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


Scholkmann, F; Spichtig, S; Muehlemann, T; Wolf, M (2010). How to detect and reduce movement artifacts in near-infrared imaging using moving standard deviation and spline interpolation. Physiological Measurement, 31(5):649-662.

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 interpolationwas 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 ofMAs and an increase in signal quality are achieved. The effectiveness and usability of
themethod 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.

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 interpolationwas 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 ofMAs and an increase in signal quality are achieved. The effectiveness and usability of
themethod 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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Neonatology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:May 2010
Deposited On:26 May 2010 07:44
Last Modified:26 Jan 2017 08:47
Publisher:Institute of Physics Publishing
ISSN:0967-3334
Additional Information:The accepted manuscript is an author-created, un-copyedited version of an article accepted for publication in Physiological Measurement. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The definitive publisher authenticated version is available online at doi:10.1088/0967-3334/31/5/004
Publisher DOI:https://doi.org/10.1088/0967-3334/31/5/004
Official URL:http://iopscience.iop.org/0967-3334/31/5/004/pdf/0967-3334_31_5_004.pdf

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