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PubMed · 15026830

Estimating respiratory pattern variability by symbolic dynamics.

P Caminal·J Mateu·M Vallverdú·B Giraldo·S Benito·A Voss
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Abstract

OBJECTIVES: The traditional techniques of data analysis are often not sufficient to characterize the complex dynamics of respiration. In this study the respiratory pattern variability was analyzed using symbolic dynamics. METHODS: A group of 20 patients on weaning trials from mechanical ventilation were studied at two different pressure support ventilation levels. Breath duration (T(TOT)) time series and the relation T(I)/T(TOT), that contains the influence of inspiratory time (T(I)), were considered. Length-3 words and 3 different symbols were proposed. The incidence of the overlapping tau and the parameter alpha were analyzed. RESULTS: From the breath duration time series, the distribution of words with probability of occurrence higher than 6% was concentrated on one word for low respiratory variability, whereas high variability was characterized by 4 words, presenting a statistically significant difference (p </= 0.0005). The probability occurrence of words "110" and "111" was also significantly different (p</= 0.0005) when comparing both variabilities. CONCLUSION: The analysis carried out obtained discriminant functions able to correctly classify all the testing set series. These results permit the consideration of symbolic dynamics as a promising methodology to study the respiratory pattern variability.

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Data Interpretation, StatisticalForced Expiratory VolumeHumansIncidenceModels, StatisticalNonlinear DynamicsProbabilityReference ValuesRespiratory MechanicsSensitivity and SpecificitySignal Processing, Computer-AssistedTime FactorsVentilator WeaningComparative StudyJournal ArticleResearch Support, Non-U.S. Gov't

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P Caminal, J Mateu, M Vallverdú, B Giraldo, S Benito, A Voss. 2004. Estimating respiratory pattern variability by symbolic dynamics.. https://pubmed.ncbi.nlm.nih.gov/15026830/

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