Lozano-García Manuel, Estrada Luis, Jané Raimon
Biomedical Signal Processing and Interpretation group, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), UPC Campus Diagonal-Besòs, Av. d'Eduard Maristany 10-14, 08930 Barcelona, Spain.
Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 08028 Barcelona, Spain.
Entropy (Basel). 2019 Feb 15;21(2):183. doi: 10.3390/e21020183.
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.
固定样本熵（fSampEn）已成功应用于肌电图信号以估计吸气肌活动，减少心脏活动的干扰。然而，根据应用的不同，已提出了几个fSampEn参数值，并且对于最佳值没有共识标准。本研究旨在对肌电图呼吸信号中最相关的fSampEn参数的性能进行全面评估，并首次提出一组最佳的通用fSampEn参数，以正确估计吸气肌活动。使用fSampEn参数的不同组合来计算无创和金标准有创肌电图呼吸信号中的fSampEn。所有信号均在健康受试者和慢性阻塞性肺疾病患者的异质群体中进行负荷呼吸时记录，从而能够评估fSampEn在各种吸气肌激活水平下的性能。通过fSampEn时间序列与吸气肌产生的口腔压力和跨膈压力的互协方差来评估fSampEn的性能。提出了一组最佳的通用fSampEn参数，允许比较不同受试者的fSampEn，并有助于改善对健康和疾病状态下吸气肌活动的评估。
