Alessandra Galli
Department / Institute
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RESEARCH PROFILE
Alessandra Galli is a postdoctoral researcher in the Signal Processing System group (Electrical Engineering Department) and a member of the Biomedical Diagnostic (BM/d) Lab of the Eindhoven University of Technology. Her research interests include biomedical signal processing, compression, anomaly detection, and machine learning. In particular, she is devoted to electrophysiological signals for cardiac non-invasive and long-term monitoring.
At TU/e, she is engaged in a project centered around pregnancy monitoring. Specifically, her research investigates the coupling interaction between the cardiovascular systems of both the mother and the fetus, with a focus on understanding the mediating role performed by the uterus and placenta. This investigation aims to shed light on the origins of pregnancy complications.
The ultimate objective of her work is to contribute to the development of innovative tools for the timely diagnosis and, eventually, prediction of pregnancy complications. The aspiration is that such advancements will enable pregnant women to receive treatment earlier, significantly improving the likelihood of successful delivery.
ACADEMIC BACKGROUND
Alessandra Galli received the B.Sc. and M.Sc. degrees in Biomedical Engineering from the University of Padova, Italy, in 2015 and 2017, respectively. In 2021, she received a Ph.D. degree in Information and Communication Technology from the School of Information Engineering of the University of Padova, with a dissertation about IoT measurements for long-term monitoring applications. In 2021-2022, she was a postdoctoral researcher of the Instrumentation and Measurements Group of the University of Padova, Italy. In September 2023, she joined TU/e as a postdoctoral researcher supported by a Marie Skłodowska-Curie Postdoctoral fellowship.
Recent Publications
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Patient-independent, MHD-robust R-peak detection for retrospective gating in cardiac MRI imaging
Physiological Measurement (2024) -
Improved mECG Removal and fECG Extraction by Integrated Periodic Components Analysis and Singular Value Decomposition
(2024) -
Automatic optimization of multichannel electrode configurations for robust fetal heart rate detection by Blind Source Separation
IEEE Transactions on Biomedical Engineering (2023) -
An Overview of the Sensors for Heart Rate Monitoring Used in Extramural Applications
Sensors (2022) -
Dedicated algorithm for unobtrusive fetal heart rate monitoring using multiple dry electrodes
Sensors (2021)
Ancillary Activities
No ancillary activities