Comparison between manual and automated analyses of esophageal diaphragm electromyography during endurance cycling in patients with COPD

Background: A major challenge of interpreting diaphragm electromyography (EMGdi) recorded with an esophageal catheter is “cross talk” from the electrocardiogram (ECG). Time-consuming manual exclusion of ECG by selecting EMGdi signals in between QRS complexes is typically applied. We developed a customized algorithm (Labview: National Instruments, Austin, TX) to automatically deduct ECG signals during analyses. Aim: To assess agreement between manual and automated EMGdi analysis methods. Methods: EMGdi (as % of maximal EMGdi) of six patients (FEV1; 45±16%pred) was obtained using both methods during each minute of endurance cycling (80% peak work rate) before (11±4 min) and after 8 weeks of respiratory muscle training (14±8 min). Results: Time spent on manual and automated analyses was 81±21min and 29±11min, respectively (p<0.001). Intra-class correlation coefficients between methods were 0.96 at baseline and 0.85 for pre/post differences (both p<0.001). No significant method*time interaction effects were observed either at baseline (p=0.88) or for the differences (p=0.99). Group averages of baseline analyses were presented in Figure 1. Mean differences (limits of agreement) were -0.09% (-21.84 to 21.66%) at baseline and -6.48% (-33.25 to 20.29%) for the differences. Conclusion: Automated analyses of EMGdi required less time and highly agreed with manual analyses on a group level.