Ankle muscle strength influence on muscle activation during dynamic and static ankle training modalities

Abstract

Muscle weakness is considered a risk factor for ankle injury. Balance training and barefoot running have been used in an attempt to strengthen the muscles crossing the ankle. It is expected that training tasks that successfully strengthen the ankle would elicit increased muscular activity. However, it is unknown how an individual's ankle strength will influence the muscle activity used during a given task. Twenty-six participants performed dynamic (shod, barefoot running) and static tasks (squat on ground, squat on ®Bosu Ball) believed to strengthen the muscles surrounding the ankle. Electromyographic signals of the tibialis anterior, peroneus longus, gastrocnemius lateralis (GL) and gastrocnemius medialis (GM) were recorded and analysed using a non-linearly scaled wavelet analysis. Participants were divided into a strong group and a weak group according to their isometric plantar-flexion torque. The weak group required more relative GL and GM muscle activity during each training task compared to the strong group. No difference was observed between shod and barefoot running. There was a significant effect of training task on muscle activation level for the weak group. Differences in ankle strength had a significant impact on muscle activation.

Motor Unit Action Potential Clustering—Theoretical Consideration for Muscle Activation during a Motor Task

“…We extend these model findings and indicate that MU clustering with window sizes up to 25 ms also creates increases in EMG power. Further, during dynamic tasks such as running, it is frequently observed that the EMG signal from muscles such as the gastrocnemius are higher during running vs. isometric maximal voluntary contractions (MVCs; Lucas-Cuevas et al, 2016 ). Given that during running the muscle is constrained to fire in a short time period, the motor units are likely clustered.…”

Initiating running barefoot: Effects on muscle activation and impact accelerations in habitually rearfoot shod runners

“…The vertical axis of the accelerometer was aligned to be parallel to the long axis of the tibia. The acceleration signal was filtered with Matlab (Butterworth, second‐order, low‐pass, cut‐off frequency = 50 Hz) and the following acceleration parameters were calculated from the vertical axis of the acceleration signal (Laughton, Davis, & Hamill, 2003; Lucas‐Cuevas, Priego‐Quesada et al, 2015): tibial and head peak acceleration (maximum value of the acceleration signal), acceleration magnitude (difference between the positive and negative peak), acceleration rate (slope in the acceleration signal from ground contact to peak acceleration, calculated as the 30–70% of the acceleration peak amplitude [Duquette & Andrews, 2010]), and impact attenuation (decrease of the peak acceleration between the head and the tibia as a percentage of the tibial peak acceleration). Finally, also from the acceleration signal, stride frequency was calculated as the time between consecutive leg impacts, whereas stride length was obtain by dividing running speed by stride rate.…”

Effects of Foot-Core Training on Foot-Ankle Kinematics and Running Kinetics in Runners: Secondary Outcomes From a Randomized Controlled Trial

“…The strengths of our study are the rigorous method for the RCT, its high completion and small dropout rates at follow-up, the adoption of robust statistical models (GLMM and 1D-SPM) that consider the complex non-linear iterations of foot-joint biomechanics, and its large sample size compared with other studies in the same field ( Jung et al, 2011b ; Goldmann et al, 2013 ; Baltich et al, 2015 ; Campitelli et al, 2016 ; Lucas-Cuevas et al, 2016 ; Mølgaard et al, 2018 ).…”

“…The application of this concept to the foot core it is logical as it works just like the trunk core considering that the subsystems in the foot also provide a stable base on which the primary movers of the foot-ankle complex, those with larger cross-sectional areas and moment arms, can act to cause gross motion, and the intrinsic muscles work as the local stabilizers, as they have small cross-sectional areas and small moment arms ( McKeon and Fourchet, 2015a ; McKeon et al, 2015b ). According to the “bottom-up” theoretical assumptions ( Tiberio, 1987 ; Feltner et al, 1994 ; Hollman et al, 2006 ; Lucas-Cuevas et al, 2016 ; Nigg et al, 2017 ), this approach may potentially change the mechanical or biomechanical response of more proximal joints (knee, hip). The foot is a biomechanically complex structure made of 26 bones, four layers of plantar intrinsic muscles, and several joints, providing the foot with multiple degrees of freedom.…”