Medical & Biological Engineering & Computing

, Volume 49, Issue 2, pp 213–220

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

Authors

    • Department of BioengineeringStanford University
  • Omer T. Inan
    • Department of Electrical EngineeringStanford University
  • Brian Argyres
    • Department of Mechanical EngineeringStanford University
  • Mozziyar Etemadi
    • Division of Pediatric SurgeryUniversity of California, San Francisco
  • Gregory T. A. Kovacs
    • Department of Electrical EngineeringStanford University
    • Department of MedicineStanford University
  • Laurent Giovangrandi
    • Department of Electrical EngineeringStanford University
Original Article

DOI: 10.1007/s11517-010-0722-y

Cite this article as:
Wiard, R.M., Inan, O.T., Argyres, B. et al. Med Biol Eng Comput (2011) 49: 213. doi:10.1007/s11517-010-0722-y

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.

Keywords

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

Copyright information

© International Federation for Medical and Biological Engineering 2010