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.
Torres
Abel
A
Department of Systtems Engineering, Biomedical Engineering Research Centre, Politechnical University of Catalonia, Barcelona, Spain. abel.torres@upc.edu
Fiz
José A
JA
Galdiz
Juan B
JB
Gea
Joaquim
J
Morera
Josep
J
Jané
Raimon
R
D000818:Animals; D004285:Dogs; D004576:Electromyography / Q000295:instrumentation; D019277:Entropy; D004867:Equipment Design; D001239:Inhalation; D015233:Models, Statistical; D009119:Muscle Contraction; D018482:Muscle, Skeletal / Q000473:pathology*; D009132:Muscles / Q000473:pathology; D009213:Myography / Q000295:instrumentation* / Q000379:methods*; D011312:Pressure; D012119:Respiration; D012815:Signal Processing, Computer-Assisted; D013909:Thorax