Advanced Multi-neural System for Cuff-less Blood Pressure Estimation through Nonlinear HC-features

Francesco Rundo, Alessandro Ortis, Sebastiano Battiato, Sabrina Conoci

Abstract

Blood Pressure (BP) is one of the most important physiological indicator that can provide useful information in the medical field. BP is usually measured by a sphygmomanometer device, which is composed by a cuff and a mechanical manometer. In this paper, a novel algorithmic approach to accurately estimate both systolic and diastolic blood pressure is presented. This algorithm exploits the PhotoPlethysmoGraphy (PPG) signal pattern acquired by non-invasive and cuff-less Physio-Probe (PP) silicon-based SiPM device. The PPG data are then processed with ad-hoc bio-inspired mathematical model which estimates both systolic and diastolic pressure values. We compared our results with those measured using a classical sphygmomanometer device and encouraging results of about 97% accuracy were achieved.

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Paper Citation


in Harvard Style

Rundo F., Ortis A., Battiato S. and Conoci S. (2019). Advanced Multi-neural System for Cuff-less Blood Pressure Estimation through Nonlinear HC-features.In Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP, ISBN 978-989-758-378-0, pages 321-325. DOI: 10.5220/0007909403210325


in Bibtex Style

@conference{sigmap19,
author={Francesco Rundo and Alessandro Ortis and Sebastiano Battiato and Sabrina Conoci},
title={Advanced Multi-neural System for Cuff-less Blood Pressure Estimation through Nonlinear HC-features},
booktitle={Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP,},
year={2019},
pages={321-325},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007909403210325},
isbn={978-989-758-378-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP,
TI - Advanced Multi-neural System for Cuff-less Blood Pressure Estimation through Nonlinear HC-features
SN - 978-989-758-378-0
AU - Rundo F.
AU - Ortis A.
AU - Battiato S.
AU - Conoci S.
PY - 2019
SP - 321
EP - 325
DO - 10.5220/0007909403210325