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

Content Provider	IEEE Xplore Digital Library
Author	Mananas, M.A. Romero, S. Topor, Z.L. Bruce, E.N. Houtz, P. Caminal, P.
Copyright Year	2001
Description	Author affiliation: Dept. of Autom. Control, Tech. Univ. of Catalonia, Barcelona, Spain (Mananas, M.A.; Romero, S.)
Abstract	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.
Starting Page	1115
Ending Page	1118
File Size	446304
Page Count	4
File Format	PDF
ISBN	0780372115
ISSN	1094687X
DOI	10.1109/IEMBS.2001.1020386
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-10-25
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Interference Muscles Electromyography Filtering Cardiac disease Cardiovascular diseases Signal analysis Adaptive filters Singular value decomposition Signal to noise ratio
Content Type	Text
Resource Type	Article

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