Parametric modeling of somatosensory evoked potentials using discrete cosine transform
Parametric modeling of somatosensory evoked potentials using discrete cosine transform
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DOI：
10.1109/10.959331
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发表时间：
2001-11-01
影响因子：
4.6
通讯作者：
Shibasaki, H
中科院分区：
文献类型：
--
作者：
Bai, O;Nakamura, M;Shibasaki, H
本文介绍了一种识别体感诱发电位的参数化方法。通过在离散余弦变换（DCT）域中对SEP进行零极点建模来进行识别。结果表明，双相信号的DCT系数可以用具有共轭极点对的二阶传递函数充分近似。平均SEP信号由多个二阶传递函数之和建模，并在DCT域中使用最小二乘法估计适当的零点和极点。估计结果表明，模型输出在定性和定量方面与原始SEPs非常一致。与一般的时域外输入自回归模型相比，DCT域模型以很低的阶数获得了很高的拟合优度。所提出的方法的应用是可能的，在临床实践中的特征提取，噪声消除和单个组件分解的SEP以及其他诱发电位。
This paper introduces a parametric method for identifying the somatosensory evoked potentials (SEPs). The identification was carried out by using pole-zero modeling of the SEPs in the discrete cosine transform (DCT) domain. It was found that the DCT coefficients of a monophasic signal can be sufficiently approximated by a second-order transfer function with a conjugate pole pair. The averaged SEP signal was modeled by the sum of several second-order transfer functions with appropriate zeros and poles estimated using the least square method in the DCT domain. Results of the estimation demonstrated that the model output was in an excellent agreement with the raw SEPs both qualitatively and quantitatively. Comparing with the common autoregressive model with exogenous input modeling in the time domain, the DCT domain modeling achieves a high goodness of fitting with a very low model order. Applications of the proposed method are possible in clinical practice for feature extraction, noise cancellation and individual component decomposition of the SEPs as well as other evoked potentials.