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- W2969853651 abstract "Fall detection is important for senior care. In order to classify fall and other fall-similar daily motions, a novel dynamic range-Doppler trajectory (DRDT) method based on a frequency-modulated continuous-wave (FMCW) radar system is proposed. Multi-domain features including temporal changes of range, Doppler, radar cross-section (RCS) and dispersion are extracted from echo signals for a subspace K-Nearest Neighbor (KNN) machine learning classifier. Extensive experiments demonstrated its feasibility and an average accuracy of 95.5% was achieved in recognizing six typical fall-similar motions." @default.
- W2969853651 created "2019-08-29" @default.
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- W2969853651 date "2019-05-01" @default.
- W2969853651 modified "2023-09-26" @default.
- W2969853651 title "Fall detection with multi-domain features by a portable FMCW radar" @default.
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- W2969853651 doi "https://doi.org/10.1109/ieee-iws.2019.8804036" @default.
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