Automatic Pain Intensity Estimation based on Electrocardiogram and Demographic Factors

Stefanos Gkikas, Chariklia Chatzaki, Elisavet Pavlidou, Foteini Verigou, Kyriakos Kalkanis, Manolis Tsiknakis

2022

Abstract

Automatic pain intensity estimation possess significant importance for reliable and complete pain management. The accurate and continuous monitoring is essential in order to attain objective insight about the condition of the patient. In this work, we elaborate physiological signals in order to estimate the pain intensity and investigate the impact of demographic factors. Specifically, we exploit electrocardiography signals, adopting the Pan-Tompkins algorithm to extract important features and apply well-validated classification methods, while we explore the correlation of gender and age with the pain manifestation.

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Paper Citation


in Harvard Style

Gkikas S., Chatzaki C., Pavlidou E., Verigou F., Kalkanis K. and Tsiknakis M. (2022). Automatic Pain Intensity Estimation based on Electrocardiogram and Demographic Factors. In Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE, ISBN 978-989-758-566-1, pages 155-162. DOI: 10.5220/0010971700003188


in Bibtex Style

@conference{ict4awe22,
author={Stefanos Gkikas and Chariklia Chatzaki and Elisavet Pavlidou and Foteini Verigou and Kyriakos Kalkanis and Manolis Tsiknakis},
title={Automatic Pain Intensity Estimation based on Electrocardiogram and Demographic Factors},
booktitle={Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,},
year={2022},
pages={155-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010971700003188},
isbn={978-989-758-566-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,
TI - Automatic Pain Intensity Estimation based on Electrocardiogram and Demographic Factors
SN - 978-989-758-566-1
AU - Gkikas S.
AU - Chatzaki C.
AU - Pavlidou E.
AU - Verigou F.
AU - Kalkanis K.
AU - Tsiknakis M.
PY - 2022
SP - 155
EP - 162
DO - 10.5220/0010971700003188