Surface EMG-based Estimation of Breathing Effort for Neurally Adjusted Ventilation Control

In assisted mechanical ventilation, it is of critical importance to monitor the patient's own effort to breathe. Methods currently available are either invasive (esophageal electromyography and esophageal pressure) or rely heavily on intermittent occlusion maneuvers to identify the properties of the respiratory muscles. In this article, we propose a novel, non-invasive method to identify the patient's respiratory mechanics and estimate the pressure generated by the patient, based on surface electromyographic (sEMG) measurements of the respiratory muscles. Our method is computationally efficient, real-time capable, and can be run continuously during normal ventilation. A numerical comparison with esophageal pressure measurements using three clinical data sets demonstrates the estimation procedure's good performance. Clinically, monitoring a patient's respiratory effort is of high intrinsic, diagnostic value, while also enabling a whole range of new, adaptive control algorithms for assisted mechanical ventilation. Copyright (C) 2020 The Authors.