D'Attellis C E, Isaacson S I, Sirne R O
Departamento de Matemática, Facultad de Ingeniería, Universidad de Buenos Aires, Argentina.
Ann Biomed Eng. 1997 Mar-Apr;25(2):286-93. doi: 10.1007/BF02648043.
This study deals with the problem of identification of epileptic events in electroencephalograms using multiresolution wavelet analysis. The following problems are analyzed: time localization and characterization of epileptiform events, and computational efficiency of the method. The algorithm presented is based on a polynomial spline wavelet transform. The multiresolution representation obtained from this wavelet transform and the corresponding digital filters derived allows time localization of epileptiform activity. The proposed detector is based on the multiresolution energy function. Electroencephalogram records from epileptic patients were analyzed, and results obtained are shown. Some comparisons with other methods are given.
本研究探讨了使用多分辨率小波分析识别脑电图中癫痫事件的问题。分析了以下问题：癫痫样事件的时间定位与特征描述，以及该方法的计算效率。所提出的算法基于多项式样条小波变换。从该小波变换获得的多分辨率表示以及导出的相应数字滤波器可实现癫痫样活动的时间定位。所提出的检测器基于多分辨率能量函数。对癫痫患者的脑电图记录进行了分析，并展示了所得结果。还与其他方法进行了一些比较。
