Reduction of stimulus artifact in somatosensory evoked potentials: Segmented versus subthreshold training

被引：6

作者：

Boudreau, BH

Englehart, KB

Chan, ADC

Parker, PA

机构：

[1] Univ New Brunswick, Dept Elect & Comp Engn, Fredericton, NB E3B 5A3, Canada

[2] Univ New Brunswick, Inst Biomed Engn, Fredericton, NB E3B 5A3, Canada

[3] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 2004年 / 51卷 / 07期

基金：

加拿大自然科学与工程研究理事会;

关键词：

adaptive filtering; evoked response; neural networks; stimulus artifact;

D O I：

10.1109/TBME.2004.827342

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

A new approach to stimulus artifact cancellation is introduced, which attempts to model the process of stimulus artifact generation. This is done by training an estimator with multiple exemplars of the stimulus artifact at levels below the threshold of evoked response stimulation. Two estimators are formulated: one using a dynamic neural. network and another using a linear estimator. The performance of these new approaches is compared to the segmented training approach, which has been previously demonstrated to be one of the most capable methods available. Performance assessment is carried out using a novel metric introduced in this paper, which focuses upon the relevant portion of the recorded waveform. The new cancellation schemes show distinct performance advantages over the segmented training approach.

引用

页码：1187 / 1195

页数：9