Literature DB >> 10868261

Effect of adaptive motion-artifact reduction on QRS detection.

P S Hamilton1, M Curley, R Aimi.   

Abstract

Motion artifact resulting from electrode and patient movement is a significant source of noise in ECG, EEG, EMG, and impedance pneumography recording. Noise resulting from motion is particularly troublesome in ambulatory ECG recordings, such as those made during Holter monitoring or stress tests, because the bandwidth of the motion artifact overlaps with the ECG signal bandwidth. The authors investigated the effect of an adaptive motion-artifact removal algorithm on the performance of a standard QRS detector. They made four ECG recordings on each of the three subjects while manually generating artifact. Adaptive noise removal was applied to the ECG signal using a skin-stretch signal as the noise reference. Adaptive noise removal reduced the number of false QRS detections in the records from 380 to 104, for an average reduction in false detections of 72.6%. False-detection reductions for individual records ranged from 12% to 93%.

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Mesh:

Year:  2000        PMID: 10868261

Source DB:  PubMed          Journal:  Biomed Instrum Technol        ISSN: 0899-8205


  3 in total

1.  Real alerts and artifact classification in archived multi-signal vital sign monitoring data: implications for mining big data.

Authors:  Marilyn Hravnak; Lujie Chen; Artur Dubrawski; Eliezer Bose; Gilles Clermont; Michael R Pinsky
Journal:  J Clin Monit Comput       Date:  2015-10-05       Impact factor: 2.502

2.  Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Theory and Practice.

Authors:  Ramakrishna Mukkamala; Jin-Oh Hahn; Omer T Inan; Lalit K Mestha; Chang-Sei Kim; Hakan Töreyin; Survi Kyal
Journal:  IEEE Trans Biomed Eng       Date:  2015-06-05       Impact factor: 4.538

3.  A Novel Algorithm for Movement Artifact Removal in ECG Signals Acquired from Wearable Systems Applied to Horses.

Authors:  Antonio Lanata; Andrea Guidi; Paolo Baragli; Gaetano Valenza; Enzo Pasquale Scilingo
Journal:  PLoS One       Date:  2015-10-20       Impact factor: 3.240

  3 in total

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