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Analysis of respiratory and muscle activity by means of cross information function between ventilatory and myographic signals.

Author information

1
Department Automatic Control, Biomed. Eng. Research Center, Technical University of Catalonia, UPC, Barcelona, Spain.

Abstract

Analysis of respiratory muscle activity is a promising technique for the study of pulmonary diseases such as obstructive sleep apnea syndrome (OSAS). Evaluation of interactions between muscles is very useful in order to determine the muscular pattern during an exercise. These interactions have already been assessed by means of different linear techniques like cross-spectrum, magnitude squared coherence or cross-correlation. The aim of this work is to evaluate interactions between respiratory and myographic signals through nonlinear analysis by means of cross mutual information function (CMIF), and finding out what information can be extracted from it. Some parameters are defined and calculated from CMIF between ventilatory and myographic signals of three respiratory muscles. Finally, differences in certain parameters were obtained between OSAS patients and healthy subjects indicating different respiratory muscle couplings.

PMID:
17271618
DOI:
10.1109/IEMBS.2004.1403104

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