Cardiac interference in myographic signals from different respiratory muscles and levels of activity

An interesting approach to study pulmonary diseases is the analysis of the respiratory muscle activity by means of electromyographic (EMG) and vibromyographic (VMG) signals. However, both signals are contaminated by cardiac activity reflected in electrocardiographic and cardiac pulse signals, respectively. Adaptive filtering and Singular Value Decomposition techniques were applied to reduce cardiac interference (CI) in signals recorded from three respiratory muscles (genioglossus, sternomastoid and diaphragm) in 19 subjects breathing against progressively increased negative pressure. The parameter Interference Relation (IR) is presented and its reduction with filtering is highly correlated with signal to noise ratio. This correlation indicates that IR is a good index to evaluate the level of interference. The Cl is highest at low levels of ventilation when the respiratory muscles are less active. Furthermore, the level of interference depends on the selected muscle: the most affected muscle is the diaphragm, then sternomastoid, and finally genioglossus. This order is preserved for both EMG and VMG signals. That indicates similar level of CI for signals reflecting electrical and mechanical muscle activity. The reduction of CI by means of the presented filtering techniques is shown by the parameter IR especially in EMG signals.