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

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 subj...

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Bibliographic Details
Published in:	Medical & biological engineering & computing Vol. 49; no. 2; pp. 213 - 220
Main Authors:	Wiard, Richard M., Inan, Omer T., Argyres, Brian, Etemadi, Mozziyar, Kovacs, Gregory T. A., Giovangrandi, Laurent
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer-Verlag 01-02-2011 Springer Nature B.V
Subjects:	Adult Algorithms Aorta Ballistocardiography - methods Bioengineering Biomedical and Life Sciences Biomedical Engineering and Bioengineering Biomedicine Cardiac output Cardiac Output - physiology Cardiovascular system Computer Applications Engineering Female Heart failure Heart Failure - diagnosis Human Physiology Humans Imaging Male Medical tests Middle Aged Motion Motion sensors Noise Original Article Radiology Recording Segments Sensors Signal processing Signal Processing, Computer-Assisted Signal to noise ratio Strain gauges Studies Ultrasonic imaging Young Adult Heart failure Ballistocardiography Contractility Signal processing Cardiac output Cardiovascular monitoring Noise identification
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Summary:	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.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0140-0118 1741-0444
DOI:	10.1007/s11517-010-0722-y