Targeted principle component analysis:A new motion artifact correction approach for near-infrared spectroscopy

As near-infrared spectroscopy(NIRS)broadens its application area to diferent age and diseasegroups,motion artifacts in the NIRS signal due to subject movement is becoming an importantchallenge.Motion artifacts generally produce signal fiuctuations that are larger than physio-logical NIRS signals,thus it is cruciai to corect for them before obtaining an cstimate ofstimulusevoked hemodynamic responses.,There are various methods for correction such as principlecomponent analy sis(P CA),wavelet-based filt ering and spline int erpolation.Here,we introduce anew approach to motion artifact correction,targeted principle component analysis(PCA),which incorporates a PCA filter only on the segments of data identified as motion artifacts.Itis expected that this will overcome the issues of filtering desired signals that plagues standardPCA fitering of entire data sets.We compared the new approach with the most efiective motionartifact correction algorithms on a set of data acquired simultaneously with a collodion-fixedprobe(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 responsefunction(HRF)as compared to wavelet-based fltering and spline interpolation for the Velcroprobe.It resulis in a significant reduction in mean-squauared'error(MSE)and significant en-hancement in Pearson's correlation coeficient to the true HRF,The collodion-fixed fiber probewith no motion correction performed better than the Velcro probe corrected for motion artifactsin 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.I the use of a collodion-fixed probe is notfeasible,then we suggest the use of tP CA in the processing of motion artifact contaminated data.