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For: Huang LK, Huang LN, Gao YM, Lucev Vasic Z, Cifrek M, Du M. Electrical Impedance Myography Applied to Monitoring of Muscle Fatigue During Dynamic Contractions. IEEE Access 2020;8:13056-65. [DOI: 10.1109/access.2020.2965982] [Cited by in Crossref: 12] [Cited by in F6Publishing: 12] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Zhu H, Ji Y, Wang B, Kang Y. Exercise fatigue diagnosis method based on short-time Fourier transform and convolutional neural network. Front Physiol 2022;13:965974. [DOI: 10.3389/fphys.2022.965974] [Reference Citation Analysis]
2 Shi J, Liu Y, Yan H, Gao Y, Vasic ZL, Cifrek M. Detection of low back muscle state based on electrical impedance myography. 2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC) 2022. [DOI: 10.1109/imbioc52515.2022.9790108] [Reference Citation Analysis]
3 Zhang X, Xu P, Wei Z, Gao Y, Vasic ZL, Cifrek M. EIM multi-frequency Measurement System Based on Virtual Instrument. 2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC) 2022. [DOI: 10.1109/imbioc52515.2022.9790155] [Reference Citation Analysis]
4 Zhou B, Zhuang Y, Gao Y, Vasic ZL, Culjak I, Cifrek M, Du M. Electrical Impedance Myography for Evaluating Muscle Fatigue Induced by Neuromuscular Electrical Stimulation. IEEE J Electromagn RF Microw Med Biol 2022;6:94-102. [DOI: 10.1109/jerm.2021.3092883] [Reference Citation Analysis]
5 Luo X, Wang S, Terrones BS. Modeling and Simulation of Needle Electrical Impedance Myography in Nonhomogeneous Isotropic Skeletal Muscle. IEEE J Electromagn RF Microw Med Biol 2022;6:103-110. [DOI: 10.1109/jerm.2021.3091515] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Rodrigues E, Dario León Bueno de Camargo E, Luppi Silva O. Architecture and Calibration of a Multi-channel Electrical Impedance Myographer. Bioinformatics and Biomedical Engineering 2022. [DOI: 10.1007/978-3-031-07704-3_13] [Reference Citation Analysis]
7 Zhang Y, Chen S, Cao W, Guo P, Gao D, Wang M, Zhou J, Wang T. MFFNet: Multi-dimensional Feature Fusion Network based on attention mechanism for sEMG analysis to detect muscle fatigue. Expert Systems with Applications 2021;185:115639. [DOI: 10.1016/j.eswa.2021.115639] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 3.5] [Reference Citation Analysis]
8 Wang JN, Zhou HY, Gao YM, Yang JJ, Lučev Vasić Ž, Cifrek M, Du M. Optimization of the electrode configuration of electrical impedance myography for wearable application. Automatika 2020;61:475-81. [DOI: 10.1080/00051144.2020.1783615] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
9 Li D, Huang L, Wen Y, Gao Y, Vasic ZL, Cifrek M, Du M. Analysis of Electrical Impedance Myography Electrodes Configuration for Local Muscle Fatigue Evaluation Based on Finite Element Method. IEEE Access 2020;8:172233-43. [DOI: 10.1109/access.2020.3025150] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]