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Affiliation

Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Estavromenos, 71410, Heraklion, Greece

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1 Papers

Automatic Pain Intensity Estimation based on Electrocardiogram and Demographic Factors

Topics: Decision Support Systems; Home Care Monitoring Systems; Diagnostic Support; Interoperability and System Integration; Health Information Systems; Medical Data Science Technologies; Clinical Informatics

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

Affiliation: Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Estavromenos, 71410, Heraklion, Greece

Digital Object Identifier: 10.5220/0010971700003188

Proceedings of ICT4AWE 2022, ISBN: 978-989-758-566-1

Quick 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.