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Authors: Sérgio Okida 1 ; Pedro Giassi Júnior 2 ; João Fernando Refosco Baggio 2 ; Raimes Moraes 2 ; Maurício Gonçalves de Oliveira 2 and Gastão Fernandes Duval Neto 3

Affiliations: 1 Federal University of Technology of Paraná and Federal University of Santa Catarina, Brazil ; 2 Federal University of Santa Catarina, Brazil ; 3 Federal University of Pelotas, Brazil

ISBN: 978-989-8425-89-8

Keyword(s): Heart Rate Variability, Autonomic Nervous System, System Identification, Autoregressive Moving Average Model, Pulse Wave Transit Time.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Cardiovascular Signals ; Computer Vision, Visualization and Computer Graphics ; Informatics in Control, Automation and Robotics ; Medical Image Detection, Acquisition, Analysis and Processing ; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics ; Signal Processing, Sensors, Systems Modeling and Control ; Time and Frequency Response ; Time-Frequency Analysis

Abstract: This work shows that it is possible to model the heart rate autonomic control from samples of ECG, PPG and respiratory flow waveform (RFW). Usually, such modelling is carried out with physiological signals that are more difficult to acquire during the clinical exams: ECG, arterial blood pressure and instantaneous lung volume. In this work, the ECG, PPG and RFW were recorded with a portable system from volunteers at two different postures: supine and standing. The ECG, PPG and RFW were processed off line in order to obtain the RR, the inverse of the pulse wave transit time (IPWTT) and the RFW series. These series were used as input for ARMA models and the obtained results were compared to the ones available in the literature. The qualitative and quantitative comparisons of the results reveal very similar performance.

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Paper citation in several formats:
Okida, S.; Okida, S.; Giassi Júnior, P.; Fernando Refosco Baggio, J.; Moraes, R.; Gonçalves de Oliveira, M. and Duval Neto, G. (2012). NONINVASIVE CARDIOVASCULAR SYSTEM IDENTIFICATION USING PULSE WAVE TRANSIT TIME.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012) ISBN 978-989-8425-89-8, pages 232-237. DOI: 10.5220/0003775402320237

@conference{biosignals12,
author={Sérgio Okida. and Sérgio Okida. and Pedro Giassi Júnior. and João Fernando Refosco Baggio. and Raimes Moraes. and Maurício Gon\c{C}alves de Oliveira. and Gastão Fernandes Duval Neto.},
title={NONINVASIVE CARDIOVASCULAR SYSTEM IDENTIFICATION USING PULSE WAVE TRANSIT TIME},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)},
year={2012},
pages={232-237},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003775402320237},
isbn={978-989-8425-89-8},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)
TI - NONINVASIVE CARDIOVASCULAR SYSTEM IDENTIFICATION USING PULSE WAVE TRANSIT TIME
SN - 978-989-8425-89-8
AU - Okida, S.
AU - Okida, S.
AU - Giassi Júnior, P.
AU - Fernando Refosco Baggio, J.
AU - Moraes, R.
AU - Gonçalves de Oliveira, M.
AU - Duval Neto, G.
PY - 2012
SP - 232
EP - 237
DO - 10.5220/0003775402320237

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