Contributed Papers (Oral)
5. Cardiovascular and Respiratory Systems Engineering
14:20 - 15:35 | Wed 12 Jul | Webster Room | WeBT15
Measuring diaphragmatic electromyography (EMGdi) provides an indirect quantification of neural respiratory drive and allows the delimitation of diaphragm neural activation and deactivation during inspiration. EMGdi recordings have been incorporated in novel modes of assisted mechanical ventilation, such as neurally adjusted ventilatory assist (NAVA), to trigger and cycle-off the ventilator. The EMGdi signal improves the assistance delivered by more conventional ventilatory modes, in which the ventilator is synchronized with the patient employing a pneumatic triggering. In this work, we evaluate the time delay between the onset and offset of inspiratory activity estimated from EMGdi and three respiratory mechanical signals: the respiratory flow (FL), the transdiaphragmatic pressure (Pdi) and the diaphragm length (Ldi) signals. To this purpose, these signals were acquired in three mongrel dogs surgically instrumented under general anesthesia. Onsets and offsets were estimated manually and by automatic algorithms on these signals. The highest delays were obtained between EMGdi and FL (100 ms) while the lowest delays were obtained between EMGdi and Pdi (8 ms). Moreover, differences between manual and automatic estimations showed a mean absolute error lower than 45 ms. In conclusion, our study points out that both EMGdi and Pdi signals detect the onset and offset of inspiratory activity earlier than the FL signal, and would therefore be better for the improvement of patient-ventilator synchrony.
No information added