ZYY0844/radarODE-MTL
Official implementation of radarODE and radarODE-MTL
This project helps medical researchers and vital sign monitoring engineers accurately reconstruct Electrocardiogram (ECG) signals from millimeter-wave radar data without direct skin contact. It takes raw radar spectrograms as input and outputs a robust, high-fidelity ECG signal, even in the presence of noise or patient movement. This is for professionals developing contactless health monitoring systems or conducting research in biomedical signal processing.
Use this if you need to reliably extract fine-grained, long-term or single-cycle ECG data from contactless radar measurements, especially when dealing with data affected by body movement or varying radar signal quality.
Not ideal if you are looking for a simple, out-of-the-box solution with pre-processed datasets, in which case you might consider the CFT-RFcardi project for quicker implementation.
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51
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9
Language
Python
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Last pushed
Jan 26, 2026
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