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Erschienen in: Medical & Biological Engineering & Computing 2/2011

01.02.2011 | Original Article

Automatic detection of motion artifacts in the ballistocardiogram measured on a modified bathroom scale

verfasst von: Richard M. Wiard, Omer T. Inan, Brian Argyres, Mozziyar Etemadi, Gregory T. A. Kovacs, Laurent Giovangrandi

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 2/2011

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Abstract

Ballistocardiography (BCG) is a non-invasive technique used to measure the ejection force of blood into the aorta which can be used to estimate cardiac output and contractility change. In this work, a noise sensor was embedded in a BCG measurement system to detect excessive motion from standing subjects. For nine healthy subjects, the cross-correlation of the motion signal to the BCG noise—estimated using a simultaneously acquired electrocardiogram and statistics of the BCG signal—was found to be 0.94 and 0.87, during periods of standing still and with induced motion artifacts, respectively. In a separate study, where 35 recordings were taken from seven subjects, a threshold-based algorithm was used to flag motion-corrupted segments of the BCG signal using only the auxiliary motion sensor. Removing these flagged segments enhanced the BCG signal-to-noise ratio (SNR) by an average of 14 dB (P < 0.001). This integrated motion-sensing technique addresses a gap in methods available to identify and remove noise in standing BCG recordings due to movement, in a practical manner that does not require user intervention or obtrusive sensing.

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Metadaten
Titel
Automatic detection of motion artifacts in the ballistocardiogram measured on a modified bathroom scale
verfasst von
Richard M. Wiard
Omer T. Inan
Brian Argyres
Mozziyar Etemadi
Gregory T. A. Kovacs
Laurent Giovangrandi
Publikationsdatum
01.02.2011
Verlag
Springer-Verlag
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 2/2011
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-010-0722-y

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