195 related articles for article (PubMed ID: 1297013)
21. Automated decomposition of intramuscular electromyographic signals.
Florestal JR; Mathieu PA; Malanda A
IEEE Trans Biomed Eng; 2006 May; 53(5):832-9. PubMed ID: 16686405
[TBL] [Abstract][Full Text] [Related]
22. Rigorous a posteriori assessment of accuracy in EMG decomposition.
McGill KC; Marateb HR
IEEE Trans Neural Syst Rehabil Eng; 2011 Feb; 19(1):54-63. PubMed ID: 20639182
[TBL] [Abstract][Full Text] [Related]
23. A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients.
Zennaro D; Wellig P; Koch VM; Moschytz GS; Läubli T
IEEE Trans Biomed Eng; 2003 Jan; 50(1):58-69. PubMed ID: 12617525
[TBL] [Abstract][Full Text] [Related]
24. Comparison of F-waves of motor unit action potentials activated during voluntary contraction.
Yamada M
Electromyogr Clin Neurophysiol; 2004; 44(1):29-34. PubMed ID: 15008022
[TBL] [Abstract][Full Text] [Related]
25. EMG signal decomposition: how can it be accomplished and used?
Stashuk D
J Electromyogr Kinesiol; 2001 Jun; 11(3):151-73. PubMed ID: 11335147
[TBL] [Abstract][Full Text] [Related]
26. Single channel surface electromyogram deconvolution to explore motor unit discharges.
Mesin L
Med Biol Eng Comput; 2019 Sep; 57(9):2045-2054. PubMed ID: 31350669
[TBL] [Abstract][Full Text] [Related]
27. Robust decomposition of single-channel intramuscular EMG signals at low force levels.
Marateb HR; Muceli S; McGill KC; Merletti R; Farina D
J Neural Eng; 2011 Dec; 8(6):066015. PubMed ID: 22063475
[TBL] [Abstract][Full Text] [Related]
28. Can standard surface EMG processing parameters be used to estimate motor unit global firing rate?
Zhou P; Rymer WZ
J Neural Eng; 2004 Jun; 1(2):99-110. PubMed ID: 15876628
[TBL] [Abstract][Full Text] [Related]
29. Decomposition of surface EMG signals from cyclic dynamic contractions.
De Luca CJ; Chang SS; Roy SH; Kline JC; Nawab SH
J Neurophysiol; 2015 Mar; 113(6):1941-51. PubMed ID: 25540220
[TBL] [Abstract][Full Text] [Related]
30. Improved online decomposition of non-stationary electromyogram via signal enhancement using a neuron resonance model: a simulation study.
Zheng Y; Xu G; Li Y; Qiang W
J Neural Eng; 2022 Apr; 19(2):. PubMed ID: 35303735
[No Abstract] [Full Text] [Related]
31. Classification of Action Potentials With High Variability Using Convolutional Neural Network for Motor Unit Tracking.
Li Y; Zheng Y; Xu G; Zhang S; Liang R; Ji R
IEEE Trans Neural Syst Rehabil Eng; 2024; 32():905-914. PubMed ID: 38335077
[TBL] [Abstract][Full Text] [Related]
32. Using two-dimensional spatial information in decomposition of surface EMG signals.
Kleine BU; van Dijk JP; Lapatki BG; Zwarts MJ; Stegeman DF
J Electromyogr Kinesiol; 2007 Oct; 17(5):535-48. PubMed ID: 16904342
[TBL] [Abstract][Full Text] [Related]
33. Correlation-based decomposition of surface electromyograms at low contraction forces.
Holobar A; Zazula D
Med Biol Eng Comput; 2004 Jul; 42(4):487-95. PubMed ID: 15320457
[TBL] [Abstract][Full Text] [Related]
34. An evaluation of the utility and limitations of counting motor unit action potentials in the surface electromyogram.
Zhou P; Rymer WZ
J Neural Eng; 2004 Dec; 1(4):238-45. PubMed ID: 15876644
[TBL] [Abstract][Full Text] [Related]
35. Motor unit action potential conduction velocity estimated from surface electromyographic signals using image processing techniques.
Soares FA; Carvalho JL; Miosso CJ; de Andrade MM; da Rocha AF
Biomed Eng Online; 2015 Sep; 14():84. PubMed ID: 26384112
[TBL] [Abstract][Full Text] [Related]
36. Analysis of intramuscular electromyogram signals.
Merletti R; Farina D
Philos Trans A Math Phys Eng Sci; 2009 Jan; 367(1887):357-68. PubMed ID: 19008187
[TBL] [Abstract][Full Text] [Related]
37. Validation of a computer-aided EMG decomposition method.
McGill KC; Lateva ZC; Johanson ME
Conf Proc IEEE Eng Med Biol Soc; 2004; 2004():4744-7. PubMed ID: 17271369
[TBL] [Abstract][Full Text] [Related]
38. A simulation study on the relation between the motor unit depth and action potential from multi-channel surface electromyography recordings.
He J; Luo Z
J Clin Neurosci; 2018 Aug; 54():146-151. PubMed ID: 29805080
[TBL] [Abstract][Full Text] [Related]
39. Decomposing single-channel intramuscular electromyography signal sampled at a low frequency into its motor unit action potential trains with a generative adversarial network.
Sun W; Tang R; Lang Y; He J; Qiang H
J Electromyogr Kinesiol; 2019 Oct; 48():187-196. PubMed ID: 31408753
[TBL] [Abstract][Full Text] [Related]
40. Rigorous performance assessment of the algorithms for resolving motor unit action potential superpositions.
Shirzadi M; Marateb HR; McGill KC; Mañanas MA
J Electromyogr Kinesiol; 2021 Feb; 56():102510. PubMed ID: 33341461
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
