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The primary goal of hand gesture recognition with wearables is to facilitate the realization of gestural user interfaces in mobile and ubiquitous environments. A key challenge in wearable-based hand gesture recognition is the fact that a hand gesture can be performed in several ways, with each consisting of its own configuration of motions and their spatio-temporal dependencies. However, the existing methods generally focus on the characteristics of a single point on hand, but ignores the diversity of motion information over hand skeleton, and as a result, they suffer from two key challenges to characterize hand gestures over multiple wearable sensors: motion representation and motion modeling. This leads us to define a spatio-temporal framework, named STGauntlet, that explicitly characterizes the hand motion context of spatio-temporal relations among multiple bones and detects hand gestures in real-time. In particular, our framework incorporates Lie group-based representation to captu ....