Respiratory rate detection by empirical mode decomposition method applied to diaphragm mechanomyographic signals
Document typeConference report
Rights accessRestricted access - publisher's policy
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 (RRMmg) was compared with that measured from inspiratory pressure signal (RRP). 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 RRmmg and RRP 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.
CitationEstrada, L. [et al.]. Respiratory rate detection by empirical mode decomposition method applied to diaphragm mechanomyographic signals. A: International Conference of the IEEE Engineering in Medicine and Biology Society. "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)". Chicago: 2014, p. 3204-3207.
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Ponències/Comunicacions de congressos 
- IBEC - Institute for Bioengineering of Catalonia - Ponències/Comunicacions de congressos 
- BIOSPIN - Biomedical Signal Processing and Interpretation - Ponències/Comunicacions de congressos