Ecological monitoring of gait stability is a key factor in preventing falls in older adults and patients with neurological disorders. The quantification of base of support (BoS) parameters (i.e., stride width and step length) has been observed to provide crucial insights into dynamic stability. Traditionally, BoS parameters are assessed in laboratory settings using optical motion capture systems or instrumented mats, which limit ecological validity and accessibility. In recent years, a few studies proposed wearable-based methods using magneto-inertial measurement units (MIMUs) and, in addition, auxiliary sensors to estimate foot placement and inter-foot distance using machine learning or sensor fusion approaches. However, these methods have been validated exclusively during straight walking, whereas instability often emerges in more complex contexts such as turning or daily-life activities.