WIT Press


A Parallel Pattern Recognition Algorithm For Biomedical Waveform Analysis

Price

Free (open access)

Paper DOI

10.2495/ASE950291

Volume

11

Pages

9

Published

1995

Size

704 kb

Author(s)

A.N. Kastania & M.P. Bekakos

Abstract

In this work we address the problem to classify individuals into patterns of 24-hour heart rate (HR) variability, and systolic (SBP) and diastolic (DBF) blood pressure variability on the basis of up to 96 parameter values per subject, per 24-hours. Pattern recognition findings could probably lead to estimate the effect of the 24h BP variability on ventricular structure in essential hypertension. A parallel waveform pattern recognition algorithm applying measurement vector methods for the analysis of BP and HR variability is presented. 1 Introduction Blood Pressure and Heart Rate measurements derived from twenty-four hour ambulatory monitoring are of special interest in cardiological treatment. In the presence of hypertension, left ventricular hypertrophy is associated

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