Ozdamar O, Delgado R E, Eilers R E, Urbano R C
Department of Biomedical Engineering, University of Miami, Coral Gables, FL 33124.
J Am Acad Audiol. 1994 Mar;5(2):77-88.
The efficacy of utilizing an automated algorithm to identify auditory brainstem responses (ABR) was studied. A microcomputer-based threshold-seeking algorithm utilizing click-evoked ABR was developed to determine evoked-response thresholds for automated hearing screening. The software consists of an evoked-response recognizer unit, which determines the presence or absence of a response, and a threshold-tracking unit, which controls the click intensity in order to track the threshold. The response recognizer is based upon correlation methods. Threshold tracking is accomplished using a Parameter Estimation by Sequential Testing (PEST) procedure, which is commonly used to study psychophysical properties of the auditory system. Sound level is automatically adjusted, based on the results of the recognizer and the threshold tracker. Test results were generally obtained in less than 15 minutes per ear. The results of the automated procedure correlate very highly with expert judgments of ABR threshold and show good test-retest reliability, suggesting that automated procedures are viable alternatives to traditional testing methods.
研究了利用自动算法识别听觉脑干反应(ABR)的效果。开发了一种基于微型计算机的利用短声诱发ABR的阈值搜索算法,用于确定自动听力筛查的诱发反应阈值。该软件由一个诱发反应识别单元和一个阈值跟踪单元组成,诱发反应识别单元用于确定是否存在反应,阈值跟踪单元控制短声强度以跟踪阈值。反应识别基于相关方法。阈值跟踪使用顺序测试参数估计(PEST)程序完成,该程序常用于研究听觉系统的心理物理特性。根据识别器和阈值跟踪器的结果自动调整声级。每只耳朵的测试结果通常在15分钟内即可获得。自动程序的结果与ABR阈值的专家判断高度相关,并显示出良好的重测可靠性,这表明自动程序是传统测试方法的可行替代方案。