Evaluation of creating symmetry in the weight-bearing of the lower limbs of patients with chronic stroke.

Stroke is a complex neurological dysfunction resulting from vascular damage to the brain that leads to various sensorimotor impairments contributing to increased postural instability. Enhanced postural fluctuations in these patients are strongly associated with falling and the subsequent deterioration of daily functional activities. Moreover, asymmetrical weight bearing-with a greater tendency to rely on the non-affected lower limb-further aggravates balance and stability deficits. In this model, three types of signals were considered to achieve integrated simulation: (1) neurological signals representing motor commands transmitted from the brain to lower-limb muscles, (2) mechanical signals corresponding to joint forces, torques, and motion dynamics, and (3) electromyography (EMG) signals used to evaluate muscular activation and timing coordination between limbs. Biomechanical modeling of skeletal components and joints was performed in two dimensions to replicate sagittal-plane dynamics during gait and support analysis. Given the large number of interacting parameters, the resulting dynamic equations became extensive and computationally demanding; therefore, the SimMechanics standard toolbox in MATLAB Simulink was utilized to facilitate the dynamic simulation of members, joints, and ground-contact interactions. This study targeted patients with mobility impairment, defined as individuals presenting with mild hemiparesis following chronic stroke, who retain partial voluntary motor control but exhibit evident asymmetry in weight-bearing and gait dynamics. The aim was to design and implement a path control algorithm capable of enhancing symmetry and smoothness in movement patterns. The preliminary implementation of this control algorithm achieved modest improvements in step regulation. However, after extensive experimental testing, an optimized velocity field control method was proposed.