title: Noninvasive measurement of inspiratory muscle performance by means of diaphragm muscle mechanomyographic signals in COPD patients during an incremental load respiratory test.
abstract: The study of mechanomyographic (MMG) signals of respiratory muscles is a promising noninvasive technique in order to evaluate the respiratory muscular effort and efficiency. In this work, the MMG signal of the diaphragm muscle it is evaluated in order to assess the respiratory muscular function in Chronic Obstructive Pulmonary Disease (COPD) patients. The MMG signals from left and right hemidiaphragm were acquired using two capacitive accelerometers placed on both left and right sides of the costal wall surface. The MMG signals and the inspiratory pressure signal were acquired while the COPD patients carried out an inspiratory load respiratory test. The population of study is composed of a group of 6 patients with severe COPD (FEV1>50% ref and DLCO < 50% ref). We have found high positive correlation coefficients between the maximum inspiratory pressure (IPmax) developed in a respiratory cycle and different amplitude parameters of both left and right MMG signals (RMS, left: 0.68 ± 0.11 - right: 0.69 ± 0.12; Rényi entropy, left: 0.73 ± 0.10 - right: 0.77 ± 0.08; Multistate Lempel-Ziv, left: 0.73 ± 0.17 - right: 0.74 ± 0.08), and negative correlation between the Pmax and the maximum frequency of the MMG signal spectrum (left: -0.39 ± 0.19 - right: -0.65 ± 0.09). Furthermore, we found that the slope of the evolution of the MMG amplitude parameters, as the load increases during the respiratory test, has positive correlation with the %FEV1/FVC pulmonary function test parameter of the six COPD patients analyzed (RMS, left: 0.38 - right: 0.41; Rényi entropy, left: 0.45 - right: 0.63; Multistate Lempel-Ziv, left: 0.39 - right: 0.64). These results suggest that the information provided by MMG signals could be used in order to evaluate the respiratory effort and the muscular efficiency in COPD patients.
authors.affiliation: Dept. ESAII, Universitat Politècnica de Catalunya, Institut de Bioenginyeria de Catalunya (IBEC) and CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBERBBN), Barcelona, Spain. abel.torres@upc.edu
authors.forename: Abel
authors.initials: A
authors.lastname: Torres
authors.forename: Leonardo
authors.initials: L
authors.lastname: Sarlabous
authors.forename: Jose A
authors.initials: JA
authors.lastname: Fiz
authors.forename: Joaquim
authors.initials: J
authors.lastname: Gea
authors.forename: Juana M
authors.initials: JM
authors.lastname: Martinez-Llorens
authors.forename: J
authors.initials: J
authors.lastname: Morera
authors.forename: Raimon
authors.initials: R
authors.lastname: Jane
mesh_terms: D000368:Aged; D001696:Biomechanical Phenomena; D003964:Diaphragm / Q000473:pathology; D004576:Electromyography / Q000295:instrumentation / Q000379:methods*; D005541:Forced Expiratory Volume; D006801:Humans; D001239:Inhalation / Q000502:physiology*; D008875:Middle Aged; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis / Q000503:physiopathology*; D015203:Reproducibility of Results; D012119:Respiration; D012129:Respiratory Function Tests; D015656:Respiratory Mechanics / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D035441:Thoracic Wall / Q000473:pathology