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Authors: Daniel Malafaia ; José Vieira and Ana Tomé

Affiliation: Universidade de Aveiro, Portugal

ISBN: 978-989-758-069-7

Keyword(s): Signal Detection, Cyclostationarity, Bio-radar, Software Defined Radio, Cognitive Radar.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Detection and Identification ; Medical Image Detection, Acquisition, Analysis and Processing

Abstract: In this paper we present a continuous wave radar created using a software defined radio platform that uses doppler effect to measure the heart-rate and breathing. The measurements are evaluated using a classic energy detection method and a cyclic spectrum estimation technique, then the two methods are compared. The results show that by taking advantaging of the cyclic autocorrelation of the bio-signals we can get better detection than the usual energy detection.

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Paper citation in several formats:
Malafaia, D.; Vieira, J. and Tomé, A. (2015). Improving Performance of Bio-radars for Remote Heartbeat and Breathing Detection by using Cyclostationary Features.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015) ISBN 978-989-758-069-7, pages 344-349. DOI: 10.5220/0005287603440349

@conference{biosignals15,
author={Daniel Malafaia. and José Vieira. and Ana Tomé.},
title={Improving Performance of Bio-radars for Remote Heartbeat and Breathing Detection by using Cyclostationary Features},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)},
year={2015},
pages={344-349},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005287603440349},
isbn={978-989-758-069-7},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)
TI - Improving Performance of Bio-radars for Remote Heartbeat and Breathing Detection by using Cyclostationary Features
SN - 978-989-758-069-7
AU - Malafaia, D.
AU - Vieira, J.
AU - Tomé, A.
PY - 2015
SP - 344
EP - 349
DO - 10.5220/0005287603440349

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