A wavelet multiscale based method to separate the high and low frequency components of mechanomyographic signals

Noninvasive measurement of inspiratory muscle performance by means of diaphragm muscle mechanomyographic signals in COPD patients during an incremental load respiratory test

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.

Evaluation of the respiratory muscular function by means of diaphragmatic mechanomyographic signals in COPD patients

The study of mechanomyographic (MMG) signals of respiratory muscles is a promising technique in order to evaluate the respiratory muscular effort. In this work MMG signals from left and right hemidiaphragm (MMGl and MMGr, respectively) acquired during a respiratory protocol have been analyzed. The acquisition of both MMG signals was carried out by means of two capacitive accelerometers placed on both left and right sides of the costal wall. The signals were recorded in a group of six patients with Chronic Obstructive Pulmonary Disease (COPD). It has been observed that with the increase of inspiratory pressure it takes place an increase of the amplitude and a displacement toward low frequencies in both left and right MMG signals. Furthermore, it has been seen that the increase of amplitude and the decrease of frequency in MMG signals are more pronounced in severe COPD patients. This behaviour is similar for both MMGl and MMGr signals. Results suggest that the use of MMG signals could be potentially useful for the evaluation of the respiratory muscular function in COPD patients.

Inspiratory pressure evaluation by means of the entropy of respiratory mechanomyographic signals

The study of the mechanomyographic (MMG) signal of respiratory muscles is a promising technique in order to evaluate the respiratory muscles effort. The relationship between amplitude and power parameters of this signal with the respiratory effort performed during respiration is of great interest for researchers and physicians due to its diagnostic potentials. In this study, it was analyzed the MMG signal of the diaphragm muscle acquired by means of a capacitive accelerometer applied on the costal wall. The new methodology investigated was based in the calculation of the Shannon entropy of the MMG signal during the diaphragm muscle voluntary contraction. The method was tested in an animal model, with two incremental respiratory protocols performed by two non anesthetized mongrel dogs. The results obtained in the respiratory tests analyzed indicate that the Shannon entropy was superior to other amplitude parameter methods, obtaining higher correlation coefficients (with p-values lower than 0.001) with the mean and maximum inspiratory pressures. Furthermore in this study we have proposed a moving mode high pass filter in order to eliminate the very low frequency component recorded by the sensor and due to movement artifacts and the gross movement of the thorax during respiration. With this non linear filtering method we have obtained higher correlation coefficients (with both entropy and amplitude parameters) than with the Wavelet multiresolution technique proposed in a previous work.