Interpretation of the surface electromyogram in dynamic contractions

Exercise and Sport Sciences Reviews

Volumn 34, Issue 3, 2006, Pages 121-127

  Farina, Dario ^a  

^a AALBORG UNIVERSITY   (Denmark)

Author keywords

Conduction velocity; Electrode shift; EMG amplitude; Spectral analysis; Stationarity; Timing of muscle activity; Volume conductor

Indexed keywords

AMPLITUDE MODULATION; CHRONOLOGY; ELECTRODE; ELECTROMYOGRAM; FUNCTIONAL ASSESSMENT; HUMAN; MEDICAL INFORMATICS; MUSCLE ACTION POTENTIAL; MUSCLE CONTRACTION; MUSCLE STRENGTH; NERVE CONDUCTION; PRIORITY JOURNAL; REVIEW; SIGNAL PROCESSING; SPECTROSCOPY;

DENMARK; ELECTROMYOGRAPHY; HUMANS; MUSCLE CONTRACTION;

EID: 33750282284     PISSN: 00916331     EISSN: None     Source Type: Journal    
DOI: 10.1249/00003677-200607000-00006     Document Type: Review

References (15)

1. Bonato, P. (guest editor). Recent advancements in the analysis of dynamic EMG data. IEEE Med. Biol. Mag. 20, 2001.
2. Bonato, P., S. H. Roy, M. Knaflitz, and C. J. De Luca. Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions. IEEE Trans. Biomed. Eng. 48:745-753, 2001.
3. Campanini, I., A. Merlo, P. Degola, R. Merletti, G. Vezzosi, and D. Farina. Effect of electrode location on EMG signal envelope in leg muscles during gait. J. Electromyogr. Kinesiol. In press.
4. Clancy, E. A., S. Bouchard, and D. Rancourt. Estimation and application of EMG amplitude during dynamic contractions. IEEE Med. Biol. Mag. 20:47-54, 2001.
5. De Luca, C. J., and R. Merletti. Surface myoelectric signal cross-talk among muscles of the leg. Electroencephalogr. Clin. Neurophysiol. 69:568-575, 1988.
6. Dimitrova, N. A., and G. V. Dimitrov. Interpretation of EMG changes with fatigue: facts, pitfalls, and fallacies. J. Electromyogr. Kinesiol. 13:13-36, 2003.
7. Farina, D., R. Merletti, M. Nazzaro, and I. Caruso. Effect of joint angle on EMG variables in leg and thigh muscles. IEEE Eng. Med. Biol. Mag. 20:62-71, 2001.
8. Farina, D., R. Merletti, and R. M. Enoka. The extraction of neural strategies from the surface EMG. J. Appl. Physiol. 96:1486-1495, 2004.
9. Farina, D., M. Pozzo, E. Merlo, A. Bottin, and R. Merletti. Assessment of average muscle fiber conduction velocity from surface EMG signals during fatiguing dynamic contractions. IEEE Trans. Biomed. Eng. 51:1383-1393, 2004.
10. Fuglevand, A. J., D. A. Winter, and A. E. Patla. Models of recruitment and rate coding organization in motor-unit pools. J. Neurophysiol. 70:2470-2488, 1993.
11. Hermens, H. J., B. Freriks, R. Merletti, D. F. Stegeman, J. Blok, G. Rau, C. Disselhorst-Klug, and G. Hägg. European Recommendations for Surface ElectroMyoGraphy. SENIAM 8, Roessingh Research and Development, Enschede (NL), 1999.
12. Lindstrom, L., and R. Magnusson. Interpretation of myoelectric power spectra: a model and its applications. Proc. IEEE 65:653-662, 1977.
13. Merletti, R., M. Knaflitz, and C. J. De Luca. Myoelectric manifestations of fatigue in voluntary and electrically elicited contractions. J. Appl. Physiol. 69:1810-1820, 1990.
14. Merlo, E., M. Pozzo, G. Antonutto, P. E. di Prampero, R. Merletti, and D. Farina. Time-frequency analysis and estimation of muscle fiber conduction velocity from surface EMG signals during explosive dynamic contractions. J. Neurosci. Methods 142:267-274, 2005.
15. Mesin, L., M. Joubert, T. Hanekom, R. Merletti, and D. Farina. A finite element model for describing the effect of muscle shortening on surface EMG. IEEE Trans. Biomed. Eng. 53:593-600, 2006.