4.5 Article

B3X: a novel efficient algorithm for accurate automated auscultatory blood pressure estimation

期刊

PHYSIOLOGICAL MEASUREMENT
卷 44, 期 9, 页码 -

出版社

IOP Publishing Ltd
DOI: 10.1088/1361-6579/acf643

关键词

blood pressure measurement; non-invasive blood pressure; Korotkoff sounds; cross-correlation; automated measurement

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The study proposes a relatively simple methodology for blood pressure measurement by processing Korotkoff sounds recordings. The proposed approach achieves good performance and low computational burden compared to other algorithms. The results of this study support the implementation of this method into clinical blood pressure monitoring devices.
Objective. The auscultatory technique is still considered the most accurate method for non-invasive blood pressure (NIBP) measurement, although its reliability depends on operator's skills. Various methods for automated Korotkoff sounds analysis have been proposed for reliable estimation of systolic (SBP) and diastolic (DBP) blood pressures. To this aim, very complex methodologies have been presented, including some based on artificial intelligence (AI). This study proposes a relatively simple methodology, named (BX)-X-3, to estimate SBP and DBP by processing Korotkoff sounds recordings acquired during an auscultatory NIBP measurement. Approach. The beat-by-beat change in morphology of adjacent Korotkoff sounds is evaluated via their cross-correlation. The time series of the beat-by-beat cross-correlation and its first derivative are analyzed to locate the timings of SBP and DBP values. Extensive tests were performed on a public database of 350 annotated measurements, and the performance was evaluated according to the BHS, AAMI/ANSI, and International Organization for Standardization (ISO) quality standards. Main results. The proposed approach achieved 'A' scores for SBP and DBP in the BHS grading system, and passed the quality tests of AAMI/ANSI and ISO standards. The (BX)-X-3 algorithm outperformed two well-established algorithms for oscillometric NIBP measurement in both SBP and DBP estimation. It also outperformed four AI-based algorithms in DBP estimation, while providing comparable performance for SBP, at the cost of a much lower computational burden. The full code of the (BX)-X-3 algorithm is provided in a public repository. Significance. The very good performances ensured by the proposed (BX)-X-3 algorithm, at a low computational cost and without the need for parameter training, support its direct implementation into clinical blood pressure (BP) monitoring devices. The results of this study pave the way for solving/overcoming the trade-off between the accuracy of the auscultatory technique and the objectivity of oscillatory measurements, by bringing an automated auscultatory BP measurement method in clinical practice.

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