Nothing Special   »   [go: up one dir, main page]
loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Francesco Rundo 1 ; Alessandro Ortis 2 ; Sebastiano Battiato 2 and Sabrina Conoci 1

Affiliations: 1 STMicroelectronics, ADG Group – Central R&D, Str. Primosole, 50, 95121 Catania CT and Italy ; 2 Dipartimento di Matematica e Informatica, Università Degli Studi di Catania, Viale A. Doria 6, 95125 - Catania and Italy

Keyword(s): Blood Pressure Estimation, PPG, ECG.

Related Ontology Subjects/Areas/Topics: Biomedical Applications ; Multidimensional Signal Processing ; Multimedia ; Multimedia Signal Processing ; Multimedia Systems and Applications ; Multimodal Signal Processing ; Telecommunications

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 65.254.225.175

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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 - SIGMAP; ISBN 978-989-758-378-0; ISSN 2184-3236, SciTePress, pages 321-325. DOI: 10.5220/0007909403210325

@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 - SIGMAP},
year={2019},
pages={321-325},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007909403210325},
isbn={978-989-758-378-0},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - SIGMAP
TI - Advanced Multi-neural System for Cuff-less Blood Pressure Estimation through Nonlinear HC-features
SN - 978-989-758-378-0
IS - 2184-3236
AU - Rundo, F.
AU - Ortis, A.
AU - Battiato, S.
AU - Conoci, S.
PY - 2019
SP - 321
EP - 325
DO - 10.5220/0007909403210325
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic

<style> #socialicons>a span { top: 0px; left: -100%; -webkit-transition: all 0.3s ease; -moz-transition: all 0.3s ease-in-out; -o-transition: all 0.3s ease-in-out; -ms-transition: all 0.3s ease-in-out; transition: all 0.3s ease-in-out;} #socialicons>ahover div{left: 0px;} </style>