Subject: cuffless blood pressure · ECG · PPG · machine learning · deep learning

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Year: 2022

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Type: Proceedings

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Title: Using Cuffless Non-Invasive Methods for Blood Pressure Estimation: Description of the Selected Solutions

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Author: Andrashikova, Barbora
Author: Lehocki, Fedor
Author: Tyshler, Milan
Author: Madevska Bogdanova, Ana
Author: Kuzmanov, Ivan
Author: Masar, Oto
Author: Spasenovich, Marko
Author: Putekova, Silvia

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Abstract: Blood pressure is a crucial vital sign used as an indicator of patient’s medical state. However, the standard methods of measuring blood pressure continuously are not convenient enough in order to be used versatilely. Critical and life threatening situations such as civil disasters require measuring blood pressure as fast and as accurately as possible without the need of manual calibration. In this paper, we introduce several existing blood pressure estimation techniques using machine learning and deep learning algorithms based on ECG and/or PPG signals acquired from a wearable sensor.

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Publisher:

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Relation: ICT Innovations 2022

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Identifier: oai:repository.ukim.mk:20.500.12188/24997
Identifier: http://hdl.handle.net/20.500.12188/24997

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