Electromyographic normalization of vastus lateralis and biceps femoris co-contraction during gait of elderly females

• Main Authors: Katy Andrade Monteiro Zacaron (Author), João Marcos Domingues Dias (Author), Mariana Asmar Alencar (Author), Luane Landim de Almeida (Author), Carlos Alberto Mourão-Júnior (Author), Rosângela Correa Dias (Author)
• Format: Book
• Published: Editora Champagnat.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1980-5918; 10.1590/1980-5918.029.004.ao15
• Keywords: Contração Muscular; Contração Isométrica; Reprodutibilidade dos Testes; Dinamômetro de Força Muscular; Eletromiografia; Therapeutics. Pharmacology; RM1-950; Sports medicine; RC1200-1245
• Source: Fisioterapia em Movimento, Vol 29, Iss 4, Pp 787-794

Abstract Introduction: Analyze muscle co-contraction using electromyographic signals, which are normalized to compare individuals, muscles and studies. Maximum voluntary isometric contraction (MVIC) and peak electrical activity (PEA) during movement are the most widely used forms of normalization. Objective: Compare inter-subject variability and investigate the association between the co-contraction indices of the vastus lateralis and biceps femoris during gait, normalized by MVIC and PEA. Methods: Thirty elderly women, aged 70.33 ± 3.69 years took part. Electrical muscle activity during MVIC and gait was recorded using a Biopac MP100 electromyograph. MVIC was performed in a Biodex isokinetic dynamometer. For normalization, the signals were divided by the Root Mean Square values of MVIC and PEA of gait. Results: The coefficient of variation of non-normalized data was 69.3%, and those normalized by PEA and MVIC were 30.4% and 48.9% respectively. Linear regression analysis resulted in a prediction model: PEA = 0.04 + 0.16 x MVIC. The goodness of fit of the regression model was statistically significant (p=0.02). The confidence interval (95% CI) for the intercept was between 0.02 and 0.29 and for MVIC between 0.03 and 0.06. Conclusions: The data normalized by PEA showed less variation than those normalized by MVIC. A 100% variation in data normalized by MVIC resulted in a 16% variation in data normalized by PEA, while variation in normalization by MVIC accounts for 17% of the variation in normalization by PEA and vice versa.