Key result
A spatial blind source estimation method using WPCA and MUSIC algorithms achieved detection accuracies of 94.51% for respiratory rate and 97.79% for heart rate, outperforming traditional algorithms.
Why the study?
In FMCW radar environments, static clutter, white Gaussian noise, and respiratory harmonic components impede the separation and accurate estimation of respiratory rate and heart rate.
A novel spatial blind source estimation method using FMCW radar achieved high accuracy in detecting respiratory and heart rates by effectively separating signals from environmental noise.
Proposed radar method may improve respiratory-heart rate separation amid clutter; leaves open clinical validation before any practice use.
When detecting respiratory rate and heart rate in an FMCW radar room, there is a lot of static clutter and white Gaussian noise generated by hardware heat loss in the environment, which makes the separation of respiratory and heartbeat signals poor. At the same time, the harmonic component of the respiratory signal in the frequency domain will affect the estimation of heart rate. To solve the above problems, a spatial blind source estimation method was proposed to accurately estimate respiratory heart rate. Firstly, the weighted principal component analysis (WPCA) algorithm was used to extract the features of the target signal from the IF signal, and then the respiratory heart rate signal was reconstructed according to the different features. Then, the multi-signal classification (MUSIC) algorithm is used to convert the respiration and heartbeat signals into the zero domain to avoid the influence of the respective harmonic components on the detection results. The experimental results showed that the accuracy of respiratory rate detection and heart rate detection was 94.51% and 97.79%, respectively. Compared with the traditional algorithm, the proposed method is stable and has higher detection accuracy.
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Pei et al. (2025) studied Respiratory rate and heart rate detection. Spatial blind source estimation method (WPCA and MUSIC algorithms) vs. Traditional algorithm was evaluated on Accuracy of respiratory rate and heart rate detection. A spatial blind source estimation method using WPCA and MUSIC algorithms achieved detection accuracies of 94.51% for respiratory rate and 97.79% for heart rate, outperforming traditional algorithms.
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