Deep Physiological–Behavioral Representation Learning for Dynamic Hand Gesture Authentication

This research describes PB-Net v2, an improved AI system that authenticates users by analyzing their hand gestures, which contain unique physiological (body structure) and behavioral (movement patterns) characteristics. The system uses neural networks (computer models inspired by how brains work) to extract and combine these characteristics more effectively than previous versions, achieving better accuracy in recognizing legitimate users and resisting fake gesture attacks.