Gesture recognition has demonstrated considerable potential for human-machine interaction, particularly in robotic control, virtual reality, and rehabilitation training. However, existing gesture-recognition methods often suffer from high cost, limited environmental adaptability, and insufficient precision, making high-performance sensing gloves difficult to realize. Here, we present a flexible resistive sensing glove fabricated by atomized spraying of liquid metal onto commercial rubber gloves, eliminating the need for substrate pre-treatment while forming uniform conductive circuits. A helical joint design enhances pressure responsiveness and amplifies resistance variation. The glove exhibits tensile strain above 230%, hysteresis below 0.04, a gauge factor of 3.05, rapid recovery within 0.24 s, and stable operation over 1200 cycles. Integrated with a wireless module, the system enables real-time gesture recognition and control of robotic hands and humanoid robot movements, demonstrating promise for shared human-machine interaction. This cost-effective and scalable strategy addresses key limitations of adaptive wearable interfaces and advances next-generation interactive systems.
No takes yet. Share an insight, caveat, or question.
Dong et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: