Accurate detection of speech auditory brainstem responses using a spectral feature-based ANN method
Accurate detection of speech auditory brainstem responses using a spectral feature-based ANN method
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DOI：
10.1016/j.bspc.2018.05.007
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发表时间：
2018-07-01
影响因子：
5.1
通讯作者：
Dajani, Hilmi R.
中科院分区：
文献类型：
--
作者：
Fallatah, Anwar;Dajani, Hilmi R.
言语听觉脑干反应（sABR）是一种很有前途的客观评价听功能的工具。获得sABR的主要问题是高背景噪声，特别是与一般大脑活动相关的噪声。在实践中，需要非常长的记录来检测sABR。因此，我们提出了一种新的检测方法的sABR的频谱特征提取的基础上，将减少检测时间，而不降低精度。这种方法涉及一个构造的特征频率向量馈送到人工神经网络。所提出的方法的性能进行比较，其他四种方法在文献中报道：最佳线性滤波，在线估计，互信息，基于离散小波变换和近似熵的人工神经网络。所有的方法进行了评估与记录和模拟sABR的几个数据集，从非常嘈杂的相对干净。与其他方法相比，所提出的方法在检测sABR的灵敏度、特异性和总体准确性方面表现得非常好。所需记录时间的减少有望促进这种测量技术在临床环境中的应用。(C)2018爱思唯尔有限公司版权所有
The speech auditory brainstem response (sABR) is a promising tool that can be used for objectively assessing auditory function. The main problem in obtaining the sABR is the high background noise, especially noise associated with general brain activity. In practice, a very long recording is needed to detect the sABR. We therefore propose a new detection method of the sABR based on spectral feature extraction that will reduce the detection time without reducing the accuracy. This method involves a constructed feature-frequency vector fed to an artificial neural network. The performance of the proposed method is compared to four other methods reported in the literature: optimal linear filtering, online estimator, Mutual Information, and artificial neural network based on discrete wavelet transforms and approximate entropy. All the methods were evaluated with several datasets of recorded and simulated sABRs ranging from extremely noisy to relatively clean. The proposed method performed very well in terms of sensitivity, specificity, and overall accuracy in detecting the sABR, compared with the other methods The reduction in the required recording time promises to facilitate the application of this measurement technique in clinical settings. (C) 2018 Elsevier Ltd. All rights reserved.