Paper Info
Title
Towards Automatic Artifact Rejection In Resting-State Meg Recordings: Evaluating The Performance Of The Sound Algorithm
Abstract
In this study, a new automated noise rejection algorithm, the SOurce-estimate-Utilizing Noise-Discarding algorithm (SOUND), was evaluated on magnetoencephalographic (MEG) resting-state signals in order to select its optimal configuration parameters. Different values of the epoch length and the regularization parameter lambda(0) were assessed in three scenarios with ascending noise levels. Results show that it is possible to remarkably improve the Signal-to-Noise Ratio, without overly altering the signal of interest. An optimal lambda(0) value of 0.1 was obtained. However, the epoch length should be adapted to the specific problem. In conclusion, our results suggest that the SOUND algorithm is an appropriate and useful tool to be applied in a preprocessing pipeline for MEG resting state signals.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8856587
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Noise measurement,Computer science,Noise level,Resting state fMRI,Signal-to-noise ratio,Algorithm,Preprocessor,Signal of interest,Regularization (mathematics)
Conference
2019
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
9
Name
Order
Citations
PageRank
Víctor Rodríguez-González100.68
Jesús Poza25512.29
Pablo Núñez331.80
Carlos Gómez48615.72
María García518611.96
Yoshihito Shigihara600.34
Hideyuki Hoshi700.34
Eduardo Santamaría-Vázquez800.34
Roberto Hornero960367.74