124 related articles for article (PubMed ID: 18710816)
1. Spherical classification of wavelet transformed EMG intensity patterns.
von Tscharner V
J Electromyogr Kinesiol; 2009 Oct; 19(5):e334-44. PubMed ID: 18710816
[TBL] [Abstract][Full Text] [Related]
2. Analysis and classification of compressed EMG signals by wavelet transform via alternative neural networks algorithms.
Ozsert M; Yavuz O; Durak-Ata L
Comput Methods Biomech Biomed Engin; 2011 Jun; 14(6):521-5. PubMed ID: 20645198
[TBL] [Abstract][Full Text] [Related]
3. Electromyographic assessment of trunk muscle activation amplitudes during a simulated lifting task using pattern recognition techniques.
Butler HL; Hubley-Kozey CL; Kozey JW
J Electromyogr Kinesiol; 2009 Dec; 19(6):e505-12. PubMed ID: 19041264
[TBL] [Abstract][Full Text] [Related]
4. A pattern recognition technique to characterize the differential modulation of co-activating muscles at the performer/environment interface.
Pelland L; McKinley P
J Electromyogr Kinesiol; 2004 Oct; 14(5):539-54. PubMed ID: 15301773
[TBL] [Abstract][Full Text] [Related]
5. Optimized wavelets for blind separation of nonstationary surface myoelectric signals.
Farina D; Lucas MF; Doncarli C
IEEE Trans Biomed Eng; 2008 Jan; 55(1):78-86. PubMed ID: 18232349
[TBL] [Abstract][Full Text] [Related]
6. Principal components analysis preprocessing for improved classification accuracies in pattern-recognition-based myoelectric control.
Hargrove LJ; Li G; Englehart KB; Hudgins BS
IEEE Trans Biomed Eng; 2009 May; 56(5):1407-14. PubMed ID: 19473932
[TBL] [Abstract][Full Text] [Related]
7. Surface myoelectric signal classification for prostheses control.
Al-Assaf Y; Al-Nashash H
J Med Eng Technol; 2005; 29(5):203-7. PubMed ID: 16126579
[TBL] [Abstract][Full Text] [Related]
8. Classification of multi muscle activation patterns of osteoarthritis patients during level walking.
von Tscharner V; Valderrabano V
J Electromyogr Kinesiol; 2010 Aug; 20(4):676-83. PubMed ID: 20005128
[TBL] [Abstract][Full Text] [Related]
9. Fatigue estimation using a novel multi-fractal detrended fluctuation analysis-based approach.
Talebinejad M; Chan AD; Miri A
J Electromyogr Kinesiol; 2010 Jun; 20(3):433-9. PubMed ID: 19589697
[TBL] [Abstract][Full Text] [Related]
10. Electrode placement over the innervation zone affects the low-, not the high-frequency portion of the EMG frequency spectrum.
Beck TW; Housh TJ; Cramer JT; Stout JR; Ryan ED; Herda TJ; Costa PB; Defreitas JM
J Electromyogr Kinesiol; 2009 Aug; 19(4):660-6. PubMed ID: 18479940
[TBL] [Abstract][Full Text] [Related]
11. Feature extraction of the first difference of EMG time series for EMG pattern recognition.
Phinyomark A; Quaine F; Charbonnier S; Serviere C; Tarpin-Bernard F; Laurillau Y
Comput Methods Programs Biomed; 2014 Nov; 117(2):247-56. PubMed ID: 25023536
[TBL] [Abstract][Full Text] [Related]
12. Spatial correlation of high density EMG signals provides features robust to electrode number and shift in pattern recognition for myocontrol.
Stango A; Negro F; Farina D
IEEE Trans Neural Syst Rehabil Eng; 2015 Mar; 23(2):189-98. PubMed ID: 25389242
[TBL] [Abstract][Full Text] [Related]
13. Classification of finger activation for use in a robotic prosthesis arm.
Peleg D; Braiman E; Yom-Tov E; Inbar GF
IEEE Trans Neural Syst Rehabil Eng; 2002 Dec; 10(4):290-3. PubMed ID: 12611366
[TBL] [Abstract][Full Text] [Related]
14. Investigation of optimum electrode locations by using an automatized surface electromyography analysis technique.
Nishihara K; Kawai H; Gomi T; Terajima M; Chiba Y
IEEE Trans Biomed Eng; 2008 Feb; 55(2 Pt 1):636-42. PubMed ID: 18269999
[TBL] [Abstract][Full Text] [Related]
15. Hybrid independent component analysis and twin support vector machine learning scheme for subtle gesture recognition.
Naik GR; Kumar DK; Jayadeva
Biomed Tech (Berl); 2010 Oct; 55(5):301-7. PubMed ID: 20840006
[TBL] [Abstract][Full Text] [Related]
16. Removing ECG contamination from EMG recordings: a comparison of ICA-based and other filtering procedures.
Willigenburg NW; Daffertshofer A; Kingma I; van Dieën JH
J Electromyogr Kinesiol; 2012 Jun; 22(3):485-93. PubMed ID: 22296869
[TBL] [Abstract][Full Text] [Related]
17. Classification of muscle activity based on effort level during constant pace running.
Stirling LM; von Tscharner V; Kugler PF; Nigg BM
J Electromyogr Kinesiol; 2011 Aug; 21(4):566-71. PubMed ID: 21459608
[TBL] [Abstract][Full Text] [Related]
18. Motor unit action potential duration, II: a new automatic measurement method based on the wavelet transform.
Rodríguez I; Gila L; Malanda A; Gurtubay IG; Mallor F; Gómez S; Navallas J; Rodríguez J
J Clin Neurophysiol; 2007 Feb; 24(1):59-69. PubMed ID: 17277580
[TBL] [Abstract][Full Text] [Related]
19. Classification of surface EMG signal with fractal dimension.
Hu X; Wang ZZ; Ren XM
J Zhejiang Univ Sci B; 2005 Aug; 6(8):844-8. PubMed ID: 16052721
[TBL] [Abstract][Full Text] [Related]
20. Hands-free human computer interaction via an electromyogram-based classification algorithm.
Chin C; Barreto A; Li C; Zhai J
Biomed Sci Instrum; 2005; 41():31-6. PubMed ID: 15850078
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
