Castañeda-Villa N, James C J
ISVR, University of Southampton, SO171BJ, UK.
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:6224-7. doi: 10.1109/IEMBS.2007.4353777.
Multi-channel Auditory Evoked Potentials (AEPs) are a useful methodology for evaluating the auditory performance of children with Cochlear Implants (CIs). These recordings are generally contaminated, not only with well known physiological artifacts (blinking, muscle) and line noise etc., but also by CI artifact. The CI induces an artifact in the recording at the electrodes in the temporal lobe area (where it is implanted) when specific tones are presented, this artifact in particular makes the detection and analysis of AEPs much more challenging. This paper evaluates the convenience of using Blind Source Separation (BSS) and Independent Component Analysis (ICA) in order to identify the AEPs from ongoing recordings and to isolate the artifact when testing a child with a CI. We propose a new procedure to elicit an objective differentiation between the independent components (ICs) related to the AEPs and CI artifact; two concepts are fundamental in this procedure Mutual Information (MI) and Clustering. Finally, the variability of three BSS/ICA algorithms is assessed; in order to determine which one is more convenient to isolate the respective ICs of interest. Temporal decorrelation based ICA showed the least change in the estimation of both the AEPs and the CI artifact; this has allowed for considerable autonomy in the construction of relevant, consistent clusters.
多通道听觉诱发电位（AEPs）是评估人工耳蜗（CI）植入儿童听觉表现的一种有用方法。这些记录通常受到污染，不仅有众所周知的生理伪迹（眨眼、肌肉活动）和电源噪声等，还受到CI伪迹的影响。当呈现特定音调时，CI会在颞叶区域（植入部位）的电极记录中诱发伪迹，这种伪迹尤其使得AEPs的检测和分析更具挑战性。本文评估了使用盲源分离（BSS）和独立成分分析（ICA）从连续记录中识别AEPs并在测试CI植入儿童时分离伪迹的便利性。我们提出了一种新的程序，以客观地区分与AEPs和CI伪迹相关的独立成分（ICs）；在此程序中有两个基本概念，即互信息（MI）和聚类。最后，评估了三种BSS/ICA算法的可变性，以确定哪一种算法在分离各自感兴趣的ICs时更方便。基于时间去相关的ICA在AEPs和CI伪迹估计中显示出最小的变化；这使得在构建相关、一致的聚类时具有相当大的自主性。
