Abstract
As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson’s correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson’s correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data.
Highlights
As the applications broaden to di®erent age and disease groups, motion artifacts in the Near-Infrared Spectroscopy (NIRS) signal due to subject movements become an important challenge
We introduce a new approach for motion artifact correction: targeted principle component analysis which is a modied version of regular PCA
The signal obtained is highly contaminated by motion artifacts as opposed to channels of data acquired with the collodion- ̄xedber probe where each optode is tightly glued on the head of the subject
Summary
As the applications broaden to di®erent age and disease groups, motion artifacts in the NIRS signal due to subject movements become an important challenge. The second approach involves various post-processing motion artifact correction methods. These methods either require an external measurement of the movements that is incorporated into an adaptiveltering algorithm[15] or they use spatial and/or temporal features of the NIRS signal itself, as is the case for wavelet-basedltering,[16] principle component analysis (PCA),[17] spline interpolation[18] or Kalmanltering.[19] Comparison of the methods has shown that the most e®ective methods for motion artifact correction are wavelet-basedltering and spline interpolation.[20,21]. We introduce a new approach for motion artifact correction: targeted principle component analysis (tPCA) which is a modied version of regular PCA. We compare the motion artifact corrected NIRS signal obtained with a standard Velcro NIRS probe vs a more stable collodion- ̄xed NIRS probe, to assess the e®ectiveness of post-processing to correct motion artifacts vs the more time consuming approach of creating a NIRS probe less susceptible to motion artifacts
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
