Simulation of Tilt Sensor for Hand Motion Capture, Expression, and Haptic Feedback

The human hand is a central medium for interacting with the external world, capable of sensitively perceiving surface roughness and softness/hardness properties while efficiently expressing complex gestures and sign language. However, existing sensing technologies struggle to achieve high‐precision simulation of hand motion, gesture expression, and tactile feedback within a single integrated system. To address this challenge, this study proposes a tilt sensor based on the dynamic wetting mechanism of liquid metal (LM). By injecting LM into a bio‐inspired anisotropic microchannel, the sensor achieves a highly linear mapping between resistance signals and tilt angles through gravity‐induced Laplace pressure changes. It exhibits high resolution (2°), rapid response (1.78 s), strong durability (>15,000 s), long‐term stability (40 days), and a broad detection range (−90°–90°). The study successfully integrates the sensor into a hand motion capture system, enabling natural gesture recognition and sign language expression. Additionally, in combination with a developed surface scanning platform, tactile‐like measurement of object roughness and elastic modulus distribution is realized. This work provides a novel integrated sensing solution for wearable interaction, robotic tactile sensing, and intelligent human‐machine interfaces.