@inproceedings{,
    author = {Alirezazad, Keivan; Schmitt, Jonas; Maurer, Linus},
    title = {Vital Sign Monitoring in Cluttered Environments: Leveraging FMCW Radar and PCA Analysis},
    editor = {},
    booktitle = {2024 25th International Microwave and Radar Conference (MIKON) : Wroclaw, Poland, 2024},
    series = {},
    journal = {},
    address = {Piscataway, NJ},
    publisher = {IEEE},
    edition = {},
    year = {2024},
    isbn = {},
    volume = {},
    number =  {},
    pages = {103-108},
    url = {},
    doi = {10.23919/MIKON60251.2024.10633997},
    keywords = {},
    abstract = {This research project focuses on monitoring and recording specific vital signs, such as heartbeat rate (HR) and breathing rate (BR), from human participants. Leveraging the capabilities of the INRAS GmbH Radarbook2, a 77 GHz multiple-input and multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar, we employ principal component analysis (PCA) on aggregated range-angle maps (RAM) that are spatially sliced. Through the analysis of multiple features extracted from slow-time samples of phase data, PCA effectively distinguishes between signal and noise, resulting in a more robust representation of the underlying vital signals. This study evaluates the performance of the proposed algorithm against the EQ02+ LifeMonitor, a cutting-edge wearable sensor employed for establishing ground truth values. Analysis of conducted experiments indicates a low mean absolute percentage error (MAPE) of 2% for HR and 3.3% for BR measurements.},
    note = {},
    institution = {Universität der Bundeswehr München, Fakultät für Elektrotechnik und Informationstechnik, EIT 4 - Institut für Mikroelektronik und Schaltungstechnik, Professur: Maurer, Linus},
    
    
}