Yildirim I.Kahya Y.P.Sen I.2024-03-132024-03-1320179781509064946https://doi.org/10.1109/SIU.2017.7960477https://hdl.handle.net/20.500.12662/286225th Signal Processing and Communications Applications Conference, SIU 2017 -- 15 May 2017 through 18 May 2017 -- -- 128703In this work, a new methodology to estimate the respiratory air flow rate from pulmonary sounds is proposed. Previously in the literature, it has been suggested to use the auto-regressive model to estimate the flow rate from pulmonary sounds, moreover, it has been presented that sounds are more correlated with the flow rate in certain frequency bands. In this work, on the other hand, the optimal auto-regressive model order for the estimation is determined, and the estimates from the optimal auto-regressive model and from the frequency bands are combined through a Wiener filter to increase the success of the estimation. The correlation coefficient is increased to 0.71 with the proposed method, which was 0.66 for the optimal-order auto-regressive model and 0.62 for the most-correlated frequency band. © 2017 IEEE.trinfo:eu-repo/semantics/closedAccessair flow estimationauto-regressive modelPulmonary soundsWiener filterConference Object10.1109/SIU.2017.79604772-s2.0-85026294542N/A