Fraunhofer Center for Assistive Information and Communication Solutions – AICOSDescription:
The aim of this project is to implement, test and compare different approaches for cuffless BP estimation using Machine Learning and, specifically, Deep Neural Networks from the ECG and PPG signals or solely PPG signal.
The expected output will be a comparison, in terms of magnitude of the measurement error, of different machine learning based approaches for estimating cuffless BP.
Outcome:
AICOS will continue building on existing knowledge in the innovative field of cuffless blood pressure measurement, which is expected to contribute to future projects submissions in the scope of personalised / value-based medicine approaches.
In this thesis, the topic of Deep Neural Networks for regression will also be explored, allowing us to gain experience and create notable examples in this area.
Author: Niccolo Pietralata
Type: MSc thesis
Partner: FCT NOVA – Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa
Year: 2021