dc.contributor.author | SAATÇI, ESRA | |
dc.contributor.author | Akan, Aydin | |
dc.date.accessioned | 2021-03-03T16:25:47Z | |
dc.date.available | 2021-03-03T16:25:47Z | |
dc.identifier.citation | SAATÇI E., Akan A., "Lung model parameter estimation by unscented Kalman filter", 29th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, Lyon, Fransa, 22 - 26 Ağustos 2007, ss.2556-2557 | |
dc.identifier.other | vv_1032021 | |
dc.identifier.other | av_442a0505-0d06-4d28-9af4-0816b27f6fc8 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12627/49519 | |
dc.identifier.uri | https://doi.org/10.1109/iembs.2007.4352850 | |
dc.description.abstract | Dynamic nonlinear models are the best choice to analyze respiratory systems and to describe system mechanics. In this work, Unscented Kalman Filtering (UKF) was used to estimate the dynamic nonlinear model parameters of the lung model by using the measured airway flow, mask pressure and integrated lung volume. Artificially generated data and the data from Chronic Obstructive Pulmonary Diseased (COPD) patients were analyzed by the proposed model and the proposed UKF algorithm. Simulation results for both cases demonstrated that UKF is a promising estimation method for the respiratory system analysis. | |
dc.language.iso | eng | |
dc.subject | RADYOLOJİ, NÜKLEER TIP ve MEDİKAL GÖRÜNTÜLEME | |
dc.subject | Tıp | |
dc.subject | Sağlık Bilimleri | |
dc.subject | Dahili Tıp Bilimleri | |
dc.subject | Nükleer Tıp | |
dc.subject | Biyomedikal Mühendisliği | |
dc.subject | Mühendislik ve Teknoloji | |
dc.subject | Klinik Tıp | |
dc.subject | Mühendislik, Bilişim ve Teknoloji (ENG) | |
dc.subject | Mühendislik | |
dc.subject | MÜHENDİSLİK, BİYOMEDİKSEL | |
dc.subject | Klinik Tıp (MED) | |
dc.subject | GÖRÜNTÜLEME BİLİMİ VE FOTOĞRAF TEKNOLOJİSİ | |
dc.title | Lung model parameter estimation by unscented Kalman filter | |
dc.type | Bildiri | |
dc.contributor.department | İstanbul Kültür Üniversitesi , , | |
dc.contributor.firstauthorID | 133337 | |