Don M, Elberling C, Waring M
Scand Audiol. 1984;13(4):219-28. doi: 10.3109/01050398409042130.
Detection of an auditory brainstem response, ABR, usually relies on visual evaluation of two or more data acquisition runs of a fixed number of sweeps to determine if there is sufficient replication of the averaged waveforms to indicate a response. Visual interpretation can be difficult when the signal-to-noise ratio is poor because of either a small response or high levels of physiological background noise. Moreover, variations in the background noise from run to run can result in poor or spurious replications of component peaks and troughs in the waveform. A previous study (Elberling & Don, 1984) described a statistical approach for objective evaluation of the quality of an ABR recording. The method uses variance analysis in calculating the ratio of the magnitude of the ABR to the estimated averaged background noise. This study further applies this method to obtain a quantitative definition of the ABR threshold, to demonstrate its application in automatic threshold detection, and to estimate the number of sweeps required to reach detection criterion. Application of this method is valuable in reducing the variability of test interpretation and in maximizing the efficiency of recording ABRs by avoiding the averaging of excessive or insufficient numbers of sweeps. These improvements enhance the cost-benefit of ABR testing to the patient.
听觉脑干反应(ABR)的检测通常依靠对固定次数扫描的两个或更多次数据采集运行进行视觉评估,以确定平均波形是否有足够的重复性来表明存在反应。当信噪比很差时,由于反应较小或生理背景噪声水平较高,视觉解读可能会很困难。此外,每次运行时背景噪声的变化可能会导致波形中成分峰谷的重复性差或出现虚假重复。先前的一项研究(埃尔伯林和唐,1984年)描述了一种用于客观评估ABR记录质量的统计方法。该方法在计算ABR幅度与估计的平均背景噪声之比时使用方差分析。本研究进一步应用该方法来获得ABR阈值的定量定义,展示其在自动阈值检测中的应用,并估计达到检测标准所需的扫描次数。该方法的应用对于减少测试解读的变异性以及通过避免过多或过少扫描次数的平均来最大化记录ABR的效率很有价值。这些改进提高了ABR测试对患者的成本效益。