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Authors: Giorgio Biagetti ; Paolo Crippa ; Laura Falaschetti ; Simone Orcioni and Claudio Turchetti

Affiliation: Università Politecnica delle Marche, Italy

Keyword(s): Photoplethysmography, PPG, Motion Artifact Reduction, Heart Rate, Bayesian Classification, Identification, GMM, Expectation Maximization, Karhunen-Loève Transform.

Related Ontology Subjects/Areas/Topics: Applications ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Classification ; Computer Vision, Visualization and Computer Graphics ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems ; Signal Processing ; Software Engineering ; Theory and Methods

Abstract: Accurate heart rate (HR) estimation from photoplethysmography (PPG) recorded from subjects’ wrist when the subjects are performing various physical exercises is a challenging problem. This paper presents a framework that combines a robust algorithm capable of estimating HR from PPG signal with subjects performing a single exercise and a physical exercise identification algorithm capable of recognizing the exercise the subject is performing. Experimental results on subjects performing two different exercises show that an improvement of about 50% in the accuracy of HR estimation is achieved with the proposed approach.

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Paper citation in several formats:
Biagetti, G.; Crippa, P.; Falaschetti, L.; Orcioni, S. and Turchetti, C. (2016). Motion Artifact Reduction in Photoplethysmography using Bayesian Classification for Physical Exercise Identification. In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - ICPRAM, ISBN 978-989-758-173-1; ISSN 2184-4313, pages 467-474. DOI: 10.5220/0005755304670474

@conference{icpram16,
author={Giorgio Biagetti. and Paolo Crippa. and Laura Falaschetti. and Simone Orcioni. and Claudio Turchetti.},
title={Motion Artifact Reduction in Photoplethysmography using Bayesian Classification for Physical Exercise Identification},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - ICPRAM,},
year={2016},
pages={467-474},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005755304670474},
isbn={978-989-758-173-1},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - ICPRAM,
TI - Motion Artifact Reduction in Photoplethysmography using Bayesian Classification for Physical Exercise Identification
SN - 978-989-758-173-1
IS - 2184-4313
AU - Biagetti, G.
AU - Crippa, P.
AU - Falaschetti, L.
AU - Orcioni, S.
AU - Turchetti, C.
PY - 2016
SP - 467
EP - 474
DO - 10.5220/0005755304670474