Paper Info
Title
Respiratory rate detection by empirical mode decomposition method applied to diaphragm mechanomyographic signals.
Abstract
Non-invasive evaluation of respiratory activity is an area of increasing research interest, resulting in the appearance of new monitoring techniques, ones of these being based on the analysis of the diaphragm mechanomyographic (MMGdi) signal. The MMGdi signal can be decomposed into two parts: (1) a high frequency activity corresponding to lateral vibration of respiratory muscles, and (2) a low frequency activity related to excursion of the thoracic cage. The purpose of this study was to apply the empirical mode decomposition (EMD) method to obtain the low frequency of MMGdi signal and selecting the intrinsic mode functions related to the respiratory movement. With this intention, MMGdi signals were acquired from a healthy subject, during an incremental load respiratory test, by means of two capacitive accelerometers located at left and right sides of rib cage. Subsequently, both signals were combined to obtain a new signal which contains the contribution of both sides of thoracic cage. Respiratory rate (RR) measured from the mechanical activity (RR(MMG)) was compared with that measured from inspiratory pressure signal (RR(P)). Results showed a Pearson's correlation coefficient (r = 0.87) and a good agreement (mean bias = -0.21 with lower and upper limits of -2.33 and 1.89 breaths per minute, respectively) between RR(MMG) and RR(P) measurements. In conclusion, this study suggests that RR can be estimated using EMD for extracting respiratory movement from low mechanical activity, during an inspiratory test protocol.
Year
DOI
Venue
2014
10.1109/EMBC.2014.6944304
EMBC
Keywords
Field
DocType
inspiratory pressure signal,pearsons correlation coefficient,empirical mode decomposition method,rib cage,capacitive accelerometer,diaphragm mechanomyographic signals,emd method,biomedical measurement,thoracic cage,incremental load respiratory test,pneumodynamics,medical signal processing,respiratory rate detection,mmgdi signal,mechanical activity,intrinsic mode function,respiratory movement,empirical mode decomposition,accelerometers,estimation,band pass filters
Correlation coefficient,Diaphragm (structural system),Computer science,Accelerometer,Rib cage,Respiratory rate,Electronic engineering,Respiratory system,Vibration,Hilbert–Huang transform
Conference
Volume
ISSN
Citations 
2014
1557-170X
2
PageRank 
References 
Authors
0.46
2
5
Name
Order
Citations
PageRank
Luis Estrada1226.84
Abel Torres2196.63
Leonardo Sarlabous3186.57
José Antonio Fiz4153.55
R Jané513143.71