Performance Evaluation of Fixed Sample Entropy in Myographic Signals for Inspiratory Muscle Activity Estimation

Abstract

Fixed sample entropy (fSampEn) has been successfully applied to myographic signals for inspiratory muscle activity estimation, attenuating interference from cardiac activity. However, several values have been suggested for fSampEn parameters depending on the application, and there is no consensus standard for optimum values. This study aimed to perform a thorough evaluation of the performance of the most relevant fSampEn parameters in myographic respiratory signals, and to propose, for the first time, a set of optimal general fSampEn parameters for a proper estimation of inspiratory muscle activity. Different combinations of fSampEn parameters were used to calculate fSampEn in both non-invasive and the gold standard invasive myographic respiratory signals. All signals were recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing, thus allowing the performance of fSampEn to be evaluated for a variety of inspiratory muscle activation levels. The performance of fSampEn was assessed by means of the cross-covariance of fSampEn time-series and both mouth and transdiaphragmatic pressures generated by inspiratory muscles. A set of optimal general fSampEn parameters was proposed, allowing fSampEn of different subjects to be compared and contributing to improving the assessment of inspiratory muscle activity in health and disease.

Noninvasive Assessment of Inspiratory Muscle Neuromechanical Coupling During Inspiratory Threshold Loading

“…2), using a moving window of 500 ms with a 50-ms step, m equal to 2 and r equal to 0.05 (fSEoesEMG di ), 0.3 (fSEsEMG lic ), and 0.5 (fSE|sMMG lic |) times the global standard deviation of each signal. These are the optimal general fSampEn parameters for inspiratory muscle activity estimation as we previously described [34].…”

Combining Bioimpedance and Myographic Signals for the Assessment of COPD During Loaded Breathing

“…Then, the sM M G lic signals were resampled to 200 Hz and band-pass filtered by a highpass filter (zero-phase 8 th order Butterworth, f c = 5 Hz) and a low-pass filter (zero-phase 8 th order Butterworth, f c = 40 Hz). The global acceleration |sM M G lic | was obtained as the Euclidian norm of the acceleration in each axis [31].…”

“…The selection of fSampEn parameters is important when assessing respiratory effort using myographic signals [34]. Consequently, we selected the fSampEn parameters following the conclusions of the Lozano-Garcia et al [31] study where different combinations of fSampEn parameters were evaluated in terms of their ability to estimate inspiratory muscle activity. We used windows lengths of 500 ms with a 90 % of overlap, an embedded dimension of 2 and a tolerance of 0.2 for sEM G lic and 0.5 for |sM M G lic |.…”

“…The most common embedding dimensions for SampEn calculation are 1 and 2, and no relevant differences between these values were reported in myographic signals [34]. On the other hand, the tolerance parameter influences the performance of fSampEn as it was shown in [31]. Although the current study did not include an analysis of the fSampEn parameters performance, we selected these parameters values according to the good results shown in myographic respiratory signals [18].…”

“…The selection of fSampEn parameters is an important issue when assessing respiratory muscle effort and consequently, we selected them based on previous studies findings in myographic respiratory signals [18], [31], [34]. The most common embedding dimensions for SampEn calculation are 1 and 2, and no relevant differences between these values were reported in myographic signals [34].…”