Assessment of clog in endotracheal tube by analyzing the variability of Rhonchi signals

This study investigates the presence and degree of clog in endotracheal tube (ET tube) using rhonchi audio signals. An obstruction was controlled at six levels (0–5 mL) using artificial mucus designed to simulate phlegm. To measure airflow-related changes inside the ET tube, the rhonchi capture adaptor (RCA) was used and it was connected between ventilator and ET tube. An artificial mucus was injected into the middle of the ET tube and rhonchi and pressure signals were acquired simultaneously. Based on pressure, each respiratory cycle was divided into inspiratory and expiratory phases. The interval of 1.66 s following the onset of inspiration was defined as phase A, and subsequent 1.66 s during which expiration begins was defined as phase B. For each phase, Poincaré analysis was performed, and short-term variability (SD1), long-term variability (SD2), and area derived from SD1 and SD2 were calculated. The results showed that in phase A, SD1, SD2, and area increased with increasing volumes of injected artificial mucus and were statistically significant ( p < 0.05); however, no statistically significant differences were observed at volumes of 3 mL or higher. In phase B, SD1, SD2, and area were statistically significant in comparison between normal (0 mL) and all other conditions, as well as among the obstruction conditions (all p < 0.05). These results indicate that respiratory phase segmentation combined with variability analysis can be used to identify clog inside the ET tube, and degree of obstruction can be classified using SD1 or area analysis during phase B.