. The artifacts include electrooculographic artifacts, electromyographic artifacts, etc., and the artifacts are filtered out by methods such as spatial filters.

[0016] A method for preparing music to relieve depression based on electroencephalogram signals comprises the following steps: collecting electroencephalogram data of a subject when the subject is listening to music, selecting right-side data from the electroencephalogram data to synthesize music sound waves, and producing music based on the music sound waves.

[0017] According to the present invention, collecting brain wave data of subjects when listening to music includes the following steps: selecting n pieces of music from a music library, playing them to the subjects in an experimental environment, and collecting brain wave data of all subjects when listening to music.

[0018] According to the present invention, before selecting the right-side data from the EEG data to synthesize the music sound wave, the following steps are also included: resampling the above-mentioned EEG signal, adjusting the sampling rate to 44100 Hz, and extracting the signal EEG_α in the α frequency band of the selected EEG signal through an 8-13 Hz filter.

[0019] According to the present invention, the method of selecting right-side data from brain wave data to synthesize music sound waves specifically includes: calculating the mean of the square of the amplitude of each corresponding sampling point of the 16 channels of the brain wave signal EEG_α obtained by S2 to obtain a time-power sequence X, i.e., the music sound wave;

[0020] Preferably, the specific steps for obtaining the time-power sequence X are as follows: assuming that the number of sampling time points after resampling is N, the size of the EEG signal EEG_α we obtain is 16*n, and the 16 values ​​of a column of data in EEG_α are squared and averaged respectively to obtain the average power of all channels of the sampling point. The same operation is performed on each column, and finally a 1*n average power matrix, i.e., the time-power sequence X, is obtained.

[0021] According to the present invention, the method of making music according to music sound waves specifically comprises the following steps: converting the music sound waves into .wav format, using the audioread function to read the audio data Y of the music, superimposing X and Y to obtain new audio data Z, and using the audiowrite function to rewrite Z into music M in .wav format;

[0022] Preferably, the audio data Y read by the audioread function is in n*2 format, where n is the sampling point and 2 is the left and right channels. Suppose the two columns of data obtained are y1 and y2, y1 and y2 are added to X' respectively to obtain z1 and z2, and (z1, z2) is the new audio data Z obtained.

[0023] According to the present invention, the method of making music according to music sound waves also includes the following steps: removing noise from the obtained music M through audition software and converting it into .mp3 format.

[0024] A storage medium storing the above-mentioned music for relieving depression.

[0025] Beneficial Effects

[0026] The electric field fluctuations generated by brain neural activities can reflect the state and changes of the nervous system, and further reflect the emotional changes of the subject in real time. By collecting and analyzing EEG signals, the psychological state of the subject can be monitored. Therefore, the present invention collects EEG signals when listening to different music and re-produces the music to obtain music that has a better guiding effect on the depressive area, which can effectively adjust and relieve depressive emotions. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a system block diagram for preparing depression-relieving music based on EEG signals in the present invention. DETAILED DESCRIPTION

[0028] The following will be further described in detail with reference to specific examples of the general formula compound of the present invention and its preparation method and application. It should be understood that the following examples are only for exemplary description and explanation of the present invention and should not be construed as limiting the scope of protection of the present invention. All technologies realized based on the above content of the present invention are included in the scope that the present invention is intended to protect.

[0029] See also Figure 1 As shown, the present invention provides a system for preparing music for alleviating depression based on electroencephalogram signals, comprising:

[0030] A database module is used to store pentatonic music, Mozart K448 and Bach BWV1050.

[0031] The EEG signal acquisition module is used to collect music EEG signals when the subject listens to any music in the database. The EEG instrument used to collect signals includes 16 EEG channels, namely Fp1, Fp2, F3, F4, C3, C4, P3, P4, O1 O2, F7, F8, T3, T4, T5 and T6.

[0032] A signal processing module is used to process EEG signals. Specifically, the signal processing module is used to remove device interference and artifacts. The device interference includes interference from the EEG device and the transmission line itself. The device interference is removed by removing limit drift, power frequency interference and bandpass filtering. The artifacts include electrooculographic artifacts, electromyographic artifacts, etc., and the artifacts are removed by filtering out using methods such as spatial filters.

[0033] The music production module is used to generate music according to the processed EEG signals, and specifically includes an editing band selection unit and a production unit.

[0034] According to previous research results, the angular music in the pentatonic adjustment, Mozart K448 and Bach BWV1050 as basic music all have a certain soothing effect on depression. Therefore, this embodiment uses the angular music in the pentatonic adjustment, Mozart K448 and Bach BWV1050 as basic music, and collects the EEG signals corresponding to the patient subjects listening to any three pieces of music in the above database module in a quiet state with eyes closed.

[0035] Suppose the 16-channel EEG signal collected by listening to horn-tone music is EEG_J, the EEG signal collected by listening to Mozart K448 is EEG_M, and the EEG signal collected by listening to Bach BWV1050 is EEG_B.

[0036] According to previous studies, the power spectrum asymmetry index A (hereinafter referred to as the lateral deviation value) between the left and right hemispheres in the α band of patients with depression is significantly higher than that of normal people, indicating that the left hemisphere activity of patients with depression is enhanced compared with normal people. This feature is particularly obvious in the F3-F4 and F7-F8 parts of the frontal area. Therefore, when making music, the EEG signal with the smallest power spectrum asymmetry index between the left and right hemispheres in the α band is selected, that is, the feature is closer to that of a normal person (one of the three EEG_J, EEG_M, EEG_B).

[0037] The editing band selection unit is used to calculate the lateralization value A according to the channel power ratio of the alpha band F3-F4 (frontal lobe) and F7-F8 (lateral frontal lobe) in the EEG signal, and select the band corresponding to the lateralization value A<0 as the band to be edited.

[0038] A=(Pl-Pr) / (Pl+Pr)……Formula 1

[0039] Among them, Pl is the natural logarithm of the left frontal EEG data, and Pr is the natural logarithm of the right frontal EEG data; EEG data with A < 0 are selected as right-side data;

[0040] Preferably, EEG data with −0.21≤A<0 is selected as the data on the right side; preferably, EEG data with −0.15≤A<0 is selected as the data on the right side; more preferably, EEG data with −0.1≤A<0 is selected as the data on the right side.

[0041] The production unit is used to produce the to-be-edited band into a music file, specifically, including producing music sound waves, synthesizing the music file according to the music sound waves, and then adding sound sources to the music file.

[0042] The present invention also provides a method for preparing depression-relieving music based on electroencephalogram signals, comprising the following steps:

[0043] S1. Select n pieces of music from the music library and play them to the subjects in an experimental environment. At the same time, collect the electroencephalogram (EEG) data of all subjects while listening to the music.

[0044] S2. Since the original sampling rate of the EEG signal is 1000 Hz and the sampling rate of the music is 44100 Hz, the above EEG signal is resampled to keep it consistent with the sampling rate of the music.

[0045] S3. Extract the signal EEG_α in the α frequency band of the selected EEG signal through an 8-13 Hz filter.

[0046] S4. According to research, the power of the α frequency band of patients with depression is greater than that of normal people. Therefore, the present invention uses the power of the α frequency band in the EEG signal to transform music. The specific transformation method is to calculate the mean of the square of the amplitude of each corresponding sampling point of the 16 channels of the EEG signal EEG_α obtained by S2 to obtain a time-power sequence X. (Assume that the number of sampling time points after resampling is N, then the size of the EEG signal EEG_α we obtain is 16*n. The 16 values ​​of a column of data in EEG_α are squared and averaged respectively to obtain the average power of all channels of the sampling point. The same operation is performed on each column, and finally a 1*n average power matrix, i.e., the time-power sequence X, is obtained.)

[0047] S5. Then, convert the selected music into .wav format, use the audioread function to read the audio data Y of the music, superimpose X and Y to obtain new audio data Z (the audio data Y obtained by this function is n*2, where n is the sampling point, 2 is the left and right channels, and the two columns of data obtained are y1 and y2. Add y1 and y2 to X' respectively to obtain z1 and z2, and (z1, z2) is the new audio data Z).

[0048] S6. Use the audiowrite function to rewrite Z into music M in .wav format.

[0049] S7. The obtained music M is denoised by audition software and converted into .mp3 format.

[0050] A storage medium storing the above-mentioned music for relieving depression.

[0051] The above is an explanation of the embodiments of the present invention. However, the present invention is not limited to the above embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for preparing music to relieve depression based on electroencephalogram signals, characterized in that: The method comprises the following steps: collecting brain wave data of a subject while listening to music, resampling the brain wave data, adjusting the sampling rate to 44100 Hz, extracting the signal EEG_α in the α frequency band of the selected brain wave data through an 8-13 Hz filter; selecting right-side data from the brain wave data to synthesize music sound waves, and producing music according to the music sound waves; Collecting brain wave data of subjects when listening to music includes the following steps: selecting n pieces of music from a music library, playing them to the subjects in an experimental environment, and collecting brain wave data of all subjects when listening to music. The selecting right-side data from the brain wave data to synthesize music sound waves specifically includes: calculating the mean of the square of the amplitude of each corresponding sampling point of the 16 channels of the obtained brain wave signal EEG_α, and obtaining a time-power sequence X, that is, the music sound wave; The specific steps to obtain the time-power sequence X are as follows: let the number of sampling time points after resampling be N, then the size of the EEG signal EEG_α we get is 16*N, square the 16 values ​​of a column of data in EEG_α and calculate the average value to get the average power of all channels at the sampling point, perform the same operation on each column, and finally get a 1*N average power matrix, that is, the time-power sequence X; Convert the above music sound wave into .wav format, use audioread function to read the audio data Y of the music sound wave, superimpose X and Y to obtain new audio data Z, and use audiowrite function to rewrite Z into music M in .wav format; The audio data Y read by audioread function is in N*2 format, where N is the number of sampling time points and 2 is the left and right channels. Suppose the two columns of data are y1 and y2, add y1 and y2 to X' respectively to get z1 and z2, and (z1, z2) is the new audio data Z.

2. The method for preparing depression-relieving music based on EEG signals according to claim 1, characterized in that: After making music according to music sound waves, the method also includes the following steps: removing noise from the obtained music M through audition software and converting it into .mp3 format.

3. A storage medium, characterized in that: It stores music for relieving depression prepared by the method for preparing music for relieving depression based on electroencephalogram signals as described in any one of claims 1 to 2.

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