Publications

In this study, we propose a model-based tool for the detection of obstructive apnea episodes by using ECG features from a single lead channel. Several sequences of recurrent apnea were provoked in separate 15-min periods in anesthetized rats during an experimental model of obstructive sleep apnea (OSA). Morphology-based ECG markers and the beat-to-beat interval (RR) were assessed in each sequence. These markers were used to train dynamic Bayesian networks (DBN) with different orders and feature combinations to find a good tradeoff between network complexity and apnea-detection performance. By using a filtering approach, the resulting DBNs were used to infer the apnea probability signal for subsequent episodes in the same rat. These signals were then processed using by 15-s epochs to determine whether epochs were classified as apneic or nonapneic. Our results showed that fifth-order models provided suitable RMSE values, since higher order models become significantly more complex and present worse generalization. A global threshold of 0.2 gave the best overall performance for all combinations tested, with Acc = 81.3%, Se = 69.8% and Sp = 81.5%, using only two parameters including the RR and Ds (R-wave downslope) markers. We concluded that multivariate models using DBNs represent a powerful tool for detecting obstructive apnea episodes in short segments, which may also serve to estimate the number of total events in a given time period.

JTD Keywords: chronic respiratory diseases, obstructive sleep apnea, probabilistic models, Obstructive sleep apnea,probabilistic models,respiratory events,chronic respiratory disease, Respiratory events, Sleep-apnea syndrome,automated detection,oxygen-saturation,classification,recordings,signal

The use of wearable devices in clinical routines could reduce healthcare costs and improve the quality of assessment in patients with chronic respiratory diseases. The purpose of this study is to evaluate the capacity of a Shimmer3 wearable device to extract reliable cardiorespiratory parameters from surface diaphragm electromyography (EMGdi). Twenty healthy volunteers underwent an incremental load respiratory test whilst EMGdi was recorded with a Shimmer3 wearable device (EMGdiW). Simultaneously, a second EMGdi (EMGdiL), inspiratory mouth pressure (Pmouth) and lead-I electrocardiogram (ECG) were recorded via a standard wired laboratory acquisition system. Different cardiorespiratory parameters were extracted from both EMGdiW and EMGdiL signals: heart rate, respiratory rate, respiratory muscle activity and mean frequency of EMGdi signals. Alongside these, similar parameters were also extracted from reference signals (Pmouth and ECG). High correlations were found between the data extracted from the EMGdiW and the reference signal data: heart rate (R = 0.947), respiratory rate (R = 0.940), respiratory muscle activity (R = 0.877), and mean frequency (R = 0.895). Moreover, similar increments in EMGdiW and EMGdiL activity were observed when Pmouth was raised, enabling the study of respiratory muscle activation. In summary, the Shimmer3 device is a promising and cost-effective solution for the ambulatory monitoring of respiratory muscle function in chronic respiratory diseases.

JTD Keywords: Cardiorespiratory monitoring, Chronic respiratory diseases, Fixed sample entropy, Non-invasive respiratory monitoring, Surface diaphragm electromyography, Wearable wireless device

Bioimpedance is an unobtrusive noninvasive technique to measure respiration and has a linear relation with volume during normal breathing. The objective of this paper was to assess this linear relation during inspiratory loading protocol and determine the best electrode configuration for bioimpedance measurement. The inspiratory load is a way to estimate inspiratory muscle function and has been widely used in studies of respiratory mechanics. Therefore, this protocol permitted us to evaluate bioimpedance performance under breathing pattern changes. We measured four electrode configurations of bioimpedance and airflow simultaneously in ten healthy subjects using a wearable device and a standard wired laboratory acquisition system, respectively. The subjects were asked to perform an incremental inspiratory threshold loading protocol during the measurements. The load values were selected to increase progressively until the 60% of the subject's maximal inspiratory pressure. The linear relation of the signals was assessed by Pearson correlation (r ) and the waveform agreement by the mean absolute percentage error (MAPE), both computed cycle by cycle. The results showed a median greater than 0.965 in r coefficients and lower than 11 % in the MAPE values for the entire population in all loads and configurations. Thus, a strong linear relation was found during all loaded breathing and configurations. However, one out of the four electrode configurations showed robust results in terms of agreement with volume during the highest load. In conclusion, bioimpedance measurement using a wearable device is a noninvasive and a comfortable alternative to classical methods for monitoring respiratory diseases in normal and restrictive breathing.

JTD Keywords: Bioimpedance, Chronic respiratory diseases, Electrode configurations, Inspiratory threshold protocol, Wearable

Obstructive sleep apnea (OSA) is characterized by recurrent upper airway obstructions during sleep. The most common animal model of OSA is based on subjecting rodents to intermittent hypoxic exposures and does not mimic important OSA features, such as recurrent hypercapnia and increased inspiratory efforts. To circumvent some of these issues, a novel murine model involving non-invasive application of recurrent airway obstructions was developed. An electronically controlled airbag system is placed in front of the mouse's snout, whereby inflating the airbag leads to obstructed breathing and spontaneous breathing occurs with the airbag deflated. The device was tested on 29 anesthetized mice by measuring inspiratory effort and arterial oxygen saturation (SaO(2)). Application of recurrent obstructive apneas (6s each, 120/h) for 6h resulted in SaO(2) oscillations to values reaching 84.4 +/- 2.5% nadir, with swings mimicking OSA patients. This novel system, capable of applying controlled recurrent airway obstructions in mice, is an easy-to-use tool for investigating pertinent aspects of OSA.

JTD Keywords: Animal model, Upper airway Obstruction, Mouse model, Non-invasive system, Model sleep apnea, Respiratory disease

The structural integrity of the alveolar monolayer, which is compromised during lung inflammation, is determined by the balance between cell-cell and cell-matrix tethering forces and the centripetal forces owing to cell viscoelasticity and contraction. Dexamethasone is an anti-inflammatory glucocorticoid with protective effects in lung injury. To determine the effects of Dexamethasone on the stiffness and contractility of alveolar epithelial cells. Cell stiffness (G') and average traction exerted by the cell (T) were measured by magnetic twisting cytometry and by traction microscopy, respectively. A549 cells were treated 24 h with Dexamethasone (1 mu M) or vehicle (control). G' and T were measured before and 5 min after challenge with the inflammatory mediator Thrombin (0.5 U/ml). Changes induced by Dexamethasone in actin cytoskeleton polymerization were assessed by the fluorescent ratio between F-actin and G-actin obtained by staining cells with phalloidin and DNase I. Dexamethasone significantly increased G' and T by 56% (n = 11; p < 0.01) and by 80% (n = 17; p < 0.05), respectively. Dexamethasone also increased F/G-actin ratio from 2.68 +/- 0.07 to 2.96 +/- 0.09 (n = 10; p < 0.05). The relative increase in stiffness and contraction induced by Thrombin in control cells was significantly (p < 0.05) reduced by Dexamethasone treatment: from 190 to 98% in G' and from 318 to 105% in T. The cytoskeleton remodelling and the increase in cell stiffness and contraction induced by Dexamethasone could account for its protective effect in the alveolar epithelium when subjected to inflammatory challenge.

JTD Keywords: Cell mechanics, Cytoskeleton, Magnetic twisting cytometry, Traction microscopy, Respiratory diseases