Key result
The third order cyclic temporal moment and cumulant signal processing approach was evaluated for non-contact detection of vital signs using 10, 17, and 26 GHz ISM frequencies.
Why the study?
Prior cyclostationary radar approaches for non-contact vital sign monitoring focused on single frequencies and omitted the impact of parameters such as attenuation and random body movement.
The use of third-order cyclic temporal moments and cumulants in radar signal processing may improve the non-contact estimation of heart and respiratory rates.
Due to the microwave sensitivity toward small movements,non-contact and noninvasive continuous monitoring radar, has been pointed out as one of the most promising technologies for estimation of human cardiopulmonary activity. Various signal processing methods have been proposed in the literature to extract the heart rate (HR) and respiratory rate (RR). Although the RF-reflected signal from the human body is corrupted by noise of the environment, random body movements and clutter. Given these limitations, the interest information RR and HR might be strenuous to extract. In this purpose, cyclostationary approach has been use for non-contact detection of vital signs. However, the preliminary works focus only on one frequency and do not include the impact of other parameters (attenuation and random movement of the body) in the analysis. In this paper, we evaluate a wide range of several parameters that might influence on the cyclic features of the reflected signal from the person’s chest. Besides, we inspect the assessment of the third orders cyclic features of the cyclostationary signal processing performance by developing the third cyclic temporal moment and the third cyclic temporal cumulant. The analysis is carried out using a reduced number of samples to reduce the response time and complexity of system radar for three ISM frequencies 10, 17 and 26 GHz. To validate and assess the performances of the simulation part, we carried out a series of tests on a clothed person seated in a laboratory environment. All of the results obtained make it possible to consider a setting guide for a better estimation of RR and HR.
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Sekak et al. (2022) studied Estimation of human cardiopulmonary activity. Third order cyclic temporal moment and cumulant signal processing was evaluated on Estimation of respiratory rate (RR) and heart rate (HR). The third order cyclic temporal moment and cumulant signal processing approach was evaluated for non-contact detection of vital signs using 10, 17, and 26 GHz ISM frequencies.
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