本文選題：腦電 + 音樂�。� 參考：《電子科技大學》2013年博士論文

【摘要】：腦電信號（Electroencephalogram，簡稱EEG）是人腦神經(jīng)元活動的綜合表現(xiàn)，包含豐富的神經(jīng)信息。音樂是人腦智力活動的產(chǎn)物，對人的身心有著巨大的影響。大腦和音樂之間的關系，一直是神經(jīng)科學、心理學等領域研究的熱點問題。研究如何將腦電信號轉(zhuǎn)換為音樂，并對得到的音樂進行分析和研究，對深入探討大腦與音樂的關系有重要意義。 本文從挖掘腦電信號與音樂的數(shù)理共性入手，提出了系列的基于腦電與音樂共同遵循的無標度性質(zhì)的腦波音樂轉(zhuǎn)換方法，主要工作如下： 1.根據(jù)腦電的振幅和音樂中音高的分布都滿足的無標度特征，提出了基于單道EEG數(shù)據(jù)的無標度腦波音樂方法，將EEG信號按照波形特征標記為“事件”，將一個事件映射為一個音符，其中事件的時間長度映射為音長，波形的振幅按照無標度關系映射為音高，平均功率映射為音強。實際的EEG信號被用于音樂生成，結(jié)果發(fā)現(xiàn)，不同狀態(tài)下的腦波音樂可以被較好地區(qū)分，與另一種基于喚醒度水平的腦波音樂生成方法相比，這種無標度的方法忠實反映了波形的細節(jié)信息，并保留了信號原有的無標度性質(zhì)。同時開發(fā)了相應的實時腦波音樂系統(tǒng)，可以用于實時監(jiān)控或者反饋。 2.在單道無標度腦波音樂方法基礎上，提出了一種將兩道對稱電極的EEG信號轉(zhuǎn)換為兩聲部合奏腦波音樂的方法。首先將取自左右半球?qū)ΨQ電極的信號分別轉(zhuǎn)換為MIDI音樂序列，然后根據(jù)中國五聲調(diào)式和西方七聲調(diào)式的概念對其進行處理，結(jié)果發(fā)現(xiàn)音樂的音高分布都符合無標度性，且兩種調(diào)式在大腦不同狀態(tài)下得到的標度指數(shù)有顯著的差異，其中五聲調(diào)式的音樂聲部之間的協(xié)和性更高，其和聲音程的分布更符合無標度性。另外，經(jīng)過五聲調(diào)式的處理，大腦兩種不同睡眠狀態(tài)音樂的差異變得更為明顯。 3.通過對大量音樂作品的分析，發(fā)現(xiàn)音程的協(xié)和性振蕩具有無標度性，可以一定程度上反映作曲家的創(chuàng)作偏好，據(jù)此建立的音樂家網(wǎng)絡可以反映他們之間在和聲應用上的傳承和相互影響。在此基礎上，提出了無標度振蕩的腦波音樂方法，首先將兩個電極的信號分別轉(zhuǎn)換為MIDI音樂序列，然后利用同樣滿足無標度振蕩的EEG相位同步指數(shù)，對該合奏音樂的音程協(xié)和性和音強進行調(diào)整。當兩個信號同步指數(shù)高時，音樂協(xié)和性就高，音強較大；當同步指數(shù)低時，音樂趨向于不協(xié)和，音強較小。對安靜狀態(tài)下睜眼和閉眼的腦波合奏音樂進行分析，發(fā)現(xiàn)調(diào)整后音樂的標度指數(shù)更加接近原始腦電信號。這種方法可以對大腦各腦區(qū)的協(xié)作性的動態(tài)變化進行藝術(shù)性地表達。 4.分析和討論了音樂中節(jié)奏的功率譜，選擇了各種不同風格的中國樂曲，包括古曲、兒歌、流行樂和地方戲曲，發(fā)現(xiàn)其節(jié)奏功率譜均符合標度分布。在此基礎上，提出了多聲部腦波音樂方法。在將每個電極的信號分別轉(zhuǎn)換為MIDI音樂序列后，模擬作曲家的創(chuàng)作，設計了藝術(shù)濾波器，保留原始音樂中符合調(diào)式和節(jié)拍要求的音符，最終形成多聲部的合奏音樂。結(jié)果表明，合奏腦波音樂比單道音樂更具節(jié)奏感，其音樂性與豐富性也明顯優(yōu)于單道音樂。此外，合奏腦波音樂還具有更接近原始數(shù)據(jù)的標度指數(shù)，，且更加易于區(qū)分不同的狀態(tài)。 5.將無標度腦波音樂用于齒科正畸疼痛控制。實驗中，被試在放置弓絲以后，被分為三個組，施以不同的干預措施。腦波音樂組的被試要求每天聆聽本人的腦波音樂，該音樂采用的是在放置弓絲前采集的安靜閉眼狀態(tài)的EEG數(shù)據(jù)；空白對照組的被試不接受任何干預；認知行為療法（CBT）組的被試要求每天聆聽相應的錄音指導。實驗結(jié)果表明，腦波音樂對于正畸疼痛有較好的控制作用，與空白組和CBT組相比，腦波音樂組在疼痛量表得分上比其他兩組有明顯的降低，其EEG相干網(wǎng)絡的連接密度明顯大于空白組，比CBT組也略大，網(wǎng)絡參數(shù)更接近小世界屬性。這說明腦波音樂在疼痛控制上有較為明顯的效果，甚至略優(yōu)于當前熱門的行為療法。
[Abstract]:Electroencephalogram (EEG) is a comprehensive manifestation of the activity of the human brain neuron, which contains rich nerve information. Music is the product of the mental activity of the human brain. It has a great influence on human body and mind. The relationship between the brain and music has always been a hot issue in the fields of neuroscience and psychology. The conversion of electrical signals into music and the analysis and research of the music obtained are of great significance to further explore the relationship between the brain and music.
This paper, starting with the discovery of the mathematical generality of EEG and music, presents a series of scale-free brain wave music conversion methods based on the common compliance of EEG and music. The main work is as follows:
1. according to the scale-free characteristics of the amplitude of electroencephalogram and the distribution of the high sound in the music, a method of scale-free brain wave music based on single channel EEG data is proposed. The EEG signal is marked as "event" according to the waveform characteristics, and an event is mapped to a note, in which the length of the event is mapped to the length, and the amplitude of the waveform is in accordance with no standard. The degree relationship is mapped to pitch, and the average power is mapped to the sound intensity. The actual EEG signal is used for music generation. The results show that brain wave music in different states can be better divided. Compared with another method based on the wakefulness level, this method faithfully reflects the details of the waveform and preserves the information of the waveform. The original scale-free property of the signal is developed, and the corresponding real-time brain wave music system is developed, which can be used for real-time monitoring or feedback.
2. on the basis of single channel non scale-free brain wave music method, a method of converting the EEG signal of two symmetrical electrodes into two voice ensemble brain wave music is proposed. First, the signals from the left and right hemispherical symmetrical electrodes are converted into MIDI music sequences, and then they are carried out according to the concept of Chinese five tone and Western seven tones. The results show that the pitch distribution of the music is in conformity with the scale-free degree, and the scale index of the two modes in different states of the brain is significantly different. Among them, the concordance of the five sound modes is higher, and the distribution of the sound course is more consistent with the standard degree. In addition, the brain is treated with five tones and two different kinds of sleep in the brain. The difference in the sleeping state of music became more obvious.
3. through the analysis of a large number of music works, it is found that the concordance oscillation of the range has no scale, which can reflect the composer's creation preference to a certain extent. On this basis, the network of musicians can reflect the inheritance and mutual influence of the harmonic application between them. On this basis, a method of brainwave music with no scale oscillation is proposed. First, the signals of the two electrodes are converted into MIDI music sequences, and then the synchro and intensity of the ensemble music are adjusted by using the same EEG phase synchronization index that satisfies the scale-free oscillation. When the two signal synchronization index is high, the music concordance is high and the sound intensity is large; when the synchronization index is low, the music tends to be uncoordinated. An analysis of brain wave ensemble music of open and closed eyes in quiet states shows that the scale index of the adjusted music is closer to the original EEG. This method can express the cooperative dynamic changes in the brain regions of the brain.
4. analyze and discuss the power spectrum of rhythm in music, choose different styles of Chinese music, including ancient music, nursery rhyme, pop music and local opera, and find that the power spectrum of the rhythm is in conformity with the scale distribution. On this basis, a multi part brain wave music method is proposed. After converting the signals of each electrode to the MIDI music sequence, The composition of the simulated composer, designed the art filter, retained the notes in the original music that conforms to the requirements of the tone and beat, and finally formed the ensemble music of the multiple voices. The result shows that the ensemble brain wave music is more rhythmic than single music, and its musicality and richness are obviously better than single track music. In addition, the ensemble brain wave music is also more connected. The scaling index near the original data is more easily distinguished from different states.
5. the scale-free brain wave music was used to control the orthodontic pain control. In the experiment, the subjects were divided into three groups after placing the bow wire and were divided into different intervention measures. The subjects of the brain wave group were asked to listen to my brain wave music every day. The music used the EEG data of quiet closed eye state before placing the bow wire; blank control The group's subjects did not accept any intervention; the subjects of the cognitive behavioral therapy (CBT) group were asked to listen to the corresponding recording instructions every day. The results showed that brain wave music had a better control effect on orthodontic pain. Compared with the blank group and the CBT group, the brain wave group was significantly lower than the other two groups in the score of the pain scale, and its EEG coherence. The connection density of the network is obviously larger than that of the blank group, which is slightly larger than the CBT group, and the network parameters are closer to the small world properties. This shows that the brain wave music has a more obvious effect on the pain control, and is even slightly better than the current popular behavioral therapy.
【學位授予單位】：電子科技大學
【學位級別】：博士
【學位授予年份】：2013
【分類號】：R318

【引證文獻】

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1 孟可;王凡;王毅;;生理檢測綜合評價工作負擔研究[J];中國測試;2015年04期

相關碩士學位論文 前2條

1 王超前;意守丹田功法對注意力影響的實驗研究[D];揚州大學;2014年

2 孟可;基于生理檢測與音樂調(diào)節(jié)綜合評價工作負擔研究[D];中北大學;2015年

本文編號：2066206