Key result
Singular spectrum analysis combined with variational modal decomposition enabled high-accuracy extraction of vital signs from 10 subjects at different distances using UWB radar sensors.
Why the study?
Accurate heart rate measurement with UWB radar is challenging due to weak heartbeat amplitude and measurement noise.
The combination of SSA and VMD improves the accuracy of vital sign extraction from UWB radar sensors by eliminating noise peaks around the heartbeat rate.
May enable non-contact vital-sign monitoring in occupational settings; leaves open clinical adoption pending validation.
The combination of advanced radar sensor technology and smart grid has broad prospects. It is meaningful to monitor the respiration and heartbeat of grid employees under resting state through radar sensors to ensure that they are in a healthy working state. Ultra-wideband (UWB) radar sensor is suitable for this application because of its strong penetration ability, high range resolution and low average power consumption. However, due to weak heartbeat amplitude and measurement noise, the accurate measurement of the target heart rate is a challenge. In this paper, singular spectrum analysis (SSA) is proposed to reconstruct the eigenvalues of noisy vital signs to eliminate noise peaks around the heartbeat rate; combined with the variational modal decomposition (VMD), the target vital signs can be extracted with high accuracy. The experiment confirmed that the target vital sign information can be extracted with high accuracy from ten subjects at different distances, which can play an important role in short distance human detection and vital sign monitoring.
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Yu et al. (2023) studied Healthy resting state (n=10). Singular spectrum analysis (SSA) combined with variational modal decomposition (VMD) was evaluated on Accurate extraction of target vital signs (heart rate and respiration). Singular spectrum analysis combined with variational modal decomposition enabled high-accuracy extraction of vital signs from 10 subjects at different distances using UWB radar sensors.
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