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

IEEE Transactions on Bio-medical Engineering
Brigitte H BoudreauPhilip A Parker

Abstract

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.

References

Feb 1, 1982·IEEE Transactions on Bio-medical Engineering·K C McGillB Widrow
May 1, 1995·Medical & Biological Engineering & Computing·S A Harrison, D F Lovely
May 1, 1997·Medical & Biological Engineering & Computing·R N ScottP A Parker
Feb 25, 1998·IEEE Transactions on Bio-medical Engineering·V ParsaR N Scott
Apr 1, 2000·IEEE Transactions on Bio-medical Engineering·R GrieveK Englehart

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Citations

Oct 11, 2013·IEEE Transactions on Biomedical Circuits and Systems·Kanokwan LimnusonPedram Mohseni
Jan 17, 2019·International Journal of Neural Systems·Yurong LiYuan Yang

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