Institute of Sound and Vibration Research, Faculty of Engineering and the Environment, University of Southampton, United Kingdom.
Interacoustics Research Unit, c/o Technical University of Denmark, Denmark.
Ear Hear. 2021 May/Jun;42(3):574-583. doi: 10.1097/AUD.0000000000000959.
Statistical detection methods are useful tools for assisting clinicians with cortical auditory evoked potential (CAEP) detection, and can help improve the overall efficiency and reliability of the test. However, many of these detection methods rely on parametric distributions when evaluating test significance, and thus make various assumptions regarding the electroencephalogram (EEG) data. When these assumptions are violated, reduced test sensitivities and/or increased or decreased false-positive rates can be expected. As an alternative to the parametric approach, test significance can be evaluated using a bootstrap, which does not require some of the aforementioned assumptions. Bootstrapping also permits a large amount of freedom when choosing or designing the statistical test for response detection, as the distributions underlying the test statistic no longer need to be known prior to the test.
To improve the reliability and efficiency of CAEP-related applications by improving the specificity and sensitivity of objective CAEP detection methods.
The methods included in the assessment were Hotelling's T2 test, the Fmp, four modified q-sample statistics, and various template-based detection methods (calculated between the ensemble coherent average and some predefined template), including the correlation coefficient, covariance, and dynamic time-warping (DTW). The assessment was carried out using both simulations and a CAEP threshold series collected from 23 adults with normal hearing.
The most sensitive method was DTW, evaluated using the bootstrap, with maximum increases in test sensitivity (relative to the conventional Hotelling's T2 test) of up to 30%. An important factor underlying the performance of DTW is that the template adopted for the analysis correlates well with the subjects' CAEP.
When subjects' CAEP morphology is approximately known before the test, then the DTW algorithm provides a highly sensitive method for CAEP detection.
统计检测方法是协助临床医生进行皮质听觉诱发电位（CAEP）检测的有用工具，有助于提高测试的整体效率和可靠性。然而，许多这些检测方法在评估测试显著性时依赖于参数分布，因此对脑电图（EEG）数据做出了各种假设。当这些假设被违反时，可能会降低测试的灵敏度和/或增加或降低假阳性率。作为参数方法的替代方法，可以使用不要求上述某些假设的自举来评估测试显著性。自举还允许在选择或设计用于响应检测的统计测试时有大量的自由度，因为测试统计量的分布在测试之前不再需要知道。
通过提高客观 CAEP 检测方法的特异性和灵敏度，提高 CAEP 相关应用的可靠性和效率。
评估中包括的方法有 Hotelling 的 T2 检验、Fmp、四个修改后的 q 样本统计量以及各种基于模板的检测方法（在集合相干平均值和一些预定义模板之间计算），包括相关系数、协方差和动态时间扭曲（DTW）。评估使用模拟和从 23 名听力正常的成年人中收集的 CAEP 阈值系列进行。
最敏感的方法是基于自举的 DTW，最大测试灵敏度（相对于传统的 Hotelling 的 T2 检验）增加高达 30%。DTW 性能的一个重要因素是用于分析的模板与受试者的 CAEP 很好地相关。
当在测试之前大约了解受试者的 CAEP 形态时，那么 DTW 算法为 CAEP 检测提供了一种高度敏感的方法。
