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Physiol Meas. 2010 May;31(5):649-62. doi: 10.1088/0967-3334/31/5/004. Epub 2010 Mar 22.

How to detect and reduce movement artifacts in near-infrared imaging using moving standard deviation and spline interpolation.

Author information

1
Biomedical Optics Research Laboratory (BORL), Clinic of Neonatology, University Hospital Zurich, 8091 Zurich, Switzerland. Felix.Scholkmann@usz.ch

Abstract

Near-infrared imaging (NIRI) is a neuroimaging technique which enables us to non-invasively measure hemodynamic changes in the human brain. Since the technique is very sensitive, the movement of a subject can cause movement artifacts (MAs), which affect the signal quality and results to a high degree. No general method is yet available to reduce these MAs effectively. The aim was to develop a new MA reduction method. A method based on moving standard deviation and spline interpolation was developed. It enables the semi-automatic detection and reduction of MAs in the data. It was validated using simulated and real NIRI signals. The results show that a significant reduction of MAs and an increase in signal quality are achieved. The effectiveness and usability of the method is demonstrated by the improved detection of evoked hemodynamic responses. The present method can not only be used in the postprocessing of NIRI signals but also for other kinds of data containing artifacts, for example ECG or EEG signals.

PMID:
20308772
DOI:
10.1088/0967-3334/31/5/004
[Indexed for MEDLINE]

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