PMID: 2487783Jan 1, 1989Paper

Respiratory waveform pattern recognition using digital techniques

Computers in Biology and Medicine
J B Korten, G G Haddad

Abstract

An algorithm for detection of ventilatory events using digital signal processing techniques is described. Start and end of inspiration of each breath are detected using a combination of first derivative peak detection and second derivative analysis for edge detection. A convolution algorithm for computation of smoothed first and second derivatives is employed. Ventilatory data obtained automatically were compared to those calculated manually. Our results show that the difference in mean values for inspiratory time, expiratory time and total respiratory cycle time are very small (less than 6%).

References

Dec 1, 1986·IEEE Transactions on Bio-medical Engineering·T GasserL Sroka

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Citations

Apr 28, 2004·Respiratory Physiology & Neurobiology·Kendall F Morris, David Gozal
Sep 24, 2013·Medical & Biological Engineering & Computing·Gonzalo C Gutiérrez-TobalRoberto Hornero
Aug 16, 2015·IEEE Transactions on Bio-medical Engineering·Gonzalo C Gutiérrez-TobalRoberto Hornero
Jan 18, 2003·Sleep Medicine Reviews·Thomas Penzel, Regina Conradt
Sep 2, 1999·Computers and Biomedical Research, an International Journal·B S Todd, D C Andrews
Jun 28, 2012·Physiological Measurement·G C Gutiérrez-TobalF del Campo
Jun 11, 1998·Journal of Applied Physiology·R ShannonB G Lindsey
Oct 24, 1998·Clinical Physiology·J Rittweger, A Pöpel

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