Study of myographic signals from sternomastoid muscle in patients with chronic obstructive pulmonary disease.
Analysis of the respiratory muscle activity is a promising technique for diagnosis of respiratory diseases, such as chronic obstructive pulmonary disease (COPD). The sternomastoid muscle (SMM) was selected to study the activity of respiratory muscles due to its accessibility in order to define a noninvasive analysis. The aims of this work are two: analyze the relationship between the SMM function and pulmonary obstruction, and study the influence of spectral estimator on frequency parameters related with the muscle activity. For the first goal, we propose the analysis of vibromyographic and electromyographic signals from the SMM to study the muscle function during two ventilatory tests. Activity of SMM was found by means of several indexes: root-mean-square (rms) values, mean and median frequencies, and ratio between high and low-frequency components. For the second goal, spectral analysis was performed by means of nonparametric methods: Correlogram and Welch periodogram, and parametric methods: autoregressive (AR), moving average (MA), and ARMA models. It is deduced that these indexes show muscle activity and certain fatigue of the SMM, whose muscle function depends on the level of pulmonary obstruction, and they depend a lot of spectral estimator being the more suitable an AR model with high order.
Mañanas
M A
MA
ESAII Department, Centre de Recerca en Enginyeria Biomèdica, Universitat Politècnica de Catalunya, Barcelona, Spain. manyanas@creb.upc.es
Jané
R
R
Fiz
J A
JA
Morera
J
J
Caminal
P
P
D000368:Aged; D004576:Electromyography; D006801:Humans; D016014:Linear Models; D008173:Lung Diseases, Obstructive / Q000503:physiopathology*; D008297:Male; D018763:Muscle Fatigue / Q000502:physiology; D012132:Respiratory Muscles / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D018709:Statistics, Nonparametric; D014732:Vibration