Change in slope of conduction velocity linear regression as an indicator of muscle fatigue

Author(s):  
A.C.F. Souza ◽  
F.P. Schwartz ◽  
F.A.O. Nascimento ◽  
J.F. Souza
2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Akihiko Ando ◽  
Michiaki Miyamoto ◽  
Kazuhiko Kotani ◽  
Kenta Okada ◽  
Shoichiro Nagasaka ◽  
...  

The cardio-ankle vascular index (CAVI) is used to test vascular function and is an arterial stiffness marker and potential predictor of cardiovascular events. This study aimed to analyze the relation between objective indices of diabetic polyneuropathy (DPN) and the CAVI. One hundred sixty-six patients with type 2 diabetes mellitus were included in this study. We used nerve conduction studies (NCSs) and the coefficient of variation of the R-R interval to evaluate DPN. We estimated arteriosclerosis by the CAVI. Simple and multiple linear regression analyses were performed between neuropathy indices and the CAVI. In univariate analysis, the CAVI showed significant associations with sural sensory nerve conduction velocity and median F-wave conduction velocity. Multiple linear regression analysis for the CAVI showed that sural nerve conduction velocity and median F-wave conduction velocity were significant explanatory variables second only to age. In multiple linear regression analysis for sural nerve conduction velocity among neuropathy indices, the CAVI remained the most significant explanatory variable. In multiple linear regression analysis for median nerve F-wave conduction velocity among neuropathy indices, the CAVI remained the second most significant explanatory variable following HbA1c. These results suggest a close relationship between macroangiopathy and DPN.


2014 ◽  
Vol 30 (4) ◽  
pp. 312-321 ◽  
Author(s):  
Fabiano Peruzzo Schwartz ◽  
Martim Bottaro ◽  
Rodrigo Souza Celes ◽  
Maria Claudia Pereira ◽  
Valdinar de Araújo Rocha Júnior ◽  
...  

1990 ◽  
Vol 69 (5) ◽  
pp. 1810-1820 ◽  
Author(s):  
R. Merletti ◽  
M. Knaflitz ◽  
C. J. De Luca

The time course of muscle fiber conduction velocity and surface myoelectric signal spectral (mean and median frequency of the power spectrum) and amplitude (average rectified and root-mean-square value) parameters was studied in 20 experiments on the tibialis anterior muscle of 10 healthy human subjects during sustained isometric voluntary or electrically elicited contractions. Voluntary contractions at 20% maximal voluntary contraction (MVC) and at 80% MVC with duration of 20 s were performed at the beginning of each experiment. Tetanic electrical stimulation was then applied to the main muscle motor point for 20 s with surface electrodes at five stimulation frequencies (20, 25, 30, 35, and 40 Hz). All subjects showed myoelectric manifestations of muscle fatigue consisting of negative trends of spectral variables and conduction velocity and positive trends of amplitude variables. The main findings of this work are 1) myoelectric signal variables obtained from electrically elicited contractions show fluctuations smaller than those observed in voluntary contractions, 2) spectral variables are more sensitive to fatigue than conduction velocity and the average rectified value is more sensitive to fatigue than the root-mean-square value, 3) conduction velocity is not the only physiological factor affecting spectral variables, and 4) contractions elicited at supramaximal stimulation and frequencies greater than 30 Hz demonstrate myoelectric manifestations of muscle fatigue greater than those observed at 80% MVC sustained for the same time.


2008 ◽  
Vol 88 (9) ◽  
pp. 1061-1067 ◽  
Author(s):  
Cláudia Tarragô Candotti ◽  
Jefferson Fagundes Loss ◽  
Ana Maria Steffens Pressi ◽  
Flávio Antonio de Souza Castro ◽  
Marcelo La Torre ◽  
...  

Background and Purpose Pain is currently evaluated with “subjective” methods (eg, patient self-report). This study aimed to test whether fatigue indexes are able to accurately discriminate between subjects with and subjects without low back pain. Subjects Sixty subjects separated into 2 groups—a group with low back pain (n=30) and a group without low back pain (n=30)—participated in this study. Methods Electromyographic (EMG) and force data were obtained during a muscle fatigue test. The same test was repeated to monitor recovery. Linear regression analysis was used to obtain fatigue indexes. Results Subjects with pain produced significantly lower force values than those without pain. The use of fatigue indexes and force values permitted accurate classification in 89.5% of cases. Discussion and Conclusion The results confirm that subjects with pain show early myoelectrical manifestations of muscle fatigue and that EMG can be a useful tool in the evaluation of low back pain.


Sign in / Sign up

Export Citation Format

Share Document