Artifact Detection of Wrist Photoplethysmograph Signals

Kaat Vandecasteele, Jesús Lázaro, Evy Cleeren, Kasper Claes, Wim Van Paesschen, Sabine Van Huffel, Borbála Hunyadi

Abstract

There is a growing interest in monitoring of vital signs through wearable devices, such as heart rate (HR). A comfortable and non-invasive technique to measure the HR is pulse photoplethysmography (PPG) with the use of a smartwatch. This watch records also triaxial accelerometry (ACM). However, it is well known that motion and noise artifacts (MNA) are present. A MNA detection method, which classifies into a clean or MNA segment, is trained and tested on a dataset of 17 patients, each with a recording duration of 24 hours. PPG-and ACM-derived features are extracted and classified with a LS-SVM classifier. A sensitivity and specificity of respectively 85.50 % and 92.36 % are obtained. For this dataset, the ACM features do not improve the performance, suggesting that ACM recording could be avoided from the point of view for detecting MNA in PPG signals during daily life.

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Paper Citation


in Harvard Style

Vandecasteele K., Lázaro J., Cleeren E., Claes K., Van Paesschen W., Van Huffel S. and Hunyadi B. (2018). Artifact Detection of Wrist Photoplethysmograph Signals.In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS, ISBN 978-989-758-279-0, pages 182-189. DOI: 10.5220/0006594301820189


in Bibtex Style

@conference{biosignals18,
author={Kaat Vandecasteele and Jesús Lázaro and Evy Cleeren and Kasper Claes and Wim Van Paesschen and Sabine Van Huffel and Borbála Hunyadi},
title={Artifact Detection of Wrist Photoplethysmograph Signals},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS,},
year={2018},
pages={182-189},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006594301820189},
isbn={978-989-758-279-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS,
TI - Artifact Detection of Wrist Photoplethysmograph Signals
SN - 978-989-758-279-0
AU - Vandecasteele K.
AU - Lázaro J.
AU - Cleeren E.
AU - Claes K.
AU - Van Paesschen W.
AU - Van Huffel S.
AU - Hunyadi B.
PY - 2018
SP - 182
EP - 189
DO - 10.5220/0006594301820189