中医脉象信号的短时傅里叶分析

STFT Analysis of Pulse Signals

众所周知,短时傅里叶变换是信号时频分析的变换方法。连续短时功率谱表示信号在连续时间与连续频率平面内的能量分布,而离散短时功率谱表示信号x(n)在离散时间与连续频率平面内的功率分布。应用全极点滑动窗递归算法,分析了15例吸毒者和15例正常人脉象信号的离散短时功率谱,发现吸毒者脉象信号在特定时频区域内的平均功率值P1一般高于正常人的值。以平均功率P1与总平均功率P的比值为特征参数,提出了用于划分正常人和吸毒者的临界参数,据此15例吸毒者全被检测出来,但有两例正常人被误判。研究结果表明,短时傅里叶变换是分析脉象信号的有效方法。

It is well known that the short-time Fourier transform (STFT) is a transformation method used for timefrequency analysis of signals.The continuous short-time power spectrum represents the energy distribution of a signal x(t) on the plane with continuous time and frequency. However, the discrete short-time power spectrum represents the power distribution of a signal x(n) on the plane with discrete time and continuous frequency. An efficient recursive algorithm with all-pole moving-windows is used to analyze the discrete short-time power spectra of pulse signals for 15 heroin addicts and 15 healthy persons. It is found that the average power p1 of heroin addicts on a specified time-frequency region is generally higher than that of healthy persons. Using the ratio of average power p1 to total average power p as characteristic parameter, a critical parameter is determined that is used to classify heroin addicts and healthy persons. Thus, all of the 15 heroin addicts are identified. Only two healthy persons are misjudged. It is shown that the STFT is really an effective method for the analysis of pulse signals.