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Autoregressive model based on third order statistics for characterizing cough transmission filters.
Friend KA; Goldsmith WT; McKinney WH; Reynolds JS; Frazer D
Ann Biomed Eng 2001 Oct; 29(Suppl 1):S143
An autoregressive model based on third order statistics was used to characterize the transmission filter during a cough recorded by a recording system (Goldsmith, et al., Proccedings 3rd International Workshop on Biosignal Interpretation, 1999) from subjects awaiting pulmonary function testing at the West Virginia University Hospital. Because the respiratory tract changes shape with respect to the excitation with time, it can be modeled as a time-varying filter with fixed parameters over short time intervals. In order to determine the filter characteristics, cough samples were processed through an all-pole digital filter created with an autoregressive routine (Iyer, et al., IEEE Transaction of Biomedical Engineering, 1989) based on third order cumulants (Hadjileontiadis, et al., Technology and Health Care 1997). Filter response was analyzed. The inverse filter was used to separate the excitation source. Coughs were analyzed from healthy control subjects, as well as patients diagnosed with obstructive and restrictive lung disease. Results showed differences between the group of control subjects and those with lung disease in both the characteristics of cough sound source and the sound transmission path.
Models; Sampling; Lung disease; Pulmonary system disorders; Pulmonary congestion; Respiratory system disorders; Pulmonary function
Abstract; Conference/Symposia Proceedings
Annals of Biomedical Engineering
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