Electromyographic Signatures of Postural Control: Insights into Gender Differences

Postural control (PC) ensures balance and body orientation through the integration of multisensory inputs and adaptive neuromuscular responses. Electromyography (EMG) is a key tool for investigating these mechanisms, providing insights into muscle activation patterns and strategies adopted to maintain stability. In this study, EMG signals were recorded from six calf muscles during a postural control task consisting of four experimental phases in a virtual reality environment: three static conditions (BASE, PRE, and POST) and one dynamic phase (MOV), characterised by mechanically induced perturbations generated by platform movement. Features extracted from EMG signals were analyzed to identify significant differences between gender and to determine which muscles, parameters and phase contributed most to group discrimination. Statistical and machine learning analyses consistently indicated that muscle activity patterns during postural tasks can discriminate between males and females, particularly under dynamic perturbation conditions. The soleus and tibialis anterior muscles contributed most consistently to gender discrimination, confirming their crucial role in maintaining balance and compensating for perturbations. The results aim to enhance understanding of the neuromuscular strategies underlying PC and to provide a quantitative basis for the development of intelligent and sustainable diagnostic tools for neuromuscular assessment and predictive health.