Time domain analysis of diaphragmatic electromyogram during fatigue in men

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Abstract
Diaphragmatic fatigue has been correlated with a change in the electromyogram recorded from the diaphragm (EMGdi), which suggests that the electromyogram is a potential clinical tool to detect respiratory muscle fatigue. Changes in the EMGdi have previously been quantified by using the power spectral parameters high-low ratio or mean frequency. In this study, we developed an autoregressive model of the EMG in an attempt to improve the analysis of the EMGdi. This model was tested on recordings of the EMGdi that were obtained from an esophageal electrode in five normal subjects breathing to fatigue through an inspiratory resistor. The data obtained from the autoregressive model were directly compared with data from the high-low ratio and mean frequency techniques. The autoregressive model showed an excellent correlation with mean frequency. Both techniques were superior to the high-low ratio measurement. Because the autoregressive model requires much less computation than mean frequency and can be easily implemented in real time on a minicomputer, we propose this as a preferable approach.

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