cyrillknecht/radar_vital_signs_ml
ETH Zürich Semester Project exploring the possibilities of using Deep Learning to extract vital signs from Radar Data
This project helps healthcare professionals and researchers develop advanced methods for continuous, contact-less vital sign monitoring. It takes raw radar data as input and produces high-quality heart and breath rate signals, even when traditional methods struggle with noise or artifacts. This system is designed for medical device developers, researchers, and engineers working on next-generation patient monitoring solutions.
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Use this if you are developing non-contact vital sign monitoring systems using radar and need to improve the robustness and accuracy of heart and breath rate extraction through machine learning.
Not ideal if you are looking for an out-of-the-box vital sign monitoring product for immediate clinical use, as this is a research project focused on algorithm development.
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22
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4
Language
Python
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Last pushed
May 06, 2024
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