Estimating Respiratory Pattern Variability by Symbolic Dynamics - Caminal, P.; Mateu, J.; Vallverdú, M.; Giraldo, B.; Benito, S.; Voss, A. (Methods of Information in Medicine, 2004)
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 (TTOT) time series and the relation TI/TTOT, that contains the influence of inspiratory time (TI), were considered. Length-3 words and 3 different symbols were proposed. The incidence of the overlapping τ and the parameter α 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 ≤ .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.
Keywords: Respiratory; pattern variability; symbolic dynamics