A Novel MIMO FMCW Radar-Based Approach for Heart Rate Estimation Using Positional Feature Selection

This paper proposes a heart rate estimation method using Variational Mode Decomposition (VMD) employing Multiple-Input Multiple-Output (MIMO) Frequency Modulated Continuous Wave (FMCW) radar. The proposed method first estimates the human position within the radar's coverage area, then reduces noise by focusing on the signal from these positions. The signal is decomposed into Intrinsic Mode Function (IMF) signals using VMD, and only the IMF signal related to the heartbeat is retained. Heart rate signal is reconstructed by weighting IMF signals based on their energy within the specific spatial area in which the human is located. The reconstructed signals are utilized for heart rate estimation through peak detection. The estimation is done over consecutive time windows. Until the fourth time window, among the estimated heart rates from the different cells, the selection is based on energy and periodicity. From the fifth time window onwards, the heart rate closest to the average of the previous four estimates is chosen. This approach considers the gradual transition of heart rate estimation over time to mitigate extraneous variations. Validation experiments involved 4 subjects being seated and stationary within the radar coverage area, with heart rate observed via MIMO FMCW radar. Results showed an average Mean Absolute Error (MAE) of 2.54 BPM, with an exclusion rate of 2.12%.