During the course of an experiment, esophageal, gastric, and transdiaphragmatic pressures, as well as the volume signal from the VMM and the filtered EMG signal were digitized by an A-to-D (analog to digital) converter (Data Translation No. 2801). These five digitized channels were displayed in real-time on a microcomputer (WYSE 386-16) using data acquisition software (Laboratory Technologies Corp, Wilmington, MA), and they were recorded on the hard disk for postexperiment processing. We also recorded Pdi, EMG, and expiratory volume on a strip-chart recorder (Gould 2400, Cerritos, CA).
Software was developed to perform breath-by-breath analysis on the recorded digital data. The algorithm is described herein: Initially, the volume waveform was scanned to mark inspiratory and expiratory cycles. During each inspiration, Pes, Pga, and Pdi waveforms were averaged for measurement of mean Pes (Pes), mean Pga (Pga), and mean Pdi (Pdi). Furthermore, the pressure time integral of the diaphragm (PTI = /Pdidt) was calculated during each inspiration. flovent inhaler
The software also integrated the digitized EMG signal during each inspiration. Bigland and Lippold have shown that integrated EMG (iEMG) signal strength varies directly with the force developed by the muscle it monitors. Usually, in measuring the strength of activity of respiratory muscles, an analog device called a “leaky integrator” with a time constant of 100 to 200 ms is used. The peak amplitude of the leaky-integrated EMG wave is then used as an estimate of the integrated EMG during the inspiratory maneuver. Instead of using a leaky integrator, we digitized the filtered EMG signal and integrated it directly in software during each inspiratory period. This has two advantages: (1) The integration that was done in software was triggered by the inspiratory volume signal.
Category: Lung function
Tags: neuromuscular, neuromuscular disease, patients copd, ventilatory muscle