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

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

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)213-220
Number of pages8
JournalMedical and Biological Engineering and Computing
Volume49
Issue number2
DOIs
StatePublished - Feb 1 2011

Keywords

  • Ballistocardiography
  • Cardiac output
  • Cardiovascular monitoring
  • Contractility
  • Heart failure
  • Noise identification
  • Signal processing

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications

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