DocumentCode :
1827727
Title :
Application of the Empirical Mode Decomposition method to the Analysis of Respiratory Mechanomyographic Signals
Author :
Torres, A. ; Fiz, J.A. ; Jane, R. ; Galdiz, J.B. ; Gea, J. ; Morera, J.
Author_Institution :
Univ. Politec. de Catalunya, Barcelona
fYear :
2007
fDate :
22-26 Aug. 2007
Firstpage :
1566
Lastpage :
1569
Abstract :
The study of the mechanomyographic (MMG) signals during dynamic contractions requires a criterion to separate the low frequency (LF) component (basically due to gross movement of the muscle or of the body) and the high frequency (HF) component (related with the vibration of the muscle fibers during contraction). In this study, we propose to use the Empirical Mode Decomposition method in order to analyze the Intrinsic Mode Functions of MMG signals of the diaphragm muscle, acquired by means of a capacitive accelerometer applied on the costal wall. This signal, as the MMG signals during dynamic contractions, has a LF component that is related with the movement of the thoracic cage, and a HF component that could be related with the vibration of diaphragm muscle fibers during contraction. The method was tested on an animal model, with two incremental respiratory protocols performed by two non anesthetized mongrel dogs. The results show that the proposed EMD based method provides very good results for the cancellation of low frequency component of MMG signals. The obtained correlation coefficients between respiratory and MMG parameters were higher than the ones obtained with a Wavelet multiresolution decomposition method utilized in a previous work.
Keywords :
biomechanics; muscle; pneumodynamics; MMG signals; capacitive accelerometer; diaphragm muscle; dynamic contractions; empirical mode decomposition method; mongrel dogs; muscle contraction; muscle fiber vibration; respiratory mechanomyographic signals; respiratory protocols; thoracic cage; Accelerometers; Animals; Dogs; Frequency; Hafnium; Muscles; Optical fiber testing; Performance evaluation; Protocols; Signal analysis; Acceleration; Algorithms; Animals; Diagnosis, Computer-Assisted; Dogs; Electromyography; Manometry; Muscle Contraction; Oscillometry; Respiratory Mechanics; Respiratory Muscles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
ISSN :
1557-170X
Print_ISBN :
978-1-4244-0787-3
Type :
conf
DOI :
10.1109/IEMBS.2007.4352603
Filename :
4352603
Link To Document :
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