Clayton R H, Murray A, Campbell R W
Regional Medical Physics Department, Freeman Hospital, Newcastle upon Tyne, UK.
Med Biol Eng Comput. 1993 Mar;31(2):111-7. doi: 10.1007/BF02446668.
Four ventricular fibrillation (VF) detection techniques were assessed using recordings of VF to evaluate sensitivity and VF-like recordings to evaluate specificity. The recordings were obtained from Coronary Care Unit patients. The techniques were: threshold crossing intervals (TCI); peaks in the autocorrelation function (ACF); signal content outside the mean frequency (VF-filter); and signal spectrum shape (spectrum). Using 70 extracts, each 4 s long, from VF recordings, the VF filter achieved a sensitivity of 77 per cent; the ACF, TCI and spectrum algorithms had sensitivities of 67, 53 and 46 per cent, respectively. Susceptibility to false alarms was assessed using 40 extracts from VF-like recordings. The TCI algorithm was the most specific (93 per cent), while the spectrum, VF filter and ACF algorithms had specificities of 72, 55 and 38 per cent, respectively. The TCI algorithm achieved overall sensitivity of 93 per cent and specificity of 60 per cent. The spectrum, VF filter and ACF algorithms had overall sensitivities of 80, 93 and 87 per cent, and overall specificities of 60, 20 and 0 per cent, respectively.
使用室颤（VF）记录评估了四种室颤检测技术，以评估敏感性，并使用类室颤记录评估特异性。记录取自冠心病监护病房患者。这些技术包括：阈值穿越间隔（TCI）；自相关函数（ACF）中的峰值；平均频率之外的信号内容（VF滤波器）；以及信号频谱形状（频谱）。使用来自室颤记录的70个时长均为4秒的片段，VF滤波器的敏感性达到77%；ACF、TCI和频谱算法的敏感性分别为67%、53%和46%。使用来自类室颤记录的40个片段评估误报敏感性。TCI算法特异性最高（93%），而频谱、VF滤波器和ACF算法的特异性分别为72%、55%和38%。TCI算法的总体敏感性为93%，特异性为60%。频谱、VF滤波器和ACF算法的总体敏感性分别为80%、93%和87%，总体特异性分别为60%、20%和0%。
