小波变换在吸毒者脉象信号分析中的应用

Application of the Wavelet Transform to the Pulse Signal Analysis of Druggers

根据脉象信号的随机特性,采用小波变换中的多分辨率分析算法对其进行分析,旨在提取海洛因吸毒者脉象信号的异常信息,并得出区分正常人与吸毒者的初步的判断依据.基于小波变换的脉象信号的尺度谱携带有人体健康状况的重要特征信息.对15例海洛因吸毒者和15例正常人的脉象信号进行分析,提取出每例信号的尺度谱和该信号的总能量,发现吸毒者脉象信号在特定尺度与时间区域内的尺度谱之和(即尺度-小波能量)和该信号总能量的比值明显高于正常人.以该尺度与时间区域内的尺度-小波能量和该信号总能量之比的百分值作为判断正常人和吸毒者的特征参量,提出了用于划分正常人和吸毒者的临界参数.据此,15例正常人从30例受测者中全部被正确地检测出来,但有两例吸毒病人被误判为正常人.结果表明,该方法是检测海洛因吸毒者脉象信号异常的有效且可行的方法.

According to the randomness of human pulse signals, the multiresolution analysis of the wavelet transform is used to analyze such signals. Its purpose is to extract the abnormal information from the pulse signals of heroin druggers and to obtain the primary judgment criterion which can be used to identify druggers from healthy persons. The scale spectrum based on the wavelet transform of pulse signals carries the important characteristic information of the health situation of human body. The pulse signals of 15 heroin druggers and 15 healthy persons are analyzed and the scale spectrum and the total signal energy of every signal are extracted. It is found that the ratio between the sum （ i. e. , scalewavelet energy） of the scale spectrum in a specific scale-time region and the total signal energy for heroin druggers is generally higher than that of healthy persons. Using the percentage of the ratio between the scale-wavelet energy in the specific scale-time region and the total signal energy as characteristic parameter, a critical parameter is determined that is used to classify heroin druggers and healthy persons. Thus, all of the 15 healthy persons are identified correctly from 30 subjects. Only two heroin persons are misjudged. The experiment results of classification show that the method presented is feasible and effective for detecting the pulse abnormalities of heroin druggers.