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OSCILLOMETRIC NONINVASIVE BLOOD PRESSURE MEASUREMENTS: THE INFLUENCE OF EXTERNAL ARTIFACTS

OSCILLOMETRIC NONINVASIVE BLOOD PRESSURE MEASUREMENTS: THE INFLUENCE OF EXTERNAL ARTIFACTS. V. Jazbinsek, J. Luznik, S. Mieke * and Z. Trontelj Institute of Mathematics, Physics and Mechanics, University of Ljubljana, Ljubljana, Slovenia

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OSCILLOMETRIC NONINVASIVE BLOOD PRESSURE MEASUREMENTS: THE INFLUENCE OF EXTERNAL ARTIFACTS

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  1. OSCILLOMETRIC NONINVASIVE BLOOD PRESSURE MEASUREMENTS: THE INFLUENCE OF EXTERNAL ARTIFACTS V. Jazbinsek, J. Luznik, S. Mieke* and Z. Trontelj Institute of Mathematics, Physics and Mechanics, University of Ljubljana, Ljubljana, Slovenia *Physikalisch-Technische Bundesanstalt, Berlin, Germany

  2. Introduction • Non-invasive blood pressure (NIBP) measuring devices are based on recording the arterial pressure pulsations in an inflated cuff wrapped around a limb during the cuff pressure deflation. • The recorded NIBP data contains the pressure pulses in the cuff, called oscillometric pulses, superimposed on the cuff pressure deflation.

  3. Objective • to separate the deflation and external artifacts from the pressure pulses and to obtain the typical shapes of pressures changes in the cuff due to those artifacts

  4. Measurements • EU-project “Simulator for NIBP” • Compressor for the cuff inflation and a sensor for pressure detection, built in a PC(LODE, NL) • 25 healthy volunteers took part in this research

  5. Measurement • Measured dataArterial pressure pulses, called oscillometric pulses, superimposed on the cuff pressure deflation. • Filtered pulsesDeflation can be removed from data by the digital high pass filtering. Subtraction of negative envelope (curve defined by blue dots) leads to • Oscillometric pulsesThe waveform describing the pulse amplitudes (red dots) as a function of the cuff pressure is a base for automated determination of the systolic and diastolic pressures.

  6. Data presentation • Segmentation of data (red) into pulses (blue vert. lines) • The deflation signal is calculated by the interpolation of data between subsequent segment borders (green) • Subtraction of deflation from the measured data to obtain only pulses with positive deflections (oscillometric pulses - black)

  7. Extraction of tapping artifact Mesurements: tapping on the cuff with a plastic tube every 2 s Segmentation of artefact was obtained from filtered data (band pass 2.5-250 HZ) by selecting 0.7 s time interval around the artefact peak.

  8. Typical shapes ofhigh frequency artifacts Averaging of tapping artifacts

  9. Projection into normalized heart beat view – reference waveform

  10. Subtraction of reference waveform • 3rd recording • Subtracted reference using waveform optimization (WO) • Subtracted reference using single beat optimization (SBO)

  11. Extraction of fist closing artifact Mesurements:fist closing every 5 s

  12. Typical shapes of low frequency artifacts

  13. Conclusion I • High frequency artifacts (tapping, vibrations) can be exctracted by applying digital fitering

  14. Conclusion II Low frequency artifacts (moving) extraction require: • Transformation into heartbeat view to obtain the reference signal. • Reference can be applied as a template to extract a normal oscillometric waveform used for automated determination of systolic and diastolic pressures. • Subtraction of normalized oscillometric waveform from contaminated data. • Averaging of extracted artifacts to obtain typical shape.

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