K-means clustering method for auditory evoked potentials selection
K-means clustering method for auditory evoked potentials selection
复制标题
DOI：
10.1007/bf02348081
复制
发表时间：
2003-07-01
影响因子：
3.2
通讯作者：
Le Bouquin-Jeannes, R
中科院分区：
文献类型：
--
作者：
Gourevitch, B;Le Bouquin-Jeannes, R
表面听觉诱发电位一般使用32个、或128个电极的耳机记录，但在头皮表面的反应质量是相当不均匀的。在某些情况下，例如分析在射频领域中记录的听觉诱发电位，信号质量是必不可少的，似乎只考虑有限数量的电极是恰当的。因此，在分析受射频场影响的信号之前，有必要考虑选择听觉活动较强的通道的初步步骤。这一步骤通常通过人类视觉选择来实现，可能需要相当长的时间。本文提出了一种简单的k-均值聚类方法，用于自动选择重要频道，并将结果与传统的选择方法进行了比较。该方法检测到的通道与视觉选择(由5个人进行)的符合率为86.5%，并给出了相同的最终选择(在自动情况下仅额外的两个电极)。此外，这种自动选择所需的时间比视觉选择少100倍，也避免了人类的变异性。
Surface auditory evoked potentials are generally recorded using a headset of 32, 64 or 128 electrodes, but the quality of the responses is quite heterogeneous on the scalp surface. In some contexts, such as the analysis of auditory evoked potentials recorded in radio-frequency fields, the signal quality is essential, and it appears pertinent to consider only a limited number of electrodes. Therefore, before analysing signals influenced by radio-frequency fields, it is necessary to consider the preliminary step of selecting the channels where auditory activity is strong. This step is often realised by human visual selection and can take a considerable time. In this paper, a simple k-means clustering method is proposed, to select automatically the important channels, and the results are compared with traditional methods of selection. The method detected channels that showed a concordance rate of 86.5% with the visual selection (performed by five individuals) and gave the same final selection (only two extra electrodes in the automatic case). Moreover, the time needed for this automatic selection was 100 times less than that for the visual selection, and also human variability was avoided.