Estimating Respiratory Pattern Variability by Symbolic Dynamics

Summary

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 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

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