Why the study?
Remote radar vital sign assessment suffers from low cardiac signal resolution from chest micro displacement, hindering exact peak localization and compromising HRV assessment.
A novel synthetic radar signal model derived from ECG using adaptive filtering enables the evaluation of lower carrier radars for accurate, remote heart rate variability assessment.
Low cardiac resolution in radar vital signs limits peak localization; leaves open need for refined algorithms before clinical validation.
The ability to remotely assess vital signs using radar systems may potentialize the healthcare systems, since it does not require any direct interaction with the subject. Nonetheless, these systems present inherent challenges that could compromise the accuracy of the vital signs parameters. For instance, there is a lack of resolution on the cardiac signal, since the radar only detects the chest micro displacement. Low cardiac resolution prevents the exact localization of signal peaks, compromising the Heart Rate Variability (HRV) assessment. In this work, we use a customized band-pass filter obtained through adaptive filtering, applied to the Electrocardiography (ECG) signal to generate the corresponding synthetic radar signal. This provides an easy way to extract a cardiac radar signal model, free of issues that arise from random body motion or from an eventual decrease in signals quality, which are inherent issues of long-term acquisitions. This model was further used to verify if the signal resolution provided by lower carrier radars is suitable to determine the HRV parameters accurately.
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Gouveia et al. (2022) studied this question.