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Motion artifact cancellation in NIR spectroscopy using Wiener filtering.

Meltem Izzetoglu·Ajit Devaraj·Scott Bunce·Banu Onaral
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Abstract

We present a Wiener filtering based algorithm for the elimination of motion artifacts present in Near Infrared (NIR) spectroscopy measurements. Until now, adaptive filtering was the only technique used in the noise cancellation in NIR studies. The results in this preliminary study revealed that the proposed method gives better estimates than the classical adaptive filtering approach without the need for additional sensor measurements. Moreover, this novel technique has the potential to filter out motion artifacts in functional near infrared (fNIR) signals, too.

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AlgorithmsArtifactsBrainBrain MappingDiagnosis, Computer-AssistedHead MovementsHemoglobinsHumansReproducibility of ResultsSensitivity and SpecificitySignal Processing, Computer-AssistedSpectroscopy, Near-InfraredClinical TrialJournal ArticleResearch Support, U.S. Gov't, Non-P.H.S.

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Meltem Izzetoglu, Ajit Devaraj, Scott Bunce, Banu Onaral. 2005. Motion artifact cancellation in NIR spectroscopy using Wiener filtering.. https://doi.org/10.1109/tbme.2005.845243

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