Detailed Information on Publication Record
2023
Diagnostic accuracy of Tensiomyography parameters for monitoring peripheral neuromuscular fatigue
KALC, Miloš, Katarina PUŠ, Armin PARAVLIĆ, Jure URBANC, Boštjan ŠIMUNIČ et. al.Basic information
Original name
Diagnostic accuracy of Tensiomyography parameters for monitoring peripheral neuromuscular fatigue
Authors
KALC, Miloš (705 Slovenia), Katarina PUŠ (705 Slovenia), Armin PARAVLIĆ (688 Serbia, guarantor, belonging to the institution), Jure URBANC (705 Slovenia) and Boštjan ŠIMUNIČ (705 Slovenia)
Edition
JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY, ENGLAND, ELSEVIER SCI LTD, 2023, 1050-6411
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
30306 Sport and fitness sciences
Country of publisher
Slovenia
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 2.500 in 2022
RIV identification code
RIV/00216224:14510/23:00134787
Organization unit
Faculty of Sports Studies
UT WoS
000985118200001
Keywords in English
TMG; Vastus lateralis; MVC; Twitch
Změněno: 23/4/2024 14:39, Ing. Petra Svobodníková
Abstract
V originále
The diagnostic accuracy of tensiomyography (TMG) parameters compared to the gold standard in neuromuscular fatigue evaluation using voluntary and electrically induced muscle activation is unclear. This study aimed to investigate the diagnostic accuracy of TMG parameters to detect individual changes after interventions that were designed to induce central or peripheral fatigue. Nineteen males (age: 32.2 +/- 9.3 years) performed two interventions, consisting of maintaining 25% of maximal voluntary contraction (MViC25%) and a 30 s all-out cycling test (Wingate), respectively. TMG parameters, maximum voluntary contraction (PtMViC), voluntary activation (VA%) and electrically elicited double twitches (Dtw) were assessed on the knee extensors before (PRE), one minute (POST) and seven minutes after (POST7) the intervention. The diagnostic accuracy (AUC) of TMG parameters were evaluated in comparison to two criteria measures (PtMViC and Dtw). RM ANOVA revealed a significant interaction between the effects of intervention and time on VA% (p = 0.001) and Dtw (p < 0.001) but not for PtMViC (p = 0.420). AUC showed that TMG parameters had a good ability in detecting muscular fatigue assessed by Dtw but not by PtMViC. The results of the current study suggest that TMG parameters can be used to monitor peripheral neuromuscular fatigue.