Sobre interpretações de eletromiografia de superfície: descobrindo padrões elétricos em mapas topográficos, decomposição de unidades motoras e respostas à fadiga aguda e acumulada

Abstract

The study of individual or pooled motor units’ activity by means of surface electromyography (sEMG) opens a window of opportunities to study human movement. However, sEMG requires adequate signal processing, and there are physiological and non-physiological factors that can bias the measurement and interpretation of sEMG signals. Examples include technical and methodological choices for signal processing and presentation, as well as physiological factors such as acute and cumulative muscle fatigue and orthopedic conditions such as persistent weakness after an Achilles tendon rupture. Therefore, the proper use of sEMG information relies not only on how the signal is acquired and processed but also on the physiological condition of the individuals. In this research, we aimed to determine sEMG signal segmentation, posttraumatic muscle weakness, and fatigue conditions influencing myoelectrical manifestations, sEMG maps, and motor unit decomposition obtained from sEMG measurements. The experiments conducted and reported here hypothesized that 1) methodological biases are introduced during typical signal processing procedures when analyzing electrical manifestations to estimate muscle fatigue and muscle activation maps, 2) sEMG maps and motor unit decomposition patterns can be appropriately used to identify acute and chronic muscle adaptation in conditions of inhibition similar to cumulative fatigue, and 3) cumulative muscle fatigue impairs neurophysiological characteristics (firing rate and motor unit recruitment) expressed in sEMG signals. Our main findings were that 1) signal processing methods to estimate fatigue and activation maps introduce biased electrical manifestations, 2) sEMG maps and motor unit decomposition are sensible to identify patterns in acute and chronic adaptations, and 3) increased firing rate and new motor unit recruitment are the most relevant changes in sEMG signals in response to cumulative fatigue. Furthermore, the results highlight the relevance of visualization techniques in the analysis of regional muscle activation (sEMG maps) and regional distribution and suggest the increase in firing rate as the most relevant marker of cumulative fatigue. We expect that our results can have an important impact on how to approach signal processing and define procedures to study different physiological conditions throughout the use of sEMG.