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Influence of the Fuzzy Function on the Estimation of the Fuzzy Sample Entropy with Fixed Tolerance Values for the Evaluation of Surface EMG Muscle Activity

文献类型： 会议论文

第一作者： Abel Torres

作者： Abel Torres 1 ; Luis Estrada-Petrocelli 2 ;

作者机构： 1.The Institut de Bioenginyeria de Catalunya (IBEC), The Barcelona Institute of Science and Technology (BIST), Universitat Politècnica de Catalunya · BarcelonaTech (UPC)|Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain

2.Facultad de Ingeniería, Universidad Latina de Panamá, Panama City, Republic of Panama

关键词： Estimation;Muscles;Entropy;Electromyography;Biology

会议名称： Annual International Conference of the IEEE Engineering in Medicine and Biology Society

主办单位：

页码： 1-4

摘要： Fixed sample entropy (fSampEn) is a technique that has demonstrated superior performance to other amplitude estimators for assessing respiratory muscle electromyographic activity. This technique is based on the calculation of sample entropy (SampEn) using fixed tolerance thresholds. Fuzzy entropy (FuzzyEn) introduces an improvement to the SampEn algorithm based on the use of a fuzzy measure to evaluate the similarity between vectors. However, several fuzzy functions have been used to calculate the FuzzyEn, and not all of them allow an effective comparison with the SampEn calculation parameters. In the present work, an analysis of the different fuzzy functions previously used has been carried out and a new sigmoid fuzzy function for the calculation of FuzzyEn with fixed tolerance thresholds (fFuzzyEn) has been proposed. The results show that the proposed fuzzy function outperformed both fSampEn and previously proposed FuzzyEn-based algorithms. These results suggest that fFuzzyEn could improve the assessment of muscle activity providing potentially useful diagnostic information.Clinical Relevance— This sets out the appropriate use of the fuzzy function for the estimation of the fuzzy sample entropy with fixed tolerance thresholds (fFuzzyEn). The use of fFuzzyEn could improve methods for detecting the onset and offset of respiratory electromyographic (EMG) signals, as well as the assessment of EMG activation level.

分类号： q81

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