OSCILLOMETRIC NONINVASIVE BLOOD PRESSURE MEASUREMENTS: THE INFLUENCE OF EXTERNAL ARTIFACTS V. Jazbinsek, J. Luznik, S. Mieke* and Z. Trontelj Institute.

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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

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.

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

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

Measurement  Measured data Arterial pressure pulses, called oscillometric pulses, superimposed on the cuff pressure deflation.  Filtered pulses Deflation can be removed from data by the digital high pass filtering. Subtraction of negative envelope (curve defined by blue dots) leads to  Oscillometric pulses The 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.

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) Data presentation

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

Typical shapes of high frequency artifacts Averaging of tapping artifacts

Projection into normalized heart beat view – reference waveform

Subtraction of reference waveform a)3 rd recording b)Subtracted reference using waveform optimization (WO) c)Subtracted reference using single beat optimization (SBO)

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

Typical shapes of low frequency artifacts

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

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.