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Vojko Jazbinšek , Janko Lužnik, Zvonko Trontelj Institute of Mathematics, Physics and Mechanics

Influence of different representations of the oscillometric index on automatic determination of the systolic and diastolic blood pressures. Vojko Jazbinšek , Janko Lužnik, Zvonko Trontelj Institute of Mathematics, Physics and Mechanics Jadranska 19, 1000 Ljubljana, Slovenia

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Vojko Jazbinšek , Janko Lužnik, Zvonko Trontelj Institute of Mathematics, Physics and Mechanics

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  1. Influence of different representations of the oscillometric index on automatic determination of the systolic and diastolic blood pressures Vojko Jazbinšek, Janko Lužnik, Zvonko Trontelj Institute of Mathematics, Physics and Mechanics Jadranska 19, 1000 Ljubljana, Slovenia vojko.jazbinsek@imfm.uni-lj.si

  2. Introduction • Most of automated non-invasive blood pressure – (NIBP) devices use oscillometric technique based on some empirically derived criteria applied to the so-called oscillometric index [1], which is defined as a certain characteristic physical property of the measured arterial pressure pulses. • The recorded data in a typical NIBP device contain the arterial pressure pulses in the cuff, superimposed on the cuff deflation. • Some NIBP devices have also implanted microphone inside the cuff, which enables measurements of Korotkoff sounds [2], which are otherwise listened by a stethoscope in a conventional BP measurement in the office. • In this study we use different physical properties of recorded data to form different representations of oscillometric index. • The aim of this study is to find out how these different representations influence on systolic (SP) and diastolic (DP) pressures determined by known algorithms, such as height (HB) and slope based(SB) methods. 1 K-G. Ng, CF .Small. Survey of automated non-invasive blood pressure monitors, Journal of Clinical Engineering; 19:452-475, 1994. 2 N.C. Korotkoff. On the subject of methods of determining blood pressure. Bull. Imperial Mil. Med. Acad. (St. Petersburg), 11:365-367, 1905.

  3. Measurements • EU-project “Simulator for NIBP” • LODE (Groningen, NL) • Compressor for the cuff inflation and a pressure sensor built in a personal computer • Upper arm cuff (Accoson, UK) with implanted microphone • Simultaneous measurements with commercial automated NIBP device OSZ4 (Welch Alyn)

  4. Measured data – pressure Pressure pulses - filter[0.3-40] Hz Time derivative of pressure data Overview of data obtained with NIBP device Measured data – microphone Audible part (Korotkoff) [10-40] Hz Low frequency part [0.3-10] Hz

  5. Filtered pulses [0.3-40] Hz Time derivative of pressure data Audible part of pressure data Filtered pulses [0.3-40] Hz Time derivative of pressure data Audible part of microphone data NIBP data Oscillometric index

  6. Filtered pulses [0.3-40] Hz Time derivative of pressure data Audible part of pressure data Characterization of oscillometric index Exy

  7. Height based (HB)methoduses characteristic height ratios (SP - 0.45, DP – 0.7) Slope based (BS)methoduses maximum slope of the curve • Non-monotonic curve – constraints in SB method Algorithms for SP and DP

  8. Evaluation of NIBP devices Two standard protocols for evaluation of NIBP devices: • British Hypertension Society (BHS) – at least grade B • American Association for the Advancement of Medical Instrumentation (AAMI): • Average absolute difference: I∆p| ≤ 5 mm Hg • Standard deviation: SD ≤ 8 mm Hg

  9. Similar to BHS protocol, results were classified into grades (6) • For every SP and DP, we found classification values VSP and VDP, and calculated combined value VSP+DP(biased to the worse of the VSP and VDP) Evaluation protocol • Modified version of AAMI and BHS protocols • Like in AAMI protocol, we calculated I∆p|±SD (average absolute difference). • In addition, we have also calculated ∆p ±SD (average difference), • linear regression correlation coefficient r, • and maximum difference∆pm

  10. Filtered pulses [0.3-40] Hz Time derivative of pressure data Audible part of pressure data Height based method (HB) - Average height ratios HSxy in HDxy for 92 recordings

  11. Results for height based method (HB) Type of envelope: min-max (p) min-cog (c) cog-max (d) • Type of data: • p – • pressure pulses • (92 recordings) • b) d – derivatives • (92 recordings) • c) k - Korotkoff • (32 recordings)

  12. Type of envelope: min-max (p) min-cog (c) cog-max (d) Tip of data: a) p – pressure pulsesSB with constraints (92 recordings) b) p – pressure pulses SB without constraints (92 recordings) c) d - derivative SB with constraints (92 recordings) c) k - Korotkoff SB with constraints (32 meritev)

  13. Filtered pulses [0.3-40] Hz Filtered pulses without constraints Audible part of pressure data Summary of evaluation results for SB method

  14. Filtered pulses [0.3-40] Hz Time derivative of pressure data Audible part of pressure data Summary of evaluation results for HB method

  15. Comparison of HB and SB evaluation results for Epp (peak-to-peak pressure pulses) envelopes Linear regression Bland-Altman plot HB SB

  16. Conclusions • Study of 92 recordings performed on 23 healthy volunteers. • Evaluation of two known algorithms, height based (HB) and slope based (SB) methods, applied to different representations of oscillometric index Exy. • We used modified combination of standard AAMI in BHS evaluation protocols. • We found that HB method can be applied toenvelopes that exhibit a rapid change of amplitude near DP and SP. • Same behaviour is needed also for SB method, but additional constraints should be applied due to non-monotonic shape of envelopes (especially for SP). • For both methods we got best results for oscillometric index formed from peak-to-peak values of pressure pulses.

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