Fast Extraction of Somatosensory Evoked Potential using RLS Adaptive Filter Algorithms

被引：0

作者：

Ren, Zhaoli ^{[1
]}

Zou, Yuexian ^{[1
]}

Zhang, Zhiguo ^{[2
]}

Hu, Yong ^{[2
]}

机构：

[1] Peking Univ, Shenzhen Grad Sch, Adv Digital Signal Proc Lab, Shenzhen, Guangdong, Peoples R China

[2] Univ Hong Kong, Dept Orthopaed & Traumatol, Hong Kong, Peoples R China

来源：

PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9 | 2009年

关键词：

SEP; Adaptive Filter; RLS-ANC; LMS-ANC;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper evaluates the efficacy of the recursive least squares (RLS) in adaptive noise canceller (RLS-ANC) for fast extraction of somatosensory evoked potentials (SEPs). The RLS-ANC method was verified by simulation of electroencephalography (EEG) and Gaussian noise contaminated SEP signals at different signal-to-noise ratios (SNRs). RLS was found to converge faster than the least mean squares (LMS) algorithm in ANC, i.e. SEP extraction by RLS-ANC required fewer trials than LMS-ANC. Experimental results showed that RLS-ANC with less than 50 trials could provide similar performance in SEP extraction to those extracted by the conventional ensemble averaging with 500 trials even at SNR of - 20dB.

引用

页码：4444 / +

页数：2