Why the study?
Doppler-based radar systems can remotely monitor vital signs via chest-wall displacement, but properly separating respiratory and cardiac signals remains challenging due to spectral overlap.
Discrete Wavelet Transform is an effective method for extracting cardiac signals from Doppler radar systems in real-world, non-controlled environments.
DWT may aid radar-based cardiac signal separation; leaves open clinical validation before practice adoption.
Doppler-based radar systems have been seen as a promising tool to assess vital signs, since they are capable to monitor the respiratory and cardiac signal remotely, by measuring the chest-wall displacement. However, due to the spectral overlap of these signals, their proper separation is a challenging task. In this paper, we demonstrate the effectiveness of using Discrete Wavelet Transform in the cardiac signal extraction, by comparing this method with other approaches widely used in literature, namely a standalone Band-Pass Filtering, the Ensembled Empirical Mode Decomposition, the Continuous Wavelet Transform and the Wavelet Packet Decomposition. The comparison metrics were defined taking into consideration the heart rate computation accuracy, and also the peak detection consistency to further evaluate the Heart Rate Variability. The efficiency of those methods is also tested considering real application scenarios, characterized by non-controlled monitoring environment conditions and the ability to equally assess the vital signs of different subjects, regardless their physical stature.
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Gouveia et al. (2022) studied this question.
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