Title :
Leakage Estimation Using Kalman Filtering in Noninvasive Mechanical Ventilation
Author :
Rodrigues, G.G. ; Freitas, U.S. ; Bounoiare, D. ; Aguirre, L.A. ; Letellier, C.
Author_Institution :
Centro Fed. de Educ. Tecnol. de Minas Gerais, Belo Horizonte, Brazil
Abstract :
Noninvasive mechanical ventilation is today often used to assist patient with chronic respiratory failure. One of the main reasons evoked to explain asynchrony events, discomfort, unwillingness to be treated, etc., is the occurrence of nonintentional leaks in the ventilation circuit, which are difficult to account for because they are not measured. This paper describes a solution to the problem of variable leakage estimation based on a Kalman filter driven by airflow and the pressure signals, both of which are available in the ventilation circuit. The filter was validated by showing that based on the attained leakage estimates, practically all the untriggered cycles can be explained.
Keywords :
Kalman filters; biomedical equipment; biomedical measurement; diseases; flow measurement; leak detection; pneumodynamics; signal processing; Kalman filtering; airflow signal; chronic respiratory failure; noninvasive mechanical ventilation; pressure signal; variable leakage estimation; ventilation circuit nonintentional leaks; Atmospheric modeling; Biomedical measurements; Covariance matrix; Estimation; Kalman filters; Mathematical model; Ventilation; Kalman filter (KF); leakage estimation; noninvasive mechanical ventilation (NIV); Algorithms; Humans; Models, Theoretical; Noninvasive Ventilation; Reproducibility of Results; Respiratory Insufficiency; Signal Processing, Computer-Assisted; Statistics, Nonparametric;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2012.2230630