article · Biomedical Signal Processing and Control
The supervision of respiratory movements is undoubtedly an important tool for detecting respiratory diseases and functional abnormalities. The accuracy of respiratory diagnostics using respiratory motion depends to a large extent on the respiratory signal modeling. Hence the need for a realistic model that can reproduce the characteristics of the respiratory signal. The aim of this study is to provide an accurate analytical model that takes into account the random fluctuations of the amplitude and the cycle-duration of the respiration over several respiratory cycles. The proposed model, which by the way exhibits cyclostationary properties, is then validated by using it to fit a real-life respiration signal. Moreover, the cyclostationarity character is proven through a theoretical study. Finally, simulations on synthetic and experimental data are performed to confirm the effectiveness and the cyclostationarity property of the proposed respiratory model.
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DOI: 10.1016/j.bspc.2025.108503
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