Stride Length

Stride length, a key gait parameter, is being extensively studied to understand and improve human locomotion, particularly in individuals with neurological impairments. Current research focuses on accurate stride length estimation using wearable sensors and machine learning techniques, including convolutional neural networks and graph optimization algorithms, to overcome challenges like sensor drift and individual variability. These advancements are improving the accuracy of gait analysis for applications ranging from personalized healthcare monitoring and rehabilitation to more robust pedestrian navigation systems. The development of large, well-labeled datasets is crucial for further refining these methods and expanding their applicability.