Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/50948
Título: Effects of strength training on muscle fatigue mapping from surface EMG and blood metabolites
Autores/as: Izquierdo, Mikel 
González-Izal, Miriam
Navarro-Amezqueta, Ion
Calbet, Jose A L 
Ibañez, Javier
Malanda, Armando
Mallor, Fermin
Häkkinen, Keijo
Kraemer, William J.
Gorostiaga, Esteban M.
Clasificación UNESCO: 241106 Fisiología del ejercicio
Palabras clave: SURFACE ELECTROMYOGRAPHY
MEAN AVERAGE VOLTAGE
POWER OUTPUT
NEUROMUSCULAR ADAPTATIONS
DYNAMIC CONTRACTION
Fecha de publicación: 2011
Editor/a: 0195-9131
Publicación seriada: Medicine and Science in Sports and Exercise 
Resumen: Purpose: This study examined the effects of heavy resistance training on the relationships between power loss and surface EMG (sEMG) indices and blood metabolite concentrations on dynamic exercise-induced fatigue with the same relative load as in pretraining. Methods: Twelve trained subjects performed five sets consisting of 10 repetitions in the leg press, with 2 min of rest between sets before and after a strength training period. sEMG variables (the mean average voltage, the median spectral frequency, and the Dimitrov spectral index of muscle fatigue) from vastus medialis and lateralis muscles and metabolic responses (i.e., blood lactate, uric acid, and ammonia concentrations) were measured. Results: The peak power loss after the posttraining protocol was greater (61%) than the decline observed in the pretraining protocol (46%). Similar sEMG changes were found for both protocols, whereas higher metabolic demand was observed during the posttraining exercise. The linear models on the basis of the relations found between power loss and changes in sEMG variables were significantly different between pretraining and posttraining, whereas the linear models on the basis of the relations between power loss and changes in blood metabolite concentrations were similar. Conclusions: Linear models that use blood metabolites to map acute exercise-induced peak power changes were more accurate in detecting these changes before and after a short-term training period, whereas an attempt to track peak power loss using sEMG variables may fail after a strength training period.
URI: http://hdl.handle.net/10553/50948
ISSN: 0195-9131
DOI: 10.1249/MSS.0b013e3181edfa96
Fuente: Medicine and Science in Sports and Exercise[ISSN 0195-9131],v. 43, p. 303-311
Colección:Artículos
Vista completa

Citas SCOPUSTM   

44
actualizado el 15-dic-2024

Citas de WEB OF SCIENCETM
Citations

43
actualizado el 15-dic-2024

Visitas

74
actualizado el 23-dic-2023

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.