Surface EMG-based quantification of inspiratory effort: a quantitative comparison with P_es

Area of Science:

• Respiratory Physiology
• Biomedical Engineering
• Critical Care Medicine

Background:

• Assessing patient inspiratory effort during mechanical ventilation is crucial for optimizing patient-ventilator interaction.
• Traditional methods rely on esophageal pressure monitoring, requiring invasive catheter placement and calibration.
• Surface electromyography (sEMG) presents a non-invasive alternative for monitoring respiratory muscle activity.

Purpose of the Study:

• To evaluate surface electromyography (sEMG) as a non-invasive method for quantifying inspiratory effort in mechanically ventilated patients.
• To compare sEMG-derived measurements with traditional esophageal pressure-derived metrics.
• To investigate an automated method for improving sEMG signal quality and a novel occlusion-based approach for estimating neuromechanical coupling.

Main Methods:

• A prospective observational study involving patients on assisted mechanical ventilation.
• Simultaneous recording of airway pressures, esophageal/gastric pressures, and respiratory muscle sEMG (diaphragm and intercostals).
• Quantification of patient effort using EMG-time products (ETP) and pressure-time products ([Formula: see text]), and assessment of neuromechanical coupling via a conversion factor ([Formula: see text]).

Main Results:

• sEMG-derived EMG-time products (ETP) showed good correlation with esophageal pressure-derived pressure-time products ([Formula: see text]).
• An automated sEMG channel selection method improved the correlation between ETP and [Formula: see text].
• The neuromechanical conversion factor ([Formula: see text]) derived from occlusions correlated well with patient-specific factors, with a low breath-wise deviation.

Conclusions:

• Surface electromyography (sEMG) is a viable non-invasive alternative for monitoring breath-by-breath inspiratory effort in patients on assisted mechanical ventilation.
• The findings support the clinical utility of sEMG for assessing patient-ventilator synchrony and optimizing ventilation.
• Automated signal processing and occlusion-based calibration enhance the reliability of sEMG for clinical application.