Elberling C, Wahlgreen O
Scand Audiol. 1985;14(2):89-96. doi: 10.3109/01050398509045928.
The present paper describes a new method to estimate the auditory brainstem response when the electrical activity from the recording electrodes displays non-stationarity, i.e. varies between low and high levels. The method is based on a statistical approach called Bayesian inference and weights the individual components (here blocks of 250 sweeps) inversely proportional to the level of the noise activity during the recording. Fifty sets of data from 10 consecutive patients obtained during stimulation at high intensity are used to evaluate the difference between the classic averaging and the present method which is called Bayes estimation. In approximately 30% of the cases, a significant all-over improvement is obtained by the new method. The classic averaging technique would here require 50% more sweeps to be taken to obtain the same precision of the ABR estimate, on average. Also the latency and amplitude parameters of the Jv wave complex are evaluated and it is shown that the parameter variance decreases by a factor of approximately 2 by using the Bayes estimation. The new technique is compared with a similar technique recently presented by Hoke et al. (1984) and the differences and similarities are discussed.
本文描述了一种新方法,用于在记录电极的电活动显示非平稳性(即在低水平和高水平之间变化)时估计听觉脑干反应。该方法基于一种称为贝叶斯推理的统计方法,并根据记录期间噪声活动的水平,对各个分量(此处为250次扫描的块)进行反比加权。使用在高强度刺激期间从10名连续患者获得的50组数据,来评估经典平均法与称为贝叶斯估计的当前方法之间的差异。在大约30%的病例中,新方法取得了显著的全面改善。在此,经典平均技术平均需要多采集50%的扫描次数才能获得相同精度的听觉脑干反应估计值。还对Jv波复合体的潜伏期和振幅参数进行了评估,结果表明,使用贝叶斯估计,参数方差减少了约2倍。将新技术与霍克等人(1984年)最近提出的类似技术进行了比较,并讨论了它们的异同。