Spatio-temporal gait parameters estimation during lateral walking

Gait analysis plays a critical role in understanding human locomotion, with most research focusing on forward walking. However, lateral walking, characterized by sideways movement, presents unique biomechanical and spatio-temporal challenges that remain underexplored. This study aims to estimate gait spatio-temporal parameters during lateral walking, with a particular focus on Anticipatory Postural Adjustments (APAs), which are crucial for maintaining balance and stability before movement initiation. Wearable sensors and stereophotogrammetric systems were employed to analyze stride length, step velocity, and step time, comparing their accuracy in characterizing lateral walking mechanics. The findings reveal that lateral walking introduces significant asymmetry and variability in gait parameters, requiring distinct motor control strategies compared to forward walking. Additionally, APAs in lateral walking exhibit unique characteristics that influence gait stability and efficiency. The results contribute to advancing gait analysis methodologies, particularly for clinical populations such as stroke survivors and individuals with neurological impairments. By leveraging wearable technologies, this research provides a foundation for real-time monitoring and rehabilitation interventions aimed at improving balance and coordination in lateral movement.