Literature DB >> 8582723

Reduction of motion artifacts using a two-frequency impedance plethysmograph and adaptive filtering.

J Rosell1, K P Cohen, J G Webster.   

Abstract

We measured transthoracic impedance in nine presumed healthy adult subjects with a two-frequency plethysmograph at 57 kHz and 185 kHz. The measurement protocol included periods of normal breathing without motion and periods of motion without breathing. We analyzed the cross-correlation and the ratio between the signals at both frequencies for all the different maneuvers. The correlation coefficient was between 0.97 and 1 for breathing, the minimal cross-correlation (0.81) was for simulated obstructive apnea. We found that the amplitude ratio between the two-frequency signals was different for normal breathing and for motion. Based on these results, we designed and tested an adaptive filter to increase the signal-to-artifact ratio (SAR). The increase in SAR (mean +/- standard deviation) compared with the signal at 57 kHz was: 183% +/- 117% for arm movement, 133% +/- 93% for leg movement, and 34% +/- 62% for simulated obstructive apnea.

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Mesh:

Year:  1995        PMID: 8582723     DOI: 10.1109/10.464380

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

1.  A quantitative approach to measure women's sexual function using electromyography: a preliminary study of the Kegel exercise.

Authors:  Mas Sahidayana Mohktar; Fatimah Ibrahim; Nur Farahana Mohd Rozi; Juhaida Mohd Yusof; Siti Anom Ahmad; Khong Su Yen; Siti Zawiah Omar
Journal:  Med Sci Monit       Date:  2013-12-13

2.  Artefact Detection in Impedance Pneumography Signals: A Machine Learning Approach.

Authors:  Jonathan Moeyersons; John Morales; Nick Seeuws; Chris Van Hoof; Evelien Hermeling; Willemijn Groenendaal; Rik Willems; Sabine Van Huffel; Carolina Varon
Journal:  Sensors (Basel)       Date:  2021-04-08       Impact factor: 3.576

3.  Cross-Entropy Learning for Aortic Pathology Classification of Artificial Multi-Sensor Impedance Cardiography Signals.

Authors:  Tobias Spindelböck; Sascha Ranftl; Wolfgang von der Linden
Journal:  Entropy (Basel)       Date:  2021-12-10       Impact factor: 2.524

  3 in total

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