Fig 1.
Breathing pattern in a representative subject.
(a), An experimental tracing of abdominal and rib cage movement signals recorded continuously by pneumotrace bands (only a few seconds of tracing is presented for clarity). The plethysmography signals were calibrated to volume using an artificial neural network model. (b) and (c), Original (“raw”) inter-breath interval (b) and lung volume (c) time series during 60 min of resting breathing in a representative subject.
Table 1.
The mean ± SD values of the average and the coefficient of variation (CV) of inter-breath interval and lung volume series.
Fig 2.
Detrended fluctuation analysis (DFA) plots for the inter-breath interval(a) and lung volume (b) time series in representative subjects.
A linear relationship between log(n) and log[f(n)] indicates the presence of fractal dynamics. The scaling exponent α quantifies the strength of long-range correlations within the time series. CAA, controlled atopic asthma; UAA, uncontrolled atopic asthma; UNAA, uncontrolled non-atopic asthma.
Fig 3.
Differences of complexity indices between cases.
a, p < 0.05 comparing to Healthy; b, p < 0.05 comparing to CAA; c, p < 0.05 comparing to UAA. CAA, controlled atopic asthma; UAA, uncontrolled atopic asthma; UNAA, uncontrolled non-atopic asthma; DFA, Detrended fluctuation analysis; SampEn, sample entropy; LLE, Largest Lyapunov exponents; IBI, inter-breath interval; V, volume.
Fig 4.
ROC curves for the ability of the complexity indices.
(a), discriminating asthma from healthy; (b), discriminating uncontrolled from controlled asthma; (c), discriminating non-atopic from atopic asthma. DFA, detrended fluctuation analysis; SampEn, sample entropy; LLE, largest Lyapunov exponents; IBI, inter-breath interval; LV, lung volume.
Table 2.
The clinical potential of the complexity indices in discriminating asthma (n = 30) from healthy subjects (n = 10).
Table 3.
The clinical potential of the complexity indices in discriminating uncontrolled (n = 20) from controlled asthma (n = 10).
Table 4.
The clinical potential of the complexity indices in discriminating non-atopic (n = 10) from atopic asthma (n = 20).
Table 5.
The clinical potential of complexity indices combination in discriminating various types of asthma.