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基于EEG的音乐舒缓紧张情绪的研究 被引量:8

Research on EEG-Based Music Relieving Occupational Stress
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摘要 将音乐、脑电波(Electroencephalogram,EEG)与情绪治疗三者相结合,让处于紧张情绪下的人聆听不同类型音乐,观察在不同音乐作用前后被测者EEG波形能量变化,以此分析出情绪刺激下左右脑区对不同类型音乐的敏感程度;利用快速傅里叶变换(Fast Fourier Transform,FFT)加窗函数实现对脑电信号α、β波段的特征提取,由对应节律的功率谱的对比发现,音乐舒缓后α波主要占用频宽无明显改变,β波主要占用频宽变大;最后,利用Hjorth参数进行时频分析,检测时间序列的信号活动,从而验证舒缓的音乐有利于缓解紧张情绪,并且左脑对节奏欢快的音乐更敏感,右脑对忧伤的音乐更敏感。在此研究的基础上提出,未来进行音乐治疗时,针对不同情绪,选择不同音乐的融合比例,会达到更好的治疗效果。 Combining music,electroencephalogram(EEG) and emotion therapy,allowing people under stress to listen to different types of music,the EEG waveform energy changes of the subject before and after different musical effects was observed;and the emotional stimuli sensitivity degrees of the lower left and right brain regions under different types of music were analyzed;the features of the alpha and beta wave bands of the brain electrical signals were extracted by using fast Fourier transform(FFT) windowing functions. Through the comparison of the power spectrum of the corresponding rhythms after music soothing,there is no obvious change in the main occupied bandwidth of αwave;and β wave mainly occupies a larger bandwidth. Finally,Hjorth parameters were used for time-frequency analysis to detect the signal activity of time series;thus verifying that soothing music is beneficial to relieve tension. And the left brain is more sensitive to rhythmic music,and the right brain is more sensitive to sad music. Based on this research,it is proposed that in the future of music therapy different music will be selected for different emotions;and a better therapeutic effect will be achieved.
作者 彭金歌 郭滨 沙文青 白雪梅 张晨洁 PENG Jinge;GUO Bin;SHA Wenqing;BAI Xuemei;ZHANG Chenjie(School of Electronics and Information Engineering,Changchun University of Science and Technology,Changchun 130022)
出处 《长春理工大学学报(自然科学版)》 2019年第1期106-112,共7页 Journal of Changchun University of Science and Technology(Natural Science Edition)
基金 吉林省自然科学基金项目(20150101013JC)
关键词 脑电信号 音乐 紧张情绪 功率谱 Hjorth参数 EEG signals music tension power spectrum Hjorth parameter
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