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Journal of Shanghai University >

2021 , Vol. 27 >Issue 3: 514 - 524

DOI: https://doi.org/10.12066/j.issn.1007-2861.2163

Research Articles

Electroencephalogram features based on detrended fluctuation analysis of different features of music stimulation

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  • Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China

Received date: 2019-05-29

  Online published: 2020-02-02

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Abstract

In this study, we investigated the effects of different musical features on the electrophysiological and psychological responses of participants, and explored the long-range correlations of electroencephalograms (EEGs). We recruited 10 students to participate in four listening tasks involving different musical features. After each task, the participants completed a self-evaluation of their emotions. Scalp EEG signals were collected synchronously during the tasks. Considering the non-stationary and nonlinear characteristics of music-stimulated EEGs, we used a nonlinear method to detect the long-range correlation of non-stationary time series, namely, detrended fluctuation analysis. Long-range correlations were analysed by calculating the scale index of the EEG signal sub-band sequence, and combining it with behavioural data. The results show that the positive emotions induced by the rising tone of the happy version are significantly reduced, and whether it was rising tone or falling tone, it would significantly reduce the sad emotions induced by sad music. Under musical stimulation involving different tonal features, the subjects showed obvious brain lateralisation characteristics in the alpha and beta bands, with the left hemisphere brain dynamics showing greater activity. Moreover, the scale index used in this study was shown to reflect the specificity of EEG under different musical stimuli.

Key words： emotional music; electroencephalogram (EEG); detrended fluctuation analysis; lateralisation

Cite this article

ZHU Jiacheng, LI Yingjie . Electroencephalogram features based on detrended fluctuation analysis of different features of music stimulation[J]. Journal of Shanghai University, 2021 , 27(3) : 514 -524 . DOI: 10.12066/j.issn.1007-2861.2163

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