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本文基于多重分形去趋势波动分析方法(MFDFA)实现了对受试者心理压力状态的评估。研究针对不同心理压力状态下,脑电信号多重分形去趋势波动分析中最优分形阶数确定问题,重点分析了多重分形去趋势波动分析方法中的奇异指数、Hurst指数等参数与阶数的关系,进而确定最优分形阶数,实现了基于脑电信号多重分形去趋势波动分析的心理压力状态评估。试验采集了14名在校学生有/无心理压力状态下的脑电信号,分别比较了奇异指数、奇异维数、Hurst指数、质量指数与阶数关系,确定了最优分形阶数范围为[—5,5],实现了基于脑电信号β波多重分形去趋势波动分析方法的心理压力状态评估。研究结果表明,心理压力状态下,脑电信号的Hurst指数和质量指数大于无压力状态下,脑电信号的相应参数,随着阶数的变大,Hurst指数减小,趋近于定值,而质量指数增大,奇异值随阶数的变化幅度较明显。本文还比较了有/无心理压力状态下,脑电信号的峰值和奇异谱宽度,结果表明,不同心理压力状态下脑电信号多重分形谱特性不同,心理压力状态下,脑电信号的奇异谱宽度明显大于无压力状态下脑电信号的奇异谱宽度。本文研究结果说明,该方法可以有效地评估心理压力状态,为实现心理压力状态干预,提高心理健康等提供支持与帮助。
In this paper, based on the multifractal de-trend analysis method (MFDFA) to achieve the assessment of the psychological stress status of the subjects. This paper focuses on the problem of determining the optimal fractal order in the trend analysis of multi-fractal depolarization of EEG under different psychological stress states. The relationship between singular exponent, Hurst exponent and other order in multi-fractal de-trend fluctuation analysis , And then determine the optimal fractal order to achieve the psychological pressure state assessment based on the multi-fractal trend analysis of EEG signals. The experiment collected 14 EEG signals with and without psychological stress in school students, and compared singular index, singular dimension, Hurst index, mass index and order, and determined the optimal range of fractal order as [ -5,5], to achieve the psychological pressure state assessment based on β-wave multifractal trend analysis of EEG signals. The results show that under the condition of psychological stress, the Hurst index and the mass index of EEG are greater than the corresponding parameters of EEG signals under no pressure. As the order becomes larger, the Hurst index decreases and approaches the fixed value, The quality index increases, the singular value with the magnitude of the change is more obvious. In addition, the peak and singular spectral widths of EEG signals with / without psychological stress are compared. The results show that the multifractal spectrum characteristics of EEG signals under different psychological stress are different. Under singular stress, the singular spectrum of EEG signals The width is significantly larger than the singular spectral width of EEG signals under no pressure condition. The results of this study show that this method can effectively assess the state of psychological stress and provide support and help for psychological stress intervention and mental health improvement.