Abstract 309: An Electromyographic System for Guiding Tracheal Intubation

Introduction: When tracheal intubation is necessary outside the hospital setting, inadvertent esophageal intubation may occur due to lower levels of provider experience and less access to equipment that can verify tracheal intubation. Therefore, we created a simple, rapid method for guiding endotracheal tube insertion. Methods: We constructed a system that can differentiate between the esophagus (smooth muscle tissue) and the trachea (nonmuscular tissue) based on electromyographic signal-response characteristics. We modified an endotracheal tube by adding 4 electrodes (2 for stimulating tissue with applied voltage and 2 for recording the tissue response) and tested the tube in a warm porcine model. We recorded 9 samples in 3 different locations in both the esophagus and the trachea, for a total of 18 samples. Both the stimulating voltage and the tissue response were recorded. We then used computational tools to analyze the resulting data and to create an integrative algorithm for differentiating between esophageal and tracheal tissue, based on the response signal. We differentiated the tissue types by using 3 integrated methods to measure 1) baseline frequency components to determine the average magnitude of contraction of the esophageal muscle tissue; 2) the rate of rectification of the response signal after the stimulation period; and 3) the difference between the average response voltages before and directly after stimulation. Results: The average magnitude of contraction was 24.3±13.7 V for esophageal tissue and 6.7±2.7 V for tracheal tissue ( P =0.013). The average rate of rectification of the response signal was 22.7±15.6 mV/sec for esophageal tissue and -0.177±8.35 mV/sec for tracheal tissue ( P =0.021). The difference between the average response voltages before and after stimulation was 2.89±1.84 mV for esophageal tissue and 0.834±0.930 mV for tracheal tissue ( P =0.023). By integrating these 3 methods, our algorithm had a sensitivity of 87.5% and specificity of 100%. Conclusion: With our system, rapid differentiation of the endotracheal-tube tip location provides real-time feedback information that may facilitate tube insertion into the trachea.