A kurtosis-based wavelet algorithm for motion artifact correction of fNIRS data

Volume: 112, Pages: 128 - 137
Published: May 1, 2015
Abstract
Movements are a major source of artifacts in functional Near-Infrared Spectroscopy (fNIRS). Several algorithms have been developed for motion artifact correction of fNIRS data, including Principal Component Analysis (PCA), targeted Principal Component Analysis (tPCA), Spline Interpolation (SI), and Wavelet Filtering (WF). WF is based on removing wavelets with coefficients deemed to be outliers based on their standardized scores, and it has...
Paper Details
Title
A kurtosis-based wavelet algorithm for motion artifact correction of fNIRS data
Published Date
May 1, 2015
Journal
Volume
112
Pages
128 - 137
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