Variability analysis of the respiratory volume based on non-linear prediction methods.
Med Biol Eng Comput
; 42(1): 86-91, 2004 Jan.
Article
em En
| MEDLINE
| ID: mdl-14977227
ABSTRACT
This work proposed and studied a method of automatically classifying respiratory volume signals as high or low variability by means of non-linear analysis of the respiratory volume. The analysis used volume signals generated by the respiratory system to construct a model of its dynamics and to estimate the quality of the predictions made with the model. Different methods of prediction evaluation, prediction horizons and embedding dimensions were also analysed. Assessment of the method was made using a database that contained 40 respiratory volume signals classified using clinical criteria into two classes low or high variability. The results obtained using the method of surrogate data provided evidence of non-linear determinism in the respiratory volume signals. A discriminant analysis carried out using non-linear prediction variables classified the respiratory volume signals with an accuracy of 95%.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Respiração Artificial
/
Mecânica Respiratória
/
Dinâmica não Linear
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Med Biol Eng Comput
Ano de publicação:
2004
Tipo de documento:
Article
País de afiliação:
Espanha