Sign language recognition is the problem of automatically identifying and interpreting hand gestures and movements associated with sign language using wireless sensing signals, particularly WiFi-based CSI measurements captured as users perform signs in the vicinity of antenna arrays. This task matters for the field because it demonstrates the potential of contactless, device-free sensing to enable natural human-computer interaction and assistive communication technologies without requiring wearable sensors or cameras, thereby preserving user privacy and reducing hardware dependency. Key variants include static gesture classification, where individual hand shapes are recognized in isolation, and continuous or dynamic sign recognition, where temporally extended sequences of gestures must be segmented and decoded to form meaningful words or phrases.
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