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心率变异性(HRV)是现代医学中判定人体状态的重要指标,本文采用改进的Welch方法分析HRV的频域特性,研究人体疲劳度与迷走神经的关系。本文首先给待处理信号加一个时间窗函数,根据需求设定时间长度之后再进行信号频域分析。此方法与经典谱分析方法中的周期图法相比,谱估计的分辨率和方差均得到改善,并且可以任意设定分析HRV的时间长度(目前测量短时HRV的国际标准是5min)。依照本文方法以PhysioNet提供的心电数据库分析疲劳人群的HRV特点,结果显示以Welch法结合适当的窗函数对HRV分析的准确度大大提高,并得到疲劳人群迷走神经活性下降、交感神经活性增强的结果。
Heart rate variability (HRV) is an important index for judging the state of human body in modern medicine. In this paper, the improved Welch method is used to analyze the frequency-domain characteristics of HRV to study the relationship between human fatigue and vagal nerve. In this paper, we first add a time window function to the signal to be processed, and set the time length according to the demand and then analyze the signal frequency domain. This method improves the resolution and variance of the spectral estimation compared with the periodogram method in the classical spectral analysis method, and the length of time for analyzing the HRV can be set arbitrarily (currently, the international standard for measuring the short-term HRV is 5 minutes). The HRV features of fatigue population were analyzed according to the ECG database provided by PhysioNet in this paper. The results showed that the accuracy of HRV analysis with Welch method and appropriate window function was greatly improved, and the results showed that vagal activity decreased and sympathetic activity increased in fatigue population .