TY - GEN
T1 - High-Accuracy Cardiac Activity Extraction Using RLMD-Based Frequency Envelogram in FMCW Radar Systems
AU - Li, Jian Fu
AU - Yang, Chin Lung
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper proposes an accurate extraction of beat-to-beat interval (BBI) using the robust local mean decomposition (RLMD)-based frequency envelogram (FEnv) method in frequency-modulated continuous wave (FMCW) radar systems with lower signal-to-noise ratio (SNR). The FEnv benefits from spectral integration of time-frequency representation (TFR) and can further emphasize the vital signal fragments with strong characteristics. However, the performance of original FEnv suffers from the insufficient time-frequency resolution of the Fourier transform, resulting in poor BBI estimates. RLMD decomposes the reflected signals into the amplitude-modulated (AM) signals and the frequency-modulated (FM) signals, which can be reshaped according to heartbeat frequency band, to improve time-frequency resolution. After proper preprocessing of the received I/Q signals, the cardiac activity can be extracted accurately by the proposed RLMD-based FEnv. The results of the proposed algorithm are in high agreement with the reference signals ECG, and the error rate can reach 1.84 % on average.
AB - This paper proposes an accurate extraction of beat-to-beat interval (BBI) using the robust local mean decomposition (RLMD)-based frequency envelogram (FEnv) method in frequency-modulated continuous wave (FMCW) radar systems with lower signal-to-noise ratio (SNR). The FEnv benefits from spectral integration of time-frequency representation (TFR) and can further emphasize the vital signal fragments with strong characteristics. However, the performance of original FEnv suffers from the insufficient time-frequency resolution of the Fourier transform, resulting in poor BBI estimates. RLMD decomposes the reflected signals into the amplitude-modulated (AM) signals and the frequency-modulated (FM) signals, which can be reshaped according to heartbeat frequency band, to improve time-frequency resolution. After proper preprocessing of the received I/Q signals, the cardiac activity can be extracted accurately by the proposed RLMD-based FEnv. The results of the proposed algorithm are in high agreement with the reference signals ECG, and the error rate can reach 1.84 % on average.
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U2 - 10.1109/IMS37964.2023.10188114
DO - 10.1109/IMS37964.2023.10188114
M3 - Conference contribution
AN - SCOPUS:85168541011
T3 - IEEE MTT-S International Microwave Symposium Digest
SP - 1097
EP - 1100
BT - 2023 IEEE/MTT-S International Microwave Symposium, IMS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE/MTT-S International Microwave Symposium, IMS 2023
Y2 - 11 June 2023 through 16 June 2023
ER -